Chapter 5. Detection Probabilities and Optimal Survey Methods for Tasmanian Anurans Under Varying Environmental Conditions

Chapter 5. Detection probabilities and optimal survey methods for Tasmanian anurans under varying environmental conditions.

David Wilson, Matt Webb, Annie Philips

Biodiversity Conservation Branch, Department of Primary Industries, Parks, Water and Environment, PO Box 44 Hobart, Tasmania, 7001.

Introduction

Recent declines have been reported in many frog species worldwide (Stuart et al. 2004), leading to calls for increased anuran research and monitoring programs (Alford and Richards 1999; Collins and Storfer 2003). This has resulted in the growth of studies examining the best methods for monitoring frogs. One commonly used method of monitoring frog species is by the use of call surveys of males during the breeding season (e.g. de Solla et al. 2005; Pellet and Schmidt 2005; Weir and Mossman 2005). Research on how to best monitor include the best time of day to survey (e.g. Heard et al. 2006), how long each survey should last (Shirose et al. 1997; Pierce and Gutzwiller 2004), and the effects of environmental conditions on detection (Pellet and Schmidt 2005; Weir et al. 2005).

A critical assumption of this single survey methods is that species not detected during surveys are truly absent, rather than being present and undetected (MacKenzie et al. 2002; Bailey et al. 2004), and this is unlikely to be true for most anuran species (Pellet and Schmidt 2005; Schmidt 2005; Jackson et al. 2006). Unless accounted for in the analysis, non- detection of species actually present may have serious consequences for inferences drawn from the data (Moilanen 2002; Gu and Swihart 2004). Recent analytical advances have shown that it is possible to quantify a species’ probability of detection when repeat surveys at a series of sites are done in a relatively short time period (MacKenzie et al. 2002; Royle and Nichols 2003; MacKenzie et al. 2006).

Developing accurate detection probabilities is particularly important for threatened and endemic species, which are often the focus of research and monitoring activities (e.g. Buckley and Beebee 2004; Heard et al. 2006; Jackson et al. 2006). For these species accurate assessment of site occupancy is vital to underpin monitoring activities and evaluate species’ responses to management activities. Tasmania has five species of threatened or endemic anurans for which this information is particularly important and timely. Recently, the emerging infectious disease Batrachochytrium dendrobatidis has been detected in Tasmania (Obendorf and Dalton 2006) and this may pose a significant threat to Tasmania’s threatened and endemic anurans, especially given the catastrophic declines reported elsewhere (Berger et al. 1998; Stuart et al. 2004).

Here we provide data to guide the design of monitoring programs for Tasmanian anurans. Specifically we compare detection probabilities between four survey types - five or 20 minute survey duration and diurnal or nocturnal surveys - to determine an optimal survey type for each species. We then develop cumulative detection probability graphs for any given number of surveys. Next we consider the effect of environmental variables on detection probabilities for the optimum method. Taken together, this information is essential to design an optimal monitoring strategy.

Materials and Methods

Study species and data collection

Eleven species of anurans occur in Tasmania, seven of which breed during the austral spring – summer period (Anstis 2002; Littlejohn 2003) and are the focus of research presented here. The green and gold frog Litoria raniformis is listed as vulnerable while the striped marsh frog Limnodynastes peronii is listed as endangered (Tasmanian Threatened Species Act 1995). Drainage and clearance of wetlands has been identified as the major threat to L. raniformis, and declines have been noted in all areas of the state in the last 20 years (Threatened-Species-Unit 2001). Of the three endemic species, the moss froglet Bryobatrachus nimbus has a very restricted range in sub-alpine moorland and rainforest while the Tasmanian froglet Crinia tasmaniensis and the Tasmanian tree frog Litoria burrowsae are restricted to the west and southwest areas of the state (Littlejohn 2003, authors' unpubl. data). Results for Limnodynastes tasmaniensis and Limnodynastes dumerilii are also presented, although both these species are common throughout their range.

We established sampling sites in three areas of Tasmania (Figure 1) to cover the seven species of interest; along the north coast (Area A: 40 sites), in the southwest (Area B: 31 sites) and in the southeast (Area C: 10 sites). We surveyed sites during both the day (only Areas A and B) and night (all three areas) during two periods: November 2008 to January 2009 (Area A) and November 2009 to February 2010 (Areas B & C). Day surveys were completed at least an hour before sunset, while night surveys commenced after civil twilight. The order of surveys on any given night was randomised to reduce potential autocorrelation in the data.

Figure 1. Study areas used to determine detection probabilities for anurans in Tasmania, Australia.

Surveys differed between species due to variation in their ecology. For six species we sat quietly at each site and recorded the species heard calling within a five and 20 minute period. Thus for these species we have four survey types – five minute day aural, 20 minute day aural, five minute night aural and 20 minute night aural. We varied this methodology for L.raniformis as this species is large and has a propensity to bask (Littlejohn 2003). After the initial five minute listening period we played five minutes of recorded L. raniformis calls through a megaphone in order to provoke a response from individuals that may have been present but not calling. In the following 10 minutes we conducted a visual search for active L. raniformis at each site.

At the end of each survey we recorded a number of environmental variables which may affect the propensity of individuals to call. We recorded air and water temperature using a digital thermometer, and relative humidity using a whirling psychrometer. We also scored cloud cover (0-8), wind speed (0-3) and rainfall (0-2) averaged over the duration of the survey.

Statistical analysis

When species are present at a site, but not always detected, then their detection probability is less than 1.0, and this can be estimated when repeat sampling occurs at a number of sites using maximum likelihood methods (MacKenzie et al. 2002; MacKenzie et al. 2006), We use the program PRESENCE (MacKenzie et al. 2002; Hines 2006) to fit models for detection of seven species of Tasmanian frogs using repeat sampling data. We estimated detection probabilities using a basic model for six (L. raniformis) or four (other six species) survey types for each species. This basic model assumes that detection probability was constant among both sites and survey occasions. The optimum survey type for each species was defined as the one with the highest basic detection probability.

The estimated single-survey detection probability (p) can be used to estimate an overall detection probability given any number of surveys. We used the basic detection probability with the optimal survey type to develop these curves for each species using the equation:

P = 1 – (1-p)n

Where P is the overall estimated probability of detection after n surveys (Kéry 2002).

We then extended the optimal survey type model to examine the effects of environmental and other covariates on detection probabilities. For all seven species we ran 12 separate models; the basic model (as above), one with survey specific detection probability, another which accounted for seasonal variation, and nine models using environmental parameters. These consisted of the six recorded at the end of each survey, plus the amount of moon visible during the survey (data from Geosciences Australia http://www.ga.gov.au/geodesy/astro/moonrise.jsp and the United States Naval Observatory http://aa.usno.navy.mil/data/docs/RS_OneDay.php) and whether or not it rained in the 24h or 72h prior to each survey (data from the Australian Bureau of Meteorology www.bom.gov.au). The relative support for alternative models was assessed by comparing the values of the corrected Akaike’s information criterion (AICc) and the normalised Akaike’s model selection weights (w) for each model (Burnham and Anderson 2002). Survey numbers for each species were reduced when compared with the basic detection probability comparison as we only included surveys with full covariate information. Where an environmental variable was the best supported model (three species) we plotted how changes in this variable altered the single-visit detection probability using the PRESENCE model output.

Results

We undertook 797 surveys of 81 sites across Tasmania over two breeding seasons. Litoria burrowsae was the least common species (11 records in 315 surveys), while L. dumerilii and C. tasmaniensis were the most commonly recorded species (112 records in 318 surveys and 94 records in 176 surveys respectively). Bryobatrachus nimbus was heard on every night survey (32 of 32), while L. burrowsae was never recorded calling during the day.

Basic detection probabilities varied from 0.00 (L. burrowsae in both 5 and 20 minute day aural surveys) to 0.77 for C. tasmaniensis. Comparison of basic detection probabilities for each species under alternative survey types found varying responses. For the six species where we undertook aural surveys only, optimum survey types for three of these species (L. dumerilii, L. peronii and L. tasmaniensis) were 20 minute night surveys. For both B. nimbus and L. burrowsae there was no statistical difference between five and 20 minute night surveys, but for differing reasons. In B. nimbus calling was recorded during the first five minutes of every survey, while for L. burrowsae we only recorded calling during an extra two surveys when extending survey length to 20 minutes, but this did not affect the basic detection probability (5 minute = 0.250, 20 minute = 0.255). Crinia tasmaniensis was best detected by 20 minute aural day time surveys. For L. raniformis the highest basic detection probability was 20 minutes night surveys when both aural and visual survey techniques were combined.

Table 1

Basic detection probabilities of seven species of Tasmanian frogs under six different survey types and the most parsimonious environmental model to explain variation in detection under the optimal survey type. Optimum survey type is highlighted in bold, and was chosen as that one for each species with the highest basic detection probability. The most parsimonious model for each species is based on the highest normalised Akaike’s model selection weight (see Appendix H for outputs from all models).

Single-visit detection probability (number of times detection / total number of surveys Most Optimum basic detection probability (95% confidence interval)) parsimonious Species survey 20 minutes 20 minutes model 5 minutes day, 5 minutes night, 20 minutes combination 20 minutes day, aural day, aural + night, aural + (where possible) aural aural night, aural visual visual 34 / 181 43 / 137 9 / 181 12 / 137 20 minute night, L. raniformis - 0.50 (0.37- - 0.69 (0.56- p(Survey) 0.12 (0.03-0.35) 0.34 (0.16-0.57) aural + visual 0.63) 0.80) 0 / 173 0 / 173 9 / 142 11 / 142 20 minutes L. burrowsae - - - 0.00 0.00 0.25 (0.11-0.48) 0.26 (0.12-0.46) aural, night 45 / 97 62 / 97 24 / 79 32 / 79 20 minutes C. tasmaniensis - - p(Air Temp) 0.57 (0.45-0.68) 0.77 (0.66-0.84) 0.32 (0.22-0.47) 0.48 (0.35-0.61) aural, day Limnodynastes 39 / 181 46 / 181 53 / 137 66 / 137 20 minutes - - p(Water) dumerili 0.45 (0.33-0.57) 0.48 (0.37-0.59) 0.58 (0.46-0.69) 0.66 (0.55-0.76) aural, night 21 / 100 27 / 100 20 minutes L. tasmaniensis - - - - - 0.34 (0.23-0.47) 0.44 (0.32-0.57) aural, night 8 / 181 15 / 181 21 / 137 25 / 137 20 minutes L. peronii - - p(Water) 0.21 (0.07-0.49) 0.32 (0.18-0.51) 0.57 (0.38-0.73) 0.64 (0.46-0.78) aural, night Bryobatrachus 13 / 32 18 / 32 32 / 32 32 / 32 5 minutes aural, - - -b nimbus 0.41 (0.25-0.58) 0.56 (0.39-0.72) 1.0 1.0 night

These basic detection probabilities for optimum survey types were used to develop graphs of the cumulative detection probability after any given number of surveys (Fig. 2). These can be used to determine the number of surveys required to obtain a probability of detection with any given confidence level. For example, within the period we surveyed, two surveys are required to be 90% confident of detecting C. tasmaniensis and L. raniformis, while this number increases to three for L. peronii and L. dumerilii, four for L. tasmaniensis and nine for L. burrowsae.

