S. E. Williams, J. VanDerWal, J. Isaac, L. P. Shoo, C. Storlie, S. Fox, E. E. Bolitho, C. Moritz, C. J. Hoskin, and Y. M. Williams. 2010. Distributions, life-history specialization, and phylogeny of the rain forest vertebrates in the Austalian Wet Tropics. Ecology 91:2493.

INTRODUCTION

The Wet Tropics bioregion in northeastern Queensland is a biodiversity hotspot of global significance, with a unique regional biota.  In 1988 the Wet Tropics Bioregion was listed as a World Heritage Area, primarily because of it’s biodiversity values. The region is dominated by mountain ranges varying from sea level to 1600 meters and elevation (temperature) is the strongest environmental gradient affecting species composition and patterns of biodiversity in the region (Nix 1991, Williams et al. 1996; Williams and Pearson 1997; Williams 2006).

 Tropical mountain systems like the Australian Wet Tropics are expected to be extremely vulnerable to climatic change due to their fragmentary nature, relatively small area, high levels of local endemism and ecological specialization and the compression of climatic zones over the elevation gradient (Williams et al. 2003).  Upland rain forests types in the region are predicted to become greatly reduced in area and more fragmented (Hilbert et al. 2001). Minimizing the impacts of climate change on biodiversity will require informed prioritization of adaptation options based on an understanding of biodiversity patterns and processes and the relative vulnerability of species, ecosystems, and processes. Understanding biodiversity requires detailed information on the factors that determine the distribution of each constituent species. One of the most fundamental pieces of information in ecology and conservation biology is knowledge of which species occur in what places. Although conceptually simple, understanding species’ distributions is a complex undertaking that may be the single most important fact underpinning all ecological research and applications in conservation biology. It is impossible to make informed decisions about conservation management without some knowledge on distributions. The comprehensive data available describing the biodiversity of the Wet Tropics bioregion makes the system an ideal case study for many macroecological, evolutionary, and climate change questions.

 The biogeographic and evolutionary history of the region predisposes the biota to being vulnerable to climate change because most of the regionally endemic species are adapted to a cool, wet, and relatively aseasonal environment. The spatial pattern of long-term habitat stability in the cool, wet uplands of the region has been a major factor determining the current spatial patterns of distributions and species richness (Williams and Pearson 1997; (Winter 1997); (Schneider and Williams 2005); (Graham et al. 2006), (VanDerWal et al. 2009)).  A significant body of ecological and molecular-phylogeographic research provides evidence that previous climatic changes during the Quaternary ice-ages resulted in significant levels of localized species extinction followed by periods of re-colonization as the rain forest expanded again, with little evidence for rapid evolutionary adaptation (Williams and Pearson 1997; (Moritz et al. 2000); Schneider and Williams 2005; Graham et al. 2006; (Williams et al. 2008); (Moritz et al. 2009)). Within-year climatic stability is also an important factor, areas with lower seasonality (more stable rainfall pattern) support higher biodiversity and abundances (Williams and Middleton 2008).

The aim of the data compiled here is to provide our best estimate of the distribution and ecological characteristics of as many species of rain forest vertebrates as possible within the Wet Tropics bioregion. To address this aim we needed to integrate existing data sets on the physical environment and biodiversity with ongoing regional-scale monitoring (vertebrates, invertebrates, plants, ecosystem processes) and spatial modeling of distributions. The distribution maps represent a combination of bioclimatic modeling, habitat preferences, biogeographic distributions, and expert knowledge. There is also a comprehensive species list of all vertebrates in the region, including those for which insufficient data was available to model their distribution.  Also provided is information concerning species range size (mapped species only), indices of habitat specialization, and summaries of species richness by taxa both in spatially continuous maps and tabulated. Most macroecological analyses are greatly improved by more detailed information on the functional and ecological characteristics of each species. To this end, we have included a compilation of traits describing each species including taxonomy, morphology, various indices of ecological specialization and macrecological variables such as potential and realized range size estimates for both total range and core habitat. Most analyses are improved by consideration of phylogeny, therefore we have included broad phylogenies for all taxa to facilitate analyses that can account for phylogenetic constraints.

These data provide access to an extensive baseline data set for future analyses that includes comprehensive distribution and ecological data across a whole regional ecosystem for vertebrates that will inform a diverse suite of meta-analyses on macroecology, biogeography, evolution, global change biology, niche theory, and conservation biology, and serve as a comprehensive baseline data set to compare with future monitoring and adaptive management in a changing global climate.

METADATA

CLASS I. DATA SET DESCRIPTORS

A. Data set identity: Distributions and ecology of rain forest vertebrates in the Australian Wet Tropics

B. Data set identification code

C. Data set description

Principal Investigator: Stephen E. Williams, Centre for Tropical Biodiversity and Climate Change, School of Marine and Tropical Biology, James Cook University, Townsville, Queensland 4811 Australia

Abstract: The purpose of this data set was to compile distributional, general life-history characteristics and phylogenies for Australian tropical rain forest vertebrates to inform a wide range of comparative studies on the determinants of biodiversity patterns and to assess the impacts of global climate change. We provide three distinct data sets: (1) a table of species-specific distributional and life-history traits for 242 vertebrate species found in the rain forests of the Australian Wet Tropics; (2) species distribution maps (GIS raster files) for 202 of the species displaying both the realized and potential distributions; and (3) phylogenies for these species. These species represent 93 birds, 31 amphibians, 31 mammals (including one monotreme), and 47 reptiles. Where information exists, the distributional and life-history data compiled here present information on: indices of environmental specialization (ENFA), habitat specialization, average body mass and size, sexual dimorphism, reproductive characteristics such as age at first reproduction, clutch/litter size, number of reproductive bouts per year and breeding seasonality, longevity, time of day when most active, and dispersal ability; distributional characteristics such as range size (potential and realized for both total and core ranges) and observed ranges in temperature, precipitation, and elevation; and niche attributes such as environmental marginality and specialization. The distribution maps provided represent a combination of presence-only ecological niche modeling (using MaxEnt) to estimate the potential distribution of a species followed by biogeographic clipping by expert opinion based on extensive field data and a subregional classification relevant to the topography and biogeographic history of the region to produce best-possible estimates of the realized distribution. Our assemblage contains many species with a shared evolutionary history, and thus many analyses of these data will need to account for phylogeny. Although a comprehensive phylogeny with branch length information does not exist for this diverse group of species, we present a best-estimate composite phylogeny constructed primarily from recently published molecular phylogenies of included groups..

