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Birds of the Diamantina River and Associated Channel Country Wetlands of South Australia

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Birds of the Diamantina River and Associated Channel Country Wetlands of South Australia Birds of the Diamantina River and Associated Channel Country Wetlands of South Australia Julian Reid June 2017 Report to the South Australian Arid Lands Natural Resources Management Board Fenner School of Environment & Society, Australian National University, Canberra Disclaimer The South Australian Arid Lands Natural Resources Management Board, and its employees do not warrant or make any representation regarding the use, or results of use of the information contained herein as to its correctness, accuracy, reliability, currency or otherwise. The South Australian Arid Lands Natural Resources Management Board and its employees expressly disclaim all liability or responsibility to any person using the information or advice. © South Australian Arid Lands Natural Resources Management Board 2017 This report may be cited as: Reid, J. R. W. 2017. Birds of the Diamantina River and associated channel country wetlands of South Australia. Report by Australian National University to the South Australian Arid Lands Natural Resources Management Board, Pt Augusta. Cover images: Pelicans at Diamantina River waterhole May 2015; Sedges on the Warburton River April 2014 Copies of the report can be obtained from: Natural Resources Centre, Port Augusta T: +61 (8) 8648 5300 E: [email protected] Birds of the Diamantina River 2 Contents Abstract 7 1 Introduction 9 1.1 Connectivity 12 1.2 Study Objectives 13 2 Methods 14 2.1 Field Surveys 18 2.2 Data Management 18 2.3 Data Analyses 19 3 Results 25 3.1 Bird Diversity by Site and Year 26 3.2 Landbird Diversity and Abundance 36 3.3 Habitat Variation 41 3.4 Frequency and Abundance of Individual Landbird Species 44 3.5 REML Models 47 3.6 Landbird Assemblages and Multivariate Analyses 57 4 Discussion 66 4.1 Importance of Mistletoes in Riparian Vegetation 69 4.2 Landbird Assemblages and Summary of Distribution and Diversity Patterns 69 4.3 Key Drivers of Bird Diversity and Population Health 75 4.4 Ecosystem and Biogeographic Connectivity and Ecological Refugia 76 4.5 Management Issues 78 4.6 Particular Sites and Areas of Significance to Birds 78 4.7 Significant Bird Species and their Research Needs 79 4.8 Broader Research Needs 80 5 References 81 Appendix 1 Density estimates of birds at each visit to subsites 89 Appendix 2 Complete Birdlist with scientific names 139 Appendix 3 Brief description and midpoint of each transect/subsite 145 List of Tables Table 1 Bird survey schedule and distribution of sites among management zones and major rivers or wetland complex 15 Table 2 Year in which subsites and broad habitats were established and surveyed across sites 16 Table 3 Rank summary scoring system for prevalence of hollows and dead timber categories assessed at each transect subsite 19 Table 4 Habitat codes 21 Birds of the Diamantina River 3 Table 5 Variations in proportionate and actual numbers (means +/- se) of all, waterbird and landbird species at sites across management zones. 29 Table 6 Variations in proportionate and actual numbers (means +/- se) of all, waterbird and landbird species at sites between years. One-way analysis of variance results are shown 29 Table 7 Values of the Simple Matching Coefficient (SMC), expressed as percentage similarity, for all between-site visit comparisons and for various subsets of the data by Year, Property and Site, focussing on within- Property comparisons 30 Table 8 Values of the Simple Matching Coefficient (SMC), expressed as percentage similarity, for all between-site visit comparisons and for various subsets of the data by Year and Property, focussing on between-Property comparisons 31 Table 9 Permutation and distance-based analysis of variance of the survey design factors, year of survey (Year) and management zone (MZU) on site assemblage composition. Sørensen distance on presence-absence data used in adonis routine. Probabilities derived from 999 randomisations 35 Table 10 Summary statistics for landbird community abundance (summed densities of all species per ha), species richness, and their ratio (Ab/Rich) by year of survey and major habitat. Habitats: Riparian (Rip), Floodplain (Fld) and Dune (Dun); the few gibber samples are not shown 36 Table 11 Diversity and evenness indices for landbird communities averaged across the three main habitats (Riparian: Rip; Floodplain: Fld; Dune: Dun) and year. Mean species richness data are first presented for comparison, followed by the community abundance to richness ratio (Abun/Rich). Three diversity indices are presented, namely Shannon-Weaver (Shannon H’), Simpson D1 and Simpson D2. Three evenness indices are presented, namely Pielou E, Simpson E (1 – D1) and Heip E2 (exp(H')/richness) 37 Table 12 Loadings of most influential plant and habitat variables on the first four axes of the PCA 43 Table 13 Frequency and mean abundance (mean density: number of individuals per ha) of landbird species across 140 subsites, with results of Indicator Species Analysis (IV) for the four main survey