Livestock is represented in big cat diets throughout the world. Husbandry approaches aim to reduce depredation, which may influence patterns of prey choice, but whether felids have a preference for livestock or not often remains unclear as most studies ignore livestock availability. We assessed prey choice of the endangered Persian leopard (Panthera pardus saxicolor) in Golestan National Park, Iran, where conflict over livestock depredation occurs. We analyzed leopard diet (77 scats) and assessed wild and domestic prey abundance by line transect sampling (186 km), camera-trapping (2777 camera days), double-observer point-counts (64 scans) and questionnaire surveys (136 respondents). Based on interviews with 18 shepherds, we estimated monthly grazing time outside six villages with 96 conflict cases to obtain a small livestock (domestic sheep and goat) availability coefficient. Using this coefficient, which ranged between 0.40 and 0.63 for different villages, we estimated the numbers of sheep and goats available to leopard depredation. Leopard diet consisted mainly of wild boar (Sus scrofa) (50.2% biomass consumed), but bezoar goat (Capra aegagrus) was the most preferred prey species (Ij = 0.73), whereas sheep and goats were avoided (Ij = -0.54). When absolute sheep and goat numbers (~11250) were used instead of the corrected ones (~6392), avoidance of small livestock appeared to be even stronger (Ij = -0.71). We suggest that future assessments of livestock choice by felids should incorporate such case-specific corrections for spatiotemporal patterns of availability, which may vary with husbandry methods. Such an approach increases our understanding of human-felid conflict dynamics and the role of livestock in felid diets.

No abstract

Biomass regression models and associated correction factors derived from feeding trials are essential to convert frequency of prey occurrence from scats into biomass and numbers of prey individuals consumed by carnivores. These dietary analyses form a substantial part of many research projects on predator-prey relationships and human-carnivore conflicts. So far, diet studies of leopard (Panthera pardus) applied the linear biomass model developed for puma (Puma concolor). Recent works, however, suggested that non-linear biomass models are more meaningful for estimating prey biomass and numbers, and presented a generalized model of biomass consumption for all tropical felids. This model accounted for partial consumption of prey, but did not include ecological factors limiting prey consumption by felids. Hence, using 35 feeding trials we developed a leopard specific regression equation by setting a consumption limit for leopard per prey. This new correction factor takes into account the proportion of inedible matter of prey and daily food intake. Besides refining the leopard specific biomass models, our study also showed the saturation in scat production with consumption of larger prey, which was described in recent studies. A reanalysis of prey consumption by leopards from published diet studies by using our new regression models suggests a significant decrease in estimated absolute numbers of prey individuals consumed. This finding and the higher share of larger prey in leopard diet may affect subsequent analyses using prey profiles, and may affect decisions made in biodiversity conservation and management, especially in the area of human-carnivore conflict. Jethva & Jhala, 2004). To overcome this bias in estimating biomass and individuals of consumed prey from scats, several methods are proposed and have been reviewed by R€ uhe et al. (2008) and Klare et al. (2011). These are usually based on

Widespread prey depletion forces carnivores to rely more on livestock, which may lead to increased persecution by humans. Reliable quantification of livestock consumption is essential for understanding depredation scales, but a comparative analysis of extant biomass models used for this purpose has never been done before. We conducted a global meta‐analysis of two linear and three non‐linear biomass models used to estimate consumption of prey biomass and individuals by seven big cat species. We applied the z‐test to perform pairwise comparisons of estimates produced by five models for each prey record. Further, we used logistic regression to assess the effects of species of big cats and their prey, scat sample size, prey body mass, and study sites on significantly different and similar estimates. The analysis of 769 prey records from 47 sites demonstrated that, in over 95% of cases, linear and non‐linear biomass models produced similar estimates of prey biomass and individuals consumed. Significantly different estimates of prey biomass consumed (in 1.5% of cases) and prey individuals consumed (4%) were obtained only in certain study sites and for a few big cat species (tiger Panthera tigris, leopard Panthera pardus, and puma Puma concolor). Due to the paucity of different estimates, the effects of predictors could not be ascertained. Our study demonstrated that linear models tend to estimate higher biomass of large prey, lower biomass of medium‐sized prey and fewer individuals of large and medium‐sized prey consumed than non‐linear models. This disagreement in estimates suggests that the numbers of livestock lost to depredation can be underestimated by linear models, and that re‐calculation by non‐linear models is required. However, the difference between estimates produced by linear and non‐linear models is generally small and such re‐calculation may be recommended only for tiger, puma and leopard in certain areas.

<p>Green spaces, from small-scale structures such as green roofs and individual trees in cities to large grasslands and forests, fulfill climate-relevant, ecological and social functions. The protection and monitoring of these spaces as well as dissemination and awareness raising in the field of nature conservation is of  socio-politically relevant concern. The project SEMONA RELOADED (funded by the Austrian Research Promotion Agency, FFG) aims to identify these functions through inventories and change detection. The classification and monitoring of areas with biodiversity worthy of protection (e.g. Natura 2000), as well as green infrastructure in settlement areas (e.g. green space monitoring of the City of Vienna - GRM) are obligatory within the framework of nature conservation laws and are also required within the framework of national and international reporting obligations. Currently, such studies are often based on expert-based mapping in the field (biotope types) and/or indices derived from individual remote sensing data.<br />The motivation for SEMONA RELOADED is to support this labor-intensive process by linking regionally available very high spatial resolution remote sensing data such as airborne laser scanning (ALS) and aerial photography (AP) with high temporal resolution sentinel data (S1, S2). In addition to assisting with the initial identification and classification of green space, including remote sensing data in the workflow should enable constant monitoring of the areas. This builds on successful results from the feasibility study completed in 2021 (SeMoNa22). <br />The processing of test areas in Vienna has shown that the combination of S1 and S2 as well as high-resolution AP and ALS data has high potential for the differentiation of biotope types and green infrastructure in urban areas. By training classification algorithms using combined features, different biotope types could be successfully identified in test areas. In the inner-city area, green roofs could be successfully identified as a sub-area of green infrastructure monitoring better than with previously applied methods.<br />In the presented follow-up study, the research area is enlarged to a regional scale including the protected areas of Nationalpark Donau-Auen, the Vienna Woods Biosphere Reserve and the Natura 2000 area Wachau, the City of Krems as well as the whole area or the City of Vienna. In addition, different Stakeholders (provincial administration, national park and biosphere park administration, federal forestry office) are included in the research process to ensure the applicability of the developed methods for the applied use in mapping and monitoring. <br />In the presented poster, the relevant outcomes of the previous feasibility study will be presented and an overview of the planned research activities of the current SEMONA RELOADED project will be given. </p>