Palaeoecology of Oligo-Miocene Local Faunas from Riversleigh

Troy J. M. Myers 2002

i

Table of Contents

Chapter 1 Introduction...... 1

Chapter 2 Marsupial body mass prediction ...... 8

Chapter 3 A review of cenogram methodology and body-size distribution moment statistics in the determination of environmental parameters...... 38

Chapter 4 A discriminant function analysis of recent and fossil Australian faunas 69

Chapter 5 Classification and ordination analysis of selected Riversleigh Local Faunas ...... 88

Chapter 6 The Nambaroo-Balbaroo palaeocommunity...... 110

Chapter 7 The Litokoala – Muribacinus palaeocommunity ...... 129

Chapter 8 The Last Minute-Ringtail palaeocommunity ...... 146

Chapter 9 The independent Local Faunas ...... 158 The Hiatus Local Fauna ...... 159 The White Hunter Local Fauna...... 162 The Cleft-Of-Ages Local Fauna...... 182 The Keith’s Chocky Block Local Fauna...... 187 The Encore Local Fauna, a late Miocene assemblage from Riversleigh, northwestern Queensland...... 190

Chapter 10 Conclusion ...... 204

Chapter 11 References...... 219

Appendix One: Cluster Analyses Appendix Two: Taxonomic relative abundance and presence/absence data for Riversleigh Local Faunas Appendix Three: Table of higher level taxonomy and ecodiversity of fossil species ii

Table of Figures

Figure 1: Location of Riversliegh world heritage area...... 6

Figure 2: Riversleigh site locations ...... 7

Figure 3: Cenogramic curve (from Valverde, 1964)...... 68

Figure 4: Canonical scores plot for DFA utilising 67 extant Australian faunas (derived from Table 10) and all variables...... 74

Figure 5: Conical scores plot for DFA with 114 extant Australian faunas (derived from Table 10), excluding small-mammal slope and gradient difference variables...... 78

Figure 6: Principle component analysis on species ( presence/absence) (acronyms refer to sites/local faunas as given on p. vi)...... 103

Figure 7: Detrended correspondence analysis on species abundance (acronyms refer to sites/local faunas as given on p. vi)...... 104

Figure 8: Principle component analysis on genera (presence/ absence) (acronyms refer to sites/local faunas as given on p. vi)...... 105

Figure 9: Detrended correspondence analysis on genera (abundance) (acronyms refer to sites/local faunas as given on p. vi)...... 106

Figure 10: Principle component analysis on family (presence/ absence) (acronyms refer to sites/local faunas as given on p. vi)...... 107

Figure 11: Principle component analysis on super family ( presence/absence) (acronyms refer to sites/local faunas as given on p.vi)...... 108

Figure 12: Detrended correspondence analysis on super family (abundance) (acronyms refer to sites/local faunas as given on p. vi)...... 109

Figure 13: Superfamilial NISP ...... 156

Figure 14: Generic NISP ...... 156

Figure 15: Specific NISP ...... 157

Figure 16: Element breakage (%) at White Hunter (entire, partial & fragmentary)...... 179

Figure 17: Voorhies Group analysis of White Hunter skeletal elements (%) ...... 180

Figure 18: Voorhies group comparison of total WH skeletal elements, WH macropodoids and an ‘average’ macropodoid (%) ...... 180 iii

Figure 19: Abrasion stages of White Hunter skeletal elements (%) ...... 181

Figure 20: Element weathering stages in White Hunter LF (%) ...... 181

Figure 21. Taxonomic representation by Order of marsupials in Encore Local Fauna compared to Neville’s Garden Local Fauna (% species and % genera)...... 202

Figure 22: Riversleigh local faunas and palaeocommunities analysed in this study, with estimated ages, inferred extant vegetation structure analogues, climatic phases and characteristic ecodiversity...... 218

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Table of Tables

Table 1: Species used in analysis...... 29

Table 2. Ranked body mass equations for the ‘all species’ data-set...... 30

Table 3: Ranked body mass equations for the ‘All species excluding dasyuromorphians’ data- set...... 31

Table 4: Ranked body mass equations for dasyuromorphians ...... 32

Table 5: Ranked body mass equations for diprotodontians ...... 33

Table 6: Multiple variable regressions...... 34

Table 7: Body mass predictions for extinct marsupial taxa ...... 35

Table 8: Comparison of body mass predictions and published body masses for extant species...... 37

Table 9: Variables used in analysis ...... 55

Table 10: Extant fauna data utilised in analysis...... 57

Table 11: Associated variables (excluding 'carnivores')...... 61

Table 12: Associated variables (including carnivores)...... 64

Table 13:Classification matrix (cases in row categories classified into columns) ...... 73

Table 14: Jackknifed classification matrix ...... 73

Table 15: Classification matrix (cases in row categories classified into columns)...... 77

Table 16: Jackknifed classification matrix ...... 77

Table 17: Group means for variables (DFA with 114 faunas) ...... 83

Table 18: Defining and characteristic species of the Nambaroo-Balbaroo palaeocommunity ...... 113

Table 19: Non-volant mammalian species present in the Nambaroo-Balbaroo palaeocommunity constituent local faunas...... 114

Table 20: Characteristic genera of the Nambaroo-Balbaroo palaeocommunity...... 119

Table 21: Chiropteran and non-mammalian species ...... 120

Table 22: Defining species of the Litokoala-Muribacinus palaeocommunity...... 131

Table 23: Characteristic species of the Litokoala-Muribacinus palaeocommunity ...... 132

Table 24: Defining and characteristic genera of the Litokoala-Muribacinus palaeocommunity ...... 134 v

Table 25: Species variably present in GAG and HH LF's ...... 135

Table 26: Characteristic families for the Litokoala-Muribacinus palaeocommunity...... 137

Table 27: ‘Super-familial’ NISP comparison for palaeocommunities and LF’s...... 138

Table 28: Non-mammalian and chiropteran species of the GAG and HH LF’s...... 143

Table 29: Characteristic species of LM-RING palaeocommunity ...... 147

Table 30: Characteristic genera of the LM-RING palaeocommunity ...... 148

Table 31: Variably present species of the LM & RING palaeocommunity ...... 151

Table 32: Non-mammalian and chiropteran species of the LM and RING LF’s ...... 152

Table 33: Faunal list for Hiatus Local Fauna...... 159

Table 34: Marsupial faunal list for White Hunter Local Fauna...... 169

Table 35: Faunal list for Cleft-Of-Ages Local Fauna...... 184

Table 36: Species present in the KCB LF ...... 188

Table 37: The Encore Local Fauna...... 192 vi

Table of Plates

Plate 1: (Top) Camel Sputum looking east; (Bottom) Camel Sputum looking south

Plate 2: (Top) Camel Sputum looking north; (Bottom) Camel Sputum looking north- west

Plate 3: Mike’s Menagerie looking towards Camel Sputum

Plate 4: (Top) Encore looking south; (Bottom) Encore looking west

Plate 5: (Top) Hiatus; (Bottom) Hiatus looking East

Plate 6: (Top) Keith’s Chocky Block looking South; (Bottom) KCB looking NE

Plate 7: (Top) Neville’s Garden; (Bottom) Neville’s Garden looking south-east

Plate 8:(Top) Upper Site looking north-west; Upper Site looking east

Plate 9: (Top) Wayne’s Wok looking south-west; (Bottom) Wayne’s Wok

Plate 10: (Top) White Hunter looking north-east; (Bottom) White Hunter looking east

Plate 11: (Top) White Hunter Femora; (Bottom)White Hunter Vertebrae

Plate12: (Top) White Hunter Pelvic Elements; (Bottom) White Hunter Metapodials vii

Frequently used abbreviations

CA - correspondence analysis COA - Cleft-of-Ages CS - Camel Sputum DCA - detrended correspondence analysis DFA - discriminant function analysis ENC - Encore GAG - Gag HH - Henk’s Hollow HI - Hiatus KCB - Keith’s Chocky Block LF - local fauna LM - Last Minute MM - Mike’s Menagerie MNI - minimum number of individuals NISP - number of identified specimens NG - Neville’s Garden PCA - principal components analysis PCO - principal coordinates analysis RING - Ringtail UP - Upper UPGMA unweighted pair group method using arithmetic averages WH - White Hunter WW - Wayne’s Wok viii

Acknowledgements

Many people have assisted me in the production of this thesis over the years. In particular, I would like to thank Professor Michael Archer, Dr Suzanne Hand, and all the students of the University of New South Wales Vertebrate Palaeontology Laboratory, including: Ben “Q” Kear, Mina “the mooch” Bassarova, Kirsten “with the hair” Crosby, Karen “Kaz” Black, Jenni “Crazy” Brammall, Adam Morell, Kelly Carberry, Erwin “Erwinator” Budde, Bernie Cooke, Anna Gillespie, Anne Musser, Steve Wroe, Susan “Susaninator” Henderson, Matthew Crowther, Rick “Ricky-boy” Arena, Jeanette Muirhead, Henk Godthelp and Stephan Williams. Special thanks must also go to my family for all their support and patience over the years, and to my wife, Mary, who helped me more than she can know, this is as much her thesis as it is mine. Thanks also to Mr. P. Unch for all his late night commentary and guidance.

For all those who waited - thank you.

Mina Bassarova supplied many of the photos in the thesis. Matthew Crowther supplied some body weights. Dr Sandy Ingleby assisted in finding and loaning specimens from the Australian Museum. Ben Kear assisted with identifying specimens in the taphonomy section. Rick Arena supplied Riversleigh site information and maps.

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Chapter 1 Introduction

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Introduction

Over 300 fossil localities spanning the late Oligocene to late Pleistocene have been identified from the Riversleigh World Heritage Fossil deposits in northwestern Queensland (M. Archer, pers. comm.) (Figure 1). Each site is characterised by a constituent fossil assemblage, lithology and taphonomic history. Traditionally, the biota of each site has been designated a local fauna, defined as the assemblage of animals collected from one locality (Tedford, 1970; Archer et al., 1991), with the hope that future investigations will allow for clumping of these local faunas into Faunas. Some of the better sampled sites have had preliminary species lists compiled, but apart from observations on the autecology of various species and a study of perameloid palaeoguilds (Muirhead, unpub.), little is known about the spatial and temporal synecology of Riversleigh’s fossil faunas. These fossil assemblages potentially provide a rare opportunity to study the synecology of a palaeocommunity (or palaeocommunities) changing over a significant period of geological time, through at least one cycle of climatic change and associated extinction events.

A sample of these local faunas, representing ‘snapshots’ in time over the temporal range of Riversleigh’s fossil deposits, are analysed. Included among these sites are: White Hunter; Wayne’s Wok; Neville’s Garden; Upper Site; Camel Sputum; Mike’s Menagerie; Gag; Henk’s Hollow; Ringtail; Last Minute; Cleft-Of- Ages; Keith’s Chocky Block; Hiatus and Encore (Figure 2). The 14 assemblages to be investigated span the temporal range of Riversleigh’s late Oligocene to late Miocene sites (‘Systems A, B and C’; sensu Archer et al., 1995). Selection of the local faunas to be investigated was influenced by the uniformity of lithology and degree of horizontal and vertical confinement of each site, as well as by the sampling effort already undertaken. An attempt was also made to include a suite of sites that covered the entire temporal range of the Riversleigh deposits.

Although taxonomic composition is an important feature of a fauna, it does not allow for changes in species assemblages to be tracked over considerable periods

______3 of time, except at higher taxonomic levels. The palaeoecological attributes of each local fauna are best characterised by taxon-free eco-diversity (Andrews et al., 1979) indicators such as trophic structure, locomotor diversity and perhaps most informatively, body-size distribution.

Chapter description

However, prior to undertaking palaeoecological analyses using body-size parameters it is necessary to first determine body-sizes for the taxa to be investigated. For placental taxa this is a straight-forward process with many methodologies existing for determining body-size from both cranio-dental and postcranial variables, for both extinct and extant taxa (e.g. Damuth & MacFadden, 1990; Anderson et al., 1985). Conversely, no adequate approach exists for the determination of body-size in marsupial taxa, other than broad-scale methods incorporating datasets such as ‘all mammals’. The latter are invariably less reliable than methods using more restricted taxonomic groupings. In Chapter Two a methodology for predicting marsupial body-size from cranio-dental variables is presented. The equations given are used to establish body-sizes for fossil species throughout the study.

Cenograms, rank-ordered size distributions for non-volant and non- carnivorous species (Legendre, 1986, 1989; Morgan et al., 1995), have been proposed as useful tools for determining palaeo- climatic and vegetational parameters of fossil faunas. Other researchers have recommended using moment statistics for analyses of body-size distributions (e.g. Alroy, 2000). The utility of both methodologies is examined in Chapter Three.

In Chapter Four a multivariate statistical technique, discriminant function analysis (DFA), is used on a dataset of body-size variables from extant Australian mammal faunas as well as a sample of Riversleigh’s Oligo-Miocene local faunas, in order to find possible vegetation structure analogues for the fossil faunas. Extant mammal faunas from outside of Australia were not used in the DFA because: 1) the focus was construction of a database of faunas from Australia, which has not been previously done; 2) published faunal lists from countries suggested as having

______4 possibly analogous vegetation types (e.g. New Caledonia and Papua New Guinea; Archer et al., 1998) were not easily accessible; 3) the latter were not published in sufficient numbers; 4) overseas datasets did not contain adequate habitat information; and/or 5) body-size or habitat preferences for overseas species were unknown.

Bennington & Bambach (1996) define a local palaeocommunity as “…the assemblage collectable from a single bed at one outcrop, assuming that sedimentological and taphonomic interpretation indicate that the fossil deposit is generally untransported”. The sample of local faunas examined herein are considered to be equivalent to local palaeocommunities, as initial investigations suggest that these sites are largely unstratified and lack strong evidence for transport.

To test assertions that some of Riversleigh’s local palaeocommunities (local faunas) can be amalgamated into palaeocommunities and palaeocommunity types (sensu Bennington & Bambach, 1996), various multivariate analyses are performed on taxonomic relative abundance and presence/absence data. The results of this preliminary palaeoecological analysis are given in Chapter Five. Resultant palaeocommunities and non-clustering independent local faunas are then further described in Chapters Six, Seven, Eight and Nine.

Species list compilation

For the extant faunas, used in the discriminant function analysis and in the analysis of body-size distribution methodologies (Chapters Three and Four), published species lists were employed, either directly or for further determination of habitat-specific lists. For fossil species lists, which formed the basis of the various palaeoecological analyses, lists were compiled by: 1) searching computer database records for all specimens and catalogue numbers relevant to a particular site; 2) checking computer records against the handwritten catalogue to include specimens missed by the computer database, to ensure that specimens with temporary and permanent catalogue numbers have not been counted twice and to allow for recent revisions of specimen descriptions and taxonomic assignments; 3) using literature reviews for the majority of higher level taxa to determine whether new species have been identified or revised and adjusting the specimen records accordingly; 4)

______5 discussion of taxonomic work being undertaken with all group specialists to determine if specimens have been identified but not yet published; and 5) sorting through of newly found specimens for any identifiable taxa.

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Figure 1: Location of Riversleigh world heritage area (from Megerian, 1992)

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Figure 2: Riversleigh site locations

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Chapter 2 Marsupial body mass prediction

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Marsupial body mass prediction *

Troy J. Myers

Vertebrate Palaeontology Laboratory, School of Biological Science,

University of New South Wales, NSW 2052, Australia.

Abstract Cranio-dental variables are correlated with body mass in marsupials, using a species data-set derived from extant australidelphian representatives, to predict body mass in fossil species. Thirty-eight extant australidelphian species including 10 dasyuromorphians, 22 diprotodontians, one notoryctomorphian and five peramelemorphians, were analysed. Where sexual dimorphism was prominent, genders were evaluated separately. Twenty nine cranio-dental variables were measured for each specimen and species averages calculated. Body masses were taken as recorded for each specimen or as published species averages. The cranio- dental measures for each morpho-species were then regressed against average body mass in four distinct data-sets: 1) the entire species sample; 2) only dasyuromorphian taxa; 3) only diprotodontians and 4) all species excluding dasyuromorphians. Each cranio-dental variable was then ranked according to various error statistics and correlation coefficients. Results suggest that eutherian predictors of body size, such as first lower molar area, commonly used to estimate marsupial body mass may not be reliable or accurate indicators. Significant differences in the usefulness of predictor variables between taxonomic data-sets were also observed. Total jaw length is the most reliable predictor for diprotodontians as well as all species combined, while lower molar row length appears to be more appropriate for dasyuromorphians.

* This paper was published in Australian Journal Of Zoology, 2001, 49, 99-118

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Multiple variable regressions variably offer more precision than those derived from individual parameters. Based upon these data, body mass estimations are provided for a number of extinct marsupial taxa.

Introduction The prediction of body size in fossil vertebrates serves a number of palaeobiological and palaeoecological purposes, such as the determination of behaviour or physiology of species or individuals (e.g. McNab 1990; Martin 1990; Roth 1990). In recent times body size predictions, specifically body mass, have been utilised in an attempt to elucidate palaeoecological characteristics such as community structure, home range, population density and biomass. Damuth and MacFadden (1990) suggest that body size ‘…may be the most useful single predictor of that species’ adaptations’. It is therefore not surprising that the literature concerning prediction of body size in fossil mammals is extensive. However, this work is biased heavily towards eutherian mammals. Janis (1990) correlated cranio-dental variables with body size in extant macropodoids but only for comparative purposes, with the focus concerning determination of body size in fossil ungulates. Other studies, such as Van Valkenburgh (1990), include marsupials in their data-sets, but sample sizes are usually too small to allow for separate analysis of marsupials. Legendre (1989) correlates first lower molar area with body mass in marsupials, as well as a number of other taxa, but only to confirm the usefulness of this dental variable for that purpose.

Furthermore, the majority of studies have dealt primarily with the correlation of cranio-dental elements and body size. Although predictions based on postcranial elements, especially limb variables such as cross-sectional area, are generally more reliable estimators of body size, it remains the case that most researchers do not have the luxury of access to sufficient numbers of postcranial elements. In addition, it has long been recognised that, due to the robustness of cranio-dental elements, they are proportionately over-represented in the fossil record. Given this taphonomic bias, the relative ease of identifying dental and skull elements and, in contrast, the present difficulties associated with recognition of species-specific postcranials, it is likely

______11 that cranio-dental elements will remain the tools of choice for researchers investigating body size in fossil groups.

The focus of this study is therefore the correlation of cranio-dental variables with body mass in marsupials, using a species data-set derived from extant australidelphian representatives to predict body mass in fossil species. A comparison has also been made between regressions previously determined for eutherian groups and the new marsupial versions.

Methods Thirty-eight extant australidelphian species, including 10 dasyuromorphians, 22 diprotodontians, one notoryctomorphian and five peramelemorphians, have been included in this analysis. These included species spanning the entire spectrum of body mass, ranging from a 10g Planigale to a 70kg Macropus. In addition, the wide range of species includes a number of trophic, locomotory and taxonomic groups. Males and females have been separated for species exhibiting sexual dimorphism, giving a total of 55 morpho-species (Table 1).

Twenty nine cranio-dental variables were measured directly using a WILD M5A Microscope, a further eight variables are composite area measurements combining maximum width and length (sensu Gould 1975). These ‘area’ measurements were determined by multiplication of average tooth width by average tooth length and do not as such represent actual molar areas.

Width and length dental measurements were taken as maximum crown distances, in occlusal view. Each tooth in a row was therefore reoriented before measuring, such that the maximum occlusal area was visible. Janis (1990) found that widths, in particular muzzle width, were poorly correlated with body mass in kangaroos and ungulates, so measurements of this dimension were not undertaken for skull variables. In addition to measurements on individual teeth, the following cranio-dental measurements were made:

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LMORL & UMORL - The ‘lower molar occlusal row length’ and ‘upper molar occlusal row length’ variables are measurements from the most anterior portion of the first molar crown to the most posterior portion of the fourth molar crown.

LMRL & UMRL - These variables are similar to LMORL & UMORL but measurements are taken from the respective alveoli instead of the molars, following Janis (1990).

TJL - The ‘total jaw length’ was measured from the most posterior part of the dentary, be that angular process or condyle, to the most anterior part of the first incisor. The first incisor is deemed to be a functional part of the lower jaw in most diprotodontians, particularly macropodoids (Janis 1990).

TSL - ‘Total skull length’ was taken from the anterior part of the muzzle, including incisors, to the most posterior part of the occipital region.

OCH - The ‘occipital height’ variable was measured from the basioccipital to the most dorsal part of the occipital.

PJL - ‘Posterior jaw length’ was determined by measuring from the posterior extremity of the fourth lower molar crown to the most posterior of the lower jaw, be that condyle or angular process.

PSL - Similarly, ‘posterior skull length’ measured from the posterior extremity of the fourth upper molar crown to the posterior edge of the occipital condyles.

Body mass measurements are means for species as published in various sources, or determined by averaging weights from museum records. Ideally mean weights should be calculated using individual weights recorded for every specimen measured, but these data are rarely available in sufficient numbers for museum specimens. Martin (1980) found no significant difference between using published means or tag data in regression analyses.

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Where possible species used were represented by 10 or more individuals of each sex from similar geographic locations so as to provide more accurate averages, although in many cases it was not possible to obtain this number of suitable specimens. Only ‘adults’ were used in the analysis, as determined by the eruption of the fourth molar. Specimens from older animals, or those exhibiting potentially significant tooth wear, were excluded. For dasyuromorphians the second premolar (the tooth anterior to the first molar) was counted as a third premolar for purposes of the analysis. Third premolar variables such as 3UPW, 3UPL, 3LPW and 3LPL are therefore measures of the ‘tooth anterior to the first molar’ for the ‘all species’ data- set.

Cranio-dental variables were correlated against mean body mass for species using least-squares regression methods. The data were analysed, using SigmaStat (1992), as four separate species data-sets; 1) all species; 2) all species excluding dasyuromorphians; 3) diprotodontian species and 4) dasyuromorphian species, as previous studies (e.g. Damuth 1990) have suggested that prediction estimates improve with regressions based on taxonomically restricted data-sets. The dasyuromorphians, in particular, as carnivore-insectivores with specialised skull modifications may not follow allometric equations derived for non-carnivorous taxa (Van Valkenburgh 1990).

For each regression, studentized residuals were calculated such that outliers, those data-points lying outside of the regression population’s 95% confidence limits, were removed from the data-set before the regression equation was computed.

As the correlation coefficient, and its derivatives, are: 1) affected by the range of data being analysed; 2) influenced by the slope of the regression and 3) poorly reflect the confidence with which predictions can be made (Smith 1984), it has been necessary to include other determinators of a regression’s ability to predict and ‘goodness-of -fit’. The indicators used in this analysis, besides the correlation coefficient, are the percent standard error of the estimate (SEE%) and percent prediction error (PE%). Determination of PE% and SEE% follow Smith (1981,1984).

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All regressions have been ranked, in order of decreasing accuracy, according to these determinators and where necessary the adjusted determination coefficient (adj. R2).

Due to logarithmic transformation bias (Smith 1993) predicted body mass, presented here as detransformed values, are almost certainly underestimates. To correct for this bias the smearing estimate (SE) (Duan 1983; Smith 1993) has been applied to all predictor variables (Table 2). Application of the SE to a predicted body mass estimate will largely correct for transformation bias.

Accuracy and precision of regressions have been further tested by predicting body mass for a number of extant taxa, not used in the original data-sets, as well as for a variety of extinct species (Tables 7 & 8).

Specimens used in this analysis are held in the Australian Museum, Queensland Museum (QMF, QMJ and QMJM) and the University of New South Wales zoology and palaeontology collections (UNSW and AR respectively).

Results

Single variable regressions All species - For the data-set including all species the ‘best predictor’ variable is TJL, followed by TSL and UMORL (Table 2). The best dental predictor is UMORL followed closely by LMORL. In general, composite ‘area’ variables are slightly better predictors than those based solely on length or width. Premolar variables are poorly correlated with body mass, having high percent standard errors in excess of 88% and as high as 124%, as well as similarly high PE% values. Only the 4th upper molar width (4UMW) exhibits accuracy statistics below those for premolar variables. Additionally, lower molar width regressions are better predictors than those derived from upper molar widths. For regressions using the entire sample the standard error of the estimate (SEE%) has a large range, from 39 to 160 percent.

All non-dasyuromorphian species - The most accurate predictor variable for the data-set excluding dasyuromorphians is UMRL, followed by UMORL and TJL. As for the ‘all species’ data-set, premolar variables are among the least accurate

______15 variables to use for predicting body mass, as highlighted by the relatively low accuracy statistics for these variables (Table 3). First lower and first upper molar variables are also poor predictors. In general the SEE% and PE% are lower for regressions in this data-set than they are for those including all species. Exclusion of dasyuromorphians from the data-set results in a SEE% range for the regressions from 34 to 110 percent.

The highest ranked individual predictor variable for the ‘all species’ sample is TJL, interestingly UMRL in the non-dasyuromorphian data-set has lower error statistics, and is therefore a better predictor, than the former. Comparing just UMRL, ranked first in the non-dasyuromorphian data-set and fourth for ‘all species’, SEE% is 34 in the former and 52 in the latter, despite both data-sets exhibiting similar correlation coefficients for this parameter.

In contrast to the ‘all species’ regressions: 1) there is no evidence for upper molar widths being less accurate predictors than lower molar widths; 2) TSL is ranked far lower as a predictor variable and 3) 4UMW is ranked far higher.

Dasyuromorphian species - For dasyuromorphian species alone, LMRL, followed by UMRL, are the best predictor variables, being separated in the accuracy rankings by only one PE%. The second upper molar area (2UMA) is the best individual dental predictor. Lower molar row length (LMRL) is the best correlated non-dental variable, with a SEE% of 18. The dasyuromorphian regressions exhibit the lowest range of SEE% values, from 18 to 74 percent (Table 4).

Diprotodontians only- TJL is again the best overall predictor of body mass. The most accurate dental predictor appears to be UMORL. Surprisingly, 4UMW, a lowly ranked variable in other data-sets and the worst predictor variable for ‘all species’, is a more accurate predictor of body mass for diprotodontian species.

For diprotodontians first molar variables are ranked among the least accurate of body mass predictors, with errors far exceeding those exhibited by their dasyuromorphian counterparts (Table 5). Only third upper and lower premolar length and third lower premolar width (3UPL, 3LPL and 3LPW) rank lower than the first

______16 molar variables. In contrast, third upper premolar width (3UPW) is the third most accurate predictor variable for diprotodontians, despite being a particularly poor predictor in other data-sets. The SEE% range for diprotodontians is from 29 to 165 percent.

The first lower molar crown area has been extensively cited as one of the most accurate dental estimators of body mass in mammals. However, 1LMA ranked as one of the least accurate estimators in the diprotodontian, dasyuromorphian and non-dasyuromorphian data-sets. In the ‘all species’ data-set this variable was ranked higher, albeit only as the 16th most accurate predictor. Indeed, composite area measurements of other lower molars consistently ranked far higher than 1LMA (Tables 2,3,4 and 5).

Multiple variable regressions In addition to correlating body mass against individual variables, ‘best subsets’ analyses were performed on each data set such that the ‘best’ pair of predictor variables could be determined. Using multiple variables does not necessarily lessen the percent standard error of the estimate or the prediction error.

All species - For the data-set including all species the best overall subset of cranio-dental variables is a combination of second upper molar length (2UML) and UMRL (Table 6). The relevant error statistics are slightly lower for the multiple linear regression than they are for the highest ranked individual estimator, in this case TJL. The most reliable combination of individual teeth variables is first lower molar width and fourth lower molar length (1LMW & 4LML). However, the PE% and SEE% figures for this regression are far higher than those for TJL alone, potentially making the former redundant. For upper molars only, the best pair of variables are first upper molar area (1UMA) and fourth upper molar length (4UML). Using cranial variables only, the two best variables are OCH and TSL. The latter has a lower SEE% and PE% than the multiple variable regressions based on individual teeth (Table 6).

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All non-dasyuromorphian species - The best pair of overall variables is fourth lower molar width (4LMW) and TSL. This combination exhibits marginally better error statistics than the highest ranked individual variable (UMRL). First upper molar width (1UMW) and fourth upper molar area (4UMA) are the most reliable combination of single dental variables. For lower dentition only the best subset is a combination of third lower molar width and fourth lower molar area (3LMW & 4LMA). Using cranial data the best variable pair is OCH and TJL. The last two multi-variable regressions do not exhibit error values smaller than those for the best individual variable regression (UMRL).

Dasyuromorphians only - The best pair of predictor variables is 2UML and LMRL. For lower dental and cranial variables the best combinations are: second lower molar area and third lower molar length (2LMA & 3LML) and PSL & OCH respectively. A ‘best’ subset of upper dental variables could not be determined, as the second variable was consistently redundant. None of the bivariate regressions proved to have lower predictive error margins than the best individual predictor, LMRL (Tables 4 and 6).

Diprotodontians only – The most reliable pair of cranial, and overall, variables is PSL and TJL. The best pair of dental predictors for upper molars is the 1UMW and 4UMA, while the best pair for lower molars is 3LMW and 4LML. The multiple variable regressions are better predictors than the majority of individual variable regressions, although none approach the predictive power of the best individual variable regression (TJL).

The Smearing Estimate (SE) For variables derived from the ‘all species’ data-set the smearing estimate correction factor ranges from 5.2 to 49.9 percent; for the data-set excluding dasyuromorphians from 3.9 to 45.6 percent; 1.2 to 16.3 percent for ‘dasyuromorphians’ and 1.3 to 64.5 percent for the ‘diprotodontian’ data-set (Tables 2,3,4 and 5). Prediction equations derived from the dasyuromorphian data-set exhibit the lowest range and absolute figures for SE suggesting that the geometric mean is

______18 more closely approximating the arithmetic mean for these variables, relative to the other data-sets analysed.

For the multiple variable regressions presented the smearing estimate correction factor ranged as follows: 1) from 2.3 to 3.9% for diprotodontians; 2) from 1.1 to 3.5% for dasyuromorphians; 3) 5.6 to 25.4% for all species excepting dasyuromorphians; and 4) 1.2 to 10.1% for the whole sample (Table 6).

Body mass estimations Body mass predictions were made for seven extinct taxa, based on the ‘best’ and second ‘best’ predictor variables for the taxon concerned. The predictor variables used were not always the first and second most highly ranked for the data-set employed, due to the limitations associated with the completeness of specimens. These estimates vary between one and 18 percent of the most reliable. Predictions made for these taxa using first lower molar area (1LMA), differ significantly from those derived from more reliable variables.

In addition, body mass predictions are given for 10 randomly selected extant Australidelphian taxa, derived from the most reliable variables. These exhibit PE% values ranging from 4 to 41 percent, with a mean of 27.4 percent (Table 8).

Discussion Fortelius (1990) suggested that within Mammalia ‘…it is always possible to get an approximate idea of body size … In the case of morphologically similar, closely related species, quite precise relative sizes can also be determined, no matter how imprecise the estimates of absolute size’. One would therefore expect that regression equations derived from restricted taxonomic subsets would result in more precise body mass predictions than those employing paraphyletic or polyphyletic groupings. In the present study this assertion holds true for the dasyuromorphian subset, which consistently exhibits the lowest error statistics. Only nine variables, eight in the dasyuromorphian data-set and one in the diprotodontian, have a SEE% equal to or less than 30% and none represent individual tooth parameters. This is

______19 consistent with the findings of Damuth & MacFadden (1990) that standard errors less than 30% are rare in dental regressions.

However, this hypothesis is less robust when applied to the monophyletic ‘diprotodontian’ data-set which, although possessing minimum error statistics below those for the ‘all species’ and ‘all species excluding dasyuromorphians’ data, has a larger error range for SEE% and PE% than any other data-set. This suggests that the predictive power of the regressions derived from data-sets incorporating diprotodontian, peramelemorphian and notoryctomorphian species, with or without dasyuromorphians, is greater than that for the diprotodontians alone. Likewise, the range of adjusted R2 coefficients is substantially smaller for the ‘all species’ and ‘all species excluding dasyuromorphian’ data-sets relative to ‘diprotodontians’ only, implying a stronger relationship between body size and cranio-dental variable in the former.

Admittedly, it is difficult to understand why predictive power should be improved by inclusion of unrelated and morphologically dissimilar species. Damuth (1990) suggests that grouping taxa based on crown morphology and diet increases a regression’s predictive power, and that groups defined on morphological or functional criteria are better than those based on taxonomy alone. The inclusion of peramelemorphians which, as generalist omnivores feeding largely upon arthropods and succulent plant material, fill similar dietary niches to many small to medium diprotodontians, may therefore account for the observed increase in predictive power of ‘all species excluding dasyuromorphians’ regressions over those from the diprotodontian data-set. Although dasyuromorphians are primarily faunivores they exhibit a dental morphology which is largely congruent with most peramelemorphians, differing largely only in the position and size of the metaconule. The increased overlap in tooth morphology and diet, with the increase in species sample size, may explain the slightly lower error range for the ‘all species’ regressions compared to the ‘diprotodontians’ alone. However, the removal of dasyuromorphians from the entire sample results in a significantly smaller error range, perhaps suggesting that trophic overlap is a more important factor than tooth morphology. Additionally, it is apparent that removing dasyuromorphians from the

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‘all species’ data-set reduces the usefulness of cranial variables. The implication being that there is greater variability in diprotodontian skull morphology than there is in dasyuromorphian. The increased predictive power of cranial variables in the ‘all species excluding dasyuromorphians’ data-set over the diprotodontian data-set may therefore be due to similar factors. As peramelemorphians share a relatively uniform skull shape their addition in the data-set increases overall uniformity of this character such that the correlation between body size and cranial variable also improves.

Damuth & MacFadden (1990) also state that ‘… care should be taken to recognise fossil species that may be aberrant in one or more characters that for most species yield good estimates’. Using dental regression equations derived from the ‘diprotodontian’ data-set to predict the body-weight of any thylacoleonid, for example, would result in highly misleading estimates due to the hypertrophy of the carnassial P3, a feature not found in any other diprotodontian family. It is also questionable as to whether any cranial variable derived from the ‘diprotodontian’ data-set is appropriate to use for thylacoleonids, given the influence the P3 has had on the morphology of the skull. None of the predictor variables mentioned here should be used without firstly considering the overall cranial morphology of the species in question, relative to the data-set sample employed in determining the regression equation.

Dental variables Premolar variables are poorly correlated throughout all groups, with the exception of 3UPW, actually the second upper premolar for dasyuromorphians, which ranks as the third most reliable predictor for diprotodontians. These results reaffirm the findings of Janis (1990) where premolar variables were found to be generally poor predictor variables. The greatly varied functional roles of the third premolar, even among closely related taxa, accounts for most of the inconsistency in the degree of correlation between body size and the dental parameters of this tooth. Ultimately the third premolar may play a greater role in the initial acquisition of food items than it does in later processing and, subsequently, metabolic rate. In many diprotodontian groups, for instance, the shape and size of the plagiaulacoid premolar

______21 is largely controlled by the amount of pressure this tooth needs to exert on the food item, rather than by the quantity of food to be processed.

An interesting contrast between dasyuromorphians and diprotodontians is in the relative usefulness of regressions based on first molar dimensions. At least regarding morphology of the first molar, it would seem that diprotodontian species exhibit far greater variation in tooth design and size, with a weaker relationship between body size and any tooth parameter. First molar variables rank below all variables, other than those based on the third premolar, in the ‘diprotodontian’ data- set. These variables are also very poor predictors in the ‘all species excluding dasyuromorphians’ data-set. A factor that may account for lower variation in dasyuromorphian first molars is the increased responsibility of this tooth in food processing, through greater carnassialisation of the tooth row. A greater role in this process would ensure that the first molar scales with metabolic rate and consequently with body size. Whatever the reason, it is clear that regressions derived from first molar variables will not provide accurate or precise predictions when used in relation to diprotodontian species.

Janis (1990) found third molar variables to be poorly correlated with body size in ungulates, but the best estimator for kangaroos, thereby supporting the hypothesis that the third molar in kangaroos is analogous to the second molars of ungulates. This present study could find no evidence to support this hypothesis. For diprotodontians, fourth and third molar variables rank higher than first or second molar variables. Excepting the fact that two of the three highest ranking individual dental variables are derived from the fourth upper molar, there is no clear indication as to whether the fourth or third molar is the better estimator. Similarly, for the ‘all species’ data, all molar variables were interspersed with none clearly ranking higher than another. A restriction of the diprotodontian data-set such that only macropodoids are included would clarify Janis’s hypothesis.

The results from this analysis do not concur with the prevalent assertion that lower first molar crown area is the most accurate estimator of body mass in marsupials (e.g. Conroy 1987; Damuth 1990; Gagnon 1997; Gunnell 1994; Kay and

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Madden 1997; Legendre 1988, 1989; Martin 1990). Indeed, for diprotodontians, dasyuromorphians and for regressions derived from the ‘all species excluding dasyuromorphians’ data-set, 1LMA is one of the least accurate predictors of body mass, exhibiting high error statistics. According to the data presented here 2LMA and third lower molar area (3LMA) are always betters estimators of body-weight in marsupials than 1LMA. This is clear despite the high correlation coefficients for this variable against body-weight, further supporting the hypothesis (Smith 1981) that correlation coefficients do not reflect the ability of a regression to make accurate or precise predictions.

The inability of 1LMA to predict accurate or precise mass estimates is best demonstrated in Table 7. For the extinct taxa Nimiokoala greystanesi (Phascolarctidae), Kuterintja ngama (Ilariidae), Djilgaringa gillespieae (Pilkipildridae), Ngamalacinus timmulvaneyi (Thylacinidae) and Yarala burchfieldi (Yaralidae), using 1LMA results in body mass predictions between 5 and 398% greater than that derived from more reliable estimators. Conversely the dasyurid Mayigriphus orbus is significantly underestimated by 1LMA, with an estimate 24% lower than that derived from the ‘best’ variable.

In addition to highlighting the degree of usefulness of 1LMA as a predictor variable, Table 7 provides a number of body mass estimates for a series of Australian Oligocene and Miocene taxa utilising: 1) the most reliable regressions for the specimen used, as determined by error statistic rankings, and 2) the next most reliable variable(s) for the specimen concerned. Ignoring the 1LMA values in Table 7 (the purpose of which were to merely illustrate the unreliability of this variable), it is apparent that the majority of body mass estimates are in broad agreement with one another. Variation between ‘best’ and ‘second best’ estimates is as little as one percent for Djilgaringa gillespieae and only as large as 18 percent for Nimiokoala greystanesi. This range of body mass compares favourably with that for six Oligocene predators exhibiting a range from five to 323% of the ‘best’ estimate (Van Valkenburgh 1990). Janis (1990) predicts body mass for a number of extinct ungulates, using three ‘constant’ cranio-dental variables, for which the range of estimates differ by up to 87 percent (for Stenomylus hitchcocki) from that of the most

______23 reliable variable. While body mass estimates are presented here for only a few marsupial taxa it would appear that they are at least as precise as any previously published for eutherian taxa.

4UMW varies substantially in its usefulness as a predictor variable between data-sets. It is the least reliable for the ‘all species’ sample and is poorly ranked, with similarly poor error statistics, in the ‘all species excluding dasyuromorphians’ data- set. Yet for dasyuromorphians and diprotodontians alone, 4UMW ranks far higher with improved error statistics. It must therefore be concluded that, either, 4UMW is poorly correlated with body mass in peramelemorphians, or else has vastly disparate scaling rates between marsupial orders.

Janis (1990) found length measures to be better correlated than width or area, at least for kangaroos. Results from diprotodontian data used here, which include a number of macropodoid species, do not confirm this hypothesis, although a restricted data-set may. Fortelius (1990) also postulates that tooth length is a better estimator of body size than tooth width, and subsequently area which includes width. This argument is based primarily on the assertion that tooth width better measures shape than size, and is more significantly influenced by adaptation than length. No evidence for one dental dimension being a better estimator of body size was found in this analysis, with the possible exception of the data-set incorporating all species (Table 2). In the latter width variables appear to cluster towards the bottom of the rankings, indicating more error in predictions based on these variables. For the remaining taxonomic groupings the variables are freely interspersed throughout the rankings.

As noted earlier, UMRL ranks as a far better predictor of body size than LMRL for all data-sets other than that comprising dasyuromorphian species. This implies that there is an intrinsic factor of UMRL which causes it to scale with body size at a more predictable rate than LMRL. A possible explanation can be provided by focusing on the diastema and procumbent incisor, features present in most diprotodontians. As TJL is the most precise estimator of body size for both the diprotodontian and ‘all species’ data-sets, and given the lack of variation in LMRL, it

______24 is probable that part of the lower jaw other than the molar row must be scaling with body size. The diastema, part of the jaw directly involved in food processing and subsequently metabolic rate, and first lower incisor, also a functional part of the jaw in many species (e.g. macropodoids, Janis 1990), are the obvious candidates for expansion with body size.

For dasyuromorphians, the lack of a diastema and/or procumbent incisors limits the areas of the lower jaw available for expansion. Hence the molar row, again directly responsible for processing food and metabolic rate, is more likely to be acted upon by natural selection than other parts of the jaw. Similarly, the slightly lower error statistics in the dasyuromorphian data-set for LMRL, compared to UMRL, may be the consequence of greater potential for expansion in the typical dasyuromorphian snout or posterior skull region, compared to the molar row.

The results from this study contrast with the conclusions of Janis (1990) who found lower molar row length to be ‘… superior to any single dental variable’ as well as ‘…a consistently good predictor in herbivores with enlarged individual cheek teeth’. While LMRL is the most highly ranked predictor variable in the dasyuromorphian data-set and ranks higher than any individual dental variable in the ‘all species’ data-set, it is only as the sixth most reliable predictor in the latter. When dasyuromorphians are removed from the ‘all species’ data-set LMRL drops to be the ninth most reliable predictor variable, and is ranked equal eighth in the diprotodontian sample. LMRL appears to be a very good predictor for faunivorous dasyuromorphians, but far less so for insectivorous/omnivorous peramelemorphians. At least for herbivorous diprotodontian marsupials LMRL is not ‘…a consistently good predictor’, with many single dental variables exhibiting a superior ranking. Despite this, LMRL may still be an appropriate variable to use in many cases, given its relatively fair ranking combined with the relatively high preservational potential and taphonomic advantage typically attributed to dentaries.

Janis (1990) found molar row length to be highly correlated with body mass in ungulates, but less well for kangaroos, which was ascribed to molar progression. Results presented here suggest UMRL to be a substantially better estimator of body

______25 size than LMRL, in all but the dasyuromorphian data-set. For diprotodontians UMRL is highly correlated, ranking as the third most reliable predictor. Perhaps the use of macropodoid specimens with all four molars present accounts for the high correlation, eliminating the effects of molar progression. The fact that the diprotodontian data-set was not restricted to macropodoids may confound these results.

Non-dental variables OCH was found to be a poor estimator of body mass in all data-sets. This variable was equally most highly ranked in the ‘all species’ and dasyuromorphian data-sets but exhibited a SEE% of 69 and PE% of 47 in the former. While ranked lowly relative to all other variables in the dasyuromorphian data-set the SEE% and PE% were far lower compared to other sample groups (SEE% = 34; PE% = 24). These figures compare favourably with those found for OCH in ungulates when suines are excluded (PE% = 28.1; SEE% = 42.5) (Janis 1990).

In contrast, TSL is variably useful as a predictor of body size throughout the samples analysed. This variable is a good predictor for marsupials in general, but significantly more so for diprotodontians than dasyuromorphians when considering error statistics as opposed to ranking. The error statistics for TSL in the diprotodontian sample compare favourably with those of ungulates (Janis 1990), perhaps suggesting that this cranial variable scales with body size in herbivores better than it does in carnivores. Van Valkenburgh (1990) found skull length to rate second only to head-body length as a predictor of body size in carnivores, although the PE% and SEE% were substantially larger than they are for the faunivorous dasyuromorphians, for which TSL ranks seventh, in the present study. Van Valkenburgh (1990) also notes that the inaccuracy of the total sample regressions can be explained as a result of differences in scaling among families or size groups.

Multiple variable regressions Damuth and MacFadden (1990) found that the use of multiple variables in body size regressions could increase accuracy of predictions. Best subset analyses performed here suggest that multiple variables may result in a significant

______26 improvement in predictive power, although significance disappears if more than two variables are used (Table 6). For the ‘all species’ and ‘all species excluding dasyuromorphians’ data-sets analysed at least one multiple variable regression exhibited error statistics lower than those found for the best individual variable regression. For example, utilising the regression derived from the best overall pair of variables (2UML & UMRL) substantially improves predictive power for marsupials in general (based on the ‘all species’ data). Likewise, predictive power is increased by using a combination of 4LMW and TSL for ‘all species excluding dasyuromorphians’. However, the single variables LMRL and TJL are better predictors than their bivariate counterparts in the dasyuromorphian and diprotodontian data-sets respectively.

To determine the actual usefulness of the predictive regression equations, as already outlined, average body masses were determined for selected extant marsupials. The highest ranking appropriate variable from a suitable data-set, exhibiting the lowest error statistics, was used to make the predictions (Table 8). The results confirm the reliability of the regression equations, with the average difference being 27.4% between actual and predicted average species body mass. It is important to remember that these predictions (as with the extinct species’ predictions) are average species masses as determined from one randomly selected, but hopefully typical, specimen. Undoubtedly better estimates will be derived from using as many specimens as possible for a species and averaging the resultant estimates.

How useful is all this? Fortelius (1990) noted that any body-size distribution ‘…will inevitably be a trivialised version of the real thing’ as the use of allometric body mass equations involves averaging. This should not be forgotten. When a body mass estimate is derived from allometric equations, such as those presented here, we are given an average for a species’ (or particular sex’s) weight based on the fossil specimen used. Arguments concerning the predictive power of a particular regression, based on error statistics for the variable in question, have more to do with the precision of an estimate than its accuracy. We will probably never be certain of a particular fossil species’ body mass, but by using the most appropriate dental variable(s), or

______27 combination of dental, cranial and postcranial variables, we can maximise the likelihood of precision and accuracy, given Recent scaling trends.

A cautionary tale Several factors should be taken carefully into consideration when estimating body size:

i) When predicting morphological features, such as body mass, of extinct animals an assumption inherent in our models is that regarding similarity of scaling trends and similarity of rates of evolution with extant taxa. This may not be justified. Alroy (1998) concludes that for North American Cainozoic mammals, at least, new species have on average been 9.1 percent larger than their predecessors in the same genera, affirming Cope’s rule (Cope 1887). On its own, this is not a problem if it can be demonstrated that scaling rates have remained the same for marsupials over time, otherwise adjustments in body mass estimates will be required.

ii) As always extrapolation beyond the range should be avoided, as it can result in erroneous predictions, due to potential changes in regression slope (Underwood 1997).

iii) When deciding on the most appropriate regression variable and data-set to use it is important to take into consideration the specimen being used as well as the species in question. Where possible a restricted taxonomic data-set should be used, but only if the variable to be used exhibits error statistics lower than those from another sample. Additionally, the highest ranked variable in any sample should be used ahead of those more lowly ranked.

iv) The relationship between correlation coefficients and range is well known (e.g. Smith 1981, 1984). Certainly the ‘all species’ data-set includes five orders of magnitude of body size. For dasyuromorphians the correlation coefficients would appear to be a more realistic guide for determining a

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regression’s predictive power, given the low number of species included and the fact that the species’ body mass range over only three orders of magnitude. The correlation coefficient (r), coefficient of determination (r2) and adjusted r2 are not reliable indicators of the prediction power of a regression. Take for example 4UMW in the ‘all species’ data-set, with the highest SEE% and PE% statistics for any sample, but with a correlation coefficient suggesting a very strong relationship. Use of this variable as a predictor of body size would result in highly inaccurate and imprecise estimates, despite the apparent goodness-of-fit.

Acknowledgments Extant mammal specimens were kindly loaned from the Australian and Queensland Museums. Vital assistance in finding and providing appropriate specimens came from Dr Sandy Ingleby. Helpful suggestions for this manuscript were provided by Dr Suzanne Hand, Mary Knowles and two anonymous referees. Matthew Crowther kindly provided some body mass data. Many thanks to all of them.