D. Key words: distribution; life history; rain forest vertebrates; Australia Wet Tropics.

CLASS II. RESEARCH ORIGIN DESCRIPTORS

A. Overall project description

Identity: Distributional and life-history traits of Australia Wet Tropics rain forest vertebrates

Originator: Dr. Stephen Williams

Period of Study: 1990–present

Objectives: To describe patterns of distribution, abundance, species richness, assemblage structure, and natural history of rain forest vertebrates of the Australia Wet Tropics and to understand general patterns in macroecology and evolution using a diverse assemblage of rainforest fauna with a unique evolutionary history. To then use this data to evaluate the relative vulnerability of biodiversity to global climate change. The Centre for Tropical Biodiversity and Climate Change Research (CTBCC) is a multidisciplinary research centre aimed at understanding the patterns and processes underlying tropical biodiversity and the impacts that global climate change will have on the natural environment. The CTBCC is currently examining a diverse range of research topics on climate change and biodiversity (vertebrates, invertebrates, plants, and ecosystem processes) including population genetics, thermal physiology, paleo-modeling of habitats and species distributions, extinction proneness, phenology, soil/leaf litter nutrient cycling, climatic seasonality, assemblage structure, trophic interactions, net primary productivity, vegetation structure, ecological resilience, ecological and evolutionary adaptation to climate change, microclimate/microhabitat thermal refugia, and estimating relative vulnerability of species and habitats.

Abstract: same as above.

Source(s) of funding: Rainforest Co-operative Research Centre, Australian Research Council, James Cook University, Marine and Tropical Science Research Facility (CERF Hub), Queensland Government Smart State program, Wet Tropics Management Authority, National Science Foundation (USA), Earthwatch Institute.

B. Specific subproject description

Study Region: The region for which the data on the vertebrate species is assembled is the Australian Wet Tropics (AWT) bioregion. The AWT is a ~80 km wide strip of land along the coast of NE Australia between -16.5° to -19.5° N (for further description see, e.g., Nix 1991, Williams et al. 1996). Containing the largest area of rain forest in Australia (Switzer 1991), the AWT is a discrete biogeographical region encompassing a chain of tropical rain forests surrounded by drier and warmer environments (Nix 1991, Moritz 2005). A long history of rain forest expansion and contractions has created an assemblage of species with high levels of endemism (Williams and Pearson 1997). The AWT is one of the best studied rain forests worldwide; flora and fauna have been extensively surveyed (Williams 2006).

Research methods:

Life-history attributes: Life-history attributes were gathered from a variety of sources. Where possible, traits such as body size, length, and mass were taken from our own database to insure that measurements are specific to individuals from the Wet Tropics. Otherwise, data was collated from the primary and secondary literature. Where possible for each major taxonomic group (e.g., Mammals, Birds…etc), a primary literature source was used in order to gather as much data as possible. However, if multiple estimates of traits such as body mass were available the arithmetic mean was used in order to reduce the influence of erroneous data. In total, 19 traits were included. The text below includes definitions of each of these traits and how they were collected.

Mass (grams): A continuous variable. The body mass of adult individuals. This estimate is the average mass of the species given, including males and females.

Male Mass (grams): A continuous variable. The body mass of adult males.

Female Mass (grams): A continuous variable. The body mass of adult females.

Size (mm): A continuous variable. The size of adult individuals. This estimate is the average size of the species, including males and females. Length definitions are as follows: Birds - total length (beak - tail); Frogs: snout-urostyle length; Reptiles: Snout-vent length; Mammals: Combined head and body length.

Male Size (mm): A continuous variable. The size of adult males, if available.

Female Size (mm): A continuous variable. The size of adult males, if available.

Color dimorphism: A dichotomous/nominal variable. Species where data exists to suggest males and females have significantly different coloring for at least part of the year are denoted by a 1, those species in which the sexes are not known to differ in color are denoted by a 0. Where this information is unavailable, species are not given a value.

Age at first reproduction (days): A continuous variable. The age (in days) at which a female individual of the species first breeds and could potentially conceive. By definition, this is only recorded for females. This variable does not include gestation. If the age of first birth is given by a data source then gestation length was subtracted from the value to yield an estimate of first breeding.

Maximum Lifespan (years): A continuous variable. Maximum lifespan is the oldest age recorded for a member (male or female) of that species. Maximum lifespan, unlike the other variables, represents a single data point not an average; estimates come from both wild and captive populations.

Reproductive characteristics: A nominal variable. Includes information on potentially important reproductive characteristics for each broad taxonomic group. For example, identifies frogs which are obligate stream breeders, those that have a larval stage and those that have direct development. Mammals are identified as semelparous or iteroparous; reptiles are identified as those which are known to brood their clutch, and those which are not; and birds are classified into a variety of groups including those which are parasitic (the cuckoos); those which do not breed in the Wet Tropics, species with known cooperative breeding systems; those which maintain a pair-bond and/or provide bi-parental care; those with uniparental care and also species with no parental care.

Clutch or Litter size: A continuous variable. The average number of offspring produced in a single reproductive event.

Reproductive events/year: A continuous variable. The average number of reproductive event/bouts per year known for that species.

Reproductive seasonality: An ordinal variable. Includes information on the seasonal reproductive patterns. Species are grouped into three broad categories based on the estimated number of births which occur throughout the year.

Broad diet: A nominal variable. Includes information on the broad dietary classification of each species. Species are grouped into four broad categories based on the main proportion of their diet.

Activity period: A nominal variable. Species are grouped into one of four categories based on their primary period of activity (e.g.: nocturnal, diurnal, etc).

Shelter type: A nominal variable. Species are classified into one of three groups based on the type of shelter or refuge they are known to use.

