Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes

Détails

ID Serval
serval:BIB_68DBC60CD3C3
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Synthèse (review): revue aussi complète que possible des connaissances sur un sujet, rédigée à partir de l'analyse exhaustive des travaux publiés.
Collection
Publications
Institution
Titre
Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes
Périodique
Biological Conservation
Auteur(s)
Tulloch A.I.T., Sutcliffe P., Naujokaitis-Lewis I., Tingley R., Broton L., Ferraz K.M.P.M.B., Possingham H., Guisan A., Rhodes J.R.
ISSN
1873-2917
ISSN-L
0006-3207
Statut éditorial
Publié
Date de publication
2016
Peer-reviewed
Oui
Volume
199
Pages
157-171
Langue
anglais
Résumé
Limited conservation resources mean that management decisions
are often made on the basis of scarce biological information. Species
distribution models (SDMs) are increasingly proposed as a way to improve
the representation of biodiversity features in conservation planning, but
the extent to which SDMs are used in conservation planning is unclear. We
reviewed the peer-reviewed and grey conservation planning literature to
explore if and how SDMs are used in conservation prioritisations. We use
text mining to analyse 641 peer-reviewed conservation prioritisation
articles published between 2006 and 2012 and find that only 10% of
articles specifically mention SDMs in the abstract, title, and/or
keywords. We use topic modelling of all peer-reviewed articles plus a
detailed review of a random sample of 40 peer-reviewed and grey
literature plans to evaluate factors that might influence whether
decision-makers use SDMs to inform prioritisations. Our results reveal
that habitat maps, expert-elicited species distributions, or metrics
representing landscape processes (e.g. connectivity surfaces) are used
more often than SDMs as biodiversity surrogates in prioritisations. We
find four main reasons for using such alternatives in place of SDMs: (i)
insufficient species occurrence data (particularly for threatened
species); (ii) lack of biologically-meaningful predictor data relevant to
the spatial scale of planning; (iii) lack of concern about uncertainty in
biodiversity data; and (iv) a focus on accounting for ecological,
evolutionary, and cumulative threatening processes that requires
alternative data to be collected. Our results suggest that SDMs are
perceived as best-suited to dealing with traditional reserve selection
objectives and accounting for uncertainties such as future climate change
or mapping accuracy. The majority of planners in both the grey and peerreviewed
literature appear to trade off the benefits of using SDMs for
the benefits of including information on multiple threats and processes.
We suggest that increasing the complexity of species distribution
modelling methods might have little impact on their use in conservation
planning without a corresponding increase in research aiming at better
incorporation of a range of ecological, evolutionary, and threatening
processes.
Mots-clé
reserve selection, decision-making, conservation plan, threat map, population process modelling, spatial prioritization
Web of science
Création de la notice
17/04/2016 11:02
Dernière modification de la notice
20/08/2019 15:23
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