{"author":"Nunes","year":2015,"acronym":"ADEPD","method_name":"prioritization metric","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Creation of new prioritization metric (ADEPD) that After Downlisting a species gives the Expected Phylogenetic Diversity at some future time","DOI/link":"http://dx.doi.org/10.1098/rstb.2014.0004","ID":"Nunes2015","example_taxon_standard":"birds","example_area_standard":"global","scalability":"high"}
{"author":"Cattarino","year":2015,"acronym":"APA","method_name":"action prioritization algorithm","scale":"regional","implementation_standard":"R script","target":"species","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":1,"free_text_description":"An algorithm that can prioritize multiple alternative actions within the same site, within a spatially-explicit framework that accounts for connectivity between priority sites","DOI/link":"https://doi.org/10.1371/journal.pone.0128027","ID":"Cattarino2015","example_taxon_standard":"bony fish/shark","example_area_standard":"Australia","scalability":"intermediate"}
{"author":"Fattorini","year":2006,"acronym":"BCC","method_name":"biodiversity conservation concern (BCC)","scale":"regional","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"proposal of a new index (BCC) that combines the conservation status of each species belonging to a given species assemblage with the total species richness","DOI/link":"https://doi.org/10.1111/j.1469-1795.2005.00009.x","ID":"Fattorini2006","example_taxon_standard":"arthropods","example_area_standard":"Greece","scalability":"high"}
{"author":"Tanalgo","year":2018,"acronym":"BCVI","method_name":"Local Ecological Cave values","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Bat Cave Vulnerability Index in prioritising bat caves for conservation based in index through equations","DOI/link":"https://doi.org/10.1016/j.ecolind.2017.11.064","ID":"Tanalgo2018","example_taxon_standard":"mammals","example_area_standard":"Philippines","scalability":"high"}
{"author":"Shi","year":2005,"acronym":"BioCPS","method_name":"Conservation Priority Setting","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A relative ranking method for identifying priority conservation areas that integrates both biological (endemism) and social aspects ( the habitat’s status, human population pressure, human efforts to protect habitat)","DOI/link":"https://doi.org/10.1111/j.1523-1739.2005.00225.x","ID":"Shi2005","example_taxon_standard":"vascular plants, amphibians, mammals, birds, squamates, turtles/tortoises","example_area_standard":"global","scalability":"high"}
{"author":"Magris","year":2018,"acronym":"BioMarCons","method_name":"Marxan","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":1,"free_text_description":"Link prioritization methods with population models to explore the impact of integrating both representation and connectivity into conservation planning for species persistence","DOI/link":"https://doi.org/10.1111/conl.12439","ID":"Magris2018","example_taxon_standard":"bony fish/shark","example_area_standard":"other","scalability":"intermediate"}
{"author":"Ramesh","year":2017,"acronym":"BRT","method_name":"Boosted Regression Tree","scale":"regional","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Test the accuracy of the geographic range sizes used by the IUCN for endemic birds threat assessmen using independently reviewed data from eBird within a species distribution modeling framework","DOI/link":"https://doi.org/10.1016/J.BIOCON.2017.03.019","ID":"Ramesh2017","example_taxon_standard":"birds","example_area_standard":"India","scalability":"high"}
{"author":"Mishler","year":2014,"acronym":"CANAPE","method_name":"categorical analysis of neo- and paleoendemism","scale":"global","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A combination of phylogenetic endemism and phylogenetic diversity measures to identify centres of neo and paleo endemism","DOI/link":"https://doi.org/10.1038/ncomms5473","ID":"Mishler2014","example_taxon_standard":"vascular plants","example_area_standard":"Australia","scalability":"high"}
{"author":"Sharafi","year":2012,"acronym":"CAR","method_name":"Comprehensiveness, Adequacy, Representativeness","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Model to examine efficiency of existing protected areas and define gaps in current reserve systems","DOI/link":"https://doi.org/10.1016/j.ecolind.2011.11.023","ID":"Sharafi2012","example_taxon_standard":"none","example_area_standard":"Australia","scalability":"intermediate"}
{"author":"Ceia-Hasse","year":2017,"acronym":"CarnRoads","method_name":"remote sensing","scale":"global","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":1,"free_text_description":"Global assessment of the exposure of terrestrial mammalian carnivores to roads using an integrated modelling framework","DOI/link":"https://doi.org/10.1111/geb.12564","ID":"Ceia-Hasse2017","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"Leathwick","year":2010,"acronym":"CAZ","method_name":"Core Area Zonation","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A zonation method for spatial conservation prioritization at community level","DOI/link":"https://doi.org/10.1016/j.biocon.2010.01.012","ID":"Leathwick2010","example_taxon_standard":"bony fish/shark, other","example_area_standard":"New Zealand","scalability":"high"}
{"author":"Valerio","year":2016,"acronym":"CBI","method_name":"composite biodiversity indicator, MaxEnt","scale":"regional","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of a biodiversity indicator, based on Shannon diversity index and built from distribution maps of protected species","DOI/link":"https://doi.org/10.1016/j.ecolind.2016.07.043","ID":"Valerio2016","example_taxon_standard":"birds","example_area_standard":"Italy","scalability":"intermediate"}
{"author":"Hämmerle","year":2018,"acronym":"CCND","method_name":"Assessment risk","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":1,"includes_simulation":1,"free_text_description":"New method for jointly assessing risk combining climate envelope modelling and the evaluation of exceedance of empirical critical loads for eutrophication through N deposition.","DOI/link":"https://doi.org/10.1016/j.biocon.2018.09.014","ID":"Hammerle2018","example_taxon_standard":"vascular plants","example_area_standard":"Austria","scalability":"intermediate"}
{"author":"Pereira","year":2017,"acronym":"CentLandGraph","method_name":"Landscape connectivity","scale":"regional","implementation_standard":"R script","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of individual ranking (single-node) and group prioritization (multi-node) methods to identify key patches in the habitat network","DOI/link":"https://doi.org/10.1111/2041-210X.12783","ID":"Pereira2017","example_taxon_standard":"birds","example_area_standard":"Spain","scalability":"intermediate"}
{"author":"Martínez-Tilleria","year":2017,"acronym":"ChileTerEco","method_name":"Land use/cover assessment","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Ecosystem framework that combines land use, functional traits of dominant plant species, and climatic factors for the classification of terrestrial ecosystems to assess ecosystem conservation status","DOI/link":"https://doi.org/10.1007/s10531-017-1393-x","ID":"Martinez-Tilleria2017","example_taxon_standard":"vascular plants","example_area_standard":"Chile","scalability":"high"}
{"author":"McRae","year":2008,"acronym":"Circuitscape","method_name":"circuit‐theoretic connectivity","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Introduction of a new class of ecological connectivity models based in electrical circuit theory","DOI/link":"https://doi.org/10.1890/07-1861.1","ID":"McRae2008","example_taxon_standard":"none","example_area_standard":"none","scalability":"high"}