Strata used: A nominal variable. Gives information on the primary type of strata of habitat used by a species. For example, whether a species is primarily terrestrial, arboreal or is able to fly (volant).

Potential for long distance dispersal: An ordinal variable. This variable is an index based on the sum of the following characteristics, which are thought to influence capacity for dispersal, for each species: Flight (1= yes, 0 = no); known movements sourced from the literature (1 = sedentary (<5 km); 2 = local dispersion (5–10 km); 3 = altitudinal migrations/nomadic (10–50 km); 4 = long-distance migrations (>50 km); Body size (1 = 0–100 mm; 2 = 101–250 mm; 3 = 251–500 mm; 4 = 500–1000 mm; 5 = >1000 mm). For frogs, a further category was included, to identify those species which had a freshwater tadpole dispersal stage (1 = yes, 0 = no). For example; for the southern cassowary (Casuarius casuarius): No flight (0), local movements of 5–10 km recorded (2), body size >1000 mm (5) totalling 0+2+5 = 7.

Endemic Status: A nominal variable. Species are grouped as either regional endemics or non-endemics.

Rain forest specialization: An ordinal variable. The variable describes increasing degree of specialization to rain forest based on patterns of abundance and occurrence in rain forest and adjacent forest types within the region: 0 – does not occur in rain forest; 1 – occasionally recorded in rain forest; 2 – use rainforest as sub-optimal/marginal habitat; 3 – commonly recorded in rain forest but not the species core habitat; 4 – rain forest is a main habitat but common in other forest environments; 5 – rain forest is core habitat but also occurring in wet sclerophyll; 6 – rain forest obligate.

Distribution attributes and modeling: Distributional data for the rain forest vertebrates of the AWT was collected during field intensive surveys and collated from the literature and institutional databases (as per Williams 2006). Major sources of species occurrences included: field intensive surveys by various researchers in the School of Marine and Tropical Biology, James Cook University, from which the data is now maintained and continued monitoring standard survey sites is done by the Centre for Tropical Biodiversity and Climate Change, James Cook University; Birds Australia Atlas of Australian Birds; QPWS Wildnet fauna database; and individual biologists (see special reference section of Williams et al. 1996). All occurrences were vetted for positional and taxonomic accuracy prior to use in modeling. The occurrences were used to model the distributions of the species, extract temperature, precipitation and elevational extents from the environmental data (described below), and estimate the marginality and specialization of a species with respect to the environmental space of AWT.

We utilized a maximum entropy algorithm (Maxent) (Phillips et al. 2006) to model a subset of the vertebrates of the rainforests in the AWT for which we had sufficient occurrence information. Sufficient number of occurrences for a species was quantified by species-specific experts as having localities that covered the full environmental space of the species. Thus for example, only two records for Cophixalus mcdonaldi were sufficient as the species only inhabits several square km on the top of a single mountain.. Maxent represents an ecological niche modeling approach that has been shown to outperform other modeling approaches for this type of study (Elith et al. 2006, Hernandez et al. 2006) and is more capable of dealing with small sample sizes than Bioclim, Domain or GARP (Hernandez et al. 2006). The ecological niche models (distribution models) were created using species occurrence data that were related to environmental data that included climatic and vegetation information. Occurrence information was collected as described above. The climatic data included annual mean temperature, temperature seasonality, maximum temperature of the warmest week, coldest temperature of the coldest week, annual precipitation, precipitation seasonality, precipitation of the driest quarter and precipitation of the wettest quarter, all of which were created using the Anuclim 5.1 software (McMahon et al. 1995) and an 80-m resolution DEM (resampled from GEODATA 9 Second DEM Version 2; Geoscience Australia, http://www.ga.gov.au/). The vegetation data consisted of floristically classified broad vegetation groups (BVG at a 1:2million resolution)(Accad et al. 2006).

Models were trained using geographically unique occurrence data and either 36,000 background points from a 1-km grid placed over the AWT region or a taxon-specific target group background (model_background, see Class IV meta-data). This dual approach was adopted because sampling effort was more concentrated in rain forest. Using a taxon specific target group background reduces the effect of environmentally biased sampling effort, especially for species that are more habitat generalist and their distribution extends beyond the rain forest, as per method recommended by Phillips and Dudik (2008). Individual target group backgrounds were created for birds, mammals, reptiles, and amphibians separately. The background points represented unique geographic localities for which surveys for the taxa of interest were completed.  For the rain forest species (rain forest specialization >3, see Class IV metatdata) that almost entirely used rain forests as their habitats, we used the standard 1-km grid consisting of ~36,000 background points. Models were then projected onto the spatial layers representing the study area at an 80-m resolution. Maxent produces spatial predictions of environmental suitability, a value between 0 (not suitable) to 1 (most suitable). These potential distributions were reclassified to rank the suitability of the environment into 6 classes: 0 – unsuitable and 1 to 5 representing increasing suitability. The breaks in these categories were defined such that anything below a threshold that minimizes 6 * training omission rate + .04 * cumulative threshold + 1.6 * fractional predicted area) was classified as 0 (unsuitable). This threshold produced the most realistic current distribution as validated by expert opinion (Stephen E. Williams¹, Yvette M. Williams¹, Luke P. Shoo1 and Craig Moritz², personal communication). Values between the threshold and 1 were equally divided into five categories and ranked accordingly. While the distributions supplied here are GIS files representing the six categories of suitability, raw Maxent predictions and thresholds are available upon request.

The modelled distributions were the potential distributions of the species (akin to the fundamental niche of (Hutchinson 1957). However, the realized distributions are often much smaller than the potential distributions due to biotic interactions, dispersal limitation, biogeographic barriers both now and over the habitat fluctuations of the Quaternary, and thus these potential distributions were clipped to represent a best estimate of realized distribution as defined by the expertise of Stephen E. Williams¹, Yvette M. Williams¹, Luke P. Shoo1, Conrad J. Hoskin² and Craig Moritz³. Potential distributions were clipped using a subregional species presence/absence matrix (Class IV meta-data, File: realizeddistmatrix.csv) that was compiled using all known records, literature and expert opinion based on an updated version of the distributions published in Williams et al. 1996 and Williams 2006. Subregional matrix and geographically defined subregions are provided and meta-data detailed in Class IV. Persons identified as experts were affiliated with (1) the Centre for Tropical Biodiversity and Climate Change Research, School of Marine and Tropical Biology, James Cook University, Queensland, Australia, (2) Australian National University and (2) Museum of Vertebrate Zoology, Berkeley, California, USA.