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Table 1: Species used in analysis Mean Body mass (g) Species Sample Size Source (Male/Female) Diprotodontians Aepyprymnus rufescens 2 -/2500 7 Bettongia penicillata 2 1300 3 Cercartetus caudatus 12 3 3 Dactylopsila trivirgata 10 423 3 Dendrolagus goodfellowi 6 -/8150 2 Dorcopsis atrata 2 7500/- 4 Dorcopsis hageni 3 -/5500 2 Dorcopsulus vanheurni 4 1750/- 2 Macropus giganteus 7 43000/- 7 Macropus robustus 4 39000/20000 7 Macropus rufus 8 66000/26500 3 Petauroides volans 15 1068/1130 1 Petaurus norfolcensis 9 230 3 Phascolarctos cinereus 16 6254/5281 5 Pseudocheirus peregrinus 12 987/878 1 Setonix brachyurus 3 -/2900 3 Spilocuscus maculatus 23 4567 1 Thylogale billardierii 4 -/3900 3 Thylogale stigmatica 8 5100/4100 3 Trichosurus vulpecula 18 2701/2362 1 Vombatus ursinus 14 26000 3 Wallabia bicolor 2 17000/13000 3 Peramelemorphians Echymipera kalubu 18 1313/604 2 Echymipera rufescens 7 1450/- 6 Isoodon macrourus 13 2100/1100 3 Microperoryctes longicauda 16 478/598 2 Perameles nasuta 15 1441/895 6 Dasyuromorphians Antechinus flavipes 9 56/34 3 Antechinus minimus 6 65/- 3 Antechinus stuartii 20 35/20 3 Antechinus swainsonii 4 65/- 3 Dasyrurus maculatus 15 3210/1830 5 Dasyurus viverrinus 11 1300/880 3 Planigale maculata 4 12/10 Sminthopsis crassicaudata 5 15/- 3 Sminthopsis macroura 3 20/- 3 Thylacinus cynocephalus 12 29500 9 Notoryctomorphians Notoryctes caurinus 3 -/55 8 Source: 1 - Flannery, T.F. (1994). ‘Possums of the world.’ (Geo Productions: Sydney.); 2 - Flannery, T.F. (1995). ‘Mammals of New Guinea.’ (Reed: Sydney); 3 - Strahan, R. (ed.) (1995). ‘Mammals of Australia.’ (Reed Books & Australian Museum: Sydney); 4- Flannery, T.F. (1995). ‘Mammals of the South-west Pacific and Moluccan Islands.’ (Reed: Sydney.); 5 - averages from Australian Museum specimens (from NSW only); 6 - averages from Australian Museum specimens; 7 - Janis (1990); 8 - median of weight range presented in: Strahan, R. (ed.) (1983). ‘The Australian Museum Complete Book of Australian Mammals.’ (Cornstalk Publishing: Sydney); 9 – Paddle, R. (2001). ‘The last Tasmanian Tiger: The History and Extinction of the Thylacine’. (Cambridge University Press: Cambridge.)

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Table 2. Ranked body mass equations for the ‘all species’ data-set

smearing see% pe% Total 2 Regression Variable (x) SEE% PE% adj. R estimate rank rank rank (%) log y = -3.036 + 3.464(logx) TJL 39 27 1 1 1 0.980 5.2 log y = -3.733 + 3.641(logx) TSL 40 28 2 2 2 0.979 5.5 log y = -0.914 + 3.320(logx) UMORL 51 35 3 3 3 0.967 8.6 log y = -0.944 + 3.372(logx) UMRL 52 36 4 4 4 0.970 8.9 log y = -1.253 + 3.540(logx) LMORL 55 38 5 5 5 0.962 9.4 log y = -1.302 + 3.602(logx) LMRL 60 39 6 6 6 0.962 10.3 log y = 1.385 + 1.536(logx) 4UMA 61 42 7 8 7 0.959 12.1 log y = 1.005 + 1.857(logx) 2LMA 63 41 8 7 7 0.951 11.9 log y = 0.914 + 3.327 (logx) 3UML 66 44 9 9 8 0.953 13.4 log y = 1.124 + 1.710(logx) 3LMA 66 44 9 9 8 0.952 13.7 log y = 1.422 + 3.396(logx) 3LMW 68 45 10 10 9 0.950 14 log y = 1.657 + 3.112(logx) 4LMW 69 45 11 10 10 0.948 14.9 log y = -1.295 + 3.529(logx) OCH 69 47 11 11 11 0.949 14.7 log y = 0.909 + 3.245(logx) 4LML 69 47 11 11 11 0.948 15.1 log y = 1.360 + 1.546(logx) 4LMA 71 47 12 11 12 0.947 14.9 log y = 1.423 + 3.495(logx) 2LMW 71 47 12 11 12 0.942 14.3 log y = 0.751 + 3.525(logx) 3LML 71 48 12 12 13 0.945 14.5 log y = 0.606 + 3.846(logx) 2LML 72 48 13 12 14 0.939 15.3 log y = 1.865 + 2.408(logx) 4UML 72 50 13 14 15 0.946 16.6 log y = 1.278 + 1.759(logx) 1LMA 75 50 14 14 16 0.933 16.3 log y = -1.448 + 3.443(logx) PJL 79 49 16 13 17 0.936 16.3 log y = 0.633 + 3.782(logx) 2UML 77 50 15 14 17 0.933 16.1 log y = 0.737 + 1.951(logx) 1UMA 77 51 15 15 18 0.931 16.6 log y = 1.669 + 3.345(logx) 1LMW 79 50 16 14 18 0.928 16.7 log y = 0.662 + 1.942(logx) 2UMA 80 52 17 16 19 0.930 16.7 log y = 0.421 + 4.146(logx) 1UML 81 54 18 17 20 0.924 18.4 log y = 1.685 + 2.377(logx) 3LPL 88 50 21 14 20 0.914 18.6 log y = 0.813 + 1.791(logx) 3UMA 84 54 20 17 21 0.933 18.6 log y = 0.792 + 3.770(logx) 1LML 82 56 19 19 22 0.923 19.5 log y = 1.015 + 3.681(logx) 1UMW 88 55 21 18 23 0.916 22 log y = 0.634 + 4.073(logx) 2UMW 88 57 21 20 24 0.920 20.1 log y = -2.789 + 3.885(logx) PSL 91 57 22 20 25 0.920 20.8 log y = 2.052 + 2.753(logx) 3UPW 100 72 23 23 26 0.902 33.2 log y = 0.638 + 3.953(logx) 3UMW 110 66 24 22 26 0.900 26.9 log y = 1.494 + 2.626(logx) 3UPL 115 64 25 21 26 0.880 28.4 log y = 2.327 + 2.806(logx) 3LPW 124 82 26 24 27 0.868 40 log y = 1.072 + 3.418(logx) 4UMW 160 95 27 25 28 0.835 49.9

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Table 3: Ranked body mass equations for the ‘All species excluding dasyuromorphians’ data-set regression variable see% pe% see% pe% total adj. R2 smearing rank rank rank estimate (%) log y = -0.229 + 2.880(logx) UMRL 34 23 1 1 1 0.961 3.9 log y = -0.366 + 2.936(logx) UMORL 36 25 2 2 2 0.963 4.6 log y = -3.027 + 3.475(logx) TJL 37 25 3 2 3 0.957 4.7 log y = 1.743 + 1.305(logx) 4LMA 41 28 4 3 4 0.946 7.2 log y = 1.301 + 1.527(logx) 3UMA 42 29 5 4 5 0.946 5.6 log y = 1.591 + 1.408(logx) 3LMA 42 30 5 5 6 0.944 5.8 log y = 1.810 + 1.257(logx) 4UMA 43 30 6 5 7 0.956 6.2 log y = 1.291 + 2.927(logx) 3LML 44 31 7 6 8 0.926 5.5 log y = -0.370 + 2.978(logx) LMRL 46 30 9 5 9 0.935 6.7 log y = -3.273 + 3.425(logx) TSL 45 32 8 7 10 0.951 6.6 log y = -0.549 + 3.056(logx) LMORL 45 32 8 7 10 0.947 6.8 log y = 1.210 + 3.326(logx) 3UMW 50 31 10 6 11 0.929 7.2 log y = 1.310 + 2.908(logx) 3UML 46 32 9 7 11 0.925 6.6 log y = 1.262 + 1.568(logx) 2UMA 46 33 9 8 12 0.912 7.1 log y = 1.989 + 2.609(logx) 4LMW 51 32 11 7 13 0.920 9 log y = -1.043 + 3.230(logx) PJL 53 32 13 7 14 0.935 8.1 log y = 2.077 + 2.074(logx) 4UML 52 39 12 10 15 0.924 8.3 log y = 1.801 + 2.809(logx) 3LMW 57 38 16 9 16 0.907 9.9 log y = 1.423 + 2.804(logx) 2UML 54 41 14 12 17 0.889 10.1 log y = 1.586 + 1.436(logx) 2LMA 56 40 15 11 17 0.881 9.2 log y = 1.299 + 3.193(logx) 2UMW 59 38 18 9 18 0.869 9.5 log y = 1.142 + 3.204(logx) 2LML 58 40 17 11 19 0.836 8.8 log y = -2.410 + 3.724(logx) PSL 61 39 19 10 20 0.918 10.6 log y = 1.665 + 2.391(logx) 4LML 61 41 19 12 21 0.894 12.5 log y = 1.675 + 2.778(logx) 4UMW 65 41 21 12 22 0.914 11.2 log y = 1.815 + 2.815(logx) 2LMW 66 45 22 14 23 0.846 12.7 log y = -0.850 + 3.232(logx) OCH 68 43 24 13 24 0.904 12.3 log y = 1.314 + 1.558(logx) 1UMA 66 46 22 15 24 0.846 10 log y = 2.307 + 2.141(logx) 3UPW 67 45 23 14 24 0.843 14.1 log y = 1.762 + 2.578(logx) 1UMW 68 45 24 14 25 0.792 9.8 log y = 2.112 + 1.747(logx) 3LPL 62 71 20 20 26 0.828 42.6 log y = 1.249 + 3.081(logx) 1UML 71 52 25 18 27 0.827 12.7 log y = 1.688 + 1.431(logx) 1LMA 73 51 26 17 27 0.817 13.1 log y = 1.964 + 2.769(logx) 1LMW 78 50 27 16 27 0.799 13.3 log y = 1.568 + 2.694(logx) 1LML 88 62 28 19 28 0.761 18.3 log y = 1.871 + 2.102(logx) 3UPL 110 62 30 19 29 0.763 29.9 log y = 2.640 + 1.966(logx) 3LPW 91 86 29 21 30 0.747 45.6

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Table 4: Ranked body mass equations for dasyuromorphians regressions variable see% pe% see% pe% total adj. R2 smearing rank rank rank estimate (%) log y = -1.075 + 3.209(logx) LMRL 18 13 1 1 1 0.996 3 log y = -0.992 + 3.279(logx) UMRL 18 14 1 2 2 0.996 1.2 log y = -1.098 + 3.350(logx) UMORL 19 14 2 2 3 0.996 1.2 log y = -1.225 + 3.340(logx) LMORL 20 16 3 3 4 0.995 1.6 log y = -2.551 + 3.496(logx) PSL 24 16 4 3 5 0.993 2 log y = -2.722 + 3.207(logx) TJL 26 18 5 4 6 0.991 2.3 log y = -3.465 + 3.436(logx) TSL 27 19 6 5 7 0.991 2.2 log y = -1.409 + 3.183(logx) PJL 28 20 7 6 8 0.990 2.6 log y = 0.426 + 1.890(logx) 2UMA 31 21 8 7 9 0.989 2.9 log y = 0.379 + 4.038(logx) 2UMW 31 21 8 7 9 0.989 3 log y = 0.290 + 3.945(logx) 1UML 31 22 8 8 10 0.989 3 log y = 0.567 + 3.400(logx) 3LML 33 22 9 8 11 0.987 3.5 log y = -1.341 + 3.434(logx) OCH 34 24 10 10 12 0.986 3.7 log y = 0.775 + 3.143(logx) 3UML 35 23 11 9 12 0.985 4 log y = 0.528 + 3.381(logx) 4UMW 36 23 12 9 13 0.977 3.8 log y = 0.559 + 1.720(logx) 3UMA 36 24 12 10 14 0.984 4.2 log y = 2.053 + 3.372(logx) 3UPW 36 24 12 10 14 0.977 16.3 log y = 0.878 + 1.777(logx) 3LMA 37 25 13 11 15 0.984 4.4 log y = 0.771 + 3.116(logx) 4LML 37 25 13 11 15 0.984 4.4 log y = 0.560 + 1.977(logx) 1UMA 38 24 14 10 15 0.983 4.5 log y = 0.511 + 3.622(logx) 2LML 38 25 14 11 16 0.983 4.5 log y = 1.085 + 1.622(logx) 4LMA 37 26 13 12 16 0.983 4.5 log y = 1.156 + 1.724(logx) 4UMA 38 26 14 12 17 0.983 4.4 log y = 0.312 + 3.780(logx) 3UMW 39 25 15 11 17 0.982 4.8 log y = 0.811 + 3.984(logx) 1UMW 40 25 16 11 18 0.982 4.7 log y = 1.432 + 3.374(logx) 4LMW 39 27 15 13 19 0.982 4.8 log y = 0.519 + 3.497(logx) 2UML 39 27 15 13 19 0.982 4.9 log y = 0.890 + 1.845(logx) 2LMA 40 27 16 13 20 0.981 5 log y = 0.723 + 3.688(logx) 1LML 42 27 17 13 21 0.980 5.3 log y = 1.228 + 3.702(logx) 3LMW 44 29 18 14 22 0.978 6.2 log y = 1.163 + 1.845(logx) 1LMA 44 30 18 15 23 0.978 5.9 log y = 1.806 + 3.231(logx) 4UML 46 30 19 15 24 0.977 5.9 log y = 1.253 + 3.337(logx) 3UPL 49 29 21 14 25 0.974 6.6 log y = 1.298 + 3.734(logx) 2LMW 48 31 20 16 26 0.975 6.8 log y = 1.612 + 3.664(logx) 1LMW 52 34 22 17 27 0.971 8 log y = 2.248 + 3.302(logx) 3LPW 55 35 23 18 28 0.968 9 log y = 1.575 + 2.694(logx) 3LPL 74 46 24 19 29 0.949 13.7

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Table 5: Ranked body mass equations for diprotodontians

Regression variable see% pe% see% pe% total adj. R2 smearing (x) rank rank rank estimate (%) log y = -2.884 + 3.426(logx) TJL 29 20 1 1 1 0.977 2.8 log y = -0.567 + 3.072(logx) UMORL 37 25 3 2 2 0.962 4.7 log y = 1.775 + 2.991(logx) 3UPW 36 26 2 3 2 0.954 1.3 log y = -0.418 + 3.011(logx) UMRL 38 25 4 2 3 0.906 4.4 log y = -3.410 + 3.508(logx) TSL 38 26 4 3 4 0.962 4.9 log y = 1.774 + 1.291(logx) 4UMA 40 29 5 6 5 0.959 5.4 log y = 1.733 + 1.322(logx) 4LMA 41 28 6 5 5 0.955 5.8 log y = 1.275 + 1.559(logx) 3UMA 42 28 7 5 6 0.957 5.5 log y = 1.804 + 2.706(logx) 4UMW 42 28 7 5 6 0.956 5.5 log y = 1.371 + 1.555(logx) 3LMA 43 28 8 5 7 0.953 5.9 log y = 1.907 + 2.719(logx) 4LMW 44 27 9 4 7 0.950 6.2 log y = 1.809 + 2.400(logx) 4UML 44 31 9 7 8 0.953 6.4 log y = 1.303 + 3.242(logx) 3UMW 46 29 10 6 8 0.948 6.3 log y = -0.719 + 3.236(logx) LMRL 47 28 11 5 8 0.865 6.4 log y = 1.348 + 2.890(logx) 3UML 46 32 10 8 9 0.949 6.8 log y = -0.783 + 3.222(logx) LMORL 46 32 10 8 9 0.945 7.1 log y = 1.225 + 3.019(logx) 3LML 47 32 11 8 10 0.944 7.1 log y = -2.748 + 3.964(logx) PSL 53 33 13 9 11 0.937 8.4 log y = 1.587 + 3.114(logx) 3LMW 53 33 13 9 11 0.932 8.3 log y = 1.640 + 2.490(logx) 4LML 51 35 12 11 12 0.937 8.3 log y = 0.951 + 1.778(logx) 2UMA 54 34 14 10 13 0.919 8.6 log y = -0.952 + 3.313(logx) OCH 55 35 15 11 14 0.931 8.7 log y = -0.998 + 3.211(logx) PJL 61 36 17 12 15 0.918 9.6 log y = 1.039 + 3.340(logx) 2UML 57 38 16 13 15 0.912 9.6 log y = 1.016 + 3.582(logx) 2UMW 63 36 18 12 16 0.898 10.1 log y = 1.214 + 1.708(logx) 2LMA 61 39 17 14 17 0.902 10.5 log y = 0.959 + 3.442(logx) 2LML 65 43 19 15 18 0.890 12.8 log y = 1.543 + 3.257(logx) 2LMW 71 45 20 16 19 0.876 12.5 log y = 1.109 + 3.470(logx) 1UMW 73 43 21 15 19 0.858 13.2 log y = 0.910 + 1.821(logx) 1UMA 75 48 22 17 20 0.851 15 log y = 0.848 + 3.632(logx) 1UML 82 58 23 19 21 0.828 18.5 log y = 1.682 + 3.226(logx) 1LMW 89 56 24 18 21 0.805 19.2 log y = 1.271 + 1.740(logx) 1LMA 89 60 24 20 22 0.807 20.6 log y = 0.971 + 3.515(logx) 1LML 106 75 25 21 23 0.750 28.6 log y = 2.424 + 2.377(logx) 3LPW 119 75 26 21 24 0.706 34.3 log y = 1.841 + 2.116(logx) 3UPL 132 78 27 22 25 0.692 39.2 log y = 2.263 + 1.703(logx) 3LPL 165 107 28 23 26 0.587 64.5

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Table 6: Multiple variable regressions

Data-set Regression equation adj. R2 SEE% PE% smearing estimate (%)

All species log y = -2.23 – 3.01(log2UML) + 6.08(logUMRL) 0.983 36 27 1.2

All species log y = 1.38 + 2.06(log1LMW) + 1.28(log4LML) 0.959 55 37 10.1 All species log y = 1.27 + 0.989(1UMA) + 1.25(log4UML) 0.956 58 37 9.9 All species log y = -3.1 + 0.853(logOCH) + 2.74(logTSL) 0.977 42 29 6.7 All – dasyuromorphians log y = -0.919 + 1.27(log4LMW) + 1.86(logTSL) 0.972 32 23 5.6 All – dasyuromorphians log y = 1.22 + 1.55(log1UMW) + 0.915(log4UMA) 0.956 58 41 22.9 All – dasyuromorphians log y = 1.38 + 1.85(log3LMW) + 0.72(log4LMA) 0.957 62 43 25.4 All – dasyuromorphians log y = -2.54 + 0.919(logOCH) + 2.55(logTJL) 0.977 42 28 11.7 Dasyuromorphians log y = -3.75 – 5.91(log2UML) + 8.61(logLMRL) 0.993 23 13 2.5 Dasyuromorphians log y = 0.369 – 1.15(log2LMA) + 5.51(log3LML) 0.987 33 22 3.5 Dasyuromorphians log y = -2.28 + 0.789(logOCH) + 2.7(logPSL) 0.993 23 16 1.1 Diprotodontians log y = -2.83 – 1.07(logPSL) + 4.3(logTJL) 0.973 31 22 3.9 Diprotodontians log y = 1.61 + 0.819(log1UMW) + 0.985(log4UMA) 0.955 36 24 3.8 Diprotodontians log y = 1.56 + 1.54(log3LMW) + 1.34(log4LML) 0.963 37 23 2.3

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Table 7: Body mass predictions for extinct marsupial taxa

Taxon Family Order Specimen Variable Data-set Smearing Weight estimate (%) (g)

Hypsiprymnodon Hypsiprymnodontidae Diprotodontia QMF13051 UMRL All species excluding 3.9 696 bartholomaii dasyuromorphians H. batholomaii Hypsiprymnodontidae Diprotodontia QMF13051 1UMW & Diprotodontians 3.8 621 4UMA Nimiokoala greystanesi Phascolarctidae Diprotodontia QMF16378 3UPW Diprotodontians 1.3 2714 N. greystanesi Phascolarctidae Diprotodontia QMF16378 3LMW & Diprotodontians 2.3 2220 4LML N. greystanesi Phascolarctidae Diprotodontia QMF30487 1LMA All species excluding 13.1 4448 dasyuromorphians Kuterintja ngama Ilariidae Diprotodontia QMF23306 3LMW & Diprotodontians 2.3 13378 4LML K. ngama Ilariidae Diprotodontia QMF40324 1UMW & Diprotodontians 3.8 13861 4UMA K. ngama Ilariidae Diprotodontia QMF40324 4UMA Diprotodontians 5.4 11559 K. ngama Ilariidae Diprotodontia QMF23306 1LMA All species excluding 13.1 21493 dasyuromorphians Djilgarinja gillespiei Pilkipildridae Diprotodontia QMF13028 3LMW & Diprotodontians 2.3 415 4LML D. gillespiei Pilkipildridae Diprotodontia QMF13028 4LMA Diprotodontians 5.8 411 D. gillespiei Pilkipildridae Diprotodontia QMF13028 1LMA All species excluding 13.1 2066 dasyuromorphians

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Taxon Family Order Specimen Variable Data-set Smearing Weight estimate (%) (g)

Mayigriphus orbus Dasyuridae Dasyuromorphia QMF23780 LMRL Dasyuromorphians 3 17 M. orbus Dasyuridae Dasyuromorphia QMF23780 3LML Dasyuromorphians 3.5 16 M. orbus Dasyuridae Dasyuromorphia QMF23780 1LMA Dasyuromorphians 5.9 13 Ngamalacinus Thylacinidae Dasyuromorphia QMF16853 LMRL Dasyuromorphians 3 5743 timmulvaneyi N. timmulvaneyi Thylacinidae Dasyuromorphia QMF16853 & 2UML & Dasyuromorphians 2.5 5201 QMF30300 LMRL N. timmulvaneyi Thylacinidae Dasyuromorphia QMF16853 1LMA Dasyuromorphians 5.9 12912 Yarala burchfieldi Yaralidae Peramelemorphia QMF16860 UMRL All species excluding 3.9 63 dasyuromorphians Y. burchfieldi Yaralidae Peramelemorphia QMF16860 2UML & All species 1.2 53 UMRL Y. burchfieldi Yaralidae Peramelemorphia QMF16860 1LMA All species excluding 13.1 66 dasyuromorphians

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Table 8: Comparison of body mass predictions and published body masses for extant species

Species Family Specimen Variable Sample Predicted Actual Source for actual weight weight weight (g) (g) Sarcophilus harissii Dasyuridae UNSWZ456 LMRL Dasyuromorphians 14066 9000 mean for males, Strahan (1995) Pseudocheirops archeri Pseudocheiridae AR2534 UMRL All species 1801 1190 species mean, Strahan (1983) excluding dasyuromorphians Bettongia lesueur Potoroidae AR15735 UMRL All species 1644 ~1500 approximate mean, Strahan (1995) excluding dasyuromorphians Petaurus australis Petauridae UNSWZ455 UMRL All species 426 582 mean for males, Craig (1985) excluding dasyuromorphians Potorous tridactylus Potoroidae AR1568 PSL & TJL Diprotodontians 1931 1300 species mean, Grainger, Gunn & Watts (1987) Macropus dorsalis Macropodidae AR1580 UMRL All species 11458 16000 mean for males, Strahan (1983) excluding dasyuromorphians Antechinus godmani Dasyuridae QMJ3673 LMRL Dasyuromorphians 56 58 mean for females, Strahan (1995) Sminthopsis hirtipes Dasyuridae QMJM5239 LMRL Dasyuromorphians 20 15 mean for males, Strahan (1995) Sminthopsis youngsonii Dasyuridae QMJM6186 LMRL Dasyuromorphians 16 10 mean for males, Strahan (1995) Thylogale thetis Macropodidae AR627 UMRL All species 6216 7000 mean for males, Strahan (1983) excluding dasyuormorphians

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Chapter 3 A review of cenogram methodology and body-size distribution moment statistics in the determination of environmental parameters

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A review of cenogram methodology and body-size distribution moment statistics in the determination of environmental parameters

Introduction Cenogram methodology has been used extensively by palaeomammalogists to determine broad palaeoenvironmental characteristics for fossil faunas, such as levels of ‘humidity’ and ‘vegetation structure’ (e.g. Legendre 1986,1989), Gingerich (1989), de Bonis et al. (1992), Legendre and Hartenberger (1992), Ducrocq et al. (1994), Gunnell (1994), Maas & Krause (1994), Morgan et al. (1995), Gunnell (1997), Montuire & Desclaux (1997), Wilf et al. (1998)). Legendre (1986, 1989) introduced palaeomammalogists to cenograms, adapting the neoecological methodology developed by Valverde (1964). Initially, ‘cenogramic curves’ were devised to examine relationships between predator and prey size. Cenograms were constructed for particular extant mammalian ‘micro-communities’, by ranking head and body length, on the y- axis, and specific trophic groups, on the x-axis, (Figure 3). (Valverde (1964) determined that predators are usually intermediate in size compared to their prey.

Legendre (1986) altered the methodology by adopting a log body-size distribution on the y-axis of the cenogram, removing carnivores (thereby using only species subject to predation) and flying mammals, and amalgamating all prey trophic groups such that they were rank ordered according to ‘average’ species body weight on the x-axis. Three size categories, ‘empirically derived’ from modern fauna studies, were used: small – weighing less than 500g; medium – between 500g and 8kg; and large – weighing more than 8kg. Cenograms were then constructed for a number of Recent communities from around the world. Utilising this database, Legendre (1986,1989) made a number of observations regarding the structure of cenograms and environmental parameters: 1) a gap in the medium sized species should indicate an open environment whereas a continuous distribution suggests a more closed one; 2) the slope for large

______40 mammals reflects the aridity of the environment, where the larger the slope the greater the aridity; and 3) the slope for small species could be an index of minimal temperatures. Legendre (1986,1989) then introduced cenogram methodology into the realm of palaeoecology, using these empirical rules to infer environmental conditions for a number of Eocene and Oligocene communities from southern France.

Since this time palaeontologists have adopted cenogram methodology with vigour, with relatively few of these studies attempting to confirm or refute the earlier work of Legendre (1986,1989). Maas & Krause (1994) use cenograms only for comparing body-size distributions between faunal zones and not to infer palaeoenvironmental parameters, believing sampling and taphonomic factors for fossil faunas confound cenogram interpretations. Morgan et al. (1995) also mention that various problems exist in the construction of cenograms and other size-distributions, including taphonomic biases, the possibility that extinct biotas have no modern analogues and time-averaging factors which associate non-coeval species.

Rodriguez (1999) provided the first critical exploration of the empirical evidence for cenogram parameters and their relationship to climatic and habitat variables. Rodriguez (1999) found partial support for the ‘gap’ or ‘offset’ rule although with the rider that the “… pattern should only be interpreted as a trend towards more mammal species existing in this size interval in more forested areas”. Additionally, it was found that annual rainfall was not associated with the slope of large (>8kg) animals; a weak relationship existed for medium to large (500g to 250kg) and large (>8kg) mammal slopes and certain aridity indices; and that no association existed between the slope of the small mammals (<500g) and temperature (Rodriguez, 1999). Only weak relationships existed between proposed cenogram and environmental variables, and that more significant relationships should have been found by chance alone (ibid.).

Alroy (2000) suggested that moment statistics, such as the mean, standard deviation, skewness and kurtosis, might be more informative than cenogram variables as:

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1) quantitative methods relating to cenograms usually require arbitrary binning of the body mass spectrum;

2) cenogram information can also be more easily expressed by moment statistics, for instance skewness indicates higher species richness in either small or large body mass categories and negative kurtosis indicates the presence of a gap in the medium size range;

3) species richness, which defines cenogram slopes, is not captured by moment statistics;

4) no empirical evidence exists indicating a strong relationship between cenogram parameters and measures of climate and habitat; and

5) the mammalian body mass spectrum was not filled during the early and possibly middle Tertiary, thereby affecting any interpretations that are dependant on observations of species richness.

Other authors have attempted to quantify the empirical rules suggested by Legendre (1986,1989), providing ranges for medium body-size slopes and offsets from various modern faunas (e.g. Gingerich, 1989).

Methods

A database of 45 extant Australian mammal faunas was compiled from published literature. Faunal lists were limited to those from national parks, other protected areas or discrete geographical areas, where possible. Each faunal list was then further subdivided, if necessary, such that probable mammal communities from distinct habitats were identified. Utilising regional species lists to assign species to habitats and communities is not, however, an unambiguous exercise. Habitats for species were derived from the literature or inferred from their biology. A possible caveat arises from the fact that, although a species is known from a region and is also known to inhabit a specific habitat, it does not necessarily follow that the species is definitely found in that

______42 habitat in that particular region. The species in question may be a transient member of many habitats, but may only inhabit one habitat in a specific region. For the most part, however, these habitat-specific faunal lists are considered to be reasonably accurate.

Species that have become extinct since European settlement were included where historical records were available. A total of 118 habitat-specific faunal lists were thus constructed. Twenty-eight variables were recorded for each community, including a grouping variable with five vegetational categories, various body-mass moment statistics, a selection of cenogram parameters, and eight climatic variables (Table 9 and Table 10). Climatic data were taken from the nearest Australian Bureau of Meteorology station (Australian Bureau of Meteorology, 2002), and as such the climatic variables therefore overlap for some geographically adjacent faunas.

The five vegetation categories used are: 1) ‘Closed forest’; 2) ‘Forest / wet forest / wet open forest’; 3) ‘Dry forest / dry open forest’; 4) ‘Woodland’ and 5) ‘Open woodland / forested grassland’. These categories are loosely derived from Specht (1981) relating to the ‘Foliage Projective Cover of tallest stratum’ or the degree of ‘openness’ of the vegetation. Hence, ‘closed forest’ used herein equates to 100-70% foliage projective cover; ‘forest or wet open forest’ to 70-50% cover; ‘dry open forest’ to 50- 30% cover; ‘woodland’ to 30-10% cover and ‘open woodland’ to less than 10% foliage projective cover.

Authors have identified their own vegetation types for the 118 habitat-specific faunas used herein. These identifications were then re-assigned to one of the five vegetation categories mentioned above using Specht (1981). The ‘closed forest’ category employed therefore includes classifications, cited in the database of extant mammal faunas, such as ‘tall closed-forest’, ‘closed-forest’, and ‘low closed-forest’. The ‘forest or wet forest’ category includes classifications such as ‘tall forest’, ‘forest’, ‘low forest’, ‘wet sclerophyll’ and ‘wet open forest’. Similarly, ‘dry open forest’, incorporates groupings such as ‘tall open-forest’, ‘open-forest’, ‘low open-forest’ and ‘dry sclerophyll’. The ‘woodland’ category relates to classifications such as ‘tall woodland’,

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‘woodland’ and ‘low woodland’. Lastly, ‘open woodland’ used herein, is synonymous with groupings such as ‘low open woodland’, ‘tall open shrubland’, ‘open shrubland’.

To test the assertion that the slope for the medium-large mammals reflects aridity of the environment (Legendre, 1986;1989), the total annual rainfall and Martonne’s aridity index (IA) were included, following Rodriguez (1999).

The association between variables was tested using Spearman’s rho, which is a non-parametric rank-order test of correspondence, rather than direct linear correlation (Steel & Torrie, 1980).

Analyses were run on data-sets including and excluding ‘carnivorous’ taxa (Table 11 and Table 12) to test hypotheses that carnivores should be removed from cenogram analyses (Legendre, 1986; 1989). ‘Carnivores’ were defined as those species exceeding 500g that consume significant quantities of meat. Below 500g faunivorous taxa are principally insectivores. The carnivores excluded from the first dataset were therefore dasyuromorphians and one canid (Canis lupus dingo), as well as more recently introduced species such as Felis catus and Sus scrofa.

Results

Statistically significant relationships, excluding ‘carnivores’, are outlined in Table 11, while those including ‘carnivores’ are provided in Table 12.

Excluding ‘Carnivores’:

The number of species is relatively strongly associated with the size of the gap and the slope of the medium-large species, but not nearly as strong an association exists with the slope of the small species (Table 11).

Moment statistics The mean (normal) is quite well associated with the size of the gap or offset (r = 0.61) and the vegetation group (r = 0.67), but less well so in relation to climatic

______44 variables. The mean (normal) is not as well correlated with the slope of the small species (r = -0.406) as is the mean (log) (r = 0.63). The latter also exhibits an average negative association with mean minimum temperature (r = -0.51), but is never the less the best temperature determinant. The mean (log) is also the best variable for determining a precipitation-related parameter, in this case mean daily evaporation (r = -0.434), albeit a weak negative association. A poor association was observed between the mean (log and normal) and annual rainfall (r = -0.272 & r = -0.276).

The standard deviation (normal) is also only weakly associated with the climatic variables, and less well than the mean (normal). Standard deviation (normal) is well associated with vegetation group (r = 0.7).

The skewness (normal) is associated quite well with the mean slope of the small species (r = -0.61), while the kurtosis (normal) is only averagely associated with the latter (r = -0.54).

Cenogram variables The mean slope of the small mammals is not well associated with any climatic variable. It does, however, associate reasonably well with mean (log) (r = 0.63) and skewness (normal) (r = -0.61). It also associates averagely with kurtosis (normal) (r = - 0.54). A very weak negative association was observed between the mean slope of the small species and mean temperature (r = -0.279), as well as mean minimum (r = -0.346) and maximum temperature (r = -0.268). The strongest association of any climatic variable with the small mammal gradient is with total annual rainfall, although the correspondence is still particularly weak (r = -0.378).

The mean gradient for the medium-large mammals does not correlate with any climatic variables, and is only reasonably associated with the number of species (r = - 0.62), among the remaining parameters. No association was found between the medium- large gradient and annual rainfall, Martonne’s index of aridity, the relative humidity indices or mean daily evaporation. Indeed, the index of aridity was not associated with

______45 any cenogram parameter, and only poorly with the mean (log) (r = 0.271) among moment statistics.

A weak positive relationship exists between the difference in small and large mammal slopes and annual rainfall (r = 0.39).

The size of the cenogram ‘gap’ was found to be reasonably well associated with vegetation structure (r = 0.61). However, the moment statistics, mean (normal) and standard deviation (normal) seem to be better determinants of vegetation structure (r = 0.67 and 0.7 respectively). The size of the offset is also reasonably well associated with the mean (normal) (r = 0.61) and to a greater degree, albeit it negative, with the number of species (r = -0.66).

Overall there is only a marginal difference between association values for the dataset incorporating ‘carnivorous’ taxa (Table 11) and those excluding these species (Table 12). The skewness and kurtosis are less useful for determining vegetation structure with carnivores included than without (Table 11 and Table 12). Variables related to environmental precipitation, such as mean daily evaporation, Martonne’s index of aridity, annual rainfall and mean 9am humidity, appear to be better associated with log-transformed moment statistics such as the mean, standard deviation, skewness and kurtosis, with the inclusion of carnivores (Table 11 and Table 12). Similarly, the temperature-related variables (Mntemp, Mnmintemp and Mnmaxtemp) generally exhibit higher association values overall when carnivores are included. In addition, the largest difference between the datasets (including and excluding carnivores) appears to be between the association of variables related to gradient differences of small and medium-large mammals (i.e. Abslpediff and Slpediff). Generally the inclusion of carnivores is related to an increase in association between the absolute gradient difference (of small and medium-large mammals) and other variables, while the exclusion of these species tends to result in an increase in associations with raw gradient difference (Slpediff). Of particular note is the good association of Slpediff and the log- transformed mean (r = -0.7) when carnivores are included, and the very good association

______46 of Slpediff and log-transformed skewness (Skwln = 0.89) when carnivores are excluded. The slope of the large mammals is weakly associated with annual rainfall when carnivorous species are included (Table 12). Associations for all variable pairs are generally stronger when carnivorous taxa are included in the dataset.

Discussion Results from this analysis suggest that moment statistics may be better for determining vegetation structure of mammalian faunas than the ‘gap’ of cenograms. Of course, the advantage of the cenogram methodology is that the gap or openness of the habitat can be roughly determined by visual examination alone. Never the less, a database could be compiled for worldwide faunas which would provide strong empirical evidence for vegetation structure as opposed to tentative qualitative determinations from visual comparison of cenograms. Having said this, it is apparent that the ‘gap’ is reasonably well associated with vegetation structure at least for Australian localities. Wilf et al. (1998) suggested that the size of the gap decreased from ‘woodland’ environments to more open ‘savannah’ environments (contra Legendre, 1986, 1989). This assertion cannot be supported by results determined herein. Although all vegetation categories exhibited wide ranges of gap sizes, the trend was consistently positive between means.

The mean (log) is a better determinant for all temperature variables than the mean slope of the small mammals (which does never the less associate weakly), or any other variable, although the associations are only average at best. Similarly, mean (log) is the best variable for determining precipitation-related parameters, but association values are poor. It can therefore be concluded that neither moment statistics or cenogram variables are very useful for determining any indicator of precipitation and that the mean (log) is only marginally useful for indicating mean minimum temperatures.

Legendre (1986) suggests that the slope for the small species could be an indicator of minimal temperatures. Similarly, Montuire & Desclaux (1997) suggests the

______47 possibility that the gradient of the small mammals in the cenogram is an indicator of ‘temperature’. Morgan et al. (1995) accept that the slope for small mammals varies with mean annual temperature. At no stage do any of these authors suggest that this slope is in anyway related to the openness of the environment. Disregarding this de Bonis et al. (1992) state that “The cenogram shows a steeply inclined slope in its first part and a break for the medium sized species, two conditions which would indicate an open environment”.

Alroy (2000) asserts that much cenogram information is captured by moment statistics: “… skewness indicates higher species richness in either small or large body mass categories, and negative kurtosis indicates the presence of a gap in the medium size range”. Furthermore it is claimed that moment statistics are preferable due to their ease of calculation and greater informative power (Alroy, 2000). While univariate moment statistics may be useful for describing body size distributions their value for determining vegetational and climatic properties of mammalian communities has not been rigorously investigated. No evidence could be found here to confirm a significant association between medium-large body mass variables and skewness. However, skewness (normal) was quite well associated (r = 0.61) with the slope of the small mammals. As the slope is a function of species richness it could be extrapolated that skewness (normal) is also an indicator of the latter. Kurtosis (normal) was found to be associated with the ‘gap’, but only very weakly (r = -0.295). Interestingly, two moment statistics, the mean and standard deviation (normal), not mentioned as determinants of vegetation structure by Alroy (2000), recorded a stronger association with vegetation structure.

Rodriguez (1999) could not find an association between total annual rainfall and any cenogram variable other than the size of the ‘gap’. However, this association was found to be very weak and was deemed to be an artefact of the large sample size alone (Rodriguez, 1999). Results presented herein suggest that only a weak association exists between total annual rainfall and the mean slope of the small mammals (r = -0.378) and slightly stronger with the difference in slopes (r = 0.39). No significant relationship was

______48 found between total annual rainfall and the ‘gap’. Several weak associations were noted between total annual rainfall and various moment statistics, as outlined above.

Rodriguez (1999) found Martonne’s Index of Aridity (IA) was weakly associated with some cenogram parameters. In the present study, no association could be found between IA and any cenogram variable, although an association was observed with the mean (log). The cenogram ‘gap’ was found to be better associated with vegetation structure (r = 0.61) than that noted by Rodriguez (1999; r = 0.24).

Rodriguez (1999) found that the highest association values were found with the slope of the medium to large species (500g to 25kg), than with any other cenogram variables. This is, however, qualified by the observation that visual plots of these relationships appear very weak and non-linear (Rodriguez, 1999).

Although Legendre (1989) notes that it is only the shape of the cenogram that is relevant to interpretations, many authors have attempted to quantify the parameters (e.g. Gingerich, 1989). However, there has been a lack of consistency in defining the cenogram parameters that are being measured. When measuring the slope of ‘large’ mammals, some authors variably use those animals above 500g, between 500g and 5- 6kg, 500g and 8kg, 500g and 10kg and between 500g and 25kg. For instance Legendre (1989) refers to large species as those in excess of 8kg, but ambiguously employs those species in excess of 500g to demonstrate the slope of the large mammals (see Fig 26.5; Legendre, 1989). Wilf et al. (1998) state that the slope of the medium-sized mammals (500g to 10kg) has been related to environmental moisture. Alternatively, Montuire & Desclaux (1997) observe that an abundance of large-sized species, over 8kg, characterizes humid conditions and that a steep slope is associated with arid conditions. Similarly, Morgan et al. (1995) accept that the slope of the large animals corresponds to those in excess of 8kg. Gunnell (1994) identifies drier environments as having a steeper slope for medium to large mammals, defined as those above 500g. Maas & Krause (1994) adopt yet another interpretation, that the significant slope is that for the medium sized mammals from 500g to 8kg. Yet, the most confused approach appears to be that of

______49 de Bonis et al. (1992) who state that the slope of larger mammals is steeper in open environments as there are fewer species, therefore mixing proposed cenogram concepts.

The inconsistency in the use of cenogram rules, as defined by Legendre (1986, 1989), is not confined to discrepancies concerning cenogram slopes and their related interpretations of aridity. The ‘offset’ or ‘gap’ between small and larger mammals, suggested by Legendre (1986, 1989) to relate to the degree of openness of the vegetation, has been construed in many different ways by various authors utilising cenogram methodology. de Bonis et al. (1992) utilise a break in the cenogram curve between 1 and 6 kg as indicative of an open environment. However, both the 1kg and 6kg cut-off points appear arbitrary and without precedent. Maas & Krause (1994) refer to the presence or absence of a break at 500g. Morgan et al. (1995), Montuire & Desclaux (1997), Legendre & Hartenberger (1992) and Gunnell (1994) accept Legendre’s (1986, 1989) assertion that an offset exists in the medium size range, between 500g and 8kg. Others have arbitrarily changed the range of body sizes in which the offset can be located. Ducrocq et al. (1994) reduced the accepted range of the offset to between 500g and 5-6kg. Alternatively, Wilf et al. (1998) increased the range to between 500g and 10kg. These differences do not alter the significance of a gap in the medium size range, but do add to the confusion regarding categorisation of ‘medium’ and ‘large’ species.

Doubts about the empirical basis, as well as the capacity of cenograms to accurately predict climatic and vegetational parameters, have been expressed by previous authors. Maas & Krause (1994) are sceptical of the ecological significance of the ‘breakpoint’ between small and medium sized mammals and believe that any variation may reflect taphonomic or collecting biases as well as real ecological factors. Maas & Krause (1994) therefore use cenogram methodology to compare change or stasis in community structure between faunal zones, and not to infer habitat type. Morgan et al. (1995) adopt cenogram methodology to interpret climate and vegetation, and also to compare mammalian palaeofaunal structure through time, although they too express concerns regarding the construction of cenograms. These problems, not unique

______50 to cenograms among size distribution analyses, include taphonomic biases, the possibility that no modern analogue exists for some extinct biotas, and issues related to time averaging.

Gunnell (1994) does not explicitly express concerns with cenogram methodology, but does emphasize that cenograms reflect regional rather than local conditions, following Legendre (1988) and Legendre & Hartenberger (1992). Gunnell (1997) appears to contradict this by stating that any cenogram patterns are independent of geographic or taxonomic influences. Morgan et al. (1995) provide yet another interpretation, citing various authors as having demonstrated that size distributions of modern mammal faunas are related to climate and vegetation “… at the scale of ecological communities”. Similarly, Legendre and Hartenberger (1992) champion the empirical basis of cenogram methodology, stating that cenogram “…characteristics have been found in faunas from different continents, and are therefore independent of taxonomic composition of the community”.

Of particular concern is the use of modern faunas occupying vast tracts of land, and consequently, a diversity of habitat types and climatic zones. For example, Legendre (1989) recognises a ‘tropical rainforest community’ (citing Tate, 1952) from Cape York Peninsula, Queensland, as one of the modern comparative faunas included in the database. However, Cape York Peninsula comprises an area of over 200,000 km2 containing many ecosystems and highly variable micro-climates across its expanse. At this scale the species-area relationship is likely to have a dramatic effect on the richness of the fauna, and consequently also the cenogramic slope and ‘offset’.

One of the fundamental principles of cenogram methodology is the exclusion of ‘carnivores’ and bats from the curve (e.g. Legendre 1986, 1989; Montuire & Desclaux, 1997). Yet the justification for removing these guilds is ambiguous. Maas & Krause (1994) affirm that carnivorous mammals (including carnivorans, creodonts and mesonychid ‘condylarths’) were removed from their analyses following Legendre (1986), as the body size to molar relationship for extant carnivores differs significantly

______51 from other mammals. Interestingly, one of the two papers cited by Maas & Krause (1994), that being Legendre & Roth (1988), makes no mention of the ‘significant’ difference between the body size/molar relationship of carnivores and other mammals. Instead, Legendre & Roth (1988) is an investigation of relationships within Recent carnivore groups.

Alternatively Montuire & Desclaux (1997) suggest that carnivores and bats are excluded because of their generally poor representation in fossil faunas. Legendre (1986) never explicitly states the reason for excluding carnivores and bats from the cenogram curve. Legendre (1986) refers to Valverde (1964, 1967) as showing that potential prey species tend to be large or small, with predators being intermediate in size. It is stated that species subject to predation were plotted on the cenogram curves, with predatory and flying mammals plotted above and below the main curve (Legendre, 1986.). Yet no further clarification of possible ecological reasons for the exclusion is provided. The rationale for removing ‘carnivores’ and bats from cenograms is possibly alluded to by discussion concerning the under-representation of predators in fossil faunas, supporting the claim of Montuire & Desclaux (1997) (see Legendre, 1986). Similar attention is not, however, given to the taphonomic biases affecting bats. Furthermore, the definition of a carnivore is unclear. Legendre (1986, 1989) consistently refers to predators (sensu Valverde, 1964; 1967) but appears to later identify the trophically diverse carnivorans (distinguished from Creodonts, Perissodactyls, Artiodactyls, Rodents, Primates, Bats, ‘Insectivores’ and Marsupials) in the cenogram keys.

The inclusion of ‘carnivorous’ dasyuromorphians and the dingo (Canis lupus dingo) in the datasets made no significant difference to results. The relationship between some moment statistics and vegetation groups decreases, while association values for the former and indices of precipitation increase slightly. Generally weak associations between temperature-related variables and other parameters form, or increase, when carnivores are included. It is interesting that an association, albeit very weak, was found between the slope of medium-large mammals and annual rainfall with the inclusion of

______52 carnivores. Surprisingly the majority of association values are greater when carnivorous taxa are included. This result, combined with ambiguous justifications for excluding carnivores (e.g. Legendre, 1986; 1989; Montuire & Desclaux, 1997), as well as difficulties in defining ‘carnivores’, indicates that the removal of carnivores from body size analyses is superfluous, at least for Australian datasets.

Another tenet of the cenogram method is the constancy of the small and medium- large mammal slopes in ‘humid’ or low aridity areas. Legendre (1986) notes that slopes are constant for his sample for small species (<500g) and that gradients for larger species (>500g) are more variable. According to Legendre (1986, 1989) and Montuire & Desclaux (1997) the greater the discrepancy in the slopes between the two size categories, the more arid the environment. However, this study cannot corroborate this conclusion. Indeed results presented here confirm the converse that the difference in slope gradients (not absolute values) increases with increasing total annual rainfall. There also seems to be some confusion as to whether the gradient for medium-large mammals is large in arid areas or whether a change in slope is adequate.

The acceptance by all authors of the adequacy of the lower first molar as an indicator of body-size, is a major concern. This dental predictor can produce wildly inaccurate and imprecise body size predictions, despite apparently high coefficients of correlation (see Chapter Two). The first lower molar is typified by high percent prediction errors and standard errors that vary dramatically in, and between, taxonomic groups, and is one of the least accurate dental predictors, at least for marsupials. Variation between cenogram slopes could well be merely the result of variation in body weight predictions, between authors and specimens employed.

This analysis suggests that no cenogram variable (sensu Legendre, 1986, 1989) is particularly useful for determining climatic variables. Nevertheless, support was found for the assertion of Legendre (1986, 1989) that a gap or ‘offset’ between small and medium sized mammals (>500g) is related to the ‘openness’ of the vegetation (Spearman’s r = 0.6). Although this relationship is reasonably strong the usefulness of

______53 the ‘gap’ is diminished, given that at least two moment statistics (normal standard deviation and mean) are significantly better determinants. The gradient of the medium- large mammals (>500g) was not found to be associated with any indicator of aridity as suggested by Legendre (1986) or any other climatic variable. The slope of the small mammals was found to be weakly associated with mean minimum, mean maximum and mean temperature. The strongest of these associations was with mean minimum temperature, thus providing extremely tentative support for the contention that small mammal gradients indicate minimal temperatures (Legendre, 1986) or ‘temperature’ in general (Montuire & Desclaux, 1997). Interestingly, the strongest association between the slope of the small mammals and a climatic variable was with total annual rainfall, although this was again very weak (r = -0.378). Rodriguez (1999) could not find any association between the slope of the micro-mammals (<500g) and ‘mean annual temperature’, although the latter did appear to associate weakly with other cenogram variables.

The best approach may be to develop discriminant function analysis databases incorporating cenogram variables and body-size moment statistics, as well as other potentially informative parameters such as species-richness, for extant faunas from each continent. Such a database of cenogram parameters already exists for many regions of the world (i.e. Legendre, 1989) and moment statistics could easily be determined from these data. In addition Australian data presented here could be included in this worldwide database. These databases would incorporate the most useful cenogram and moment statistic variables.

