Species distribution models (SDMs) are valuable tools for assessing species' responses to environmental factors and identifying areas suitable for their survival. The careful selection of input variables is critical, as their interactions and correlations with other environmental factors can affect model performance. This study evaluates the influence of climate and soil variables on the performance of SDMs for 5033 Australian terrestrial vascular plant species, representing the largest phylogenetic diversity of native flora assessed in such an analysis. Using an ensemble of correlative models, we assessed the predictive performance of climate and soil variables, individually and in combination, across four distinct ecoregions: Desert (n = 640 species), Mediterranean (n = 1246), Temperate (n = 1936), and Tropical (n = 1211). Our results demonstrate that on a continental scale, climate variables have a greater influence on plant distributions than soil variables. Although incorporating soil and climate variables enhanced model performance in some ecoregions, our results indicate that relying solely on small-scale variables such as soil may increase the likelihood of underfitting. The most influential predictor variables in the models varied across ecoregions and between specialist and generalist species. Mean annual rainfall (bio1) was consistently a strong climate predictor variable across ecoregions, but other climate variables became more important when analyses were restricted to ecoregion-specific species (i.e., specialists). Soil organic carbon (SOC) was the most important soil variable in the Temperate and Tropical ecoregions across generalist and specialist species. In the Mediterranean ecoregion, clay content (CLY) became more important than SOC when analyses were restricted to ecoregion-specific species, whereas nitrogen total organic (NTO) was consistently the strongest predictor soil variable for plants in the Desert. Our findings have significant implications for understanding the interplay between climate, soil, and plant distribution within diverse ecoregions. This study serves as a foundation for developing more accurate SDM predictions.

College of Arts and Sciences Qatar University Doha Qatar

College of Science and Engineering Flinders University Bedford Park South Australia Australia

Department of Ecological Modelling Helmholtz Centre for Environmental Research UFZ Leipzig Germany

Department of Natural Resources Isfahan University of Technology Isfahan Iran

Department of Plant Sciences University of California Davis Davis California USA

Faculty of Science University of South Bohemia České Budějovice Czech Republic

INIFAP National Research Institute of Agriculture Forestry and Livestock Zacatecas México

Institute of Parasitology Biology Centre CAS České Budějovice Czech Republic

Postgraduate Program in Plant Science Diamantina Minas Gerais Brazil

RIKEN Center for Advanced Intelligence Project Goal Oriented Technology Research Group Disaster Resilience Science Team Tokyo Japan

School of Agriculture Food and Ecosystem Sciences University of Melbourne Richmond Victoria Australia

School of Engineering and Technology Central Queensland University Rockhampton Queensland Australia

See more in PubMed

Adde, A. , Rey P. L., Fopp F., et al. 2023. “Too Many Candidates: Embedded Covariate Selection Procedure for Species Distribution Modelling With the Covsel R Package.” Ecological Informatics 75: 102080.

Aerts, R. , and Chapin F. S. I.. 1999. “The Mineral Nutrition of Wild Plants Revisited: A Re‐Evaluation of Processes and Patterns.” Advances in Ecological Research 30: 1.

Ahmadi, M. , Hemami M. R., Kaboli M., and Shabani F.. 2023. “MaxEnt Brings Comparable Results When the Input Data Are Being Completed; Model Parameterization of Four Species Distribution Models.” Ecology and Evolution 13: e9827. PubMed PMC

Ala . 2024. “Atlas of Living Australia Website.” Accessed June 28, 2024. https://www.ala.org.au/.

ANPSA . 2024. “Australian Native Plants Society.” Accessed July 10, 2024. https://anpsa.org.au/.

Apc . 2024. “Australian Plant Census.” Accessed July 10, 2024. https://biodiversity.org.au/.

Araújo, M. B. , and Guisan A.. 2006. “Five (Or So) Challenges for Species Distribution Modelling.” Journal of Biogeography 33: 1677–1688.

Araújo, M. B. , and New M.. 2007. “Ensemble Forecasting of Species Distributions.” Trends in Ecology & Evolution 22: 42–47. PubMed

Arenas‐Castro, S. , Regos A., Martins I., Honrado J., and Alonso J.. 2022. “Effects of Input Data Sources on Species Distribution Model Predictions Across Species With Different Distributional Ranges.” Journal of Biogeography 49: 1299–1312.

