Climate and land-use changes coupled with low coverage of protected areas threaten palm species in South Brazilian grasslands

Climatic variables are more effective on the spatial distribution of oak forests than land use change across their historical range

The current research is conducted to model the effect of climate change and land use change (LUC) on the geographical distribution of Quercus brantii Lindl. (QB) forests across their historical range. Forecasting was done based on six general circulation models under RCP 2.6 and RCP 8.5 future climate change scenarios for the future years 2050 and 2070. In order to model the species distribution, different modeling methods were used. The results indicated that, in general, climatic variables had a higher influence on the distribution of QB than land use-related attributes. The mean diurnal range (bio2), the precipitation seasonality (bio15), and the mean temperature of the driest quarter (bio9) were the main predictors in the distribution of QB forests, while land use variables were less important in oak species distribution. The GBM, MaxEnt, and RF had higher accuracy and performance in modeling species distribution. The outputs also showed that in the current climate circumstances, 97,608.81 km2 of the studied area has high desirability for the presence of QB, and by 2070, under the pessimistic scenario, 96.29% of these habitats will be lost under the concomitant effect of LUC and climate change. By using the results of this research, it is possible to predict and identify the effective factors in changing the habitat of this oak species with more certainty. Based on the insights obtained from the results of such studies, the protection and restoration planning of the habitat of this key species, which supports diverse species, will be provided more efficiently.

An ensemble modeling approach to predict spatial risk patches of the Persian leopard-livestock conflicts in Lorestan Province, Iran

This study was conducted in the Lorestan Province in the west of Iran with two objectives of identifying major environmental variables in spatial risk modeling and identifying spatial risk patches of livestock predation by the Persian leopard. An ensemble approach of three models of maximum entropy (MaxEnt), generalized boosting model (GBM), and random forest (RF) were applied for spatial risk modeling. Our results revealed that livestock density, distance to villages, forest density, and human population density were the most important variables in spatial risk modeling of livestock predation by the leopard. The center of the study area had the highest probability of livestock predation by the leopard. Ten spatial risk patches of livestock predation by the leopard were identified in the study area. In order to mitigate the revenge killing of the leopards, the findings of this study highlight the imperative of implementing strategies by the Department of Environment (DoE) to effectively accompany the herds entering the wildlife habitats with shepherds and a manageable number of guarding dogs. Accordingly, the identified risk patches in this study deserve considerable attention, especially three primary patches found in the center and southeast of Lorestan Province.

Habitat suitability and connectivity implications for the conservation of the Persian leopard along the Iran-Iraq border

Habitat fragmentation has major negative impacts on wildlife populations, and the connectivity could reduce these negative impacts. This study was conducted to assess habitat suitability and structural connectivity of the Persian leopard along the Iran-Iraq border (i.e., the Zagros Mountains) and compare the situation of identified core habitats and connectivity with existing conservation areas (CAs). An ensemble modeling approach resulting from five models was used to predict habitat suitability. To identify core habitats and corridors along the Iran-Iraq border, factorial least-cost path analyses were applied. The results revealed that topographic roughness, distance to CAs, annual precipitation, vegetation/cropland density, and distance to rivers were the most influential variables for predicting the occurrence of the Persian leopard in the study area. By an estimated dispersal distance of 82 km (suggested by previous studies), three core habitats were identified (two cores in Iran and one core in Iraq). The largest cores were located in the south and the center of the study area, which had the highest connectivity priorities. The connectivity from these cores was maintained to the core within the Iraqi side. Only about one-fifth of detected core habitats and relative corridors were protected by CAs in the study area. Detected core habitats and connectivity areas in this study could be an appropriate road map to accomplish the CAs network along the Iran-Iraq border regarding Persian leopard conservation. Establishing transboundary CAs, particularly in the core habitat located in the center of the study area, is strongly recommended to conserve existing large carnivores, including the Persian leopard.