Standards for distribution models in biodiversity assessments

Biodiversity assessments use a variety of data and models. We propose best-practice standards for studies in these assessments. Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.

[1]  Michael Obersteiner,et al.  The methodological assessment report on scenarios and models of biodiversity and ecosystem services , 2016 .

[2]  J. Nichols,et al.  Advances and applications of occupancy models , 2014 .

[3]  Raimundo Real,et al.  Spatial, environmental and human influences on the distribution of otter (Lutra lutra) in the Spanish provinces , 2001 .

[4]  J. Metcalf,et al.  Integrating multiple lines of evidence into historical biogeography hypothesis testing: a Bison bison case study , 2014, Proceedings of the Royal Society B: Biological Sciences.

[5]  F. Jiguet,et al.  How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models , 2010 .

[6]  Jerald B. Johnson,et al.  Model selection in ecology and evolution. , 2004, Trends in ecology & evolution.

[7]  J. Lennon,et al.  Incorporating uncertainty in predictive species distribution modelling , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[8]  B. McGill,et al.  Testing the predictive performance of distribution models , 2013 .

[9]  R. A. Garcia,et al.  Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates , 2011, Global Change Biology.

[10]  S. Lavorel,et al.  Biodiversity conservation: Uncertainty in predictions of extinction risk , 2004, Nature.

[11]  Miguel B. Araújo,et al.  Life on a tropical planet: niche conservatism and the global diversity gradient , 2013 .

[12]  Nicholas W. Synes,et al.  Choice of predictor variables as a source of uncertainty in continental‐scale species distribution modelling under climate change , 2011 .

[13]  Patrick A. Zollner,et al.  Improving the forecast for biodiversity under climate change , 2016, Science.

[14]  Vincent Bretagnolle,et al.  Spatial leave‐one‐out cross‐validation for variable selection in the presence of spatial autocorrelation , 2014 .

[15]  Luis V. García,et al.  Controlling the false discovery rate in ecological research. , 2003 .

[16]  Anne Larigauderie,et al.  The Biodiversity and Ecosystem Services Science-Policy Interface , 2011, Science.

[17]  S. Lavorel,et al.  Effects of restricting environmental range of data to project current and future species distributions , 2004 .

[18]  Kristin Shrader-Frechette,et al.  Method in Ecology: Strategies for Conservation , 1993 .

[19]  Damaris Zurell,et al.  Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .

[20]  M. Maslin,et al.  Defining the Anthropocene , 2015, Nature.

[21]  Michael J. Watts,et al.  Adapted conservation measures are required to save the Iberian lynx in a changing climate , 2013 .

[22]  John-Arvid Grytnes,et al.  Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe , 2013, Global change biology.

[23]  H. Possingham,et al.  Spatial conservation prioritization: Quantitative methods and computational tools , 2009 .

[24]  M. White,et al.  Measuring and comparing the accuracy of species distribution models with presence–absence data , 2011 .

[25]  S. Carpenter,et al.  Planetary boundaries: Guiding human development on a changing planet , 2015, Science.

[26]  M. Araújo,et al.  How Does Climate Change Affect Biodiversity? , 2006, Science.

[27]  Jarrett E. K. Byrnes,et al.  A global synthesis reveals biodiversity loss as a major driver of ecosystem change , 2012, Nature.

[28]  A. Gimona,et al.  Opening the climate envelope reveals no macroscale associations with climate in European birds , 2008, Proceedings of the National Academy of Sciences.

[29]  C. Marshall,et al.  Has the Earth’s sixth mass extinction already arrived? , 2011, Nature.

[30]  M. Araújo,et al.  Biotic and abiotic variables show little redundancy in explaining tree species distributions , 2010 .

[31]  A. Fielding,et al.  Testing the Generality of Bird‐Habitat Models , 1995 .

[32]  Emily Anthes,et al.  Hospital checklists are meant to save lives — so why do they often fail? , 2015, Nature.

[33]  M. Araújo,et al.  Five (or so) challenges for species distribution modelling , 2006 .

[34]  Michael Hoffmann,et al.  The value of the IUCN Red List for conservation. , 2006, Trends in ecology & evolution.

[35]  K. Bollmann,et al.  Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change , 2013 .

[36]  O. Phillips,et al.  Extinction risk from climate change , 2004, Nature.

[37]  Gerald Calnen,et al.  A Strategy for the Future , 2010 .

[38]  H. Resit Akçakaya,et al.  Use and misuse of the IUCN Red List Criteria in projecting climate change impacts on biodiversity , 2006 .

[39]  Robert P. Anderson,et al.  Bioclimatic variables derived from remote sensing: assessment and application for species distribution modelling , 2014 .

[40]  S. Long,et al.  2013 reviews of Global Change Biology , 2013, Global change biology.