Austin, M. P. , and Meyers J. A.. 1996. “Current Approaches to Modelling the Environmental Niche of Eucalypts: Implication for Management of Forest Biodiversity.” Forest Ecology and Management 85: 95–106.

Austin, M. P. , and Van Niel K. P.. 2011. “Improving Species Distribution Models for Climate Change Studies: Variable Selection and Scale.” Journal of Biogeography 38: 1–8.

Baltzer, J. L. , Davies S. J., Bunyavejchewin S., and Noor N. S. M.. 2008. “The Role of Desiccation Tolerance in Determining Tree Species Distributions Along the Malay–Thai Peninsula.” Functional Ecology 22: 221–231.

Beck, J. , Böller M., Erhardt A., and Schwanghart W.. 2014. “Spatial Bias in the GBIF Database and Its Effect on Modeling Species' Geographic Distributions.” Ecological Informatics 19: 10–15.

Berg, G. , and Smalla K.. 2009. “Plant Species and Soil Type Cooperatively Shape the Structure and Function of Microbial Communities in the Rhizosphere.” FEMS Microbiology Ecology 68: 1–13. PubMed

Booth, T. H. 2017. “Assessing Species Climatic Requirements Beyond the Realized Niche: Some Lessons Mainly From Tree Species Distribution Modelling.” Climatic Change 145: 259–271.

Brenes, T. , Paredes M. R., Rivas‐Torres G., Blundo C., Coley P. D., and Kursar T.. 2008. “The Effect of Soil on the Growth Performance of Tropical Species With Contrasting Distributions.” Oikos 117: 1453–1460.

Broadhurst, L. , and Coates D.. 2017. “Plant Conservation in Australia: Current Directions and Future Challenges.” Plant Diversity 39: 348–356. PubMed PMC

Brown, C. J. , O'connor M. I., Poloczanska E. S., et al. 2016. “Ecological and Methodological Drivers of Species' Distribution and Phenology Responses to Climate Change.” Global Change Biology 22: 1548–1560. PubMed

Bui, E. N. , González‐Orozco C. E., and Miller J. T.. 2014. “Acacia, Climate, and Geochemistry in Australia.” Plant and Soil 381: 161–175.

Castellanos, A. A. , Huntley J. W., Voelker G., and Lawing A. M.. 2019. “Environmental Filtering Improves Ecological Niche Models Across Multiple Scales.” Methods in Ecology and Evolution 10: 481–492.

Chust, G. , Chave J., Condit R., Aguilar S., Lao S., and Pérez R.. 2006. “Determinants and Spatial Modeling of Tree β‐Diversity in a Tropical Forest Landscape in Panama.” Journal of Vegetation Science 17: 83–92.

Connolly, S. R. , Keith S. A., Colwell R. K., and Rahbek C.. 2017. “Process, Mechanism, and Modeling in Macroecology.” Trends in Ecology & Evolution 32: 835–844. PubMed

Connor, T. , Hull V., Viña A., et al. 2017. “Effects of Grain Size and Niche Breadth on Species Distribution Modeling.” Ecography 41, no. 8: 1270–1282.

Crimmins, S. M. , Dobrowski S. Z., and Mynsberge A. R.. 2013. “Evaluating Ensemble Forecasts of Plant Species Distributions Under Climate Change.” Ecological Modelling 266: 126–130.

Datta, A. , Schweiger O., and Kühn I.. 2020. “Origin of Climatic Data Can Determine the Transferability of Species Distribution Models.” NeoBiota 59: 61–76.

Davidar, P. , Rajagopal B., Mohandass D., et al. 2007. “The Effect of Climatic Gradients, Topographic Variation and Species Traits on the Beta Diversity of Rain Forest Trees.” Global Ecology and Biogeography 16: 510–518.

Delgado‐Baquerizo, M. , Reich P. B., Bardgett R. D., et al. 2020. “The Influence of Soil Age on Ecosystem Structure and Function Across Biomes.” Nature Communications 11, no. 1: 4721. PubMed PMC

Dormann, C. F. , Schymanski S. J., Cabral J., et al. 2012. “Correlation and Process in Species Distribution Models: Bridging a Dichotomy.” Journal of Biogeography 39: 2119–2131.

Dubuis, A. , Giovanettina S., Pellissier L., Pottier J., Vittoz P., and Guisan A.. 2013. “Improving the Prediction of Plant Species Distribution and Community Composition by Adding Edaphic to Topo‐Climatic Variables.” Journal of Vegetation Science 24: 593–606.

