Search

Climate change has led to an increase in fire frequency in some areas on Earth. Satellite-derived spectral indices such as the Burn Area Index (BAI), the Normalized Burn Ratio (NBR), and their various derivatives are important for monitoring fires. The Burn Area Index for Sentinel-2 (BAIS2), which relies on the spectral bands of Sentinel-2, has a limitation due to its dependence on the red-edge spectral region unique to this satellite. To address this limitation, two new spectral indices (the Optimized Burned Area Index (OBAI) and the Optimized Burned Area Thermal Index (OBATI)) for burned scar mapping have been proposed based on the spectral separability concept and inter-band correlations. These indices aimed to improve the effectiveness of burned scar mapping by utilizing a wider range of spectral bands, including Landsat-8 thermal band and visible, near infrared (NIR), and mid infrared (MIR) regions of either Landsat-8 or Sentinel-2 sensors, which are more responsive to burned scars. We used spatial and spectral accuracy assessments to compare the effectiveness of the standard burned scar mapping indices (BASI2 and NBR) with the newly developed indices in discriminating the burned scars in several world regions. Based on Emergency Management Service fire perimeters, the vector distance algorithm (VDA) revealed that the accuracy of the fire perimeters extracted from the newly developed index, OBAI, was more reliable than the perimeters extracted using the BAIS2 and NBR. The BAIS2 index had the lowest performance in terms of spectral sensitivity compared to the other indices in the detection of burned scars. The performance of the developed optical index was high once the Landsat-8 data used to calculate it compared to Sentinel-2 data. Our findings could be used to further optimize global burned scar products derived from spaceborne data. [ABSTRACT FROM AUTHOR]

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 km2). 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. [ABSTRACT FROM AUTHOR]

The need to obtain information on population size to informmanagement actions for conservation is imperative. Despite this, reliable data on Caucasian grouse abundance is scarce in Iran. The goal of this study was to explore the potential distribution ofCaucasian grouse using an ensemble of small models with outstanding performance for modelling rare species'distributions to estimate the potential population size in Iran. We fitted an ensemble of small models with generalized boosted model (GBM) and maximum entropy (MaxEnt), and then built a final ensemble prediction by averaging across these two ensembles of small models. We considered ten environmental descriptors (land-cover, anthropogenic and topographic features) which were extracted over a 70 hectare spatial extent surrounding 22 Caucasian grouse lek occurrences. The best model's prediction map was used to estimate the potential population size ofCaucasian grouse in Iran. The ensemble of smallmodels with generalized boostedmodel showed higher transferability performances than the two other models on both 10-fold cross-validation and a geographically independent dataset. Based on the published species' densities and our prediction map, the potential population size of Caucasian grouse for Iran was estimated to be 98-196 individuals, which is considerably less than 350 reported by previous assessments. The predicted distribution map can be used to select priority areas for conservation, and to identify survey locations for the species in areas which so far have been poorly sampled. [ABSTRACT FROM AUTHOR]

Caucasian Grouse (Lyrurus mlokosiewiczi) is an endemic species found in the Caucasus whose population is declining. Initial assessment of genetic variation and phylogenetic status of the species confirmed themonophyly of L. mlokosiewiczias and indicated a sister relationship between L. mlokosiewiczi and L. tetrix (Black grouse). Further theCaucasian grouse from Georgia, Caucasus and Iran created three genetic groups with no shared haplotype. This separation could be the result of different evolutionary events or geographic distances between them. Four different haplotypeswere identified in north-western Iran, distributed inside and outside Arasbaran protected area (APA), suggesting the expansion of APAto include Caucasian grouse habitats in the Kalibar Mountains (western APA) and enhance the protection of the species in the region. [ABSTRACT FROM AUTHOR]

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, range‐wide 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. We investigated if Caucasian grouse (CG)'s functional responses to habitat features differ between the core and peripheral populations and thus, the occurrence‐habitat relationships could be explained by region‐specific models. Our study indicated that the southeastern population of CG is living under separately and unique climate conditions and does not share the same affinity to climate conditions as CG elsewhere; this may lead the species to be locally adapted this special climate condition through phenotypic plasticity or local adaptation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]