The consequences of misinterpreting palaeoenvironmental parameters, through the use of flawed cenogram ‘rules’, is no trivial matter. Of particular concern is the apparent trend to accept the results of cenogram analyses and rationalise previous, disparate palaeoenvironmental findings. For example, Morgan et al. (1995) summarise cenograms from the Paleogene of the U.S.A and Neogene sites from Pakistan. They conclude that the cenogram results for the Paleogene are generally congruent with palaeoenvironmental interpretations derived from trophic structure and palaeofloral data,

______54 with the exception of those from the Wasatchian. The authors suggest that the differences may be due to discrepancies in the time intervals represented by the samples, poor matches between modern analogues and fossil faunas, and the fact that the some cenograms were derived from just the one quarry (Morgan et al.,1995). At no stage is it suggested that the cenogram methodology may be flawed.

Of equal concern is the trend to over-analyse the results of the cenogram analysis. The original use of cenograms, as defined by Legendre (1986, 1989), involved the identification of possible modern palaeoenvironmental analogues, as well as interpretations of the relative openness of the vegetation, the relative humidity and possibly some indication of minimum annual temperatures. Yet some authors appear to interpret more than mere generalisations about the palaeoenvironment. Morgan et al. (1995), for instance, conclude that “…low slopes for the small species in … Paleogene cenograms suggest tropical to subtropical annual temperatures and winters without frost”, and for the Neogene cenograms that “ The increase in slope for small species suggests a slight decrease in mean annual temperature, but not freezing winters”. Likewise, Ducrocq et al. (1994) appear to overstep the boundaries of cenogram interpretation, concluding for middle Miocene Thailand faunas that “…the relative abundance of large and small species is indicative of a quite high average temperature”.

It is unclear if differences in the degree of association between cenogram variables and environmental parameters found herein, and those observed by Rodriguez (1999), are due to inter-continental factors. Of the 92 recent mammalian faunas used by Rodriguez (1999) none are Australian. Likewise, inter-continental differences may account for discrepancies between moment statistic relationships observed herein and those of Alroy (2000). For instance, Alroy (2000) mentions that Recent North American assemblages usually include more than 20 terrestrial species and up to 42 species in South American faunas such as the Amazon, while only 14% of fossil faunas in the North American database employed included more than 10 identified species. For the 118 Recent Australian faunas employed herein the average number of terrestrial mammalian species was 11, with only 8 faunas (7%) having more than 20 species

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(although the habitat-specific nature of these ‘faunas’ may have reduced overall species richness). In addition, of the 14 Australian fossil faunas utilised the average number of terrestrial mammal species was 27, with 12 local faunas (86%) possessing greater than 10 species. Furthermore, Alroy (2000) argues that the mammalian body mass spectrum was not nearly filled during the early and arguably even middle Tertiary, thereby affecting comparisons of Recent and fossil cenograms. While this is probably true of Australian early Tertiary faunas (Palaeocene and Eocene) and possibly the early middle Tertiary (early-middle Oligocene), it is uncertain whether this assertion applies to the late middle Tertiary (late Oligocene to early Miocene) of Australia. For although the late Oligocene White Hunter local fauna, as well as constituent local faunas of the early Miocene Nambaroo-Balbaroo local fauna (see Chapters Six & Nine), possess terrestrial marsupials encompassing a range of body weights, from 13g acrobatids to diprotodontoids weighing in excess of 100kg, there are intervals devoid of species that are today filled. In particular the range from 20-90kg is rarely occupied by medium- large carnivores (e.g. Wakaleo sp.) in fossil faunas, but is more commonly filled by larger macropodid and vombatid species in Recent Australian faunas.

Table 9: Variables used in analysis

Variable Abbreviation Description

Number of species #spp. Number of mammal species in habitat-specific fauna

Mean (normal) Mnnrm The arithmetic mean of the body-size distribution

Standard deviation Stdvnrm The standard deviation of the body-size distribution (normal) Skewness (normal) Skwnrm The skewness of the body-size distribution

Kurtosis (normal) Krtnrm The kurtosis of the body-size distribution

Mean (log natural) Mnln The geometric mean of the log-natural body-size distribution Standard deviation Stdvnln The standard deviation of the log-natural body-size (log natural) distribution Skewness (log Skwln The skewness of the log-natural body-size distribution natural) Kurtosis (log natural) Krtln The kurtosis of the log-natural body-size distribution

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Variable Abbreviation Description

Size of ‘gap’ (log Szgap500 The size (in natural log units) of the cenogramic gap (or natural) offset) between small & medium sized mammals Number of gaps #gaps The number of cenogramic gaps in the body-size (>0.5 ln) distribution greater than 0.5 natural log units Minimum slope of the Minsmlslpe The minimum slope (or gradient) of the small (<500g) small mammals mammals in the log-natural body-size distribution; allowing for error range Maximum slope of Maxsmlslpe The maximum slope of the small mammals in the log- the small mammals natural body-size distribution Mean slope of the Mnsmlslpe The geometric mean slope of the small mammals in the small mammals log-natural body-size distribution Minimum slope of the Minslpe>500 The minimum slope (or gradient) of the medium-large medium-large (>500g) mammals in the log-natural body-size mammals distribution; allowing for error range Maximum slope of Maxslpe>500 The maximum slope of the medium-large mammals in the medium-large the log-natural body-size distribution mammals Mean slope of the Mnslpe>500 The geometric mean slope of the medium-large medium-large mammals in the log-natural body-size distribution mammals Difference in slopes Slpediff The difference in gradients between the medium-large and small mammals in the log-natural body-size distribution Absolute difference Abslpediff The absolute difference in gradients between medium- in slopes large and small mammals in the log-natural body-size distribution Mean minimum Mnmintemp The mean minimum temperature (deg C) recorded at temperature the nearest Bureau of Meteorology station Mean maximum Mnmaxtemp The mean maximum temperature recorded at the temperature nearest Bureau of Meteorology station Mean temperature Mntemp The mean temperature recorded at the nearest Bureau of Meteorology station Mean annual rainfall Annrnfll The mean annual rainfall (mm) recorded at the nearest Bureau of Meteorology station Mean daily MnDevap The mean daily evaporation (mm) recorded at the evaporation nearest Bureau of Meteorology station Mean 9am relative Mn9relhum The mean relative humidity (%) recorded at 9am at the humidity nearest Bureau of Meteorology station Mean 3pm relative Mn3relhum The mean relative humidity recorded at 3pm at the humidity nearest Bureau of Meteorology station Martonne’s Index of IndexA Martonne’s aridity index (IA); IA=P/T + 10; where Aridity P=annual rainfall and T=mean annual temperature; the lower the value the drier the environment (following Rodriguez, 1999).

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Table 10: Extant fauna data utilised in analysis

Vegetation Bureau of Met Locality Vegetation structures Source category Station Naringal, VIC Dense Forest 2 Terang - 090077 1 Royal National Park, Tall Open Forest 3 Lucas Heights

NSW (ANSTO) – Woodland 4 066078 Lower Gordon River Closed Forest 1 Region, South-west Low Closed Forest 1 Strathgordon Tasmania Open Forest 3 2 Village – 097053 Tall Woodland 4 Open scrubland 3 Bondi State Forest, Dry Open Forest 3 (from paper) 3 NSW Moist Open Forest 2 Stockyard Ck., Open Forest 3 Coolangubra State Tall Open Forest 3 Bombala Post 4 Forest, NSW Woodland/swampland 4 Office – 070005 Shrubland 4 Brother State Forest, Closed Forest 1 NSW Wet Sclerophyll Forest 2 Glen Innes (Mt Dry Sclerophyll Forest 3 Mitchell) – 5 Woodland 4 057082 Forested Grassland 5 Clouds Creek, N.E. Closed Forest 1 NSW Tall Open Forest 3 Clouds Ck State 6 Open Forest 3 Forest – 059008 Woodland 4 Grassland 5 Kinglake, VIC. Wet Open Forest 2 Dry Open Forest 3 Mt St Leonards – 7 Woodland 4 086142 Grassy Forest 5 Dartmouth Dam, NE Moist Open Forest 2 Dartmouth 8 VIC Reservoir – Dry Open Forest 3 082076 Kakadu National Monsoon Rainforest 1 Jabiru Airport - Park, N.T. Open Forest 3 014198 9 Savannah Woodland 5 Tanami Desert Rabbit Flat – Desert 5 9 015666

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Vegetation Bureau of Met Locality Vegetation structures Source category Station Greater Simpson Desert 5 (from paper) Desert 9 Mitchell Plateau, Woodland 4 (from paper) 10 W.A. Cooloolah, QLD Closed Forest 1 Double Island Point lighthouse - 11 Open Forest 3 040068

Beerwah, QLD Crohamhurst – Open Forest 3 11 040062 Drysdale River, W.A. Low Open Forest 3 Low Open Woodland 5 (from paper) 12 Low Woodland 4 Closed Forest 1 Karroun Hill, W.A. Tall Shrubland 4 Bencubbin – 13 Open Woodland 5 010007 Queen Victoria State Cundalee, Nature Reserve, Open Woodland 5 Kalgoorlie & 14 W.A Rawlinna Butterleaf State Closed Forest 1 Forest, NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodland 4 Forested Grassland 5 Curramore State Closed Forest 1 Forest, NSW Wet Sclerophyll 2 Dry Sclerophyll 3 (from paper) 5 Woodland 4 Forested Grassland 5 London Bridge State Closed Forest 1 Forest, NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodland 4 Forested Grassland 5 Oakwood State Closed Forest 1 Forest, NSW Wet Sclerophyll Forest 2 5 Dry Sclerophyll Forest 3 (from paper)

Woodland 4 Forested Grassland 5 Torrington State Closed Forest 1 Emmaville & Mt 5 Forest, NSW Wet Sclerophyll Forest 2 Mitchell - 056009

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Vegetation Bureau of Met Locality Vegetation structures Source category Station Dry Sclerophyll Forest 3 Woodland 4 Forested Grassland 5 Binghi State Forest, Closed Forest 1 NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodlands 4 Forested Grassland 5 Warra State Forest, Closed Forest 1 NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodlands 4 Forested Grassland 5 Gibraltar Range Closed Forest 1 National Park, NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodlands 4 Forested Grassland 5 Washpool National Closed Forest 1 Park, NSW Wet Sclerophyll Forest 2 Dry Sclerophyll Forest 3 (from paper) 5 Woodland 4 Forested Grassland 5 Mann River Nature Wet Sclerophyll Forest 2 (from paper) 5 Reserve, NSW Dry Sclerophyll Forest 3 Glen Nevis State Wet Sclerophyll Forest 2 Forest, NSW Dry Sclerophyll Forest 3 (from paper) 5 Woodlands 4 Forested Grassland 5 Myanba Ck Bombala P.O & Tall Open Forest 3 15 catchment, NSW paper Atherton Uplands, Closed Forest 1 Atherton 16 Wet Tropics Bellenden-Ker, Wet Kairi Research Closed Forest 1 16 Tropics station – 031034 Bloomfield- Cooktown – Helenvale Lowlands, Closed Forest 1 16 031072 Wet Tropics Cairns-Cardwell Cooktown – Lowlands, Wet Closed Forest 1 16 031072 Tropics

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Vegetation Bureau of Met Locality Vegetation structures Source category Station Townsville Lowlands, Wet Closed Forest 1 Townsville 16 Tropics Windsor Uplands, Butcher’s Hill Closed Forest 1 16 Wet Tropics Station – 039018 Seven Mile Beach, Open Forest 3 Nowra Council – 17 NSW Littoral Rainforest 1 068105 Lower Burdekin, N. Open Forest 3 Millaroo – 18 QLD Closed Forest 1 033090 Port Essington, N.T. Tall Open Forest 3 Cape Don - Woodlands 4 014008 19 Monsoon Rainforest 1 Stanthorpe Shire, Stanthorpe – Open Forest 3 20 S.E.QLD 041095 Nalbaugh State Wet Sclerophyll Forest 2 Nalbaugh State 21 Forest, SE NSW Dry Sclerophyll Forest 3 Forest – 041095 Moeyan Hill, NSW Nowra Council – Wet Sclerophyll Forest 2 18 068105 Murray Scrub, NSW Urbenville SF – Closed Forest 1 22 057021 Bungdoozle, NSW Urbenville SF – Closed Forest 1 22 057021 Cambridge Plateau, Urbenville SF - Closed Forest 1 22 NSW 057021 Veg. categories: 1 = ‘closed forest / rainforest’; 2 = ‘wet forest / wet open forest / forest / wet sclerophyll’; 3 = ‘dry open forest / open forest / dry sclerophyll’; 4 = ‘woodland’ 5 = ‘open woodland / forested grassland’ Source 1. Bennett (1990) 12. Kabay & Burbidge (1977) 2. Hocking and Guiler (1983) 13. Youngson & McKenzie (1977) 3. Fanning & Mills (1989) 14. Burbidge et al. (1976) 4. Fanning & Mills (1991) 15. Fanning & Mills (1990) 5. Smith, Moore & Andrews (1992) 16. Williams et al. (1996) 6. Barnett et al. (1976) 17. Murphy (1998) 7. Nicol (1978) 18. Lavery & Johnson (1974) 8. Thomas & Gilmore (1976) 19. Frith and Calaby 1974 9. Woinarski et al. (1992) 20. Kirkpatrick & Searle (1977) 10. Kitchener et al. (1981) 21. Binns & Kavanagh (1990) 11. Dwyer et al. (1979) 22. Barker et al. (1994)

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Table 11: Associated variables (excluding 'carnivores')

Variable Associated variable Spearman’s r Probability Vegetation group #spp. -0.281 0.002 Mnnrm 0.67 <<0.05 Stdvnrm 0.7 <<0.05 Skwnrm -0.4 <<0.05 Krtnrm -0.38 <<0.05 Mnln 0.44 <<0.05 Szgap500 0.61 <<0.05 #gaps -0.231 0.012 Mn3relhum -0.205 0.041 #spp. Mnnrm -0.35 <<0.05 Stdvnrm -0.31 <<0.05 Skwnrm 0.39 <<0.05 Krtnrm 0.3 <<0.05 Mnln -0.33 <<0.05 Krtln 0.32 <<0.05 Szgap500 -0.66 <<0.05 #gaps 0.66 <<0.05 Mnsmlslpe -0.295 0.014 Mnslpe>500 -0.62 <<0.05 Slpediff -0.256 0.037 MnDevap 0.39 0.044 Mntemp 0.222 0.016 Mnmintemp 0.256 0.005 Mnmaxtemp 0.219 0.017 Mnnrm Szgap500 0.61 <<0.05 #gaps -0.219 0.017 Mnsmlslpe -0.406 <<0.05 Slpediff -0.316 0.009 Annrnfll -0.276 0.003 Mntemp -0.32 <<0.05

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Variable Associated variable Spearman’s r Probability Stdvnrm Mnsmlslpe 0.29 0.016 Szgap500 0.6 <<0.05 Mnslpe>500 0.19 0.042 Annrnfll -0.22 0.017 Mn3relhum -0.248 0.013 Mntemp -0.201 0.029 Mnmintemp -0.225 0.015 Skwnrm Szgap500 -0.35 <<0.05 #gaps 0.21 0.023 Mnsmlslpe -0.61 <<0.05 Slpediff 0.5 <<0.05 Annrnfll 0.246 0.007 Mntemp 0.32 <<0.05 Krtnrm Szgap500 -0.295 0.001 Mnsmlslpe -0.54 <<0.05 Slpediff 0.43 <<0.05 Annrnfll 0.217 0.019 Mntemp 0.284 0.002 Mnln Szgap500 0.45 <<0.05 #gaps -0.287 0.002 Mnsmlslpe 0.63 <<0.05 Maxslpe>500 -0.185 0.048 Mnmintemp -0.51 <<0.05 Mnmaxtemp -0.39 <<0.05 Annrnfll -0.272 0.003 MnDevap -0.434 0.024 Mntemp -0.41 <<0.05 IndexA 0.271 0.003 Stdvnln #gaps 0.42 <<0.05 Minsmlslpe 0.312 0.009 Mnslpe>500 0.293 0.002 Mnmintemp 0.185 0.045

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Variable Associated variable Spearman’s r Probability Mn3pmhum -0.36 <<0.05 Skwln #gaps -0.276 0.003 Mnsmlslpe -0.65 <<0.05 Mnslpe>500 0.31 <<0.05 Slpediff 0.89 <<0.05 Mnmintemp 0.268 0.003 Mnmaxtemp 0.252 0.006 Mntemp 0.262 0.004 Annrnfll 0.288 0.002 Krtln Mnslpe>500 -0.36 <<0.05 Slpediff -0.331 0.006 Abslpediff 0.264 0.031 Szgap500 #gaps -0.55 <<0.05 Mnslpe>500 0.33 <<0.05 Slpediff 0.241 0.05 Mnmintemp -0.201 0.029 #gaps Mnsmlslpe 0.331 0.006 Mnslpe>500 -0.246 0.008 Slpediff -0.44 <<0.05 Mnsmlslpe Mnmintemp -0.346 0.004 Mnmaxtemp -0.268 0.026 Annrnfll -0.378 0.001 Mntemp -0.279 0.02 Slpediff -0.75 <<0.05 Mnslpe>500 Slpediff 0.73 <<0.05 Abslpediff 0.41 <<0.05 Slpediff Mnmintemp 0.249 0.043 Annrnfll 0.39 0.001 Abslpediff Annrnfll 0.261 0.033

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Table 12: Associated variables (including carnivores)

Variable Associated variable Spearman’s r Probability Vegetation group #spp. -0.32 <<0.05 Mnnrm 0.66 <<0.05 Stdvnrm 0.7 <<0.05 Skwnrm -0.185 0.045 Mnln 0.42 <<0.05 Szgap500 0.63 <<0.05 #gaps -0.298 0.001 Abslpediff 0.314 0.01 Mn3hum -0.205 0.041 #spp. Mnnrm -0.43 <<0.05 Stdvnrm -0.33 <<0.05 Skwnrm 0.48 <<0.05 Krtnrm 0.41 <<0.05 Mnln -0.37 <<0.05 Krtln 0.31 <<0.05 Szgap500 -0.69 <<0.05 #gaps 0.67 <<0.05 Mnsmlslpe -0.276 0.022 Mnslpe>500 -0.65 <<0.05 Slpediff -0.259 0.035 MnDevap 0.392 0.043 Mntemp 0.226 0.014 Mnmintemp 0.242 0.008 Mnmaxtemp 0.222 0.016 Mnnrm Szgap500 0.64 <<0.05 #gaps -0.32 <<0.05 Mnsmlslpe 0.48 <<0.05 Slpediff -0.307 0.012 Abslpediff 0.295 0.016 Annrnfll -0.29 0.002

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Variable Associated variable Spearman’s r Probability Mntemp -0.33 <<0.05 Mnmintemp -0.38 <<0.05 Mnmaxtemp -0.31 <<0.05 Stdvnrm Mnsmlslpe 0.291 0.016 Szgap500 0.59 <<0.05 #gaps -0.19 0.039 Annrnfll -0.208 0.024 Mn3relhum -0.248 0.013 Mnmintemp -0.19 0.039 Skwnrm Szgap500 -0.33 <<0.05 #gaps 0.294 0.001 Mnsmlslpe -0.53 <<0.05 Minslpe>500 -0.184 0.049 Maxslpe>500 -0.186 0.046 Slpediff 0.298 0.015 Abslpediff -0.318 0.009 Annrnfll 0.234 0.011 Mnmintemp 0.44 <<0.05 Mnmaxtemp 0.41 <<0.05 Mntemp 0.42 <<0.05 Krtnrm Szgap500 -0.257 0.005 #gaps 0.222 0.016 Mnsmlslpe -0.48 <<0.05 Abslpediff -0.314 0.01 Annrnfll 0.212 0.021 Mntemp 0.38 <<0.05 Mnmintemp 0.38 <<0.05 Mnmaxtemp 0.37 <<0.05 Mnln Szgap500 0.47 <<0.05 #gaps -0.37 <<0.05 Mnsmlslpe 0.62 <<0.05 Slpediff -0.7 <<0.05

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Variable Associated variable Spearman’s r Probability Abslpediff 0.315 0.01 Mnmintemp -0.55 <<0.05 Mnmaxtemp -0.41 <<0.05 Annrnfll -0.282 0.002 MnDevap -0.567 <<0.05 Mntemp -0.43 <<0.05 IndexA 0.273 0.003 Stdvnln #gaps 0.4 <<0.05 Minsmlslpe 0.276 0.022 Mnslpe>500 0.297 0.001 Slpediff -0.213 0.021 Mndevap 0.404 0.037 Mnmintemp 0.205 0.026 Mn3hum -0.38 <<0.05 Skwln Abslpediff -0.303 0.013 Mnsmlslpe -0.66 <<0.05 Mnslpe>500 0.31 <<0.05 Abslpediff -0.3 <<0.05 Mnmintemp 0.39 <<0.05 Mnmaxtemp 0.34 <<0.05 Mntemp 0.35 <<0.05 Annrnfll 0.3 <<0.05 Mndevap 0.44 0.022 indexA -0.206 0.025 Krtln Mnslpe>500 -0.48 <<0.05 Mnsmlslpe 0.366 0.002 Szgap500 -0.196 0.034 Slpediff -0.66 <<0.05 Abslpediff 0.378 0.002 #gaps 0.238 0.01 Annrnfll -0.188 0.043 Mndevap 0.495 0.009

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Variable Associated variable Spearman’s r Probability Mn9hum -0.249 0.011 Szgap500 #gaps -0.57 <<0.05 Mnslpe>500 0.283 0.002 Mnmintemp -0.268 0.003 Mnmaxtemp -0.196 0.034 Mntemp -0.219 0.017 indexA 0.192 0.037 #gaps Mnsmlslpe 0.289 0.016 Mnslpe>500 -0.224 0.016 Slpediff -0.372 0.002 Mnmintemp 0.201 0.029 Mnsmlslpe Mnmintemp -0.346 0.004 Mnmaxtemp -0.268 0.026 Mntemp -0.279 0.02 Annrnfll -0.378 0.001 Slpediff -0.80 <<0.05 Abslpediff 0.42 <<0.05 Mnslpe>500 Slpediff 0.7 <<0.05 Annrnfll 0.224 0.016 Slpediff Abslpediff -0.245 0.043 Mnmintemp 0.352 0.004 Annrnfll 0.45 <<0.05 Mntemp 0.253 0.039

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Figure 3: Cenogramic curve (from Valverde, 1964)

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Chapter 4 A discriminant function analysis of recent and fossil Australian faunas

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A Discriminant Function Analysis of Recent and Fossil Australian faunas

Introduction Independently, the majority of cenogram and moments statistics appear to be largely inadequate for determining palaeoenvironmental parameters from body size distributions (see Chapter Three). However, used in conjunction these variables may have more utility. To test this hypothesis, and in order to determine possible palaeo- habitat information (primarily vegetation structure), discriminant function analyses were performed. Kappelman et al. (1997) undertook similar analyses, using bovid femoral variables in a discriminant function analysis, to indicate palaeo-habitats for Plio- Pleistocene sites in East Africa.

Discriminant Function Analysis (DFA) attempts to maximise the separation between samples and also allows for new cases to be assigned to established groups (Harper & Owen, 1999). The discriminant function is determined by orienting clusters, or samples, in multidimensional space until they exhibit maximum geometric separation (Davis, 1986; cited in Harper & Owen, 1999). Effectively cases are assigned to predefined groups by determining linear or quadratic functions of variables that best separate them, and their placement is tested using Hotelling’s T2, the multivariate equivalent of Student’s t-test (SYSTAT; Harper & Owen, 1999.). The Mahalanobis distance is used to determine the separation between clusters, and to provide posterior probabilities for classifying cases into a priori groupings (ibid.). Cases with missing data, for any variable analysed, are not included in the DFA.

Methods The cenogram, body size moment statistic, species richness and vegetation structure variables previously identified for 118 Recent Australian faunas (Chapter Three) were used in a discriminant function analysis (DFA). The climatic variables were excluded. The objective of the DFA was to attempt to classify the 118 faunas into one of

______71 the five a priori vegetation groupings (refer to Chapter Three). In addition two other variables, relating to potential cenogramic ‘gaps’ at 3kg and 3.5kg body size distributions, were included in the analyses. DFA’s were run including all variables and another excluding variables associated with small mammal slopes (Mnsmlslpe, Minsmlslpe and Maxsmlslpe) and the difference between small and medium-large mammal gradients (Slpediff & Abslpediff).

Jackknifed classification matrices were also produced from the original DFA data matrices. Jackknifing is a method similar to bootstrapping whereby numerous sample subsets of n-1 size are produced from the original datasets and re-analysed (Carlson, 1999). Classifications that recur in the jackknifed results add weight to classifications resulting from the original data.

In addition 12 of the 14 Oligo-Miocene local faunas (LF’s) from Riversleigh being studied herein were included in the DFA. Hiatus and Keith’s Chocky Block LF’s were excluded from the DFA due to low sample sizes (only 9 and 10 marsupial species known respectively). For fossil species body-mass was determined from the ‘best’ cranio-dental variables, depending on the specimen employed (see Chapter Two). Posterior probabilities and Mahalanobis distances were used to place the fossil local faunas within one of the five vegetation groupings.

Legendre (1986, 1989) has suggested that carnivores should be removed from cenograms (refer to Chapter Three). As the DFA’s incorporate cenogram variables both DFA’s were run inclusive and exclusive of ‘carnivorous’ taxa, to further analyse the effect of removing this trophic group. As for Chapter Three, ‘carnivores’ were defined as those species exceeding 500g and incorporating significant quantities of meat into their diet.

To facilitate classification large diprotodontoid species were removed from the fossil local faunas, where necessary. In the extant Australian faunas the largest species is Macropus rufus (the Red Kangaroo) with an average body weight of about 66kg for the male. Any fossil species larger than 66kg was therefore removed from the analysis, as

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very large species could disproportionately skew body weight distributions, thereby disallowing classification of fossil local faunas when compared to extant faunas with less variable body weight ranges.

Results

1) Discriminant Function Analysis including all variables Only 67 faunas, excluding the additional fossil faunas, were included in the analysed matrix as the remaining faunas had missing data. The mean gradient of the small mammals (Mnsmlslpe), the mean gradient of the medium-large mammals (Mnslpe>500) and the difference between the former two (Slpediff), were found to be redundant and excluded by the discriminant function.

The size of the cenogramic ‘gap’ (szgap500) was identified as the most useful variable in the discriminant function, followed closely by the size of the gap at 3.5kg (szgap3.5kg) and the normal mean (Mnnrm).

The classification was reasonably successful with an average correct classification of 79% (Table 13; Figure 4). The open woodland category was the most successful, with all cases being correctly grouped. The dry open forest category was the least successful with 70% of cases being correctly classified. A jackknifing matrix was also produced to test the reliability of the classification figures. After jackknifing the average correct classification had dropped to 46%. The wet forest classifications are the most reliable with 62% of cases correctly grouped after jackknifing. The woodland values are the least supportable, with no cases being correctly classified after jackknifing (Table 14).

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Table 13:Classification matrix (cases in row categories classified into columns)

Vegetation 1 2 3 4 5 %correct categories

1 17 2 0 2 1 77

2 0 12 1 0 0 92

3 1 1 14 4 0 70

4 1 1 0 5 0 71

5 0 0 0 0 5 100 1 = ‘closed forest’; 2 = ‘wet forest’; 3 = ‘dry open forest’; 4 = ‘woodland’; 5 = ‘open woodland’

Table 14: Jackknifed classification matrix

Vegetation 1 2 3 4 5 %correct categories

1 13 4 0 4 1 59

2 1 8 4 0 0 62

3 2 2 7 7 2 35

4 2 2 3 0 0 0

5 1 0 0 1 3 60

The first resultant eigenvector accounted for 42% of the total dispersion, the second eigenvector another 36% and the third another 17%.

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Canonical Scores Plot

FACTOR(1) FACTOR(2) FACTOR(3)

FACTOR(1) FACTOR(1) FACTOR(1) FACTOR(1) FACTOR(1)

FACTOR(1)

FACTOR(2) FACTOR(2) FACTOR(2) FACTOR(2) FACTOR(2)

FACTOR(2) VEGGROUP

FACTOR(3) FACTOR(3) FACTOR(3) FACTOR(3) FACTOR(3) 5 1 4 3

FACTOR(3) 2 FACTOR(1) FACTOR(2) FACTOR(3)

Figure 4: Canonical scores plot for DFA utilising 67 extant Australian faunas (derived from Table 10) and all variables

Vegetation groups: 1 = ‘closed forest’; 2 = ‘wet forest’; 3 = ‘dry open forest’; 4 = ‘woodland’; 5 = ‘open woodland’

The DFA classified the White Hunter Local Fauna (WH LF), in order of increasing ‘openness’ of the vegetation, as: 1) closed forest (p = 0.02); 2) dry open forest (p = 0.01); and 3) open woodland (p = 0.97). For the WH LF to be classified by the DFA it is necessary to remove the large outlier diprotodontoids from the data-set.

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The Last Minute Local Fauna (LM LF) was classified as closed forest (p = 0.08) and wet forest (p = 0.92).

The Neville’s Garden Local Fauna (NG LF) cannot be classified when large diprotodontids are included in the data. The removal of these outliers allows for classification of NG LF as closed forest (p = 0.15) and wet forest (p = 0.84).

The Cleft-Of-Ages Local Fauna (COA LF) is classified by the DFA as dry open forest (p = 1.0).

The Wayne’s Wok (WW LF), Upper (UP LF), and Camel Sputum (CS LF) Local Faunas, cannot be classified with any extant vegetation structure, even with large diprotodontid outlier species removed.

The Mike’s Menagerie Local Fauna (MM LF) grouped with wet forest communities (p = 1.0) with diprotodontids removed. MM LF cannot be grouped by the DFA when diprotodontids are included.

The Ringtail Local Fauna (Ring LF) grouped with closed rainforest communities (p = 0.37), with wet forest (p =0.6), and with dry open forest and woodland environments (p = 0.01 for each).

The late Miocene Encore Local Fauna (Encore LF) was classified as closed forest (p = 0.03), dry open forest (p = 0.16), woodland (p = 0.79) and open woodland (p = 0.02).

Removing large diprotodontid outliers results in the Gag Local Fauna (Gag LF) grouping with wet forest (p = 0.99).

The Henk’s Hollow Local Fauna (HH LF) is classified as wet forest (p = 0.99) and dry open forest (p = 0.01), with outlier species removed.

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2) Discriminant Function Analysis (excluding Minsmlslpe, Maxsmlslpe, Mnsmlslpe, Slpediff and Abslpediff)

114 faunas were analysed by this DFA, excluding the fossil faunas. As in the first DFA the mean gradient of the medium-large mammals was found to be superfluous. The size of the ‘gap’ was also again found to be the most influential variable in the discriminant function, followed by the number of gaps in the distribution (>0.5 log units), and then the size of the gap at 3.5kg.

The classification results were less successful on average than for the dataset including all variables, with an average of 73% of faunas correctly assigned, as opposed to 79% in the latter (Table 15; Figure 5). The most successful classifications were with the ‘wet forest’ vegetation category, with 83% of faunas correctly grouped. The least successful grouping was for the ‘woodland’ category, with a success rate of 65%. The jackknifing results for this dataset were, however, far better than for the first DFA. The jackknifed matrix correctly assigned 60% of faunas on average, as opposed to only 46% for the inclusive dataset (Table 16). The jackknifed matrix suggests that the most reliable classification results occur within the ‘wet forest’ category, with 72% of cases correctly assigned, while the least reliable are the ‘woodland’ faunas with 50% of faunas grouped accurately. These results are far better than those determined for the inclusive dataset.

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Table 15: Classification matrix (cases in row categories classified into columns)

Vegetation category 1 2 3 4 5 %correct

1 20 3 2 1 1 74

2 0 15 2 1 0 83

3 2 2 22 5 1 69

4 3 1 1 13 2 65

5 1 0 1 2 13 76

1 = ‘closed forest’; 2 = ‘wet forest’; 3 = ‘dry open forest’; 4 = ‘woodland’; 5 = ‘open woodland’

Table 16:Jackknifed classification matrix

Vegetation category 1 2 3 4 5 %correct

1 16 6 2 2 1 59

2 0 13 4 1 0 72

3 3 3 17 8 1 53

4 3 2 3 10 2 50

5 1 0 3 1 12 71

The first eigenvalue, or factor, accounts for about 60% of the total variance, the second for about 26% and the third for just 10% of total dispersion.

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Canonical Scores Plot

FACTOR(1) FACTOR(2) FACTOR(3)

FACTOR(1) FACTOR(1) FACTOR(1) FACTOR(1) FACTOR(1)

FACTOR(1)

FACTOR(2) FACTOR(2) FACTOR(2) FACTOR(2) FACTOR(2)

FACTOR(2) VEGGROUP

FACTOR(3) FACTOR(3) FACTOR(3) FACTOR(3) FACTOR(3) 5 1 4 3 FACTOR(3) 2 FACTOR(1) FACTOR(2) FACTOR(3)

Figure 5: Conical scores plot for DFA with 114 extant Australian faunas (derived from Table 10), excluding small-mammal slope and gradient difference variables

Vegetation structure groups: 1 = ‘closed forest’; 2 = ‘wet forest’; 3 = ‘dry open forest’;4 = ‘woodland’; 5 = ‘open woodland’

This DFA resulted in WH LF being reclassified as a significantly less open environment: closed forest (p = 0.67), dry open forest (p = 0.33) and woodland (p = 0.01).

Classification of LM LF has also changed, albeit not as significantly, from the first DFA. The likelihood of LM LF being closed forest has increased (p = 0.27) and subsequently the possibility of LM LF representing wet forest has decreased markedly

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(p = 0.72). The first DFA did not identify this LF with dry open forest or woodland, but both are slight possibilities (p = 0.01 for both) according to the present DFA.

The possible vegetation structural groupings for NG LF have broadened from those identified in the first DFA. NG LF is classified as being similar to closed forest (p = 0.38), wet forest (p = 0.56), dry open forest (p = 0.05) and woodland (p = 0.01). Neither of the latter two categories were identified as possible groupings for NG LF in the first DFA. The possibility of this fossil fauna being analogous to closed forest has increased, while the potential for NG LF representing wet forest has decreased.

In the first DFA (with all variables and only 67 Recent faunas) COA LF was determined to be analogous to dry open forest (p = 1.0). The second DFA, with 114 Recent faunas, has increased the number of potential vegetation groupings for COA LF, although dry open forest remains the most likely: closed forest (p = 0.05); wet forest (p = 0.03); dry open forest (p = 0.8); and woodland (p = 0.12).

The WW LF was one of three LF’s that could not be classified by the first DFA, despite the removal of possible outliers. However, possible vegetation analogues were identified by the second DFA after removing large diprotodontid species: closed forest (p = 0.28); wet forest (p = 0.68); and dry open forest (p = 0.04).

The CS and UP LF’s remain unclassified, despite the improved reliability of this DFA.

Relative to the previous DFA the probability of MM LF representing a closed forest has increased (p = 0.03), while the likelihood of this LF being wet forest has decreased (p = 0.92). Additionally MM LF is classified as dry open forest (p = 0.05) and woodland (p = 0.01) in the DFA incorporating 114 extant faunas. It was necessary to remove large diprotodontid outlier species from the dataset before classification.

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The possibility of the Ringtail LF being analogous to closed forest has increased (p = 0.85) as has dry open forest (p = 0.02), while the probability for Ring LF being wet forest has decreased (p = 0.14). There is also a small probability (p = 0.01) that Ring LF is equivalent to a woodland environment.

The Encore LF is reclassified as closed forest (p = 0.02), dry open forest (p = 0.39) and woodland (p = 0.59). The classification probabilities have therefore shifted from woodland to dry open forest, relative to the first DFA, although woodland remains the most likely analogue. The possibility of Encore LF being closed forest has decreased, while the open woodland grouping recognised in the first DFA is not found in the present DFA.

This DFA identified GAG LF as closed forest (p = 0.08), wet forest (p = 0.86) and dry open forest (p = 0.06). The previous DFA, including only 67 Recent faunas, but all variables, classified GAG LF only as wet forest (p = 0.99).

The HHLF is classified as wet forest (p = 0.24), dry open forest (p = 0.69), and woodland (p = 0.07). HH LF was previously grouped as more closed vegetation types.

For the DFA incorporating all variables the classification results improved from 79 to 85 percent on average, while the jackknifed classification results improved from 46 to 55 percent, with the removal of carnivorous taxa. For the second DFA (utilising 114 faunas and with certain variables excluded) classification results improved from 73 to 75 percent, and jackknifed results from 60 to 61 percent, with the exclusion of this trophic guild. The most significant difference within each vegetation category was observed for ‘closed forest’. For the first DFA (including all variables) the closed forest faunas correctly classified improved from 77 to 95 percent, likewise the jackknifed classification increased from 59 to 73 percent. For the second DFA classification success improved from 74 to 96 percent, and from 59 to 85 percent for the jackknifed matrix. Other vegetation categories only improved or decreased marginally with the exclusion of carnivores.

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Discussion The jackknifing results for the DFA incorporating all species richness, cenogram and moment statistic variables, indicates reduced reliability for classification results. Of the initial 118 Recent faunas employed in the dataset, only 67 were analysed by the DFA due to the necessity for no missing values in DFA’s. Consequently two of the five vegetation categories, ‘woodland’ and ‘open woodland’, were significantly under- sampled (n = 7 and 5 respectively). Such low sample sizes overall are further reduced by jackknifing, lowering within-group variation and resulting in less reliable discriminant functions for categories. The second DFA was run on 114 Recent faunas by excluding variables that contained much missing data. Sample sizes for the ‘woodland’ and ‘open woodland’ categories increased dramatically. Consequently the jackknifing results were much higher. Even though the number of correct classifications had, on average, reduced slightly, the reliability of the correct groupings was much greater.

The mean gradient of the medium-large mammals was not used in the DFA on either dataset. It can therefore be assumed that this cenogram variable is not useful for environmental or palaeoenvironmental determination by DFA. In contrast, the size of the cenogramic gap (above 500g) was the greatest contributor to the discriminant function, for both datasets. Interestingly the size of the gap at 3.5kg was also found to be a useful variable in both analyses. This variable was generated for the purposes of this analysis, based on apparent gaps observed in body-size distributions, as was the size of the gap at 3kg. However the latter was not found to be as useful as the former, implying that any association between vegetation structure and a gap at 3kg is not strong.

Determination of palaeoenvironment

The DFA results for WH LF differ markedly depending on the datasets employed. The first under-sampled and less reliable DFA strongly indicates vegetation structure analogous to an open woodland environment for the WH LF. In contrast the second, and more reliable, DFA suggests that there is a 2/3 chance that WH LF is most similar to extant closed forest, yet also a 1/3 chance that it may also be dry open forest,

______82 with no possibility of open woodland. Interestingly there is also no indication of WH LF being analogous to wet forest. Typically when a LF groups with one type of vegetation structure it also exhibits reasonable probabilities for vegetation types to either side (i.e. slightly more open and/or more closed). If the results of the second DFA (with a larger sample size and some variables excluded) are taken as more accurate, as indicated by the superior jackknifing results, it is likely that WH LF was analogous to extant Australian closed forest. However, the probability of a dry open forest grouping, suggested by the second DFA, in conjunction with the classification of this fauna as open woodland by the first DFA, may indicate that the closed forest contained significantly drier and more open patches. Likewise the failure of either DFA to identify WH LF with wet forest may suggest that any open patches may have abutted sharply against closed forest, with no gradual transition.

Neither of the CS or UP LF’s could be successfully classified. This suggests that neither is analogous to any extant Australian vegetation structure. Both LF’s are particularly species rich, even allowing some latitude for possible time-averaging effects. Such high species richness is usually associated with moist tropical environments. In this analysis faunas in the ‘wet forest’ category exhibited the highest species richness on average, closely followed by those from the ‘closed forest’ group (Table 17). It is therefore likely that CS and UP LF’s represent species-rich closed to wet forest types not present in extant Australia, or at least not represented in the dataset utilised. Archer et al. (1995) have suggested that analogues for ‘System B’ LF’s, such as CS and UP, may be found in mid-montane New Guinea or lowland Sarawak.

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Table 17: Group means for variables (DFA with 114 faunas)

Vegetation Categories 1 2 3 4 5 NUSPP 12.519 12.778 12.375 9.000 9.353 MNNRM 3826.543 5666.676 7719.752 8613.833 11020.844 STDEVNRM 5665.886 7433.407 10527.355 11085.475 12214.805 SKEWNRM 1.984 1.419 1.687 1.560 1.505 KURTNRM 4.040 1.006 2.618 2.022 1.992 MNLN 6.645 7.242 7.264 7.552 8.008 STDEVLN 2.170 2.129 2.357 2.299 1.732 SKEWLN -0.175 -0.579 -0.467 -0.498 0.148 KURTLN -1.163 -0.361 -0.582 -0.716 -1.515 Variables Variables SIZEGP 1.467 2.108 2.139 3.294 5.991 NUGAPS 5.481 6.444 6.281 5.150 4.176 MAXSLPELGE 0.653 0.502 0.615 0.688 0.663 MNSLPELGE 0.580 0.456 0.539 0.598 0.577 SZGAPTHREEKG 0.767 0.605 0.956 1.137 1.264 SZGPTHHLFKG 0.691 0.656 0.946 1.161 0.824 MINSLPELGE 0.506 0.410 0.464 0.513 0.492

Vegetation categories: 1 = closed forest; 2 = wet forest; 3 = dry open forest; 4 = woodland; 5 = open woodland

The NG and WW LF’s were similarly classified by the second DFA as predominantly wet forest, but also with substantial probabilities of closed forest and low possibilities that they group with dry open forest. These LF’s may therefore have exhibited vegetation structures indicative of modern wet forest, possibly with considerable areas that were more closed.

The MM LF was classified as a wet forest equivalent by both DFA’s, with only minor possibilities of this fauna representing closed forest or dry open forest. Relative to

______84 other System B LF’s MM LF is relatively under-sampled, which may ultimately have affected the vegetational grouping of this LF.

LM LF grouped predominantly with wet forest, but also with the closed forest category, particularly for the better sampled and more reliable DFA. This suggests that LM LF was analogous to extant Australian wet forest, perhaps with minor areas of closed forest interspersed.

The Ring LF was classified by the first DFA primarily as wet forest but also with a significant possibility of it being closed forest. The more reliable second DFA indicated a predominantly closed forest grouping for the Ring LF, with a much lower possibility of this LF being analogous to wet forest. It is suggested that the Ring LF was therefore equivalent to some type of closed forest, probably with minor more open areas similar to extant wet forest.

For the GAG LF both DFA’s strongly suggested a wet forest environment. The second DFA also indicated low probabilities for closed forest and dry open forest, which may indicate minor areas of both more open and more closed vegetation.

The classifications for the HH LF were quite different between DFA’s. The first strongly indicated wet forest, while the more reliable second DFA suggested that HH LF was probably dry open forest, but also with a reasonable chance of it being wet forest and a minor possibility for woodland. It is therefore likely that HH LF represented some variety of open forest structural analogue, probably dry open forest but potentially with significant moister and more closed vegetation structures. It is also possible that, structurally, the HH LF represents a form of deciduous vine thicket, a form of rainforest with dry open forest structure (P. Adams, pers. comm.).

Both DFA’s strongly suggest that COA LF was equivalent to extant Australian dry open forest. However minor probabilities indicate possible closed forest and more substantial areas similar to woodland.

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The late Miocene Encore LF is identified predominantly as a woodland equivalent, possibly with more closed areas analogous to dry open forest.

The case for the carnivores Excluding ‘carnivorous’ taxa from the datasets improved classification results on average, before and after jackknifing, for both DFA’s. While the improvement is only marginal overall, it is very significant within the ‘closed forest’ category. It would therefore seem prudent to remove ‘carnivorous’ species in excess of 500g, when performing DFA on body size variables. For Recent Australian faunas this means primarily removing dasyuromorphians and ‘introduced’ taxa such as the dingo and cat.

Time-averaged versus ‘snapshot’ faunal assemblages It could be argued that time-averaged fossil faunas and ‘snapshots’ of Recent faunas are not directly comparable. Time-averaging and taphonomic factors can result in fossil faunas potentially incorporating species, as well as individuals, which did not interact in life. However, in many respects time-averaged fossil faunas can be more representative of a community, as they counter the effects of ‘patchiness’, incorporating many species that lived in the local habitat over time: “… the local palaeocommunity will more closely approximate the total species assemblage that was present in the entire living local community than the sampling of live organisms at a single location would produce” (Bennington & Bambach, 1997; Brenchley & Harper, 1998). The local palaeocommunity (= local fauna) is defined as the fauna collected from a single bed at one outcrop, assuming that other evidence indicates a lack of transportation (ibid.). This definition applies to the Oligo-Miocene Riversleigh LF’s examined here. Strictly, the Recent and fossil faunas are not directly comparable, but we have little other choice. Where possible the temporal range (time-averaging) of the fossil faunas examined must be minimised, and that of the Recent faunas maximised.

It is possible that some of the Riversleigh LF’s are ‘within-habitat time-averaged assemblages’, derived from a single community that persisted over periods of relative environmental stability (sensu Kidwell & Flessa, 1996). These assemblages can

______86 incorporate many generations and generally formed over years to thousands of years (ibid.). The temporal difference between the Riversleigh LF’s examined, and the Recent faunas, may therefore only be one or two orders of magnitude. It is however also likely that a time-averaged assemblage, such as those at Riversleigh, will incorporate a number of geographically lateral communities through natural migration with time. By minimising the lateral and vertical extent of the fossil deposit, and ensuring that the locality is generally unstratified (as with most of the LF’s utilised in this study), the likelihood of incorporating mosaic habitats, mixed communities or transitional species is reduced. Furthermore, by analysing extant geographical variants of broad vegetation types (i.e. ‘closed forest’, ‘wet forest’ etc.), that allow for some variation in community structure, it should be possible to identify characteristic body-size signatures that can be used to identify time-averaged palaeohabitat structures in fossil LF’s.

Furthermore, the majority of variables examined in the DFA’s relate to body size distributions. It is unlikely that the addition of a few non-sympatric species in the LF’s would dramatically alter these distributions, particularly as large outlier species were removed.

The removal of large diprotodontoid species from the analysis clearly has a significant effect on the classification of many of the fossil local faunas. The White Hunter, Neville’s Garden, Mike’s Menagerie, GAG and Henk’s Hollow local faunas cannot be classified into any of the proposed vegetational categories without first removing diprotodontoid species in excess of 66kg. The species concerned are: 1) Neohelos tirarensis (129kg) from NG, WW, CS and MM LF’s; 2) Propalorchestes ponticulus (95kg) from NG, WW, GAG and CS LF’s; 3) Neohelos stirtoni (242kg) from HH LF; 4) Bematherium angulum (127kg) from WH LF; 5) Neohelos gregoriaei (136kg) from COA LF; and 6) Palorchestes anulus (109kg) from Encore LF. No local fauna is therefore affected by the removal of more than two species. Mammals of these sizes do not exist in Australian habitats today, and as a result classifications into extant vegetation groupings are extremely unlikely if they are included, as distribution statistics will be strongly altered by the inclusion of only one or two very large species. It is

______87 possible that recently extinct Plio-Pleistocene megafaunal species, such as Diprotodon optatum, may have filled some of the niches left vacant by earlier diprotodontoids. Current biogeographical understanding of megafaunal species is not sufficient, however, to include these species in extant faunal lists. If the larger Oligo-Miocene diprotodontoid species were to be included in the local fauna DFA lists it is likely that the LF’s would be re-classified as more ‘open’ vegetational communities, as statistics such as mean body size and standard deviation would be increased dramatically (see Table 17). It is difficult to justify inclusion of these larger species given that they typically represent a minor portion of overall species diversity for each LF. It must also be considered that it is quite possible that the extant Australian reference assemblages are significantly different from the fossil LF’s and that the inability of the DFA to classify the latter when large diprotodontoids are included merely reflects this difference. No extant vegetational analogue may exist for Australian Oligo-Miocene palaeoenvironments. Similarly, it is possible that unclassified fossil LF’s represent mixed habitats and when compared to more restricted, or better defined, extant vegetation types they cannot be resolved.

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Chapter 5 Classification and ordination analysis of selected Riversleigh Local Faunas

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Classification and Ordination analyses of selected Riversleigh Local Faunas

Introduction Etter (1999) recommends classification as the first step in any analysis of palaeocommunities as it simplifies large data-sets, allows for the grouping of recurrent assemblages, and ultimately identifies palaeocommunities. Etter (1999) also notes that any sampling units are time-averaged accumulations that lasted on average several thousand years, and are possibly mixed assemblages representing different palaeocommunities. However, in any analysis of multiple assemblages it soon becomes clear that certain species always occur together and probably belonged to the same community. The recurrence of species combinations over multiple sampling units, usually with a characteristic pattern of relative abundances, is usually the measure by which palaeocommunities are recognised (e.g. Etter, 1999; Bennington & Bambach, 1996; Popov et al., 1994).