0.8

0.6

0.4

0.2 Litoria raniformis 0 0 2 4 6 8 10

0.8

0.6

0.4

0.2 Litoria burrowsae 0 0 2 4 6 8 10

Cumulative probability of detection of probability Cumulative

0.8

0.6

0.4

0.2 Crinia tasmaniensis 0 0 2 4 6 8 10

Number of surveys

0.8

0.6

0.4

0.2 Limnodynastes dumerilii 0 0 2 4 6 8 10

0.8

0.6

0.4

0.2 Limnodynastes tasmaniensis 0 0 2 4 6 8 10

Cumulative probability of detection of probability Cumulative

0.8

0.6

0.4

0.2 Limnodynastes peronii 0 0 2 4 6 8 10

Number of surveys

Figure 2. Cumulative detection probabilities for key Tasmanian anurans under each species’ optimum survey type, based on the highest basic detection probability (Table 1).

In four species we were able to model the effect of individual environmental variables in explaining the observed variation in detection using optimum survey methods. For L. raniformis the best model was one with a survey-specific detection probability (w=0.719), while for C. tasmaniensis air temperature during the survey accounted for the most variation in detection probabilities between surveys (w=0.592) (Table 1, Appendix 1). In two species (L. dumerilii and L. peronii) water temperature at the time of the survey was the best

supported model (w=0.473 and w=0.145 respectively) (Table 1, Appendix 1). While water temperature was the best candidate model for L. peronii, five models had high levels of support (w >0.10 for water temperature, air temperature, relative humidity, constant and wind, Appendix 1). For the three species where air or water temperature was the most parsimonious model, detection probabilities increased with increasing temperature (Fig. 3).

0.8

0.6

0.4

0.2 Basic detection probability detection Basic Crinia tasmaniensis 0 0 10 20 30 40 Air Temperature (Celcius)

0.8

0.6

0.4

0.2 Basic detection probability detection Basic Limnodynastes dumerilii 0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Water Temperature (Celcius)

0.8

0.6

0.4

0.2 Basic detection probability detection Basic Limnodynestes peronii 0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Water Temperature (Celcius)

Figure 3.The effect of the most important environmental variable on single-survey detection probability for three Tasmanian anuran species where this was possible. The bold line represents the detection probability and the line above and below represent the 95% confidence intervals.

Discussion

Anurans are under considerable threat from a variety of sources, and recent declines have led to a call for increased monitoring and research (Alford and Richards 1999; Collins and Storfer 2003). These actions rely on accurate knowledge of site occupancy and appropriate survey methods, information which is lacking for many species. Our work shows that for the seven species studied, the optimum survey type is species-specific, although 20 minute surveys at night using aural (or aural + visual) are the most effective combination. Importantly, our results show that even using an optimum survey type, detection probabilities can be low during a single survey. Air and water temperatures explain significant variation in calling for some species, and surveying during optimum environmental conditions increases the likelihood of detection for these species. Together, these findings have significant implications for the design of research and monitoring programs for these species and inference of population trends using historical presence / absence data.

Optimal survey type

While the best time of day to undertake anuran call surveys and the effect of survey duration on detection probabilities would seem obvious, this has rarely been tested (but see Pierce and Gutzwiller 2004; Heard et al. 2006). For five of the seven species we studied longer survey duration increased species’ detection; however this was neither the case for B. nimbus nor L. burrowsae when we had no increase in detection probability with an extra 15 minutes of survey. For L. burrowsae we believe that this result is an artefact of the

analysis method rather than a reflection on the species biology. We found they called only intermittently during surveys and were detected only a few times from few sites. For these reasons we suggest conducting 20 minute rather than five minute surveys at night for this species. Six of the Tasmanian anuran species we studied were more vocal at night than during the day, as has traditionally been assumed (Littlejohn 2003). Detection probabilities have been previously calculated for one species which we studied; L. raniformis in Victoria (Heard et al. 2006). While the two studies used different survey methods the results are broadly comparable and reach the same conclusions, with higher detection probabilities at night than during the day. Using our most comparable methods (20 minutes, aural and visual survey), during the day our study had a detection probability of 0.50 compared with 0.11 for L. raniformis in Victoria, however detection probabilities for both studies were 0.69 at night (Heard et al. 2006).

We undertook surveys at times of the year when species were thought to be most detectable (authors' unpubl. data, Littlejohn 2003; Pauza et al. in review), as has been recommended for other large-scale anuran monitoring programs (e.g. Weir and Mossman 2005). Detection probabilities have been shown to vary widely during a season for a single species (Weir et al. 2005; Jackson et al. 2006), and thus may be significantly different for species in this study at times other than those we surveyed. We did however, find congruence in L. raniformis detection probabilities (both 0.69) between our optimal survey type and the equivalent method used by Heard et al. (2006), despite the spatial and temporal separation of the two studies. This suggests, for this species at least, that detection may not vary significantly between areas or seasons. We recommend, however, that repeat sampling be incorporated at a subset of sites in any research or monitoring program. These can be used to develop detection probabilities specific to that study, and be a useful contrast to already published information.

Effect of environmental variables

Environmental conditions are known to affect calling in anurans (Oseen and Wassersug 2002; Saenz et al. 2006), and can have important effects on detection probabilities (e.g. Pellet and Schmidt 2005; Weir et al. 2005). Of the four species where environmental analysis was possible, we found that temperature explained the most variation for three (air temperature in C. tasmaniensis and water temperature in both L. dumerilii and L. peronii). In general, air and water temperatures are strongly collated, and this is reflected in C. tasmaniensis and L. peronii where the two best supported models were air and water temperature (Appendix 1).These results are intuitive, and supports findings elsewhere that temperature best explains variation in calling of some species (Pellet and Schmidt 2005; Weir et al. 2005; Gooch et al. 2006). Thus for these three species the likelihood of detection can be increased by doing surveys during warmer conditions. If minimum environmental conditions are set a priori of surveys commencing, then this may require fewer visits to have

the same confidence in the results, however this increase in efficiency must be contrasted with fewer opportunities for surveys given the reduced suitable environmental conditions.

Implications for monitoring programs

The information we provide here is a framework for determining appropriate future monitoring for these species. Through repeated sampling of specific sites, occupancy can be rigorously assessed and robust conclusions drawn about species status at locations. Secondly, this information can be used to re-assess historical records of species presence or absence. Changes in extent of occurrence must be viewed with caution unless repeat sampling has occurred. We suggest that detection probabilities be incorporated more widely into studies of wildlife populations and be considered when making decisions based on species’ status at specific sites.

Acknowledgements

We would like to thank those landholders who provided access to survey sites. Duncan MacKenzie and Wayne Robinson contributed to early discussions on appropriate statistical analysis. Clare Hawkins, Michael Driessen, Phil Bell and Anna Egan helped to collect data in the field. Comments by Wayne Robinson greatly improved earlier versions of the manuscript. Fieldwork was undertaken in line with collection permits issued under the Nature Conservation Act 2002.

Appendix. Full model results of explanatory variables on frog detection

Full model results for each species under optimum survey types (ΔAIC = change in Akaike’s information criterion when compared to the most parsimonious model, w = relative weighting of each model, K = relative degrees of freedom in the model, ψ = site occupancy (which was constant for all models) and p = detection probability).

Model Log-likelihood ΔAIC w K

Litoria raniformis (basic ψ = 0.46 (95% CI 0.31-0.62)) ψ(.)p(Survey) 60.02 0.00 0.719 24 ψ(.)p(Water Temp) 106.65 2.63 0.193 2 ψ(.)p(Moon) 110.37 6.35 0.030 2 ψ(.)p(Day) 111.22 7.20 0.020 2 ψ(.)p(.) 112.20 8.18 0.012 2 ψ(.)p(RH) 112.57 8.55 0.010 2 ψ(.)p(Air Temp) 112.97 8.95 <0.01 2 ψ(.)p(Rain72) 115.35 11.33 <0.01 2 ψ(.)p(Cloud) 115.82 11.80 <0.01 2 ψ(.)p(Rain) 116.12 12.10 <0.01 2 ψ(.)p(Rain24) 117.02 13.00 <0.01 2 ψ(.)p(Wind) 117.48 13.46 <0.01 2

Crinia tasmaniensis (basic ψ = 0.76 (95% CI 0.52-0.90)) ψ(.)p(Air Temp) 101.62 0.00 0.5922 2 ψ(.)p(Water Temp) 103.98 2.38 0.1802 2 ψ(.)p(Rain72) 105.47 3.87 0.0855 2 ψ(.)p(Wind) 106.70 5.10 0.0462 2 ψ(.)p(.) 107.14 5.54 0.0371 2 ψ(.)p(Day) 108.37 6.77 0.0201 2 ψ(.)p(RH) 114.70 13.10 <0.01 2 ψ(.)p(Survey) 90.07 14.47 <0.01 15 ψ(.)p(Cloud) 118.60 17.00 <0.01 2 ψ(.)p(Rain24) 118.69 17.09 <0.01 2 ψ(.)p(Rain) 129.34 27.74 <0.01 2

Limnodynastes dumerilii (basic ψ = 0.73 (95% CI 0.55-0.86)) ψ(.)p(Water Temp) 147.09 0.00 0.4727 2 ψ(.)p(.) 149.20 2.11 0.1646 2 ψ(.)p(RH) 149.74 2.65 0.1256 2 ψ(.)p(Rain72) 150.79 3.70 0.0743 2 ψ(.)p(Air Temp) 150.95 3.86 0.0686 2 ψ(.)p(Rain24) 152.27 5.18 0.0355 2 ψ(.)p(Moon) 153.13 6.04 0.0231 2 ψ(.)p(Day) 153.56 6.47 0.0186 2 ψ(.)p(Cloud) 155.00 7.91 <0.01 2 ψ(.)p(Wind) 155.27 8.18 <0.01 2 ψ(.)p(Rain) 166.36 19.27 <0.01 2

ψ(.)p(Survey) 129.46 26.37 <0.01 24

Limnodynastes peronii (basic ψ = 0.26 (95% CI 0.14-0.43)) ψ(.)p(Water Temp) 83.64 0.00 0.1446 2 ψ(.)p(Air Temp) 83.67 0.03 0.1424 2 ψ(.)p(RH) 83.82 0.18 0.1321 2 ψ(.)p(.) 84.06 0.42 0.1172 2 ψ(.)p(Wind) 84.33 0.69 0.1024 2 ψ(.)p(Day) 84.44 0.80 0.0969 2 ψ(.)p(Cloud) 85.03 1.39 0.0721 2 ψ(.)p(Rain72) 85.27 1.63 0.0640 2 ψ(.)p(Rain24) 86.17 2.53 0.0408 2 ψ(.)p(Moon) 86.47 2.83 0.0351 2 ψ(.)p(Rain) 86.94 3.30 0.0278 2 ψ(.)p(Survey) 47.18 3.54 0.0246 22

Chapter 6. Environmental modelling of historic and current distribution for Tasmania's two threatened and three endemic frog species

David Wilson

Biodiversity Conservation Branch, Department of Primary Industries, Parks, Water and Environment, PO Box 44 Hobart, Tasmania, 7001.