[41]  H. D. Cooper,et al.  Scenarios for Global Biodiversity in the 21st Century , 2010, Science.

[42]  Wilfried Thuiller,et al.  Reopening the climate envelope reveals macroscale associations with climate in European birds , 2009, Proceedings of the National Academy of Sciences.

[43]  Jane Elith,et al.  What do we gain from simplicity versus complexity in species distribution models , 2014 .

[44]  M. Araújo,et al.  Uses and misuses of bioclimatic envelope modeling. , 2012, Ecology.

[45]  Julian D. Olden,et al.  Assessing transferability of ecological models: an underappreciated aspect of statistical validation , 2012 .

[46]  J. Elith,et al.  Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models , 2009 .

[47]  M. Boyce,et al.  Evaluating resource selection functions , 2002 .

[48]  Barbara R Stein,et al.  Mammals of the World: MaNIS as an example of data integration in a distributed network environment , 2004 .

[49]  A. Márcia Barbosa,et al.  Discrimination capacity in species distribution models depends on the representativeness of the environmental domain , 2013 .

[50]  Antoine Guisan,et al.  Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe , 2013 .

[51]  Carsten F. Dormann,et al.  Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents , 2012 .

[52]  Ingolf Kühn,et al.  Inferring model‐based probability of occurrence from preferentially sampled data with uncertain absences using expert knowledge , 2014 .

[53]  Miguel B. Araújo,et al.  Quaternary climate changes explain diversity among reptiles and amphibians , 2008 .

[54]  Carsten F Dormann,et al.  An evidence assessment tool for ecosystem services and conservation studies. , 2015, Ecological applications : a publication of the Ecological Society of America.

[55]  P. Leadley,et al.  Impacts of climate change on the future of biodiversity. , 2012, Ecology letters.

[56]  A. Peterson,et al.  Evidence of climatic niche shift during biological invasion. , 2007, Ecology letters.

[57]  Robert A. Boria,et al.  Spatial filtering to reduce sampling bias can improve the performance of ecological niche models , 2014 .

[58]  A. Townsend Peterson,et al.  Rethinking receiver operating characteristic analysis applications in ecological niche modeling , 2008 .

[59]  James Haile,et al.  Species-specific responses of Late Quaternary megafauna to climate and humans , 2011, Nature.

[60]  Jin-Kyung Hong,et al.  Environmental Variables Shaping the Ecological Niche of Thaumarchaeota in Soil: Direct and Indirect Causal Effects , 2015, PloS one.

[61]  M. Araújo,et al.  How can a knowledge of the past help to conserve the future? Biodiversity conservation and the relevance of long-term ecological studies , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[62]  John Bell,et al.  A review of methods for the assessment of prediction errors in conservation presence/absence models , 1997, Environmental Conservation.

[63]  R. O’Hara,et al.  Plateau: a new method for ecologically plausible climate envelopes for species distribution modelling , 2016 .

[64]  M. Araújo,et al.  Climate warming and the decline of amphibians and reptiles in Europe , 2006 .

[65]  M. Araújo,et al.  Consequences of spatial autocorrelation for niche‐based models , 2006 .

[66]  C. Dormann Promising the future? Global change projections of species distributions , 2007 .

[67]  A. Márcia Barbosa,et al.  Favourable areas for co‐occurrence of parapatric species: niche conservatism and niche divergence in Iberian tree frogs and midwife toads , 2017 .

[68]  Sylvain Arlot,et al.  A survey of cross-validation procedures for model selection , 2009, 0907.4728.

[69]  M. Austin,et al.  Improving species distribution models for climate change studies: variable selection and scale , 2011 .

[70]  Larissa L Bailey,et al.  Experimental investigation of false positive errors in auditory species occurrence surveys. , 2012, Ecological applications : a publication of the Ecological Society of America.

[71]  D. Sax,et al.  Climatic niche shifts between species' native and naturalized ranges raise concern for ecological forecasts during invasions and climate change , 2014 .

[72]  C. A. Howell,et al.  Niches, models, and climate change: Assessing the assumptions and uncertainties , 2009, Proceedings of the National Academy of Sciences.

[73]  J. Franklin,et al.  Modeling plant species distributions under future climates: how fine scale do climate projections need to be? , 2013, Global change biology.

[74]  A Townsend Peterson,et al.  Ecological Niches in Sequential Generations of Eastern North American Monarch Butterflies (Lepidoptera: Danaidae): The Ecology of Migration and Likely Climate Change Implications , 2007, Environmental entomology.

[75]  M. Araújo,et al.  Choice of threshold alters projections of species range shifts under climate change , 2011 .

[76]  J. Lamarque,et al.  Global Biodiversity: Indicators of Recent Declines , 2010, Science.

[77]  J. Elith,et al.  Sensitivity of predictive species distribution models to change in grain size , 2007 .