Bennington & Bambach (1996) define a local palaeocommunity (roughly comparable to a local community) as “…the assemblage collectable from a single bed at one outcrop, assuming that sedimentological and taphonomic interpretation suggest that the fossil deposit is generally untransported”. Bennington & Bambach (1996) also suggest that the local palaeocommunity may be a more accurate representation of a living community determined through the sampling of species at a single location, as: 1) more of the total species assemblage that lived in the local habitat over time will be represented; and 2) the effects of species patchiness in living communities, are reduced in palaeocommunities as they are aggregates of living communities.

The recurrence of species at particular abundances at several sites is indicative of recurring structure in a local community, and consequently implies that the sites represent “…the same ecological entity” (ibid.) Similarly, a palaeocommunity equates to the aggregate of local palaeocommunities that cannot be differentiated statistically (ibid.).

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Popov et al. (1994) conclude that taxa which are most associated together as recurrent groups could be viewed as possibly having lived together in the past as a community. These local palaeocommunities therefore hold the same position in the palaeoecological hierarchy as local communities do in the neoecological hierarchy (Bennington & Bambach, 1996).

Likewise, Bennington & Bambach (1996) define the ‘palaeocommunity type’ as the grouping of local palaeocommunities and palaeocommunities that occur in stratigraphically similar settings and can be identified using cluster analysis.

Classification The most commonly used classification technique is cluster analysis (e.g. Etter, 1999; de Bonis et al. 1992; Brenchley & Harper, 1998; Bennington & Bambach, 1996). Typically cluster analysis involves: 1) the construction of a sampling units by sampling units dissimilarity matrix from the species by sampling units data matrix, using one of the dissimilarity or distance measures; and 2) employment of a clustering algorithm to hierarchically group larger and larger clusters. In general classification methods using quantitative data are superior to those employing qualitative (i.e. presence/absence) data (Etter, 1999).

Various dissimilarity and distance measures exist for constructing dissimilarity matrices, the first step in cluster analysis. Included among these are: 1) Euclidean distance – which is widely applicable and used in analyses of relative abundance (Hammer et al. 2001); 2) Correlation using Pearson’s r and Spearman’s rho – which are strongly affected by sample size and should not be used when matrices contain much missing information (Etter, 1999); 3) Dice (also Czekanowski or Sorensen coefficient) – uses presence/absence data and expresses the similarity between sampling units by focussing on joint occurrences rather than differences (Hammer et al. 2001; Etter, 1999); 4) Jaccard – is a similarity measure for presence/absence data; 5) Bray-Curtis – this measure highlights the difference in relative abundance between common species but its value is diminished by large sample sizes (Etter, 1999); 6) Chord – this dissimilarity measure is susceptive to changes in species proportions rather than absolute abundance

______91 and is considered by Etter (1999) and Hammer et al. (2001) to be very useful; 7) Morisita’s – another recommended measure (e.g. Hammer et al., 2001; Etter, 1999) which uses abundance and is almost independent of sample size; and 8) Raup-Crick – recommended by Hammer et al. (2001) and uses similarity matrices of binary data.

The most common clustering algorithms, used to classify sampling units into a hierarchy from the similarity/dissimilarity matrices, are: 1) single linkage; 2) complete; 3) average (or UPGMA); 4) centroid; and 5) Ward’s method. Etter (1999) recommends average linkage and Ward’s method.

Principally there are two methods of approaching a clustering analysis, R-mode and Q-mode (Brenchley & Harper, 1998; Etter, 1999; Hammer et al., 2001). R-mode analysis uses a species similarity or dissimilarity matrix to identify species groupings, while Q-mode uses a matrix of sampling units to identify groups of sampling units. Popov et al., (1994), for example, use principal components analysis in Q and R modes for examining small mammal assemblages from Bulgaria.

Ordination According to Etter (1999) the purpose of ordination is to order ‘…sampling units in a continuum according to their similarity’. Principally, ordination analyses are graphical techniques whereby a priori groupings of sampling units are structured along eigenvectors. The loadings along axes gradients can be examined to determine variables responsible for clustering (Brenchley & Harper, 1998). Once classification has been undertaken ordination identifies similar clusters by grouping them close together. All ordination techniques reduce multidimensional data into only a few dimensions (Etter, 1999).

Principal components analysis (PCA) is an ordination technique which constructs hypothetical variables or eigenvectors from multivariable data arranged as correlation or variance-covariance matrices (Brenchley & Harper, 1998; Hammer et al., 2001). Principal co-ordinates analysis (PCO) is comparable to PCA but constructs eigenvectors using a matrix based on a measure of distance between data points. Correspondence

______92 analysis (CA) is similar to PCA but is used primarily on abundance data (although Brenchley & Harper (1998) suggest that it is more useful for presence/absence data). In CA there is a tendency for data-points to spiral and cluster at the edges of the resultant graph. Detrended correspondence analysis (DCA) is a variant of CA which attempts to remedy these effects. Ordination and classification techniques have only recently begun to be used extensively in palaeoecological analyses of vertebrate assemblages (e.g. de Bonis et al., (1992) use cluster, PCA and CA analyses on Greek late Miocene mammalian faunas).

When using abundance data, for example in DCA, Etter (1999) recommends transforming values when particular species are very common, effectively giving less weight to common species and more to those that are rarer. Logarithmic transformation is generally used when some species are particularly dominant, reducing the differences between species abundances while maintaining differences in population sizes between sampling units (Etter, 1999).

Methodology Fourteen Oligocene-Miocene local faunas from Riversleigh were subjected to classification and ordination analyses (although Encore Local Fauna (LF) was excluded from analyses of relative abundance above specific level, due to insufficient data). Cluster analysis was used in the classification process. All dissimilarity and distance measures were used, with the exception of correlation techniques, due to the problems associated with sample size mentioned above. The unweighted pair group method using arithmetic averages (UPGMA) or ‘average’ algorithm was used in conjunction with each distance measure. Etter (1999) noted that UPGMA was superior to the single linkage and complete algorithms, at least for ecological data, due to various problems such as ‘chaining’. Ward’s clustering algorithm was also used, as recommended by Etter (1999). All clustering results were then examined to find commonly reoccurring clusters of LF’s (see Appendix One).

Raw abundance data, recorded as the number of identified specimens (NISP) at various taxonomic levels, was log (base e) transformed where necessary, following Etter

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(1999). NISP values were used in preference to other counting methods, such as the minimum number of individuals (MNI), following Grayson (1984) who identified that: 1) NISP is more convenient to use when dealing with a large quantity of bone material as it is not necessary to associate skeletal elements, only to determine their taxonomy; 2) MNI is a function of NISP, so that any perceived problems with using NISP (such as association of elements) will also affect MNI determination; and 3) MNI is heavily influenced by the way in which the investigator arbitrarily divides their fossil sites into stratigraphic units.

NISP values were derived from a combination of sources, including the specimen database, published papers and unpublished data. Taxonomic assignments are therefore more reliable at lower taxonomic levels, although the increased sample size at higher taxonomic levels potentially filters out incorrect assignments.

Ordination techniques were used on datasets of taxonomic presence/absence and relative abundance. Principal components analysis (PCA) and principal co-ordinates analysis (PCO) were performed on a dataset of specific, generic, familial and super- familial presence/absence data. Indices of relative abundance, at various taxonomic levels, were analysed using detrended correspondence analysis (DCA).

A total of 104 species, 71 genera, 26 families and 18 ‘super-families’ were included in the taxonomic datasets analysed (see Appendix Two).

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Results Commonly reoccurring groups of sampling units (local faunas), identified by Q- mode cluster analyses, are summarised below:

Species presence/absence data: Familial presence/absence data: 1) UP & NG 1) WW & NG 2) UP, NG, CS & WW &MM 2) ENC & COA 3) LM & RING 3) GAG & HH 4) GAG & HH 4) MM & RING 5) GAG, HH, LM & RING 5) ENC, COA & KCB 6) NG, WW & UP Spp abundance data log(e): 1) WW, CS, NG & UP&MM Super familial presence/absence: 2) GAG & HH 1) COA & KCB 2) GAG & HH Generic presence/absence: 3) NG & CS 1) WW & CS 2) GAG & HH Super familial abundance data: 3) LM & RING 1) WH & MM 4) WW, CS, UP, NG 2) COA & HI 3) HH&CS Generic abundance: 4) WH, MM & NG 1) WH & MM 2) CS & WW Super familial abundance log(e): 3) WW, CS, UP & NG 1) WH & MM 2) COA & HI Generic abundance log(e): 3) GAG&LM 1) GAG & HH 4) WW, CS & NG 2) WW & CS 3) WW, CS, UP & NG

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These results suggest the presence of at least 3 palaeocommunities and 2 palaeocommunity types (sensu Bennington & Bambach, 1996). The presence of a cluster of NG, WW, CS & UP LF’s in all generic and specific analyses, and some analyses at higher taxonomic levels, indicates one natural palaeocommunity. MM local fauna was not consistently linked with these local faunas, therefore disallowing inclusion within the palaeocommunity. The combination of NG, WW, CS, UP & MM LF’s does, however, appear to represent a palaeocommunity type. GAG and HH LF’s constitute another natural grouping, being consistently linked at all taxonomic levels. Only analyses based on the relative abundance of superfamilies failed to consistently group these two local faunas. The third identifiable palaeocommunity is a combination of LM and RING LF’s. The latter grouping is common in analyses incorporating specific and generic presence/absence data, but less frequent at higher taxonomic levels or utilising abundance data.

The second proposed palaeocommunity type encompasses GAG, HH, LM & RING LF’s. This grouping occurs infrequently within the various cluster analyses, but often enough to suggest that the combination of GAG & HH represents a similar palaeocommunity to LM & RING.

Ordination analyses Principal components analysis of species presence/absence (Figure 6) data supports the grouping of NG, CS, WW and UP LF’s. This cluster is clearly separate from the remaining local faunas, particularly on the first eigenvector which accounts for 26% of the variation. Interestingly, of the remaining sampling units MM LF is situated most closely to this cluster, reinforcing the inclusion of this LF in a palaeocommunity type with NG, WW, CS & UP LF’s.

Those species with the highest loadings for the first component, and therefore the most important in determining clustering, from the PCA on species presence/absence are: Galadi speciosus, Madju variae, Galadi grandis, Bulungamaya delicata, Wabularoo naughtoni, Balbaroo gregoriensis and Nambaroo camilleriae. Of these, G. grandis has

______96 the highest loading value. These species are more likely to be present to the right of the graph (see Figure 6), towards the palaeocommunity cluster.

The PCA on species presence/absence also supports the other two proposed palaeocommunities, GAG & HH and LM & RING, as well as the palaeocommunity type incorporating both these palaeocommunities. Although clustering with other LF’s towards the left side of the graph (at one end of eigenvector one), the latter two palaeocommunities are separated from other LF’s by clustering at one end of eigenvector two (towards the top of the graph). Species with high loadings (>0.2) for component two include: Yarala burchfieldi; Madju ignotae; Nimbadon lavarackorum; Litokoala kanunkaensis; Galadi amplus; Trichosurus dicksoni; Ganguroo robustiter; and Muribacinus gadiyuli. The close association of these four LF’s, on both eigenvectors, emphasizes their amalgamation as a palaeocommunity type.

Principal coordinates analyses (PCO) of presence/absence data provided identical results to PCA at all taxonomic levels.

Detrended correspondence analysis (DCA) of the species abundance data (log base e) supports the grouping of NG, UP, CS & WW LF’s as a palaeocommunity (Figure 7). These four LF’s cluster towards the centre of all the sampling units and exhibit values low on axis one and towards the centre of axis two. Perhaps supporting the exclusion of MM LF from the palaeocommunity of NG, WW, CS and UP, is the fact that MM LF is situated close to this cluster, but not as close as KCB LF. This analysis also suggests WH and HI LF’s are very different from the remaining local faunas as they have high axis two values, due primarily to the presence of a high number of taxa unique to each LF, as well as Bematherium angulum which is common to both.

The same DCA also supports the proposed RING & LM and GAG & HH palaeocommunities (Figure 7). These LF’s cluster towards the bottom of axis one, although HH LF is particularly low and disparate from the other LF’s. Encore LF is similarly isolated on axis one albeit at the other extreme.

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Generic level PCA performed on generic presence/absence data is essentially the same as that at specific level (Figure 8). The three palaeocommunities are all supported by discrete clusters. Similarly, the palaeocommunity type consisting of GAG, HH, LM & RING LF’s is again confirmed. However, evidence for the palaeocommunity type incorporating NG, WW, CS, UP & MM LF’s is less strong as MM and WH LF’s have effectively switched places from their specific-level positions.

DCA of generic abundance data (log transformed) is again supportive of the proposed palaeocommunities and types (Figure 9). GAG, HH, LM & RING LF’s cluster in the lower left part of the graph towards lower axis one values. NG, UP, CS, WW & MM LF’s cluster in the centre of the graph, expressing median values on both axes. KCB LF is positioned further from the NG, UP, CS, WW & MM cluster than it was in the specific analysis. The positioning of HI and WH LF’s on axis two is also less exaggerated than it was in the specific DCA.

Familial analysis The familial PCA on specific presence/absence provided evidence for the NG, CS, WW & UP cluster, as well as the GAG & HH cluster (Figure 10). Both clusters are positioned high on component one with the GAG & HH cluster centred around eigenvalue 3 and the NG, CS, WW & UP cluster around eigenvalue 3.5. The GAG & HH cluster has slightly higher values for component two. Acrobatids, yaralids and pilkipildrids have the highest loadings for component one, implying that NG, WW, CS & UP are more likely to have these families than the other palaeocommunities or individual LF’s. The LM & RING cluster, observed at other taxonomic levels, is only weakly supported by the familial analysis. Additionally, the MM LF is significantly separated from the NG, CS, WW & UP cluster.

A DCA was not performed on familial abundance data due to insufficiently accurate NISP values at the familial level, and difficulties associated with separating families from super-families (for example with many of the macropodoid families).

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Taxa have for the most part been classified at species, generic and super-familial level, with increasing sample size at each higher taxonomic level.

‘Super-familial’ analysis The abundance and presence/absence data matrices for the super-familial analyses incorporate super-families as well as monotypic families, due to the fact that some families cannot be assigned to superfamilies (e.g. Ilariidae). The PCA on super- familial presence/absence data distinguishes the NG, UP, CS & WW as well as the GAG & HH clusters (Figure 11). Very little support is provided for the LM & RING cluster at this level, as both LF’s are clearly separated on the second eigenvector.

Together the first three eigenvectors account for 63% of the total variance of the analysis, with the first eigenvector explaining 28%, the second 20% and the third 15%. The two ‘super-families’ with the highest loadings (>0.4) for the first component are the notoryctids and the pilkipildrids. The presence of these two super-families within the NG, WW, CS & UP grouping is therefore largely responsible for the clustering of these LF’s towards the top of component one. GAG & HH also cluster towards the higher end of component one although it is the high component two values that separates them from the NG, WW,CS & UP cluster. The presence of wynyardiids and absence of notoryctids hold the highest loadings for component two.

The super-familial DCA supports all the proposed palaeocommunities, although the LM & RING grouping is tentative due to the degree of separation of the two LF’s (Figure 12). The NG, WW, CS & UP LF’s cluster at the centre of the graph with median loadings on both axes. GAG & HH cluster at the bottom of axis two and with median values on axis one.

Discussion It is proposed that three palaeocommunities (sensu Bennington & Bambach, 1996) are evident in the sample of 14 local faunas analysed here: 1) comprising WW, NG, CS and UP LF’s; 2) GAG and HH LF’s and 3) RING and LM LF’s. The remaining

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6 LF’s cannot be confidently placed within any of these palaeocommunities, and should probably remain as individual local palaeocommunities (synonymous with LF’s). Furthermore it is likely that the complex consisting of GAG, HH, RING and LM represents a palaeocommunity type (sensu Bennington & Bambach, 1996), at a level higher in the palaeoecological hierarchy than the palaeocommunity. It is equally likely that the suite consisting of WW, NG, CS and UP with MM also represents another palaeocommunity type.

Legendre & Legendre (1984; cited in Etter, 1999) suggest that the separation of classification clusters in ordination validates the results of classification. The palaeocommunities identified by classification are, for the most part, distinct clusters separate from the remaining LF’s. The exceptions occur in: 1) the species-level DCA, where the NG, WW, CS & UP cluster is slightly obscured by KCB LF; 2) the familial PCA, where MM LF verges on the LM & RING palaeocommunity; and 3) the superfamilial analyses, in which the LM & RING cluster ranges over a large portion of the axes.

Support for the palaeocommunity types suggested by classification is evident in the ordination results, but not as strong as for the palaeocommunities. MM LF is in most cases the most proximal LF to the WW, CS, UP & NG cluster, although in the species DCA, KCB LF is situated closer and in some of the higher level ordination analyses WH LF is as close or closer to the proposed palaeocommunity. Similarly, the LM & RING and GAG & HH palaeocommunities are for the most part situated adjacent to each other. However, in the familial and super-familial PCA’s the conjunction of these two clusters is obscured by WH and MM LF’s.

Etter (1999) notes that the first three eigenvalues should account for 40 to 80% of total variation in PCA. This is the case for all PCA’s performed in this analysis, ranging from 50% at the specific level and increasing at higher levels to a maximum of 63% at the level of superfamily. These results reaffirm the efficacy of the PCA analyses and the reliability of the results.

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Independent support for the proposed palaeocommunities is provided by a number of sources. For instance, Muirhead (unpub.), after examining the distribution of the highly diverse perameloid taxa from Riversleigh, concluded that CS and UP LF’s were “…found to correspond in many taxa and appear, at present, to be indistinguishable”. Furthermore, a preliminary cluster analysis performed on perameloid species abundances suggested that NG, UP, WW, CS & MM formed a group (with other LF’s) clearly distinct from a cluster containing HH, LM & GAG LF’s (RING LF was not analysed) (Muirhead, unpub.). It is interesting that the species with the highest factor loadings in the specific PCA were primarily yaralid perameloids and macropodoids.

In addition the proposed palaeocommunities and independent LF’s coincide with the ‘Systems A, B and C’ of Archer et al., (1989; 1995). For example, the WH LF, considered to belong to late Oligocene ‘System A’ (Archer et al.,1989; 1995) was not found to unite consistently with any other LF in classification and was also usually isolated within ordination analyses. Similarly, the NG, WW, CS, & UP LF’s (forming a palaeocommunity) and the latter cluster plus MM LF (forming a palaeocommunity type), are considered to be early Miocene System B LF’s (ibid.). Moreover the GAG & HH and LM & RING palaeocommunities, as well as the palaeocommunity type incorporating these palaeocommunities, consist of LF’s derived from the middle Miocene System C (ibid.).

The various palaeocommunities and palaeocommunity types identified are recognisable at differing taxonomic levels and utilising varying datasets. The UP, NG, CS, WW & MM palaeocommunity type is identifiable only at the level of species, using presence/absence or abundance data. The UP, NG, WW & CS palaeocommunity is recognised at the specific or generic level, using either dataset. The LM, RING, GAG & HH palaeocommunity type is only completely distinguished using species presence/absence data. The LM & RING palaeocommunity is identifiable using presence/absence data at the level of species or genus. In contrast, the GAG & HH palaeocommunity is the most easily recognised, as it can be determined at any taxonomic level using either dataset.

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One of the most important uses of ordination is the identification of potential environmental gradients (e.g. Etter, 1999). Generally the palaeocommunities identified align along the first component of the ordination, although there is some overlap in a couple of the analyses, particularly the superfamilial DCA. It is not entirely clear what palaeoenvironmental parameters are responsible for the ordering of the palaeocommunities, types and individual LF’s. It is possible that vegetation structure, examined in Chapter Four and found to differ markedly between LF’s, is one potential ordering factor.

It is unlikely that taphonomic processes could have generated similar fossil assemblages from dissimilar living communities (Bennington & Bambach, 1996). Taphonomy is generally considered to be a disorganising process. Even if samples are drawn from the same underlying species abundance distributions it is expected that they will be variable to some degree due to sampling error.

Utility of distance measures and clustering algorithms At the specific level it appears that the Jaccard and Dice presence/absence measures are equally most useful for identifying the proposed palaeocommunities and palaeocommunity types. The Raup-Crick measure was the least useful, as it only partially identified some palaeocommunities. Ward’s method also appears to be a useful for recognising palaeocommunities but not palaeocommunity types. These results were also confirmed at the generic level. At higher taxonomic levels the distance measures and algorithms used are variably useful for identifying palaeocommunities and types.

As far as species abundance data was concerned, the most useful distance measure for identifying palaeocommunities and types was the Bray-Curtis. The Euclidean measure recognised all three palaeocommunities. The Chord and Morisita methods were equally partially successful, identifying the NG, WW, CS, UP & MM palaeocommunity type, but only recognising the GAG & HH palaeocommunity. At higher taxonomic levels the Bray-Curtis, Chord and Morisita methods were equally

______102 useful, but only identified the WW, CS, UP & NG palaeocommunity, failing to recognise the GAG & HH or LM & RING palaeocommunities.

Cautionary notes The palaeocommunities identified are not equivalent to neontological communities due to a number of factors, including: 1) information loss from taphonomic processes as the life assemblage, or biocoenosis, progresses to the death assemblage (thanatocoenosis) and eventually to the biased fossil assemblage (taphocoenosis); 2) time-averaging, which confuses attempts to identify contemporaneous individuals in a fossil assemblage; and 3) a lack of precise information regarding the biology of extinct species (such as species distributions) (Bennington & Bambach, 1996).

Furthermore Bennington and Bambach (1996) consider that clusters should be considered as palaeocommunity types until within-palaeocommunity variation can be accounted for (contra Etter, 1999; de Bonis et al., 1992).

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Figure 6: Principle component analysis on species ( presence/absence) (acronyms refer to sites/local faunas as given on p. vii)

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Figure 7: Detrended correspondence analysis on species abundance (acronyms refer to sites/local faunas as given on p. vii)

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Figure 8: Principle component analysis on genera (presence/ absence) (acronyms refer to sites/local faunas as given on p. vii)

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Figure 9: Detrended correspondence analysis on genera (abundance) (acronyms refer to sites/local faunas as given on p. vii)

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Figure 10: Principle component analysis on family (presence/ absence) (acronyms refer to sites/local faunas as given on p. vii)

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Figure 11: Principle component analysis on super family ( presence/absence) (acronyms refer to sites/local faunas as given on p.vii)

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Figure 12: Detrended correspondence analysis on super family (abundance) (acronyms refer to sites/local faunas as given on p. vii)

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Chapter 6 The Nambaroo-Balbaroo palaeocommunity

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The Nambaroo-Balbaroo palaeocommunity

Multivariate analyses (Chapter Five) identified three distinct mammalian palaeocommunities within the sample of local faunas (LF’s) investigated in this study. One of these palaeocommunities comprises Neville’s Garden, Wayne’s Wok, Upper and Camel Sputum LF’s. It is also possible that the Mike’s Menagerie LF should be included in this palaeocommunity, although there is currently insufficient evidence to support the inclusion. Further sampling of the latter LF may provide the data required for such an amalgamation, but was beyond the scope of this study. It is therefore suggested that Mike’s Menagerie LF and the identified palaeocommunity constitute a palaeocommunity type (sensu Bennington and Bambach, 1996). Such a palaeocommunity type infers that the entities are very similar in composition and structure but not necessarily identical. All of these sites are regarded as belonging to ‘System B’ (Archer et al., 1989).

The two species that define the Nambaroo-Balbaroo palaeocommunity are, as the title implies, the balbarine kangaroos Balbaroo gregoriensis and Nambaroo camilleriae (N. sp5 of Cooke, 1997c) (Table 18). These species are exclusive to the WW, UP, NG and CS LF’s within the study sample. It is likely that any other LF not included in the present study, but possessing both these species, could also be classified as a member of this palaeocommunity. Interestingly, Cooke (1997c) noted that the Dirk’s Towers (DT) LF includes both these species. Creaser (1997) suggests that DT site may correlate with some of the sites included in this palaeocommunity. The identification of Balbaroo gregoriensis from MM LF would provide strong support for the inclusion of this LF within the Nambaroo-Balbaroo palaeocommunity.

Other characteristic species of the Nambaroo-Balbaroo palaeocommunity include the pseudocheirid ‘ringtail’ possum Pseudocheirops sp2 (Archer, unpub.), the burramyid ‘pygmy possum’ Burramys brutyi, the hypsiprymnodontid ‘giant omnivorous rat- kangaroo’ Ekaltadeta ima, the yaraloid ‘bandicoots’ Yarala burchfieldi, Bulungu palara,

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Gunawidji tubus, Galadi speciosus, Madju variae, Galadi grandis, the bulungamayine kangaroos Bulungamaya delicata and Wabularoo naughtoni (Table 18). These species are all present in the Nambaroo-Balbaroo palaeocommunity constituent LF’s, at least within the sample investigated, although they are not exclusive to it. It is suggested that a significant number of the latter species would also need to be present to justify inclusion of any other LF within the present palaeocommunity. Interestingly, Galadi grandis is known only from the four constituent LF’s of this palaeocommunity and Mike’s Menagerie LF. If MM LF is later shown to be part of the Nambaroo-Balbaroo palaeocommunity it is likely that G. grandis would also become a defining species for this palaeocommunity.

Sampling intensity varies markedly between the Nambaroo-Balbaroo palaeocommunity constituent local faunas. The level of sampling and/or specimen identifications (to at least superfamilial level) is recognised by the number of identifiable specimens (NISP) from each local fauna. The NISP values vary significantly between LF’s. At one end of the spectrum Mike’s Menagerie LF has a NISP of 219, while at the other extreme Upper LF has a NISP of 8561. Further sampling, or taxonomic identifications, is required for Neville’s Garden LF (NISP=336) which has only 1/3 the number of identified specimens of WW LF (NISP=925), ¼ the NISP of CS LF (NISP=1408) and only 1/25 the NISP of Upper site (Figure 13). It is therefore likely that species common to WW, UP and CS LF’s are possibly only absent from NG and MM due to lower NISP. For instance, the petauroid Djaludjangi yadjana, is absent from NG but present in all other LF’s in the palaeocommunity as well as Mike’s Menagerie.

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Species-level NISP values suggest that species relative abundances within the palaeocommunity should be within the following ranges:

Table 18: Defining and characteristic species of the Nambaroo-Balbaroo palaeocommunity

Higher level taxon Relative Body size Species abundance (g) (%) Defining Macropodoidea1 Nambaroo 0.3 – 1 5427 species camilleriae Balbaroo 0.3 - 1.4 8416 gregoriensis Characteristic Pseudocheiridae Pseudocheirops sp2 0.3 - 0.9 931 species Burramyidae Burramys brutyi 5.9 – 44 21 Hypsiprymnodontidae Ekaltadeta ima 0.6 - 2.9 16358 Yaralidae Yarala burchfieldi 4.7 - 8.3 63 Bulungu palara 6.3 - 11.2 86 Gunawidji tubus 8.4 - 27.1 200 Galadi speciosus 0.6 - 2.8 766 Madju variae 0.7 - 9.4 959 Galadi grandis 0.3 - 0.9 1519 Macropodoidea2 Bulungamaya 0.9 - 9.4 1631 delicata Wabularoo naughtoni 1.7 - 16.2 4312

1 – N. camilleriae and B. gregoriensis were, for the purposes of this study, considered to be balbarine macropodids (sensu Cooke, 1997). Cooke and Kear (1999) elevated balbarines to the Balbaridae; 2 – B. delicata and W. naughtoni were, for the purposes of this study, considered to be bulungamayine potoroids (sensu Cooke, 1997). Cooke and Kear (1999) placed the Bulungamayinae within the Macropodidae.

The values listed above are not considered to be as robust as the generic or familial NISP values due to lower sample sizes and, consequently, more pronounced weighting effects. Nevertheless, these values do provide an estimate of relative abundances of species within the palaeocommunity. For instance, it is clear that Burramys brutyi, Gunawidji tubus and Bulungu palara, and Wabularoo naughtoni were probably quite abundant. Conversely it is likely that the defining balbarine species,

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Pseudocheirops sp2, and at least one yaraloid bandicoot (Galadi grandis), were relatively uncommon.

Non-volant mammalian taxonomic representation The bulungamayine kangaroos, W. naughtoni and B. delicata, are characteristic of the Nambaroo-Balbaroo palaeocommunity. Cooke (1997c) observes that W. naughtoni is a common species within systems A and B, while B. delicata occurs in all three systems (but only low in the system C sequence). Both bulungamayines differ significantly in size with W. naughtoni weighing approximately 4312g and the ‘presumably rainforest adapted’ (Cooke, 1997c) B. delicata about 1631g (Table 19).

Table 19: Non-volant mammalian species present in the Nambaroo-Balbaroo palaeocommunity constituent local faunas

(1 = present; 0 = absent)

Body Higher level taxon Species NG WW UP CS MM Weight* Acrobatidae Acrobatid gen1 sp1 (RivLacro) 1 0 0 0 0 - Acrobatid gen2 sp1 (RivSacro) 1 0 1 0 0 13 Acrobatid indet. 0 0 0 1 1 - Burramyidae Burramys brutyi 1 1 1 1 0 21 Dasyuridae Barinya sp3 1 1 1 0 0 22 Barinya wangala 1 0 1 0 0 426 Barinya sp2 1 0 1 1 0 123 Diprotodontidae Neohelos tirarensis 1 1 0 1 1 128883 Ektopodontidae Chunia sp. 1 0 1 0 0 - Hypsiprymnodontidae Ekaltadeta ima 1 1 1 1 1 16358 Macropodoidea Bulungamaya delicata 1 1 1 1 0 1631 Ganawamaya acris 0 0 0 1 0 5055 Ganawamaya ornata 0 1 0 0 0 3743 Ganguroo bilamina 0 1 1 1 1 1513 Nambaroo camilleriae3 1 1 1 1 0 5427 Nambaroo cooki3 0 1 0 0 0 6765

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Body Higher level taxon Species NG WW UP CS MM Weight* Nambaroo gillespieae3 0 1 0 0 0 8040 Nambaroo longmorei3 1 1 1 0 0 6481 Nambaroo ngari? 0 1 0 0 0 - Nambaroo vandycki3 0 0 1 0 0 6687 Nambaroo wilkonsonae3 0 1 0 0 0 6645 Nowidgee matrix 0 1 1 1 0 1524 Wabularoo naughtoni 1 1 1 1 1 4312 Wururoo gadiyuli3 0 1 0 1 0 8427 Balbaroo gregoriensis 1 1 1 1 0 8416 Miralinidae Durudawiri inusitatus 0 1 0 0 0 451 Notoryctidae Notoryctes sp. 0 1 1 1 1 - Ornithorhynchidae Obdurodon dicksoni 1 0 0 0 0 - Palorchestidae Propalorchestes ponticulus 1 1 0 1 0 94980 Petauridae Petaurid gen2 sp1 (RivSpet) 1 1 1 0 1 95 Petaurid gen1 sp1 (RivLpet) 0 1 1 1 1 278 Petauroidea Djaludjangi yadjana 0 1 1 1 1 273 Phalangeridae Phalangerid indet. 1 0 0 1 0 - Phascolarctidae Nimiokoala greystanesi 1 0 1 1 0 2220 Pilkipildridae Pilkipildrid indet. 1 0 0 1 0 - Pseudocheiridae Hyperpaljara sp12 0 1 1 0 0 - Marlu kutjamarpensis 1 1 0 1 0 504 Marlu sp1 0 1 0 0 0 - Marlu sp3 0 0 0 1 0 - Paljara maxbourkei 0 0 0 1 0 325 Paljara nancyhawardae 0 1 1 1 0 160 Paljara tirarensae 0 1 0 0 0 273 Parapops sp12 1 0 1 0 0 750 Pildra sp.2 0 0 0 1 0 - Pildra sp.3 0 0 1 0 0 357 Pildra sp4. 0 1 0 0 0 357 Pseudocheirops Sp2 1 1 1 1 0 931 Thylacinidae Thylacinid indet. 0 1 0 0 0 - Thylacinus macknessi 1 0 0 0 1 9017

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Body Higher level taxon Species NG WW UP CS MM Weight* Wabulacinus ridei 0 0 0 1 0 5340 Ngamalacinus timmulvaneyi 0 0 0 1 0 5743 Thylacoleonidae Priscileo roskellyae 0 0 1 0 0 2969 Priscileo sp. 0 0 0 1 0 - Wynyardiidae Namilamadeta sp. 1 1 0 1 1 - Yalkaparadontidae Yalkaparidon coheni 0 0 1 1 0 280 Yaraloidea Bulungu palara1 1 1 1 1 0 86 Galadi grandis1 1 1 1 1 1 1519 Galadi speciosus1 1 1 1 1 1 766 Gunawidji tubus1 1 1 1 1 1 200 Madju ignotae1 1 0 1 1 0 783 Madju variae1 1 1 1 1 1 959 Praegawinga winsburyorum1 0 0 1 0 0 126 Yarala burchfieldi 1 1 1 1 0 63 Galadi amplus1 0 0 0 1 0 1058 Yingabalanaridae Yingabalanara richardsoni 0 0 1 0 0 - * - as determined from appropriate body mass equations in Chapter Two 1 – unpublished yaraloid species (Muirhead, unpublished PhD thesis) 2 - unpublished pseudocheirid genus (Archer, unpublished) 3 – unpublished macropodoid species (Cooke, unpublished PhD thesis) Characteristic macropodid Nambaroo species are considered to be plesiomorphic within the balbarinae, while B. gregoriensis is considered more derived than any species of Nambaroo (Cooke 1997a;c). B. gregoriensis has been recorded from systems A and B, while the two species of Nambaroo from NG are found in low and upper system B. The entire macropodoid fauna from NG supports the system B classification (Cooke, 1997c). The defining species Nambaroo camilleriae (5427g) is substantially smaller than the other defining balbarine B. gregoriensis (8416g).

Muirhead & Filan (1995) note that Yarala burchfieldi was about the size of a small antechinus, its dentition plesiomorphic compared to other bandicoots and that its diet was closer to that of extant strictly insectivorous-carnivorous dasyurids than it was to insectivorous-omnivorous living bandicoots. Extant male Antechinus minimus and A. swainsonii have average male body weights of approximately 65g (Myers, 2001), and

______117 are among the largest antechinus species. The estimated body weight of Y. burchfieldi (63g; Table 18) is roughly equivalent to these extant antechinus, suggesting that Muirhead (1995) may have significantly underestimated the size of Y. burchfieldi. Muirhead & Filan (1995) postulated that yaralids, because of their dentition and size, may have competed with dasyurids. While no dasyurid is characteristic of the Nambaroo-Balbaroo palaeocommunity, at least one of the three known species is present within each of the constituent LF’s (Table 19). None of the species of Barinya come close to approaching the body weight of Y. burchfieldi (Table 19). Muirhead & Filan (1995) provided support for the dasyurid-yaraloid competition hypothesis by noting that dasyurids appeared to be low in abundance and richness within Riversleigh’s Miocene LF’s.

Although occurring in at least ten sites at Riversleigh, and over two systems, Muirhead & Filan (1995) suggest that Y. burchfieldi was less abundant than other bandicoots, except at Upper site where this species was locally abundant. Contrary to this is the fact that at least two species of bandicoot, G. grandis and G. speciosus (and possibly M. variae), appear to be frequently less common within the Nambaroo- Balbaroo palaeocommunity than Y. burchfieldi (Table 18).

The pseudocheirid ‘ringtail possum’ Pseudocheirops sp2 has many congenerics in systems B and C of Riversleigh, all of which are closer to living P. archeri than any of the diverse New Guinean species (Archer et al., 1997). P. archeri is restricted to dense upland rainforest in the Wet Tropics region of Queensland (Strahan, 1995).

The burramyid ‘pygmy possum’ Burramys brutyi, known from hundreds of specimens and numerous sites throughout systems A, B and C, is one of the most widespread marsupial taxa within the Riversleigh assemblages, from both a spatial and temporal perspective (Brammall & Archer, 1997). Small, refugia rock-dwelling populations from alpine regions of New South Wales and Victoria provide little information on the palaeoenvironmental preferences of the Oligo-Miocene congener.

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The omnivorous to carnivorous hypsiprymnodontid ‘rat-kangaroo’, Ekaltadeta ima, similarly occurs throughout Riversleigh’s systems, therefore providing little biocorrelative information (Archer et al., 1997; Wroe, 1997b).

Some of the ‘transient’, or variably present, species in the palaeocommunity’s constituent LF’s (Table 19) may prove to be at least characteristic species with further sampling of the LF’s from which they have not yet been recorded. For example, the dasyurids Barinya sp2 and sp3, the petauroid Djaludjangi yadjana, the macropodoids Ganguroo bilamina, Nambaroo longmorei, the yaraloid ‘bandicoot’ Madju ignotae, the palorchestid Propalorchestes ponticulus, petaurid gen1 sp1 and petaurid gen2 sp1, are known from at least 3 of the 4 constituent LF’s and are possibly unrecognised characteristic species within the palaeocommunity.

Evidence for the Nambaroo-Balbaroo palaeocommunity Multivariate classification and ordination analyses support the Nambaroo- Balbaroo palaeocommunity at a number of levels. Within the cluster analyses the palaeocommunity was revealed by species presence/absence, species abundance, generic presence/absence and generic abundance data (see Chapter Five). The species-level cluster analyses also support the inclusion of MM LF in the palaeocommunity. The Nambaroo-Balbaroo palaeocommunity is also recognisable at the generic level. Seventeen genera have been identified as characteristic of this palaeocommunity (Table 20), including four genera not present in the list of characteristic species. The absence of these genera simply implies that the corresponding species were not distinguishable below generic level. No genus is exclusive to the four constituent local faunas, and consequently none defines the palaeocommunity.

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Table 20: Characteristic genera of the Nambaroo-Balbaroo palaeocommunity

Barinya Pildra Yarala Bulungu Wabularoo Balbaroo Pseudocheirops Namilamadeta* Nambaroo Yalkaparidon Gunawidji Madju Galadi Bulungamaya Burramys Ekaltadeta Notoryctes# *assumed that all wynyardiids are Namilamadeta sp. (N. Pledge, pers. comm.) #assumed that notoryctids are Notoryctes

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Other fauna and palaeoenvironmental indicators A great number of non-mammalian and chiropteran species are variably present within the Nambaroo-Balbaroo palaeocommunity and its constituent LF’s (Table 21).

Table 21: Chiropteran and non-mammalian species

Group High-level Family Species Present at Taxon Frogs Lechriodus intergerivus CS, UP, WW, NG Litoria magna CS Litoria rubelliformis CS, NG Crinia presignifera CS, WW Limnodynastes CS, NG antecessor Birds Casuariidae Emuarius gidju CS, UP Dromornithidae CS, UP, WW, NG Phalocrocoracidae CS Rallidae CS Apodidae CS Passeriformes CS, WW Oriolidae WW, NG Longimornis NG robustirostrata Turtles Meiolaniidae CS, NG Lizards Agamidae CS, NG, UP, WW Physignathus UP, WW Scincidae CS, UP, NG, WW Varanidae WW, NG Gekkota Pygopodidae Pygopus hortulanus NG Gekkonidae UP, NG Snakes Madtsoiidae Yurlunggur CS, UP, WW Nanowana godthelpi CS, UP, MM Nanowana schrenki CS, MM, UP

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Group High-level Family Species Present at Taxon Wonambi CS, UP, WW Pythonidae CS, WW, NG Morelia cf. antiqua UP Boidae CS, UP, WW, NG Fish Dipnoa CS, WW, NG Bats Macroderma UP, WW, NG Molossidae UP Rhinolophoidea UP Rhinonicteris tedfordi UP Vespertilionoidea WW Hipposideridae Hipposideros NG bernardsigei CS, NG Megadermatidae NG Mystacinidae Icarops aenae WW Icarops paradox NG Icarops sp. UP Crocodiles CS, UP, WW, NG Arthropod CS, UP Slater WW Gastropod UP

Archer et al. (1997) note that Lechriodus intergerivus, with extant congeners confined to New Guinean rainforest, is the most common frog within Riversleigh’s Oligo-Miocene deposits. Tyler et al., (1994) conclude that Riversleigh’s system B and C frog assemblages indicate the persistence of moisture at ground level year round, without the possibility of seasonal aridity.

Boles (1997c) indicates that dromornithids were large, flightless and terrestrial birds, with at least two dromornithid genera present within the Riversleigh deposits. The

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Riversleigh species, including Barawertornis tedfordi and Bullockornis planei, do not show cursorial adaptations and are therefore thought to have been forest dwellers (Boles, 1997c). Although they often occur with aquatic fauna there is no indication that dromornithids were in anyway aquatic, but were instead gregarious terrestrial herbivores (ibid.). Wroe (1999) has suggested a more carnivorous diet for some dromornithids.

Boles (1997a) suggests that the casuariid Emuarius gidju was more cursorial than Casuarius and may have approached that of the modern emu Dromaius novaehollandiae. E. gidju may have had similar ecological requirements to the emu, occupying open country or possibly rainforest with an open understorey (Boles 1997a).

The oriolid Longimornis robustirostrata has been identified from NG LF and is only the third songbird described from Tertiary Australia (Boles, 1999). This presumably frugivorous species is the largest oriolid and shows only minor variation from Recent congeners (ibid.).

Phalacrocoracids, or cormorants, have been identified from Wayne’s Wok and Camel Sputum LF’s. Boles (1997c) indicates that phalacrocoracids are not particularly informative for determining palaeoenvironment, other than that they indicate a lacustrine setting.

Boles (1997c) indicates that Riversleigh’s rails, present in CS LF, are from a medium-sized flightless rail of a similar size to the extant Gallinula tenebrosa. The Riversleigh rail, related to the native hen Tribonyx, was probably gregarious and indicates only the proximity of wetlands (Boles, 1997c).

Boles (1997c) indicates that the Riversleigh apodid, from the CS LF, was a medium-sized swift similar to the cave-nesting swiftlet Collocalia that presently breeds in Australia. Swifts are not good environmental indicators as they are aerial feeders capturing prey above the habitat canopy (Boles, 1997c).

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Hand (1997b) suggests that Hipposideros bernardsigei roosted in limestone caves within rainforest, like many of its extant congeners. H. bernardsigei was probably low flying, foliage gleaning or perching forager, making short flights from forest perches to intercept insects (Hand, 1997b). Differences in bat faunas between NG, CS & UP (3 of the 4 palaeocommunity LF’s) might be due to different cave microhabitats and associated forest (ibid.).

Rhinonicteris tedfordi has not been recorded from any system C sites (Hand, 1997a). The extant R. aurantius roosts in very warm, humid caves from NW QLD to NW WA, feeding at night on moths, beetles, wasps, ants, weevils and other insects (Hand, 1997a). Although the extinct and extant species are similar in many morphological characters it is not certain that they were ecological equivalents (ibid.).

Hand et al., (1998) considers Icarops aenae from the Wayne’s Wok LF to be the most plesiomorphic species of Icarops, and I. paradox from NG LF to be the most derived. Hand et al., (1998) suggests that the cranial morphology of these species is indicative of consuming very hard prey, although it also suggested that these species foraged for insects or fish over water, and roosted in limestone caves. S. Hand (pers. comm.) also recognises Icarops sp. from Upper site.

Regarding the lizards, Hutchinson (1997) indicates that pygopodids show considerable ecomorphological diversity, with some being fossorial, others diurnal surface-dwellers and still others primarily surface-dwellers. Most are invertebrate feeders, while some are ambush predators of skinks. Hutchinson (1997) also notes that the presence of Pygopus hortulanus from NG LF is indicative of either dry open patches near the rainforest or that P. hortulanus has no living ecological analogues.

Scanlon (1997) describes two small (up to 1.5m) madtsoiid snakes from early Miocene (System B) CS, UP and MM LF’s. These snakes may have been sympatric and had very similar ecological requirements, probably also occupying similar niches (ibid.). It is suggested that these snakes preyed primarily on skinks as borne out by the structure

______124 of their teeth. The two species may have differed behaviourally, or occupied slightly different habitats, with N. godthelpi living closer to the water (due to higher abundance of less abraded elements) and N. schrenki in more open or drier areas (ibid.).

Archer et al., (1997) note that Riversleigh’s abundant gekkonids, and rarer scincids and varanids (in contrast to their diversity in modern Australia) have yet to be taxonomically studied.

Meiolaniid turtles, large, terrestrial turtles with shells up to 1m long and body masses between 150 and 200kg, are restricted to systems B and C at Riversleigh (White, 1997). White (1997) also suggests that Riversleigh’s wet rainforest must have had substantial clearings where meiolaniids could gain access to high fibre food and sunlight, probably needing temperatures above 30 degrees Celsius if living tortoises are any indication.

Cooke (1997c) concludes that B. delicata was ‘presumably rainforest adapted’. Cooke (1997c) found that none of Riversleigh’s pre-Pliocene macropodoids exhibit dental adaptations for grazing, which would be expected if these taxa were drawn from more mesic environments (sensu Megirian, 1992). System B assemblages are characterised by a high diversity of macropodoids and is suggestive of rainforest diversity (Cooke, 1997c). Compared to system A, system B is typified by high balbarine species richness but low abundances and low richness for bulungamayines combined with high abundances.

Discriminant function analysis All of the Nambaroo-Balbaroo palaeocommunity constituent LF’s were included in a discriminant function analysis (DFA) with Recent Australian faunas, in an attempt to elucidate vegetational structure (see Chapter Four).

Based on the first DFA (67 extant faunas with small slope variables included and large diprotodontid excluded) the NG LF was classified as closed forest (p = 0.15) and

______125 wet forest (p = 0.84). None of the other constituent LF’s of the palaeocommunity could be classified. MM LF, presently included in a palaeocommunity type with NG, WW, CS and UP LF’s, was classified as wet forest (p = 1.0).

The more reliable second DFA (114 Recent faunas and excluding some variables; see Chapter Four) classified: 1) NG LF as closed forest (p = 0.38), wet forest (p = 0.56), dry open forest (p = 0.05) and woodland (p = 0.01); and 2) WW LF as closed forest (p = 0.28), wet forest (p = 0.68), and dry open forest (p = 0.04). Neither CS nor UP LF’s could be classified in this DFA. The MM LF was grouped with closed forest (p = 0.03), wet forest (p = 0.92), dry open forest (p = 0.05) and woodland (p = 0.01).

Palaeoenvironmental conclusions The results of the DFA are strongly suggestive of the Nambaroo-Balbaroo palaeocommunity being analogous to Recent Australian closed to wet forest, at least regarding the degree of ‘openness’ of the upper stratum. Although probabilities for the LF’s that could be classified are higher for the ‘wet forest’ category, the ‘closed forest’ post-probabilities are never the less significant. Such results could indicate a possibly mixed habitat structure for the palaeocommunity, with the dominant structure being equivalent to wet forest but with significant areas of closed vegetation. It is interesting that CS and UP LF’s, the two most highly sampled LF’s, could not be classified by the DFA’s. Increased sample size increases species richness and could increase the likelihood to incorporate species from mixed assemblages. High species richness is not necessarily indicative of closed forest, as the sample of Recent ‘wet forest’ Australian faunas exhibited a higher mean for species richness than the ‘closed forest’ faunas (see Chapter Four). Furthermore, WW LF, which could not be classified by the first DFA, was strongly classified as wet forest by the second DFA.

The defining and characteristic species are largely equivocal for determining the palaeoenvironment of the Nambaroo-Balbaroo palaeocommunity. However, the presence of a species of Pseudocheirops and Bulungamaya delicata are indicative of at least some closed forest, as may be the presence of six yaralids within the suite of

______126 characteristic species. Muirhead (unpub.) suggests that bandicoot niches were finely partitioned according to size, with up to eight sympatric species at Upper site. Such high bandicoot diversity is found in the extant mid-montane rainforests of New Guinea (ibid.)

Among the more transient mammal species of the palaeocommunity is further evidence for closed and more open forest types. For instance, Nimiokoala greystanesi, present in three of the four constituent LF’s of the palaeocommunity, is a phascolarctid with a living counterpart entirely restricted to open sclerophyllous forests and woodlands. While petaurids, variably present in all constituent LF’s of the palaeocommunity, are, with the exception of one dactylopsiline, present from woodland to wet forests bordering rainforest in Recent communities. Yet the large number of transient, defining and characteristic macropodoid species, between one and eight kilograms, points towards more closed forests. In addition, the lack of grazing macropodoids indicates minimal open areas containing significant coarser grasses.

Supporting evidence for closed and wet forest, as well as a mixture of the two, also stems from possible non-mammalian and chiropteran species within the Nambaroo- Balbaroo palaeocommunity, in particular: 1) the presence of Lechriodus spp., with congenerics confined to rainforest and other anuran species which require year-round moisture; 2) the forest-dwelling nature of dromornithids; 3) the biology of Emuarius gidju with the need for an open understorey within any rainforest; 4) species of Pygopus which indicate drier and more open patches; 5) meiolaniid turtles which suggest substantial open areas and temperatures in excess of 30 degrees Celsius; 6) Hipposideros bernardsigei with congeners that roost in rainforest caves; and 7) the presence of two species of Nanowana with slightly different habitat requirements.