Introduction

Chytrid fungus was first reported from the wild in Tasmania in 2004 (Obendorf and Dalton 2006), although it was detected in a captive individual in 1993 (Animal Health Laboratory, Launceston). Chytrid has cause catastrophic declines and extinctions of anurans worldwide, including in Australia, and declines can occur rapidly (e.g. Berger et al. 1998; Skelly et al. 2003; Brem and Lips 2008). In light of the potential threat posed by chytrid and the knowledge that it has been in the state since at least 1993, we assessed the historic and current known and predicted distribution of five of Tasmania’s anuran species to determine any changes in range which may be a result of chytridiomycosis. These species are those which are either listed under state or federal legislation (Litoria raniformis, Limnodynastes peronii) or those endemic to Tasmania and thus embody unique qualities (Litoria burrowsae, Crinia tasmaniensis, Bryobatrachus nimbus). Methods

We separated records of each species into those occurring before 1995 (historic) and after 2006 (current). Historic distribution represents the period before chytrid was present in the state, while 2006 represents the start of intense anuran monitoring associated with this report and the resultant chytrid management plan. Records between these time periods were ignored to allow any changes in distribution to be evident between the two time periods.

Historic location records were sourced from the Tasmanian Government’s Natural Values Atlas (NVA), while current location records were primarily from our fieldwork, plus additional records sourced from the NVA and private individuals.

I used all locations records for each species within each time period to model the predicted distribution of that species in Tasmania. Models of predicted distribution were developed in MaxEnt (Phillips et al. 2006: version 3.3.1) using 19 environmental parameters at 30 second resolution. These were downloaded from the WorldClim dataset (Hijmans et al. 2005: version 1.4) and cropped to include only Tasmania (S 39.27 - 43.90, E 143.60 – 148.70). Locations for each species in each time period were overlaid on the environmental variables to produce a predicted probability of occurrence across Tasmania. In the MaxEnt model

output values for each cell (approximately 1km2) range from 0.0 to 1.0, with larger values indicating a greater probability of occurrence and any cell value greater than 0.1 indicating it is suitable for occurrence (Phillips et al. 2006). Outputs were projected in ArcMap 9.3 (ESRI Inc., USA) for display. Results

I was able to produce current and historic known and predicted distribution maps for four of Tasmania’s five threatened or endemic species as B. nimbus was only described in 1994 (Rounsevell et al. 1994). For two of the other four species where comparisons between historic and current distributions were possible no changes were evident in either known or predicted distributional ranges (L. peronii and L. burrowsae). In L. raniformis both the known and predicted distribution declined in the current period when compared to the historic period. This decline was most obvious in the south and east (see Chapter 7 for further information and discussion of the decline in this species). Crinia tasmaniensis showed a marked decline in known distribution from historic to current scenarios, with no records from much of the north half of the island in the current period. The predicted distribution shows a corresponding decline in distribution, although this is not as large and some areas with suitable conditions are still predicted in the north of the state. Discussion

With one exception, my results support the current status of the five frogs under consideration here. Crinia tasmaniensis is of concern though as my results show that it has suffered a significant range contraction, and is now found over only half of its former range. This species has a unique call (Littlejohn 2003) and it is highly detectable during the day (Chapter 5) which means it is unlikely to have been overlooked.

While two species have shown declines between the two periods, it is problematic to attribute this decline to a single factor, or even a combination of factors. While the criteria used to select time periods were based on the discovery of chytrid in Tasmanian, there is no direct evidence that chytrid has caused these declines. For L. raniformis previous threats that have been identified include degradation, fragmentation and alteration of habitat (Threatened Species Unit 2001), and it is likely that their ongoing affect has led to the decline observed here. Although chytrid occurs throughout their range, they are not very susceptible to the disease under laboratory conditions (Chapter 3) and no populations are known to have gone extinct due to chytrid.

In contrast, chytrid is implicated in the decline of C. tasmaniensis. This species has declined from all areas known to be infected with chytrid fungus, and now only occurs in areas known to be chytrid negative. Other factors may also be implicated, as the area where C. tasmaniensis has declined has intense agriculture which may also affect the species. Further work is required in both the laboratory and field to determine if there is a causal link between the presence of chytrid fungus and the decline of this species.

Figure 1. Current (2006-present) and historic (pre 1995) distributions and predicted distributions of Tasmania’s two threatened (L. raniformis and L. peronii) and three endemic (L. burrowsae, C. tasmaniensis and B. nimbus) frog species. Points indicted species presence (either by visual identification or call surveys). Grey shading indicates predicted distribution. Note we assume chytrid fungus was introduced to wild Tasmanian amphibians around in mid 1990’s. Note also historic records are not available for B. nimbus.

Chapter 7. Recent range contraction of Litoria raniformis in Tasmania inferred through environmental modelling and repeat surveys

David Wilson

Biodiversity Conservation Branch, Department of Primary Industries, Parks, Water and Environment, PO Box 44 Hobart, Tasmania, 7001.

Introduction

Amphibians have shown recent worldwide rapid declines and extinctions, which have been variously attributed to habitat degradation and loss, climate change or infectious disease (Stuart et al. 2004). Declining amphibian species are overrepresented in Australia (Stuart et al. 2004), where recent drastic declines in tropical species have been linked to the amphibian fungus, Batrachochytrium dendrobatidis (hereafter Bd) (Berger et al. 1998).

The green and gold frog Litoria raniformis (Hylidae) is listed as endangered on both the IUCN redlist (Hero et al. 2004) and in Tasmania (Threatened Species Conservation Act 1995) due to recent declines. Causes for these declines have been attributed to a multiple of factors including introduced species, an increase in agricultural chemical use, and habitat loss, degradation and fragmentation (Threatened Species Unit 2001; Hero et al. 2004). Here we use two complementary methods to assess the population trend of L. raniformis in Tasmania.

While rapid declines are often obvious and easily detected, gradual declines are harder to identify without long-term monitoring. Amphibians are especially problematic in this regard as they are often highly cryptic outside of a relatively short breeding season, and suitable breeding conditions may occur on a less than annual basis. Thus, surveys comprising of singe visits to a site may record false absences (Wilson et al. in prep) and lead to incorrect conclusions on the population trends or status of the species in question (e.g. Gu and Swihart 2004). Methods and Results

Initially, we modelled the distribution of L. raniformis over two time periods (pre-1995 – ‘historic’ and 2008-10 – ‘current’) to examine changes in their predicted area of occupancy. This break corresponds to the first known record of Bd into Tasmania (1993, Animal Health Laboratory, Launceston). Bd has been implicated in amphibian declines and extinctions worldwide (Stuart et al. 2004), and is known to infect L. raniformis, causing significant mortality in this species (Voyles et al. prep). Historic records of L. raniformis were sourced from the Tasmanian Government’s Natural Vegetation Atlas (www.naturalvaluesatlas.dpiw.tas.gov.au), while current records came from our own research (authors’ unpubl. data). Duplicate records for each time period (those within 500m) were removed from the input data.

Models of predicted distribution for L. raniformis in each time period were developed in MaxEnt (Phillips et al. 2006: version 3.3.1) using 19 environmental parameters at 30 second resolution. These were downloaded from the WorldClim dataset (Hijmans et al. 2005: version 1.4) and cropped to include only Tasmania (S 39.27 - 43.90, E 143.60 – 148.70). Locations of L. raniformis (85 historic or 46 current: see Appendix A) were overlaid on the environmental variables to produce a predicted probability of occurrence across Tasmania. Values for each cell (approximately 1km2) ranged from 0.0 to 1.0 with larger values indicating a greater probability of occurrence for L. raniformis. For the purposes of comparison we separated occurrence probabilities into four groups; species absent (values 0.0-0.1), range (0.1-1.0), intermediate (0.33-1.0) and core (0.66-1.0) distribution areas (Phillips et al. 2006; Penman et al. in press). Outputs were projected in ArcMap 9.3 (ESRI Inc., USA) to calculate areas of occurrence.

Discussion

Outputs from the two time periods showed general agreement in areas where L. raniformis was predicted to occur, despite unbalanced sampling in both space and time between the two periods. Additionally, the same environmental variable (precipitation of the warmest quarter) explained the most variation in both models (32% and 37% in historic and current models respectively). These factors suggest that environmental modelling is valid way to assess range contractions in this species.

Comparison of the models show that the predicted area of occurrence all declined by approximately 50% for all three metrics between historic and current periods (core: 53%, intermediate: 57%, and range: 43%). Our historical model predicted the range of L. raniformis to include much of northern and eastern Tasmania, including offshore islands, plus an isolated southern population (Fig. 1a). Using current locations, the predicted range

of occurrence for L. raniformis in our model has contracted significantly northwards, with very little area predicted for the southern population or in the north-east of the state. While shrinking under the current model, the predicted core area of occurrence under both situations appears to be geographically maintained in the north-east, and on both northern islands.

To add support to these conclusions, we undertook targeted surveys for L. raniformis in an area with the largest predicted core area range contraction; the southern population. Eleven sites where L. raniformis had been recorded historically (in bold, Appendix A) were monitored ten times, or until L. raniformis was heard, between December 2009 and January 2010. Aural surveys at each site lasted 20 minutes and commenced at least 30 minutes after civil twilight. Ten repeats are required to be certain that L. raniformis are absent (with a 90% confidence), rather than simply not detected (Wilson et al. in prep).

