Climate change disproportionately threatens alpine species, by reducing available habitat and by isolating their populations. These pressures are particularly relevant for rear-edge populations, which typically occupy more marginal habitat compared to populations at the core of species' ranges. We studied Caucasian grouse Lyrurus mlokosiewiczi in the Caucasus ecoregion, a global biodiversity hotspot where this species is endemic, to understand potential climate change impacts on the species. Specifically, we assessed how climate change impacts rear-edge populations and how important these populations are for understanding range shifts and adaptive capacity under climate change. We used maximum entropy modeling to assess changes in the distribution of climatically suitable habitat under present and 2070 climate conditions for the representative concentration pathways 8.5 (RCP8.5). Our results revealed that ignoring rear-edge populations leads to a significant underestimation of the future range (by about 14,700 km 2). Rear-edge populations were better adapted to warmer climates compared to core populations, and ignoring them, therefore, also underestimates adaptive capacity. Preventing the loss of rear-edge populations should, therefore, be a priority for conservation planning in the face of climate change. Because the Caucasian grouse is associated with alpine mountain tops, conservation should focus on establishing connectivity between rear-edge and core populations (e.g., via transboundary corridors or assisted colonizations). Our study reveals how species distribution modeling can highlight the importance of rear-edge populations for mitigating climate change impacts on species of conservation concern.

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Context To create management strategies with the goal of sustaining a species such as Caucasian grouse (Lyrurus mlokosiewiczi), it is important to identify the habitat requirements of species, not just in terms of a correlation with a given habitat feature, but also the relationship between species presence and vegetation coverage, proximity to other habitat types, and importance at different spatial scales. Aims To predict the proportions and spatial configuration of major habitat types that are associated with high probabilities of Caucasian grouse lek occurrence. Methods Using minimum mapping-unit scale (i.e. grain) for land cover, we applied spatial analysis at three spatial extents (472-, 702- and 867-m-radius circles) to assess how the importance of different land-cover patterns and patch characteristics surrounding leks of Caucasian grouse changed with scale within the Arasbaran landscape (316.56 km2) in East Azerbaijan, Iran. A set of a priori models has been developed on the basis of landscape metrics linked to hypotheses that could explain the spatial pattern of Caucasian black habitat use at each scale. We used an information-theoretic approach based on Akaike’s information criterion (AIC) within a general additive models framework to model habitat selection, so as to compare the values of landscape metrics calculated for Caucasian grouse lek sites (n = 22) with those calculated for non-lek points (n = 44). Key results The probability of lek occurrence at each of the spatial scales increases with a larger amount of open, young forests in the landscape. At each scale, we could indicate the landscape composition and structure required to create an ideal habitat mosaic for Caucasian grouse. Such an ideal habitat mosaic within mountain forests of Arasbaran, for a 702-m-radius area around a potential lek site, would consist of non-square (i.e. more geometrically complex) patches of rangeland cover and deciduous stands with canopy cover of <50%, which encompass over 30% of landscape. Conclusions Our results identified differences in black grouse requirements at several scales within the landscape. We believe this will help managers improve the habitat focusing on the area around existing or inactive leks, to adapt the landscape to species requirements, and to encourage targeting new sites. Implications These findings demonstrated that not only can we identify important landscape requirements at a range of scales, but by characterising landscape composition and structure across these scales, forest managers can help prioritise combinations of habitats that best serve the conservation of the target species.

Treating a species as an evolutionally homogenous entity over its entire range and ignoring the effect of local adaptations and the consequences of species functional response to environmental gradients can lead to misguided conservation measures. The spatially distinct Caucasian grouse (CG) (Lyrurus mlokosiewiczi) populations across discontinuous range in the Caucasus Mountains would likely possess different adaptation traits which are of importance for conservation management. Using a separate distribution model for each of four different regions with the MaxEnt technique, we investigated if CG's functional responses to habitat features differ between the core and peripheral populations and thus, the occurrence-habitat relationships could be better explained by region-specific models than a single, rangewide model. We validated the models using each region as a geographically independent dataset. The results revealed that although there was a similar response to elevation in the four regions and the species occurrence probability was highest at altitude about 2,500 m, there was a consistently higher mean annual temperature in the species' southeastern Lesser Caucasus range compared to the western and eastern parts of the Greater Caucasus region (p < 0.001). The southeastern population of CG was living under separate and unique climate conditions and did not share the same affinity to climate conditions as CG elsewhere; this may lead the species to be adapted this special climate condition through phenotypic plasticity or local adaptation. Long-term evolutionary studies are essential to confirm CG intra-specific variations, but in lack of knowledge of local adaptation, our recommendation is to treat CG as geographically distinct populations that may each require specific management.

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