design variables. The ten most frequent species (bold) are listed first, followed by five of the most abundant species (italics), with the remainder in order of decreasing frequency. MaxCls (class in which maximum abundance and frequency were recorded) and probability values (Pval) from IV indicate those species distributed non- randomly across the four factors 45 Table 14 REML models of landbird species richness as a function of the survey design variables year, management zone and property identity, and habitat, presented in increasing order of complexity from a) year alone, and with the addition of b) management zone and/or property, and c) habitat. LRT: likelihood ratio tests comparing simpler and more complex models, using the change in deviance (chng_dev) assessed with Chi- squared distribution on the difference in degrees of freedom (df). Where all levels of a factor have a t value < 2, as with ManagZone in b), the factor is unlikely to be significant, but formal LRTs were undertaken to assess actual significance 48 Table 15 Improved REML model (tYrFP2H6BrW) of landbird species richness as a function of year, property identity (Prop2), the habitat factor, HabMin, with six levels, and cover of Broughton Willow. The variance estimates for the random effects (1|Site + 1|Site:subsite) are also presented. The standard deviations of the random effects can be interpreted as the expected average difference between species richness at a pair of subsites (1.1) and sites (1.8), while the mean residual of any observation fitted by this model averages ca +/- 3.1 species (see Figure 14) 50 Table 16 REML models including PCA composite variables 52 Table 17 One multi-variable REML model of richness including five plant variables 53 Table 18 A multi-variable REML model of bird species richness including five habitat variables which had the lowest deviance at convergence with all included terms significant 54 Table 19 A multi-variable REML model of bird species richness which included Coolibah and five other significant plant variables 55 Table 20 A multi-variable REML model of square root of landbird species richness which included Coolibah and five other significant plant variables 55 Table 21 Stepwise built multi-variable REML models of square root of landbird community abundance as functions of year and individual habitat variables, excluding Prop2 and habitat (a). Random effect terms were Site and subsite. The square root of species richness was included in b) 56 Birds of the Diamantina River 4 Table 22 Plant and habitat variables strongly correlated with 3d ordination of 138 landbird assemblages. Rm: multiple correlation coefficient; P: probability from 999 randomisations 57 Table 23 Bird species strongly correlated with and responsible for 3d ordination of 138 landbird assemblages. Rm: multiple correlation coefficient. Probabilities from 999 randomisations were 0.001 except for three species asterisked, where P < 0.01. Abbreviations (Abbrv) are given for the species plotted in Figure 18. Species with large negative scores on PCS1 (bold) have strong affinities with riparian sites. Species with large negative scores on PCS2 were more frequent or abundant in 2016 62 Table 24 Centroids (mean position) of sites belonging to the categories (survey design factors) of year, habitat, property identity and management zone. Ignoring the two observations at sites constituting gibber habitat (outliers in the ordination), for each factor the PCS axis values encompassing the greatest spread of groups are bolded 63 Table 25 Results of a) cca tests of the factors year, habitat, property and management zone on the raw data of 138 transect observations of 64 landbird species, and b) capscale tests of habitat, property and management zone on the NMDS ordination scores (PCS1-3) averaged across years for 81 unique subsites, under different permutation models for assessing levels of significance: P1- unconstrained (free) permutations across all observations; P2- shuffling of subsite observations only permitted within sites; P3- shuffling within sites in cca tests and within habitat classes in capscale test. Chi-square (ChiSq) partitioning in cca is the equivalent of variance partitioning in capscale analyses. All tests assessed the partial effect of the focal term, in combination with other factors in the model 65 Table 26 Correlative strength of the most influential individual plant and habitat variables in relation to bird species richness (REML models) and assemblage composition (PCC), for comparison. The first 15 variables are listed in rank order of the multiple correlation coefficient (Rm) from PCC (bolded values indicate P = 0.001); the last seven variables were in the top 18 ranks from REML models (bolded values indicate P <= 0.005). All REML models contained the Site and subsite terms as random effects and YrF and Prop as fixed effects, with the effect of plant and habitat variables tested one at a time (n = 142). PCC results are from Table 22, relating to the NMDS ordination shown in Figure 15 (n = 138) 68 Table 27 Species most frequently observed in the three main habitats on a) riparian, b) floodplain, and c) sand dune transects.
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