Dunne, K. A. , and Willmott C. J.. 1996. “Global Distribution of Plant‐Extractable Water Capacity of Soil.” International Journal of Climatology 16: 841–859.

Duursma, D. E. , Gallagher R. V., Roger E., Hughes L., Downey P. O., and Leishman M. R.. 2013. “Next‐Generation Invaders? Hotspots for Naturalised Sleeper Weeds in Australia Under Future Climates.” PLoS One 8: e84222. PubMed PMC

Edwards, M. , and Richardson A. J.. 2004. “Impact of Climate Change on Marine Pelagic Phenology and Trophic Mismatch.” Nature 430: 881–884. PubMed

Eflorasa . 2024. “Electronic Flora of South Australia.” Accessed July 12, 2024. https://ecobits.net.au/eflorasa‐electronic‐flora‐of‐south‐australia/.

Ejaz, M. R. , Jaoua S., Lorestani N., and Shabani F.. 2025. “Global Climate Change and Its Impact on the Distribution and Efficacy of PubMed

Elith, J. , Kearney M., and Phillips S.. 2010. “The Art of Modelling Range‐Shifting Species.” Methods in Ecology and Evolution 1: 330–342.

Elith, J. , and Leathwick J.. 2009. “Species Distribution Models: Ecological Explanation and Prediction Across Space and Time.” Annual Review of Ecology, Evolution, and Systematics 40: 120159.

Figueiredo, F. O. G. , Zuquim G., Tuomisto H., Moulatlet G. M., Balslev H., and Costa F. C.. 2018. “Beyond Climate Control on Species Range: The Importance of Soil Data to Predict Distribution of Amazonian Plant Species.” Journal of Biogeography 45: 190–200.

Fitzpatrick, M. C. , Gove A. D., Sanders N. J., and Dunn R. R.. 2008. “Climate Change, Plant Migration, and Range Collapse in a Global Biodiversity Hotspot: The Banksia (Proteaceae) of Western Australia.” Global Change Biology 14: 1337–1352.

Franklin, J. 2010. Mapping Species Distributions: Spatial Inference and Prediction. Cambridge Cambridge University Press.

Gamalero, E. , Bona E., Todeschini V., and Lingua G.. 2020. “Saline and Arid Soils: Impact on Bacteria, Plants, and Their Interaction.” Biology 9: 116. PubMed PMC

Gbif . 2024. “Occurrence Download. The Global Biodiversity Information Facility.” Accessed June 18, 2024. 10.15468/dl.zp4ffq. DOI

Grundy, M. J. , Rossel R. a. V., Searle R. D., Wilson P. L., Chen C., and Gregory L. J.. 2015. “Soil and Landscape Grid of Australia.” Soil Research 53, no. 8: 835–844.

Guisan, A. , and Zimmermann N. E.. 2000. “Predictive Habitat Distribution Models in Ecology.” Ecological Modelling 135: 147–186.

Hageer, Y. , Esperón‐Rodríguez M., Baumgartner J. B., and Beaumont L. J.. 2017. “Climate, Soil or Both? Which Variables Are Better Predictors of the Distributions of Australian Shrub Species?” PeerJ 5: e3446. PubMed PMC

Hazen, E. L. , Jorgensen S., Rykaczewski R. R., et al. 2013. “Predicted Habitat Shifts of Pacific Top Predators in a Changing Climate.” Nature Climate Change 3: 234–238.

Hijmans, R. 2023. “Raster: Geographic Data Analysis and Modeling.”

Hijmans, R. , Cameron S. E., Parra J. L., Jones P. G., and Jarvis A.. 2004. “The WorldClim Interpolated Global Terrestrial Climate Surfaces.”

Hulshof, C. M. , and Spasojevic M. J.. 2020. “The Edaphic Control of Plant Diversity.” Global Ecology and Biogeography 29: 1634–1650.

Ibra . 2024. “Interim Biogeographic Regionalisation for Australia (IBRA), Version 7 (Regions).” Accessed June 10, 2024. Australian Government Department of Climate Change, Energy, the Environment and Water. https://data.gov.au/data/dataset/interim‐biogeographic‐regionalisation‐for‐australia‐ibra‐version‐7‐regions.

Iverson, L. R. , Prasad A. M., Matthews S. N., and Peters M.. 2008. “Estimating Potential Habitat for 134 Eastern US Tree Species Under Six Climate Scenarios.” Forest Ecology and Management 254: 390–406.