{"author":"Albert","year":2017,"acronym":"ConNect","method_name":"Landscape connectivity","scale":"regional","implementation_standard":"R script","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":1,"free_text_description":"A method to integrate uncertainty in climate and land-use change projections with network-connectivity for conservation prioritization","DOI/link":"https://doi.org/10.1111/cobi.12943","ID":"Albert2017","example_taxon_standard":"mammals, birds, amphibians","example_area_standard":"Canada","scalability":"high"}
{"author":"Dauby","year":2017,"acronym":"ConR","method_name":"ConR","scale":"global","implementation_standard":"R package","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Using species occurrence information together with assumptions on species range to approximate IUCN assessments based on criterion B","DOI/link":"https://doi.org/10.1002/ece3.3704","ID":"Dauby2017","example_taxon_standard":"vascular plants","example_area_standard":"other","scalability":"high"}
{"author":"Hofman","year":2018,"acronym":"ConsevNet","method_name":"Landscape corridors","scale":"regional","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Combining least-cost and graph-theory to identify priorities for connectivity conservation","DOI/link":"https://doi.org/10.1016/j.landurbplan.2018.05.013","ID":"Hofman2018","example_taxon_standard":"mammals","example_area_standard":"Belize","scalability":"high"}
{"author":"Ciarleglio","year":2009,"acronym":"ConsNet","method_name":"ConsNet","scale":"global","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Program to define areas for potential conservation management through biodiversity surrogates","DOI/link":"https://doi.org/10.1111/j.1600-0587.2008.05721.x","ID":"Ciarleglio2009","example_taxon_standard":"mammals","example_area_standard":"Mexico","scalability":"high"}
{"author":"Melbourne-Thomas","year":2011,"acronym":"CORSET","method_name":"Coral Reef Scenario Evaluation Tool","scale":"regional","implementation_standard":"python","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Model to investigate potential future of coral reefs and associated human systems under alternative management scenarios","DOI/link":"https://doi.org/10.1890/09-1564.1","ID":"Melbourne-Thomas2011","example_taxon_standard":"corals, bony fish/shark, other","example_area_standard":"marine","scalability":"intermediate"}
{"author":"Mazor","year":2014,"acronym":"costMPA","method_name":"Marxan","scale":"continental","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A framework to include cost when planning large‐scale Marine Protected Area (MPA) networks that span multiple countries","DOI/link":"https://doi.org/10.1890/13-1249.1","ID":"Mazor2014","example_taxon_standard":"amphibians, mammals, birds, squamates, turtles/tortoises","example_area_standard":"other","scalability":"high"}
{"author":"Lin","year":2014,"acronym":"CPPA","method_name":"LUPOlib, Marxan","scale":"regional","implementation_standard":"stand-alone commandline","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A two-stage conservation planning approach using the Land-Use Pattern Optimization-library following by the systematic conservation planning tool, Marxan.","DOI/link":"https://doi.org/10.1016/j.envsoft.2014.06.009","ID":"Lin2014","example_taxon_standard":"birds","example_area_standard":"Taiwan","scalability":"high"}
{"author":"Bonfim","year":2019,"acronym":"CrazENM","method_name":"Ecological niche modeling","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":1,"free_text_description":"Ecological niche modeling of a large body bird (Crax blumenbachii) in Atlantic Rainforest","DOI/link":"https://doi.org/10.1016/j.gecco.2018.e00426","ID":"Bonfim2019","example_taxon_standard":"birds","example_area_standard":"Brazil","scalability":"low"}
{"author":"Saura","year":2009,"acronym":"CS22","method_name":"Conefor Sensinode","scale":"regional","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Calculate the connectivity of habitat patches based n graph theory","DOI/link":"https://doi.org/10.1016/j.envsoft.2008.05.005","ID":"Saura2009","example_taxon_standard":"NA","example_area_standard":"none","scalability":"low"}
{"author":"Simaika","year":2009,"acronym":"DBI","method_name":"Dragonfly Biotic Index","scale":"regional","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Index to maximising representation of globally Red Listed species","DOI/link":"https://doi.org/10.1016/j.biocon.2008.11.012","ID":"Simaika2009","example_taxon_standard":"arthropods","example_area_standard":"South Africa","scalability":"high"}
{"author":"Diniz-Filho","year":2012,"acronym":"DipSCP","method_name":"Simulated anneling algorithm","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of Systematic Conservation Planning (SCP) framework through population genetic diversity (microsatellites)","DOI/link":"https://doi.org/10.1007/s10592-012-0356-8","ID":"Diniz-Filho2012","example_taxon_standard":"vascular plants","example_area_standard":"Brazil","scalability":"intermediate"}
{"author":"Chernomor","year":2015,"acronym":"divCCP","method_name":"integer linear programming","scale":"global","implementation_standard":"PDA","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure","DOI/link":"https://doi.org/10.1111/2041-210X.12299","ID":"Chernomor2015","example_taxon_standard":"vascular plants, corals, other, bony fish/shark, arthropods","example_area_standard":"South Africa, marine","scalability":"high"}
{"author":"Marsh","year":2018,"acronym":"downscale","method_name":"Downscaling Species Occupancy","scale":"global","implementation_standard":"R package","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"R package to aid in the production of consistent species and ecosystem Red List assessments","DOI/link":"https://doi.org/10.18637/jss.v086.c03","ID":"Marsh2018","example_taxon_standard":"other","example_area_standard":"United Kingdom","scalability":"high"}
{"author":"Clark","year":2014,"acronym":"EBSA identification method","method_name":"Ecologically or Biologically Significant Areas","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Defining ecologically or biologically significant areas in open-ocean and deep-sea habitats","DOI/link":"https://doi.org/10.1016/j.ocecoaman.2014.01.016","ID":"Clark2014","example_taxon_standard":"NA","example_area_standard":"marine","scalability":"intermediate"}
{"author":"Roberts","year":2003,"acronym":"ECMR","method_name":"series of criteria to avaluate marine areas","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Development of a criteria that allow objective assessment of the biological value of candidate marine reserves (just theoretical approach)","DOI/link":"https://doi.org/10.1890/1051-0761(2003)013[0199:ECFECS]2.0.CO;2","ID":"Roberts2003","example_taxon_standard":"other","example_area_standard":"none","scalability":"high"}
{"author":"d'Acampora","year":2018,"acronym":"EcoCon","method_name":"probabilistic connection models","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"A method to combine various connectivity metrics in a concise measurement","DOI/link":"https://doi.org/10.1016/j.ecolmodel.2018.06.005","ID":"dAcampora2018","example_taxon_standard":"mammals","example_area_standard":"Brazil","scalability":"intermediate"}
{"author":"Klein","year":2009,"acronym":"EcoEvoSCP","method_name":"Marxan","scale":"regional","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Development of a method to identify priorities along waterways that allows for trade-offs to be made between connectivity and acquisition costs","DOI/link":"https://doi.org/10.1890/07-1684.1","ID":"Klein2009","example_taxon_standard":"vascular plants, birds","example_area_standard":"Australia","scalability":"low"}
{"author":"Foltete","year":2017,"acronym":"EcoFunc","method_name":"Landscape modularity","scale":"regional","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use modularity graph metrics to validate landscape compartments for species demography or genetic population","DOI/link":"https://doi.org/10.1007/s10980-016-0445-z","ID":"Foltete2017","example_taxon_standard":"mammals","example_area_standard":"France","scalability":"intermediate"}