L. raniformis was detected at only one of the eleven survey sites, and can thus be reliably inferred as absent from the other ten (as opposed to undetected). These records represent local extinctions, and together with the environmental modelling represent a significant decline in the extent of occurrence of L. raniformis in southern Tasmania.

While our results clearly suggest a significant decline in the geographic extent of L. raniformis in Tasmania, it appears that this decline cannot be attributed to the standard threats of habitat clearance, alteration or fragmentation, nor the introduction of Bd into Tasmania. We know that L. raniformis can persist in heavily modified landscapes (authors’ pers. obs.), although survival and reproduction may be reduced. Similarly, although Bd is assumed to have entered Tasmania around the mid 1990’s (Animal Health Laboratories, Launceston) and has caused catastrophic declines in anurans elsewhere (Berger et al. 1998; Skerratt et al. 2007) it appears to not cause significant mortality in L. raniformis (Voyles et al. in prep). We suggest that, at least in part, climate change has led to the dramatic declines seen here. Since 1995 Tasmania has received 10 years of below average rainfall, including the driest year on record (Figure 2; BOM data from web). This led to the drying up of many ponds etc (pers. obs.) and may have led to the local extinction of many L. raniformis populations.

While the ‘endangered’ threat rating for L. raniformis (Hero et al. 2004) is supported by our data, we find some cause for optimism as the species is still common in core areas (northern coastal Tasmania and northern islands). Further work is required to fully understand the status and population trend of this species in Tasmania, especially its interaction with Bd, and its ability to persist and reproduce in modified landscapes.

Acknowledgements

We would like to thank who owners of properties who provided access to their land during surveys and all people who submitted records of L. raniformis to either the Natural Values Atlas or directly to us.

Chapter 8. Skeletochronology of Litoria raniformis phalanges to assess age

Charna Stowe Veterinary Student, Sydney University with assistance from Graeme Knowles and Bruce Jackson Veterinary Pathologists, Biosecurity and Product Integrity, Department of Primary Industries, Parks, Water and Environment. Mt Pleasant Laboratories, Prospect Tasmania 7250.

Introduction

Litoria raniformis commonly referred to as the Green and Gold frog is listed as a vulnerable species under Tasmania’s Threatened Species Protection Act 1995. This species occurs in localized parts of Tasmania in lowland areas mainly on the Northeast coast. It is also distributed in southern areas of Victoria (Burns and Crayn 2006). Green and Gold frogs live in or near streams, swamps, farm dams, or vegetated pools. The frogs spend much of their time on the ground near the water or among the vegetation, and are hardly ever found in open water (Bryant and Jackson 1999). They depend on permanent freshwater for breeding, preferring sites that are shallow and vegetative. Population evaluations have estimated that fifty percent of their range has declined in the last twenty years. This may be due to habitat destruction, including: loss of wetland, weed invasion, pollution from pesticides, overgrazing areas with cattle, collection for fish bait (Read 1999) or diseases, particularly, chytridiomycosis (Berger et al. 2005).

Techniques to identify age of L. raniformis frogs in relation to the threat of chytridiomycosis would be beneficial in monitoring their population dynamics and decline. Many authors have used skeletochronology to age amphibians. This method has become the most reliable tool to estimate the age and longevity of amphibians in temperate zones where they hibernate overwinter, resulting in cessation of their growth (Kumbar and Pancharatna 2001). This technique is based on layers of annular or cyclic bone growth recorded in cross- sections of long bones or phalanges (Halliday and Verrell 1988; Marangoni et al. 2009). Amphibians generate growth markings that correspond to border zones. These zones are linked to periods of faster growth or periods of rest in their hard tissues resulting in lines of arrested growth (LAG). LAGs represent the number of cycles of bone growth that the animal would have experienced over its lifespan (Kumbar and Pancharatna 2001) and can be used to age individual species (Morrison et al. 2004).

LAGs are formed when bone growth slows down during hibernation or aestivation (Morrison et al. 2004). Rings that are darkly stained are interpreted as (LAGs) or hematoxylinophilic lines. LAGs occur in periosteal bone which can become obscured in

older species by endosteal bone. The endosteal bone originates at the edge of marrow cavity (MC) and progresses to the bone perimeter where it replaces periosteal bone (Morrison et al. 2004). Resorbtion of endosteal bone can destroy LAGs resulting in misinterpretation of age by skeletochronology (Morrison et al. 2004). A single ring in the innermost side is a metamorphosis line (ML). ‘As a rule the metamorphosis line is associated with the presence of woven fibered embryonic bone’ (Guarino et al. 2003). This line is always present in juveniles just after metamorphosis and are distinguishable by their different shapes (Marangoni et al. 2009).

Skeletochronology is a reliable technique to determine individual mean longevity, age growth rates and sexual maturity in amphibians (Guarino et al. 2003). This can be performed on phalanges, albeit some studies have collected phalanges and femurs to cross confirm exact ages. This method is less desirable for sampling endangered or threatened species such as Litoria raniformis because it sacrifices the entire animal (Guarino et al. 2003).

Skeletochronology in relation to Snout Vent Length

Studies have attempted to determine whether an individual frog’s snout vent length (SVL) is a reliable estimate of age. Snout-vent length is measured from the tip of the snout to the anterior corner of the cloaca with a caliper to the nearest mm (Marangoni et al. 2009).

According to previous studies SVL and age were poorly correlated. Many early reports state that although skeletochronology is useful to age frogs, body size alone was a poor indicator for age estimates (Halliday and Verrell 1988; Caetano and Castanet 1993; Khonsue et al. 2000). Ento and Matsui (2002) also suggest that estimates of age by size data is not the best technique to use because body size in adults varies within the same age group and overlaps within the same age group. Morrison et al. (2004) also concluded that body size was not an accurate or reliable indicator for reproductive individuals in their study. The study did reveal significant correlation between body sizes in some of the species but the correlation coefficients were low and variation in body size at comparable ages were high. Similar results were reported in R.sakuraii (Kusano et al. 1995), R.sylvatica (Sagor et al. 1998), and T.vulgaris frogs (Halliday and Verrell 1988).

Interestingly, Morrison et al. (2004) demonstrated a significant correlation of body size and age in male species of L.chloris. and L. pearsoniana. This paper considered the length of time to reach sexual maturity as an important factor of population dynamics. This paper determined that Age of Maturity (AM) was linked to: growth factors or active season, difference between sexes of adults and juveniles and metabolic levels. Species with faster growth rates reached minimal reproductive size faster than species with slower growth rates, because reproductive maturity is dependent on body size (Morrison et al. 2004).

Ento and Matsui (2002) investigated the influence of rate of growth and sexual maturity in H.nebulosus which remained high until sexual maturity and then subsided. Growth rates of ectoderms slow down after sexual maturity. Species with a shorter onset of reproduction tend to grow larger and animals with shorter lifespan start to reproduce earlier to compensate for a shorter breeding period. Studies show that frogs which live longer are much older when they breed for the first time (Caetano and Castanet 1993). Ento and Matsui (2002) suggest that this is possibly because more energy is used for growth before they reach sexual maturity and then later their energy is used for reproduction.

In Esteban et al.(2004), mean SVL differed significantly between sexes for the whole sample, and within each age class females were larger than males. Sexual dimorphism seemed to increase with age. A marked correlation between age and body length was observed in males and females. The phalanges perimeters increased in both sexes as age increased. Growth curves for both sexes showed an abrupt decrease after reproductive activity commenced. Male growth decreased after the first year; where females delayed reproduction and continued to grow for two years longer than males. Sexual body length dimorphism, increased with age and may be so for females, to delay their first reproduction to maintain higher growth rates, in order to reach a critical size before egg production, where males are able to breed when they are mature (Esteban et al. 2004). In addition some froglets P.punctatus reached adult body size and sexual maturity before their first hibernation (Esteban et al. 2004).

Guarino and Erismis (2008) recent skeletochronology study involving both sexes in anurans revealed a strong correlation between body size and age and that skeletochronology is a reliable method to determine age and growth patterns in some species. In a few species a strong correlation only existed in males or only for females (Gibbons and McCarthy 1984; Guarino et al. 1995). Guarino & Erismis (2008) also showed that there is a large overlap of age classes, even when a correlation of body length and age are determined. Age and size were positively correlated although the correlation was not strong for females in R. holtzi.

This project aims to investigate whether L. raniformis frogs (Gold and Green frogs) can be aged by their snout vent length (SVL). This project will also investigate the technique of skeletochronology as a reliable tool for aging L. raniformis frogs in Tasmania.

Correlation of snout vent length is of particular interest for aging juvenile L. raniformis frogs, as this species has recently been declared threatened, possibly due to the introduction of chytridiomycosis caused by the fungal pathogen Batrachochytrium dendrobatidis.

Materials/ Methods

Materials provided by Jamie Voyles and Annie Philips (DPIPWE): L. raniformis hind foot phalanges, SVL data, references.

Eighteen L. raniformis frogs were sampled; hind limb toes were placed into seventy percent alcohol. The last two distal phalanges of the fourth toe of the hind limb (longest digit) was sampled and sectioned into three, approximately 1 -2 mm slices then placed into decal for an hour. Slides were prepared and stained with H&E stain or with Giemsa stain. Rings were identified under 100µm microscopic lens.

Results

Determination of Growth should be based on Von Bertalanffy growth curve (von Bertalanffy 1957):

L(t) = A[1-exp(k(t-t0))] SVLmax –(SVLmax-SVL0)e –k(t-t0), where SVLt = body size at age t

(mm); SVLmax= asymptotic maximum body size; SVL0=body size at metamorphosis; t = age estimate in years; t0=age at metamorphosis (in this study, t0 is assumed to be 0); k = growth coefficient that defines the shape of the curve.

Frog ID Snout Vent Length Lines of Arrested Growth (SVL) (LAGs)/Hematoxylinophilic lines F27 63.4 2 F28 62.7 1 F29 71.4 2 F32 65 4 or 5 F33 71 - F34 68.3 1 F35 63 3 F38 66.9 1 F39 53 - F40 68.1 1 F41 64.9 3 or 4 F42 70.6 2 F44 65.3 1 F45 61.3 3 or 4 F46 72.9 - F47 75.5 - F48 69.4 2 F49 64.9 2

Table 1. Randomly collected samples of L. Raniformis frogs, measurement of snout vent length (SVL) and determination of Lines of Arrested Growth (LAGs).

Figure 1. H&E stain of a cross section of L. Raniformis frog’s fourth hind limb toe to identify LAGs by skeletochronology.