Jarvis, A. M. , and Robertson A.. 1999. “Predicting Population Sizes and Priority Conservation Areas for 10 Endemic Namibian Bird Species.” Biological Conservation 88: 121–131.

Jiménez‐Valverde, A. 2014. “Threshold‐Dependence as a Desirable Attribute for Discrimination Assessment: Implications for the Evaluation of Species Distribution Models.” Biodiversity and Conservation 23: 369–385.

Jin, Y. , and Qian H.. 2022. “V.PhyloMaker2: An Updated and Enlarged R Package That Can Generate Very Large Phylogenies for Vascular Plants.” Plant Diversity 44: 335–339. PubMed PMC

John, R. , Dalling J. W., Harms K. E., et al. 2007. “Soil Nutrients Influence Spatial Distributions of Tropical Tree Species.” Proceedings of the National Academy of Sciences of the United States of America 104: 864–869. PubMed PMC

Karger, D. N. , Conrad O., Böhner J., et al. 2017. “Climatologies at High Resolution for the Earth's Land Surface Areas.” Scientific Data 4: 170122. PubMed PMC

Kearney, M. , and Porter W.. 2009. “Mechanistic Niche Modelling: Combining Physiological and Spatial Data to Predict Species' Ranges.” Ecology Letters 12: 334–350. PubMed

Kearney, M. , Wintle B., and Porter W.. 2010. “Correlative and Mechanistic Models of Species Distribution Provide Congruent Forecasts Under Climate Change.” Conservation Letters 3, no. 3: 203–213.

Keith, D. A. , Akçakaya H. R., Thuiller W., et al. 2008. “Predicting Extinction Risks Under Climate Change: Coupling Stochastic Population Models With Dynamic Bioclimatic Habitat Models.” Biology Letters 4: 560–563. PubMed PMC

Körner, C. 2012. Alpine Treelines: Functional Ecology of the Global High Elevation Tree Limits. Springer.

Kramer‐Schadt, S. , Niedballa J., Pilgrim J. D., et al. 2013. “The Importance of Correcting for Sampling Bias in MaxEnt Species Distribution Models.” Diversity and Distributions 19: 1366–1379.

Kurniawan, S. , Corre M. D., Matson A. L., et al. 2018. “Conversion of Tropical Forests to Smallholder Rubber and Oil Palm Plantations Impacts Nutrient Leaching Losses and Nutrient Retention Efficiency in Highly Weathered Soils.” Biogeosciences 15: 5131–5154.

Laliberté, E. , Norton D. A., and Scott D.. 2013. “Contrasting Effects of Productivity and Disturbance on Plant Functional Diversity at Local and Metacommunity Scale.” Journal of Vegetation Science 24: 834–842.

Lay, G. L. , Engler R., Franc E., and Guisan A.. 2010. “Prospective Sampling Based on Model Ensembles Improves the Detection of Rare Species.” Ecography 33: 1015–1027.

Lobo, J. M. , Jiménez‐Valverde A., and Real R.. 2008. “AUC: A Misleading Measure of the Performance of Predictive Distribution Models.” Global Ecology and Biogeography 17: 145–151.

Lorestani, N. , Hemami M.‐R., Rezvani A., and Ahmadi M.. 2022. “Ecological Niche Models Reveal Divergent Habitat Use of Pallas's Cat in the Eurasian Cold Steppes.” Ecology and Evolution 12: e9624. PubMed PMC

Luoto, M. , Heikkinen R. K., Pöyry J., and Saarinen K.. 2006. “Determinants of the Biogeographical Distribution of Butterflies in Boreal Regions.” Journal of Biogeography 33: 1764–1778.

Martinson, E. , Eddy Z. B., Commerford J., Blevins E., Rolfsmeier S. J., and Mclauchlan K. K.. 2011. “Biogeographic Distributions of Selected North American Grassland Plant Species.” Physical Geography 32, no. 6: 583–602.

Martirosyan, V. , Unc A., Miller G., Doniger T., Wachtel C., and Steinberger Y.. 2016. “Desert Perennial Shrubs Shape the Microbial‐Community Miscellany in Laimosphere and Phyllosphere Space.” Microbial Ecology 72: 659–668. PubMed

Martre, P. , North G. B., Bobich E. G., and Nobel P. S.. 2002. “Root Deployment and Shoot Growth for Two Desert Species in Response to Soil Rockiness.” American Journal of Botany 89: 1933–1939. PubMed

Mcbratney, A. B. , Mendonça Santos M. L., and Minasny B.. 2003. “On Digital Soil Mapping.” Geoderma 117: 3–52.