{"author":"McGarigal","year":2018,"acronym":"ecoImpact","method_name":"Index of ecological Impact","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":1,"includes_simulation":0,"free_text_description":"Model for ecosystem based assessment of ecological integrity","DOI/link":"https://doi.org/10.1007/s10980-018-0653-9","ID":"McGarigal2018","example_taxon_standard":"NA","example_area_standard":"USA","scalability":"high"}
{"author":"Oikonomou","year":2018,"acronym":"ECOMORPH","method_name":"Ecomorphological originality","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Identifying ecomorphologically distinct species of fish based on morphological traits to identify conservation hotspots","DOI/link":"https://doi.org/10.1007/s10641-018-0759-6","ID":"Oikonomou2018","example_taxon_standard":"bony fish/shark","example_area_standard":"Greece","scalability":"low"}
{"author":"Mirzaei","year":2017,"acronym":"EcoNiche","method_name":"Ecological niche modeling","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of the spatial pattern of birds' diversity to determine hotspots","DOI/link":"https://doi.org/10.22034/gjesm.2017.03.02.002","ID":"Mirzaei2017","example_taxon_standard":"birds","example_area_standard":"Iran","scalability":"high"}
{"author":"Faith","year":2015,"acronym":"EDf","method_name":"ED-based functional diversity measure (EDf)","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Construction of an EDf framework that combines functional trait space with environmental/habitat variables to conservation prioritization","DOI/link":"https://doi.org/10.1007/s11258-015-0454-z","ID":"Faith2015","example_taxon_standard":"birds","example_area_standard":"global","scalability":"high"}
{"author":"Isaac","year":2007,"acronym":"EDGE","method_name":"Evolutionarily distinct and globally endangered","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Creation of EDGE index","DOI/link":"https://doi.org/10.1371/journal.pone.0000296","ID":"Isaac2007","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"Gumbs","year":2018,"acronym":"EDGEmis","method_name":"Evolutionarily distinct and globally endangered correcting for missing species","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"EDGE prioritisations rely on adequate phylogenetic and extinction risk data to generate meaningful priorities for conservation","DOI/link":"https://doi.org/10.1371/journal.pone.0194680","ID":"Gumbs2018","example_taxon_standard":"amphibians, birds, mammals, squamates, turtles/tortoises","example_area_standard":"global","scalability":"high"}
{"author":"Redding","year":2015,"acronym":"EDGETraits","method_name":"Evolutionarily distinct and globally endangered","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Test if the EDGE metric captures total evolutionary history and traits","DOI/link":"https://doi.org/10.1371/journal.pone.0141435","ID":"Redding2015","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"van Zonneveld","year":2014,"acronym":"EEM","method_name":"environmental envelope modelling","scale":"continental","implementation_standard":"other","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A method on the basis of cultural consensus theory to formalize expert model evaluations","DOI/link":"https://doi.org/10.1111/AVSC.12081","ID":"vanZonneveld2014","example_taxon_standard":"vascular plants","example_area_standard":"other","scalability":"high"}
{"author":"Zhang","year":2015,"acronym":"ERCPF","method_name":"extinction risk index","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Assessment of extinction risks and conservation priorities for 64 endemic fish species under a hydropower construction","DOI/link":"https://doi.org/10.1007/s10641-014-0257-4","ID":"Zhang2015","example_taxon_standard":"bony fish/shark","example_area_standard":"China","scalability":"low"}
{"author":"Yuan","year":2017,"acronym":"ESC","method_name":"ecosystem services coefficient","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Based on land use pattern and benefit transfer method, value of ecosystem services was estimated","DOI/link":"https://doi.org/10.1007/s11356-017-8795-x","ID":"Yuan2017","example_taxon_standard":"none","example_area_standard":"Taiwan","scalability":"high"}
{"author":"Canadas","year":2014,"acronym":"EVPR","method_name":"Endemic vascular plant richness","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Defining diversity micro and nano-hotspots of species diversity within larger hotspots","DOI/link":"https://doi.org/10.1016/j.biocon.2013.12.007","ID":"Canadas2014","example_taxon_standard":"vascular plants","example_area_standard":"other","scalability":"high"}
{"author":"Jones","year":2006,"acronym":"ExtPar","method_name":"CHAID","scale":"global","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use Decision Tree approach to assess which combinations of species traits most closely define the grouping of species into IUCN categories","DOI/link":"https://doi.org/10.1007/s10531-005-4316-1","ID":"Jones2006","example_taxon_standard":"birds","example_area_standard":"global","scalability":"high"}
{"author":"Darrah","year":2017,"acronym":"ExtPlants","method_name":"random forest","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Machine learning model on biological and environmental variables to identify correlates of extinction risk in plants","DOI/link":"https://doi.org/10.1111/ddi.12532","ID":"Darrah2017","example_taxon_standard":"vascular plants","example_area_standard":"global","scalability":"high"}
{"author":"Luiz","year":2016,"acronym":"ExtRisk","method_name":"Species trades and extinction risk","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of an ordinal analytical approach to model relationships between species‐level traits and extinction risk categories in groupers","DOI/link":"https://doi.org/10.1111/conl.12230","ID":"Luiz2016","example_taxon_standard":"bony fish/shark","example_area_standard":"marine","scalability":"high"}
{"author":"Pierik","year":2016,"acronym":"FFI","method_name":"Fuzzy Functionality Index","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Index to inspect complex and non-linear landscape dynamics","DOI/link":"https://doi.org/10.1016/j.ecolind.2016.03.032","ID":"Pierik2016","example_taxon_standard":"amphibians, squamates, turtles/tortoises","example_area_standard":"Italy","scalability":"intermediate"}
{"author":"Maire","year":2013,"acronym":"FloodCons","method_name":"synthetic index of a multifaceted fish assemblage diversity","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"New method to select priority areas based on four aspects of their diversity: taxonomic (i.e. according to species classification), functional (i.e. relationship between species and ecosystem processes), natural heritage (i.e. species threat level), and socio-economic (i.e. species interest to anglers and fishermen) diversity","DOI/link":"https://doi.org/10.1016/J.ECOLIND.2013.06.009","ID":"Maire2013","example_taxon_standard":"bony fish/shark","example_area_standard":"France","scalability":"low"}
{"author":"Tracey","year":2013,"acronym":"FMM","method_name":"finite mixture modeling","scale":"regional","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of finite mixture modeling approach to analyze data for movement of three bobcats in relation to urban areas","DOI/link":"https://doi.org/10.1890/12-0687.1","ID":"Tracey2013","example_taxon_standard":"mammals","example_area_standard":"USA","scalability":"low"}
{"author":"McGarigal","year":1995,"acronym":"FRAGSTAT","method_name":"spatial pattern analysis","scale":"global","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"FRAGSTATS is a spatial pattern analysis program for quantifying the structure (i.e., composition and configuration) of landscapes.","DOI/link":"none","ID":"McGarigal1995","example_taxon_standard":"none","example_area_standard":"none","scalability":"high"}
{"author":"Pimiento","year":2020,"acronym":"FUSE","method_name":"Functionally Unique Specialized and Endangered species","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"An index combining the species functional uniqueness, and functional specialization with species threat","DOI/link":"https://doi.org/10.1126/sciadv.aay7650","ID":"Pimiento2020","example_taxon_standard":"mammals, bony fish/shark","example_area_standard":"global","scalability":"high"}
