Bridging the research-implementation gap in IUCN Red List assessments.

[1]  D. Silvestro,et al.  IUCNN - deep learning approaches to approximate species’ extinction risk , 2021, bioRxiv.

[2]  A. Tulloch,et al.  Determining ranges of poorly known mammals as a tool for global conservation assessment , 2021 .

[3]  S. Turvey,et al.  Global patterns of extinction risk and conservation needs for Rodentia and Eulipotyphla , 2021, Diversity and Distributions.

[4]  Jason T. Bried,et al.  Calculating population reductions of invertebrate species for IUCN Red List assessments , 2021 .

[5]  L. Santini,et al.  The interface between Macroecology and Conservation: existing links and untapped opportunities , 2021, Frontiers of Biogeography.

[6]  Friederike C. Bolam,et al.  A robust goal is needed for species in the Post‐2020 Global Biodiversity Framework , 2020, Conservation Letters.

[7]  D. Silvestro,et al.  iucn_sim: A new program to simulate future extinctions based on IUCN threat status , 2019, bioRxiv.

[8]  P. Reich,et al.  Extinction risk and threats to plants and fungi , 2020, PLANTS, PEOPLE, PLANET.

[9]  Aaron C. Greenville,et al.  Simultaneously operating threats cannot predict extinction risk , 2020, Conservation Letters.

[10]  Melinda L. Moir,et al.  Incorporating coextinction in threat assessments and policy will rapidly improve the accuracy of threatened species lists , 2020 .

[11]  D. Silvestro,et al.  Automated conservation assessment of the orchid family with deep learning , 2020, Conservation biology : the journal of the Society for Conservation Biology.

[12]  P. Cardoso,et al.  Methods for the assessment and conservation of threatened animal parasites , 2020 .

[13]  K. Tockner,et al.  Combined effects of life‐history traits and human impact on extinction risk of freshwater megafauna , 2020, Conservation biology : the journal of the Society for Conservation Biology.

[14]  Friederike C. Bolam,et al.  Caution Needed When Predicting Species Threat Status for Conservation Prioritization on a Global Scale , 2020, Frontiers in Plant Science.

[15]  Jeremy P. Bird,et al.  Generation lengths of the world's birds and their implications for extinction risk , 2020, Conservation Biology.

[16]  Steven P. Bachman,et al.  Rapid Least Concern: towards automating Red List assessments , 2020, Biodiversity data journal.

[17]  E. Milner‐Gulland,et al.  A framework for evaluating the impact of the IUCN Red List of threatened species , 2019, Conservation biology : the journal of the Society for Conservation Biology.

[18]  G. Zizka,et al.  Biogeography and conservation status of the pineapple family (Bromeliaceae) , 2019, Diversity and Distributions.

[19]  Nicholas K. Dulvy,et al.  Estimating IUCN Red List population reduction: JARA—A decision‐support tool applied to pelagic sharks , 2019, Conservation Letters.

[20]  Clinton N. Jenkins,et al.  Measuring Terrestrial Area of Habitat (AOH) and Its Utility for the IUCN Red List. , 2019, Trends in ecology & evolution.

[21]  P. Cardoso,et al.  A review of the relation between species traits and extinction risk , 2019, Biological Conservation.

[22]  Steven P. Bachman,et al.  Progress, challenges and opportunities for Red Listing , 2019, Biological Conservation.

[23]  Calvin K. F. Lee,et al.  Redlistr: tools for the IUCN Red Lists of ecosystems and threatened species in R , 2019, Ecography.

[24]  E. Revilla,et al.  Range area matters, and so does spatial configuration: predicting conservation status in vertebrates , 2019, Ecography.

[25]  M. Huijbregts,et al.  Applying habitat and population‐density models to land‐cover time series to inform IUCN Red List assessments , 2019, Conservation biology : the journal of the Society for Conservation Biology.

[26]  A. Davis,et al.  Least concern to endangered: Applying climate change projections profoundly influences the extinction risk assessment for wild Arabica coffee , 2019, Global change biology.

[27]  Nico Eisenhauer,et al.  Recognizing the quiet extinction of invertebrates , 2019, Nature Communications.

[28]  Jack Sullivan,et al.  Predicting plant conservation priorities on a global scale , 2018, Proceedings of the National Academy of Sciences.

[29]  Hugh P Possingham,et al.  Changes in human footprint drive changes in species extinction risk , 2018, Nature Communications.

[30]  E. Milner‐Gulland,et al.  Quantifying species recovery and conservation success to develop an IUCN Green List of Species , 2018, Conservation biology : the journal of the Society for Conservation Biology.

[31]  L. Santini,et al.  TetraDENSITY: A database of population density estimates in terrestrial vertebrates , 2018 .

[32]  D. Keith,et al.  Scaling range sizes to threats for robust predictions of risks to biodiversity , 2018, Conservation biology : the journal of the Society for Conservation Biology.

[33]  Lucie M. Bland,et al.  Global correlates of extinction risk in freshwater crayfish , 2017 .

[34]  Tariq Stévart,et al.  ConR: An R package to assist large‐scale multispecies preliminary conservation assessments using distribution data , 2017, Ecology and evolution.

[35]  Pedro Cardoso,et al.  red - an R package to facilitate species red list assessments according to the IUCN criteria , 2017, Biodiversity data journal.

[36]  C. Thompson,et al.  Inferring extinctions II: A practical, iterative model based on records and surveys , 2017 .

[37]  A. Solow,et al.  Inferring extinctions I: A structured method using information on threats , 2017 .

[38]  Carsten F. Dormann,et al.  Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure , 2017 .

[39]  Ben Collen,et al.  Toward reassessing data‐deficient species , 2017, Conservation biology : the journal of the Society for Conservation Biology.