Mccune, J. L. 2016. “Species Distribution Models Predict Rare Species Occurrences Despite Significant Effects of Landscape Context.” Journal of Applied Ecology 53: 1871–1879.

Mcpherson, J. M. , and Jetz W.. 2007. “Effects of Species' Ecology on the Accuracy of Distribution Models.” Ecography 30: 135–151.

Merow, C. , Smith M. J., Edwards T. C. Jr., et al. 2014. “What Do We Gain From Simplicity Versus Complexity in Species Distribution Models?” Ecography 37: 1267–1281.

Mf, D. S. 2009. “Flora of Tasmania Online.” Tasmanian Herbarium, Tasmanian Museum & Art Gallery: Hobart. Accessed July 13, 2024. https://flora.tmag.tas.gov.au/.

Mod, H. K. , Scherrer D., Luoto M., and Guisan A.. 2016. “What We Use Is Not What We Know: Environmental Predictors in Plant Distribution Models.” Journal of Vegetation Science 27: 1308–1322.

Muhling, B. A. , Brill R., Lamkin J. T., et al. 2017. “Projections of Future Habitat Use by Atlantic Bluefin Tuna: Mechanistic vs. Correlative Distribution Models.” ICES Journal of Marine Science 74: 698–716.

Naimi, B. 2015. “Usdm: Uncertainty Analysis for Species Distribution Models.” 1, 1–12.

Nielsen, U. N. , and Ball B. A.. 2015. “Impacts of Altered Precipitation Regimes on Soil Communities and Biogeochemistry in Arid and Semi‐Arid Ecosystems.” Global Change Biology 21: 1407–1421. PubMed

Olson, D. M. , Dinerstein E., Wikramanayake E. D., et al. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth: A New Global Map of Terrestrial Ecoregions Provides an Innovative Tool for Conserving Biodiversity.” Bioscience 51: 933–938.

Paoli, G. D. , Curran L. M., and Slik J. W. F.. 2008. “Soil Nutrients Affect Spatial Patterns of Aboveground Biomass and Emergent Tree Density in Southwestern Borneo.” Oecologia 155: 287–299. PubMed

Pebesma, E. 2018. “Simple Features for R: Standardized Support for Spatial Vector Data.” R Journal 10, no. 1: 439–446.

Posada, J. M. , and Schuur E. A.. 2011. “Relationships Among Precipitation Regime, Nutrient Availability, and Carbon Turnover in Tropical Rain Forests.” Oecologia 165, no. 3: 783–795. PubMed

Powo . 2017. “Plants of the World Online.” The Royal Botanic Gardens, Kew. Accessed July 10, 2024. https://powo.science.kew.org/.

Ramirez‐Cabral, N. Y. Z. , Kumar L., and Shabani F.. 2017. “Global Risk Levels for Corn Rusts (Puccinia Sorghi and Puccinia Polysora) Under Climate Change Projections.” Journal of Phytopathology 165: 563–574.

Ramos, R. S. , Kumar L., Shabani F., and Picanço M. C.. 2019. “Risk of Spread of Tomato Yellow Leaf Curl Virus (TYLCV) in Tomato Crops Under Various Climate Change Scenarios.” Agricultural Systems 173: 524–535.

Randin, C. F. , Engler R., Normand S., et al. 2009. “Climate Change and Plant Distribution: Local Models Predict High‐Elevation Persistence.” Global Change Biology 15: 1557–1569.

Reddell, P. , Bowen G. D., and Robson A. D.. 1985. “The Effects of Soil Temperature on Plant Growth, Nodulation and Nitrogen Fixation in PubMed

Renner, I. W. , and Warton D. I.. 2013. “Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology.” Biometrics 69: 274–281. PubMed

Robertson, M. P. , Peter C. I., Villet M. H., and Ripley B. S.. 2003. “Comparing Models for Predicting Species' Potential Distributions: A Case Study Using Correlative and Mechanistic Predictive Modelling Techniques.” Ecological Modelling 164: 153–167.

Searle, R. , Malone B., Wilford J., et al. 2022. Tern Digital Soil Mapping Raster Covariate Stacks CSIRO.