Figure 2. Giemsa stain of a cross section of L. raniformis frog’s fourth hind limb toe to identify LAGs by skeletochronology.

Discussion

Skeletochronology has proven to be a useful tool to identifying the age of various species of frogs in temperate climates. Based on previous studies it has been suggested that snout vent length may not be a reliable means of accurate estimation of frog ages because, species variation, sexual dimorphisms, age of sexual maturity of various species, and the size that frogs metamorphose is highly variable, depending on population density and available food during larval stage (Alford 1999; Esteban et al. 2004).

Sex identification should have been determined for each frog during initial sample collection of toes to improve standardization and correlation of SVL in relation to sex. If this study is to be repeated this vital information should be included. It would be beneficial to provide a sample of a frog of known age to determine if skeletochronology is a valid method of aging L. raniformis frogs.

Chapter 9. The Tasmanian Tree Frog Litoria burrowsae; distribution, habitat use and seasonal activity patterns

Matthew Pauza, Michael Driessen and David Wilson

Biodiversity Conservation Branch, Department of Primary Industries, Parks, Water and Environment, PO Box 44 Hobart, Tasmania, 7001.

Introduction

The Tasmanian Tree Frog Litoria burrowsae is one of three anurans endemic to Tasmania, two of which are primarily restricted to the Tasmanian Wilderness World Heritage Area (TWWHA) (Driessen and Mallick 2003; Littlejohn 2003). Adults are variously patterned green and brown and can reach a maximum of 60mm (Barker et al. 1995). Although recorded from a wide geographic area (Littlejohn 2003), much of the area within this region is inaccessible and rarely visited; thus the true distribution of this species is poorly known. Similarly, this inaccessibility means that little is known of its biology and ecology.

Following the recent global declines in some anuran species there have been strong calls for increased monitoring and studies of frog communities (Alford and Richards 1999; Collins and Storfer 2003). Implicated in this decline, especially in Australia, is the chytrid fungus Batrachochytrium dendrobatidis (Berger et al. 1998). Chytrid is largely absent from the TWWHA (Pauza et al. in press), however it causes significant mortality to L. burrowsae in the laboratory (J. Voyles pers. comm.) and its effect on populations in the wild is unknown. Assessment of population status requires an understanding of calling patterns to effectively monitor at the most appropriate time of the year. A lack of basic knowledge into the distribution and activity patterns of L. burrowsae limits our ability to appropriately manage and conserve this species, or to assess the impact of chytrid in the wild.

Here we describe our recent work on L. burrowsae to increase the basic ecological knowledge for this little-known endemic species. This includes the first comprehensive field surveys for this species to determine known localities and suitable vegetation communities, and identification of its potential distribution using ecological niche modelling. Furthermore we report the results of repeated call surveys to determine seasonal patterns of breeding activity, including the use of call playback to increase detection of L. burrowsae, to underpin effective monitoring.

Materials and Methods

Species localities to predict distributions

Field surveys for L. burrowsae were conducted between 2006 and 2009 across the species’ known range. Survey locations were based on historic record locations and accessible areas of apparently suitable habitat. This species was considered present at a site if we observed an adult, heard a call (either unsolicited or in response to call playback) or identified tadpoles during our time at the site. Males of L. burrowsae have a unique call (Littlejohn 2003) while tadpoles can be identified from the sympatric Litoria ewingi by their broadly rounded snout, larger overall size, and lack of a distinct cluster of chromataphores between the nares or fine flagellum (Anstis 2002, M. Pauza pers. obs). At sites where L. burrowsae was present we recorded location co-ordinates and altitude using a GPS (GPSmap 60 Cx). Where elevations were not recorded as primary data these were derived from topographical maps. We also retrieved historic records stored on the Tasmanian Natural Values Atlas (NVA: https://www.naturalvaluesatlas.dpiw.tas.gov.au).

The vegetation of Tasmania has been categorised into a series of discrete communities which are also stored on the NVA (DPIPWE unpubl. data). Presence locations for L. burrowsae were overlain onto this map for Tasmania to determine suitable vegetation communities for this species, and their extent across the state. Eight records from ‘Agriculture, Urban and Exotic Vegetation’ were omitted from this process to avoid misrepresenting the potential distribution of L. burrowsae. No current records of L. burrowsae are from these vegetation categories, and it is likely that land uses have changed between these location records and the most recent vegetation classification. Habitat preferences per se were not examined as this requires comparison on used and unused sites, and unused sites are difficult to comprehensively determine for this species (Wilson et al. in prep).

Potential predicted distribution

The historic and current datasets were combined and duplicates (those records within 500m of another record) removed, leaving 80 records for further analysis. These locations were used to develop a model of the predicted distribution for L. burrowsae across Tasmania based on abiotic conditions. This model was developed in MaxEnt (Phillips et al. 2006: version 3.3.1) using 19 environmental parameters at 30 second resolution (approximate cell size of 1km2). These were downloaded from the WorldClim dataset (Hijmans et al. 2005: version 1.4) and cropped to include only Tasmania (S 39.27 - 43.90, E 143.60 – 148.70). Locations of L. burrowsae were overlaid on the environmental variables to produce a set of abiotic parameters at known sites, which were then extrapolated for all cells across Tasmania. Values for each cell ranged from 0.0 to 1.0 with larger values indicating a greater

predicted probability of occurrence for L. burrowsae, where values over 0.1 are considered to be environmentally suitable for a species to occur (Phillips et al. 2006).

Seasonal activity patterns and response to call playback

Seasonal activity patterns were assessed between January 2006 and March 2007 at two locations: 18 sites around Cardigan Flats (42° 12` S, 146° 4` E, 500m altitude, Area A on Figure 1) and 20 around Lune River (43° 26` S 146° 54` E, 50m altitude, Area B on Figure 1). Sites at Cardigan Flats are primarily natural ponds occurring in a mosaic of buttongrass moorland vegetation communities, while those at Lune River are primarily artificial roadside ponds for water storage and occur in a mosaic of scrub, heathland and coastal vegetation communities. All sites in either area were visited on the same night to minimize the effect of environmental variation on calling behaviour. Surveys lasted for five minutes at each site and occurred between 2000h and 0100h. At each site we recorded the number of calling individuals during the survey. Following the initial five minute period we played the advertisement call of L. burrowsae for 10 seconds followed by two minutes of listening, then repeated the sequence. Any extra L. burrowsae individuals heard calling were recorded. We pooled results from all sites during any one month for L. burrowsae due to low number of sites where this species was detected and low total number of individuals recorded.

Results

We recorded L. burrowsae from 40 sites across much of southern and western Tasmania, and retrieved an additional 81 location records from the Natural Values Atlas (Fig 1). Locations ranged in altitude from 5m to 1320m and were located in 25 natural vegetation communities, plus eight records from agriculture, urban or exotic environments (Table 1). Litoria burrowsae were most often found in buttongrass moorland vegetation communities (31 records), and were also commonly found in scrub, heathland and coastal complexes (12 records) and rainforest and related scrub (11 records). Historic and current locations showed broad concurrence (compared black and white locations on Fig. 1), however historic surveys had a greater geographic spread of locations.

Potential predicted distributions

Ecological niche modelling predicted two areas of environmentally suitable conditions for L. burrowsae; a large area in the west of the state which included all records, and a much smaller area in the northeast which contained no records (Fig. 1).

Seasonal activity patterns and response to call playback

In general L. burrowsae showed a strongly seasonal pattern of calling activity with no calling recorded between April and June (Fig. 2a & b). Calling activity increased from July to peaks in September and January then decreased until March. This pattern was evident in both the number of sites with calling males (Fig. 2a) and the total number of males calling (Fig. 2b). Calling activity was generally low across all months, with a maximum of seven sites (of 38

surveyed) having calling activity during any one month (September of Fig. 2a). The use of call playback increased the number of sites where L. burrowsae was detected by between one and three, and was most effective between July and December (Fig. 2a). The number of extra individual L. burrowsae calling following playback varied from zero to six, and was again most effective from July to December (Fig. 2b). Importantly, call playback only increased detection in months when L. burrowsae were already calling (except in April when call playback induced calling at a single site).

Figure 1. Known and predicted distribution for Litoria burrowsae in Tasmania, Australia. Circles are presence locations for the species from historic (black) and current (white) records. The grey area is the predicted potential distribution based on 80 records using ecological niche modelling. Sites used in determining the seasonal calling patterns were from Areas A and B.

Table 1. Records for Litoria burrowsae in Tasmanian vegetation communities, and the area of each of those communities.

Number Area of Vegetation community (‘000 hectares) records (31) Buttongrass moorland (269.4) 7 Sparse buttongrass moorland on slopes 80.2 6 Eastern buttongrass moorland 2.7 5 Buttongrass moorland 43.7 5 Western buttongrass moorland 64.9 4 Western lowland sedgeland 32.4 3 Buttongrass moorland with emergent shrubs 42.9 1 Restionaceae rushland 2.6 (12) Scrub, Heathland and Coastal Complexes (94.8) 5 Melaleuca squamea heathland 6.0 4 Leptospermum scrub 28.8 2 Western wet scrub 57.2 1 Lowland sedgy heathland 2.8 (11) Rainforest and Related Scrub (206.1) 6 Nothofagus rainforest 180.6 3 Highland low rainforest and scrub 2.4 1 Lagarostrobos franklinii rainforest and scrub 12.0 1 Nothofagus - Leptospermum short rainforest 11.1 8 Agricultural, Urban and Exotic Vegetation Not assessed (8) Wet Eucalypt Forest and Woodland (40.2) 4 Eucalyptus obliqua wet forest 11.4 2 Eucalyptus nitida wet forest 21.7 1 Eucalyptus delegatensis wet forest 1.2 1 Eucalyptus subcrenulata forest and woodland 5.9 (5) Highland Treeless Vegetation (1.4) 3 Western alpine sedgeland/herbland 1.2 2 Cushion moorland 0.2 (2) Dry Eucalypt Forest and Woodland (19.3) 1 Eucalyptus coccifera forest and woodland 8.6 1 Eucalyptus nitida dry forest and woodland 10.7 (2) Non-Eucalypt Forest and Woodland (10.7) 1 Leptospermum scoparium - Acacia mucronata forest 7.5 1 Leptospermum lanigerum - Melaleuca squarrosa swamp forest 3.2 0 Native Grassland 0 0 Other Natural Environments 0 0 Saltmarsh and Wetland 0

Figure 2. Seasonal activity patterns of Litoria burrowsae in Tasmania, Australia: a) number of sites where species was detected (of a maximum of 38 sites), and b) number of individuals detected over all sites. Black columns are the results from five minute aural surveys, open columns are additional records following call playback after the initial five minute listening period.