Synopsis of the Nambaroo-Balbaroo palaeocommunity

The presence of two medium-sized terrestrial, browsing kangaroos, Nambaroo camilleriae and Balbaroo gregoriensis, currently defines membership of this palaeocommunity. Also present, but in far greater numbers, will be two smaller

______127 bulungamayine kangaroos, Bulungamaya delicata and Wabularoo naughtoni. The ‘possum’ component of the palaeocommunity includes at least one species of medium sized arboreal folivorous pseudocheirid, Pseudocheirops sp2, in low abundance, as well as the ubiquitous, mouse-sized, omnivorous, terrestrial-arboreal burramyid, Burramys brutyi. The latter may comprise nearly half of all individual mammals within the palaeocommunity. Occupying most of the terrestrial, carnivorous-omnivorous weight spectrum between 50g and 2kg, are at least six species of yaraloid ‘bandicoots’. In total the bandicoot fauna may comprise up to 60% of all individuals in the palaeocommunity. One yaraloid species, the 200g Gunawidji tubus, was particularly common, representing up to one quarter of all individuals. Another characteristic species of the palaeocommunity is the large (‘swamp wallaby’ sized), terrestrial, omnivorous- carnivorous ‘rat-kangaroo’, Ekaltadeta ima.

Thus the Nambaroo-Balbaroo palaeocommunity, as it is currently defined, was dominated, collectively, by small-medium sized terrestrial insectivores-carnivores, and small terrestrial-arboreal omnivorous pygmy possums. Medium-sized browsing macropodoids were a smaller but significant component. Larger browsing-omnivorous macropodoids and medium-sized folivorous possums constituted only a minor part of overall diversity.

Currently several species are classed as transient or ambiguous members of the palaeocommunity, yet some are known from most of the constituent local faunas and, with further sampling, may become characteristic species, significantly increasing the known diversity of the Nambaroo-Balbaroo palaeocommunity. These species include: three small insectivorous-nectivorous petauroid possum species (Djaludjangi yadjana, petaurid gen1 sp1 and petaurid gen2 sp1), two medium-sized browsing bulungamayine kangaroos (Ganguroo bilamina and Nowidgee matrix), at least one other medium-sized yaraloid bandicoot (Madju ignotae), two small, folivorous pseudocheirid ringtails (Marlu kutjamarpensis and Paljara nancyhawardae), a medium-sized balbarine kangaroo (Nambaroo longmorei), a medium-sized folivorous phascolarctid (Nimiokoala greystanesi), a small insectivorous notoryctid (Notoryctes sp.), one medium-sized

______128 browsing wynyardiid (Namilamadeta sp.), two large browsing diprotodontoids (Neohelos tirarensis and Propalorchestes ponticulus), as well as three species of dasyurids (Barinya wangala, B. sp2 and B. sp3).

Muirhead (2000) has suggested that yaraloid bandicoots were carnivorous. Certainly species of Barinya, small insectivorous-carnivorous dasyurids, that are transient within the palaeocommunity, have body sizes that are intermediate between some of the yaraloid species. This body size partitioning, combined with the transient nature of the species within the constituent local faunas, suggests at least some competitive exclusion of the dasyurids.

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Plate 1: (Top) Camel Sputum looking east; (Bottom) Camel Sputum looking south

Plate 2: (Top) Camel Sputum looking north; (Bottom) Camel Sputum looking north-west

Plate 3: Mike’s Menagerie looking towards Camel Sputum

Plate 4: (Top) Encore looking south; (Bottom) Encore looking west

Plate 5: (Top) Hiatus; (Bottom) Hiatus looking East

Plate 6: (Top) Keith’s Chocky Block looking South; (Bottom) KCB looking NE

Plate 7: (Top) Neville’s Garden; (Bottom) Neville’s Garden looking south-east

Plate 8:(Top) Upper Site looking north-west; Upper Site looking east

Plate 9: (Top) Wayne’s Wok looking south-west; (Bottom) Wayne’s Wok

Plate 10: (Top) White Hunter looking north-east; (Bottom) White Hunter looking east

Plate 11: (Top) White Hunter Femora; (Bottom) White Hunter Vertebrae

Scale Bar = 5cm

Plate12: (Top) White Hunter Pelvic Elements; (Bottom) White Hunter Metapodials

Scale Bar = 5cm

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Chapter 7 The Litokoala – Muribacinus palaeocommunity

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The Litokoala - Muribacinus palaeocommunity

Gag and Henk’s Hollow sites are located in the northern section of the Gag Plateau, within the Riversleigh World Heritage Fossil Deposits. Creaser (1997) reports that Gag Site is located 188 metres above sea level (ASL), while Henk’s Hollow is towards the top of the section at 198m ASL. Archer et al., (1989) found the Gag Plateau sequence to include a series of basal sediments, calcarenites, tufa, and pool deposits. Creaser (1997) suggested a more complex series of basal sediments and found Gag and Henk’s Hollow to be tufa deposits dominated by terrestrial faunas. In contrast, ‘deep water pool’ deposits, such as Ringtail Site, are considered to have been principally aquatic faunas (Creaser, 1997).

The combination of Gag and HH LF’s as a palaeocommunity was identified by cluster analysis and confirmed through ordination (see Chapter Five). The GAG and HH palaeocommunity, herein referred to as the Litokoala-Muribacinus palaeocommunity, is defined by the presence of four mammal species: the diprotodontid Nimbadon lavarackorum; the phascolarctid Litokoala kanunkaensis; the phalangerid Trichosurus dicksoni and the thylacinid Muribacinus gadiyuli (Table 22). Other characteristic species, not necessarily exclusive to this palaeocommunity, are: the palorchestid Propalorchestes ponticulus; the burramyid Burramys brutyi; the hypsiprymnodontid Ekaltadeta ima; the yaraloids Yarala burchfieldi, Bulungu palara, Gunawidji tubus, Galadi amplus, Madju ignotae; the pseudocheirids Marlu sp1 and Marlu kutjamarpensis; and the macropodoid Ganguroo robustiter (Table 23).

Trichosurus dicksoni appears to be the most abundant mammalian taxa within the palaeocommunity with up to 24% of identifiable specimens (NISP) representing this phalangerid ‘possum’ (Table 22). The ubiquitous burramyid ‘pygmy possum’ Burramys brutyi is also relatively abundant with up to 19% of specimens. Ekaltadeta ima, yaralid bandicoots and Ganguroo robustiter are also quite common. The fact that the two most common species are arboreal taxa suggests that they may have been very abundant,

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more so than the NISP values suggest, as arboreal taxa are generally under-represented as fossils.

Sample sizes for various taxa are higher at the generic level, and therefore provide more accurate relative abundances for monotypic genera (Table 24). Generic abundance suggests Trichosurus may not be as abundant as suggested by the species level identifications with only 14% of NISP. In contrast Burramys remains relatively unchanged, compared to the species figure, with up to 20% of NISP. Nimbadon are more common than species abundance suggests with up to 17% of specimens instead of 2% as suggested at specific level. Litokoala is slightly more common, with 3.2% of NISP at the generic level and 1.8% at species level. Muribacinus decreases a little from 2.5% of species NISP to 1.3% of generic

Table 22: Defining species of the Litokoala-Muribacinus palaeocommunity

Higher level taxon Taxon Relative abundance Body size (kg) (NISP%) Diprotodontidae Nimbadon lavarackorum 1.3-1.8 52 Phascolarctidae Litokoala kanunkaensis 1.3-1.8 3.7 Phalangeridae Trichosurus dicksoni 6.3-23.6 1.5 Thylacinidae Muribacinus gadiyuli 1.8-2.5 1.5

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Table 23: Characteristic species of the Litokoala-Muribacinus palaeocommunity

Higher level taxon Taxon Relative Body size (kg) abundance (%NISP) Burramyidae Burramys brutyi 5.5-19 0.021 Hypsiprymnodontidae Ekaltadeta ima 1.8-8.9 16.4 Macropodoidea Ganguroo robustiter 1.8-3.8 3.9 Pseudocheiridae Marlu kutjamarpensis 1.3-1.8 0.504 Marlu sp1 1.3-1.8 - Yaraloidea Bulungu palara 1.8-3.8 0.086 Galadi amplus 1.8-6.3 1.06 Gunawidji tubus 1.3-1.8 0.2 Madju ignotae 1.3-1.8 0.783 Yarala burchfieldi 1.8-5.1 0.063 As mentioned in Chapter Five, the Litokoala-Muribacinus palaeocommunity is identifiable at all taxonomic levels up to and including ‘superfamily’ utilising presence/absence and log abundance data.

Of the available pool of 47 mammalian species, just 14 (30%) can be said to belong, with some certainty, to the palaeocommunity (i.e. these species are characteristic and defining). Considerably more sampling or species-level identifications will have to be done to determine if the remaining 70% of non-diagnostic species are members of the palaeocommunity, highly-mobile or transient species, or artefacts of taphonomy. The latter seems unlikely, given that taphonomic biases are believed to be minimal in most Riversleigh sites (Archer et al., 1995).

It appears that among the non-diagnostic, or variable, species there are at least two sets of congeners that are transposable within the palaeocommunity: 1) Propalorchestes spp. and 2) Wanburoo spp. The bulungamayine macropodoids W. hilarus and W. wulugu shared very similar body weights (Table 25) and presumably similar ecological and biological characteristics. Likewise, it is conceivable that the

______133 large palorchestids, Propalorchestes novaculacephalus and P. ponticulus, occupied similar niches and were interchangeable within the palaeocommunity. The apparent difference in body size between the latter species may be an artefact of the statistical techniques used to determine body weight. Both estimates of size were ascertained by extrapolating beyond the range of allowable weight ranges and the smaller estimate is based on a less reliable dental predictor. The discrepancy may not be as significant as is revealed in Table 25, with P. ponticulus being up to 50% heavier than P. novaculacephalus. Murray (1990) and Black (1997b) propose that P. ponticulus is less robust and less derived than P. novaculacephalus.

Although body weights could not be determined for a number of Pseudocheirops species it is possible that these pseudocheirids too could have alternated within a similarly broad niche.

Among representative genera of the Litokoala-Muribacinus palaeocommunity Litokoala is classed as a characteristic genus, due to the presence of an indeterminate species of Litokoala in the Upper Local Fauna (Table 24). The latter is however likely to be L. kutjamarpensis, an early Miocene taxon from the Kutjamarpu LF, Lake Ngapakaldi (Black and Archer, 1997b), rather than the middle Miocene L. kanunkaensis that defines the Litokoala-Muribacinus palaeocommunity.

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Table 24: Defining and characteristic genera of the Litokoala-Muribacinus palaeocommunity

Genus Relative abundance (%NISP) Defining genera Nimbadon 1.3-17 Trichosurus 6-14 Muribacinus 1.1-1.3 Characteristic Propalorchestes 1.3-2.1 genera Neohelos 1.3-7.4 Pseudocheirops 1.1-1.3 Burramys 3.2-20 Ekaltadeta 8.5-10.7 Yarala 1.1-5.3 Bulungu 1.1-4 Gunawidji 1.1-1.3 Madju 1.1-2.7 Galadi 1.1-10.7 Balbaroo 1.3-2.1 Marlu 1.1-1.3 Ganguroo 3.2-4 Yalkaparidon 1.1-1.3 Litokoala 1.3-3.2 Wanburoo 2.7-3.2

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Table 25: Species variably present in GAG and HH LF's

(present =1, absent =0) Body weight Higher level taxon Species Gag HH (g) Acrobatidae Acrobatid indet. 0 1 - Burramyidae Burramys brutyi 1 1 21 Dasyuridae Barinya wangala 0 1 426 Dalamana muizonae2 1 0 - Dasylurinja nov. sp. 0 1 - Diprotodontidae Neohelos sp2 1 0 - Neohelos stirtoni 0 1 241799 Nimbadon lavarackorum 1 1 52194 Hypsiprymnodontidae Hypsiprymnodon bartholomaii 1 0 696 Ekaltadeta ima 1 1 16358 Macropodoidea Balbaroo nalima1 0 1 8089 Bulungamaya delicata 1 0 1631 Ganguroo robustiter1 1 1 3896 Wanburoo hilarus1 1 0 7801 Wanburoo wulugu1 0 1 7567 Palorchestidae Propalorchestes 0 1 59508 novaculacephalus Propalorchestes ponticulus 1 0 94980 Petauridae Petaurid indet. 1 1 - Petauroidea Djaludjangi yadjana 0 1 273 Phalangeridae Strigocuscus reidi 1 0 7434 Trichosurus dicksoni 1 1 1476 Phascolarctidae Litokoala kanunkaensis 1 1 3731 Pilkipildridae Djilgaringa gillespieae 1 0 415 Pilkipildrid indet. 0 1 - Potoroidae Bettongia moyesi 0 1 885 Pseudocheiridae Marlu kutjamarpensis 1 1 504 Marlu sp.5 1 0 - Marlu sp1. 1 1 - Marlu sp2. 1 0 - Paljara nancyhawardae 1 0 160 Parapops sp.2 1 0 -

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Body weight Higher level taxon Species Gag HH (g) Parapops sp1 1 0 750 Pildra sp.1 1 0 - Pildra sp.2 1 0 - Pildra sp.5 1 0 - Pseudocheirops sp.1 0 1 - Pseudocheirops sp.3 0 1 - Pseudocheirops sp.4 1 0 - Pseudocheirops sp2 1 0 931 Thylacinidae Nimbacinus dicksoni 0 1 5023 Thylacinus macknessi 1 0 9017 Muribacinus gadiyuli 1 1 1563 Thylacoleonidae Wakaleo vanderleuri 0 1 50000 Yalkaparadontidae Yalkaparidon jonesi 1 0 280 Yaraloidea Bulungu palara 1 1 86 Galadi amplus 1 1 1058 Gunawidji tubus 1 1 200 Madju ignotae 1 1 783 Madju variae 1 0 959 Praegawinga badcocki3 1 0 66 Yarala burchfieldi 1 1 63

1 = unpublished macropodoid species (Cooke, unpublished PhD thesis) 2 = unpublished dasyurid species (Wroe, unpublished PhD thesis) 3 = unpublished yaraloid species (Muirhead, unpublished PhD thesis)

A total of 16 families characterise the Litokoala-Muribacinus, although in some respects it is easier to characterise this palaeocommunity by the absence of mammal families rather than those that are present, in particular: 1) ornithorhynchids; 2) miralinids; 3) ektopodontids; 4) yingabalanarids; 5) vombatoids; 6) ilariids; 7) wynyardiids and 8) notoryctids (Table 26).

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Table 26: Characteristic families for the Litokoala-Muribacinus palaeocommunity

Acrobatidae Phalangeridae

Burramyidae Phascolarctidae

Dasyuridae Pilkipildridae

Diprotodontidae Potoroidae

Hypsiprymnodontidae Pseudocheiridae

Macropodidae Thylacinidae

Palorchestidae Yalkaparadontidae

Petauridae Yaralidae

‘Super-familial’ results, based on presence/absence data, do not differ substantially from those observed at the familial level. However, utilising relative abundance data it is possible to infer differences between the Litokoala-Muribacinus palaeocommunity and other palaeocommunities found in Chapter Five (Table 27). For instance, it is clear that the Litokoala-Muribacinus palaeocommunity is characterised by an abundance of phalangeroids relative to the other two palaeocommunities, as well as a greater number of macropodoids, phascolarctids and thylacoleonids compared to the LM & RING palaeocommunity. In addition the Litokoala-Muribacinus palaeocommunity exhibits fewer yalkaparadontids than the Nambaroo-Balbaroo palaeocommunity.

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Table 27: ‘Super-familial’ NISP comparison for palaeocommunities and LF’s

NISP (%) Litokoala- RING & LM Nambaroo-Balbaroo palaeocommunity Muribacinus palaeocommunity palaeocommunity

Super-family/Family NG CS WW UP MM GAG HH RING LM HI COA KCB WH

Phalangeroidea 3.6 0.6 3.4 1.0 5.0 7.6 5.9 0.5 3.8 6.7 0.7 1.0 0.0 Macropodoidea 28.3 18.5 54.1 8.0 69.4 17.0 14.7 2.7 7.3 6.7 32.2 21.3 52.1 Burramyoidea 4.2 0.7 2.1 1.8 0.0 4.5 0.2 3.8 8.9 0.0 3.9 0.6 0.9 Petauroidea 9.8 1.8 6.3 1.4 1.4 7.9 3.9 15.7 2.6 0.0 2.0 3.7 3.0 Yalkaparadontidae 6.8 3.3 1.5 1.4 0.9 0.3 0.1 0.0 1.0 0.0 0.0 0.1 0.9 Yaraloidea 15.8 69.1 16.8 83.4 6.8 53.6 67.4 60.5 70.6 0.0 1.3 72.0 21.7 Diprotodontoidea 2.4 1.6 1.2 0.0 7.8 2.4 3.2 0.0 1.0 60.0 44.1 0.7 3.3 Dasyuroidea 6.0 0.7 3.4 0.5 0.5 5.2 2.8 4.3 3.5 13.3 2.6 0.3 6.5 Tarsipeoidea 10.1 0.1 1.3 0.7 0.5 0.9 0.4 1.1 1.0 0.0 0.0 0.0 0.3 Phascolarctidae 5.4 0.5 0.0 0.0 0.0 0.3 0.3 0.0 0.0 6.7 0.0 0.0 0.0 Ornithorhynchidae 1.2 0.0 0.0 0.0 0.0 0.0 0.0 10.3 0.0 0.0 0.0 0.0 0.0 Wynyardiidae 1.2 2.3 4.1 0.1 7.3 0.0 0.0 0.5 0.0 6.7 0.0 0.0 4.8 Notoryctidae 3.3 0.4 5.8 1.6 0.5 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 Pilkipildridae 1.8 0.2 0.1 0.0 0.0 0.3 0.2 0.0 0.3 0.0 0.0 0.0 0.0 Thylacoleonidae 0.3 0.1 0.1 0.1 0.0 0.0 0.9 0.0 0.0 0.0 5.9 0.1 2.4 Vombatoidea 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.2 0.0 0.0 Ilariidae 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.2 Yingabalanaridae 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

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Taxonomic representation

Diprotodontians Characteristic macropodoid species within the Litokoala-Muribacinus palaeocommunity include Ekaltadeta ima and Ganguroo robustiter. Cooke (1997c) finds G. robustiter, as well as species of Wanburoo to be among the most highly derived bulungamayines. Ekaltadeta ima is quite common within the palaeocommunity, representing up to 9% of NISP by species and 11% by genera. Only the burramyid Burramys brutyi, the diprotodontid Nimbadon lavarackorum and the phalangerid Trichosurus dicksoni are potentially more abundant. G. robustiter is only half as abundant, with up to 4% of NISP by species. Other potential macropodoid members of the Litokoala-Muribacinus palaeocommunity, that are variably present in constituent local faunas, are Balbaroo nalima, Bettongia moyesi, Bulungamaya delicata, Hypsiprymnodon bartholomaii, Wanburoo hilarus and W. wulugu.

Balbaroo nalima (from HH LF) is considered to be the most derived balbarine macropodoid. Cooke (1997c) suggests that the presence of B. nalima, Ganguroo robustiter, and Wanburoo wulugu indicates a system C site, or younger.

There is also a diversity of arboreal diprotodontian taxa in the Litokoala- Muribacinus palaeocommunity. The phalangerid Trichosurus dicksoni and the phascolarctid Litokoala kanunkaensis are defining species, while the burramyid Burramys brutyi and pseudocheirids Marlu sp1 and Marlu kutjamarpensis are also characteristic. Table 25 indicates that a number of other ‘possum’ taxa, including Djaludjangi yadjana, Djilgaringa gillespieae, Marlu sp2 & sp5; Paljara nancyhawardae; Parapops sp1 & sp2; Pildra sp1, sp2 & sp5; Pseudocheirops sp1,2, 3 & 4 and Strigocuscus reidi, may well be members of this palaeocommunity, given greater sampling and identification of taxa.

Propalorchestes ponticulus and Nimbadon lavarackorum comprise the diprotodontoid component of the Litokoala-Muribacinus palaeocommunity. Black

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(1997b) suggests that large numbers of Nimbadon lavarackorum in AL90 and COA sites may indicate that they were moving in mobs, a feature of slow-moving medium to large- sized herbivores in open environments. Further sampling and/or identification of specimens is required to determine whether Neohelos stirtoni, Propalorchestes novaculacephalus and Pr. ponticulus, are transient members, anomalies or true members of the palaeocommunity.

Wakaleo vanderleuri is present in the HH LF, but has not yet been identified in the GAG LF. The thylacoleonids therefore have ambiguous membership of the palaeocommunity.

Peramelemorphians At least five peramelemorphians characterise the Litokoala-Muribacinus palaeocommunity. Galadi amplus is generally the most common of the ‘bandicoots’ (6% NISP), with Yarala burchfieldi (5%) and Bulungu palara (4%) slightly less common. Each of the latter species is roughly twice as abundant as Madju ignotae and Gunawidji tubus (2%). The yaralid bandicoots appear to be partitioned along a body size gradient, with each species being at least 30% heavier than the next lightest (Table 25). If non- characteristic yaralid species, Madju variae and Praegawinga badcocki, are included the partitioning remains significant although much finer, with at least 5% difference in body size between a species and the next lightest.

Dasyuromorphians The thylacinid, Muribacinus gadiyuli, is a defining species for this palaeocommunity. Wroe (1996b) considers M. gadiyuli to be the most plesiomorphic thylacinid described to date, and closest phylogenetically to Nimbacinus dicksoni. M. gadiyuli is the smallest thylacinid described, being comparable in size to the extant dasyurid Dasyurus maculatus (Table 25). M. gadiyuli probably concentrated on small vertebrates for prey, and may have been at least partially arboreal.

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Archer et al., (1997) note that the megadermatid Macroderma godthelpi occurs throughout System B (early Miocene) sites as well as lower system C (early middle Miocene) sites, such as Gag. M. godthelpi is ancestral to M. malugara from younger system C sites, such as HH LF (Archer et al., 1997; Hand, 1996). The small megadermatid Macroderma sp., less than two thirds the size of M. godthelpi, is recognised from GAG LF (ibid.). Megadermatid indet., from HH LF, is a very small megadermatid which cannot be assigned to Macroderma (ibid.). Hand (1996) notes that the Dwornamor variant of M. godthelpi is intermediate in size between the small HH megadermatid and the large Gotham site M. malugara. In the HH LF there is therefore evidence for sympatry of very differently-sized megadermatids, while in the GAG LF there were two similarly sized, sympatric megadermatids from different lineages (ibid.).

The scincid Tiliqua pusilla, present in GAG LF, is a small species (less than 15cm long) not related to any previously known congeneric (Archer et al., 1997; 1996; Riversleigh book). Contrary to this, Archer et al. (1996) state that T. pusilla appears to be related to the living pygmy blue-tongue.

The pythonid Morelia riversleighensis (previously Montypythonoides) is present in the Litokoala-Muribacinus palaeocommunity. This species may be synonymous with M. antiqua from the early Miocene Bullock Creek fauna (Archer et al., 1997).

Palaeoenvironmental indicators According to the discriminant function analysis using 67 faunas, and incorporating all variables, GAG LF is classified as ‘wet forest’ (p = 0.99) while HH LF is classified as wet forest (p = 0.99) and dry open forest (p = 0.01) (see Chapter Four). On this basis it is likely that the vegetation structure (or degree of ‘openness’ of the upper stratum) of the Litokoala-Muribacinus palaeocommunity is most similar to extant Australian ‘wet forest’, at least as determined by body size structure.

However, according to the more reliable discriminant analysis (incorporating 114 faunas and with small mammal slopes removed) GAG LF is classified as closed forest (p

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= 0.08), wet forest (p = 0.86) and dry open forest (p = 0.06), and HH LF as wet forest (p = 0.24) dry open forest (p = 0.69) and woodland (p = 0.07). Given these results it is probable that the Litokoala-Muribacinus palaeocommunity was derived from an ecotone between wet and dry open forest. Species that are variably present within the palaeocommunity (Table 25), may therefore have occupied wetter or drier components of the habitat over time.

Among the defining and characteristic species only the phalangerid Trichosurus dicksoni has an extant congeneric. The living species of ‘brush-tail’ possum, T. vulpecula, occupies a diverse range of habitats, including rainforest, although it is more often found in open forests and woodland (Strahan, 1995).

Another potential palaeohabitat indicator species is Litokoala kanunkaensis. This phascolarctid is considered to be, with Phascolarctos, the derived sister-group of Nimiokoala (Black & Archer, 1997b). The living phascolarctid, P. cinereus, inhabits Eucalyptus wet forests and woodlands (Strahan, 1995).

Species that are variably present in the palaeocommunity’s constituent LF’s (Table 25) provide ambiguous evidence for the palaeohabitat. For instance, modern Bettongia ‘rat-kangaroos’, congenerics of B. moyesi, are confined to woodland and dry open forest (Strahan, 1995).

In contrast the four species of Pseudocheirops, none of which are present in both GAG and HH LF’s, have a living pseudocheirid congeneric which is confined to the Australia’s Wet Tropics upland rainforest (ibid.). Similarly, the living hypsiprymnodontid, Hypsiprymnodon moschatus, is restricted to rainforest of northern Queensland (ibid.).

A number of non-mammalian and chiropteran taxa are present in the Litokoala- Muribacinus palaeocommunity (Table 28). These taxa have variable utility as indicators of palaeoenvironment.

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Table 28: Non-mammalian and chiropteran species of the GAG and HH LF’s

(1= Present, 0= not present) Group High level taxon Family Species GAG HH Bats Macroderma godthelpi 1 0 Macroderma malugara 0 1 Megadermatidae Macroderma sp. 0 1

Indet. 0 1 Dwornamor variant 1 0 Hipposideriidae 1 1 Turtles 1 1 Snakes Boidae 0 1

Pythonidae Morelia riversleighensis 1 1 Anurans 1 1 Lizards Agamidae 1 1 1 1 Scincidae Tiliqua pusilla 1 0 Mollusca Gastropoda 1 1 Fish Lungfish 0 1 Crocodile 0 1 Birds Passeriformes 0 1 Casuariidae Emuarius gidju 1 0

Boles (1997a,b) suggests that Emuarius gidju had cursorial hind-limb proportions, but suggests that this does not exclude the possibility of dense rainforest at Riversleigh during the Oligo-Miocene as: 1) the groundcover of the rainforest may have been sufficiently open to allow rapid movement and 2) large rainforest mammals may have created runways through the rainforest undergrowth. Alternatively, Boles (1997a,b) suggests that E. gidju may have had open habitat preferences approaching those of the extant emu (Dromaius novaehollandiae).

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Boles (1997b) reports that passeriformes are good habitat indicators at specific and generic level. Unfortunately the Litokoala-Muribacinus passeriformes have not yet been identified at lower taxonomic levels.

The presence of turtles in the Litokoala-Muribacinus palaeocommunity as well as lungfish and crocodiles in one constituent local fauna (HH), suggests the presence of at least semi-permanent water-bodies. Archer et al. (1997) note that none of the seven species of Riversleigh lungfish are unique to Riversleigh and that none are of biostratigraphic value.

Indeterminate agamids are present in the palaeocommunity. Archer et al. (1996) indicate that some may be the same species as the living water dragon, Physignathus, while others are distinct species. All modern species of Physignathus occur close to the moist east coast (ibid.).

Creaser (1997) found GAG and HH sites to be tufa deposits dominated by terrestrial faunas. In contrast, ‘deep water pool’ deposits, such as RING Site, were principally thought to represent aquatic faunas (Creaser, 1997). However, the presence of indeterminate chelonian, crocodilian and lungfish taxa, as well as possible Physignathus spp., in the Litokoala-Muribacinus palaeocommunity implies that the difference may not be as marked.

The GAG LF, previously referred to as the Dwornamor LF (e.g. Hand, 1985; 1996; Archer et al., 1991), has been presented as a highly species-diverse LF indicative of a rainforest community equivalent to System B LF’s (e.g. Archer et al, 1995 ;1997). In particular, the presence of numerous ‘sympatric’ arboreal folivores has been cited as evidence of ‘…high floral diversity … a feature characteristic of rain forests but not of open forests’ (Archer et al., 1995). Confusingly, the HH LF has been variably presented as a highly species-diverse community similar to GAG LF (Archer et al., 1995) and a far less diverse community representative of the opening-up of Australia’s rainforests (Archer et al., 1997). Results herein suggest that only three arboreal folivores, Litokoala

______145 kanunkaensis, Marlu kutjamarpensis and M. sp1, can presently be ascribed to the Litokoala-Muribacinus palaeocommunity and are therefore possibly sympatric (Table 25). While the high diversity of species within each time-averaged LF is more indicative of relatively closed habitat structures, the body-size structure of these assemblages is more typical of extant Australian habitats with open upper vegetation stratum (see Chapter Four). P. Adams (pers. comm.) has suggested that the seemingly anomalous DFA results for HH LF (‘dry open forest’ and ‘closed forest’ classification) might be explained by the presence of deciduous vine thicket, a type of rainforest with dry open forest structure.

Synopsis of the Litokoala-Muribacinus palaeocommunity

The Litokoala-Muribacinus palaeocommunity is characterised by a diversity of ecomorphotypes, including: one medium sized browsing macropodoid (Ganguroo robustiter), one large omnivorous-carnivorous macropodoid (Ekaltadeta ima), one large browsing terrestrial diprotodontoid (Nimbadon lavarackorum), three medium arboreal folivores (Litokoala kanunkaensis, Marlu kutjamarpensis and Marlu sp1.), one tiny terrestrial-arboreal omnivorous possum (Burramys brutyi), one medium arboreal omnivore (Trichosurus dicksoni), five small-medium terrestrial-arboreal omnivorous- carnivorous yaraloid bandicoots (Yarala burchfieldi, Bulungu palara, Gunawidji tubus, Madju ignotae and Galadi amplus), and one medium sized terrestrial-arboreal carnivore (Muribacinus gadiyuli). The phalangerid, Trichosurus dicksoni, may have been the most abundant mammal within this palaeocommunity, comprising up to one quarter of all individuals. The burramyid, Burramys brutyi, was probably only slightly less abundant. The hypsiprymnodontid, Ekaltadeta ima, may also have been a significant contributor to overall abundance, which combined with a large average body size (about 16kg) suggests that this species also made up a large portion of overall body-mass for the palaeocommunity.

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Chapter 8 The Last Minute-Ringtail palaeocommunity

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The Last minute-Ringtail palaeocommunity

Last Minute (LM) and Ringtail (RING) sites are located in the northern section of Gag Plateau within the Riversleigh World Heritage fossil deposits. Archer et al. (1989, 1997) consider LM site to be a shallow pool accumulation belonging to ‘System C’ (middle Miocene). Creaser (1997) suggests that LM site is basal within the Gag Plateau Sequence, located at about 188m above sea level, adjacent to Gag, LD’94 and Jim’s Jaw sites. RING site is located approximately 4 metres higher (above sea level) than LM site, adjacent to Melody’s Maze site, and is considered to be a ‘deep water pool’ dominated by aquatic faunas (Creaser, 1997; Archer et al., 1989).

No species appear to define this palaeocommunity as none are exclusive to the two constituent local faunas. However, there are five characteristic species: 1) the burramyid Burramys brutyi; 2) the yaralid Yarala burchfieldi; 3) the yaralid Gunawidji tubus; 4) the yaralid Madju ignotae and 5) the pseudocheirid Parapops sp1 (Table 29).

Table 29: Characteristic species of LM-RING palaeocommunity

Higher level taxon Species Relative abundance NISP (%) Burramyidae Burramys brutyi 19.4-60 Pseudocheiridae Madju ignotae 2.8-2.9 Parapops sp1 2.8-2.9 Yaraloidea Gunawidji tubus 2.8-2.9 Yarala burchfieldi 2.8-8.6

Burramys brutyi is a dominant species within the palaeocommunity, with high to very high relative abundances. Yarala burchfieldi is also quite common, while the other two characteristic yaralids and pseudocheirid are far less abundant. These species-level abundances may, however, be heavily influenced by the smaller sample sizes resulting from fewer successful identifications at lower taxonomic levels.

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Table 30: Characteristic genera of the LM-RING palaeocommunity

Genus Relative abundance NISP (%) Pildra 2.6 Pseudocheirops 2.6 Burramys 18.4-55.3 Yarala 1.1- 5.3 Gunawidji 1.1 Madju 2.6 Parapops 2.6

The relative abundance of Burramys brutyi observed in the species-level results is supported at the generic level, with an only slightly lower range of NISP values (Table 30). The other characteristic monotypic genus, Yarala, also exhibits only slightly lower NISP values at the generic level.

Interestingly, this palaeocommunity is identifiable at the generic level, but apparently using only presence/absence data, not relative abundance (see Chapter Five). The LM & RING palaeocommunity cannot be readily distinguished at higher taxonomic levels.

Taxonomic representation

Diprotodontians The LM & RING palaeocommunity is characterised by the presence of two diprotodontian species, the burramyid Burramys brutyi and the pseudocheirid Parapops sp1. Other non-diagnostic species from constituent local faunas include the pseudocheirids Marlu kutjamarpensis, Marlu sp1, Pildra sp1 and Pildra sp4, as well as the pilkipildrid Djilgaringa gillespieae, the phalangerid Strigocuscus reidi, and the macropodoids Ganguroo robustiter and Wanburoo wulugu.

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Peramelemorphians The three remaining characteristic species of the LM & RING palaeocommunity are the yaraloid bandicoots Yarala burchfieldi, Gunawidji tubus and Madju ignotae. Two other bandicoot species, Bulungu palara and Galadi speciosus, are non-diagnostic and patchy members of the palaeocommunity, each being present in the constituent local faunas.

Dasyuromorphians No dasyuromorphian species are presently defining or characteristic for this palaeocommunity. However, one new species of the thylacinid Nimbacinus and an undescribed species of the dasyurid Barinya, are potential members.

Yalkaparadontian Yalkaparidon jonesi has been identified from the LM LF, but has not yet been recorded from RING LF. The status of this species as a definite member of the palaeocommunity is therefore presently ambiguous.

Monotremata The ornithorhynchid Obdurodon dicksoni is a potential member of the palaeocommunity as this species has been identified in the RING LF.

Notoryctemorphian Notoryctids are dubious members of the RING & LM palaeocommunity, given that the only record, for this typically abundant group, is one ulna from RING LF.

The LM & RING palaeocommunity is not as diverse as either the Litokoala- Muribacinus (with 47 identified potential mammalian species members) or Nambaroo- Balbaroo (with 57 potential mammalian species) palaeocommunities. Only 20 identified mammalian species constitute the pool of possible taxa within the LM & RING palaeocommunity (Table 31). The lower diversity of the latter may however be due to

______150 lower NISP values at all taxonomic levels (Figure 13; Figure 14; Figure 15). At the ‘superfamilial’ level LM LF has NISP values on par with those of GAG LF, but far less than HH LF. RING LF has only half the NISP of LM LF at this taxonomic level. At the species level LM and RING LF’s have similar NISP values (n = 35 and 36 respectively) which are significantly lower than those for GAG and HH LF’s (n = 77 and 54). Thus the total species NISP for the LM & RING palaeocommunity is about half that of the Litokoala-Muribacinus palaeocommunity.

The known body size distribution of identified, but variably present mammalian species, within the palaeocommunity ranges from a 21g Burramys to a 7.5kg Wanburoo (Table 31). However, the inclusion of an indeterminate acrobatid and an unidentified diprotodontid would increase this body size range significantly.

Although there is a diverse array of non-mammalian and chiropteran taxa, few have been identified to species (Table 32).

Archer et al. (1997) note that the mekosuchine crocodile Trilophosuchus rackhami is a monotypic genus unique to Riversleigh’s System C (middle Miocene) deposits.

The pythonid Morelia riversleighensis (previously Montypythonoides) is present only in the RING LF, and is therefore ascribed only tentative membership of the Litokoala-Muribacinus palaeocommunity. This species may be synonymous with M. antiqua from the early Miocene Bullock Creek fauna (Archer et al., 1997).

Ramphotyphlops from LM LF are blind burrowing snakes with many living congeners in Australia (Archer et al,. 1996). These are small, non-venomous snakes that feed on ants and termites (ibid.).

The madtsoiid snakes Yurlunggur and Wonambi are both present in the RING LF, but have not yet been found in the LM LF. Scanlon (1997) suggests that species of

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Wonambi possess shallow jaws with a limited ability to subdue prey, and hence focus on subduing prey through constriction.

Table 31: Variably present species of the LM & RING palaeocommunity

(1= present; 0= not present) Higher level Body taxon Species RING LM weight (g) Acrobatidae Acrobatid indet. 1 1 - Burramyidae Burramys brutyi 1 1 21 Dasyuridae Barinya sp2 0 1 123 Dasyurid indet. 1 0 - Diprotodontidae Diprotodontid indet. 0 1 - Macropodoidea Ganguroo robustiter 0 1 3896 Wanburoo wulugu 0 1 7567 Notoryctidae Notoryctes sp. 1 0 55 Ornithorhynchidae Obdurodon dicksoni 1 0 - Petauridae Petaurid indet. 1 0 - Phalangeridae Phalangerid indet. 1 0 - Strigocuscus reidi 0 1 7434 Pilkipildridae Djilgaringa gillespieae 0 1 415 Pseudocheiridae Marlu kutjamarpensis 1 0 504 Marlu sp1. 1 0 - Parapops sp1 1 1 750 Pildra sp.1 0 1 470 Pildra sp4. 1 0 - Pseudocheirops sp. 1 1 - Thylacinidae Nimbacinus nov. sp 1 0 5023 Wynyardiidae Namilamadeta sp. 1 0 - Yalkaparadontidae Yalkaparidon jonesi 0 1 280 Yaraloidea Bulungu palara 1 0 86 Galadi speciosus 1 0 766 Gunawidji tubus 1 1 200 Madju ignotae 1 1 783 Yarala burchfieldi 1 1 63

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Palaeoenvironmental indicators Very few of the identified mammalian species from the LM & RING palaeocommunity (or those that are variably present in the constituent LF’s) have living congenerics. Any palaeoenvironmental insight that can be gleaned from extant congeners is therefore limited. Indeterminate species of Pseudocheirops have been identified from both LM & RING LF’s. Extant P. archeri are presently confined to rainforest within the Wet Tropics region of north-eastern Australia.

Table 32: Non-mammalian and chiropteran species of the LM and RING LF’s (1= present; 0= not present) Group Family Species LM RING Fish Dipnoa 1 1 Bird Accipitridae 0 1 Cacatuidae 0 1 Passeriformes 0 1 Halcyonidae Gen. Indet. (Boles,1997a) 1 0 Melphahagidae 1 0 Orthonychidae Orthonyx kaldowinyeri 1 0 Bat Megadermatidae 0 1 Macroderma sp. 1 0 Hipposideridae 0 1 Rhinolophoidea 0 1 Amphibia Anura 1 0 Turtle Meiolaniidae 0 1 1 0 Chelidae Pseudemydura 0 1 Lizard Agamidae 0 1 Sulcatidens quadratus 0 1 1 0 Crocodile Trilophosuchus rackhami 0 1 Baru? 0 1 Mekosuchus sanderi 0 1 1 0 Mollusca Gastropoda 1 1

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Group Family Species LM RING Snake Pythonidae Morelia riversleighensis 0 1 Typhlopidae Ramphotyphlops 1 0 Madtsoiidae Yurlunggur 0 1 Wonambi 0 1

The non-mammalian fauna may be more useful for determining palaeoenvironmental conditions for the LM & RING palaeocommunity. Although presently very few of the LM LF taxa have been identified to species level, limiting the list of species that can be definitely attributed to this palaeocommunity.

An accipitrid (diurnal bird of prey) is present in the RING LF but has not yet been identified from the LM LF, suggesting that this taxon may not be characteristic of the LM-RING palaeocommunity. Boles (1997c) points out that extant accipitrids occupy a variety of habitats.

Boles (1997c) identified a cacatuid from RING LF, making this taxon another tentative avian member of the LM-RING palaeocommunity. The cockatoos are of little value in determining palaeohabitat as modern congeners occur in a variety of habitats from rainforest to arid country (Boles, 1997c).

The LM LF contains the sole representative of the halcyonidae, or the kingfishers, from Riversleigh. Boles (1997c) considered this taxon to be an early member of the Todiramphus lineage which has extant species which occupy rainforests outside Australia, but other habitats within Australia.

The LM LF also contains the only specimen of an orthonychid, or logrunner, from Riversleigh (Boles 1993;1997c). This genus has two living species, both of which live in rainforest of eastern Australia and New Guinea (Boles, ibid.).

Chelonians have been identified from both LM and RING LF’s, but only indeterminate taxa from the former. Meiolaniids and Pseudemydura sp. are recognised

______154 from the RING LF. According to White (1997) Pseudemydura, a short-necked chelid, is represented at Riversleigh by a single skull fragment and partial plastron, both from RING LF. The living species, P. umbrina is confined to swamps north of Perth (White, 1997). Chelid diversity increases from System A to System C and is indicative of increasing small, shallow or slow-moving aquatic habitats in the middle Miocene (ibid.). Meiolaniids were large, terrestrial turtles and during System B and C times had shells up to 1m long and body masses between 150 and 200kg (ibid.). White (1997) also suggests that any wet rainforest at Riversleigh must have had substantial clearings where meiolaniids could gain access to high fibre food and sunlight, as they probably required temperatures above 30 degrees Celsius.

The temperature requirements of the meiolaniid turtles are somewhat at odds with those of the anurans. Tyler et al. (1994) concluded that System B and C (early to middle Miocene) frog assemblages indicate persistent moisture at ground-level throughout the year, as well as mild temperatures not in excess of 25 degrees Celsius. Lechriodus intergerivus, with extant rainforest congenerics, decreases in abundance towards the upper Oligo-Miocene sequence at Riversleigh (Tyler et al., 1994). This evidence supports the hypothesis that the vegetation opened up and climate became increasingly drier during the middle Miocene.

Discriminant function analysis (see Chapter Four; 67 faunas & all variables) classifies the LM LF as ‘closed forest’ (p = 0.08) and ‘wet forest’ (p = 0.92) utilising body-size structure of representative modern mammalian faunas. Similarly, the vegetation structure of the RING LF is classified as ‘closed forest’ (p = 0.37), ‘wet forest’ (p = 0.60), ‘dry open forest’ (p = 0.01) and ‘woodland’ (p = 0.01). These results suggest that the vegetation (habitat) structure of the LM-RING palaeocommunity is most similar to extant Australian ‘wet forest’, possibly with significant areas of closed forest.

However the second DFA (114 faunas & small mammal slopes removed) reclassified the LM LF as closed forest (p = 0.27), wet forest (p = 0.72), dry open forest (p = 0.01) and woodland (p = 0.01). The RING LF was re-categorised as closed forest (p

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= 0.85), wet forest (p = 0.14) and woodland (p = 0.01). These more reliable results are equivocal, possibly indicating a mixed vegetation structure for the LM-RING palaeocommunity, probably with equivalent amounts of ‘closed’ and slightly more open ‘wet forest’.

A mixed habitat type for the LM-RING palaeocommunity, analogous to extant ‘closed’ and ‘wet forest’, might explain the possibly incongruous closed-forest requirements of some taxa and the apparent constraints of other taxa, such as meiolaniids, needing more open vegetation.

Synopsis of the Last Minute – Ringtail palaeocommunity

The Last Minute-Ringtail palaeocommunity is currently characterised by a low diversity of core mammalian species, including: one abundant to highly abundant, small terrestrial-arboreal omnivorous possum (Burramys brutyi), three small-medium terrestrial omnivore-carnivore bandicoots (Yarala burchfieldi, Gunawidji tubus and Madju ignotae), and one medium-sized arboreal folivore (Parapops sp1.). Identification of currently indeterminate acrobatids and pseudocheirids (Pseudocheirops sp) could, however, increase the pool of characteristic species. Even with the inclusion of transient or ambiguous species this palaeocommunity is clearly depauperate in medium-large browsers.

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Superfamilial NISP

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WH. Gag KCB COA Upper N.Gard Ringtail Hiatus W.Wok Henks H Last Min Mikes M Camel S

Figure 13: Superfamilial NISP

Generic NISP

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WH. Gag KCB COA Upper N.Gard Ringtail Hiatus W.Wok Henks H Last Min Mikes M Camel S

Figure 14: Generic NISP

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Specific NISP

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WH. Gag KCB COA Upper N.Gard Ringtail Hiatus W.Wok Henks H Last Min Mikes M Camel S

Figure 15: Specific NISP

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Chapter 9 The independent Local Faunas

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The Independent Local Faunas

Several local faunas (LF’s), White Hunter (WH), Hiatus (HI), Cleft-Of-Ages (COA), Keith’s Chocky Block (KCB) and Encore (ENC), could not be categorised into palaeocommunities by classification or ordination analyses. The inability of the various multivariate analyses to associate these LF’s with any of the three palaeocommunities, two palaeocommunity types, or each other, suggests that the former represent: 1) distinct time intervals; 2) distinct palaeoenvironments; 3) massively biased taphocoenoses or 4) significantly under-sampled or under- researched sites. These LF’s are synonymous with local palaeocommunities (sensu Bennington & Bambach, 1996).

The Hiatus Local Fauna Hiatus site is located on the northern side of Hal’s Hill to the south of Godthelp’s Hill (Creaser, 1997) (Figure 1). This site is basal in the sequence of sediments in this area and lies above Precambrian sediments (ibid.).

Just 17 mammalian specimens have been identified to at least superfamilial level within the Hiatus LF (Table 33). Despite the incredibly low NISP value over 50% of the specimens represent unique taxa. Nine of the 17 identified specimens are diprotodontoid.

Table 33: Faunal list for Hiatus Local Fauna

Class/Subclass Order Family/Superfamily Species Marsupialia Diprotodontia Wynyardiidae Phalangeridae Phascolarctidae Macropodidae Balbaroo sp. Diprotodontidae Silvabestius michaelbirti Bematherium angulum Vombatoidea Dasyuromorphia Dasyuridae

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Class/Subclass Order Family/Superfamily Species Thylacinidae Wabulacinus sp. Aves Snakes Boidae Madtsoiidae Pythonidae Lizards Varanidae Crocodiles Chelonia Anura Litoria rubelliformis Chiroptera Hipposideridae

Taxonomic representation Only five taxa from the Hiatus LF have been identified to at least generic level, and only three to species.

Diprotodontian taxa include a wynyardiid, a phalangerid, a phascolarctid, a balbarine macropodid (Balbaroo), two diprotodontids (Silvabestius michaelbirti and Bematherium angulum), as well as an unidentified vombatoid.

Only one indeterminate dasyurid has been recorded, as well as a thylacinid assigned to Wabulacinus (S. Wroe, pers. comm.). Interestingly peramelemorphians, which are common to very common (in both richness and abundance) in system B and C sites, have not been recorded from the Hiatus LF.

The HI LF has been considered to be a System A (late Oligocene) assemblage (e.g. Black, 1997b; Creaser, 1997). Both identified diprotodontid species are consistent with this suggestion. Black and Archer (1997a) consider Silvabestius michaelbirti to be the most plesiomorphic zygomaturine. Bematherium angulum is restricted to System A sites (Black, 1997b). Species of Balbaroo are less useful for determining age as they are found in all Systems (Cooke, 1997c). Wabulacinus species exhibit intermediate morphology between plesiomorphic Nimbacinus and derived Thylacinus, and are currently only known from System B faunas (Muirhead, 1997). The confirmation of HI LF as a System A assemblage would therefore extend the range of the latter species.

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Among the non-mammalian taxa the presence of frogs, as well as indeterminate crocodiles and turtles suggests the presence of at least a semi- permanent water body of large size.

Conclusions A lack of specimens and species level identification prevents the inclusion of this LF in the discriminant function analyses (see Chapter Four).

Classification and ordination analyses indicate that the HI LF has characteristics that distinguish it from most other LF’s investigated (see Chapter Five). Classification, using cluster analysis, indicated that HI LF did not regularly group with any LF, except at the superfamilial level (utilising abundance data) in which it clustered with COA LF. However, the latter grouping is probably a result of these LF’s having the lowest sample sizes at this taxonomic level, rather than being indicative of any similarity between the two LF’s. Most ordination analyses resulted in HI LF being isolated from all other LF’s and palaeocommunities within the study sample. Most commonly HI LF was closest to WH LF, with the exception of the species-level analysis (using presence/absence data) in which it was in closest proximity to ENC and KCB LF’s, as well as the superfamilial analysis (using abundance data) where it was located near MM LF.

Although clearly under-sampled, the HI LF mammalian component is currently characterised by an apparent abundance of large terrestrial browsers, medium-sized arboreal folivores and omnivores, a low diversity of medium-sized browsing macropodoids and vombatoids, as well as small(?)-medium sized carnivores.

Geological, topographical, phylogenetic and palaeoecological lines of evidence would therefore appear to confirm the categorisation of HI LF as a basal System A (late Oligocene) LF. Similarities to the WH LF include taxonomic representation, stratigraphic position as well as proposed environment of deposition.

