Search

Globally, amphibians are one of the most threatened vertebrate groups and are hypersensitive to human-imposed habitat changes. Here we explore ways to conserve amphibians in two of the least-known biodiversity hotspots on earth, the Caucasus and Irano–Anatolian regions. We used two techniques: (ⅰ) combining species richness, endemism, and endangerness indices and (ⅱ) a species distribution model (SDM) to identify high-priority areas for Iran's seven endemic and/or threatened amphibian species. The identified amphibian high-priority areas were then targeted to assess the levels of protection granted by the network of conservation areas (CAs) in Iran. We also computed the species-specific extent of occurrence (EOO) and the area of occupancy (AOO) to detect conservation gaps for the targeted species. Our results indicate that amphibian high-priority areas in Iran are mostly distributed across the Hyrcanian forest in the north and Zagros Mountains in the west. The gap analysis revealed that based on the most optimistic metric, 40% of amphibian hotspots are covered by CAs in Iran. However, the species-specific gap analysis showed that Iran's CAs perform poorly at representing the EOO of all of the endemic and/or threatened amphibian species. These results suggest that expansion of CAs in Iran is essential for amphibian conservation. [ABSTRACT FROM AUTHOR]

The spatial distribution modeling can simulate the suitability of species habitats on different spatial scales, based on species records and site characteristics to gain insight into ecological, and evolutionary drivers or help predict habitat suitability across large scales. Species distribution models (SDMs) based on presence-absence or presence-only data are widely used in biogeography to indicate the ecological niche and predict the geographical distribution of species habitats. Although presence-absence data is generally of higher quality, it is also less common than presence-only data because it requires more rigorous planning to visit a set of pre-determined sites. Among the algorithms available, the MaxEnt approach is one of the most widely used methods of developing habitat modeling. The MaxEnt uses maximum entropy to generalize specific observations of presence-only data and does not require data where the species is absent within the theoretical framework. This study aims to predict the suitable habitat for Goitered gazelle (Gazella subgutturosa) in the Samelghan plain in northeastern Iran. The results showed that the variables of the Mediterranean climate classes, slope 0-5% class, and semi-dense pastures with type Acantholimon-Astragalus are more important than other environmental variables used in modeling. The area under the curve (AUC), Receiver Operating Characteristic (ROC), and the classification threshold illustrate the model performance. Based on the ROC (AUC=0.99) results in this study, it was found that Maxent's performance was very good. [ABSTRACT FROM AUTHOR]

The dramatic rise of human population growth and urban development, especially in developing countries, has led to a decline in the quality, fragmentation and isolation of habitats which support rare or endangered fauna species. New areas designed to protect such species and form corridors and networks to support populations are needed. Two rare species of Chinkara and Blanford's fox habitats in Isfahan Province are used to evaluate the optimal method to determine suitable habitat. Eight statistical methods, including four widely-used methods (SVM, Random Forest, GBM and MARS) and five new methods (XGBtree, XGBLinear, Treebag and SVMRadial) are evaluated in this study; to do so two Modis products and 19 worldclim parameters are applied. In addition, the ensemble of these methods was applied using gap analysis and areas with potential for protection were prioritized. Finally, minimum cost analysis was utilized to identify possible corridors between new areas and current protected areas. Results demonstrate that the eastern parts of Isfahan province have the highest potential for these two species, and because of the diverse habitats demands for these two species, the regions are able to support a large number of fauna and flora species. [ABSTRACT FROM AUTHOR]

Oligochaetes are the most abundant benthic taxa in aquatic ecosystems that play an important role in food webs. The present study aims to assess the diversity and origin of Eiseniella tetraedra as a non-native species in the Lar National Park of Iran and also its response to current and future climate change. We obtained the specimen from rivers and sequenced the mitochondrial gene Cytochrome Oxidase subunit I (COI) and combined them with 117 sequences from the Jajroud and Karaj rivers in Iran and native regions from GenBank (NCBI). We also ran Species Distribution Modelings (SDMs) using an ensemble model approach that was estimated according to two shared socio-economic pathways (SSPs): 126 and 585 of the MRI-ESM2 based on CMIP6. According to the results, all the samples examined in the current study originated from Spanish rivers, and no unique haplotype was found in the Lar National Park. Moreover, the results also show high haplotype diversity that can positively affect the success of this non-native species in different freshwater. Also, the results of SDMs depict that climate change would remarkably affect the distribution of E. tetraedra and it verifies the invasion power of E. tetraedra in Iran's freshwater ecosystems over time., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2023. Published by The Company of Biologists Ltd.)