Sequeira, A. , Mellin C., Rowat D., Meekan M. G., and Bradshaw C. J. A.. 2012. “Ocean‐Scale Prediction of Whale Shark Distribution.” Diversity and Distributions 18: 504–518.

Shabani, F. , Ahmadi M., Peters K., et al. 2019. “Climate‐Driven Shifts in the Distribution of Koala Browse Species From the Last Interglacial to the Near Future.” Ecography 42, no. 9: 1587–1599.

Shabani, F. , Kumar L., and Ahmadi M.. 2016. “A Comparison of Absolute Performance of Different Correlative and Mechanistic Species Distribution Models in an Independent Area.” Ecology and Evolution 6: 5973–5986. PubMed PMC

Shabani, F. , Kumar L., and Ahmadi M.. 2017. “Climate Modelling Shows Increased Risk to PubMed PMC

Soberón, J. 2007. “Grinnellian and Eltonian Niches and Geographic Distributions of Species.” Ecology Letters 10: 1115–1123. PubMed

Stauffer, D. 2002. Linking Populations and Habitats: Where Have We Been? Where Are We Going? Predicting Species Occurrences.

Stolar, J. , and Nielsen S. E.. 2015. “Accounting for Spatially Biased Sampling Effort in Presence‐Only Species Distribution Modelling.” Diversity and Distributions 21: 595–608.

Svenning, J. C. , Normand S., and Kageyama M.. 2008. “Glacial Refugia of Temperate Trees in Europe: Insights From Species Distribution Modelling.” Journal of Ecology 96: 1117–1127.

Thuiller, W. , Lafourcade B., Engler R., and Araújo M. B.. 2009. “BIOMOD–a Platform for Ensemble Forecasting of Species Distributions.” Ecography 32: 369–373.

Valavi, R. , Guillera‐Arroita G., Lahoz‐Monfort J. J., and Elith J.. 2022. “Predictive Performance of Presence‐Only Species Distribution Models: A Benchmark Study With Reproducible Code.” Ecological Monographs 92, no. 1: e01486.

Varela, S. , Anderson R. P., García‐Valdés R., and Fernández‐González F.. 2014. “Environmental Filters Reduce the Effects of Sampling Bias and Improve Predictions of Ecological Niche Models.” Ecography 37: 1084–1091.

Veech, J. A. 2021. Habitat Ecology and Analysis. Oxford University Press.

Velazco, S. J. E. , Galvao F., Villalobos F., and De Marco Junior P.. 2017. “Using Worldwide Edaphic Data to Model Plant Species Niches: An Assessment at a Continental Extent.” PLoS One 12: e0186025. PubMed PMC

Vicflora . 2024. “Flora of Victoria.” Accessed July 12, 2024. https://vicflora.rbg.vic.gov.au/.

Wang, H. , Liu D., Munroe D., Cao K., and Biermann C.. 2016. “Study on Selecting Sensitive Environmental Variables in Modelling Species Spatial Distribution.” Annals of GIS 22: 57–69.

Wauchope‐Drumm, M. , Bentley J., Beaumont L. J., Baumgartner J. B., and Nipperess D. A.. 2020. “Using a Species Distribution Model to Guide NSW Surveys of the Long‐Footed Potoroo (

Wetlandinfo . 2017. “Department of Environment, Science and Innovation, Queensland.” Accessed July 15, 2024. https://wetlandinfo.des.qld.gov.au/wetlands/.

Williams, J. N. , Seo C., Thorne J., et al. 2009. “Using Species Distribution Models to Predict New Occurrences for Rare Plants.” Diversity and Distributions 15: 565–576.

Williams, S. , and Hero J.. 2001. “Multiple Determinants of Australian Tropical Frog Biodiversity.” Biological Conservation 98, no. 1: 1–10.

Zizka, A. , Silvestro D., Andermann T., et al. 2019. “CoordinateCleaner: Standardized Cleaning of Occurrence Records From Biological Collection Databases.” Methods in Ecology and Evolution 10, no. 5: 744–751.

Zuquim, G. , Tuomisto H., Jones M. M., et al. 2014. “Predicting Environmental Gradients With Fern Species Composition in Brazilian Amazonia.” Journal of Vegetation Science 25: 1195–1207.

See more in PubMed

Dryad
10.5061/dryad.9cnp5hqwn