[78]  Georgia Destouni,et al.  Comment on “Planetary boundaries: Guiding human development on a changing planet” , 2015, Science.

[79]  T. Rangel,et al.  Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change , 2009 .

[80]  M. Araújo,et al.  The importance of biotic interactions for modelling species distributions under climate change , 2007 .

[81]  C. Mora,et al.  How Many Species Are There on Earth and in the Ocean? , 2011, PLoS biology.

[82]  B. Young,et al.  IUCN SSC guidelines for assessing species' vulnerability to climate change , 2016 .

[83]  John P. A. Ioannidis,et al.  A manifesto for reproducible science , 2017, Nature Human Behaviour.

[84]  Bradford A. Hawkins,et al.  Relative influences of current and historical factors on mammal and bird diversity patterns in deglaciated North America , 2003 .

[85]  Douglas G. Altman,et al.  University of Southern Denmark Systematic review adherence to methodological or reporting quality , 2017 .

[86]  M. Austin Species distribution models and ecological theory: A critical assessment and some possible new approaches , 2007 .

[87]  Joaquín Hortal,et al.  Climate Change, Humans, and the Extinction of the Woolly Mammoth , 2008, PLoS biology.

[88]  Kristy Deiner,et al.  Perspectives on the Open Standards for the Practice of Conservation , 2012 .

[89]  Timothy M. Perez,et al.  Most ‘global’ reviews of species’ responses to climate change are not truly global , 2017 .

[90]  R. A. Garcia,et al.  Multiple Dimensions of Climate Change and Their Implications for Biodiversity , 2014, Science.

[91]  Michael R Kearney,et al.  Realized niche shift during a global biological invasion , 2014, Proceedings of the National Academy of Sciences.

[92]  Robert P. Anderson,et al.  Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models , 2014 .

[93]  Jakub Stoklosa,et al.  A climate of uncertainty: accounting for error in climate variables for species distribution models , 2015 .

[94]  T. Dawson,et al.  Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? , 2003 .

[95]  Jennifer A. Miller,et al.  Mapping Species Distributions: Spatial Inference and Prediction , 2010 .

[96]  Robert P. Anderson,et al.  A framework for using niche models to estimate impacts of climate change on species distributions , 2013, Annals of the New York Academy of Sciences.

[97]  R. Hijmans,et al.  Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. , 2012, Ecology.

[98]  Ruth Garside,et al.  Sustainability: Map the evidence , 2015, Nature.

[99]  Dan L Warren,et al.  Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. , 2011, Ecological applications : a publication of the Ecological Society of America.

[100]  Stewart J. Cohen,et al.  Climate Change 2014: Impacts,Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change , 2014 .

[101]  Drew W. Purves,et al.  Chasing a moving target: projecting climate change‐induced shifts in non‐equilibrial tree species distributions , 2013 .

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

[103]  M. Araújo,et al.  Reducing uncertainty in projections of extinction risk from climate change , 2005 .

[104]  Miguel B. Araújo,et al.  Global patterns in the shape of species geographical ranges reveal range determinants , 2012 .

[105]  D. Nogues‐Bravo,et al.  Predicting the past distribution of species climatic niches. , 2009 .

[106]  G. McGough The checklist manifesto: how to get things right Atul Gawande The checklist manifesto: how to get things right Metropolitan Books £12.99 224pp 9780805091748 0805091742 , 2010 .

[107]  Jane Elith,et al.  Error and uncertainty in habitat models , 2006 .

[108]  S. Lek,et al.  Uncertainty in ensemble forecasting of species distribution , 2010 .

[109]  W. Sutherland,et al.  The effect of scientific evidence on conservation practitioners’ management decisions , 2014, Conservation biology : the journal of the Society for Conservation Biology.

[110]  J. Franklin,et al.  Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors , 2009 .

[111]  A. Gawande,et al.  The Checklist Manifesto: How to Get Things Right , 2011 .

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

[113]  A. Townsend Peterson,et al.  Novel methods improve prediction of species' distributions from occurrence data , 2006 .

[114]  Jane Elith,et al.  POC plots: calibrating species distribution models with presence-only data. , 2010, Ecology.

[115]  Mathieu Marmion,et al.  Does the interpolation accuracy of species distribution models come at the expense of transferability , 2012 .

[116]  Alberto Jiménez-Valverde,et al.  Delimiting the geographical background in species distribution modelling , 2012 .

[117]  Hugh P. Possingham,et al.  Factors influencing the use of decision support tools in the development and design of conservation policy , 2017 .

[118]  J. Elith,et al.  Species Distribution Models: Ecological Explanation and Prediction Across Space and Time , 2009 .

[119]  Galit Shmueli,et al.  To Explain or To Predict? , 2010, 1101.0891.

