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.

Identifying species boundaries within morphologically indistinguishable cryptic species complexes is often contentious. For the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae), the lack of a clear understanding about the genetic limits of the numerous genetic groups and biotypes so far identified has resulted in a lack of consistency in the application of the terms, the approaches used to apply them and in our understanding of what genetic structure within B. tabaci means. Our response has been to use mitochondrial gene cytochrome oxidase one to consider how to clearly and consistently define genetic separation. Using Bayesian phylogenetic analysis and analysis of sequence pairwise divergence we found a considerably higher number of genetic groups than had been previously determined with two breaks in the distribution, one at 11% and another at 3.5%. At >11% divergence, 11 distinct groups were resolved, whereas at >3.5% divergence 24 groups were identified. Consensus sequences for each of these groups were determined and were shown to be useful in the correct assignment of sequences of unknown origin. The 3.5% divergence bound is consistent with species level separations in other insect taxa and suggests that B. tabaci is a cryptic species composed of at least 24 distinct species. We further show that the placement of Bemesia atriplex (Froggatt) within the B. tabaci in group adds further weight to the argument for species level separation within B. tabaci. This new analysis, which constructs consensus sequences and uses these as a standard against which unknown sequences can be compared, provides for the first time a consistent means of identifying the genetic bounds of each species with a high degree of certainty.