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The White Hunter Local Fauna Introduction Myers & Archer (1997) suggested a late Oligocene dating for the White Hunter Local Fauna (WH LF) from the Riversleigh World Heritage Fossil Deposits, northwestern Queensland. The presence of the ilariid Kuterintja ngama, previously only known from the Ngama Local Fauna, Lake Palankarinna, provided the biocorrelative evidence for a dating of 24.7-25Ma (Myers & Archer, 1997). Subsequently a number of other plesiomorphic taxa have been identified by various authors and are discussed herein (e.g. Cooke, 1997c; Muirhead & Wroe, 1998). The synecology of the WH LF has not previously been discussed. Creaser (1997) considers White Hunter site to be basal within ‘System A’ (Archer et al., 1995) strata on the south side of Hal’s Hill (Figure 1).

Chiropteran and non-mammalian taxa The non-mammalian component of the WH LF comprises agamid and varanid lizards, crocodiles, bats, birds, fish, frogs, gastropods, snakes and turtles.

Riversleigh’s fossil agamids are believed to be endemic, while the varanids are yet to be studied systematically in any detail (Archer et al., 1997). Archer et al. (1996) discuss a species of Physignathus from Riversleigh which is similar to the living water dragon P. leseurii. No modern species of Physignathus occurs far from the moist east coast.

Willis (1997) describes four new crocodilian species from the White Hunter Local Fauna: 1) the large, broad-snouted Baru wickeni; 2) the smaller, broad-snouted Baru huberi; 3) the small, short-snouted Mekosuchus whitehunterensis and 4) the ziphodont Quinkana meboldi. Willis (1997) offers two hypotheses for the high level of diversity in a single local fauna: 1) the four species are sympatric and niche differentiation was achieved by differing cranial morphology and subsequent exploitation of different prey; and 2) alternatively, the fauna represents a thanatocoenosis from at least two different habitats (with overlapping ranges for the crocodilians).

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The chiropteran Rhinonicteris tedfordi is present in the WH LF. This species has not been recorded from any system C sites (Hand, 1997a). Hand (1997a) notes that the extant R. aurantius roosts in very warm, humid caves from NW QLD to NW WA. It feeds at night on moths, beetles, wasps, ants, weevils and other insects. Although the extinct and extant species are similar in many morphological characters it is not certain that they were ecological equivalents (Hand, 1997a).

Hand et al., (1998) considers Icarops aenae from the Wayne’s Wok LF to be the most plesiomorphic species of Icarops, and I. paradox from NG LF to be the most derived. Hand et al., (1998) suggests that the cranial morphology of these species is indicative of consuming very hard prey. It is also suggested that the Miocene mystacinids roosted in limestone caves, foraged for insects or fish over water. S. Hand (pers. comm.) also recognises Icarops sp. from Upper site and the WH LF.

The vespertilionid recorded from WH LF appears to be dubious, given that the only Oligo-Miocene vespertilionid from Australia is a single specimen of Leuconoe from Riversleigh’s RV site (Archer et al., 1997).

A solitary tooth is the only tentative record of Macroderma from WH LF. This species might be Macroderma godthelpi, currently restricted to early Miocene Riversleigh sites (Hand, 1996; Archer et al., 1997), or a new species.

Boles (1997c) identified ciconiid limb and skull elements from WH and Bitesantennary LF’s. These elements could not be referred to the Australian genus Ephipphiorhynchus, but are similar to Ciconia from Eurasia, South America and Africa (Boles, 1997c).

According to Boles (1997c) there are at least two dromornithids present within the Riversleigh deposits: Barawertornis tedfordi and Bullockornis planei. Boles (1997c) suggests that dromornithids were gregarious herbivores, although Wroe (1999) has indicated a more carnivorous diet for some.

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The casuariid Emuarius gidju, present throughout Riversleigh’s systems (Boles, 1997b) has also been identified from the WH LF (Boles, 1997c).

Snakes recorded from the WH LF have been tentatively assigned to the pythonid Morelia sp. nov., the pygopodid Ramphotyphlops sp. and the madtsoiid Yurlunggur sp. Archer et al. (1997) note that madtsoiids are typically diverse in system A and lower system B, with few pythonids, while the situation reverses in upper system B and system C sites.

Indeterminate frogs, turtles, fish and gastropods have been recorded from the WH LF. System A turtles are typically large chelids, with extant counterparts that inhabit large flowing rivers and deep water bodies, while those from Systems B and C are smaller with thinner shells (White, 1997).

Mammalian taxa and body size distribution A high diversity of diprotodontian species (76% of mammalian species) is evident in the WH LF. Macropodoids make up the bulk of these species (55% of diprotodontians), vombatomorphians are the next most diverse (23% of diprotodontians), followed by petauroids (14%) and the burramyoids and tarsipedoids (each with one species or 4.5% of diprotodontians). However, the vombatomorphians are at a higher taxonomic level than the other superfamilies, and if subdivided into constituent families yield: 1) ilariids, wynyardiids and diprotodontoids – one species each and 2) thylacoleonids with two species (9%). The sole diprotodontid, Bematherium angulum, is restricted to System A sites (Black, 1997b)

The WH LF is the only Riversleigh LF to produce ilariids, thus far. Kuterintja ngama ties WH LF with the Ngama LF of the Etadunna Formation at Lake Palankarinna, northern South Australia (Myers & Archer, 1997). At approximately 14kg average body weight this ilariid would have been about the size of a small- medium dog, and probably about the length of the extant common wombat (Vombatus ursinus) albeit it far more gracile.

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The closely related wynyardiid (Myers & Archer, 2001), Namilamadeta sp., was smaller than the ilariid at about 11kg. Archer et al. (1997) note that wynyardiids were common in systems A and B but are absent from system C.

Balbarine kangaroos include four species of Nambaroo, one species each of Balbaroo, Wururoo and Ganawamaya. Bulungamayine kangaroos are represented by one species of Wabularoo and Gumardee. The hypsiprymnodontid Ekaltadeta ima is also present.

Body size distribution The WH mammalian fauna ranges from a 13g acrobatid to a 127kg diprotodontid. And the size of the latter may well be an underestimate, due to extrapolation beyond the range and the fact that the dental predictor used (UMRL) underestimates diprotodontians (see Chapter Two).

There is a high diversity of macropodoid species in the WH LF, with up to 12 species. It is unlikely that all these species were sympatric and that at least some are transient members of the fauna, or have habitat ranges which overlap. However, supporting the argument for sympatry is the differentiation of body sizes among the macropodoids (Table 34). Only four macropodoid taxa have estimated body weights within about 2% of each other. The two potoroids, Nowidgee magnamatrix and Gumardee sp., share a body weight of approximately 3.8kg. Similarly, the potoroid Wabularoo naughtoni and the macropodid Ganawamaya aediculis have body weights of about 4.3kg. Both latter species are lophodont herbivores and probably occupied very similar niches.

Cooke (1997b;c) identifies species of Nowidgee as bunolophodont omnivores. Gumardee sp., tentatively assigned to the Bulungamayinae (Cooke, 1997b), was presumably also omnivorous given its bunodont dentition (Flannery et al., 1982). It is therefore likely that these two species had different behavioural attributes if they were sympatric.

The WH LF potoroids are bettong (Bettongia) to small rock wallaby (Petrogale) sized animals. The macropodids range from the size of extant quokkas

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(Setonix) to larger rock wallabies (Petrogale) such as the brush-tailed rock wallaby. There is, however, much overlap in body sizes between the two groups, particularly from three to five kilograms.

Ekaltadeta ima is a swamp wallaby (Wallabia bicolour) to Agile Wallaby (Macropus agilis) sized macropodoid. S. Wroe (pers. comm.) suggests that the weight of approximately 16kg may be an underestimate given the robust nature of the cranium.

Flannery et al. (1982) suggest that Gumardee pascuali is of comparable size to Wabularoo naughtoni. The body sizes presented here suggest that these kangaroos are similar in size, with W. naughtoni being some 10% larger than Gumardee sp., although the record for the latter is only tentative.

Cooke (1997c) states that Nowidgee matrix is only found in System B, so the presence of this species in the WH LF would extend the range to System A. Cooke (1997c) also suggests that System A sites can be characterised by roughly equal diversity of balbarines and bulungamayines. The WH LF has 7 balbarines and 4 bulungamayines, and as such is believed to be a basal System B site (Cooke, 1997c). However, the WH LF is dominated by plesiomorphic balbarines and bulungamayines, such as species of Nambaroo and Nowidgee (ibid.). Additionally, Nambaroo albovenator is also found at Dunsinane site, which is believed to be a System A site (Arena, 1997).

Priscileo roskellyae and P. pitakantensis (the latter originally assigned as Wakaleo nov. sp. by A. Gillespie (pers. comm.)) are recognised from the WH LF. P. roskellyae, found in System A and B sites, is the most plesiomorphic thylacoleonid (Gillespie, 1997). P. pitakantensis has been recorded from the late Oligocene Ngapakaldi LF (25.3Ma), older than the Ngama LF with which the WH LF has been correlated (Myers & Archer, 1997). Consequently, the temporal range of either this species or Kuterintja ngama will be extended.

The difference in size between these two, possibly sympatric, congeneric thylacoleonids is remarkable, as P. pitakantensis is at least 12 times heavier than P.

______167 roskellyae (Table 34). Wroe (1999) suggests that P. roskellyae was about the size of a domestic cat and possibly concentrated on arboreal prey. At approximately 3kg P. roskellyae falls within the average weight range of a female Felis catus (Strahan, 1995). P. pitakantensis, in contrast, has an average body weight of about 38kg (Gillespie and Myers, unpublished data). Wroe et al. (1999) estimated an average body weight of between 44-56 kg for the holotype of Wakaleo vanderleueri. The initial difficulties in determining the taxonomic affinities of the White Hunter specimen of P. pitakantensis suggest that the estimate of 38kg is reasonable.

Valverde (1964, 1967; cited in Legendre, 1986) found that predators are typically intermediate in body size between their prey species. It is therefore conceivable that P. roskellyae had a diverse range of prey to choose from within the WH LF, including bandicoots, pseudocheirids, the petaurid, acrobatid, burramyid, yalkaparadontid, as well as the nine macropodoids up to the size of Wururoo dayamayi. Strahan (1995) notes that the domestic cat (Felis catus) has hampered the reintroduction of Lagorchestes hirsutus (weighing about 1.5kg) in Australia. Nowidgee matrix, of comparable size to the living Lagorchestes hirsutus, may have been particularly vulnerable to predation by P. roskellyae.

The leopard-sized P. pitakantensis, like species of Wakaleo, was probably an ambush predator (Wroe, 1999). The larger diprotodontian species, such as Kuterintja ngama, Nambaroo gillespieae, N. albovenator, Ekaltadeta ima, and Namilamadeta sp., may well have been the predominant prey species of P. pitakantensis. It is unlikely that adult Bematherium angulum would have regularly fallen prey to this thylacoleonid, although juveniles were probably taken. As an arboreal, ambush predator, and given the low abundance of specimens, it is unlikely that any thylacoleonid conspecifics cooperated when hunting.

Muirhead and Wroe (1998) suggest that some smaller Oligo-Miocene thylacinids, such as the highly plesiomorphic Badjcinus turnbulli, were ecomorphological equivalents of medium to large, semi-arboreal extant dasyurids. Wroe (submit) postulates an average body mass of approximately 2.4 kg for Badjcinus turnbulli, well within the body size range of the extant dasyurid Dasyurus

______168 maculatus which has a comparable average mass of approximately 3.2 kg for males and 1.8kg for females (Myers, 2001). The estimate of 2.4kg is significantly smaller than that estimated here (3.6kg), although the former is probably more accurate as it was derived from a more reliable cranio-dental variable (LMRL; see Myers, 2001). D. maculatus is partly arboreal, possessing pedal adaptations such as sole striations for this lifestyle (Strahan, 1995). In addition to carrion D. maculatus is known to take prey ranging from insects to birds and small wallabies, with medium sized mammals constituting up to two thirds of its diet (ibid.). A similar locomotory and trophic habitus is here suggested for Badjcinus sp.

Other insectivorous to carnivorous taxa in the White Hunter local fauna, potentially occupying a similar dietary niche to Badjcinus sp., include a medium sized thylacinid (Nimbacinus sp.) with a body size of approximately 5kg, a hypsiprymnodontid weighing at least 16kg on average (Ekaltadeta ima), two species of thylacoleonid (Priscileo sp. and Priscileo pitakantensis) and at least four perameloid species (Yarala burchfieldi, Bulungu palara, Gunawidji tubus and Madju ignotae) (Myers, 2001).

The perameloids range in size from 63g to 783g and were primarily insectivorous to carnivorous, in contrast to extant Australian bandicoots which are insectivorous to omnivorous (Muirhead and Filan, 1995). Any dietary competition between thylacinids and perameloids would have been minimal given the probable abundance of invertebrate prey, and probably only extended to larger insect or lizard- sized prey. It may also be significant that perameloids appear to have a low abundance and biomass, relative to other Riversleigh LF’s (Myers, unpublished), allowing for larger numbers of potential competitors.

Birds and possums may well have comprised the primary diet of the smaller thylacoleonid, with Badjcinus concentrating on ground dwelling perameloids and birds. The leopard-sized Priscileo pitakantensis would almost certainly have preyed upon all the macropodoid species, both adult and juveniles.

Other arboreal marsupial taxa include: 1) Yalkaparidon sp. which was about the size of an extant Squirrel Glider (Petaurus norfolcensis); 2) Burramys brutyi,

______169 about the size of the extant Eastern Pygmy Possum (Cercartetus nanus) and half the weight of its extant congeneric Burramys brutyi (the Mountain pygmy possum); 3) an acrobatid, well within the weight range of the extant feathertail glider, Acrobates pygmaeus; 4) a petaurid that was slightly smaller than the extant species Petaurus breviceps; and 5) the pseudocheirids, Parapops sp.1 (small compared to extant Australian pseudocheirids) and Pseudocheirops sp.2 (about the size of the extant Pseudocheirus peregrinus). Interestingly, Strahan (1995) notes that A. pygmaeus commonly falls prey to foxes, cats and large dasyurids, perhaps suggesting that the WH acrobatid was regular prey for late Oligocene size-equivalent predators such as Priscileo roskellyae and Badjcinus turnbulli.

Table 34: Marsupial faunal list for White Hunter Local Fauna Order Family Species Body Weight (g) Diprotodontia Ilariidae Kuterintja ngama 13700 Wynyardiidae Namilamadeta sp. 10447 Diprotodontidae Bematherium angulum 127370 Burramyidae Burramys brutyi 21 Acrobatidae Indet. gen. et sp. 13 Pseudocheiridae Parapops. sp1 750 Pseudocheirops sp2 931 Petaurid gen2 sp1 Petauridae 95 (RivSpet) Macropodidae Nambaroo gillespieae 8040 Nambaroo albovenator * 7699 Nambaroo camilleriae 5427 Balbaroo hatchae* 4787 Nambaroo couperi* 3126 Wururoo dayamayi* 5841 Ganawamaya aediculis 4375 Potoroidae Nowidgee magnamatrix* 3825 Nowidgee matrix 1524 Wabularoo naughtoni 4312 Gumardee sp. 3865 Hypsiprymnodontidae Ekaltadeta ima 16358 Thylacoleonidae Priscileo pitakantensis? 38000

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Priscileo roskellyae 2969 Peramelemorphia Yarala burchfieldi 63 Bulungu palara 86 Yaralidae Gunawidji tubus 200 Madju ignotae 783 Dasyuromorphia Badjcinus turnbulli 3578 Thylacinidae Nimbacinus sp. 5023 Yalkaparadontia Yalkaparadontidae Yalkaparidon sp. 280

* = unpublished macropodoid species (B. Cooke, unpublished PhD thesis)

Palaeoenvironmental indicators At least 9 mammal species (31%) from the WH LF exhibit adaptations for, or have extant congenerics that indicate, some degree of arboreality. Brammall (1998) states that up to three petauroid species, possibly in two genera, are undescribed from Riversleigh. The White Hunter species is the smallest of these undescribed species. Open forests are the domain of the extant, gliding petaurids (Brammall, 1998).

Archer et al. (1997) indicate that Pseudocheirops species from Riversleigh are more closely related to the extant P. archeri than they are to the more diverse living New Guinean species. The arboreal folivore, P. archeri, is restricted to dense upland rainforest in the Wet Tropics of Queensland (Strahan, 1995).

The extant Australian acrobatid, Acrobates pygmaeus, does not help to clarify the habitat requirements of the WH acrobatid, as it is found in woodlands and dry open forest but is more frequently located in tall, moist forests (ibid.).

The presence of a burramyid is also not very useful as a palaeoenvironmental indicator as the living species, Burramys parvus, is presently restricted to a tiny area of alpine New South Wales and Victoria, and inhabits rocky areas within its range.

From a palaeoenvironmental aspect the presence of ciconiids (storks) are of only limited value, as they are associated with shallow, slow moving water but not restricted to aquatic environments (Boles, 1997c). Ciconiids are not known to enter forested areas (ibid.).

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There are at least two herbivorous and gregarious dromornithid genera present within the Riversleigh deposits, including Barawertornis tedfordi and Bullockornis planei (Boles, 1997c). The Riversleigh fossils do not show cursorial adaptations and are therefore thought to have been forest dwellers (ibid.). Wroe (1999) has suggested a more carnivorous diet for some dromornithids.

Boles (1997c) suggests that the casuariid Emuarius gidju was more cursorial than extant Casuarius and to an extent that may have approached that of the living emu Dromaius novaehollandiae. E. gidju may have had similar ecological requirements as the latter, therefore possibly inhabiting open country or rainforest with an open understorey.

The presence of four, possibly sympatric, crocodilian species suggests that a large, semi-permanent body of water was present at White Hunter during the late Oligocene.

Archer et al. (1997) suggest that System A sites are generally less diverse than those in Systems B and C, and that the palaeoenvironments of these late Oligocene sites was probably mesic forests of an unknown nature.

Discriminant function analysis incorporating 67 extant Australian faunas and including small slope data (see Chapter Four) categorised WH LF as closed forest (p = 0.02), dry open forest (p = 0.01) and open woodland (p = 0.97). However, a more reliable DFA utilising 114 extant Australian faunas and excluding small slope variables identified WH LF as closed forest (p = 0.67), dry open forest (p = 0.33) and woodland (p = 0.01). The latter results suggest that the WH LF palaeoenvironment was far less open than that indicated by the first DFA.

The uniqueness of the WH LF is confirmed by classification and ordination analyses (see Chapter Five). In cluster analysis the WH LF grouped mainly with MM LF at the generic and super-familial levels using relative abundance data. This grouping may however be more related to the low sample sizes and NISP values for each LF, rather than any real similarity between the two LF’s. In the ordination analyses the WH LF is generally isolated from other clusters. This is most

______172 pronounced at the species level using abundance data. Generally the WH LF is situated between HI and LM LF’s.

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Taphonomic investigations of the late Oligocene White Hunter Site

Studies concerning the Riversleigh World Heritage Fossil Deposits, north- western Queensland, have focussed primarily upon taxonomy, phylogeny and, more recently, palaeoecology. Taphonomy, the study of the biases and processes affecting animal remains as they move from the biosphere to the lithosphere (Efremov, 1940; Olson, 1980), is in its infancy at Riversleigh and has generally been neglected or given only summary consideration (e.g. Arena, 1997; Boles, 1997c). However, taphonomy is an important and necessary process in any meaningful palaeoecological analysis. Characteristics of palaeocommunities, such as species richness and diversity, can be greatly biased by taphonomic factors. Taphonomic biases have been presumed to be minimal in the Riversleigh deposits, given that preservation is usually exceptional, and that most sites exhibit a diverse array of taxa and body sizes. Typically a large range of elements are also preserved, often without obvious signs of transport. Archer et al. (1991, 1995, 1996) suggest that most Riversleigh sites formed primarily as shallow pools, caves or fissure-fill deposits. Megirian (1992) concluded that the environment of deposition was principally a humid alluvial fan, and that fossiliferous sites of deposition were minor components within a karst terrain. To date nothing has been published regarding the taphonomy of White Hunter and, apart from autecological analyses of restricted taxonomic groups (e.g. Willis, 1997), little in the way of palaeoecology.

The White Hunter Local Fauna (WH LF), located in the Riversleigh World Heritage Fossil Deposits, has been tentatively dated as late Oligocene by Myers & Archer (1997). A suite of distinctive and phylogenetically primitive taxa reinforce the pre-Miocene dating for this site, with at least 5 unique macropodoid species including extremely plesiomorphic balbarines (Nambaroo spp.) and bulungamayines (Nowidgee spp.), (Cooke, 1997c). Muirhead & Wroe (1998) note the presence of Badjcinus turnbulli, a phylogenetically basal thylacinid, from White Hunter.

White Hunter site is located on the southern side of Hal’s Hill on the Riversleigh World Heritage Fossil area in northwestern Queensland. White Hunter

______174 has been placed basally within System A, as a result of its low stratigraphic and topographic position, combined with the primitive suite of fauna relative to other Riversleigh LF’s (Archer et al., 1997; Creaser, 1997). Myers and Archer (1997) provided a date of 24.6Ma for the WH LF after correlation with the Ngama LF from Lake Palankarinna in northern South Australia. The lithology is primarily calcilutite, mud to silt sized particles cemented with a calcite matrix. X-Ray Diffraction analysis (XRD) performed on rock samples from White Hunter site identified kaolin and quartz as very minor mineralogical components, while calcite constituted the majority of the sample.

Methods A total of 372 mammalian postcranial elements were examined. Each element was identified and tentative taxonomic assignments made. Distinguishing postcranial elements beyond Family or Superfamily proved difficult, principally because postcranial descriptions have not been undertaken for the bulk of Riversleigh species. The degree of weathering, abrasion and fragmentation were also noted following published methodologies (e.g. Behrensmeyer (1975, 1978), Coombs & Coombs (1997) and Voorhies (1969)).

Results

Taxonomic representation There is no obvious taxonomic bias in the White Hunter Local Fauna (WH LF). Mammalian elements range from those of a 13g acrobatid to the 127kg diprotodontid Bematherium angulum (Table 34). Additionally, small to large avifauna, crocodilians, turtles, bats, birds, fish, frogs, lizards and snakes are present. There appears to be no obvious bias against small vertebrates. Respectively, macropodoids comprise 65%, vombatomorphians 18%, dasyuromorphians 9%, peramelemorphians 6% and non-macropodoid phalangeridans 2% of postcranial elements in the bone assemblage.

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Breakage of elements Breakage of skeletal elements were recorded following the categorization of Coombs & Coombs (1997), as 1) complete; 2) partial - up to 50% of the element missing and 3) fragmentary - over 50% of the element missing (Figure 16).

In the White Hunter assemblage it is clear that metapodials and podials have for the most part resisted breakage, as have, to a lesser degree, epiphyses and phalanges (Figure 16). Coombs & Coombs (1997) note that long bones, ribs, vertebrae, girdle and cranial elements are susceptible to splitting, shattering and crushing as a result of trampling, while podials, phalanges, sesamoids and metapodials are resistant to breakage. Epiphyses, being for the most part relatively compact cuboid elements, are similar in morphology to other resistant elements, and would therefore be expected to be resistant to trampling. In contrast, girdle elements, vertebrae, ribs and epipubics are mostly partially preserved in White Hunter. Limb elements, while being generally more complete than the girdle, vertebrae, ribs or epipubics, also exhibit the greatest proportion of fragmentary postcranials. It is highly unusual for limb elements to exhibit any breakage, even under high flow regimes (Behrensmeyer, 1991).

There does not appear to be any suggestion of carnivore/scavenger preferential selection for femoral elements, with eight distal and seven proximal portions preserved within the White Hunter assemblage. Sample size is, however, particularly low. Coombs & Coombs (1997) suggest that distal femur heads should be preferentially preserved over proximal if carnivore selection is a taphonomic factor in the accumulation of an assemblage. Furthermore, there is little evidence of carnivore/scavenger damage on the elements, with only two specimens exhibiting potential puncture marks. A handful of elements exhibit tiny grooves, which may be the result of small scavenger activity. Trampling may be the primary cause of breakage for White Hunter skeletal elements.

Voorhies Group Analysis The complete skeletal set was categorized into respective Voorhies Groups according to the groupings constructed by Voorhies (1969) and later modified by

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Behrensmeyer (1975). These groupings reflect a spectrum of decreasing susceptibility of skeletal elements to transport, such that Group I elements are removed immediately, through to Group III elements representing a lag deposit (Voorhies, 1969). Macropodoid elements were analysed separately following Cassiliano (1997) and compared to an ‘average’ extant macropodid. This analysis suggests that Voorhies Groups 1 and 1\2 are significantly under-represented in the White Hunter assemblage, while Voorhies Groups 2\3 and 3 are consequently over- represented (Figure 17). The presence of elements from all 3 categories militates against high flow regimes and suggests that elements are primarily autochthonous (Coombs & Coombs, 1997). The Voorhies Group (VG) comparison of White Hunter macropodoids with an ‘average’ extant macropodoid suggests that some winnowing of VG’s 1 and 1\2 has occurred, resulting in a subsequent increase to VG’s 2\3 and 3 (Figure 18).

Behrensmeyer (1975) suggests that selective removal of skeletal elements can be identified in a bone accumulation by analysis of tooth/vertebrae ratios. Vertebrae, belonging to Voorhies group 1, will be more easily removed by fluvial activity than teeth which belong to Voorhies group 3. Most T/V ratios are close to 1 for untransported fossil assemblages, 1.5 from lake bed environs and are greater than 3 for channel and floodplains Behrensmeyer & Boaz (1980).

The tooth/vertebrae ratio of 2.24 for the White Hunter assemblage suggests that there has been some selective removal of vertebrae. Interestingly, this value falls between that for the Pleistocene channel fossil assemblages of the Koobi Fora Formation (3.12) and the Recent Lake Bed Amboseli bone assemblage (1.44) reported by Behrensmeyer & Boaz (1980). This may be coincidental but does suggest that there has been some selective removal of vertebrae by winnowing but not to the degree observed in a channel or floodplain environment.

Abrasion of skeletal elements Abrasion categories follow Coombs & Coombs (1997): 1) unabraded; 2) slight; 3) moderate; 4) substantial; 5) extensive. Overall, 17% of White Hunter elements are unabraded, 28% exhibit slight abrasion, 40% moderate levels of

______177 abrasion, 14% substantial and just 1% with extensive abrasion (Figure 19). Therefore nearly half of the elements show none or ambiguous levels of abrasion. No taxonomic grouping exhibits correlation with levels of abrasion, therefore suggesting that most taxa were members of a proximal community.

Weathering of skeletal elements 50% of White Hunter skeletal elements show no sign of weathering, while 34% ambiguous levels of weathering, 13% are moderately weathered, only 0.3% (1 element) have mosaic weathering on articulation surfaces as defined by Coombs & Coombs (1997) and just 3% are flaking (Figure 20). Therefore only 15% of elements can definitely be assigned as having been weathered to any degree. According to Behrensmeyer (1978) these results suggest that that 84% of the White Hunter elements were exposed for less than 1 year and 97% less than 3 years, with just 3% spending from 2-6 years exposed (assuming equivalent weathering rates).

Conclusions The three conditions required for an autochthonous assemblage are found in the White Hunter assemblage: 1) all Voorhies groups are well represented; 2) the skeletal elements are not hydraulically equivalent to the matrix and 3) the elements are for the most part unweathered and unabraded (Coombs & Coombs, 1997; Behrensmeyer, 1975).

The fact that most elements are unweathered could be interpreted as being indicative of minimal time-averaging, as elements encompassing all weathering stages would be expected to have accumulated over long periods of time. However countering this argument is the fact that weathered elements are less likely to be fossilised, and the observation that most fluvial and attritional assemblages lack significant quantities of weathered bone (Behrensmeyer et al., 2000).

Long bone elements are not easily broken by fluvial activity (Coombs and Coombs, 1997; Behrensmeyer, 1991). The high number of partial and fragmentary long bone elements (limbs), combined with the high frequency of unabraded elements, in the White Hunter assemblage therefore suggests processes other than

______178 vigorous fluvial transport were taking place during deposition of the White Hunter material.

In addition, the lack of association and complete disarticulation of elements suggests that elements were disturbed shortly after deposition and prior to burial, either by: 1) hydrodynamic processes; 2) the activity of scavengers or predators; or 3) trampling of elements during seasonal drying, perhaps by large Bematherium. The lack of predation scars on virtually all elements militates against crocodile or scavenger activity. Furthermore, the mode of accumulation was unlikely to have been cave deposition, given the degree of disarticulation and association of elements, as well as the lack of geological cave structures, such as speleothems, or cave lithology.

Deposition in water is known to cause rapid disarticulation of skeletal elements (Behrensmeyer, 1991). In addition, the presence of a large, semi-permanent water body is suggested by the fauna. For example, Willis (1997) described four new sympatric crocodilian species from the White Hunter Local Fauna (WH LF). Sympatry was suggested by the degree of morphological variation in the crania and the potential for occupation of different niches. It is unlikely that such a diverse guild of crocodilians could survive in anything other than a large, semi-permanent water body. The aquatic nature of the WH LF is also indicated by a diverse turtle, frog and fish fauna. White (1997) suggests that the turtle fauna from early Riversleigh sites (i.e. late Oligocene System A and earliest Miocene System B) were large-sized inhabitants of bigger or faster flowing water bodies. In contrast, turtles from later sites (middle to late Miocene) were smaller, adapting to lower flow regimes or small water bodies (White, 1997).

The lack of fluvial facies or well-rounded bone elements implies that the depositional environment for the WH LF was more lacustrine then fluvial. Taphonomic evidence for minor winnowing is indicative of some type of current into a lacustrine environment, perhaps from a small ephemeral creek.

The WH LF has been tentatively dated as late Oligocene (Myers & Archer, 1997), a period that is characterised worldwide by ‘Icehouse’ conditions (Archer et

______179 al., 1995; 1997). Taxonomic fidelity should be greater in cool and/or dry climates, where bones have higher preservation potential (Behrensmeyer et al., 2000). It could therefore be expected that, from a taphonomic viewpoint, the taxonomic representation in the WH LF is probably more reliable than in later ‘Greenhouse’ Miocene LF’s. Seasonal icehouse conditions may also explain the ephemeral nature of the White Hunter water-body and consequent trampling of surface and sub-surface skeletal material.

120

100

80 entire 60 partial frag. 40

20

0

rib limb vert podial girdle phalanx metapod. epiphyses epipubics

Figure 16: Element breakage (%) at White Hunter (entire, partial & fragmentary)

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0.4

0.35

0.3

0.25 inc. epiphyses 0.2 exc. epiphyses 0.15

0.1

0.05

0 VG1 VG1or2 VG2 VG2or3 VG3

Figure 17: Voorhies Group analysis of White Hunter skeletal elements (%)

0.4

0.35

0.3

0.25 Total 0.2 WH roos Avg roo 0.15

0.1

0.05

0 VG1 VG1or2 VG2 VG2or3 VG3

Figure 18: Voorhies group comparison of total WH skeletal elements, WH macropodoids and an ‘average’ macropodoid (%)

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0.45 0.4 0.35

0.3 0.25

0.2 0.15 0.1 0.05 0 12345

1 = unabraded; 2 = slight; 3 = moderate; 4 = substantial; 5 = extensive

Figure 19: Abrasion stages of White Hunter skeletal elements (%)

0.6

0.5

0.4

0.3

0.2

0.1

0 abcde a = weathering absent; b = ambiguous weathering; c = moderate; d = mosaic; e = flaking

Figure 20: Element weathering stages in White Hunter LF (%)

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The Cleft-Of-Ages Local Fauna Cleft-Of-Ages (COA) site is located in the southern section of the Gag Plateau within the Riversleigh World Heritage Fossil deposits (Creaser, 1997(Figure 1). Creaser (1997) notes that the stratigraphy in this section is complex as the sediments are not limited in lateral extent, are significantly different in age and are not horizontally bedded. Creaser (1997) also suggests that COA is easily recognisable as a fissure-fill deposit due to its lithology. Black (1997b) concludes that COA belongs in System C (sensu Archer et al., 1991, 1995). Alternatively Cooke (1997c) postulated that COA site could belong in Systems A or B (early Miocene), and Gillespie (cited in Creaser 1997) considers it to be system B.

In classification and ordination analyses (see Chapter Five) COA LF variably groups with other, primarily independent, LF’s. Below familial level COA LF inconsistently groups with various LF’s in cluster analysis, depending on the clustering algorithm and type of data employed (i.e. presence/absence or relative abundance). Using superfamilial presence/absence data in cluster analysis COA LF frequently grouped with KCB LF. However, COA and HI LF’s clustered together more often when relative abundance data was used. Familial presence/absence cluster analyses resulted in COA grouping with ENC LF.

Similar to the cluster analyses the ordination results varied, in regards to the grouping of COA LF, depending on the particular multivariate methodology employed. PCA analyses (of presence/absence data) consistently grouped COA LF with KCB LF at all taxonomic levels. DCA analyses (using log abundance data), in contrast, linked COA LF with: 1) the MM LF at the specific level; 2) KCB LF at the generic level; 3) KCB LF and the GAG & HH cluster at the level of superfamily.

Taxonomic representation Taxonomic diversity is quite high within the COA LF despite relatively low NISP values at all taxonomic levels (NISP=152 at superfamilial level) (Figure 13; Figure 14; Figure 15).

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Diprotodontians Vombatomorphian taxa include at least two diprotodontid species, small and medium sized thylacoleonids, as well as one vombatoid (sensu Myers et al., 1999) (Table 35). Macropodoids include the hypsiprymnodontids Hypsiprymnodon cf. bartholomaii and both known species of Ekaltadeta, as well as at least one bulungamayine. Arboreal ‘possums’ include at least one indeterminate phalangerid, Burramys brutyi and three pseudocheirids.

Ekaltadeta jamiemulvaneyi has previously only been recorded from the late Miocene Encore LF (Archer et al., 1997; see this chapter). Interestingly, COA LF was consistently associated with Encore LF in only the family level cluster analyses (utilising presence/absence data).

Diprotodontids and macropodoids comprise the bulk of identified specimens, together constituting over 76% of ‘superfamilial’ NISP (see Appendix One).

Peramelemorphians Only one small yaraloid bandicoot, Gunawidji tubus, has so far been identified from the COA LF. Indeed, perameloids are remarkably uncommon in the COA LF, representing only 1.3% of NISP at ‘superfamilial’ level.

Dasyuromorphians At least one small dasyurid, possibly Barinya, has been tentatively identified as well as the thylacinid Nimbacinus sp.

The mammalian ecodiversity of COA LF is therefore characterised by at least two species of large terrestrial browsing diprotodontoids, small-large omnivorous macropodoids, at least three species of medium-large carnivores, small-medium arboreal folivores, a medium-sized terrestrial browser, one medium-sized browsing macropodoid, one medium arboreal omnivore, as well as only two small terrestrial omnivore-carnivores. Relative to other LF’s analysed in this study this LF is depauperate in medium browsing macropodoids and ‘bandicoot’ taxa.

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Table 35: Faunal list for Cleft-Of-Ages Local Fauna

Order Family Species Body weight

Marsupials Diprotodontia Neohelos gregoriaei 135596

Neohelos sp. - Diprotodontidae Silvabestius sp. 37231

Nimbadon/Silvabestius.? sp. -

Ekaltadeta ima 16358

Hypsiprymnodontidae Ekaltadeta jamiemulvaneyi 10396

H. cf. bartholomaii 632

Burramyidae Burramys brutyi 21

Potoroidae Bulungamayine gen. et sp. indet. -

Wakaleo oldfieldi ~ 50000 Thylacoleonidae Priscileo cf. roskellyae 2969

Pseudocheiridae Marlu sp.2 -

Pseudocheirops sp.2 931

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Marlu kutjamarpensis 504

Vombatoidea Rhizophascolonus sp. -

Macropodidae Wururoo gadiyuli 8427

Phalangeridae Gen. et sp. indet. -

Dasyuromorphia Thylacinidae Nimbacinus sp. 5023

Gen. et sp. indet. - Dasyuridae Barinya? 426

Peramelemorphia Yaralidae Gunawidji tubus 200

Anurans

Snakes Pythonidae?

Boidae?

Birds

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Palaeoenvironmental indicators Results of the discriminant function analysis (DFA; see Chapter Four), utilising 67 faunas and all variables, identifies the vegetation structure of the COA LF as analogous to extant Australian ‘dry open forest’ (classified with 100% probability). The potentially more reliable DFA utilising 114 extant faunas (see Chapter Four) but excluding small mammal variables variably reclassifies COA LF as ‘dry open forest’ (p = 0.99) and woodland (p = 0.01). These results are not significantly different and strongly indicate that the COA LF was derived from an open forest type, probably with equivalent upper vegetational strata to living ‘dry open forest’. It should be noted that these results utilised body-size structure alone. It was necessary to remove the two large Neohelos spp. from the analysis to allow classification, as these were outlier species. However, the inclusion of these species would only have increased the likelihood of classification as more open forest types, as the mean body size and standard deviation tend to increase with the ‘openness’ of the vegetation (see Table 17). Never the less, other sources of palaeoenvironmental evidence need to be investigated to confirm the interpretation

Other palaeoenvironmental evidence is largely equivocal, but trends towards interpretation of COA LF as being drier and more open than many other LF’s investigated herein.

A species of Pseudocheirops and Hypsiprymnodon would tend to suggest a closed environment, as indicated by extant congenerics. However, extremely low yaralid diversity, the presence of a vombatoid, large abundances of both macropodoids and diprotodontids (perhaps moving in mobs), low diversity of arboreal mammals, as well as the connection of COA with the late Miocene ENC LF through the presence of Ekaltadeta jamiemulvaneyi, indicate a drier and relatively more open habitat type.

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The Keith’s Chocky Block Local Fauna Creaser (1997) considers Keith’s Chocky Block (KCB) site, located on the southern section of Gag Plateau, to be a fissure-fill deposit. A. Morell (pers. comm.) considers KCB to be an atypical ‘fissure-fill’, forming initially as a closed-depression (e.g. doline) by internal drainage within a karst terrain, followed by an accumulation of soil within a karstic “hollow”. This differs from the traditional definition of a fissure-fill forming as tectonic fractures opened by solution (A. Morell, pers. comm.). There is little evidence for hydrodynamic sorting with any rounding of bone elements being caused by in-situ solution. Associated remains imply that at least some of the fauna died in the immediate vicinity of the deposit, while the high degree of fragmentation of others indicates extreme bio-turbation or sedimentary slumping. There is also some evidence from bandicoot age-spectra that pitfall-trap mechanisms were operating (A. Morell, pers. comm.).

Taxonomic representation

Yaraloids account for the majority (72%) of specimens identified to at least superfamily, with macropodoids accounting for approximately 21% and petauroids the next most abundant with about 4% of specimens. Burramyids, usually one of the most abundant of taxa, represent just 1% of NISP values.

Diprotodontians Diprotodontians dominate the mammalian taxa in the KCB LF, with one phalangerid (possibly a new species of cuscus; K. Crosby (pers. comm.)), a burramyid, petaurid and one pseudocheirid (Table 36). There are numerous macropodoid species, although only one, Hypsiprymnodon sp., has been tentatively identified. Similarly, one thylacoleonid, Wakaleo sp., is recorded. Additionally, there is one unidentified diprotodontid.

Yalkaparadontians One indeterminate Yalkaparidon species is known from the KCB LF.

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Peramelemorphians Despite the relative abundance of specimens none of the yaraloids has been identified to genera or species

Dasyuromorphians Only two specimens have been identified as dasyurid (S. Wroe, pers. comm.).

The mammalian contribution to the ecodiversity of this LF can therefore be characterised as including: medium sized arboreal omnivores, medium-large terrestrial browsers, a medium-sized carnivore, at least one species of medium terrestrial omnivore, relatively few small terrestrial-arboreal omnivores, small arboreal insectivore-nectivores, as well as an abundance of small terrestrial carnivore-omnivores.

Table 36: Species present in the KCB LF

Order Family Species Marsupials Diprotodontia Phalangeridae Diprotodontidae Macropodoidea Thylacoleonidae Wakaleo sp. Hypsiprymnodontidae Hypsiprymnodon sp. Burramyidae Burramys brutyi Petauridae Pseudocheiridae Paljara nancyhawardae Dasyuromorphia Dasyuridae Peramelemorphia Yaralidae Yalkaparadontia Yalkaparadontidae Yalkaparidon sp. Snakes Anuran Crocodile Chiropterans

Not enough of the KCB mammalian species have been identified to species level to allow for inclusion of this LF within the discriminant function analysis (see Chapter Four).

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Cluster analysis indicated that the KCB LF grouped at higher taxonomic levels (familial and superfamilial) with ENC and COA LF’s, using only presence/absence data (see Chapter Five). That these LF’s did not cluster at lower taxonomic levels may be an artefact of the lack of species and generic level identifications for the KCB LF. Ordination results also support the similarity of KCB LF with ENC and COA LF’s, particularly using presence/absence data. Relative abundance data variably indicates proximity of KCB LF to the Nambaroo-Balbaroo palaeocommunity (at specifies and generic level) and to the Litokoala-Muribacinus palaeocommunity (at superfamilial level).

The geographical proximity of KCB site to ENC, as well as the topographical position and palaeoecological affinities, may indicate that KCB is a late System C (middle Miocene) or even late Miocene assemblage.

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The Encore Local Fauna, a late Miocene assemblage from Riversleigh, northwestern Queensland

TROY MYERS, KIRSTEN CROSBY, MICHAEL ARCHER AND MICHAEL TYLER

MYERS, T., CROSBY, K., ARCHER, M. & TYLER, M., 2001:12:20. The Encore Local Fauna, a late Miocene assemblage from Riversleigh, northwestern Queensland. Memoirs of the Association of Australasian Palaeontologists 25, 147-154. ISSN 0810-8889

The Encore Local Fauna from the Riversleigh World Heritage property of northwestern Queensland is reviewed. The assemblage includes gastropods, fish, amphibians, reptiles, birds and mammals. The derived nature of many taxa and inferences of their habitus from morphology suggest a late Miocene age for the site and a relatively open environment.

T. Myers and K. Crosby, Vertebrate Palaeontology Laboratory, School of Biological Science, University of New South Wales, New South Wales, 2052; M. Archer, also Australian Museum, 6-8 College St., Sydney, New South Wales, 2000; M. Tyler, Department of Zoology, University of Adelaide, Adelaide 5001, South Australia.

Keywords: Encore site, Encore Local Fauna, Alcoota, Riversleigh, Queensland, Miocene.

The Alcoota (8-7 Myr) and Ongeva (6-5 Myr) local faunas (LFs), from the Northern Territory, and the Victorian Beaumaris (~6 Myr) Local Fauna are the best known of Australia’s rare late Miocene fossil deposits (Archer et al., 1995). However, a significant contribution to our limited knowledge of this time period may be forthcoming with the discovery of Encore Site. Situated at the southern end of the Gag Plateau Sequence (Creaser 1997), it is currently the only late Miocene site so far recognised from the Riversleigh fossil deposits in northwestern Queensland. Those containing systems B and C assemblages (Archer et al., 1995, Creaser 1997) have been regarded to be early (system B) or middle (system C) Miocene in age. Palaeohabitats interpreted for these assemblages have been rainforest. Encore Site, because it contains many taxa

______191 that are more derived than those found in systems B and C assemblages, has been hypothesised (Archer et al., 1995) to be late Miocene in age.

The Encore LF includes birds, gastropods, fish, frogs, turtles, lizards, madtsoiid and elapid snakes as well as a diverse range of mammals. It is however, the derived nature of many of the marsupial species that distinguishes this LF from other Oligo-Miocene assemblages at Riversleigh. The Encore Site is, for example, the only LF at Riversleigh to produce hypselodont vombatids (referable to Warendja). Two dasyuromorphians, Ganbulanyi djadjinguli and Mayigriphus orbus, have affinities with derived dasyurines and sminthopsines respectively (Wroe 1997a, 1998). In addition, at least one palorchestid, a phascolarctid and several macropodoids exhibit relatively derived features.

Taxic representation

Dasyuromorphians At least three dasyuromorphians are present in the Encore LF (Table 37): 1) Ganbulanyi gjadjinguli; 2) Mayigriphus orbus and 3) Thylacinus sp. cf. T. macknessi. Possibly a derived sister taxon to Barinya wangala from Riversleigh’s system B deposits, G. gjadjinguli may share the greatest number of apomorphies with the Tasmanian Devil, Sarcophilus harrisii (Wroe, 1998). Arena et al. (1998) present a possible middle Miocene record for G. gjadjinguli (from RRR site on the Gag Plateau, Riversleigh), and also postulate a bone cracking or possibly molluscivorous diet for the taxon. Preliminary investigations (Myers, unpublished) suggest G. gjadjinguli may have slightly outweighed extant Dasyurus maculatus which have an average male weight of 3.2 kg (Jones 1997).

Mayigriphus orbus, potentially the most derived pre-Pliocene dasyurid, has synapomorphies uniting it with species of Planigale but importantly shares no unequivocal synapomorphies with the dasyurid or thylacinid clade. The lack of a basicranium and upper dentition for this taxon further confounds its phylogenetic placement. Wroe (1997a) indicates that M. orbus is comparable in body size to Planigale maculatus, although work in progress by one of us (TM)

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suggests this may be a significant underestimate. Thylacinus sp. cf. T. macknessi adds little to information regarding the antiquity of this fauna because T. macknessi has already been recorded from late Oligocene (system A) to middle Miocene (system C) deposits at Riversleigh.

Table 37: The Encore Local Fauna.

Family Species /Superfamily

Mollusca Gastropoda

Fish Dipnoa

Amphibia Lechriodus intergerivus Tyler, 1989 Anura Other indeterminate spp.

Turtles Indeterminate

Lizards Tiliqua sp. cf. T. pusilla Shea and Hutchinson, 1992

Scincidae Sphenomorphous sp.

Egernia sp.

Snakes Madtsoiidae Nanowana sp. indet.

Elapidae Hydropheinae nov. gen.

Marsupials Dasyuroidea Ganbulanyi gjadjinguli Wroe, 1998

Mayigriphus orbus Wroe, 1997a

Thylacinidae Thylacinus sp. cf. T. macknessi

Perameloidea Indeterminate

Phascolarctidae Phascolarctos sp.

Vombatidae cf. Warendja sp.

Wakaleo vanderleuri Clemens and Thylacoleonidae Plane, 1974

Diprotodontidae Neohelos sp.

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Family Species /Superfamily

Palorchestes anulus Black, 1997a Palorchestidae Palorchestes sp.

Macropodoidea Ekaltadeta ima Archer and Flannery, 1985

Ekaltadeta jamiemulvaneyi Wroe, 1996a

Wanburoo hilarus Cooke, 1999

Wanburoo sp.

Ganguroo sp. nov. (larger than G.

bilamina)

cf. Hadronomas sp.

Burramys brutyi Brammall and Archer, Burramyidae 1997

Phalangeridae Trichosurus sp.

cf. Pseudocheirops sp. Pseudocheiridae pseudocheirid gen. indet.

Petauroidea New genus & sp.

Bats Megadermatidae Macroderma sp.

Many other bat spp. ~12 spp.

Birds 2 indeterminate spp. (1 starling sized)

Diprotodontians Diprotodontians are very common in the Encore assemblage, in both specific and generic representation. Although abundant diprotodontians characterise Riversleigh’s local faunas, such as the highly diverse System B Neville’s Garden Local Fauna, the percentage in the Encore assemblage may be higher due to the absence of several non-diprotodontian groups such as

______194 notoryctemorphians and yalkaparadontians, combined with a deficiency of peramelemorphians (Figure 21).

One damaged upper molar from Encore represents the whole family Phascolarctidae. However, this taxon is probably congeneric with, and similar in size to, the extant koala, Phascolarctos cinereus (K. Black, pers. comm.). Because living phascolarctids are confined to sclerophyll forest and woodland habitats, presence of a congener at Encore may be support for the hypothesis that during Encore times this area was not covered by rainforest.

Vombatids in the Encore LF are represented by a species referable to Warendja. The hypselodont and hypsodont Pleistocene W. wakefieldi is the only other species known. In the Riversleigh sequence this genus is only known from Encore Site. The open roots and high crowns of the molars suggest that this vombatid had adapted to eating coarser plant material. While modern wombats are grazers, it is possible that species of Warendja were focused on other types of abrasive leaves or woody vegetation.

Other vombatomorphian taxa recovered from Encore include diprotodontoids. Neohelos sp. may be useful for refining the age of the Encore assemblage. Another species of Neohelos, yet to be described is confined to system A (late Oligocene) of Riversleigh, while two others are restricted to system C (middle Miocene) and late system C (late middle Miocene) respectively (Black 1997b.). Neohelos tirarensis, in contrast, is temporally widespread throughout the Riversleigh deposits. Palorchestes anulus (Black 1997a) is morphologically intermediate between the middle Miocene Propalorchestes novaculacephalus, from Bullock Creek and Riversleigh’s system C deposits, and Palorchestes painei from the late Miocene Alcoota LF (8-7 myo; Murray & Megirian 1992), adding weight to the argument for an early late Miocene age for Encore.