[120]  Eve McDonald-Madden,et al.  Predicting species distributions for conservation decisions , 2013, Ecology letters.

[121]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[122]  Matthew J. Smith,et al.  The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models , 2013, PloS one.

[123]  A. Peterson,et al.  The crucial role of the accessible area in ecological niche modeling and species distribution modeling , 2011 .

[124]  J. Lobo,et al.  Is current climatic equilibrium a guarantee for the transferability of distribution model predictions? A case study of the spotted hyena , 2009 .

[125]  R. Levins The strategy of model building in population biology , 1966 .

[126]  M. Araújo,et al.  The effects of model and data complexity on predictions from species distributions models , 2016 .

[127]  M. Austin Spatial prediction of species distribution: an interface between ecological theory and statistical modelling , 2002 .

[128]  Steven J. Phillips,et al.  Aligning Conservation Priorities Across Taxa in Madagascar with High-Resolution Planning Tools , 2008, Science.

[129]  Sanjeev Arora,et al.  Computational Complexity: A Modern Approach , 2009 .

[130]  M. Araújo,et al.  Uncertainty associated with survey design in Species Distribution Models , 2014 .

[131]  M. Araújo,et al.  An evaluation of methods for modelling species distributions , 2004 .

[132]  Thomas Kitzberger,et al.  Southern-most Nothofagus trees enduring ice ages: genetic evidence and ecological niche retrodiction reveal high latitude (54°S) glacial refugia. , 2010 .

[133]  Steven J. Phillips,et al.  Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. , 2009, Ecological applications : a publication of the Ecological Society of America.

[134]  Mike P. Austin,et al.  Physiological responses and statistical models of the environmental niche: a comparative study of two co‐occurring Eucalyptus species , 2009 .

[135]  Volker Grimm,et al.  Ecological models supporting environmental decision making: a strategy for the future. , 2010, Trends in ecology & evolution.

[136]  M. Zappa,et al.  Climate change and plant distribution: local models predict high‐elevation persistence , 2009 .

[137]  H. Possingham,et al.  IMPROVING PRECISION AND REDUCING BIAS IN BIOLOGICAL SURVEYS: ESTIMATING FALSE‐NEGATIVE ERROR RATES , 2003 .

[138]  Mark New,et al.  Ensemble forecasting of species distributions. , 2007, Trends in ecology & evolution.

[139]  A. Peterson,et al.  Biodiversity informatics: managing and applying primary biodiversity data. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[140]  A. H. Murphy,et al.  Diagnostic verification of probability forecasts , 1992 .

[141]  Antoine Guisan,et al.  Predicting current and future biological invasions: both native and invaded ranges matter , 2008, Biology Letters.

[142]  Robert P. Anderson,et al.  Harnessing the world's biodiversity data: promise and peril in ecological niche modeling of species distributions , 2012, Annals of the New York Academy of Sciences.

[143]  P. Legendre,et al.  Partialling out the spatial component of ecological variation , 1992 .

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

[145]  W. Berry,et al.  A Surgical Safety Checklist to Reduce Morbidity and Mortality in a Global Population , 2009, The New England journal of medicine.

[146]  N. Pettorelli,et al.  Essential Biodiversity Variables , 2013, Science.

[147]  C O M M E N T A,et al.  Can remote sensing of land cover improve species distribution modelling ? , 2008 .

[148]  Steven J. Phillips,et al.  The art of modelling range‐shifting species , 2010 .

[149]  David R. B. Stockwell,et al.  Forecasting the Effects of Global Warming on Biodiversity , 2007 .

[150]  S. Ferrier,et al.  An evaluation of alternative algorithms for fitting species distribution models using logistic regression , 2000 .

[151]  R. Loyola,et al.  Defining spatial conservation priorities in the face of land-use and climate change , 2013 .

[152]  T. Dawson,et al.  Model‐based uncertainty in species range prediction , 2006 .

[153]  A. Rozenfeld,et al.  The geographic scaling of biotic interactions , 2013 .

[154]  Robert P. Anderson,et al.  Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent , 2011 .

[155]  Bruce L. Webber,et al.  Here be dragons: a tool for quantifying novelty due to covariate range and correlation change when projecting species distribution models , 2014 .

[156]  M. Araújo,et al.  Validation of species–climate impact models under climate change , 2005 .

[157]  Wilfried Thuiller,et al.  Climate change threatens European conservation areas , 2011, Ecology letters.

[158]  G. Mace,et al.  Beyond Predictions: Biodiversity Conservation in a Changing Climate , 2011, Science.

[159]  Antoine Guisan,et al.  Are niche-based species distribution models transferable in space? , 2006 .

[160]  Heather M. Kharouba,et al.  A synthesis of transplant experiments and ecological niche models suggests that range limits are often niche limits. , 2016, Ecology letters.