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

Abstract

39Limited conservation resources mean that management decisions are often made on the basis 40 of scarce biological information. Species distribution models (SDMs) are increasingly 41 proposed as a way to improve the representation of biodiversity features in conservation 42 planning, but the extent to which SDMs are used in conservation planning is unclear. We 43 reviewed the peer-reviewed and grey conservation planning literature to explore if and how 44SDMs are used in conservation prioritisations. We use text mining to analyse 641 peer-45 reviewed conservation prioritisation articles published between 2006 and 2012 and find that 46 only 10% of articles specifically mention SDMs in the abstract, title, and/or keywords. We use 47 topic modelling of all peer-reviewed articles plus a detailed review of a random sample of 40 48 peer-reviewed and grey literature plans to evaluate factors that might influence whether 49 decision-makers use SDMs to inform prioritisations. Our results reveal that habitat maps, 50 expert-elicited species distributions, or metrics representing landscape processes (e.g. 51 connectivity surfaces) are used more often than SDMs as biodiversity surrogates in 52 prioritisations. We find four main reasons for using such alternatives in place of SDMs: (i) 53 insufficient species occurrence data (particularly for threatened species); (ii) lack of 54 biologically-meaningful predictor data relevant to the spatial scale of planning; (iii) lack of 55 concern about uncertainty in biodiversity data; and (iv) a focus on accounting for ecological, 56 evolutionary, and cumulative threatening processes that requires alternative data to be 57 collected. Our results suggest that SDMs are perceived as best-suited to dealing with traditional 58 reserve selection objectives and accounting for uncertainties such as future climate change or 59 mapping accuracy. The majority of planners in both the grey and peer-reviewed literature 60 appear to trade off the benefits of using SDMs for the benefits of including information on 61 multiple threats and processes. We suggest that increasing the complexity of species 62 distribution modelling methods might have little impact on their use in conservation planning 63 without a corresponding increase in research aiming at better incorporation of a range of 64 ecological, evolutionary, and threatening processes. 65 66 objectives (Makino et al. 2013). These advances have allowed planners to account for factors 100

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

“…It has been argued that there is a general lack of concern about data quality from both mapmakers and end-users , to the point where data quality issues are ignored and tolerated by conservation planners as an inherent part of data (Tulloch et al, 2016). Tulloch et al (2016) found out that conservation planners prefer simplicity of maps to their accuracy, which is understandable to a certain point because it is easier to make policy from a simple map than from a complex one, or one with contingencies (Borja, 2014).…”

“…Tulloch et al (2016) found out that conservation planners prefer simplicity of maps to their accuracy, which is understandable to a certain point because it is easier to make policy from a simple map than from a complex one, or one with contingencies (Borja, 2014). However, errors and uncertainty can result in inaccurate representation of the environments, and thus inaccurate maps (Wintle et al, 2005, Figure 3).…”

“…A lack of awareness and understanding of the concepts associated with data quality can in turn lead to misinformed conservation and management decisions (Rondinini et al, 2006;Beale and Lennon, 2012;Katsanevakis et al, 2012) with dire results for biodiversity (Regan et al, 2005). For instance, it can become an issue when prioritizing conservation decisions (Tulloch et al, 2016): if one area is identified as being a slightly more important target for conservation than another, but the first is associated with a higher level of uncertainty, which one should be prioritized?…”

“…In all cases, mapmakers should explicitly report commission and omission errors and their meaning when relevant (Rondinini et al, 2006;Borja, 2014), and in modeling processes probabilistic outputs accounting for model uncertainty should be provided . Finally, all of this information should be incorporated into the decision-making processes (Moilanen et al, 2006;Tulloch et al, 2016): Levin et al (2014) argued that the lack of data quality information is among the most significant impediments to adequate conservation efforts.…”

“…While this may seem obvious, data content is a matter that needs to be carefully approached: it has been reported that data for marine characterization are not always carefully selected, with data being selected primarily based on availability rather than ecological meaning and fitness-for-use (Peterson et al, 2011;Tulloch et al, 2016;Lecours et al, 2017a). It is evident that selecting different variables, for instance broad-scale currents instead of fine-scale substrate types, is likely to produce different maps and influence models differently.…”