Seeing the forest through the trees: Applications of species distribution models across an Australian biodiversity hotspot for threatened rainforest species of Fontainea

[1]  Rebecca L. Selden,et al.  Recommendations for quantifying and reducing uncertainty in climate projections of species distributions , 2022, Global change biology.

[2]  M. Betts,et al.  Factors influencing transferability in species distribution models , 2022, Ecography.

[3]  J. Elith,et al.  Modelling species presence-only data with random forests , 2020, bioRxiv.

[4]  J. Elith,et al.  Predictive performance of presence‐only species distribution models: a benchmark study with reproducible code , 2021, Ecological Monographs.

[5]  R. Ramesh,et al.  Predicting climate change impacts on potential worldwide distribution of fall armyworm based on CMIP6 projections , 2021, Journal of Pest Science.

[6]  B. Enquist,et al.  A Test of Species Distribution Model Transferability Across Environmental and Geographic Space for 108 Western North American Tree Species , 2021, Frontiers in Ecology and Evolution.

[7]  Garrett M. Street,et al.  Embracing Ensemble Species Distribution Models to Inform At-Risk Species Status Assessments , 2021, Journal of Fish and Wildlife Management.

[8]  R. Moss,et al.  Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6 , 2020, Earth System Dynamics.

[9]  Hunter J. Howell,et al.  Habitat suitability models for the imperiled wood turtle (Glyptemys insculpta) raise concerns for the species’ persistence under future climate change , 2020 .

[10]  Francis Gilbert,et al.  A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants , 2020, Ecol. Informatics.

[11]  Jane Elith,et al.  Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models , 2020 .

[12]  Hilppa Gregow,et al.  GCMeval – An interactive tool for evaluation and selection of climate model ensembles , 2020 .

[13]  L. Beaumont,et al.  Identifying climate refugia for 30 Australian rainforest plant species, from the last glacial maximum to 2070 , 2019, Landscape Ecology.

[14]  M. White,et al.  The effect of sample size on the accuracy of species distribution models: considering both presences and pseudo‐absences or background sites , 2019 .

[15]  G. Conroy,et al.  A multidisciplinary approach to inform assisted migration of the restricted rainforest tree, Fontainea rostrata , 2019, PloS one.

[16]  C. Kormos,et al.  IUCN World Heritage Outlook 2: A conservation assessment of all natural World Heritage sites , 2017 .

[17]  A. Accad,et al.  The relationship between climate change and the endangered rainforest shrub Triunia robusta (Proteaceae) endemic to southeast Queensland, Australia , 2017, Scientific Reports.

[18]  Dianne Brown,et al.  Fontainea dude thinks he's a lady - recovery of the Coastal Fontainea and investigation into temporal monoecy , 2016 .

[19]  W. Mcdonald,et al.  Modelling the spatial distribution of beta diversity in Australian subtropical rainforest , 2016 .

[20]  G. Conroy,et al.  Population genetic analysis of a medicinally significant Australian rainforest tree, Fontainea picrosperma C.T. White (Euphorbiaceae): biogeographic patterns and implications for species domestication and plantation establishment , 2016, BMC Plant Biology.

[21]  Antoine Guisan,et al.  Overcoming limitations of modelling rare species by using ensembles of small models , 2015 .

[22]  J. VanDerWal,et al.  Patterns of rain forest plant endemism in subtropical Australia relate to stable mesic refugia and species dispersal limitations , 2014 .

[23]  F. Kershaw,et al.  Informing conservation units: barriers to dispersal for the yellow anaconda , 2013 .

[24]  T. Parkes,et al.  Big Scrub: A cleared landscape in transition back to forest? , 2012 .

[25]  Gretchen G. Moisen,et al.  Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada , 2012 .

[26]  F. Jiguet,et al.  Selecting pseudo‐absences for species distribution models: how, where and how many? , 2012 .

[27]  W. Boyd,et al.  Promoting Gondwana: presentation of the Gondwana Rainforests of Australia World Heritage Area in tourist brochures , 2011 .

[28]  C. Margules,et al.  Forests of East Australia: The 35th Biodiversity Hotspot , 2011 .

[29]  J. Franklin Moving beyond static species distribution models in support of conservation biogeography , 2010 .

[30]  M. Schwartz,et al.  Using species distribution models to predict new occurrences for rare plants , 2009 .

[31]  J. Evans,et al.  Gradient modeling of conifer species using random forests , 2009, Landscape Ecology.

[32]  E J Milner-Gulland,et al.  Quantification of Extinction Risk: IUCN's System for Classifying Threatened Species , 2008, Conservation biology : the journal of the Society for Conservation Biology.

[33]  A. Pitman,et al.  Why is the choice of future climate scenarios for species distribution modelling important? , 2008, Ecology letters.

[34]  R. Real,et al.  AUC: a misleading measure of the performance of predictive distribution models , 2008 .

[35]  A. Hirzel,et al.  Evaluating the ability of habitat suitability models to predict species presences , 2006 .

[36]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[37]  T. Dawson,et al.  Selecting thresholds of occurrence in the prediction of species distributions , 2005 .

[38]  A. Guisan,et al.  An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data , 2004 .

[39]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[40]  Brian J. McGill,et al.  The priority of prediction in ecological understanding , 2017 .

[41]  R. Pearson Species’ Distribution Modeling for Conservation Educators and Practitioners , 2010 .

[42]  R. Henry,et al.  Conservation genetics of an endangered rainforest tree (Fontainea oraria – Euphorbiaceae) and implications for closely related species , 2004, Conservation Genetics.

[43]  N. Burbidge The phytogeography of the Australian region. , 1960 .