{"author":"Dedman","year":2017,"acronym":"Gbm.auto","method_name":"statistica modelling","scale":"continental","implementation_standard":"R package","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Package to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables","DOI/link":"https://doi.org/10.1371/journal.pone.0188955","ID":"Dedman2017","example_taxon_standard":"bony fish/shark","example_area_standard":"marine","scalability":"intermediate"}
{"author":"Ottewell","year":2016,"acronym":"GenAnaly","method_name":"conservation genetic analytical methods","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Network for assessing the genetic health of populations and the prioritization of population-level management actions based on the measurement of three simple metrics: genetic differentiation, genetic diversity and inbreeding","DOI/link":"https://doi.org/10.1111/ddi.12387","ID":"Ottewell2016","example_taxon_standard":"vascular plants","example_area_standard":"Australia","scalability":"low"}
{"author":"Bachman","year":2011,"acronym":"GeoCAT","method_name":"GeoCAT","scale":"global","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A tool to automate EOO and AOO estimation for IUCN assessments.","DOI/link":"https://doi.org/10.3897/zookeys.150.2109","ID":"Bachman2011","example_taxon_standard":"NA","example_area_standard":"unspecified","scalability":"high"}
{"author":"Wanghe","year":2020,"acronym":"GMT","method_name":"Gravity Model Toolbox","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"ArcGIS toolbox to assess urban connectivity and planning urban green space","DOI/link":"https://doi.org/10.1016/j.gecco.2020.e01012","ID":"Wanghe2020","example_taxon_standard":"NA","example_area_standard":"China","scalability":"intermediate"}
{"author":"Cianfrani","year":2018,"acronym":"GOVCC","method_name":"vulnerability index","scale":"global","implementation_standard":"stand-alone commandline","target":"species","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":1,"free_text_description":"Combine the species' intrinsic sensitivity to climate change (climatic niche specialization and marginality) together with components of extrinsic exposure (changes in range extent, fragmentation, coverage of protected areas, and human footprint) to develop an integrated vulnerability index.","DOI/link":"https://doi.org/10.1016/j.biocon.2018.02.031","ID":"Cianfrani2018","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"McPherson","year":2014,"acronym":"GSCD","method_name":"MaxEnt","scale":"regional","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of species distribution modeling to generate biodiversity density surfaces to identify areas of relative high biodiversity density; assess possible conservation areas; and compare modeled areas of conservation interest with those proposed by the Government of Guyana","DOI/link":"https://doi.org/10.1007/s10531-014-0696-4","ID":"McPherson2014","example_taxon_standard":"arthropods, amphibians, birds, mammals, squamates, turtles/tortoises, vascular plants, other","example_area_standard":"Guyana","scalability":"high"}
{"author":"Liu","year":2017,"acronym":"habConnec","method_name":"least-cost model","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Evaluation of road effects on the ecological status and landscape connectivity for Asian elephants","DOI/link":"10.1016/J.JNC.2017.05.001","ID":"Liu2017","example_taxon_standard":"mammals","example_area_standard":"China","scalability":"intermediate"}
{"author":"Zhang","year":2017,"acronym":"HabSuit","method_name":"Habitat suitability index","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Qualitative and quantitative relationships between waterbird populations and key habitat indicators","DOI/link":"https://doi.org/10.3846/16486897.2017.1316982","ID":"Zhang2017","example_taxon_standard":"birds","example_area_standard":"China","scalability":"intermediate"}
{"author":"Steel","year":2007,"acronym":"HEDGE","method_name":"heightened evolutionary distinctiveness and globally endangered","scale":"global","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Using phylogenies and extinction risk to quantify how much each species is likely to contribute to future biodiversity, as measured by its expected contribution to phylogenetic diversity","DOI/link":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2684137/","ID":"Steel2007","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"Gunson","year":2012,"acronym":"HSI","method_name":"habitat suitability index","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Development of a GIS modeling tool that predicts high-risk road mortality locations for selected wetland-forest herpetofauna","DOI/link":"https://www.semanticscholar.org/paper/A-tool-to-prioritize-high-risk-road-mortality-for-Gunson-Ireland/a468048a9ee03fb1bf75db471eb71a7944fa5f36","ID":"Gunson2012","example_taxon_standard":"amphibians,  turtles/tortoises","example_area_standard":"Canada","scalability":"high"}
{"author":"Schlenk","year":2011,"acronym":"HypersalGene","method_name":"osmoregulatory response element (ORE)","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":1,"includes_simulation":0,"free_text_description":"Use of gene expression to assess impact of salinity on fishes","DOI/link":"https://doi.org/10.1016/j.aquatox.2011.06.023","ID":"Schlenk2011","example_taxon_standard":"bony fish/shark","example_area_standard":"USA","scalability":"low"}
{"author":"Herrando","year":2010,"acronym":"ICUTS","method_name":"Index of Cumulative Threat Status","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Index to construct maps of conservation value over large geographical areas based on extinction risk of prevailing species","DOI/link":"https://doi.org/10.1007/s10531-009-9741-0","ID":"Herrando2010","example_taxon_standard":"birds","example_area_standard":"Spain","scalability":"high"}
{"author":"Jensen","year":2016,"acronym":"I-HEDGE","method_name":"iteratively calculated, version of HEDGE (heightened evolutionary distinctiveness and globally endangered)","scale":"regional","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Development of an iterative calculation of the heightened evolutionary distinctiveness and globally endangered metric (I-HEDGE) that produces the optimal ranked list for conservation prioritization","DOI/link":"https://doi.org/10.7717/peerj.2350","ID":"Jensen2016","example_taxon_standard":"turtles/tortoises","example_area_standard":"Ecuador","scalability":"intermediate"}
{"author":"Pascual-Hortal","year":2006,"acronym":"IIC","method_name":"Integral Index of Connectivity","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Identification of landscape elements critical for habitat conservation","DOI/link":"https://doi.org/10.1007/s10980-006-0013-z","ID":"Pascual-Hortal2006","example_taxon_standard":"NA","example_area_standard":"none","scalability":"intermediate"}
{"author":"Koyanagi","year":2013,"acronym":"INSPAN","method_name":"indicator species analysis","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Extraction of characteristic species for different management types","DOI/link":"http://doi.org/10.1111/j.1654-109X.2012.01204.x","ID":"Koyanagi2013","example_taxon_standard":"vascular plants","example_area_standard":"Japan","scalability":"low"}
{"author":"Terrado","year":2016,"acronym":"InVest","method_name":"modified habitat quality module of InVEST","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"The model provides a spatially explicit representation of habitat quality that correlates with biodiversity at the river basin scale.","DOI/link":"https://doi.org/10.1016/j.scitotenv.2015.03.064","ID":"Terrado2016","example_taxon_standard":"NA","example_area_standard":"other","scalability":"low"}
