Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes. (July 2016)

• Record Type: Journal Article
• Authors: Tulloch, Ayesha I.T.; Sutcliffe, Patricia; Naujokaitis-Lewis, Ilona; Tingley, Reid; Brotons, Lluis; Ferraz, Katia Maria P.M.B.; Possingham, Hugh; Guisan, Antoine; Rhodes, Jonathan R.
• Is Part Of: Biological conservation. Volume 199(2016)
• Page Start: 157
• Page End: 171
• Publication Date: 2016-07
• Subjects: Reserve selection -- Decision-making -- Conservation plan -- Uncertainty -- Threat map -- Population process modelling -- Spatial prioritisation; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2016.04.023
• Languages: English
• ISSNs: 0006-3207

Abstract

Abstract: 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) low 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 peer-reviewed 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. Highlights: We sample the conservation planning literature to evaluate impediments to using species distribution models (SDMs). Few peer-reviewed papers or on-ground plans use SDMs, using experts and maps of threats, ecosystems and processes instead. SDMs are perceived as best-suited to deal with traditional reserve selection objectives and account for uncertainties. Non-SDM prioritisations deal more frequently with multiple objectives and ecological processes than SDM-prioritisations. We outline ways to improve conservation outcomes by considering trade-offs and the value of data for informing different objectives.