Discussion

This study is the first to document the natural history of L. burrowsae and as such provides important information which will underpin future monitoring and conservation efforts for this species. We find that L. burrowsae is widely distributed in western Tasmania with no evidence of range contraction, occurs in a range of habitats and over a broad altitudinal range. It also has a strongly seasonal pattern of calling, and call playback is an effective method for increasing the detection of this species.

Ecological niche modelling predicted a large portion of the state as being potentially suitable for L. burrowsae. The extent of suitable vegetation communities was highly similar to the predicted distribution of L. burrowsae using abiotic factors (data not shown), which is not surprising as abiotic conditions are the primary driver in structuring the composition of vegetation communities in Tasmania (Harris and Kitchener 2005). Modelling predicts two broad areas of environmentally suitable conditions for L. burrowsae; however it was only present in the larger, western area. The abiotic conditions in the intervening area are predicted to be unsuitable for L. burrowsae and may act as a barrier to dispersal from the western to north-eastern areas. Additionally, this north-eastern area is within the range of the larger L. raniformis (Littlejohn 2003), which may outcompete L. burrowsae in this area, should it be able to disperse from the western population. Little search effort has occurred in this area however, and intensive surveys during peak activity times may detect L. burrowsae in the north-east of the state.

In the western area, records of L. burrowsae are widely spread across most of the currently suitable habitat. Many apparent gaps in the records represent inaccessible areas which have not been surveyed, rather than absences of L. burrowsae. Our fieldwork did extend the known altitude of this species from 1070m (Littlejohn and Martin 1974) to 1320m. We also find general concurrence between historic locations and those from our study, suggesting that there has not been a significant decline in the distribution of L. burrowsae in recent times. In a cautionary note however, we revisited some known locations from 2006 in 2009 and failed to record L. burrowsae, despite significant search effort (D. Wilson unpubl. data). It may be that the recent discovery of chytrid around the edges of the TWWHA (Pauza et al. in press) is starting to impact on this species, and further monitoring is warranted, especially given the high susceptibility of this species to chytrid in the laboratory (J. Voyles pers. comm.).

Calling peaked in the austral spring and early summer, as has been anecdotally reported for this species and other Tasmanian anurans (Littlejohn 2003). Calling was infrequent however, and detection probabilities are likely to be low for single surveys of this species. Our results indicate that detection of L. burrowsae may be significantly increased by the use call playback immediately after each survey period as has been found for a sister taxa L. raniformis (Heard et al. 2006, G. Heard pers. comm.). Although this technique has not been

incorporated into larger scale anuran monitoring programs (Weir and Mossman 2005), it appears useful when undertaking targeted surveys for L. burrowsae.

While our work was not directly designed to assess the conservation of L. burrowsae, our data suggest that there is little current cause for concern. We found them at most historically occupied sites across a wide geographic range within their predicted distribution. There is a significant extent of suitable vegetation, much of which is within the highly protected TWWHA and is currently free of chytrid (Pauza et al. in press). Given the susceptibility of L. burrowsae to chytrid in the laboratory (Voyles pers. comm.) ongoing sampling for chytrid should occur within this species’ distribution, and monitoring sites established to examine population trends should chytrid be detected in an area.

Acknowledgements This study was funded by the Commonwealth and Tasmanian governments through the Tasmanian Wilderness World Heritage Area Fauna Program, Department of Primary industries, Parks, Water and Environment. We would like to thank B. Priest, S. Locke and H. Ricardo for their enthusiasm and assistance on the long cold nights in the field, Forestry Tasmania for access to state forest lands and the Tasmanian Parks and Wildlife Service for access to reserved lands and accommodation throughout the state. All work was undertaken under animal ethics permit (AEC 32/2006/07) and collection permits issued under the Nature Conservation Act 2002, National Parks and Reserved land Management Act 2002 and Crown lands Act 1976.

Chapter 10. A survey for disease introductions via frogs imported in fresh produce

Stewart Blackhall (DPIPWE) with the assistance of two final year veterinary students, Kathleen Tsimbas and Chana Stowe from the University of Sydney.

Introduction

In December 2009, we surveyed fresh produce importers and examined historic laboratory records at The Animal Health Laboratories (AHL), Launceston to determine:

Whether chytrid fungus has been transferred to Tasmania with infected mainland frogs The historic and current extent of inadvertent frog imports, and the disease status of imported frogs. Methods

Twenty-one shops plus the state offices of Coles and Woolworths, were visited in Hobart, Launceston, Burnie and Devonport. Owners/managers were given a questionnaire, a poster, a booklet on chytrid fungus and several containers and asked to notify the Department if they found any frogs in future shipments.

The following questions were asked of each of the survey participants:

1. Have you ever found a frog in a shipment of fruit or vegetables arriving from outside Tasmania?

2. If so, about how often has this happened and what times of year does it happen most?

3. Have you found any other sort of animal?

4. What did you do with the animal? Results

Of the 17 questionnaires returned, 12 (71%) reported seeing a frog at in the last 10 years. Five (29%) reported never having seen one and a further 3 are known to have received frogs although they did not return a questionnaire.

Other fauna translocated in produce was found by 55% of respondents and included cockroaches, snails, snakes, black flies and grubs. The two retailers that frequently found frogs either notified quarantine or killed the frogs. The other animals that were found in produce were either killed or thrown away alive with the boxes. Discussion

These results indicate that frog importation has certainly been widespread in the past, but it now appears to be much less common than it was 3 to 5 years ago. This was attributed to

better quality assurance and quarantine inspection. Ripe fruit is fumigated with methyl bromide but some animals reportedly survive this. Hard green bananas are allowed into Tasmania without fumigation, which is aimed primarily at fruit flies. The improved methods include faster processing so that picked bananas do not accumulate in the packing sheds and more careful inspection and processing of the fruit. When bananas arrive from the grower, they are washed with a high pressure hose and then separated into “hands”. These are floated in a water trough about 10m long that may also contain chlorine. The fruit is then lifted out of the bath and inspected before putting it on a conveyor belt which takes it to the packing area. Fruit is again visually inspected as it is placed in boxes and then stored in a secure room. In previous years, boxed fruit may have been left on the floor of sheds or even outside overnight and it is thought that was when many frogs entered the boxes.

Legislation covering the importation of animals and food products into Tasmania includes the Nature Conservation Act 2002 that through the Wildlife Regulations 1999 specifies what animals are not allowed into the state and governs the possession or disposal of any wildlife. The Plant Quarantine Act 1997 governs the movement of plant material but only those animals that are considered to be a threat to plants and is largely aimed at preventing the importation of fruit flies. It also deals with hygiene and packaging standards. The Animal Health Act 1995 deals with the movement of animals and the control of diseases and includes the power to seize and destroy animals.

Fisher and Garner (2007) have shown a demonstrated link between the transportation of amphibians and the spread of chytridiomycosis and make recommendations about the importation and transport of amphibians. In 2005, the Australian Government declared chytridiomycosis a key threatening process under the Environment Protection and Biodiversity Conservation Act 1999. It has prepared a Threat Abatement Plan (Department of the Environment and Heritage 1996) and one of the mail objectives of the plan is to limit the spread of the disease.

Actions that would help to ensure that accidental imports continue to decline and that preventative actions are further refined could include:

Raising the issue with the Department’s Biosecurity Technical Group (BTG). The BTG considers biosecurity issues at its meetings twice a year and makes recommendations to senior management on issues of concern. This would be a good way to raise the profile of this issue and bring it to the attention of managers.

Alerting Departmental staff throughout the agency of the need to report importations and the people to contact. A notice has to be issued as a Biosecurity Alert, but not all Departmental offices receive or pass on the information contained in these notices. Quarantine facilities also received the alert but they also may need a follow-up asking them to forward any frogs turned into them. This advice will need to be periodically reinforced.

Providing positive feedback to packers and shippers of fruit telling them that their work has been successful and why that is important.

Another action might be to involve wildlife authorities interstate (if they are not already) who could visit packing sheds and advise on further improvements based on their knowledge of frog behaviour.

References

Adams, M., N. Chelgren, et al. (2010). "Using occupancy models to understand the distribution of an amphibian pathogen, Batrachochytrium dendrobatidis." Ecological Applications 20(1): 289–302.

Alford, R. (1999). Ecology: resource use, competition and predation. Tadpoles: the biology of anuran larvae. R. McDiarmid and R. Alling. Chicago, Chicago University Press: 240-278.

Alford, R. and S. Richards (1999). "Global amphibian declines: a problem in applied ecology." Annual Review of Ecology and Systematics 30: 133-165.

Annis, S., F. Dastoor, et al. (2004). "A DNA based assay identifies Batrachochytrium dendrobatidis in amphibians." Journal of Wildlife Diseases 40(3): 420-428.

Anstis, M. (2002). Tadpoles of South Eastern Australia: a Guide with Keys. French Forest, Australia, New Holland.

Bailey, L., T. Simons, et al. (2004). "Estimating site occupancy and species detection probability parameters for terrestrial salamanders." Ecological Applications 14(3): 692-702.

Barker, J., G. Griggs, et al. (1995). A Field Guide to Australian Frogs. Sydney, Australia, Surrey Beatty and Sons.

Berger, L., A. Hyatt, et al. (2002). "Production of polyclonal antibodies to Batrachochytrium dendrobatidis and their use in an immunoperoxidase test for chytridiomycosis in amphibians." Diseases of Aquatic Organisms 48: 213-220.

Berger, L., A. Hyatt, et al. (2005). "Life cycle stages of amphibian chytrid Batrachochytrium dendrobatidis." Diseases of Aquatic Organisms 68: 51-63.

Berger, L., G. Marantelli, et al. (2005). "Virulence of the amphibian chytrid fungus Batrachochytrium dendrobatidis varies with the strain." Diseases of Aquatic Organisms 68: 47-50.

Berger, L., R. Speare, et al. (1998). "Chytridiomycosis causes amphibian mortality associated with population declines in the rain forests of Australia and Central America." Proceedings of the National Academy of Sciences 95: 9031-9036.

Berger, L., R. Speare, et al. (1999). "Diagnosis of chytridiomycosis in amphibians by histological examination." Zoos Print Journal 15: 184-190.

Berger, L., R. Speare, et al. (in press). "Treatment of chytridiomycosis requires urgent clinical trials." Diseases of Aquatic Organisms.

Bielby, J., N. Cooper, et al. (2008). "Predicting susceptibility to future declines in the world's frogs." Conservation Letters 1: 82-90.