{"author":"Hammoud","year":2019,"acronym":"iTUPA","method_name":"Topograpfic-Unit Parsimony Analysis","scale":"continental","implementation_standard":"R","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Tool to visually explore endemism data","DOI/link":"https://doi.org/10.1093/bioinformatics/btz487","ID":"Hammoud2019","example_taxon_standard":"arthropods","example_area_standard":"Brazil","scalability":"high"}
{"author":"Zizka","year":2020,"acronym":"IUC-NN","method_name":"IUC-NN","scale":"global","implementation_standard":"python","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"A neural network method, to approximate IUCN Red List assessments of Data Deficient or Not Evaluated species","DOI/link":"https://doi.org/10.1111/cobi.13616","ID":"Zizka2020","example_taxon_standard":"vascular plants","example_area_standard":"global","scalability":"high"}
{"author":"Simpkins","year":2018,"acronym":"LandCon","method_name":"Euclidean distance; least-cost paths (LCP) length and cost; and circuit theory’s resistance distance","scale":"regional","implementation_standard":"R script","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Evaluation of the performance of four commonly used connectivity metrics over a variety of simulated landscapes","DOI/link":"https://doi.org/10.1016/j.ecolmodel.2017.11.001","ID":"Simpkins2018","example_taxon_standard":"none","example_area_standard":"none","scalability":"intermediate"}
{"author":"Kim","year":2007,"acronym":"LCALEA","method_name":"landscape character assessment and landscape ecological analysis.","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"DOI/link":"https://doi.org/10.1016/j.landusepol.2005.12.001","ID":"Kim2007","example_taxon_standard":"none","example_area_standard":"South Korea","scalability":"intermediate"}
{"author":"Yu","year":2015,"acronym":"LCBC","method_name":"least-cost model","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"A method to identify core habitats and generate a cost surface to identify both the permeability of the landscape matrix and the quality of core habitats and then use of a least-cost model between pairs of core habitats","DOI/link":"https://doi.org/10.1002/clen.201200448","ID":"Yu2015","example_taxon_standard":"none","example_area_standard":"China","scalability":"intermediate"}
{"author":"Veron","year":2016,"acronym":"LCEH","method_name":"Phylogenetic diversity, evolutionary distinctiveness","scale":"continental","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of the phylogenetic diversity and evolutionary distinctiveness to identify areas where evolutionary history is highly threatened and range-restricted","DOI/link":"https://doi.org/10.1186/s12898-016-0099-3","ID":"Veron2016","example_taxon_standard":"mammals, amphibians, squamates","example_area_standard":"Spain, France, Monaco, Italy, Slovenia, Croatia, Bosnia and Herzegovina, Montenegro, Albania, Greece, Turkey, Syria, Lebanon, Israel, Egypt, Libya, Tunisia, Algeria, Morocco,Malta,Cyprus","scalability":"high"}
{"author":"Long","year":2018,"acronym":"LEFT","method_name":"Local Ecological Footprinting Tool","scale":"regional","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"A tool to compare the relative ecological value across sites, based on different metrics of habitat intactness, biodiversity and extinction risk of the present species","DOI/link":"https://doi.org/10.1111/2041-210X.12924","ID":"Long2018","example_taxon_standard":"vascular plants, amphibians, squamates, birds, mammals","example_area_standard":"Costa Rica","scalability":"intermediate"}
{"author":"Fuller","year":2006,"acronym":"LQGraph","method_name":"Landscape Quality Graph","scale":"global","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Optimizing connectivity of conservation area network","DOI/link":"https://doi.org/10.1016/j.envsoft.2006.01.005","ID":"Fuller2006","example_taxon_standard":"NA","example_area_standard":"India","scalability":"high"}
{"author":"Ribeiro","year":2017,"acronym":"LSCORRIDORS","method_name":"LandScape Corridors","scale":"continental","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":1,"includes_simulation":1,"free_text_description":"Identification of protected areas, as corridor simulation considers species movement and landscape connectivity","DOI/link":"https://doi.org/10.1111/2041-210X.12750","ID":"Ribeiro2017","example_taxon_standard":"NA","example_area_standard":"none","scalability":"high"}
{"author":"MacLeod","year":2011,"acronym":"MacKinnon","method_name":"MacKinnon list technique","scale":"regional","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of the MacKinnon list to provide species abundance indices","DOI/link":"https://doi.org/10.1016/j.biocon.2010.12.008","ID":"MacLeod2011","example_taxon_standard":"birds","example_area_standard":"Bolivia","scalability":"intermediate"}
{"author":"Carrara","year":2017,"acronym":"MADIS","method_name":"Richness and diversity","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Several indexes for mammal distribution considering richness, endemism, and threats.","DOI/link":"https://doi.org/10.1016/j.actao.2016.11.001","ID":"Carrara2017","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"high"}
{"author":"Fourcade","year":2014,"acronym":"MapSpDist","method_name":"MAXENT","scale":"global","implementation_standard":"other","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Comparison of the performance of five methods of bias correction for species distribution","DOI/link":"https://doi.org/10.1371/journal.pone.0097122","ID":"Fourcade2014","example_taxon_standard":"amphibians, turtles/tortoises","example_area_standard":"Canada, USA, Mexico","scalability":"high"}
{"author":"Leslie","year":2003,"acronym":"MarNet","method_name":"siting algorithms","scale":"regional","implementation_standard":"other","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of siting algorithms to identify potential networks of marine reserves that comprehensively represent target habitat types","DOI/link":"https://doi.org/10.1890/1051-0761(2003)013[0185:USAITD]2.0.CO;2","ID":"Leslie2003","example_taxon_standard":"none","example_area_standard":"USA","scalability":"high"}
{"author":"Ball","year":2009,"acronym":"MARXAN","method_name":"marine reserve design using spatially explicit annealing","scale":"continental","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Prioritize landscape patches by minimizing a combination of the cost of the reserve network and the boundary length of the entire system, whilst meeting a set of biodiversity targets.","DOI/link":"https://www.researchgate.net/publication/43525654_Marxan_and_relatives_Software_for_spatial_conservation_prioritization","ID":"Ball2009","example_taxon_standard":"corals","example_area_standard":"Australia","scalability":"intermediate"}
{"author":"Daigle","year":2020,"acronym":"MarxCon","method_name":"MARXAN Connect","scale":"continental","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Assist conservation planners with the appropriate use of data on ecological connectivity in protected area network planning, by incorporating connectivity into MARXAN analyses","DOI/link":"https://doi.org/10.1111/2041-210X.13349","ID":"Daigle2020","example_taxon_standard":"corals","example_area_standard":"Australia","scalability":"high"}
{"author":"Liu","year":2019,"acronym":"MCDM","method_name":"Multicriteria decision making","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Quantitative assessment method for species based conservation","DOI/link":"https://doi.org/10.1016/j.biocon.2019.03.014","ID":"Liu2019","example_taxon_standard":"vascular plants","example_area_standard":"global","scalability":"high"}
{"author":"Crous","year":2013,"acronym":"mesofilter","method_name":"mesofilter","scale":"regional","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"To explore the value of the meso filter as an operational scale in conservation planning","DOI/link":"https://doi.org/10.1111/1365-2664.12012","ID":"Crous2013","example_taxon_standard":"arthropods, vascular plants","example_area_standard":"South Africa","scalability":"high"}
