Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

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

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