Marginality and specialization for each species were estimated using Ecological-Niche Factor Analysis (ENFA) (Hirzel et al. 2002). ENFA is a modified principal component analysis that compares climatic input data of where a species occurs with the available climatic data of the study area (background). ENFA returns values for "marginality" which is a measure of niche position quantifying the difference of the input data mean from the background mean, and "specialization" which is a measure of niche width quantifying input data variance relative to the background variance. Given identical background environmental space, the values of marginality and specialization for different species are directly comparable. For ENFA, only the climatic data was used as ENFA cannot handle categorical data (e.g., vegetation information). The climatic data was Box–Cox transformed prior to analysis. Box–Cox transformations (Box and Cox 1964) were used to normalize the climatic data because this procedure estimates the best transformation to normality using power transformations (Sokal and Rohlf 1981). The ENFA was run using the adehabitat package (v1.7.1, http://www.r-project.org) and Box–Cox transformations were done using the CAR package (v1.2-7, http://www.r-project.org), both within the R statistical program(v2.6.2, http://www.r-project.org).

From the occurrences and the environmental data, a further 14 columns were added to the distributional and life-history data table. These are defined below:

Number of occurrences: A continuous variable representing the number of unique geographic occurrence localities used to estimate the following distribution characteristics of each species.

AUC: a continuous variable ranging between 0 and 1 representing the accuracy of the modelled species distributions. The accuracy statistic is defined as the Area Under the receiver operating Curve (AUC).

Model background: a variable representing which of two background datasets was used for modeling the species distributions.

Area of the realized distribution (km²): A continuous variable representing the area of the realized distribution, which was created using a collated species by subregion matrix (see above) and expert opinion to clip the potential distribution.

Core area of the realized distribution (km²): A continuous variable representing the area of the highest 80% of environmental suitability of the realized distribution, clipped using expert opinion and the subregional species occurrence matrix.

Area of the potential distribution (km²): A continuous variable representing the area of the potential distribution, modelled using Maxent as defined above.

Core area of the potential distribution: (km²) A continuous variable representing the area of the highest 80% of environmental suitability of the potential distribution.

Elevational range (m.a.s.l.): A character string representing the range in elevation for which the species has been observed.

Temperature range (°C): A character string representing the range in mean annual temperature of the locations for which the species has been observed.

Precipitation range (mm): A character string representing the range in mean annual precipitation of the locations for which the species has been observed.

Marginality: A continuous variable representing the marginality value as estimated using Ecological Niche Factor Analysis (ENFA) (described above). Marginality is a measure describing the deviation of the environmental space utilized by a species from the mean environmental space of the study region.

Specialization: A continuous variable representing the specialization value as estimated using Ecological Niche Factor Analysis (ENFA)(described above). Specialization is a measure of the species specific niche breadth relative the available niche space of the study region.

Number of vegetation types: A continuous variable representing the number of vegetation types the species has been recorded in (based on the occurrences). Vegetation groups for each occurrence point were extracted from a spatial vegetation layer created by Stanton and Stanton (2005); we used index level 3 as this was deemed most appropriate given the wide variation of occurrence records among species. The number of unique vegetation types is reported here.

Vegetation specialization: A continuous variable representing the proportion of occurrences in the dominant vegetation type. This value represents the greatest proportion of occurrence records for a species which were recorded in a single vegetation group. For example, if a species has a total of 30 occurrence records, and 17 of them were within habitat classified as rain forest, a vegetation specialization value of 0.56 was assigned to that species. Vegetation groups for each occurrence point were extracted from a spatial vegetation layer created by Stanton and Stanton (2005); we used index level 3 as this was deemed most appropriate given the wide variation of occurrence records among species.

Expert opinion of the reliability estimates for species distribution maps

The maps represent our best estimate of the current distribution of the rain forest vertebrates of the Australian Wet Tropics. Maps are dependent on an enormous amount of field data collected within our research group over the years and supplemented with data from many other institutions and persons who have generously made their data available. We have used the data to inform the best species distribution models possible at this time based on climate, topography, and vegetation. The potential distributions are modified by a matrix of subregion by species presence that is based on the combined inputs of many years of experience in the region and all possible sources of data. This matrix quantifies the effects of biogeographic barriers and other limits to distributions in order to produce our best possible estimate of the real distribution of each species. We have been conservative in our approach here and have only removed the predicted distribution from subregions where we are very confident that the species does not occur based on extensive field work and for those species that are detectable enough that we feel that we would have observed the species if it was present. In all other cases, the predicted (potential) distribution is left unchanged. Additionally, the quality of the distribution models vary across species depending on the number of records, distribution of the records across geographic and environmental space, sampling biases, species detectability, taxonomic changes, reliability of field identification and uncertainty around species specific effects of some biogeographic barriers. We have not included maps of any species where we felt that the map was at least not useful in a rudimentary way and have provided a subjective ranking of the reliability of each distribution map based on our perception of the impact that the various biases have had on the final realized distribution. Each map is ranked on a scale of increasing reliability from 1–4 (map_reliability in Class IV metadata):

We have attempted to qualify rankings 1–3 with a descriptor that helps to identify the shortcomings of the distribution map based on our knowledge of the biology of the species and quality of the available data for that species.

Phylogenies: For each taxonomic group a ‘best estimate’ phylogeny was created by first constructing an outline tree structure at the family level, and then filling in at the species level from published phylogenies. In the majority of cases, phylogenies used from the literature were the most recent we could find and based on molecular methods. In cases where a specific endemic species was not included in a published phylogeny, they were added in at the point where other species in the genus were placed. Similarly, sub-species were added as sister species. Specific references used for the construction of phylogenies for each taxonomic group are given below. The expertise of Prof. Craig Moritz (University of California, Berkley) and Dr. Conrad J. Hoskin (Australian National University) was also used to assess relationships among lesser known taxa and endemic species. The references used to construct the phylogenies for each taxonomic group are given below.