{"author":"Willoughby","year":2015,"acronym":"MicrosDiv","method_name":"LM Genetic diversity and IUCN list","scale":"global","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Check the relationship between genetic diversity (microsatellites) and IUCN conservation status","DOI/link":"https://doi.org/10.1016/j.biocon.2015.07.025","ID":"Willoughby2015","example_taxon_standard":"amphibians, birds, mammals, squamates, turtles/tortoises","example_area_standard":"global","scalability":"high"}
{"author":"Dhanjal-Adams","year":2017,"acronym":"MigrNet","method_name":"Landscape connectivity","scale":"continental","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Spatial prioritisation conservation based on a model of potential connectivity of migration routes","DOI/link":"https://doi.org/10.1111/cobi.12842","ID":"Dhanjal-Adams2017","example_taxon_standard":"birds","example_area_standard":"other","scalability":"high"}
{"author":"Galetti","year":2009,"acronym":"MPi","method_name":"Mammalian Priority Conservation Index","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Index to reveal effect of forest type, level of hunting pressure and forest fragmentation on population abundance and biomass of large mammal species","DOI/link":"https://doi.org/10.1016/j.biocon.2009.01.023","ID":"Galetti2009","example_taxon_standard":"mammals","example_area_standard":"Brazil","scalability":"low"}
{"author":"Lagabrielle","year":2018,"acronym":"MSSP","method_name":"Marxan","scale":"regional","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":1,"free_text_description":"A multi-scale spatial planning method to prioritize ecosystem management actions","DOI/link":"https://doi.org/10.1371/JOURNAL.PONE.019258","ID":"Lagabrielle2018","example_taxon_standard":"bony fish/shark, turtles/tortoises, mammals","example_area_standard":"South Africa","scalability":"low"}
{"author":"Rüter","year":2017,"acronym":"MWP","method_name":"multi-scale Modified Whittaker plot","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Assess total and endangered species richness","DOI/link":"https://doi.org/10.1016/j.ufug.2016.11.008","ID":"Ruter2017","example_taxon_standard":"vascular plants","example_area_standard":"Germany","scalability":"high"}
{"author":"Volkmann","year":2014,"acronym":"NeighborNet","method_name":"NeighborNet network","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"An extension of evolutionary isolation indices used in conservation planning from phylogenetic trees to phylogenetic networks","DOI/link":"https://doi.org/10.1371/journal.pone.0088945","ID":"Volkmann2014","example_taxon_standard":"birds, mammals","example_area_standard":"Canada, USA, Mexico, Australia","scalability":"high"}
{"author":"Jansen","year":2018,"acronym":"NRTBiomass","method_name":"remote sensing","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Assessment of estimates of vegetation cover and above-ground biomass modeled from the remote sensing","DOI/link":"https://doi.org/10.3390/rs10071057","ID":"Jansen2018","example_taxon_standard":"vascular plants","example_area_standard":"USA","scalability":"high"}
{"author":"Coro","year":2016,"acronym":"OBIS","method_name":"absence estimation","scale":"global","implementation_standard":"other","target":"species","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A methodology to reconstruct reliable absence information from presence-only information","DOI/link":"https://doi.org/10.1016/j.ecolmodel.2015.12.008","ID":"Coro2016","example_taxon_standard":"bony fish/shark","example_area_standard":"other","scalability":"high"}
{"author":"Bonin","year":2007,"acronym":"PAI","method_name":"Population Adaptive Index","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":1,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Adaptive specificity of population relative to other populations","DOI/link":"https://doi.org/10.1111/j.1523-1739.2007.00685.x","ID":"Bonin2007","example_taxon_standard":"amphibians, squamates","example_area_standard":"France","scalability":"low"}
{"author":"McGoogan","year":2007,"acronym":"PDBioGeoPrim","method_name":"PD rankings","scale":"continental","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Compare phylogenetic diversity rank with IUCN Red List","DOI/link":"https://doi.org/10.1111/j.1365-2699.2007.01759.x","ID":"McGoogan2007","example_taxon_standard":"mammals","example_area_standard":"other","scalability":"high"}
{"author":"Faith","year":2004,"acronym":"PDCECA","method_name":"Phygenetic diversity, complemetarity, endemism","scale":"regional","implementation_standard":"other","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"demonstration of the phylogenetic diversity that is an integration of phylogeny, complementarity and endemism.","DOI/link":"https://doi.org/10.2307/3589136","ID":"Faith2004","example_taxon_standard":"arthropods","example_area_standard":"Australia","scalability":"high"}
{"author":"Larkin","year":2016,"acronym":"PIECES","method_name":"PIECES","scale":"continental","implementation_standard":"Excel","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Development of PIECES index (Phylogenetically Informed Ex situ Conservation of Endangered Species) to construct a threat rank of ex situ collections","DOI/link":"https://doi.org/10.1371/journal.pone.0156973","ID":"Larkin2016","example_taxon_standard":"vascular plants","example_area_standard":"Canada, USA, Mexico","scalability":"high"}
{"author":"Hilbers","year":2017,"acronym":"PopBodyMass","method_name":"density-dependent population dynamics models","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Use of population dynamics models to estimate minimum viable population targets intrinsically related to species body mass","DOI/link":"https://doi.org/10.1111/cobi.12846","ID":"Hilbers2017","example_taxon_standard":"mammals","example_area_standard":"global","scalability":"intermediate"}
{"author":"Hanson","year":2020,"acronym":"prioritize","method_name":"prioritize: Systematic Conservation Prioritization in R","scale":"continental","implementation_standard":"R package","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use integer linear programming (ILP) techniques to provide a flexible interface for building and solving conservation planning problems","DOI/link":"https://prioritizr.net/","ID":"Hanson2020","example_taxon_standard":"NA","example_area_standard":"none","scalability":"high"}
{"author":"Albuquerque","year":2016,"acronym":"PRWR","method_name":"Rarity weight richness","scale":"global","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Implementation of the predicted rarity-weighted richness (PRWR) as a surrogate in situations where species inventories may be available for a portion of the planning area","DOI/link":"https://doi.org/10.1002/ece3.2544","ID":"Albuquerque2016","example_taxon_standard":"vascular plants, birds","example_area_standard":"global","scalability":"high"}
{"author":"Vincent","year":2019,"acronym":"PSM","method_name":"Priority Scores Method, Zonation Land Use Filter","scale":"global","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":1,"includes_simulation":0,"free_text_description":"Model to prioritize species and ecosystem protection","DOI/link":"https://doi.org/10.1016/j.gecco.2019.e00589","ID":"Vincent2019","example_taxon_standard":"arthropods, vascular plants, squamates, turtles/tortoises, amphibians","example_area_standard":"Switzerland","scalability":"intermediate"}
{"author":"Estrada","year":2018,"acronym":"PSRGMF","method_name":"Potential species richness, geometric mean of favorabilities","scale":"regional","implementation_standard":"R script","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of PSR and GMF metrics to evaluate the national park network of mainland Spain","DOI/link":"https://doi.org/10.1093/cz/zoy001","ID":"Estrada2018","example_taxon_standard":"mammals","example_area_standard":"Spain","scalability":"high"}
{"author":"Bocedi","year":2014,"acronym":"RangeShifter","method_name":"RangeShifter","scale":"regional","implementation_standard":"GUI","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"An individual based model, to assess species population dynamics and geographic distribution, in response to environmental variables or management scenarios","DOI/link":"https://doi.org/10.1111/2041-210X.12162","ID":"Bocedi2014","example_taxon_standard":"vascular plants","example_area_standard":"United Kingdom","scalability":"low"}