Included among macropodoids at Encore are two species of the propleopine genus Ekaltadeta, three bulungamayine species and a Hadronomas-

______195 like species. Ekaltadeta jamiemulvaneyi, a possibly omnivorous-carnivorous hypsiprymnodontid macropodoid (Wroe 1996a), has only been discovered at the Encore and Cleft of Ages sites at Riversleigh. Wroe (1996a) suggests that this species is approximately 50% larger than E. ima, a longer ranged species that is also found at Encore.

The three bulungamayine species are Ganguroo sp., Wanburoo hilarus and W. sp. Ganguroo sp., a completely lophodont species, is larger than G. bilamina, which is only known from Riversleigh system B sites (Cooke 1997b;c). W. hilarus and the slightly smaller W. sp. are confined to system C sites at Riversleigh such as Gag site and Henk’s Hollow site. The two species of Wanburoo are highly derived in their lophodont molar and dental canal morphology, as well as being macropodid-like in many features, prompting a comparison with late Miocene Dorcopsoides fossilis and Hadronomas puckridgi (B. Cooke, pers. comm.). These species may also be the precursors of plesiomorphic macropodids which first appear in the late Miocene Alcoota LF (B. Cooke, pers. comm.). Another Hadronomas-like species may also be present in the Encore fauna.

The burramyid, Burramys brutyi, which is ubiquitous throughout the Riversleigh deposits, is also known from Encore. Brammall & Archer (1997) found a size decrease in this species through time, although the Encore specimens suggested a reversal in this scaling trend. Brammall & Archer (1997) also noted that Encore burramyids grouped with younger system C sites, as opposed to older system B populations, in various morphometric analyses. All pre-modern Burramys are thought to have occupied rainforest, although the extant B. parvus occupies alpine areas of southeastern Australia.

Two pseudocheirid species have been recovered from Encore, representing an indeterminate genus and a species of cf. Pseudocheirops. Of these, cf. Pseudocheirops sp. is known only from Riversleigh’s system C sites such as Henk’s Hollow, Jim’s Carousel and Main Site. The Encore specimen of this taxon appears to be much larger than those from other sites. All living

______196 species of Pseudocheirops inhabit rainforest environments except Pseudocheirops (Petropseudes) dahli, which inhabits rocky woodlands.

Brammall (1998) recognises two new petaurid genera and at least three new species from the Oligo-Miocene deposits of Riversleigh. The Encore species is included within the smaller of the two genera (J. Brammall, pers. comm.).

The single phalangerid species present at Encore probably represents a species of Trichosurus, but different to that already described from Riversleigh. T. dicksoni was originally thought to span early to middle Miocene sediments at Riversleigh; however it is now restricted to System C sediments. Modern species of Trichosurus occur in both rainforest and more open habitats.

During the early late Miocene at Riversleigh carnivore niches were filled not only by dasyuromorphians but also by marsupial lions, such as Wakaleo vanderleuri from the Encore site. Wakaleo species are present throughout Riversleigh’s deposits, although W. vanderleuri has presently only been recovered from the Encore site at Riversleigh and the middle Miocene Bullock Creek fauna (A. Gillespie, pers. comm.; Clemens & Plane 1974, Murray et al., 1987).

Peramelemorphians Perameloid bandicoots from Riversleigh systems A, B and C represent a new family (Muirhead & Filan, 1995). To date, just one perameloid specimen of indeterminate generic and specific status has been recovered from Encore.

Non-mammalian taxa There remains much to be done regarding the non-mammalian taxa from Encore Local Fauna. Many of the non-mammalian taxa have yet to be identified below familial or subfamilial level (Table 37).

i) Anurans: Lechriodus intergerivus is ubiquitous throughout late Oligocene and early Miocene sites at Riversleigh, although a decline in

______197 abundance is apparent towards the middle Miocene. Of 46 anuran individuals represented at Encore, only one represents L. intergerivus (Archer et al. 1997). Species of Lechriodus today occupy rainforest environments.

ii) Gastropods and lungfish are ubiquitous in the Oligocene and Miocene deposits of Riversleigh. The identity of the lungfish has yet to be determined. Both groups suggest the presence of at least semi-permanent pools of water.

iii)Snakes: One madtsoiid specimen (five associated vertebrae) referable to Nanowana sp. has been recovered from Encore. There are currently two species of Nanowana known from Riversleigh: N. godthelpi and N. schrenki. These are unfortunately indistinguishable in their vertebrae morphology. If Encore is late Miocene in age, this specimen would represent the youngest record for the genus (J. Scanlon, pers. comm.).

Encore elapid (Hydropheinae) material is more extensive, comprising a maxilla, dentary fragment, ribs and more than 20 vertebrae. Scanlon (1995) regards this material as representing a new genus and notes that it is consistent with being derived from one individual.

iv) Lizards: Scincid lizards from Encore include species of Egernia and Sphenomorphous, as well as Tiliqua sp. cf. T. pusilla (C. Williams & M. Hutchinson, pers. comm.). Tiliqua is well known from Pleistocene to Recent deposits, but has only one Pliocene (Wellington Caves) and a tentative early Miocene (Kutjamarpu LF) record, while T. pusilla was first described from the middle Miocene Gag LF at Riversleigh (Shea & Hutchinson, 1992). Species of Sphenomorphous and Egernia are known from desert to rainforest environments.

Birds: At least two species are present and one appears to be a starling- sized songbird (W. Boles, pers. comm.).

Turtles: None of the Encore turtle material has yet been identified (A. White, pers. comm.)

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Determining the age of Encore site There are few stratigraphic or lithologic reasons for postulating a younger age for Encore site. Creaser (1997) suggests that Encore “…could represent a tufa deposit incised into pre-existing Tertiary limestone”, as well as mentioning the lithological similarity of Encore sediments to other sites in the area. Hence evidence based on biocorrelation and phylogeny are the only methods for estimating the age of the Encore assemblage.

The Alcoota LF (8-7 Myr), from the Northern Territory, is devoid of any mammalian taxa smaller than Pseudocheirops sp. (about 1.5 kg), with the possible exception of undetermined peramelemorphian and dasyurid specimens (Murray & Megirian, 1992; contra Murray, 1997). The palaeoenvironment has been interpreted as ephemeral fluvio-lacustrine within subtropical savannah and localised open-forest (Murray & Megirian, 1992). The rarity of arboreal mammals is suggested as further evidence for a lack of, or scarce, proximal forest (ibid.). However, it is curious that of all the Alcoota species, only the casuariids are categorised by Murray (1997) as browsers/grazers. The remaining species are either scavengers, predators or browsers. The mammalian herbivores at Alcoota are typified by species with low-crowned molars and closed roots (Murray, 1997). None of the marsupial taxa are pre-adapted for a filling a grazing niche.

The Alcoota taxon, Wakaleo alcootaensis, is considerably larger than W. vanderleuri present in the Encore LF. A. Gillespie (pers. comm.) considers these species to be members of a morphocline which increased body size with time. Similarly, Kolopsis torus (Alcoota) may be the ecological successor of closely related, ecomorphologically similar species of Neohelos (such as Neohelos sp. from Encore). Additionally, Thylacinus potens (Alcoota) is considerably larger than Thylacinus sp. cf. T. macknessi (Encore). Given that thylacinids have increased body size with time, and the generally plesiomorphic nature of the Encore thylacinid, it is reasonable to conclude that the latter is an antecessor of the Alcoota thylacinid (S. Wroe, pers. comm.). Black (1997a) considers

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Palorchestes anulus from Encore to be structurally intermediate between Propalorchestes novaculacephalus and Palorchestes painei from Alcoota.

Many Encore taxa are derived relative to those from systems A, B and C from Riversleigh, or to other Oligocene or Miocene deposits. For example, compared with other Miocene dasyuromorphians, both G. djadjinguli and M. orbus are highly derived. The presence of a species of the derived phascolarctid genus Phascolarctos also suggests a younger age than any other Oligocene or Miocene phascolarctid-bearing deposit in central or northern Australia. Regardless of which Neohelos species is present in the Encore LF, the genus is clearly derived relative to other Riversleigh zygomaturine diprotodontids (Black & Archer 1997a). Furthermore, absence of Ekaltadeta jamiemulvaneyi from system A, B and C sites suggests a post-system C age for Encore. Similarly the three Encore bulungamayines exhibit a derived macropodid-like morphology, compared with other Oligocene and Miocene macropodoids, particularly in the degree of development of lophodonty. The Hadronomas-like macropodid also appears to suggest a post-system C and pre-Alcoota age for Encore.

Palaeoenvironmental indicators Encore taxa exhibit adaptations to closed or relatively open forest environments, while many also provide evidence of environmental change. For example, the hypselodont teeth of cf. Warendja sp. are unique to Encore Site at Riversleigh and represent the only pre-Pleistocene site to have this genus represented (Myers et al., 1999). The development of hypselodont molars in this Encore vombatid suggests evolution of the ability to utilise abrasive vegetation, which is more characteristic of open than closed forest environments.

The Encore taxon Phascolarctos sp., a congener of the extant phascolarctid found in open forests and woodlands, also suggests a relatively open forest palaeoenvironment. Similarly, the diprotodontoids are low-crowned browsers suited to forested environments, as are the bulungamayine macropodoids, although the derived nature of the lophodont molars evident in the latter species is indicative of a coarser diet.

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The virtual absence of peramelemorphians from Encore may be due to taphonomic factors. However this seems unlikely given the high relative abundance and species richness of bandicoots in the majority of Riversleigh sites, regardless of taphonomic or palaeoecological considerations. A more parsimonious explanation for the rarity of this rainforest group of perameloids at Encore may be environmental change.

With the exception of Tiliqua gigas, extant Tiliqua are not found in closed forest habitats. Shea and Hutchinson (1992) suggest that Tiliqua may have had greater diversity in the past or that the extant open-country species were derived from a small rainforest ancestor. In contrast, species of the phalangerid Trichosurus are today found in rainforest and open forest environments.

Conclusions Relative to other Oligocene-Miocene assemblages from Riversleigh, the Encore LF comprises many phylogenetically derived taxa. In relation to the Alcoota LF, however, the reverse situation seems to apply, with a number of Encore species appearing morphologically primitive and/or ecological predecessors to closely related Alcoota species. It is therefore reasonable to conclude that the Encore LF is older than the Alcoota LF, estimated to be 8-7 myr (Murray & Megirian, 1992), yet younger than Riversleigh system C LFs (approximately 15-10 myr, Archer et al., 1995). These restrictions suggest that Encore is early late Miocene, approximately 9 myr.

While many Encore species exhibit morphological characteristics of closed forest taxa, it is clear that some species, at least, were better suited to more open forest environments. It is possible that Encore site represents mixed communities, although a greater diversity of species, taxonomic richness and niche overlap would be likely if this were the case.

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Acknowledgments Vital financial support for the Riversleigh Project has come from the Australian Research Grant Scheme, the National Estates Grant Scheme (Queensland), the University of New South Wales, the Commonwealth Department of Environment, Sports and Territories, the Queensland National Parks and Wildlife Service, the Commonwealth World Heritage Unit, Earthwatch Pty Ltd, ICI Australia, the Australian Geographic Society, the Queensland Museum, the Australian Museum, the Royal Zoological Society of New South Wales, the Linnean Society of New South Wales, Pasminco, Surrey Beatty and Sons and the Riversleigh Society. Vital assistance in the field has come from many hundreds of volunteers as well as staff and students of the University of New South Wales.

All co-authors have agreed that this paper can constitute a chapter of this thesis. M. Archer was responsible for some editing and compilation of the pseudocheirid list. K. Crosby was responsible for some editing and compilation of phalangerid taxa. M. Tyler provided faunal lists for anuran taxa. T. Myers conducted all analyses and wrote the paper.

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90

80

70

%spp (Encore) 60

%gen (Encore) 50

%spp (N.G.)

40 %gen (N.G.)

30

20

10

0 Dasy. Dip. Pera. Other

Figure 21. Taxonomic representation by Order of marsupials in Encore Local Fauna compared to Neville’s Garden Local Fauna (% species and % genera).

Dasy. = Dasyuromorphians; Dip. = Diprotodontians; Pera. = Peramelemorphians; Other = Yalkaparadontians + Notoryctemorphians + Monotremata

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Additional palaeoenvironmental indicators for the Encore LF Discriminant function analysis (DFA) using 67 extant Australian faunas (Chapter Three) indicated that the vegetation structure (or degree of ‘openness’) for the Encore LF was most similar to modern woodland (p = 0.79), dry open forest (p = 0.16), open woodland (p = 0.02) or closed forest (p = 0.03). However, the more reliable DFA incorporating 114 extant faunas, and excluding small mammal variables, suggests far fewer possibilities: closed forest (p = 0.02), dry open forest (p = 0.39) and woodland (p = 0.59).

These results are consistent with the palaeoenvironmental conclusions mentioned above, indicating that the vegetation structure for the Encore LF was most similar, in regards to the ‘openness’ of the upper vegetation stratum, to extant Australian woodland, although possibly with significant areas that were more ‘closed’ and analogous to dry open forest.

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Chapter 10 Conclusion

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CONCLUSIONS

The determination of body-size in fossil mammals is intrinsically interesting, but also plays a vital role in understanding palaeobiology and, probably more importantly, the synecology of palaeocommunities. Much has been published on the determination of body-size, as well as its application in palaeoecology, for eutherian mammals. However, very little research has been done on the appropriateness of these methodologies for marsupial taxa. Similarly, few palaeoecological studies have been attempted for Australian fossil faunas. Indeed, for the Riversleigh World Heritage Fossil Deposits the focus has been on autecological and systematic analyses. This study has attempted to expand the Riversleigh research focus from autecology to synecology.

For the first time an extensive set of cranio-dental equations have been produced for predicting body mass exclusively in marsupials. Of all the equations, those produced for the dasyuromorphian dataset were found to be the most accurate, exhibiting the lowest error statistics. Among the cranio-dental variables premolar parameters are poor predictors of body mass. First lower molar area, often cited as the best dental predictor variable for all mammals, was found to be a poor determinant of body mass in marsupials. For composite dental variables lower molar row length is a good predictor for dasyuromorphians but not so for diprotodontians. Upper molar row length is better for all taxonomic groups other than dasyuromorphians. Among cranial variables total skull length is a good predictor for marsupials in general, but more so for diprotodontians than dasyuromorphians. In general, multivariate regressions are more useful than univariate, although lower molar row length and total jaw length are better as individual predictors for dasyuromorphians and diprotodontians respectively. Other salient results include the observation that restricted taxonomic datasets should be used where possible, and confirmation that correlation coefficients are not reliable for determining the predictive power of body mass equations.

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Cenograms have been used extensively by palaeomammalogists to determine palaeoenvironmental characteristics including vegetation structure and climate. Previous to this study the reliability of cenograms, or body size moment statistics, for interpreting Australian datasets had not been adequately tested. Results suggest that moment statistics may be better for determining vegetational structure than cenogramic ‘gaps’. The latter is, however, reasonably well associated with the ‘openness’ of the vegetation for extant Australian faunas. Neither moment statistics nor cenogram variables are particularly useful as an indicator of precipitation-related parameters. Similarly, for determining climatic characteristics only the mean (log-transformed) is marginally useful for indicating mean minimum temperatures.

The application of cenogram methodology in palaeoecological analyses of world-wide faunas has been confused in its approach. The determination of cenogramic ‘slopes’ and ‘gaps’, as well as understanding of the scales at which cenograms are meaningful, has been inconsistent. Additionally, the removal of ‘carnivorous’ taxa has not been adequately justified, and in relation to Australian faunas is unnecessary. Given the dubious empirical basis for most cenogram parameters there has been a tendency to over-interpret cenogram results. Many palaeoecological analyses that have drawn heavily upon cenogram interpretations may need to be revised.

Multivariate analyses, such as discriminant function analysis, incorporating cenogram, body-size distribution moment statistics and species richness variables are more reliable for determining vegetation structure than methods including only a few parameters. Removing variables associated with cenogramic small and medium-large mammal gradients improves the reliability of classification. The cenogramic ‘gap’ between small and medium sized mammals (at 500g) was found to be the most useful variable in DFA. A gap in size distributions at 3.5kg was also identified as being useful, suggesting that other gaps may have to be investigated as having possible palaeoecological implications.

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A number of local faunas (LF’s) from the Riversleigh World Heritage Fossil Deposits were included in the DFA. This analysis identified extant Australian broad forest types that have similar upper stratum vegetation structure, or degree of ‘openness’, to the fossil faunas, based on the body-size distribution of their constituent non-volant mammalian communities. The late Oligocene White Hunter LF was therefore interpreted as being most analogous to extant closed forest, but possibly with significant open patches that were equivalent in the degree of openness to dry open forest. The early Miocene Camel Sputum and Upper LF’s could not be classified, suggesting a species- rich closed to wet forest with no living analogue in Australia. Neville’s Garden and Wayne’s Wok LF’s (also early Miocene) are most analogous in their upper stratum vegetation structure to extant wet forest, perhaps with significant areas of closed canopy. The Mike’s Menagerie LF was found to have similarities to extant wet forest with minor possibilities of more closed and dry open forest vegetation structure, although low sample size may have affected interpretations for this LF. The middle Miocene Last Minute LF grouped with extant wet forest, with the possibility of areas of closed forest. Ringtail LF is interpreted as being most analogous to extant closed forest with minor areas of slightly more open wet forest vegetation. Gag LF was classified as wet forest, possibly with minor closed and slightly more open areas. The Henk’s Hollow LF is suggested to have a degree of openness equivalent to dry open forest, with minor areas of more open woodland types and more closed wet forest. The potentially younger Cleft- Of-Ages LF is suggested to have had a vegetation structure most analogous to extant dry open forest with possible areas equating to closed forest and woodland. The late Miocene Encore LF appears to have had an open vegetation structure similar to extant Australian woodland grading to dry open forest.

Multivariate classification and ordination analyses were performed on a dataset of 14 Oligo-Miocene mammalian LF’s from Riversleigh, in order to determine the degree of similarity between these time-averaged within-habitat assemblages. Three palaeocommunities and two palaeocommunity types were identified within the sample. One palaeocommunity consists of the early Miocene Upper, Neville’s Garden, Wayne’s Wok and Camel Sputum LF’s, and is identifiable at specific or generic level using

______208 presence/absence or relative abundance data. Mike’s Menagerie is linked with this palaeocommunity to form a palaeocommunity type, suggesting that this LF is similar but not necessarily identical to the palaeocommunity. This may however be an artefact of under-sampling of Mike’s Menagerie LF. This palaeocommunity type is distinguished using species presence/absence or abundance data. Last Minute and Ringtail LF’s form another palaeocommunity, identified at species or generic level with presence/absence data. Gag and Henk’s Hollow form a natural palaeocommunity, which can be distinguished at all taxonomic levels (including and below superfamily) with presence/absence and abundance data. In addition the latter two palaeocommunities unite to form a palaeocommunity type of similar palaeocommunities which is identifiable only at species level using presence/absence data.

Ordination generally confirms the results of classification, supporting the proposed palaeocommunities and palaeocommunity types. Independent support is also derived from palaeoecological studies of perameloid guilds (Muirhead, unpub.). The palaeocommunities also coincide with the bio-stratigraphic ‘Systems’ classification proposed by Archer et al. (1991, 1995).

The Neville’s Garden, Wayne’s Wok, Camel Sputum and Upper palaeocommunity, identified as the Nambaroo-Balbaroo palaeocommunity, is defined by the presence of the balbarine macropodoids Balbaroo gregoriensis and Nambaroo camilleriae, as well as a suite of characteristic, but non-exclusive, species. Six small- medium sized terrestrial, insectivorous-carnivorous yaraloid bandicoot species, and one species of small terrestrial-arboreal omnivorous pygmy possum species, dominated this palaeocommunity. Medium-sized browsing kangaroos were a significant, but less abundant, component. Large browsing-omnivorous kangaroos and medium folivorous possums together comprised only a minor portion of overall diversity (Figure 22).

Using palaeoenvironmental conclusions for the constituent LF’s, determined by DFA, as well as evidence from the fauna, possible palaeohabitat information was inferred for each palaeocommunity. For the Nambaroo-Balbaroo palaeocommunity it is

______209 suggested that the upper vegetation stratum was structurally, not floristically, equivalent to closed-wet forest.

The Gag and Henk’s Hollow palaeocommunity, referred to as the Litokoala- Muribacinus palaeocommunity, is defined by the presence of four marsupial species: Nimbadon lavarackorum, Litokoala kanunkaensis, Trichosurus dicksoni and Muribacinus gadiyuli. This palaeocommunity can be characterised by the absence of ornithorhynchids, miralinids, ektopodontids, yingabalanarids, vombatoids, ilariids, wynyardiids and notoryctids. The Litokoala-Muribacinus palaeocommunity is also characterised by a diversity of ecomorphotypes, including: one medium sized browsing kangaroo species; one reasonably common, large omnivorous-carnivorous kangaroo; one large browsing terrestrial diprotodontoid; three medium arboreal folivores; one common small terrestrial-arboreal omnivorous pygmy possum; one highly abundant medium arboreal omnivorous phalangerid; five small-medium terrestrial-arboreal omnivorous-carnivorous yaraloid bandicoots; and one medium sized terrestrial-arboreal carnivorous thylacinid. This palaeocommunity therefore differs from the Nambaroo- Balbaroo palaeocommunity in that the former appears to have had a lower diversity of macropodoid species, a greater diversity of arboreal ‘possums’, as well as the presence of large terrestrial browsers and medium-sized carnivores.

The Litokoala-Muribacinus palaeocommunity may have been derived from an ecotone of forest types, with upper vegetation stratum that are equivalent to extant wet to dry open forests.

No species currently define the Last Minute-Ringtail palaeocommunity although there are five characteristic species. This palaeocommunity is not as diverse as the others, possibly due to lower sampling effort for the constituent LF’s. Currently the ‘core’ mammalian ecodiversity of this palaeocommunity consists of one highly abundant, small, terrestrial-arboreal omnivorous pygmy possum, three small, terrestrial omnivorous-carnivorous yaraloid bandicoot species and one medium-sized, arboreal folivorous ‘ringtail’ possum. If we include transient or ambiguous members of the

______210 palaeocommunity (i.e. those known from one of the constituent LF’s, but not both) ecodiversity does not increase significantly, with the addition of possibly one rare large terrestrial browsing diprotodontid and one medium-large browsing wynyardiid. The diversity of arboreal ‘possums’ would, however, increase significantly. In comparison to the other two palaeocommunities, the Last Minute-Ringtail palaeocommunity is depauperate in large mammals as well as medium-large macropodoids.

The suggested vegetation structure for the Last Minute and Ringtail palaeocommunity is a mixture of closed and more open forest types, the latter being as open as extant wet forest.

The Last Minute, Ringtail, Gag and Henk’s Hollow palaeocommunity type may therefore represent a transitional fauna between the more closed Last Minute and Ringtail palaeocommunity, and the more open Gag and Henk’s Hollow palaeocommunity. The similarity between the two palaeocommunities indicates that the temporal separation was probably not substantial.

Several of the LF’s analysed could not be grouped with palaeocommunities, palaeocommunity types or each other. These represent independent LF’s and are synonymous with local palaeocommunities. The independent LF’s may represent distinct intervals of time, distinct palaeoenvironments, or biased or under-sampled assemblages. Geological, topographical, phylogenetic and palaeoecological evidence confirms the categorisation of the Hiatus LF as a basal late Oligocene (‘System A’) assemblage. The uniqueness of the White Hunter LF is suggested by many lines of evidence, including palaeoecological. This LF is characterised by a reasonably high diversity of medium-sized browsing macropodoids, yaraloid ‘bandicoots’, large terrestrial browsers and medium-large carnivores. Taphonomic investigations of the White Hunter LF indicate an autochthonous assemblage, possibly with minimal time- averaging. The environment of deposition for the WH LF was probably a large lacustrine water body with minimal fluvial input. There is some evidence for trampling

______211 of skeletal elements, possibly by large Bematherium angulum during periods of seasonal drying.

The age of the Cleft-Of-Ages LF remains indeterminate, but possibly late middle – early late Miocene. This LF is characterised by medium-level diversity of large, terrestrial browsers, but is also depauperate in medium-sized browsing macropodoids and yaraloid ‘bandicoots’.

Geographical, topographical and palaeoecological evidence suggests weak affinities between Keith’s Chocky Block and Encore LF’s. Like Cleft-Of-Ages, the Keith’s Chocky Block LF is probably a late middle (System C) – early late Miocene assemblage. The derived nature of many taxa, as well as inferences of their habitus from morphology, suggest a late Miocene age for the Encore LF. The latter LF appears to have been characterised by a high diversity of medium-large omnivorous-browsing macropodoids, medium-level diversity of large terrestrial browsers and medium-sized terrestrial carnivores. Ecodiversity changes between LF’s and palaeocommunities are not strictly comparable, as the time-averaged LF’s include many taxa that may have been transient, highly mobile, or are artefacts of taphonomy. The ecodiversity of palaeocommunities, in contrast, relates only to ‘core’ mammalian member species that characterise or define the palaeocommunity (Figure 22).

Some of the taxa analysed in this study appear to span long temporal ranges. The burramyid, Burramys brutyi, is present in all of the LF’s studied except for HI and MM LF. As previously discussed there is good reason to believe that both of theses LF’s are under-sampled. Similarly, the hypsiprymnodontid, Ekaltadeta ima, has been identified in the late Oligocene White Hunter LF, the early Miocene Nambaroo-Balbaroo palaeocommunity, the middle Miocene Litokoala-Muribacinus palaeocommunity, as well as in the late Miocene Encore LF. This would suggest that both taxa had longevity in excess of 13 million years. The fact that E. ima has not as yet been identified in the Last Minute – Ringtail palaeocommunity may indicate that this taxon was not well adapted to totally closed rainforest types, or at least the forest type present in the early

______212 middle Miocene of Riversleigh. However, the longevity of both species is probably due primarily to two factors: 1) both species were generalist omnivores; and 2) the species are at either end of the general weight spectrum for the bulk of Riversleigh’s mammal faunas (21g for B. brutyi and approximately 16kg for E. ima), rather than in the more vulnerable medium-sized weight ranges.

It is also noteworthy that dasyurids have not yet been found in the late Oligocene White Hunter LF, perhaps indicating that they were out-competed by yaraloid taxa in the closed forest types of this time. The presence of dasyurids in the Hiatus LF indicates that dasyurids were present during the late Oligocene at Riversleigh, but perhaps only in more open areas capable of supporting a higher diversity of larger terrestrial browsers. The medium-sized, terrestrial, browsing ilariids are similarly present in the late Oligocene (WH LF) but do not appear to have extended into the Miocene.

Notoryctids appear to be confined to the closed to ‘wet’ forests of the early Miocene Nambaroo-Balbaroo palaeocommunity. The presence of only one identified specimen in the Ringtail LF suggests that notoryctids had declined significantly by the early middle Miocene, in presumably similar habitats. Similarly, the more open forest types of the late middle Miocene Litokoala-Muribacinus palaeocommunity were devoid of ornithorhynchids, miralinids, ektopodontids, yingabalanarids and wynyardiids, suggesting that these families did not survive beyond the Miocene oscillation (sensu McGowran and Li, 1994).

The palaeoenvironmental conclusions suggested here for the various palaeocommunities and independent LF’s tie in with current understanding of climatic change. The late Oligocene (System A) experienced Icehouse conditions (McGowran, 1986; McGowran and Li, 1994) and the WH LF suggests closed forest with some opening-up, perhaps in response to drier conditions. The early Miocene (System B) palaeocommunities indicate closed to wet forests, perhaps forming as the more open areas of System A forest began to close as a result of new Greenhouse conditions. Early System C LF’s and palaeocommunities are similar to System B but are less diverse,

______213 perhaps indicating the initiation of another Icehouse cycle. Middle to late System C mammalian palaeocommunities are suggestive of slightly more open forest types with less areas of closed forest. Possible late Miocene LF’s indicate extensive drying with open to very open forest types.

It may be argued that the use of extant Australian forest types could have limitations in this type of palaeoecological study. For instance, many authors have suggested that Australian tropical rainforest experienced a significant loss of mammalian diversity during the late Pleistocene (e.g. Archer et al., 1995; Winter, 1988). They argue that the mammalian fauna represented in extant Australian rainforest is refugial, as rainforest came very close to being eliminated from the continent during the last glacial maximum. In turn more open forests have expanded to occupy former rainforest areas. It is therefore not surprising that species richness is relatively low in extant rainforest, particularly compared to ‘wet forest’. However, it could also be argued that ‘wet’, ‘wet open’ or ‘wet sclerophyll’ forest has undergone a similar decline, pushed aside by more open and drier forest types. Furthermore, it is possible that rainforest may have expanded onto continental shelf as sea-level dropped during Icehouse phases (P. Adams, pers. comm.). Species diversity is higher in sclerophyll forests in the Wet Tropics region of Northern Queensland than it is in the rainforest areas (Williams et al., 1996). In the Wet Tropic and Cape York regions refugia were sufficiently large to support rainforest specialists during drying periods (Winter, 1988). In contrast the rainforests of the South- east decreased in size below minimum critical sizes for supporting rainforest specialists (ibid.). This study has utilised a number of Cape York and Wet Tropic datasets which may minimise possible bias from potentially depauperate rainforest faunas.

Losses of megafauna over the last 40000 years have primarily been grazing species that inhabited open environments. So the latter too have presumably undergone extensive declines in mammal diversity over the late Pleistocene to Recent. Additionally, it is likely that rainforest mammal and vegetational communities reached some sort of equilibrium over the last 13000 years (since the last glacial maximum),

______214 prior to more recent anthropogenic changes, the latter of course which have also affected other habitat types.

There is also inconsistency in the use of ‘wet open’ or ‘wet’ forest, with some botanists classifying ‘tall wet open forest’ and ‘wet sclerophyll’ forest as types of disturbed rainforest, which may only be stable over periods of a few hundred years (P. Adams, pers. comm.). This is however contrary to the use of wet forest by Specht (1981) as well as the majority of authors of the various faunal lists used in this analysis (see Chapter Three).

Another possible caveat in the use of present Australian vegetation, as an analogue for the determination of past environments, arises from the fact that many extant ‘open’ communities are dominated by a single genus – Eucalyptus. P. Adams (pers. comm.) has suggested that the ‘non-rainforest’ areas, of the Australian Oligocene- Miocene, may have been taxonomically and ecologically different from present-day eucalypt-dominated open forest and woodland. It is further suggested that tropical or sub-tropical savannah systems might be more appropriate However, as savannah was largely absent from the Australian continent until the Pliocene (Martin, 1994; White, 1997; Archer et al., 1997), it is unlikely that this ecosystem would be anymore appropriate as an analogue than Eucalyptus-dominated ‘open’ environs. Possible non- grassland ‘savannah’ equivalents of the Oligo-Miocene were also likely to have been taxonomically and ecologically different to present Australian savannah. The principle of uniformitarianism is a basic tenet of palaeoecology. Until contrary-evidence is forthcoming we must assume that ‘open’ Australian vegetation communities of the past had characteristic body-size distributions that were similar to those used to discriminate ‘open’ environs in the present.

It should also be remembered that the DFA presented here simply identifies the closest living Australian analogues, in relation to the openness of the uppermost vegetation stratum. The five vegetation categories employed (see Chapter Three) represent a continuum of ‘openness’, from fully closed ‘rainforest’ to ‘open woodland’.

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These categories were deliberately defined as broadly as possible, so as to be statistically meaningful and to allow for differences between definitions of forest types by the authors of the various faunal lists employed. ‘Wet forest’, regardless of it’s status as a valid or ephemeral vegetation type, merely represents a forest type that is not closed but is also not as open as extant dry open forest (equivalent to 50-70% projective foliage cover sensu Specht (1981). Those fossil faunas identified as having at least partial ‘wet forest’ might be characterised as disturbed rainforest, true wet forest or a hitherto unknown forest type with a vegetation structure merely approximating extant ‘wet forest’.

Additionally, the DFA presented here incorporates many variables, primarily related to body-size, and only one that concerns species richness. Slight discrepancies in one, or only a few variables, are unlikely to dramatically alter results as the DFA is generally quite robust. Many species, or a few very large species, would need to be removed to significantly change the body-size distributions of any specific fauna.

It is important that all lines of evidence be considered when inferring palaeoenvironmental characteristics. Palaeoecological analyses presented here have used primarily body-size and diversity variables. Trophic and locomotory parameters may prove to be just as informative.

The results may only be useful in broad terms, but do never the less, correlate generally with current thinking regarding the relative vegetational changes over Riversleigh’s systems. For instance, late Oligocene (System A) ‘Icehouse’ LF’s, such as White Hunter, are thought to represent mesic forests of unknown nature (Archer et al., 1997). This does not exclude the possibility of closed forest with open patches suggested in this study. Early Miocene (System B) assemblages are thought to represent highly diverse rainforests (e.g. Archer et al., 1995, 1997). Results presented in this study suggest that this interpretation is likely, but also do not exclude the possibility of mixed rainforest and slightly more open ‘wet forest’ analogues. Lower System C assemblages (e.g. Gag site) are nearly as diverse as System B and are interpreted as rainforest, while

______216 those from the upper part of System C (e.g. Henk’s Hollow), following the mid-Miocene oscillation are less diverse, possibly representing an early phase in the opening up of Australia’s rainforests (ibid.). Results herein suggest that the Gag and Henk’s Hollow LF’s represent one palaeocommunity, as do the other System C LF’s of Last Minute and Ringtail. The Last Minute and Ringtail palaeocommunity is interpreted as closed to wet forest, possibly indicating a lower System C assemblage. The Gag and Henk’s Hollow (Litokoala-Muribacinus) palaeocommunity, in contrast, is suggestive of more open habitat, structural equivalents of extant wet and dry open forest, and possibly deciduous vine thicket. The latter may therefore represent an upper System C assemblage. The Encore LF formed during part of a major icehouse interval, is less diverse than System C, and lacks groups indicative of rainforest (ibid.). This conclusion correlates well with interpretations presented in this study.

Conclusions presented herein are also broadly consistent with the understanding of Australia’s mid-late Tertiary palaeobotanical record. White (1997b) indicates that the dominant vegetation formations of the late Oligocene (‘System A’) persisted into the early Miocene (‘System B’), with temperate Nothofagus rainforests extending over southeastern Australia from Tasmania to coastal Queensland. Martin (1994; cited in Archer et al., 1995) concluded that Australia was widely forested throughout the Tertiary and that most of the forests were rainforests prior to the middle Miocene. These forests graded such that Myrtaceae and Araucaria dominated from the coast to the inland (White, 1997b). Plants that today dominate open plains had become established by the early Miocene, including Acacia, Casuarina, Eucalyptus, grasses and Asteraceae, although they were largely restricted to open drier vegetation types. By the middle Miocene (‘System C’) Nothofagus rainforest had disappeared and wet sclerophyll dominated, coincident with the formation of the Antarctic ice cap and increased seasonality (ibid.). Martin (1994; cited in Archer et al., 1995) suggests that this disappearance did not occur until the late Miocene. From the middle Miocene vegetation changed in many areas, as the continent dried out, to increasingly fire tolerant dry sclerophyll, open woodland and grassland (White, 1997b).

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Future research should investigate the potential for overseas datasets to produce analogues for Riversleigh’s fossil faunas, based on body-size distributions. This will however be extremely difficult for potential analogues, such as montane rainforests in Papua New Guinea and lowland Sarawak (Archer et al., 1995) and South America, due to a lack of published faunal lists that: 1) are from discrete geographical areas; 2) have precise habitat information; 3) include all mammal species, not just those from specific weight groups; and 4) include species for which average body weights are known. However, as more information becomes available such studies may conclude that overseas extant forests are more analogous, structurally and floristically, to Riversleigh’s Oligo-Miocene forests than living Australian vegetation types.

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High diversity of medium Upper strata -large omnivorous – browsing macropodoids. 5.3 ‘woodland’ to ‘dry Med diversity of large Encore LF open forest’ terrestrial browsers & med-large carnivores. COA LF Upper strata ‘dry Med diversity of large terrestrial browsers. open forest’, minor Depauperate in med Late Miocene ? KCB LF closed & ‘woodland’ browsing macropodoids & yaraloid taxa 10.4 ? ? Ice-house Upper strata similar High ecodiversity. High Litokoala – Muribacinus to extant ‘wet’ to diversity of small- ‘dry open forest’ medium arboreal GAG & HH LF’s palaeocommunity possums & yaraloids.

Highly abundant LM & RING Upper strata closed burramyid. Med diversity LM & RING LF’s yaraloids. Depauperate palaeocommunity to ‘wet’ forest medium-large browsers. Middle Miocene Miocene Middle

16.4 ? High abundance of small, omnivorous burramyids and yaraloids. Medium MM LF Green-house ? sized browsing Upper strata ‘wet’ macropodoids. Lower UP, NG, WW, CS Nambaroo – Balbaroo diversity of large forest with large browsing-omnivorous LF’s palaeocommunity areas closed macropodoids & medium folivorous possums.

MioceneEarly ?

23.5 Upper strata closed High diversity of medium White Hunter LF browsing macropodoids, forest possibly with yaraloids, large terrestrial ? areas equivalent to browsers & medium- Ice-house large carnivores. Lower ‘dry open forest’ diversity of arboreal taxa. Hiatus LF Late OligoceneLate

Figure 22: Riversleigh local faunas and palaeocommunities analysed in this study, with estimated ages, inferred extant vegetation structure analogues, climatic phases and characteristic ecodiversity. ______219

Chapter 11 References

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Alroy, J. (1998). Cope's rule and the dynamics of body mass evolution in North American fossil mammals. Science 280, 731-734.

Alroy, J. (2000). New methods for quantifying macroevolutionary patterns and processes. Paleobiology 26, 707-733.

Anderson, J. F., Hall-Martin, A. & Russell, D. A. (1985). Long-bone circumference and weight in mammals, birds and dinosaurs. Journal of Zoology, London, A. 207, 53-61. Andrews, P., Lord & Evans. (1979). Patterns of ecological diversity in fossil and modern mammalian faunas. Biological Journal of the Linnean Society 11, 177-205.

Archer, M., Hand, S. & Godthelp, H. (1988). A new order of tertiary Zalambdodont Marsupials. Science 239, 1528-1531.

Archer, M., Godthelp, H., Hand, S. J. & Megirian, D. (1989). Fossil mammals of Riversleigh, North Western Queensland: preliminary overview of biostratigraphy, correlation and environmental change. Australian Zoologist 25, 29-65. Archer, M., Every, R. G., Godthelp, H., Hand, S. J. & Scally, K. B. (1990). Yingabalanaridae, a new family of enigmatic mammals from tertiary deposits of Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 28, 193-202. Archer, M., Hand, S. J. & Godthelp, H. (1991). Back to the future: the contribution of palaeontology to the conservation of the Australian forest faunas. In Conservation of Australia's forest faunas (ed. D. Lunney), pp. 67-80. Royal Zoological society of New South Wales, Mosman.

Archer, M., Hand, S. J. & Godthelp, H. (1995). Tertiary Environmental and Biotic Change in Australia. In Paleoclimate and evolution, with emphasis on human origins (ed. E. S. Vrba, G. H. Denton, T. C. Partridge and L. H. Burckle), pp. 77-90. Yale University Press, New Haven.

Archer, M., Hand, S. J. & Godthelp, H. (1996). Riversleigh, the story of animals in ancient rainforests of inland Australia. Reed Books, Kew, Victoria.

Archer, M., Hand, S. J., Godthelp, H. & Creaser, P. (1997). Correlation of the Cainozoic sediments of the Riversleigh World Heritage Fossil Property, Queensland,

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Australia. In Actes du Congres BiocroM'97 Mem. Trav. E.P.H.E., Inst. Montpellier, vol. 21 (ed. J.-P. Aguilar, S. Legendre and J. Michaux), pp. 131- 152.

Archer, M., Burnley, I., Dodson, J., Harding, R., Head, L. & Murphy, A. (1998). From plesiosaurs to people: 100 million years of Australian environmental history. Department of the Environment, Canberra.

Arena, D. A. (1997). The palaeontology and geology of Dunsinane Site, Riversleigh. Memoirs of the Queensland Museum 41, 171-181.

Arena, R., Wroe, S. & Archer, M. (1998). Additional material referred to the dasyurid Ganbulanyi djadjinguli: phylogenetic and palaeobiological implications. Abstracts of the 2nd Riversleigh Symposium, December 3-4, 1998, University of New South Wales . Australian Bureau of Meteorology. (2002). Rain gauge information Australia, 2002. http://www.bom.gov.au/hydro/wr/rgc/index.shtml. Barker, J., Lunney, D. & Bubela, T. (1994). Mammal surveys in the forests of the Carrai Plateau and Richmond Range in north-east New South Wales. Australian Mammalogy 17, 19-29. Barnett, J. L., How, R. A. & Humphreys, W. F. (1976). Mammals of Clouds Creek, north-eastern New South Wales, and their distribution in pine and native forests. Australian Zoologist 19, 23-34. Behrensmeyer, A. K. (1975). The taphonomy and paleoecology of Plio-Pleistocene vertebrate assemblages of Lake Rudolph, Kenya. Bulletin of the Museum of Comparative Zoology 146, 473-578. Behrensmeyer, A. K. (1978). Taphonomic and ecologic information from bone weathering. Paleobiology 4, 150-162.

Behrensmeyer, A. K. (1991). Terrestrial vertebrate accumulations. In Taphonomy: releasing the data locked in the fossil record, pp. 291-335.

Behrensmeyer, A. K. & Boaz, D. E. D. (1980). The Recent bones of Amboseli National Park, Kenya. In Fossils in the making: Vertebrate taphonomy and paleoecology. Prehistoric archaeology and ecology series (ed. A. K. Behrensmeyer and A. P. Hill). The University of Chicago Press, Chicago.

______222

Behrensmeyer, A. K., Kidwell, S. M. & Gastaldo, R. A. (2000). Taphonomy and paleobiology. Paleobiology 26, 103-147. Bennet, A. F. (1990). Land use, forest fragmentation and the Mammalian fauna at Naringal, South-western Victoria. Australian Wildlife Research 17, 325-47. Bennington, J. B. & Bambach, R. K. (1996). Statistical testing for paleocommunity recurrence: Are similar fossil assemblages ever the same? Palaeogeography, Palaeoclimatology, Palaeoecology 127, 107-133. Binns, D. & Kavanagh, R. P. (1990). Flora and fauna survey of Nalbaugh State Forest (part), Bombala District, Eden Region, South-Eastern New South Wales. Forestry Commission of NSW, Sydney.

Black, K. (1997a). A new species of Palorchestidae (Marsupialia) from the late middle to Early Late Miocene Encore Local Fauna, Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 181-186.

Black, K. (1997b). Diversity and biostratigraphy of the Diprotodontoidea of Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 187-192.

Black, K. & Archer, M. (1997a). Silvabestius gen. nov., a primitive zygomaturine (Marsupialia, Diprotodontidae) from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 193-208. Black, K. & Archer, M. (1997b). Nimiokoala gen. nov. (Marsupialia, Phascolarctidae) from Riversleigh, northwestern Queensland, with a revision of Litokoala. Memoirs of the Queensland Museum 41, 209-228. Boles, W. E. (1993). A logrunner Orthonyx from the Miocene of Riversleigh, northwestern Queensland. Emu 93, 44-49.

Boles, W. E. (1997a). A kingfisher (Halcyonidae) from the Miocene of Riversleigh, northwestern Queensland, with comments on the evolution of kingfishers in Australo-Papua. Memoirs of the Queensland Museum 41, 229-234.

Boles, W. E. (1997b). Hindlimb proportions and locomotion of Emuarius gidju (Patterson & Rich 1987) (Aves, Casuariidae). Memoirs of the Queensland Museum 41, 235-240.

Boles, W. E. (1997c). Riversleigh birds as palaeoenvironmental indicators. Memoirs of the Queensland Museum 41, 241-246.

______223

Boles, W. E. (1999). A new songbird (Aves: Passeriformes: Oriolidae) from the Miocene of Riversleigh, northwestern Queensland, Australia. Alcheringa 23, 51-56.

Brammall, J. & Archer, M. (1997). A new Oligocene-Miocene species of Burramys (Marsupialia, Burramyidae) from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 247-268.

Brammall, J. (1998). A new Petauroid possum from the Oligo-Miocene of Riversleigh, northwestern Queensland. Alcheringa 23, 31-50.

Brenchley, P. J. & Harper, D.A.T. (1998). Palaeoecology: ecosystems, environments and evolution. Chapman & Hall, London.

Burbidge, A. A., McKenzie, N. L., Chapman, A. & Lambert, P. M. (1976). The wildlife of some existing and proposed reserves in the Great Victoria and Gibson Deserts, Western Australia. Wildlife Research Bulletin Western Australia 5.

Cassiliano, M. (1997). Taphonomy of mammalian fossils across the Blancan- Irvingtonian boundary: Palm Spring Formation, Anza-Borrego desert of southern California. Palaeogeography, Palaeoclimatology, Palaeoecology 129, 81-108. Clemens, W. A. & Plane., M. (1974). Mid-Tertiary Thylacoleonidae (Marsupialia, Mammalia). Journal of Paleontology 48, 652-660. Conroy, G. (1987). Problems of body-weight estimation in fossil primates. International. Journal of Primatology 8, 115-137. Cooke, B. N. (1999). Wanburoo hilarus gen. et sp. nov., a lophodont bulungamayine kangaroo (Marsupialia: Macropodoidea: Bulungamayinae) from the Miocene deposits of Riversleigh, northwestern Queensland. Records of the Western Australian Museum Supplement 57, 239-254.

Cooke, B. N. (1997a). New Miocene bulungamayine kangaroos (Marsupialia, Potoroidae) from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 281-294.

Cooke, B. N. (1997b). Two new balbarine kangaroos and lower molar evolution within the subfamily. Memoirs of the Queensland Museum 41, 269-280.

______224

Cooke, B. N. (1997c). Biostratigraphic implications of fossil kangaroos at Riversleigh, northwester Queensland. Memoirs of the Queensland Museum 41, 295-302. Coombs, M. C. & Coombs, W. P. (1997). Analysis of the Geology, Fauna, and Taphonomy of Morava Ranch Quarry, Early Miocene of Northwest Nebraska. Palaios 12, 165-187. Cope, E. D. (1887). The Origin of the Fittest. Appleton, New York. Craig, S. A. (1985). Social organization, reproduction and feeding behaviour in a population of yellow-bellied gliders, Petaurus australis (Marsupialia: Petauridae). Australian Wildlife Research 12, 1-18. Creaser, P. (1997). Oligocene-Miocene sediments of Riversleigh: the potential significance of topography. Memoirs of the Queensland Museum 41, 303-314. Damuth, J. (1990). Problems in estimating body masses of archaic ungulates using dental measurements. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 22 9- 253. Cambridge University Press, Cambridge.

Damuth, J. & MacFadden, B. J. (1990). Introduction: body size and its estimation. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 1-10. Cambridge University Press, Cambridge. Davis, J. C. (1986). Statistics and Data Analysis in Geology. John Wiley, Chichester. de Bonis, L., Bouvrain, G., Geraads, D. & Koufos, G. (1992). Diversity and paleoecology of Greek Late Miocene mammalian faunas. Palaeogeography, Palaeoclimatology, Palaeoecology 91, 99-121.

Duan, N. (1983). Smearing estimate: A nonparametric re-transformation method. Journal of the American Statistical Association 78, 605-610.

Ducrocq, S., Chaimanee, Y., Suteethorn, V. & Jaeger, J-J. (1994). Ages and paleoenvironment of Miocene mammalian faunas from Thailand. Palaeogeography, Palaeoclimatology, Palaeoecology 108, 149-163.

Dwyer, P., Hockings, M. & Willmer, J. (1979). Mammals of Cooloola and Beerwah. Proceedings of the Royal Society of Queensland 90, 65-84.

______225

Efremov, J. A. (1940). Taphonomy: new branch of paleontology. Pan American Geologist 74, 81-93. Etter, W. (1999). Community Analysis. In Numerical Palaeobiology: Computer-based modelling and analysis of fossils and their distributions. (ed. D. A. T. Harper), pp. 285-360. John Wiley & Sons Ltd, Chichester.

Fanning, D. & Mills, K. (1989). Natural resource survey of the southern portion of Rockton section, Bondi State Forest, pp. 166. Forestry Commission, West Pennant Hills.

Fanning, D. & Mills, K. (1990). Flora and fauna survey of the Myanba Creek catchment, Coolangubra State Forest, Eden Region, pp. 302. Forestry Commission of NSW, Sydney. Fanning, D. & Mills, K. (1991). The Stockyard Creek catchment of Coolangubra Sate Forest, NSW. Forestry Commission of New South Wales, Pennant Hills.