Phylogeny references:

Aves

Mindell, David P., and Joseph W. Brown. 2005. Neornithes. Modern Birds. Version 14 December 2005 (under construction). http://tolweb.org/Neornithes/15834/2005.12.14 in The Tree of Life Web Project, http://tolweb.org/

Mindell, David P., Joseph W. Brown, and John Harshman. 2008. Neoaves. Version 27 June 2008 (under construction). http://tolweb.org/Neoaves/26305/2008.06.27 in The Tree of Life Web Project, http://tolweb.org/

Christidis, L., and W. Boles. 2008.  Systematics and taxonomy of australian birds.  CSIRO Publishing, Australia.

Oscine passerines

Jonsson and Fjeldsa.  2006.  A phylogenetic supertree of oscine passerine birds (Aves: Passeri), Zoologica Scripta 35:149–186. (Overall structure, and to species level when a specific phylogeny was not available).

Kusmierski, R., G. Borgia, R. H. Crozier,  and B. H. Y. Chan. 1993. Molecular information on bowerbird phylogeny and the evolution of exaggerated male characteristics. Journal of Evolutionary Biology 6:737–752.

Driskell, A. C., and L. Cristidis. 2003. Phylogeny and evolution of the Australa-Papuan honeyeaters (Passeriformes, Meliphagidae). Molecular Phylogenetics and Evolution 31:943–960.

Alcidinidae

Moyle, R. G.  2006.  A molecular phylogeny of kingfishers (Alcedinidae) with insights into early biogeographic history. The Auk 123:487–499.

 Columbiformes

Shapiro, B., D. Sibthorpe, A. Rambaut, J. Austin, G. M. Wragg, O. R. P.  Bininda-Emonds, P. L. M. Lee, and A. Cooper.  2002.  Flight of the Dodo.  Science 295:1683.

Cuculiformes

Sorenson, M. D., and R. B. Payne.  2002.  Molecular genetic perspectives on avian brood parasitism.  Integrated and Comparative Biology 42:388–400.

Psittaciformes

Christidis, L., R. Schodde, D. D. Shaw, and S. F. Maynes. 1991.  Relationships between the Australa-Papauan parrots, lorikeets and cockatoos (Aves: Psittaciformes): Protein evidence. The Condor 93:302–317.

Apodiformes and Caprimulgiformes

Mayr, G. 2003.  Phylogeny of early tertiary swifts and hummingbirds (Aves: Apodiformes) The Auk 120:145–141.

Lee, P. L. M., D. H. Clayton, R. Griffiths, and R. D. M. Page. 1996.  Does behaviour reflect phylogeny in swiftlets (Aves: Apodidae): A test using cytochrome b mitochondrial DNA sequences. Proceedings of the National Academy of Sciences 93:7091–7096.

Strigiformes

Tree of Life Web Project. 2005. Strigiformes. Version 14 December 2005 (temporary). http://tolweb.org/Strigiformes/26388/2005.12.14in The Tree of Life Web Project, http://tolweb.org/

Falconiformes

The Accipitridae (hawks and eagles)Lerner, Heather R. L., and David P. Mindell. 2006. Accipitridae. Version 09 May 2006 (temporary). http://tolweb.org/Accipitridae/26375/2006.05.09 in The Tree of Life Web Project, http://tolweb.org/

The Falconidae (falcons)

Tree of Life Web Project. 2005. Falconiformes. diurnal birds of prey. Version 14 December 2005 (temporary). http://tolweb.org/Falconiformes/56735/2005.12.14 in The Tree of Life Web Project, http://tolweb.org/

Mammals

Strahan, R. 2006.  Mammals of Australia: third edition.  New Holland Publishers, Sydney, Australia.

Marsupials

Cardillo, M., O. R. P. Bininda-Emonds, E. Boakes, and A. Purvis. 2004.  A species level phylogenetic supertree of marsupials. Journal of Zoology 264:11–31.

Rodents

Ford, F. D. 2006. A splitting headache: relationships and generic boundaries among Australian murids. Biological Journal of Linnean Society 89:117–138.

Ford, F. D. (unpublished data) Phylogeny for Rattus spp.

Bats

Jones, K. E., A. Purvis, A. MacLarnon, O. R. P. Bininda-Emonds, and N. B. Simmons.  2002.  A phylogenetic supertree of the bats (Mammalia: Chiroptera). Biological Reviews of the Cambridge Philosophical Society 77:223–259.

Frogs

Ruvinsky and Maxson.  1996.  Phylogenetic relationships among Bufonoid Frogs (Anura: Neobatrachia) inferred from mitochondrial DNA sequences.  Molecular Phylogenetics and Evolution 5:533–547.

Ford, L. S., and D. C. Cannatella. 1993. The major clades of frogs. Herpetological Monographs 7:94–117. (Outline structure)

Hoskin, C. J. and J-M. Hero.  2008.  Rainforest Frogs of the Wet Tropics, north-east Australia.  Griffith University, Gold Coast, Australia.

Hylidae

Byrne, P. G., J. D. Roberts, and L. W. Simmons.  2003.  Sperm competition selects for increased testes mass in Australian frogs. Journal of Evolutionary Biology 2002 15:347.

Donnellan, S. C., and M. J. Mahony.  2004.  Allozyme, chromosomal and morphological variation in the Litoria lesueuri species group, Including a description of a new species.  Australian Journal of Zoology 52:1–28.

Favovich, J., C. F. B. Haddad, P. C. A. Garcia, D. R. Frost, J. A. Campbell, and W.C. Wheeler.  2005.  Systematic review of the frog family hylidae, with special reference to hylinae: phylogenetic analysis and taxonomic revision. Bulletin of the American Museum of Natural History 294:1–240.