{"author":"Carlos-Júnior","year":2019,"acronym":"RarBetaDiv","method_name":"singularity index and richness","scale":"regional","implementation_standard":"R script","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of a singularity index and rarity to determine conservation priority","DOI/link":"https://doi.org/10.1111/ddi.12896","ID":"CarlosJunior2019","example_taxon_standard":"bony fish/shark, other","example_area_standard":"Brazil","scalability":"low"}
{"author":"Cadotte","year":2010,"acronym":"Rarest","method_name":"ecoPD","scale":"global","implementation_standard":"R package","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of phylogenetic metrics including data on geographical rarity to inform conservation prioritization at biogeographic scales","DOI/link":"https://doi.org/10.1111/j.1472-4642.2010.00650.x","ID":"Cadotte2010","example_taxon_standard":"NA","example_area_standard":"none","scalability":"high"}
{"author":"Cardoso","year":2017,"acronym":"red","method_name":"IUCN Red Listing Tools","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Species red list assessment according to IUCN criteria","DOI/link":"https://doi.org/10.3897/BDJ.5.e20530","ID":"Cardoso2017","example_taxon_standard":"arthropods","example_area_standard":"Portugal","scalability":"high"}
{"author":"Lee","year":2019,"acronym":"Redlistr","method_name":"Redlistr","scale":"global","implementation_standard":"R package","target":"species","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"R package to aid in the production of consistent species and ecosystem Red List assessments","DOI/link":"https://doi.org/10.1111/ecog.04143","ID":"Lee2019","example_taxon_standard":"mammals","example_area_standard":"Russia","scalability":"high"}
{"author":"Taylor","year":2016,"acronym":"REMP","method_name":"rapid evaluation of metapopulation persistence","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Modeling method used to perform an evaluation of population viability","DOI/link":"https://pubmed.ncbi.nlm.nih.gov/26902481/","ID":"Taylor2016","example_taxon_standard":"mammals, birds, amphibians","example_area_standard":"Australia","scalability":"low"}
{"author":"Arzamendia","year":2012,"acronym":"RiversCons","method_name":"General track (GT) to identify nodes (areas where two or more GT intersect are superimposed)","scale":"continental","implementation_standard":"other","target":"area","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of species track to identify priority areas for conservation along rivers","DOI/link":"https://doi.org/10.1111/j.1472-4642.2011.00829.x","ID":"Arzamendia2012","example_taxon_standard":"squamates","example_area_standard":"Bolivia, Brazil, Paraguay, Uruguay, Argentina","scalability":"high"}
{"author":"Eros","year":2018,"acronym":"RPCOM","method_name":"River Protection and Connectivity Optimization Model","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":0,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A framework to balance conservation and ecosystem service provision of rivers based on optimizing connectivity.","DOI/link":"https://doi.org/10.1111/1365-","ID":"Eros2018","example_taxon_standard":"bony fish/shark","example_area_standard":"Hungary","scalability":"low"}
{"author":"White","year":2015,"acronym":"R-rank","method_name":"NatureServe","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Assessing conservation status ranks through species' degree of relative extinction risk","DOI/link":"https://doi.org/10.1086/682287","ID":"White2015","example_taxon_standard":"arthropods","example_area_standard":"USA","scalability":"high"}
{"author":"Moilanen","year":2014,"acronym":"SACS","method_name":"structured analysis of conservation strategies","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":0,"free_text_description":"A framework for the structured analysis of conservation strategies, concentrating on their conceptual, causal, logical and qualitative aspects","DOI/link":"https://doi.org/10.1016/j.biocon.2014.01.001","ID":"Moilanen2014","example_taxon_standard":"none","example_area_standard":"none","scalability":"high"}
{"author":"Marx","year":2020,"acronym":"samc","method_name":"samc","scale":"regional","implementation_standard":"R package","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Quantifying landscape connectivity to better understand and predict how populations respond to environmental change","DOI/link":"https://doi.org/10.1111/ecog.04891","ID":"Marx2020","example_taxon_standard":"mammals","example_area_standard":"USA","scalability":"intermediate"}
{"author":"Halmy","year":2015,"acronym":"SCI","method_name":"Species conservation importance index","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Prioritizing plant species by their conservation value, including distribution, rarity, threat, traits, plant use and ecological importance","DOI/link":"https://doi.org/10.1007/s40415-015-0197-z","ID":"Halmy2015","example_taxon_standard":"vascular plants","example_area_standard":"Egypt","scalability":"intermediate"}
{"author":"Zhang","year":2016,"acronym":"SCP","method_name":"systematic conservation planning","scale":"global","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"A integration of systematic conservation planning (SCP) with gap analysis to optimize solutions of protected areas planning at local scales","DOI/link":"http://dx.doi.org/10.1016/j.jnc.2016.03.003","ID":"Zhang2016","example_taxon_standard":"vascular plants","example_area_standard":"China","scalability":"high"}
{"author":"Schlottfeldt","year":2015,"acronym":"SCPinCC","method_name":"systematic conservation planning","scale":"regional","implementation_standard":"GUI","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":1,"free_text_description":"A multi-objective solution for SCP considering future climate simulations to estimate species occurrence projected to 2080","DOI/link":"https://doi.org/10.1007/978-3-319-15892-131","ID":"Schlottfeldt2015","example_taxon_standard":"vascular plants","example_area_standard":"Brazil","scalability":"intermediate"}
{"author":"Halmy","year":2015,"acronym":"SCV","method_name":"Site conservation value","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Prioritize areas by the multidimensional conservation value of the plant species occurring in them","DOI/link":"https://doi.org/10.1007/s40415-015-0197-z","ID":"Halmy2015","example_taxon_standard":"vascular plants","example_area_standard":"Egypt","scalability":"intermediate"}
{"author":"Weeks","year":2017,"acronym":"seascapeNet","method_name":"Marxan","scale":"regional","implementation_standard":"stand-alone commandline","target":"area","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Derivation of seascape connectivity metric based on area-weighted proximity between juvenile and adult habitat patches to spatial prioritization","DOI/link":"https://doi.org/10.1371/journal.pone.0182396","ID":"Weeks2017","example_taxon_standard":"bony fish/shark","example_area_standard":"other","scalability":"high"}
{"author":"Sanchez de Dios","year":2017,"acronym":"SGRID","method_name":"Endemism, rarity, richness, and phylogenetic distance","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Improve the knowledge of the process of selection of important plant areas (IPAs)","DOI/link":"https://doi.org/10.1111/ddi.12535","ID":"SanchezdeDios2017","example_taxon_standard":"vascular plants","example_area_standard":"Spain","scalability":"intermediate"}
{"author":"Reece","year":2014,"acronym":"SIVVA","method_name":"Standardized Index of Vulnerability and Value Assessment","scale":"regional","implementation_standard":"Excel","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":1,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":1,"genetics":1,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":1,"land_use":1,"protected_area":0,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":0,"free_text_description":"A detailed protocol, integrating existing prioritization protocols into a new measure with a specific focus on sea level rise","DOI/link":"http://dx.doi.org/10.3375/043.034.0105","ID":"Reece2014","example_taxon_standard":"mammals, squamates, birds, amphibians","example_area_standard":"USA","scalability":"low"}