[40]  Steven P. Bachman,et al.  Using coarse‐scale species distribution data to predict extinction risk in plants , 2017 .

[41]  M. Huijbregts,et al.  Setting population targets for mammals using body mass as a predictor of population persistence , 2017, Conservation biology : the journal of the Society for Conservation Biology.

[42]  James E. M. Watson,et al.  Species/' traits influenced their response to recent climate change , 2017 .

[43]  J. Jeschke,et al.  Threat-dependent traits of endangered frogs , 2017 .

[44]  M. Böhm,et al.  Overcoming data deficiency in reptiles , 2016 .

[45]  S. Pimm,et al.  Incorporating explicit geospatial data shows more species at risk of extinction than the current Red List , 2016, Science Advances.

[46]  S. Butchart,et al.  Toward quantification of the impact of 21st‐century deforestation on the extinction risk of terrestrial vertebrates , 2016, Conservation biology : the journal of the Society for Conservation Biology.

[47]  Joshua S Madin,et al.  Predicting IUCN Extinction Risk Categories for the World's Data Deficient Groupers (Teleostei: Epinephelidae) , 2016 .

[48]  David A Keith,et al.  Assessing the Cost of Global Biodiversity and Conservation Knowledge , 2016, PloS one.

[49]  L. Joppa,et al.  Impact of alternative metrics on estimates of extent of occurrence for extinction risk assessment , 2016, Conservation biology : the journal of the Society for Conservation Biology.

[50]  B. Collen,et al.  Correlates of extinction risk in squamate reptiles: the relative importance of biology, geography, threat and range size , 2016 .

[51]  Steven P. Bachman,et al.  Clarifying misconceptions of extinction risk assessment with the IUCN Red List , 2016, Biology Letters.

[52]  Verde Arregoitia,et al.  Biases, gaps, and opportunities in mammalian extinction risk research , 2016 .

[53]  Anni Arponen,et al.  Projecting Global Biodiversity Indicators under Future Development Scenarios , 2016 .

[54]  G. Mace,et al.  Historical drivers of extinction risk: using past evidence to direct future monitoring , 2015, Proceedings of the Royal Society B: Biological Sciences.

[55]  Marco Celesti,et al.  Green Plants in the Red: A Baseline Global Assessment for the IUCN Sampled Red List Index for Plants , 2015, PloS one.

[56]  Brett R. Scheffers,et al.  Assessing species' vulnerability to climate change , 2015 .

[57]  C. Orme,et al.  Predicting the conservation status of data‐deficient species , 2015, Conservation biology : the journal of the Society for Conservation Biology.

[58]  Emilio Padoa-Schioppa,et al.  Habitat availability for amphibians and extinction threat: a global analysis , 2015 .

[59]  D. Bickford,et al.  Amphibians over the edge: silent extinction risk of Data Deficient species , 2014 .

[60]  Zoltan Szantoi,et al.  Drivers of extinction risk in African mammals: the interplay of distribution state, human pressure, conservation response and species biology , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[61]  L. Boitani,et al.  Update or Outdate: Long‐Term Viability of the IUCN Red List , 2014 .

[62]  Ana D Davidson,et al.  Threat to the point: improving the value of comparative extinction risk analysis for conservation action , 2014, Global change biology.

[63]  L. Santini,et al.  Generation length for mammals , 2013 .

[64]  H. Resit Akçakaya,et al.  Identifying the World's Most Climate Change Vulnerable Species: A Systematic Trait-Based Assessment of all Birds, Amphibians and Corals , 2013, PloS one.

[65]  E. Revilla,et al.  Which intrinsic traits predict vulnerability to extinction depends on the actual threatening processes , 2013 .

[66]  R. Peterman,et al.  Reliability of Indicators of Decline in Abundance , 2012, Conservation biology : the journal of the Society for Conservation Biology.

[67]  E. Meijaard,et al.  Are comparative studies of extinction risk useful for conservation? , 2012, Trends in ecology & evolution.

[68]  Jeremy P. Bird,et al.  Integrating spatially explicit habitat projections into extinction risk assessments: a reassessment of Amazonian avifauna incorporating projected deforestation , 2012 .

[69]  Ben Scott,et al.  Supporting Red List threat assessments with GeoCAT: geospatial conservation assessment tool , 2011, ZooKeys.

[70]  P. Cardoso,et al.  Adapting the IUCN Red List criteria for invertebrates , 2011 .

[71]  Bruce B. Collette,et al.  The Impact of Conservation on the Status of the World’s Vertebrates , 2010, Science.

[72]  N. Pettorelli,et al.  Phylogenetic, spatial and environmental components of extinction risk in carnivores , 2010 .

[73]  E. Wilson,et al.  The Barometer of Life , 2010, Science.

[74]  Jeremy P. Bird,et al.  Data Deficient birds on the IUCN Red List: What don’t we know and why does it matter? , 2010 .

[75]  James H Brown,et al.  Multiple ecological pathways to extinction in mammals , 2009, Proceedings of the National Academy of Sciences.

[76]  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.

[77]  Kate E. Jones,et al.  The predictability of extinction: biological and external correlates of decline in mammals , 2008, Proceedings of the Royal Society B: Biological Sciences.

[78]  Philippe Mayaux,et al.  Using remote sensing to inform conservation status assessment: Estimates of recent deforestation rates on New Britain and the impacts upon endemic birds , 2008 .

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

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

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

[82]  Lian Pin Koh,et al.  Species Coextinctions and the Biodiversity Crisis , 2004, Science.

[83]  G. Mace,et al.  Making Consistent IUCN Classifications under Uncertainty , 2000 .