Hutchinson, M. N., and L. R. Maxson.  1987.  Phylogenetic relationships among Australian tree frogs (Anura: Hylidae: Pelodryadinae): an immunological approach. Australian Journal of Zoology 35:61–74.

Young, J. E., K. A. Christian, S. Donnellan, C. R. Tracy, and D. Parry.  2005.  Comparative analysis of cutaneous evaporative water loss in frogs demonstrates correlation with ecological habits. Physiological and Biochemical Zoology 78:847–856.

Myobatrachidae

Mahony, M., S. C. Donnellan, S. J. Richards, and D. McDonald.  2006.  Species boundaries among barred river frogs, Mixophyes (Anura: Myobatrachidae) in north-eastern Australia, with descriptions of two new species. Zootaxa 1228:35–60.

Read, K., J. S. Keogh, I. A. W. Scott, J. D. Roberts, and P. Doughty.  2001. Molecular phylogeny of the Australian frog genera Crinia, Geocrinia, and allied taxa (Anura: Myobatrachidae). Molecular phylogenetics and Evolution 21:294–308.

Schauble, C. S., C. Moritz, and R. W. Slade.  2000.  A molecular phylogeny for the frog genus Limnodynastes (Anura: Myobatrachidae). Molecular Phylogenetics and Evolution 16:379–391.

Microhylidae (Cophixalus and Austrochaperina)

Hoskin, C. J.  2004.  Australian microhylid frogs (Cophixalus and Austrochaperina): phylogeny, taxonomy, calls, distributions and breeding biology. Australian Journal of Zoology 52:237–269.

Reptiles

Vidal, N., and S. B. Hedges.  2005.  A phylogeny of squamate reptiles (lizards, snakes and amphisbaenians) inferred from nine nuclear protein-coding genes. Comptes Rendus Biologies 328:1000–1008. (Outline structure)

Wilson, S., and G. Swan.  2008.   A complete guide to reptiles of Australia, second edition.  New Holland Publishers, Sydney, Australia.

Geckkonidae:

Hoskin, C. J., P. J. Couper, and C. J. Schneider.  2003.  A new species of Phyllurus (Lacertilia: Gekkonidae) and a revised phylogeny and key for the Australian leaf-tailed geckos. Australian Journal of Zoology 51:153–164.

Han, D., K. Zhou, and A. M. Bauer.  2004.  Phylogenetic relationships among the gekkotan lizards inferred from C-mos nuclear DNA sequences and a new classification of the Gekkota. Biological Journal of the Linnean Society 83:353–368.

Melville, J., J. A. Schulte II, and A. Larson.  2004.  A molecular study of phylogenetic relationships and evolution of anti predator strategies in Australian Diplodactylus geckos, subgenus Strophurus. Biological Journal of the Linnean Society 82:123–138.

Scincidae:

Goodman, B. A., A. K. Krockenberger, and L. Schwarzkopf.  2007.  Master of them all: performance specialization does not result in trade-offs in tropical lizards. Evolutionary Ecology Research 9:527–546.

Moussalli, A., A. F. Hugall, and C. Moritz.  2005.  A mitochondrial phylogeny of the rainforest skink genus Saproscincus, Wells and Wellington (1984). Molecular Phylogenetics and Evolution 34:190–202.

O’Connor, D., and C. Moritz.  2003.  A molecular phylogeny of the Australian skink genera Eulamprus, Gnypetoscincus and Nangura. Australian Journal of Zoology 51:317–330.

Reeder, T. W.  2003.  A phylogeny of the Australian Sphenomorphus group (Scincidae: Squamata) and the phylogenetic placement of the crocodile skinks (Tribolonotus): Bayesian approaches to assessing congruence and obtaining confidence in maximum likelihood inferred relationships. Molecular Phylogenetics and Evolution 27:384–397.

Stuart-Fox, D. M., A. F. Hugall, and C. Moritz.  2002.  A molecular phylogeny of rainbow skinks (Scicidae: Carlia): taxonomic and biogeographic implications. Australian Journal of Zoology 50:39–51.

Varanidae:

Fitch, A. J., A. E. Goodman,  and S. C. Donnellan.  2006.  A molecular phylogeny of the Australian monitor lizards (Squamata: Varanidae) inferred from mitochondrial DNA sequences. Australian Journal of Zoology 54:253–269.

Serpentes:

Heise, P. J., L. R. Maxson, H. G. Dowling, and S. B. Hedges.  1995.  Higher level snake phylogeny inferred from mitochondrial DNA sequences of 12S rRNA and 16S rRNA genes. Molecular Biology and Evolution 12:259–265. (Outline structure).

Greer, A. 1997.  The biology and evolution of Australian snakes. Surrey Beatty, Sydney, Australia.

Keogh, J. S., I. A. W. Scott, and J. D. Scanlon.  2000.  Molecular phylogeny of viviparous Australian elapid snakes: affinities of Echiopsis atriceps (Storr, 1980) and Drysdalia coronata (Schlegel, 1837), with a description of a new genus. Journal of Zoology 252:317–326.

Pizzatto, L., S. M. Almeida-Santos, and R. Shine.  2007.  Life history adaptations to arboreality in snakes. Ecology 88:359–368.

Reed, R. N., and R. Shine.  2002.  Lying in wait for extinction: ecological correlates of conservation status among Australian elapid snakes. Conservation Biology 16:451–461.

Scanlon, J. D., and M. S. Y. Lee.  2004.  Phylogeny of Australasian venomous snakes (Colubroidea, Elapidae, Hydrophiinae) based on phenotypic and molecular evidence. Zoologica Scripta 33:335–366.

Wuster, W., A. J. Dumbrell, C. Hay, C. E. Pook, D. J. Williams, and B. G. Fry.  2005.  Snakes across the strait: trans-Torresian phylogeographic relationships in three genera of Australasian snakes (Serpentes: Elapidae: Acanthophis, Oxyuranus, and Pseudechis). Molecular Phylogenetics and Evolution 34:1–14.

Taxonomy and systematics:Taxonomy is based on the collated and updated information contained in the references listed above.

Permit history: NA.

Legal/organizational requirements: None.