Flannery, T. F., Archer, M. & Plane, M. (1982). Middle Miocene kangaroos (Macropodoidea: Marsupialia) from three localities in northern Australia, with a description of two new subfamilies. Journal of Australian geology & geophysics 7, 287-302. Flannery, T. (1995). Mammals of New Guinea. Reed Press, Sydney. Fortelius, M. (1990). Problems with using fossil teeth to estimate body sizes of extinct mammals. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 207-228. Cambridge University Press, Cambridge. Frith, H. J. & Calaby, J. H. (1974). Fauna survey of the Port Essington District, Cobourg Peninsula, Northern Territory of Australia. Commonwealth Scientific and Industrial Research Organisation, Melbourne.

Gagnon, M. (1997). Ecological diversity and community ecology in the Fayum sequence. Journal of Human Evolution 32, 133-160.

Gillespie, A. (1997). Priscileo roskellyae sp. nov. (Thylacoleonidae, Marsupialia) from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 321-328.

______226

Gingerich, P.D. (1989). New earliest Wasatchian mammalian fauna from the Eocene of northwestern Wyoming: Composition and diversity in a rarely sampled high – floodplain assemblage. University of Michigan Papers on Paleontology 28, 97.

Gould, S. J. (1975). On the scaling of tooth size in mammals. American Zoologist 15, 351-362.

Grainger, M., Gunn, E. and Watts, D. (1987). Tasmanian mammals: a field guide. Tasmanian Conservation Trust Inc, Hobart. Grayson, D. K. (1984). Quantitative Zooarchaeology. Academic Press, Orlando. Gunnell, G. F. (1994). Paleocene mammals and faunal analysis of the Chappo Type locality (Tiffanian), Green River Basin, Wyoming. Journal of Vertebrate Paleontology 14, 81-104. Gunnell, G. F. (1997). Wasatchian-Bridgerian (Eocene) paleoecology of the western interior of North America: changing paleoenvironments and taxonomic composition of omomyid (Tarsiiformes) primates. Journal of Human Evolution 32, 105-132.

Hammer, O., Harper, D. A. T. & Ryan, P. D. (2001). PAST – data analysis for paleontologists. Computer software, Version 0.35

Hand, S. J. (1985). New Miocene Megadermatids (Chiroptera: Megadermatidae) from Australia, with comments on Megadermatid phylogenetic. Australian Mammalogy 8, 5-43

Hand, S. (1996). New Miocene and Pliocene Megadermatids (Mammalia, Microchiroptera) from Australia, with comments on broader aspects of Megadermatid evolution. Geobios 29, 365-377.

Hand, S. (1997a). New Miocene leaf-nosed bats (Microchiroptera, Hipposideridae) from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 335-350.

Hand, S. (1997b). Hipposideros bernardsigei, a new hipposiderid (Mammalia: Microchiroptera) from the Australian Miocene and a reconsideration of the monophyly of related species groups. Munchner Geowiss. Abh. 34, 73-92.

______227

Hand, S. J., Murray, P., Megirian, D., Archer, M. and Godthelp, H. (1998). Mystacinid bats (Microchiroptera) from the Australian Tertiary. Journal of Paleontology 73, 538-545.

Harper, D. A. T. & Owen, A. W. (1999). Quantitative and Morphometric Methods in Taxonomy. In Numerical Palaeobiology: Computer-based modelling and analysis of fossils and their distributions (ed. D. A. T. Harper), pp. 1-41. John Wiley & Sons Ltd, Chichester. Hocking, G. J. & Guiler, E. R. (1983). The mammals of the lower Gordon River region, South-west Tasmania. Australian Wildlife Research 10, 1-23. Hutchinson, M. (1997). The first fossil pygopod (Squamata, Gekkota), and a review of mandibular variation in living species. Memoirs of the Queensland Museum 41, 355-365. Janis, C. M. (1990). Correlation of cranial and dental variables with body size in ungulates and macropodoids. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 255-299. Cambridge University Press, Cambridge.

Jones, M. (1997). Character displacement in Australian dasyurid carnivores: size relationships and prey size patterns. Ecology 78, 2569-2587.

Kabay, E. D. & Burbidge, A. A. (1977). A biological survey of the Drysdale River National Park, North Kimberley, Western Australia. Wildlife Research Bulletin Western Australia 6, 1-133.

Kappelman, J., Plummer, T., Bishop, L., Duncan, A. & Appleton, S. (1997). Bovids as indicators of Plio-Pleistocene palaeoenvironments in East Africa. Journal of Human Evolution 32, 229-256.

Kay, R. F. & Madden, R. H. (1997). Mammals and rainfall: paleoecology of the middle Miocene at La Venta (Colombia, South America). Journal of Human Evolution 32, 161-199.

Kidwell, S. M. & Flessa, K. W. (1996). The quality of the fossil record: populations, species, and communities. Annual Review of Earth Planetary Science 24, 433- 464.

______228

Kirkpatrick, T. H. & Searle, A. K. (1977). Mammals and birds of Stanthorpe Shire, south-east Queensland. Queensland Journal of Agriculture and Animal Sciences 34, 109-121.

Kitchener, D. J., Keller, L. E., Chapman, A., McKenzie, N. L., Start, A. N. & Kenneally, K. F. (1981). Observations on mammals of the Mitchell Plateau area, Kimberley, Westerns Australia. unknown .

Lavery, H. J. & Johnson, P. M. (1974). Mammals and birds of the lower Burdekin River district, north Queensland. 1. Introduction and Mammals. Queensland journal of agricultural and animal sciences 31, 97-104. Legendre, S. (1986). Analysis of mammalian communities from the Late Eocene and Oligocene of southern France. Palaeovertebrata 16, 191-212. Legendre, S. (1988). Les communautes de mammiferes du Paleogene (Eocene superieur et Oligocene) d'Europe occidentale: structures, milieux et evolution. These du Doctorat d'Etat thesis, Universite de Montpellier. Legendre, S. (1989). Les communautes de mammiferes du Paleogene (Eocene superieur et Oligocene) d'Europe occidentale: structures, milieux et evolution. Munchner Geowissenschaftlichen Abhandlugen 16, 1-110. Legendre, S. & Hartenberger, J. (1992). Evolution of mammalian faunas in Europe during the Eocene and Oligocene. In Climatic and biotic evolution (ed. D. R. Prothero and W. A. Berggren), pp. 516-528. Princeton University Press. Legendre, L. & Legendre, P. (1984). Ecologie Numerique. Masson, Paris. Legendre, S. & Roth, C. (1988). Correlation of the lower carnassial size and the body weight in recent carnivores (Mammalia). Historical Biology 1, 85-98.

Maas, M. C. & Krause, D. W. (1994). Mammalian turnover and community structure in the Paleocene of North America. Historical Biology 8, 91-128.

Martin, R. A. (1980). Body mass and basal metabolism of extinct mammals. Comparative Biochemistry and Physiology 66, 307-314.

Martin, R. A. (1990). Estimating body mass and correlated variables in extinct mammals: travels in the fourth dimension. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 49-68. Cambridge University Press, Cambridge.

______229

Martin, H.A. (1994). Australian Tertiary phytogeography: Evidence from palynology. In History of the Australian vegetation (ed. R. Hill), pp. 104-142. Cambridge University Press, Cambridge.

McGowran, B. (1986). Cainozoic oceanic events: the Indo-Pacific biostratigraphic record. Palaeogeography, Palaeoclimatology, Palaeoecology 55, 247-265. McGowran, B. & Li, Q. (1994). The Miocene oscillation in southern Australia. Records of the South Australian Museum 27, 197-212. McNab, B. K. (1990). The physiological significance of body size. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 11-23. Cambridge University Press, Cambridge. Megirian, D. (1992). Interpretation of the Miocene Carl Creek Limestone, northwestern Queensland. The Beagle, Records of the Northern Territory Museum of Arts and Sciences. 9, 219-248. Montuire, S. & Desclaux, E. (1997). Palaeoecological analysis of mammalian faunas and environmental evolution in the South of France during the Pleistocene. Boreas 26, 355-365. Morgan, M. E., Badgley, C., Gunnell, G.F., Gingerich, P.D., Kappelman, J.W. & Maas, M.C. (1995). Comparative paleoecology of Paleogene and Neogene mammalian faunas: body-size structure. Palaeogeography, Palaeoclimatology, Palaeoecology 115, 287-317.

Muirhead, J. & Filan, S. L. (1995). Yarala burchfieldi, a plesiomorphic bandicoot (Marsupialia, Peramelemorphia) from Oligo-Miocene deposits of Riversleigh, northwestern Queensland. Journal of Paleontology 69, 127-134.

Muirhead, J. (1997). Two new Early Miocene thylacines from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 367-378.

Muirhead, J. & Wroe, S. (1998). A new genus and species, Badjcinus turnbulli (Thylacinidae: Marsupialia), from the Late Oligocene of Riversleigh, Northern Australia, and an investigation of Thylacinid phylogeny. Journal of Vertebrate Paleontology 18, 612-626.

______230

Muirhead, J. (2000). Yaraloidea (Marsupialia, Paramelemorphia), a new superfamily of Marsupial and a description and analysis of the cranium of the Miocene Yarala burchfieldi. Journal of Paleontology 74, 512-523.

Muirhead, J. (unpub.). Diversity, biostratigraphy and changing palaeoecological roles of bandicoots as signals of long term change in Australian Mammal communities.

Murphy, M. J. (1998). Mammal survey of Seven Mile Beach National Park and Coerong Island Nature Reserve on the south coast of New South Wales. Australian Zoologist 30, 419-425.

Murray, P., Wells, R. & Plane, M. (1987). The cranium of the Miocene thylacoleonid, Wakaleo vanderleuri: Click go the shears - A fresh bite at Thylacoleonid systematics. In Possums & Opossums (ed. M. Archer), pp. 433-466. Surrey Beatty & Sons, Chipping Norton. Murray, P. (1990). Primitive Marsupial tapirs (Propalorchestes novaculacephalus Murray and P. ponticulus sp. nov.) from the Mid-Miocene of North Australia (Marsupialia: Palorchestidae). The Beagle 7, 39-51. Murray, P. & Megirian, D. (1992). Continuity and contrast in Middle and Late Miocene vertebrate communities from the Northern Territory. The Beagle 9, 195-218. Murray, P. (1997). Alcoota: A snapshot of the Australian Late Miocene. Riversleigh Notes 35, 2-7. Myers, T. J. & Archer, M. (1997). Kuterintja ngama (Marsupialia, Ilariidae); a revised systematic analysis based on material from the Late Oligocene of Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 379-392. Myers, T., Archer, M., Krikmann, A. & Pledge, N. (1999). Diversity and evolutionary relationships of ilariids, wynyardiids, vombatids and related groups of marsupials. Australian Mammalogy 21, 18-20.

Myers, T. J. (2001). Prediction of marsupial body mass. Australian Journal of Zoology 49, 99-118.

Nicol, S. L. (1978). A mammal study of the Kinglake area, Victoria. Australian Wildlife Research 5.

______231

Olson, E. C. (1980). Taphonomy: Its history and role in community evolution. In Fossils in the Making (eds A.K. Behrensmeyer and A. P. Hill), pp. 5-19. University of Chicago Press, Chicago.

Popov, V. V., Gerasimov, S. & Marinska, M. (1994). Multivariate palaeoecological analysis of a Late Quaternary small mammal succession from North Bulgaria. Historical Biology 8, 261-274.

Raup, D. M. (1975). Taxonomic diversity estimation using rarefaction. Paleobiology 1, 333-342.

Rodriguez, J. (1999). Use of cenograms in mammalian palaeoecology. A critical review. Lethaia 32, 331-347.

Roth, V. L. (1990). Insular dwarf elephants: a case study in body mass estimation and ecological inference. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden), pp. 151-179. Cambridge University Press, Cambridge. Scanlon, J. (1995). An elapid snake (Hydropheinae) from the Middle Miocene Encore Site, Riversleigh. 5th Conference on Australian Vertebrate Evolution, Palaeontology & Systematics, Collected Abstracts. . Scanlon, J. D. (1997). Nanowana gen. nov., small madtsoiid snakes from the Miocene of Riversleigh: sympatric species with divergently specialised dentition. Memoirs of the Queensland Museum 41, 393-412. Shea, G. M. & Hutchison, M. N. (1992). A new species of Tiliqua from the Early Miocene of Riversleigh, Queensland. Memoirs of the Queensland Museum 32, 303-310.

SigmaStat. (1992). SigmaStat. Jandel Corporation.

Silva, M. & Downing, J. A. (1995). CRC Handbook of Mammalian Body Masses. CRC Press, Boca Raton, Florida.

Smith, R. J. (1981). Interpretation of correlations in intraspecific and interspecific allometry. Growth 45, 291-297.

Smith, R. J. (1984). Allometric scaling in comparative biology: problems of concept and method. American Journal of Physiology 246, R152-R160.

______232

Smith, R. J. (1993). Logarithmic transformation bias in allometry. American Journal of Physical Anthropology 90, 215-228. Smith, A. P., Moore, D. M. & Andrews, S. P. (1992). Proposed forestry operation in the Glen Innes Management Area. Austeco Pty. Ltd., Environmental Consultant, For Forestry Commission of NSW, Armidale.

Specht, R. L. (1981). Foliage projective cover and standing biomass. In Vegetation Classification in Australia (ed. A. N. Gillison and D. J. Anderson), pp. 10-21. CSIRO & ANU Press, Canberra.

Steel, R. G. D. & Torrie, J. H. (1980). Principles and procedures of statistics: a biometrical approach, Second edition. McGraw-Hill International Editions, Singapore. Strahan, R. (1983). Complete book of Australian mammals. Angus & Robertson Publishers, Sydney.

Strahan, R. (1995). The Mammals of Australia. Reed Books, Chatswood.

Systat. (1997). Systat. SPSS inc. Tate, G. H. H. (1952). Mammals of the Cape York Peninsula, with notes on the occurrence of rain forest in Queensland. Bulletin of the American Museum of Natural History (Results of the Archbold Expeditions. No. 66) 98, 563-616. Tedford, R. H. (1970). Principles and practices of mammalian geochronology in North America. In Proceedings of the North American Paleontological Convention, Field Museum of Natural History, Chicago, Sept. 5-7, 1969 (ed. E. L. Yochelson), pp. 666-703. Allen Press, Lawrence.

Thomas, D. J. & Gilmore, A. M. (1976). The terrestrial vertebrate fauna of the Dartmouth Dam inundation area. Australian Wildlife Research 3, 189-208.

Tyler, M. J., Godthelp, H. & Archer, M. (1994). An overview of the Riversleigh frog fauna. Abstracts of the Riversleigh Symposium 1994, University of New South Wales, Sydney, Australia: 7.

Underwood, A. J. (1997). Experiments in Ecology: Their logical design and interpretation using analysis of variance. Cambridge University Press, Cambridge.

______233

Valverde, J. A. (1964). Remarques sur la structrue et l'evolution des communautes de vertebres terrestres. Rev. Ecol. (Terre et Vie) 111, 121-154. Valverde, J. A. (1967). Estructura de una communidad de vertebrados terrestres. C.S.L.C, Madrid. Van Valkenburgh, B. (1990). Skeletal and dental predictors of body mass in carnivores. In Body Size in Mammalian Paleobiology: Estimation and Biological Implications (ed. J. Damuth and B. J. MacFadden). Cambridge University Press, Cambridge.

Voorhies, M. R. (1969). Taphonomy and Population Dynamics of an Early Pliocene Vertebrate Fauna, Knox County, Nebraska. University of Wyoming, Contributions to Geology, Special Paper No. 1 , 1-69. White, A. W. (1997). Cainozoic turtles from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 413-422.

White, M. E. (1997b). After the Greening. Kangaroo Press Pty Ltd, Kenthurst, Australia.

Wilf, P., Beard, K.C., Davies-Vollum, K.S. & Norekjo, J.W. (1998). Potrait of a Late Paleocene (Early Clarkforkian) Terrestrial Ecosystem: Big Multi Quarry and Associated Strata, Washakie Basin, Southwestern Wyoming. Palaios 13, 514- 532. Williams, S. E., Pearson, R. G. & Walsh, P. J. (1996). Distributions and biodiversity of the terrestrial vertebrates of Australia's Wet Tropics: a review of current knowledge. Pacific Conservation Biology 2, 327-62. Willis, P. M. A. (1997). New Crocodilians from the Late Oligocene White Hunter Site, Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 423-438.

Willis, P. M. A. (2000). New crocodilian material from the Miocene of Riversleigh (northwestern Queensland, Australia). In Crocodilian Biology and Evolution (eds G. C. Grigg, F. Seebacher & C. E. Franklin). Surrey Beatty & Sons, Chipping Norton.

Winter, J. W. (1988). Ecological specialization of mammals in Australian tropical and sub-tropical rainforest: Refugial or ecological determinism? Proceedings of the Ecological Society of Australia 15, 127-138.

______234

Woinarski, J. C. Z., Braithwaite, R. W., Menkhorst, K. A., Griffin, S., Fisher, A. & Preece, N. (1992). Gradient analysis of the distribution of mammals in stage III of Kakadu National Park, with a review of the distribution patterns of mammals across north-western Australia. Wildlife Research 19, 233-62. Wroe, S. (1996a). An investigation of phylogeny in the Giant Rat-kangaroo Ekaltadeta (Propleopinae, Hypsiprymnodontidae, Marsupialia). Journal of Paleontology 70, 681 -690. Wroe, S. (1996b). Muribacinus gadiyuli (Thylacinidae: Marsupialia), a very plesiomorphic Thylacinid from the Miocene of Riversleigh, northwestern Queensland, and the problem of paraphyly for the Dasyuridae (Marsupialia). Journal of Paleontology 70, 1032-1044. Wroe, S. (1997a). Mayigriphus orbus gen. et sp. nov., a Miocene dasyuromorphian from Riversleigh, northwestern Queensland. Memoirs of the Queensland Museum 41, 439-448.

Wroe, S. (1997b). Stratigraphy and phylogeny of the giant extinct rat kangaroo (Propleopinae, Hypsiprymnodontidae, Marsupialia). Memoirs of the Queensland Museum 41, 449-456.

Wroe, S. (1998). A new 'bone-cracking' dasyurid (Marsupialia) from the Miocene of Riversleigh, northwestern Queensland. Alcheringa 22, 277-284.

Wroe, S. (1999). Killer kangaroos and other murderous marsupials. Scientific American 280, 68-75.

Wroe, S. (submit) Maximucinus muirheadae gen. et sp. nov. (Thylacinidae: Marsupialia), from the Miocene of Riversleigh, northwestern Queensland, with estimates of body weights for thylacinids.

Wroe, S., Myers, T.J., Wells, R.T., & Gillespie, A. (1999). Estimating the weight of the Pleistocene marsupial lion, Thylacoleo carnifex (Thylacoleonidae: Marsupialia): implications for ecomorphology of a marsupial super-predator and hypotheses of impoverishment of Australian marsupial carnivores fauna. Australian Journal of Zoology 47, 489-498.

Youngson, W. K. & McKenzie, N. L. (1977). The wildlife of the proposed Karron Hill Nature Reserve, Western Australia, pp. 1-31. Department of fisheries and wildlife, Perth.

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Appendix One: Cluster Analysis

Cluster analysis results for all taxonomic levels using presence/absence and relative abundance data

Species presence/absence: paired Raup- Species presence/absence: paired Dice Crick algorithm

Species presence/absence: Ward’s Species presence/absence: paired method Jaccard

Species abundance (log-transformed): Species abundance (log): paired Bray- Ward’s method Curtis

Species abundance (log): paired Species abundance (log): paired Chord Euclidean

Species abundance (log): paired Morisita Generic presence/absence: paired Jaccard

Generic presence/absence: paired Raup- Generic presence/absence: paired Dice Crick

Generic presence/absence: Ward’s Generic abundance (log): paired method Euclidean

Generic abundance (log): Ward’s Generic abundance (log): paired Bray- method Curtis

Generic abundance (log): paired Chord ‘Superfamilial’ presence/absence: paired Raup-Crick

Generic abundance (log): paired Morisita ‘Superfamilial’ presence/absence: paired Jaccard

‘Superfamilial’ presence/absence: paired ‘Superfamilial’ abundance (log): Ward’s Dice method

‘Superfamilial’ presence/absence: ‘Superfamilial’ abundance (log): paired Ward’s method Euclidean

‘Superfamilial’ abundance (log): paired ‘Superfamilial’ abundance log: paired Bray-Curtis Morisita

‘Superfamilial’ abundance log: paired Familial presence/absence: paired Raup- Chord Crick

Familial presence/absence: paired Familial presence/absence: Ward’s Jaccard Method

Familial presence/absence: paired Dice

Appendix Two: Taxonomic relative abundance and presence/absence data for Riversleigh Local Faunas

Table A: ‘Superfamilial’ presence/absence. (1 = present; 0 = absent)

NG COA WW WH UP RING GAG HI HH LM MM CS KCB Phalangeroidea 1 1 1 0 1 1 1 1 1 1 1 1 1 Petauroidea 1 1 1 1 1 1 1 0 1 1 1 1 1 Burramyoidea 1 1 1 1 1 1 1 0 1 1 0 1 1 Tarsipedoidea 1 0 1 1 1 1 1 0 1 1 1 1 0 Pilkipildridae 1 0 1 0 1 0 1 0 1 1 0 1 0 Macropodoidea 1 1 1 1 1 1 1 1 1 1 1 1 1 Diprotodontoidea 1 1 1 1 1 0 1 1 1 1 1 1 1 Wynyardiidae 1 0 1 1 1 1 0 1 0 0 1 1 0 Ilariidae 0 0 0 1 0 0 0 0 0 0 0 0 0 Vombatoidea 0 1 0 0 1 0 0 0 0 0 0 0 0 Thylacoleonidae 1 1 1 1 1 0 0 0 1 0 0 1 1 Phascolarctidae 1 0 0 0 1 0 1 1 1 0 0 1 0 Yaraloidea 1 1 1 1 1 1 1 0 1 1 1 1 1 Dasyuroidea 1 1 1 1 1 1 1 1 1 1 1 1 1 Notoryctidae 1 0 1 0 1 1 0 0 0 0 1 1 0 Yingabalanaridae 0 0 0 0 1 0 0 0 0 0 0 0 0 Yalkaparadontidae 1 0 1 1 1 0 1 0 1 1 1 1 1 Ornithorhynchidae 1 0 0 0 0 1 0 0 0 0 0 0 0

Table B: Superfamilial’ relative abundance (NISP)

NG COA WW WH UP RING GAG HI HH LM MM CS KCB Phalangeroidea 12 1 31 0 86 1 25 1 81 12 11 9 7 Pilkipildridae 6 0 1 0 1 0 1 0 3 1 0 3 0 Petauroidea 33 3 58 10 116 29 26 0 54 8 3 25 25 Burramyoidea 14 6 19 3 153 7 15 0 3 28 0 10 4 Tarsipedoidea 34 0 12 1 58 2 3 0 5 3 1 2 0 Macropodoidea 95 49 500 175 683 5 56 1 201 23 152 261 142 Diprotodontoidea 8 67 11 11 4 0 8 9 44 3 17 23 5 Wynyardiidae 4 0 38 16 5 1 0 1 0 0 16 32 0 Vombatoidea 0 11 0 0 3 0 0 0 0 0 0 0 0 Ilariidae 0 0 0 14 0 0 0 0 0 0 0 0 0 Thylacoleonidae 1 9 1 8 5 0 0 0 12 0 0 1 1 Phascolarctidae 18 0 0 0 2 0 1 1 4 0 0 7 0 Dasyuroidea 20 4 31 22 43 8 17 2 38 11 1 10 2 Yaraloidea 53 2 155 73 7144 112 177 0 923 221 15 973 480 Notoryctidae 11 0 54 0 135 1 0 0 0 0 1 5 0 Ornithorhynchidae 4 0 0 0 0 19 0 0 0 0 0 0 0 Yalkaparadontidae 23 0 14 3 122 0 1 0 1 3 2 47 1 Yingabalanaridae 0 0 0 0 1 0 0 0 0 0 0 0 0 Total 336 152 925 336 8561 185 330 15 1369 313 219 1408 667

Table C: Familial presence/absence: 1 = present; 0 = absent

Family NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS

Dasyuridae 1 1 1 1 1 1 1 1 1 1 1 1 0 1

Petauridae 1 0 1 1 1 1 1 1 1 0 1 0 1 1

Diprotodontidae 1 1 1 1 1 1 0 1 1 1 1 1 1 1

Pseudocheiridae 1 1 1 1 1 1 1 1 1 0 1 1 0 1

Thylacinidae 1 1 1 1 0 1 1 1 1 1 1 0 1 1

Ornithorynchidae 1 0 0 0 0 0 1 0 0 0 0 0 0 0

Burramyidae 1 1 1 1 1 1 1 1 1 0 1 1 0 1

Phascolarctidae 1 0 0 0 0 1 0 1 1 1 1 0 0 1

Acrobatidae 1 0 1 1 0 1 1 1 0 0 1 1 1 1

Hypsiprymnodontidae 1 1 1 1 1 1 0 1 1 0 1 0 1 1

Yaralidae 1 0 1 1 0 1 1 1 0 0 1 1 0 1

Potoroidae 1 1 1 1 0 1 0 1 0 0 1 1 1 1

Thylacoleonidae 1 1 1 1 1 1 0 0 1 0 1 0 0 1

Mirilaniidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0

Ektopodontidae 1 0 1 0 0 1 0 0 0 0 0 0 0 0

Yingabalanaridae 0 0 0 0 0 1 0 0 0 0 0 0 0 0

Yalkaparadontidae 1 0 1 1 1 1 0 1 0 0 1 1 1 1

Pilkipildridae 1 0 1 0 0 1 0 1 0 0 1 1 0 1

Vombatidae 0 1 0 0 0 0 0 0 1 1 0 0 0 1

Palorchestidae 1 0 1 0 0 0 0 1 1 0 1 0 0 1

Ilariidae 0 0 0 1 0 0 0 0 0 0 0 0 0 0

Phalangeridae 1 1 1 0 1 1 1 1 1 1 1 1 1 1

Peramelemorphians 1 1 1 1 1 1 1 1 1 0 1 1 1 1

Wynyardiidae 1 0 1 1 0 1 1 0 0 1 0 0 1 1

Notoryctidae 1 0 1 0 0 1 1 0 0 0 0 0 1 1

Macropodoids 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Table D Generic relative abundance (NISP)

LM NG COA WW WH KCB UP HI RING GAG HH MM CS Strigocuscus 2 0 0 0 0 0 0 0 0 3 0 0 0 Burramys 21 13 6 16 3 4 144 0 7 15 3 0 10 Yalkaparidon 3 23 0 14 3 1 122 0 0 1 1 2 47 Pseudocheirops 1 3 1 1 1 0 1 0 1 1 1 0 1 Yarala 3 5 0 7 1 0 29 0 1 4 1 0 9 Gunawidji 1 9 1 14 1 0 59 0 1 0 1 1 46 Madju 1 4 0 8 1 0 13 0 1 2 1 1 18 Wanburoo 1 0 0 0 0 0 0 0 0 2 3 0 0 Ganguroo 1 0 0 7 0 0 4 0 0 3 3 1 4 Barinya 1 7 2 5 0 0 8 0 0 0 7 0 1 Pildra 1 1 0 1 0 0 1 0 1 1 0 0 1 Parapops 1 1 0 0 1 0 1 0 1 1 0 0 0 Paljara 0 0 0 2 0 1 8 0 0 1 0 0 4 RivSpet 0 7 0 1 0 0 1 0 0 0 0 1 0 Propalorchestes 0 1 0 4 0 0 0 0 0 1 2 0 1 Neohelos 0 6 58 4 0 0 0 0 0 1 7 1 1 Ekaltadeta 0 12 11 8 2 0 32 0 0 8 8 1 17 Chunia 0 2 0 0 0 0 1 0 0 0 0 0 0 notoryctes 0 11 0 70 0 0 135 0 1 0 0 1 5 thylacinus 0 1 0 0 0 0 0 0 0 1 0 1 0

LM NG COA WW WH KCB UP HI RING GAG HH MM CS Obdurodon 0 4 0 0 0 0 0 0 19 0 0 0 0 Hypsiprymnodon 0 2 4 0 0 1 78 0 0 1 0 4 9 Nimiokoala 0 14 0 0 0 0 3 0 0 0 0 0 3 RivSacro 0 10 0 0 0 0 1 0 0 0 0 0 0 RivLacro 0 1 0 0 0 0 0 0 0 0 0 0 0 Wakaleo 0 1 4 0 0 1 4 0 0 0 4 0 0 Bulungu 0 12 0 9 1 0 36 0 1 3 1 0 11 Ngamalacinus 0 1 0 0 0 0 0 0 0 0 0 0 2 Wabularoo 0 5 0 23 6 0 6 0 0 0 0 2 19 Balbaroo 0 1 0 5 1 0 4 1 0 1 2 0 1 Nambaroo 0 3 0 6 2 0 5 0 0 0 0 0 1 Dactylopsila 0 1 0 0 0 0 1 0 0 1 0 0 0 Marlu 0 1 1 1 0 0 0 0 1 1 1 0 1 Priscileo 0 0 2 1 8 0 1 0 0 0 0 0 1 Rhizophascolonus 0 0 4 0 0 0 0 0 0 0 0 0 0 Nimbadon 0 0 0 0 0 0 0 0 0 1 16 0 0 Wururoo 0 0 1 4 1 0 0 0 0 0 0 0 3 Silvabestius 0 0 10 0 0 0 0 1 0 0 0 0 0 Namilamadeta 0 4 0 34 16 0 5 1 1 0 0 16 32 Bulungamaya 0 12 0 11 0 0 9 0 0 3 0 0 16 Hyperpaljara 0 0 0 1 0 0 1 0 0 0 0 0 0

LM NG COA WW WH KCB UP HI RING GAG HH MM CS Durudawiri 0 2 0 3 0 0 0 0 0 0 0 0 0 Ganawamaya 0 0 0 1 1 0 0 0 0 0 0 0 1 Nowidgee 0 0 0 4 3 0 1 0 0 0 0 0 7 Gumardee 0 0 0 1 1 0 1 0 0 0 0 0 5 Djaludjangi 0 0 0 6 0 0 1 0 0 0 1 1 1 Cercartetus 0 0 0 1 0 0 0 0 0 1 0 0 0 Galadi 0 3 0 8 0 0 3 0 1 8 1 1 3 RivLpet 0 0 0 1 0 0 1 0 0 0 0 1 1 Kuterintja 0 0 0 0 14 0 0 0 0 0 0 0 0 Badjcinus 0 0 0 0 6 0 0 0 0 0 0 0 0 Bematherium 0 0 0 0 3 0 0 2 0 0 0 0 0 Nimbacinus 0 0 0 0 1 0 0 0 1 0 6 0 0 Litokoala 0 0 0 0 0 0 1 0 0 1 3 0 0 Yingabalanara 0 0 0 0 0 0 1 0 0 0 0 0 0 Wakiewakie 0 0 0 0 0 0 1 0 0 0 0 0 0 Praegawinga 0 0 0 0 0 0 1 0 0 1 0 0 0 Wabulacinus 0 0 0 0 0 0 0 1 0 0 0 0 1 Trichosurus 0 0 0 0 0 0 0 0 0 5 13 0 0 Muribacinus 0 0 0 0 0 0 0 0 0 1 1 0 0 Djilgaringa 1 0 0 0 0 0 0 0 0 1 0 0 0 Dalamana 0 0 0 0 0 0 0 0 0 1 0 0 0

LM NG COA WW WH KCB UP HI RING GAG HH MM CS Bettongia 0 0 0 0 0 0 0 0 0 0 2 0 0 Phalanger 0 0 0 0 0 0 0 0 0 0 4 0 0 Dasylurinja 0 0 0 0 0 0 0 0 0 0 1 0 0 Wyulda 0 0 0 0 0 0 0 0 0 0 0 1 0 Total 38 183 105 282 77 8 724 6 38 75 94 36 283

Table E: Generic presence/absence

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Barinya 1 1 1 0 0 1 0 0 0 0 1 1 0 1 RivSpet 1 0 1 0 0 1 0 0 1 0 0 0 1 0 Propalorchestes 1 0 1 0 0 0 0 1 0 0 1 0 0 1 Neohelos 1 1 1 0 0 0 0 1 1 0 1 0 1 1 Pildra 1 0 1 0 0 1 1 1 0 0 0 1 0 1 Pseudocheirops 1 1 1 1 0 1 1 1 1 0 1 1 0 1 Thylacinus 1 0 0 0 0 0 0 1 1 0 0 0 1 0 Obdurodon 1 0 0 0 0 0 1 0 0 0 0 0 0 0 Burramys 1 1 1 1 1 1 1 1 1 0 1 1 0 1 Nimiokoala 1 0 0 0 0 1 0 0 0 0 0 0 0 1 RivSacro 1 0 0 0 0 1 0 0 0 0 0 0 0 0 RivLacro 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Ekaltadeta 1 1 1 1 0 1 0 1 1 0 1 0 1 1 Yarala 1 0 1 1 0 1 1 1 0 0 1 1 0 1 Bulungu 1 0 1 1 0 1 1 1 0 0 1 0 0 1 Gunawidji 1 1 1 1 0 1 1 1 0 0 1 1 1 1 Madju 1 0 1 1 0 1 1 1 0 0 1 1 1 1 Galadi 1 0 1 0 0 1 1 1 0 0 1 0 1 1 Bulungamaya 1 0 1 0 0 1 0 1 0 0 0 0 0 1 Wabularoo 1 0 1 1 0 1 0 0 0 0 0 0 1 1

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Balbaroo 1 0 1 1 0 1 0 1 0 1 1 0 0 1 Nambaroo 1 0 1 1 0 1 0 0 0 0 0 0 0 1 Marlu 1 1 1 0 0 0 1 1 0 0 1 0 0 1 Wakaleo 1 1 0 0 1 1 0 0 1 0 1 0 0 0 Paljara 0 0 1 0 1 1 0 1 0 0 0 0 0 1 Hyperpaljara 0 0 1 0 0 1 0 0 0 0 0 0 0 0 Durudawiri 1 0 1 0 0 0 0 0 0 0 0 0 0 0 Ganawamaya 0 0 1 1 0 0 0 0 0 0 0 0 0 1 Ganguroo 0 0 1 0 0 1 0 1 1 0 1 1 1 1 Nowidgee 0 0 1 1 0 1 0 0 0 0 0 0 0 1 Djaludjangi 0 0 1 0 0 1 0 0 0 0 1 0 1 1 Cercartetus 0 0 1 0 0 0 0 1 0 0 0 0 0 0 Gumardee 0 0 1 1 0 1 0 0 0 0 0 0 0 1 Wururoo 0 1 1 1 0 0 0 0 0 0 0 0 0 1 Hypsiprymnodon 1 1 0 0 1 1 0 1 0 0 0 0 1 1 Chunia 1 0 0 0 0 1 0 0 0 0 0 0 0 0 Yingabalanara 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Yalkaparidon 1 0 1 1 1 1 0 1 0 0 1 1 1 1 Wakiewakie 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Wyulda 0 0 0 0 0 0 0 0 0 0 0 0 1 0 Priscileo 0 1 1 1 0 1 0 0 0 0 0 0 0 1

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Strigocuscus 0 0 0 0 0 0 0 1 0 0 0 1 0 1 Ngamalacinus 1 0 0 0 0 0 0 0 0 0 0 0 0 1 Djilgaringa 0 0 0 0 0 0 0 1 0 0 0 1 0 0 Nimbadon 0 0 0 0 0 0 0 1 0 0 1 0 0 0 Litokoala 0 0 0 0 0 1 0 1 0 0 1 0 0 0 Praegawinga 0 0 0 0 0 1 0 1 0 0 0 0 0 0 Kuterintja 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Badjcinus 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Trichosurus 0 0 0 0 0 0 0 1 0 0 1 0 0 0 Wanburoo 0 0 0 0 0 0 0 1 1 0 1 1 0 0 Silvabestius 0 1 0 0 0 0 0 0 0 1 0 0 0 0 Bematherium 0 0 0 1 0 0 0 0 0 1 0 0 0 0 Nimbacinus 0 0 0 1 0 0 1 0 0 0 1 0 0 0 Ganbulanyi 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Mayigriphus 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Phascolarctos 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Warendja 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Palorchestes 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Bettongia 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Wabulacinus 0 0 0 0 0 0 0 0 0 1 0 0 0 1 Muribacinus 0 0 0 0 0 0 0 1 0 0 1 0 0 0

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Dalamana 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Dasylurinja 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Parapops 1 0 0 1 0 1 1 1 0 0 0 1 0 0 RivLpet 0 0 1 0 0 1 0 0 0 0 0 0 1 1 Namilamadeta 1 0 1 1 0 1 1 0 0 1 0 0 1 1 dactylopsiline sp. 1 0 0 0 0 1 0 1 0 0 0 0 0 0 Notoryctes 1 0 1 0 0 1 1 0 0 0 0 0 1 1 Phalanger 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Rhizophascolonus 0 1 0 0 0 0 0 0 0 0 0 0 0 0

Table F: Species relative abundance (NISP)

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Barinya wangala 4 0 0 0 0 8 0 0 0 0 7 0 0 0 RivSpet 7 0 1 0 0 1 0 0 1 0 0 0 1 0 Pr. ponticulus 1 0 1 0 0 0 0 1 0 0 0 0 0 1 Barinya 3 2 0 5 0 0 2 0 0 0 0 0 0 0 0 Neo. tirarensis 1 0 1 0 0 0 0 0 0 0 0 0 1 1 Pseudocheirops sp2 1 1 1 1 0 1 0 1 1 0 0 0 0 1 Barinya 2 1 0 0 0 0 4 0 0 0 0 0 1 0 1 Thylacinus macknessi 1 0 0 0 0 0 0 1 1 0 0 0 1 0 Obdurodon dicksoni 4 0 0 0 0 0 19 0 0 0 0 0 0 0 Burramys brutyi 14 6 19 3 4 153 7 15 1 0 3 21 0 10 Nimiokoala greystanesi 14 0 0 0 0 3 0 0 0 0 0 0 0 3 RivSacro 10 0 0 0 0 1 0 0 0 0 0 0 0 0 RivLacro 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Ekaltadeta ima 1 1 1 1 0 2 0 7 1 0 1 0 1 5 Yarala burchfieldi 5 0 7 1 0 29 1 4 0 0 1 3 0 9 Bulungu palara 12 0 9 1 0 36 1 3 0 0 1 0 0 11 Gunawidji tubus 9 1 14 1 0 59 1 1 0 0 1 1 1 46 Madju ignotae 1 0 8 1 0 2 1 1 0 0 1 1 0 2 Galadi speciosus 3 0 1 0 0 2 1 0 0 0 0 0 1 1

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Madju variae 3 0 1 0 0 11 0 2 0 0 0 0 1 16 Galadi grandis 1 0 1 0 0 1 0 0 0 0 0 0 1 1 Bulungamaya delicata 1 0 11 0 0 9 0 3 0 0 0 0 0 16 Wabularoo naughtoni 5 0 23 6 0 6 0 0 0 0 0 0 2 19 Balbaroo gregoriensis 1 0 2 0 0 1 0 0 0 0 0 0 0 1 Nambaroo sp5 (N.camilleriae) 1 0 1 0 0 1 0 0 0 0 0 0 0 1 Nambaroo sp6 (N.longmorei) 1 0 1 0 0 3 0 0 0 0 0 0 0 0 Neohelos gregoriae 0 1 0 0 0 0 0 0 0 0 0 0 0 0 Ekaltadeta jamiemulvaneyi 0 1 0 0 0 0 0 0 1 0 0 0 0 0 Marlu sp2. 0 1 0 0 0 0 0 1 0 0 0 0 0 0 Wakaleo oldfieldi 0 1 0 0 0 0 0 0 0 0 0 0 0 0 Hyperpaljara sp1. 0 0 1 0 0 1 0 0 0 0 0 0 0 0 Durudawiri inusitatus 0 0 3 0 0 0 0 0 0 0 0 0 0 0 Nambaroo ngar 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Ganawamaya ornata 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Ganguroo bilamina 0 0 7 0 0 1 0 0 0 0 0 0 1 4 Nowidgee matrix 0 0 4 1 0 1 0 0 0 0 0 0 0 7 Djaludjangi yadjana 0 0 1 0 0 1 0 0 0 0 1 0 1 1

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Marlu sp1. 0 0 1 0 0 0 1 1 0 0 1 0 0 0 Ganawamaya aediculis 0 0 1 1 0 0 0 0 0 0 0 0 0 0 Wururoo dayamayi 0 0 1 1 0 0 0 0 0 0 0 0 0 0 Nambaroo couperi 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Pildra sp.3 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Yingabalanara richardsoni 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Yalkaparidon coheni 0 0 0 0 0 1 0 0 0 0 0 0 0 1 Priscileo roskellyae 0 1 0 1 0 1 0 0 0 0 0 0 0 0 Strigocuscus reidi 0 0 0 0 0 0 0 3 0 0 0 2 0 0 Ngamalacinus timmulvaneyi 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Djilgaringa gillespieae 0 0 0 0 0 0 0 1 0 0 0 1 0 0 Nimbadon lavarackorum 0 0 0 0 0 0 0 1 0 0 1 0 0 0 Litokoala kanunkaensis 0 0 0 0 0 0 0 1 0 0 1 0 0 0 Praegawinga badcocki 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Praegawinga winsburyorum 0 0 0 0 0 1 0 0 0 0 0 0 0 0

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Galadi amplus 0 0 0 0 0 0 0 5 0 0 1 0 0 2 Kuterintja ngama 0 0 0 14 0 0 0 0 0 0 0 0 0 0 Badjcinus turnbulli 0 0 0 6 0 0 0 0 0 0 0 0 0 0 Trichosurus dicksoni 0 0 0 0 0 0 0 5 0 0 13 0 0 0 Wururoo sp2 (W.gadiyuli) 0 1 4 0 0 0 0 0 0 0 0 0 0 1 Nambaroo sp2 (N.wilkonsonae) 0 0 2 0 0 0 0 0 0 0 0 0 0 0 Nambaroo sp3 (N.gillespieae) 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Nambaroo sp4 (N.cooki) 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Nowidgee sp2 (N. magnamatrix) 0 0 0 2 0 0 0 0 0 0 0 0 0 0 Balbaroo sp3 (B. hatchae) 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Nambaroo sp8 (N.albovenator) 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Nambaroo sp7 (N.vandycki) 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Wanburoo sp1 (W. hilarus) 0 0 0 0 0 0 0 2 1 0 0 0 0 0

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Ganguroo sp2 (G. robustiter) 0 0 0 0 0 0 0 3 0 0 1 1 0 0 Hypsiprymnodon bartholomaii 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Silvabestius michaelbirti 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Bematherium angulum 0 0 0 3 0 0 0 0 0 2 0 0 0 0 Nimbacinus dicksoni 0 0 0 0 0 0 0 0 0 0 6 0 0 0 Neohelos stirtoni 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Wakaleo vanderleuri 0 0 0 0 0 0 0 0 1 0 1 0 0 0 Wanburoo sp2 (W.wulugu) 0 0 0 0 0 0 0 0 1 0 3 1 0 0 Balbaroo sp4 (B. nalima) 0 0 0 0 0 0 0 0 0 0 2 0 0 0 Ganbulanyi djadjinguli 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Mayigriphus orbus 0 0 0 0 0 0 0 0 2 0 0 0 0 0 Warendja wakefieldi 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Palorchestes anulus 0 0 0 0 0 0 0 0 1 0 0 0 0 0 Pseudocheirops sp.1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 Bettongia moyesi 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Pr. novaculacephalus 0 0 0 0 0 0 0 0 0 0 1 0 0 0

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Yalkaparidon jonesi 0 0 0 0 0 0 0 1 0 0 0 1 0 0 Wabulacinus ridei 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Muribacinus gadiyuli 0 0 0 0 0 0 0 2 0 0 1 0 0 0 Priscileo pitakantensis 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Nimbacinus n. sp 0 0 0 0 0 0 1 0 0 0 0 0 0 0 Dalamana muizonae 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Dasylurinja n.sp. 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Parapops sp1 1 0 0 1 0 1 1 1 0 0 0 1 0 0 Pildra sp4. 0 0 1 0 0 0 1 0 0 0 0 0 0 0 Pildra sp.2 0 0 0 0 0 0 0 1 0 0 0 0 0 1 Marlu sp.3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Pildra sp.1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 Pildra sp.5 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Marlu sp.5 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Parapops sp.2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Pseudocheirops sp.4 0 0 0 0 0 0 0 1 0 0 0 0 0 0 Pseudocheirops sp.3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Marlu kutjamarpensis 1 1 1 0 0 0 1 1 0 0 1 0 0 1 RivLpet 0 0 1 0 0 1 0 0 0 0 0 0 1 1 Paljara nancyhawardae 0 0 1 0 1 1 0 1 0 0 0 0 0 1

NG COA WW WH KCB UP RING GAG ENC HI HH LM MM CS Paljara maxbourkei 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Paljara tirarensae 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Ganawamaya acris 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Total 107 16 142 49 5 348 36 77 15 3 54 35 13 170

Appendix Three: Table of higher-level taxonomy and eco-diversity of fossil species

Mammalia Monotremata Ornithorhynchidae Extant: ‘platypuses’; small-medium sized aquatic arthropod-eaters. Tachyglossidae Extant: medium-large terrestrial ant and worm eaters. Marsupialia Australidelphian Diprotodontia Phalangeriformes Burramyoidea Burramyidae Extant: small, scansorial, arboreal and terrestrial, omnivorous ‘pygmy possums’. Phalangeroidea Miralinidae Extinct: arboreal ‘possums’ Ektopodontidae Extinct: short-faced arboreal, granivorous ‘possums’ Phalangeridae Extant: arboreal, omnivorous ‘brush-tail possums’ & ‘cuscuses’ Pilkipildridae Extinct: arboreal?, omnivorous? ‘possums’ Petauroidea Petauridae Extant: arboreal, scansorial, insectivorous/omnivorous ‘gliders’, ‘striped possums’ & ‘Leadbeater’s possum’ Pseudocheiridae Extant: small-medium size, arboreal, folivorous ‘ringtail’ possums & ‘greater gliders’ Tarsipedoidea Acrobatidae Extant: arboreal, scansorial, nectivorous ‘feather-tail gliders’ Tarsipedidae Extant: arboreal, scansorial, nectivorous ‘honey possums’ Macropodoidea Hypsiprymnodontidae Extant: ‘musky-rat kangaroo’ & extinct medium-large omnivorous to carnivorous, galloping-saltatorial ‘rat-kangaroos’ Potoroidae Extant: terrestrial, saltatorial, omnivorous ‘rat-kangaroos’ Macropodidae Extant: ordinary medium-large, terrestrial-arboreal, saltatorial-scansorial, browsing-grazing ‘kangaroos’ and ‘wallabies’ Balbaridae Extinct: primitive macropodoid browsing, terrestrial ‘kangaroos’ Vombatomorphia Thylacoleonidae Extinct: omnivorous-carnivorous, terrestrial-arboreal, cursorial ‘marsupial lions’ Ilariidae Extinct: medium-large terrestrial, cursorial browsers

Wynyardiidae Extinct: medium sized terrestrial, cursorial browsers Diprotodontoidea Diprotodontidae Extinct: medium-large terrestrial, cursorial-graviportal browsers and grazers Palorchestidae Extinct: medium-large terrestrial, cursorial-graviportal browsers Vombatoidea Vombatidae Extant: ‘wombats’, medium-large fossorial-terrestrial grazers. Some extinct species were browsers. Phascolarctomorphia Phascolarctidae Extant: ‘koalas’, medium sized arboreal folivores Peramelemorphia Yaraloidea Yaralidae Extinct: omnivorous-carnivorous small terrestrial ‘bandicoots’ Perameloidea Peroryctidae Extant: ‘forest bandicoots’, small-medium sized terrestrial omnivores Peramelidae Extant: ‘bandicoots’, small-medium sized terrestrial omnivores Thylacomyidae Extant: ‘bilbies’, small-medium sized terrestrial omnivores Notoryctemorphia Notoryctidae Extant: ‘marsupial moles’, small fossorial insectivores Dasyuromorphia Dasyuridae Extant: small-medium sized terrestrial-arboreal, insectivorous-carnivorous ‘marsupi-carnivores’ Thylacinidae Extinct: ‘Tasmanian Tiger’, medium-large terrestrial, cursorial carnivores Myrmecobiidae Extant: ‘numbats’, small-medium terrestrial insectivores Incertae sedis Yingabalanaridae Extinct: small ? Incertae sedis Yalkaparadontidae Extinct: small, worm-eater? Placentalia Microchiroptera Hipposideridae Extant: ‘leaf-nosed’ bats Rhinolophidae Extant: ‘horse-shoe’ bats Emballonuridae Extant: large ‘sheath-tail’ bats Megadermatidae Extant: large ‘false-vampire’ bats Mystacinidae Extant Molossidae Extant: ‘free-tailed’ or ‘mastiff’ bats

Vespertillionidae Extant: ‘common’ or ‘plain-faced’ bats Megachiroptera Pteropodidae Extant: medium-large herbivorous ‘flying foxes’, ‘fruit bats’ and ‘blossom bats’ Rodentia Muridae Extant: ‘rats’ and ‘mice’, small, terrestrial-arboreal, granivores-omnivores