Assessing the climate change effects on the distribution pattern of the Azerbaijan Mountain Newt (Neurergus crocatus)

Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran

In recent years, lifestyle changes and urbanization of societies, as well as macro-environmental changes, i.e. climate changes (CCs), have caused changes in the land spatial structure and the transfer of resources between different economic sectors of the land. The development of long-term spatial development plans (SDPs) needs to be compatible with CCs, especially in hyperarid areas with low supplies and high demands. In this research, machine learning methods; including Cellular Automata (CA), Random Forest (RF) and regression models through PLUS model were used to simulate the amount of supplies and demands based on land cover (LC) maps during the years 2000, 2010 and 2020 in the hyperarid areas of Kerman, Iran. Then, the best predicted model (Kappa = 0.94, overall accuracy = 0.98) was used to simulate changes in LC classes under climate change scenarios (CCSs) for 2050. The results showed the efficiency of machine learning in simulating land cover changes (LCCs) under CCSs. Findings revealed that SDPs of these areas are not compatible under any possible consideration of CCSs. The modeling results showed that spatial development plans under CCSs is not environmentally efficient and there is no compatibility between supplies, based on agricultural lands, and demands, based on increased population, by 2050. Overall, under the scenario of RCP 8.5, man-made, agriculture and natural LC classes with 106.9, 2.9, and 18.6% changes, respectively, showed the greatest changes compared to 2020. Population control, adjustment of infrastructures, and changes in LC plans can reduce socio-economical and socio-environmental problems in the future of hyperarid areas to some extent.

A synoptic review of the Amphibians of Iran: bibliography, taxonomy, synonymy, distribution, conservation status, and identification key to the eggs, larvae, and adults

This study provides an illustrated account, a comprehensive update of the systematics, and a bibliography of the 15 species of anurans in five families, eight genera; and of the six species of urodeles in two families, four genera in Iran. Bufonidae, with eight species, is the most diverse family; Salamandridae has five species and Ranidae has four species. This study also presents updated identification keys for the eggs, larvae, and metamorphosed amphibians of Iran. We designated specimen NMW 19855.1 as neotype of Pelophylax persicus (Schneider, 1799) comb. nov.. Along with distribution maps obtained from all the reliable localities and museum specimens known at this time, the modelled habitat of species, and for the first time, the National Red List of amphibians based on the IUCN red list categories and criteria. Based on our evaluation we propose to categorize Bufo eichwaldi, Paradactylodon persicus, Neurergus derjugini, and N. kaiseri as Vulnerable at National Red List, and to move Bufotes (Calliopersa) luristanicus, B. (C.) surdus, Firouzophrynus olivaceus, and Rana pseudodalmatina from the category of Least Concern (LC) to Near Threatened (NT). The National Red List of amphibians that we propose has significant implications for endangered species management and conservation. Forty-one percent of amphibian species in Iran are endemic to the country, and more than forty percent of the Iranian amphibians are at risk of extinction. Zagros Mountain forest and Hyrcaniain forests have more than 80% (i.e. 18 species) of the diversity of Iranian amphibians. A considerable amount of scientific literature published on Iranian amphibians in Persian language is not easily accessible to researchers outside Iran. This monograph attempts to remedy the situation and provides broader access to international herpetology. We recognize that taxonomy is always in a state of flux, and the names and synonymies used here reflect our current view.

Distribution update of water deer (Hydropotes inermis) and prediction of their potential distribution in Northeast China

Human interventions have a great potential of spatially cornering and limiting species, therefore investigating the species distribution is one of the most crucial issues for managing wildlife populations and suggesting robust conservation strategies. Water deer (Hydropotes inermis) are widespread in China throughout history and are endemic to East Asia. However, they disappeared from Northeast China for years. We rediscovered the water deer in a previous study in Jilin Province, China. Then, we conducted further research in Northeast China to determine their distribution status, supplying fundamental data for the recovery and expansion of their population. An interview survey, line transect survey and infrared camera monitoring were carried out in some counties/cities in Northeast China from June to December 2021. The results showed that the water deer were distributed in Wuchang city of Heilongjiang Province, Changbai Korean Autonomous County, Baishan Municipal District, Ji'an city, Hunchun city, Huadian city, Antu County and Helong County of Jilin Province, Benxi Manchu Autonomous County, Huanren Manchu Autonomous County, Kuandian Manchu Autonomous County, Fengcheng city and Donggang city of Liaoning Province. The ensemble species distribution model constructed by sdm within the TSS of various models that were set as weight revealed that the potential distribution area of the water deer in the study area was 8764.66 km² (28.77% of the study area). Combining recent studies concerning the distribution of water deer and the current study, we updated the distribution of wild water deer in Northeast China, which is vital for their conservation worldwide.