Blehert, D., A. Hicks, et al. (2009). "Bat white-nose syndrome: an emerging fungal pathogen?" Science 323: 227.

Bosch, J., I. Martinez-Solano, et al. (2001). "Evidence of a chytrid fungus infection involved in the decline of the common midwife toad (Alytes obstetricans) in protected areas of central Spain." Biological Conservation 97(3): 331-337.

Boyle, D., D. Boyle, et al. (2004). "Rapid quantitative detection of chytridiomycosis (Batrachochytrium dendrobatidis) in amphibian samples using real time Taqman PCR assay." Diseases of Aquatic Organisms 60: 141-148.

Brem, F. and K. Lips (2008). "Batrachochytrium dendrobatidis infection patterns among Panamanian amphibian species, habitats and elevations during epizootic and enzootic stages." Diseases of Aquatic Organisms 81: 189-202.

Bryant, S. and J. Jackson (1999). Tasmania's threatened fauna handbook: what, where and how to protect Tasmania's threatened animals. Hobart, Threatened Species Unit, Parks and Wildlife Service.

Buckley, J. and T. Beebee (2004). "Monitoring the conservation status of an endangered amphibian: the natterjack toad Bufo calamita in Britain." Animal Conservation 7: 221-228.

Bureau of Meteorology (2010). Climate Statistics for Australian Sites. 2010: http://www.bom.gov.au/climate/averages/maps.shtml.

Burnham, K. and D. Anderson (2002). Model selection and multi-model inference: a practical information-theoretic approach. New York, Springer.

Burns, E. and D. Crayn (2006). "Phylogenetics and evolution of bell frogs (Litoria aurea species-group, Anura: Hylidae) based on mitochondrial ND4 sequences." Molecular Phylogenetics and Evolution 39: 573-579.

Caetano, M. and J. Castanet (1993). "Variablity and microevolutionary patterns in Triturus marmoratus from Portugal: age, size longevity and growth." Amphibia-Reptilia 14: 117-129.

Cashins, S., R. Alford, et al. (2008). "Lethal effect of latex, nitrile, and vinyl gloves on tadpoles." Herpetological Review 39(3): 298–301.

Collins, J. and A. Storfer (2003). "Global amphibian declines: sorting the hypotheses." Diversity and Distributions 9: 89-98.

Daszak, P., A. Cunningham, et al. (2003). "Infectious disease and amphibian population declines." Diversity and Distributions 9: 141–150.

Daszak, P., A. Strieby, et al. (2004). "Experimental evidence that the bull-frog (Rana catesbeiana) as a potential carrier of chytridiomycosis, an emerging fungal pathogen of amphibians." Herpetological Journal 14: 201-207.

De Solla, S., L. Shirose, et al. (2005). "Effect of sampling effort and species detectability on volunteer based anuran monitoring programs." Biological Conservation 121: 585-594.

Department of the Environment and Heritage (1996). Threat Abatement Plan: Infection of amphibians with chytrid fungus resulting in chytridiomycosis. Canberra, Australia, Commonwealth of Australia.

Driessen, M. and S. Mallick (2003). "The vertebrate fauna of the Tasmanian Wilderness World Heritage Area." Pacific Conservation Biology 9(3): 187-206.

Ento, K. and M. Matsui (2002). "Estimation of age structure by skelotochronology of a population of Hynobius nebulosus in a breeding season." Zoological Science 19(2): 241-247.

Esteban, M., M. Sanchez-Herraiz, et al. (2004). "Age structure and growth in an isolated population of Pelodytes punctatus in northern Spain." Journal of Natural History 38(21): 2789-2801.

Fisher, M., J. Bosch, et al. (2009). "Proteomic and phenotypic profiling of the amphibian pathogen Batrachochytrium dendrobatidis shows that genotype is linked to virulence." Molecular Ecology 18: 415- 429.

Fisher, M. and T. Garner (2007). "The relationship between the emergence of Batrachochytrium dendrobatidis, the international trade in amphibians and introduced amphibian species." Fungal Biology Reviews 21: 2-9.

Garner, T., S. Walker, et al. (2005). "Chytrid fungus in Europe." Emerging Infectious Diseases 11: 1639- 1641.

Gascon, C., J. Collins, et al. (2005). Amphibian Conservation Action Plan. Gland, Switzerland, IUCN, the World Conservation Union.

Gibbons, M. and T. McCarthy (1984). "Growth, maturation and survival of frogs Rana temporaria L." Holarctic Ecology 7: 419-427.

Gooch, M., A. Heupel, et al. (2006). "The effects of survey protocol on detection probabilities and site occupancy estimates of summer breeding anurans." Applied Herpetology 3: 129-142.

Green, D., K. Converse, et al. (2006). "Epizootiology of sixty-four amphibian morbidity and mortality events in the USA, 1996-2001." Annals of the New York Academy of Sciences 969: 223-239.

Gu, W. and R. Swihart (2004). "Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models." Biological Conservation 116: 195-203.

Guarino, F., F. Angelini, et al. (1995). "A skeletochronological analysis of three syntopic amphibian species from southern Italy." Amphibia-Reptilia 16: 297-302.

Guarino, F. and U. Erismis (2008). "Age determination and growth by skelotochronology of Rana holtzi, an endemic frog from Turkey." Italian Journal of Zoology 75(3): 237-242.

Guarino, F., S. Lunardi, et al. (2003). "A skelotochronological study of growth, longevity and age at sexual maturity in a population of Rana latastei (Amphibia, Anura)." Journal of Biosciences 28(6): 775- 782.

Halliday, T. and P. Verrell (1988). "Body size and age in amphibian and reptiles." Journal of Herpetology 22: 253-265.

Hanley, J. and A. Lippman-Hand (1983). "If nothing goes wrong, is everything all right?" The Journal of the American Medical Association 249: 1743-1745.

Harris, R., A. Lauer, et al. (2009). "Addition of antifungal skin bacteria to salamanders ameliorates the effects of chytridiomycosis." Diseases of Aquatic Organisms 83: 11-16.

Harris, S. and A. Kitchener, Eds. (2005). From Forest to Fjaeldmark: Descriptions of Tasmania's Vegetation. Hobart, Department of Primary Industries, Water and Environment, Printing Authority of Tasmania.

Heard, G., P. Robertson, et al. (2006). "Assessing detection probabilities for the endangered growling grass frog (Litoria raniformis) in southern Victoria." Wildlife Research 33: 557-564.

Hero, J.-M., G. Gillespie, et al. (2004). Litoria raniformis, IUCN Red List of Threatened Species.

Hijmans, R., S. Cameron, et al. (2005). "Very high resolution interpolated climate surfaces for global land areas." International Journal of Climatology 25: 1965-1978.

Hines, J. (2006). PRESENCE2- Software to estimate patch occupancy and related parameters, USGS- PWRC.

Humason, G. (1967). Animal tissue techniques. San Francisco, WH Freeman.

Hyatt, A., D. Boyle, et al. (2007). "Diagnostic assays and sampling protocols for the detection of Batrachochytrium dendrobatidis." Diseases of Aquatic Organisms 73: 175-192.

Hyatt, A., K. Halpin, et al. (2008). Batrachochytrium dendrobatidis real time TaqMan PCR. Geelong, Australia, CSIRO.

Jackson, J., F. Weckerly, et al. (2006). "Inferring absence of Houston toads given imperfect detection probabilities." Journal of Wildlife Management 70(5): 1461-1463.

Jarman, S., G. Kantvilas, et al. (1988). Buttongrass moorland in Tasmania. Research Report No. 2, Tasmanian Forest Research Council Inc.

Jones, M., P. Jarman, et al. (2007). "Conservation management of Tasmanian devils in the context of an emerging, extinction-threatening disease: devil facial tumor disease." Ecohealth 4: 326-337.

Kéry, M. (2002). "Inferring the absence of a species - a case study of snakes." Journal of Wildlife Management 66(2): 330-338.

Khonsue, W., M. Matsui, et al. (2000). "Age determination by skeletochronology of Rana nigrovittata, a frog from the tropical forest of Thailand." Zoological Science 17: 253-257.

Kriger, K. and J.-M. Hero (2007). "Large-scale seasonal variation in the prevalence and severity of chytridiomycosis." Journal of Zoology, London 271(3): 352-359.

Kriger, K. and J.-M. Hero (2009). "Chytridiomycosis, amphibian extinctions, and lessons for the prevention of future panzootics." Ecohealth 6(1): 6-10.

Kriger, K., F. Pereoglou, et al. (2007). "Latitudinal Variation in the Prevalence and Intensity of Chytrid (Batrachochytrium dendrobatidis) Infection in Eastern Australia." Conservation Biology 21(5): 1280–1290.

Kumbar, S. and K. Pancharatna (2001). "Determination of age, longevity and age at reproduction of the frog Microhyla ornata by skeletochronology." Journal of Biosciences 26(2): 265-270.

Kusano, T., K. Fukuyama, et al. (1995). "Age determination of the stream frog Rana sakuraii, by skeletochronology." Journal of Herpetology 29: 625-628.

Lips, K., F. Brem, et al. (2006). "Emerging infectious disease and the loss of biodiversity in a Neotropical amphibian community." Proceedings of the National Academy of Sciences 103(9): 3165-3170.

Lips, K., J. Diffendorfer, et al. (2008). "Riding the Wave: Reconciling the Roles of Disease and Climate Change in Amphibian Declines." PLoS Biology 6(3): 72.

Lips, K., J. Reeve, et al. (2003). "Ecological traits predicting amphibian population declines in central America." Conservation Biology 17(4): 1078-1088.

Littlejohn, M. (2003). Frogs of Tasmania. Hobart, Australia, University of Tasmania.

Littlejohn, M. and A. Martin (1974). The amphibia of Tasmania. Biogeography and Ecology in Tasmania. W. Williams. The Hague, Dr W Junk: 251-289.

Longcore, J., A. Pessier, et al. (1999). "Batrachochytrium dendrobatidis gen et sp nov, a chytrid pathogenic to amphibians." Mycologia 91(2): 219-227.

MacKenzie, D., J. Nichols, et al. (2002). "Estimating site occupancy rates when detection probabilities are less than one." Ecology 83(8): 2248-2255.

MacKenzie, D., J. Nichols, et al. (2006). Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. San Diego, Elsevier.

Marangoni, F., E. Schaefer, et al. (2009). "Growth formation and chronology of two neotropical anuran species." Journal of Herpetology 43(3): 546-550.

McDonald, K., D. Mendez, et al. (2005). "Decline in the prevalence of chytridiomycosis in frog populations in North Queensland, Australia." Pacific Conservation Biology 11: 114-120.