{"author":"Sinclair-Waters","year":2018,"acronym":"SNP","method_name":"single nucleotid polymorphism","scale":"continental","implementation_standard":"R package","target":"species","scope_terrestrial":0,"scope_marine":1,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":1,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Genomic tools for identifying exploitation outside MPA boundaries and estimating Ne, thus providing valuable information for the effective design and management of an MPA","DOI/link":"none","ID":"Sinclair-Waters2018","example_taxon_standard":"bony fish/shark","example_area_standard":"Canada","scalability":"intermediate"}
{"author":"Schatz","year":2014,"acronym":"spProt","method_name":"responsibility, rarity and vulnerability","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":1,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"An objective method to list taxa at nested administrative levels based on three criteria (responsibility, rarity and vulnerability)","DOI/link":"http://dx.doi.org/10.1016/j.jnc.2013.09.003","ID":"Schatz2014","example_taxon_standard":"vascular plants","example_area_standard":"France","scalability":"intermediate"}
{"author":"Pettorelli","year":2016,"acronym":"SRBioCons","method_name":"remote sensing","scale":"global","implementation_standard":"R script","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":1,"climate_change":0,"includes_simulation":0,"free_text_description":"Overview of the role of SRS to date in informing Biodiversity Variable, Natural Capital, Biodiversity Indicator and Ecosystem Service","DOI/link":"https://doi.org/10.1111/2041-210X.12545","ID":"Pettorelli2016","example_taxon_standard":"NA","example_area_standard":"Algeria, Chad, Egypt, Libya, Mali, Mauritania, Morocco, Niger, Western Sahara, Sudan, Tunisia","scalability":"high"}
{"author":"Morinha","year":2017,"acronym":"StDM","method_name":"stochastic dynamic methodology","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":1,"free_text_description":"Dynamic tool to capture the trends of relevant population foraging ground attributes","DOI/link":"https://doi.org/10.1016/j.biocon.2017.04.013","ID":"Morinha2017","example_taxon_standard":"birds","example_area_standard":"Portugal","scalability":"low"}
{"author":"Boykin","year":2013,"acronym":"SWReGAP","method_name":"Gap Analysis Project","scale":"regional","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":1,"socio_economic":1,"landscape_connectivity":0,"land_use":1,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"An approach that (1) identifies map-able biodiversity metrics that are related to ecosystem services or other stakeholder concerns, (2) maps these metrics throughout a large multi-state region, and (3) compares the metric values","DOI/link":"http://dx.doi.org/10.1016/j.ecolind.2012.11.005","ID":"Boykin2013","example_taxon_standard":"amphibians, mammals, birds, squamates, turtles/tortoises","example_area_standard":"USA","scalability":"high"}
{"author":"Wu","year":2018,"acronym":"TreeLiDAR","method_name":"wheith of evidence (WofE)","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":0,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Compare urban tree mapping potential of ALS and MLS data to detect trees and recognize their species and vitality","DOI/link":"https://doi.org/10.3390/rs10091403","ID":"Wu2018","example_taxon_standard":"vascular plants","example_area_standard":"Germany","scalability":"low"}
{"author":"Aagaard","year":2017,"acronym":"UCI","method_name":"Unit Contribution Index","scale":"regional","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Index for wildlife managers to evaluate the performance of units within the conservation estate","DOI/link":"https://doi.org/10.1016/j.gecco.2017.01.002","ID":"Aagaard2017","example_taxon_standard":"birds","example_area_standard":"USA","scalability":"intermediate"}
{"author":"Tovo","year":2019,"acronym":"UpscalingPA","method_name":"UpscalingPA","scale":"global","implementation_standard":"R script","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Script to infer species richness and abundance on large spatial scale when presence/absence information is available on scattered samples (upscaling)","DOI/link":"https://doi.org/10.1111/oik.06754","ID":"Tovo2019","example_taxon_standard":"vascular plants","example_area_standard":"Malaysia, Panama","scalability":"high"}
{"author":"Cabrelli","year":2014,"acronym":"VECC","method_name":"vulnerability index","scale":"continental","implementation_standard":"none","target":"species","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":1,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":1,"extinction_risk":1,"environment":1,"vulnerability":1,"climate_change":1,"includes_simulation":1,"free_text_description":"A framework to assess species vulnerability to climate change that considered species traits together with the projections of SDMs.","DOI/link":"https://doi.org/10.1007/s10531-014-0760-0","ID":"Cabrelli2014","example_taxon_standard":"squamates","example_area_standard":"Australia","scalability":"intermediate"}
{"author":"Farooq","year":2020,"acronym":"WEGE","method_name":"Weighted Endemism and Globally Endangered","scale":"global","implementation_standard":"R package","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":1,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"An adaptation of the EDGE system, but using endemism score instead of the phylogenetic component, to target areas rather than species","DOI/link":"https://doi.org/10.1111/ddi.13148","ID":"Farooq2020","example_taxon_standard":"mammals, birds, amphibians","example_area_standard":"global","scalability":"high"}
{"author":"Chen","year":2019,"acronym":"WildLifeHab","method_name":"remote sensing (OIF)","scale":"regional","implementation_standard":"none","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":1,"protected_area":1,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of remote sensing to monitor habitat degradation","DOI/link":"none","ID":"Chen2019","example_taxon_standard":"NA","example_area_standard":"China","scalability":"high"}
{"author":"Veloz","year":2015,"acronym":"ZCPA","method_name":"Zonation conservation prioritization algorithm","scale":"regional","implementation_standard":"other","target":"area","scope_terrestrial":1,"scope_marine":0,"scope_limnic":0,"phylogeny":0,"distribution":1,"functional":0,"rarity":1,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":0,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":1,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Use of the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models","DOI/link":"https://doi.org/10.1111/cobi.12499","ID":"Veloz2015","example_taxon_standard":"birds","example_area_standard":"USA","scalability":"high"}
{"author":"Lehtomäki","year":2013,"acronym":"Zonation","method_name":"Zonation","scale":"continental","implementation_standard":"GIS (ARC, GRASS, Q)","target":"area","scope_terrestrial":1,"scope_marine":1,"scope_limnic":1,"phylogeny":0,"distribution":1,"functional":0,"rarity":0,"pop_dynamics":0,"genetics":0,"ecosystem_services":0,"socio_economic":0,"landscape_connectivity":1,"land_use":0,"protected_area":0,"extinction_risk":0,"environment":0,"vulnerability":0,"climate_change":0,"includes_simulation":0,"free_text_description":"Multi-species landscape scale conservation planning methods using multi-species occurrence (or density) to identify areas important for landscape connectivity, by sequentially removing cells.","DOI/link":"https://doi.org/10.1016/j.envsoft.2013.05.001","ID":"Lehtomaki2013","example_taxon_standard":"arthropods","example_area_standard":"United Kingdom","scalability":"intermediate"}