Project personnel: Stephen E. Williams, Jeremy VanDerWal, Luke Shoo, Collin Storlie, Samantha Fox, Emily Bolitho, Alex Anderson, Yvette Williams, Joanne Isaac, Luke Shoo, Craig Moritz, Sara Townsend, Jeff Middleton, Robert Henriod, Petch Manopawitr, Anthony Backer, Adam Tassicker, Rachel Groom, Rebecca Fisher, Gary Langham, Richard Retallick, Martin Cohen, Greg Calvert, Greer Gilroy, Jeremy Austin.

CLASS III. DATA SET STATUS AND ACCESSIBILITY

A. Status

Latest update: June 2009.

Latest Archive date: June 2009

Metadata status: metadata are complete and up to date.

Data verification: See CLASS II, section 3, Research Methods.

B. Accessibility

Storage location and medium: (Ecological Society of America data archives [Ecological Archives], URL published in each issue of its journals). Original data files exist on author’s personal computer and on CD.

Contact person:Stephen Williams, Centre for Tropical Biodiversity and Climate Change, School of Marine and Tropical Biology, James Cook University, Townsville, Queensland 4811, Australia, [email protected]

Copyright restrictions: None.

Proprietary restrictions: None.

Costs: None.

CLASS IV. DATA STRUCTURAL DESCRIPTORS

A. Data Set File

Identity: spp_data.csv

Size:242 records, 54 kbytes.

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information:The first row of the file contains the variable names below.

Alphanumeric attributes: Mixed

Special characters/fields: N/A

Authentication procedures: N/A

B. Variable information

SPATIAL DISTRIBUTIONS – POTENTIAL

Data Set File

Identity: distributions_potential.zip

Size: 1,422,735,271 bytes.

Format and storage mode: ASCII grid files of the species potential distributions. Individual files are compressed with gzip. All files are contained and further compressed using ZIP.

Header information: A six row header in each ASCII grid file defines the number of rows, columns, position of the lower left corner, cell size and the nodata value. All grid files here have the following header information:
ncols 3368
nrows 6007
xllcorner 255161.558
yllcorner 7813802.662
cellsize 80.0
NODATA_value -9999

Alphanumeric attributes: N/A.

Special characters/fields: N/A

Authentication procedures: NA

B. Variable information

Description: This is a zipped directory, containing a series of ASCII grid file corresponding to species in the distribution and life history table (spp_data.csv). The grids represent the potential distribution of the species as defined in the Class II-B Research Methods. All grids are WGS84 UTM zone 55S projection.

SPATIAL DISTRIBUTIONS – REALIZED

20.  Data Set File

Identity: distributions_realized.zip

Size: 1,377,274,521 bytes.

Format and storage mode: ASCII grid files of the species realized distributions. Individual files are compressed with gzip. All files are contained and further compressed using ZIP.

Header information: A six row header in each ASCII grid file as which defines the number of rows, columns, position of the lower left corner, cell size and the nodata value. All grid file here have the following header information:
ncols 3368
nrows 6007
xllcorner 255161.558
yllcorner 7813802.662
cellsize 80.0
NODATA_value -9999

Alphanumeric attributes: N/A.

Special characters/fields: N/A

Authentication procedures: NA

B. Variable information

Description: This is a zipped directory, containing a series of ASCII grid files corresponding to species in the distribution and life history tables (spp_data.csv). The grids represent the realized distribution of the species as defined in the Class II-B Research Methods. All grids files are WGS84 UTM zone 55S projection.

SPATIAL DISTRIBUTIONS – IMAGES OF POTENTIAL AND REALIZED

Data Set File

Identity: distributions_images.zip

Size: 34,795,911 bytes.

Format and storage mode: PNG image files of the species potential and realized distributions. All files are contained and compressed using ZIP.

Header information: N/A.

Alphanumeric attributes: N/A

Special characters/fields: N/A

Authentication procedures: NA

B. Variable information

Description: This is a zipped directory, containing a series of PNG image files corresponding to species in the distribution and life history tables (spp_data.csv). The images represent the potential and realized distributions of the species as defined in the Class II-B Research Methods. Coloring of images are such that gray is not part of the predicted distribution and colors ramping from yellow to red represent low to high predicted environmental suitability.

DISTRIBUTION AND SUBREGION CLIPPING MATRIX

Data Set File

Identity: RealizedDistMatrix.csv

Size: 202 records, 20,742 bytes

Format and storage mode: ASCII text, comma separated. No compression scheme was used.

Header information: The first row of the file contains the variable names below.

Alphanumeric attributes: Mixed

Special characters/fields: N/A

Authentication procedures: N/A

B. Variable information

SUBREGION SHAPEFILE

Data Set File

Identity: subregion_shapefile.zip

Size: 685,449 bytes.

Format and storage mode: Polygon shapefile of biogeographical subregions with all necessary files contained and compressed using ZIP.

Header information:

Alphanumeric attributes: N/A

Special characters/fields: N/A

Authentication procedures: NA

B. Variable information

Description: A polygon shapefile outlining all biogeographical regions used to clip potential distributions of species to realized distributions. The shapefile is projected using WGS84 UTM zone 55S projection.

PHYLOGENIES OF SPECIES

20.  Data Set File

Identity: phylogonies.zip

Size: 32,306 bytes.

Format and storage mode: Nexis files (*.nex) and pdf images of phylogenies for each of the broad groups of taxa in the data table. Compressed using ZIP.

Header information: N/A

Alphanumeric attributes: Mixed

Special characters/fields: N/A

Authentication procedures: N/A

B. Variable information

Description: This is a zipped directory, containing a series of NEX and pdf images describing the phylogenies of broad taxonomic groups of the species in the distribution and life history tables (spp_data.csv). Species names have been shortened to codes as per distribution and life history table (spp_data.csv).

CLASS V. SUPPLEMENTAL DESCRIPTORS

A. Data acquisition

Data forms: N/A.

Location of completed data forms: Data entry verification procedures: See CLASS II, section 3, Research Methods.

