Global commitments to halt biodiversity decline mean that it is essential tomonitor species’ extinction risk. However, the work required to assess extinc-tion risk is intensive. We demonstrate an alternative approach to monitoringextinction risk, based on the response of species to external conditions.Using retrospective International Union for Conservation of Nature Red Listassessments, we classify transitions in the extinction risk of 497 mammaliancarnivores and ungulates between 1975 and 2013. Species that moved tolower Red List categories, or remained Least Concern, were classified as‘lower risk’; species that stayed in a threatened category, or moved to ahigher category of risk, were classified as ‘higher risk’. Twenty-four predictorvariables were used to predict transitions, including intrinsic traits (speciesbiology) and external conditions (human pressure, distribution state andconservation interventions). The model correctly classified up to 90% of alltransitions and revealed complex interactions between variables, such as pro-tected areas (PAs) versus human impact. The most important predictors were:past extinction risk, PA extent, geographical range size, body size, taxonomicfamily and human impact. Our results suggest that monitoring a targeted setof metrics would efficiently identify species facing a higher risk, and couldguide the allocation of resources between monitoring species’ extinction riskand monitoring external conditions.

Historical drivers of extinction risk: Using past evidence to direct future monitoring / Di Marco, M; Collen, B; Rondinini, Carlo; Mace, G.. - In: PROCEEDINGS - ROYAL SOCIETY. BIOLOGICAL SCIENCES. - ISSN 0962-8452. - STAMPA. - 282:1813(2015). [10.1098/rspb.2015.0928]

Historical drivers of extinction risk: Using past evidence to direct future monitoring

Di Marco M;RONDININI, CARLO;
2015

Abstract

Global commitments to halt biodiversity decline mean that it is essential tomonitor species’ extinction risk. However, the work required to assess extinc-tion risk is intensive. We demonstrate an alternative approach to monitoringextinction risk, based on the response of species to external conditions.Using retrospective International Union for Conservation of Nature Red Listassessments, we classify transitions in the extinction risk of 497 mammaliancarnivores and ungulates between 1975 and 2013. Species that moved tolower Red List categories, or remained Least Concern, were classified as‘lower risk’; species that stayed in a threatened category, or moved to ahigher category of risk, were classified as ‘higher risk’. Twenty-four predictorvariables were used to predict transitions, including intrinsic traits (speciesbiology) and external conditions (human pressure, distribution state andconservation interventions). The model correctly classified up to 90% of alltransitions and revealed complex interactions between variables, such as pro-tected areas (PAs) versus human impact. The most important predictors were:past extinction risk, PA extent, geographical range size, body size, taxonomicfamily and human impact. Our results suggest that monitoring a targeted setof metrics would efficiently identify species facing a higher risk, and couldguide the allocation of resources between monitoring species’ extinction riskand monitoring external conditions.
2015
biodiversity; conservation; human threats; mammals; random forest model
01 Pubblicazione su rivista::01a Articolo in rivista
Historical drivers of extinction risk: Using past evidence to direct future monitoring / Di Marco, M; Collen, B; Rondinini, Carlo; Mace, G.. - In: PROCEEDINGS - ROYAL SOCIETY. BIOLOGICAL SCIENCES. - ISSN 0962-8452. - STAMPA. - 282:1813(2015). [10.1098/rspb.2015.0928]
File allegati a questo prodotto
File Dimensione Formato  
Di_Marco_Historical_2015.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 465.62 kB
Formato Adobe PDF
465.62 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/893753
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 31
  • ???jsp.display-item.citation.isi??? 28
social impact