Mendelson III, J., R. Gagliardo, et al. (2005). Captive Programs. Amphibian Conservation Action Plan. C. Gascon, J. Collins, R. Mooreet al. Gland, Switzerland, IUCN, the World Conservation Union: 36-37.

Moilanen, A. (2002). "Implications of empirical data quality for metapopulation model parameter estimation and application." Oikos 96: 516-530.

Morrison, C., J.-M. Hero, et al. (2004). "Altitudinal variation in the age at maturity, longevity, and reproductive lifespan of anurans in subtropical Queensland." Herpetologica 60(1): 34-44.

Murray, K., R. Retallick, et al. (2010). "The distribution and host range of the pandemic disease chytridiomycosis in Australia, spanning surveys from 1956–2007." Ecology 91(5): 1557.

Murray, K., R. Retallick, et al. (in review). "Assessing spatial patterns of disease risk to biodiversity: implications for the management of the amphibian pathogen, Batrachochytrium dendrobatidis."

Murray, K. and L. Skerratt (in review). "Predicting wild hosts for amphibian chytridiomycosis: integrating host life-history traits with pathogen environmental requirements." Human and Ecological Risk Assessment.

Murray, K., L. Skerratt, et al. (2009). "Impact and Dynamics of Disease in Species Threatened by the Amphibian Chytrid Fungus, Batrachochytrium dendrobatidis." Conservation Biology 23(5): 1242-1252.

Murray, K., L. Skerratt, et al. (in press). "Evidence of effects of endemic chytridiomycosis on host survival, behavior, and emigration: reply to Schmidt." Conservation Biology.

Obendorf, D. (2005). Developing field and diagnostic methods to survey for chytridiomycosis in Tasmanian frogs. Canberra, Department of Environment and Heritage.

Obendorf, D. and A. Dalton (2006). "A survey for the presence of the amphibian chytrid fungus (Batrachochytrium dendrobatidis) in Tasmania." Papers and Proceedings of the Royal Society of Tasmania 140: 25-29.

OIE (2008). Aquatic animal health code 2008, World Organisation of Animal Health.

Oseen, K. and R. Wassersug (2002). "Environmental factors influencing calling in sympatric anurans." Oecologia 133: 616-625.

Pauza, M., M. Driessen, et al. (in press). "Distribution and risk factors for the spread of amphibian chytrid fungus Batrachochytrium dendrobatidis in the Tasmanian Wilderness World Heritage Area, Australia." Diseases of Aquatic Organisms.

Pauza, M., M. Driessen, et al. (in review). "The Tasmanian Tree Frog Litoria burrowsae; distribution, habitat use and seasonal activity patterns." Journal of Herpetology.

Pellet, J. and B. Schmidt (2005). "Monitoring distributions using call surveys: estimating site occupancy, detection probabilities and inferring absence." Biological Conservation 123: 27-35.

Penman, T., D. Pike, et al. (in press). "Predicting the impact of climate change on Australia's most endangered snake, Hoplocephalus bungaroides." Diversity and Distributions.

Pessier, A., D. Nichols, et al. (1999). "Cutaneous chytridiomycosis in poison dart frogs (Dendrobates spp.) and White's tree frogs (Litoria caerulea)." Journal of Veterinary Diagnostic Investigations 11: 194- 199.

Peterson, J., M. Wood, et al. (2007). "Prevalence of Batrachochytrium dendrobatidis in American bullfrog and Southern leoparde frog larvae from wetlands on the Savannah River site, South Carolina." Journal of Wildlife Diseases 43(3): 450–460.

Phillips, S., R. Anderson, et al. (2006). "Maximum entropy modeling of species geographic distributions." Ecological Modelling 190: 231-259.

Phillott, A., R. Speare et al. (2010). "Minimising exposure of amphibians to pathogens during field studies." Diseases of Aquatic Organisms. Published online.

Pierce, B. and K. Gutzwiller (2004). "Auditory sampling of frogs: detection efficiency in relation to survey duration." Journal of Herpetology 38(4): 495-500.

Piotrowski, J., S. Annis, et al. (2004). "Physiology of Batrachochytrium dendrobatidis, a chytrid pathogen of amphibians." Mycologia 96(1): 9-15.

Puschendorf, R. (2010). Environmental effects on a host-pathogen system: Frogs and Bd in wet and dry habitats, James Cook University.

Puschendorf, R. and F. Bolaños (2006). "Detection of Batrachochyrium dendrobatidis in Eleutherodactylus fitzingeri: effects of skin sample location and histologic stain." Journal of Wildlife Diseases 42: 301-306.

Puschendorf, R., F. Bolanos, et al. (2006). "The amphibian chytrid fungus along an altitudinal transect before the first reported declines in Costa Rica." Biological Conservation 132: 136–142.

Puschendorf, R., A. Carnaval, et al. (2008). "Distribution models for the amphibian chytrid Batrachochytrium dendrobatidis in Costa Rica: proposing climatic refuges as a conservation tool." Diversity and Distributions 15(3): 401-408.

Rachowicz, L., J.-M. Hero, et al. (2005). "The novel and endemic pathogen hypotheses: Competing explanations for the origin of emerging infectious diseases of wildlife." Conservation Biology 19: 1441– 1448.

Read, M. (1999). Aquatic ecology of rivers in the pipers catchment - a report forming part of the requirements for State of Rivers reporting. Hobart, Department of Primary Industries, Water and Environment.

Ricardo, H. (2006). Distribution and Ecology of Chytrid in Tasmania (Hons thesis), University of Tasmania.

Rödder, D., J. Kielgast, et al. (2009). "Global amphibian extinction risk assessment for the panzootic chytrid fungus."

Rollins-Smith, L., D. Woodhams, et al. (2005). "Antimicrobial peptide defences of the mountain yellow- legged frog (Rana muscosa)." Developmental & Comparative Immunology 30(9): 831-842.

Ron, S. (2005). "Predicting the distribution of the amphibian pathogen Batrachochytrium dendrobatidis in the New World." Biotropica 37: 209-221.

Rounsevell, D., D. Ziegeler, et al. (1994). "A new genus and species of frog (Anura: Leptodactylidae: Myobatrachinae) from southern Tasmania." Transactions of the Royal Society of South Australia 118: 171-185.

Royle, J. and J. Nichols (2003). "Estimating abundance from repeated presence absence data or point counts." Ecology 84: 777-790.

Saenz, D., L. Fitzgerald, et al. (2006). "Abiotic correlates of anuran calling phenology: the importance of rain, temperature, and season." Herpetological Monographs 20: 64-82.

Sagor, E., M. Ouellet, et al. (1998). "Skeletochronology and geographic variation in age structure in the wood frog, Rana sylvatica." Journal of Herpetology 32: 469-474.

Schmidt, B. (2005). "Monitoring the distribution of pond-breeding amphibians when species are detected imperfectly." Aquatic Conservation: Marine and Freshwater Ecosystems 15: 681-692.

Shirose, L., C. Bishop, et al. (1997). "Validation techniques of an amphibian call count survey technique in Ontario, Canada." Herpetologica 53: 312-320.

Skelly, D., K. Yurewicz, et al. (2003). "Estimating decline and distributional change in amphibians." Conservation Biology 17(3): 744-751.

Skerratt, L., L. Berger, et al. (2008). "Survey protocol for detecting chytridiomycosis in all Australian frog populations." Diseases of Aquatic Organisms 80: 85–94.

Skerratt, L., L. Berger, et al. (2007). "Spread of chytridiomycosis has caused the rapid global decline and extinction of frogs." Ecohealth 4: 125-134.

Speare, R., L. Skerratt, et al. (2005). A project that designs and trials a pilot survey to map the distribution of chyridomycosis (caused by the amphibian chytrid fungus) in Australian frogs. Final report for the Australian Government Department of the Environment and Heritage, Department of the Environment and Heritage.

Stice, M. and C. Briggs (2010). "Immunization is ineffective at preventing infection and mortality due to the amphibian chytrid fungus Batrachochytrium dendrobatidis." Journal of Wildlife Diseases 46(1): 70- 77.

Stuart, S., J. Chanson, et al. (2004). "Status and trends of amphibian declines and extinctions worldwide." Science 306: 1783-1786.

Threatened Species Unit (2001). Listing Statement: Green and Golden Frog Litoria raniformis. Hobart, Tasmania, Department of Primary Industries, Water and Environment.

Von Bertalanffy, L. (1957). "Quantitative laws in metabolism and growth." Quarterly Review of Biology 32: 217-231.

Voyles, J., A. Philips, et al. (in prep). "Assessing pathogen virulence and host susceptibility: implications for chytridiomycosis management in Tasmanian frogs."

Voyles, J., S. Young, et al. (2009). "Pathogenesis of chytridiomycosis, a cause for catastrophic amphibian declines." Science 326(5952): 582-585.

Webb, R., D. Mendez, et al. (2007). "Additional disinfectants effective against the amphibian chytrid fungus Batrachochytrium dendrobatidis." Diseases of Aquatic Organisms 74: 13–16.

Weir, L. and M. Mossman (2005). North American Amphibian Monitoring Program. Amphibian Declines: Conservation Status of United States Species. M. Lannoo. Berkeley, University of California Press: 307- 313.

Weir, L., J. Royle, et al. (2005). "Modeling anuran detection and site occupancy on North American Amphibian Monitoring Program (NAAMP) routes in Maryland." Journal of Herpetology 39(4): 627-639.

Weldon, C., L. Preez, et al. (2004). "Origin of the amphibian chytrid fungus." Emerging Infectious Diseases 10: 2100-2105.

Wilson, D., M. Webb, et al. (in prep). "Detection probabilities and optimal survey methods for Tasmanian anurans under varying environmental conditions."

Woodhams, D. and R. Alford (2005). "Ecology of Chytridiomycosis in Rainforest Stream Frog Assemblages of Tropical Queensland." Conservation Biology 19(5).

Woodhams, D., J. Ardipradja, et al. (2007). "Resistance to chytridiomycosis varies among amphibian species and is correlated with skin peptide defences." Animal Conservation 10: 409-417.

Woodhams, D., V. Kilburn, et al. (2008). "Chytridiomycosis and amphibian population declines continue to spread eastward in Panama." Ecohealth 5: 268-274.

Woodhams, D., J. Voyles, et al. (2006). "Predicted disease susceptibility in a Panamanian amphibian assemblage based on skin pepetide defenses." Journal of Wildlife Diseases 42: 207-218.

Zippel, K. and J. Mendelson III (2008). "The amphibian extinction crisis: a call to action." Herpetological Review 39: 23-29.