B. Quality assurance/quality control procedures: N/A

C. Related material: N/A

D. Computer programs and data processing algorithms: N/A

E. Archiving

Archival Procedures: Data files and associated metadata have been archived on Centre for Tropical Biodiversity and Climate Change website (www.biodiversity.jcu.edu.au). Data files may also be retrieved from this site.

Redundant Archival Sites: NA

F. Publications using the data set:

Vanderwal et al. 2009; Isaac et al. 2009, Williams et al. in review, PNAS;.

G. Publications using the same sites: N/A

H. History of data set usage

Data request history: N/A

Data set update history: N/A

Review history: N/A

Questions and comments from secondary users: N/A

ACKNOWLEDGMENTS

We would like to thank all of the organizations that helped fund the intense field work over the years to collect the data used and presented here including James Cook University, Rainforest-CRC, Marine & Tropical Science Research Facility – CERF, Earthwatch Institute, Queensland Smart State program, Australian Research Council, National Science Foundation (USA), National Geographic, Museum of Vertebrate Zoology – University of California (Berkeley), Wet Tropics Management Authority and the Skyrail Rainforest Foundation. Considerable input has been also been provided by individuals and organizations who have assisted in the field or provided access to data and permits to conduct the research including Queensland Parks and Wildlife Service, Queensland Forestry, Environmental Protection Agency – Wildlnet records, Rainforest Aboriginal Council, Queensland Museum, Birds Australia, and many individuals too numerous to name here but including many field volunteers, post-graduate students and many of the individuals that are listed in the special reference section of Williams et al. 1996 and Williams 2006.

References for the life-history table (spp_data.csv):

1.1. Marchant, S., and P. J. Higgins. Editors. 1993. Handbook of Australian, New Zealand and Antarctic birds. Volume 2: Raptors to lapwings. Oxford University Press, Sydney, Australia.

1.2. Higgins, P. J., and S. J. J. F. Davies. Editors. 1996 Handbook of Australian, New Zealand and Antarctic birds. Volume 3: Snipe to pigeons. Oxford University Press, Melbourne, Australia.

1.3. Higgins, P. J. Editor. 1999. Handbook of Australian, New Zealand and Antarctic birds. Volume 4: Parrots to dollarbirds. Oxford University Press, Melbourne, Australia.

1.4. Higgins, P. J., J. M. Peter, and W. K. Steele. Editors. 2001. Handbook of Australian, New Zealand and Antarctic birds. Volume 5: Tyrant-flycatchers to chats. Oxford University Press, Melbourne, Australia.

1.5. Higgins, P. J., and J. M. Peter. Editors. 2002. Handbook of Australian, New Zealand and Antarctic Birds. Volume 6: Pardalotes to shrike thrushes. Oxford University Press, Melbourne, Australia.

1.6. Higgins, P. J., J. M. Peter, and S. J. Cowling. Editors. 2006. Handbook of Australian, New Zealand and Antarctic birds. Volume 7: Boatbills to starlings. Oxford University Press, Melbourne, Australia.

2. The Australian bird and bat banding scheme (2008 – online). http://www.environment.gov.au/biodiversity/science/abbbs/.

3. AnAge database. Human ageing genomic resources. http://genomics.senescence.info/species/.

4 . Romer, L. 2000. Management of the double-eyed or red-browed fig parrot Cyclopsitta diophthalma macleayana at Currumbin Sanctuary, Queensland. International Zoo Yearbook, 37:152–158.

5. Cogger, H. 2000 Reptiles and amphibians of Australia: sixth edition. Reed New Holland, Sydney, Australia.

6. AmphibiaWeb. 2006. Information on amphibian biology and conservation. (web application). Berkeley, California: AmphibiaWeb. Available: http://amphibiaweb.org/.

7. Frogs Australia Network (Web Application). http://frogsaustralia.net.au/about/.

8. Felton, A.  1999.  Determinants of male mating success in the Microhylid frog Cophixalus ornatus. MSc Thesis, James Cook University, Townsville, Australia.

9. Morrison, F. C.  2001.  Altitudinal variation in the life history of anurans in southeast Queensland. PhD Thesis, Griffith University, Australia.

10. Strahan, R. 1995. The mammals of Australia. revised edition. Reed New Holland, Sydney, Australia.

11. Fisher, D. O., I. P. F. Owens, and C. N. Johnson. 2001. The ecological basis of life history variation in marsupials. Ecology 82:3531–3540.

12. Carey, J. R., and D. S. Judge.  2008 (online version).  Longevity records: life spans of mammals, birds, amphibians, reptiles, and fish. Monographs on Population Aging, 8. Odense University Press.

13. Thomson, P. C., K. Rose, and N. E. Kok.  1992.  The behavioural ecology of dingoes in north-western Australia. 6. Temporary extraterritorial movements and dispersal. Wildlife Research 19:585–595.

14. Dennis, A. J., and H. Marsh.  1997.  Seasonal reproduction in musky rat kangaroos, Hypsiprymnodon moschatus: a response to changes in resource availability. Wildlife Research 24:561–578.

15. Gardner, J. L., and M. Serena.  1995.  Spatial organization and movement patterns of adult male platypus, Ornithorhynchus anatinus (Monotremata, Ornithorhynchidae). Australian Journal of Zoology 43:91–103.

16. Greer, A. E. (online) Encyclopedia of Australian reptiles. Australian Museum Online http://www.amonline.net.au/herpetology/research/encyclopedia.pdf. Version date: various.

17. Greer, A. E.  1997.  The Biology and Evolution of Australian Snakes. Surrey Beatty, Australia.

18. Shine, R.  1995.  Australian snakes: a natural history. Cornell University Press.

19. Reptiles and amphibians in captivity – longevity (online) http://www.pondturtle.com/longev.html.

20. Shine, R.  1987.  Intraspecific variation in thermoregulation, movements and habitat use by Australian blacksnakes, Pseudichis porphyriacus (Elapidae). Journal of Herpetology  21:165–177.

21. Mahony, M., S. C. Donnellan, S. J. Richards, and D. McDonald.  2006.  Species boundaries among barred river frogs, Mixophyes (Anura: Myobatrachidae) in north-eastern Australia, with descriptions of two new species. Zootaxa 1228:35–60.

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