Biology subjects

Kafash, A.

Publications and source records attributed to Kafash, A..

3 recordsLinked to original sources

bioRxiv2025

Identifying the Levant as a potential contact and interbreeding zone for Neanderthals and modern humans

Timing of interbreeding between modern humans and Neanderthals has been subject of numerous studies but its geography remains largely unknown. Genetic evidence suggests three different interbreeding events: first in the Marine Isotope Stage (MIS) 7 ([~]250 to 200 ka), then in the MIS5 ([~]100 to 120 ka) and the final event in the MIS3 ([~]60 to 50 ka). Here, we used all known archaeological sites between 60-50 ka associated with Neanderthals and modern human presence and a set of paleoenvironmental data to reconstruct Neanderthals and modern humans habitat suitability using the Species Distribution Modeling (SDM) techniques. Assessing geographical overlap between the two species, we identify potential interbreeding zone. We found that the Levant was main potential interbreeding area of the third event. Previous research has identified the Zagros Mountains in Iran as a potential interbreeding zone during the second interbreeding event MIS5 ([~]100 to 120 ka). Compiling the results of this study to previous research can help us to better understand the dynamics of modern humans and Neanderthals interbreeding over both time and space. The two potential interbreeding areas have high priority for future research.

evolutionary biology↗

bioRxiv2024

Modeling vehicle collision risk for the jungle cat in the Hyrcanian forests of Iran: A guide for vehicle collision prevention

Wildlife-vehicle collisions are an important wildlife conservation challenge, especially for carnivores. As in other countries, vehicle collisions pose a major threat to carnivores in Iran. The jungle cat (Felis chaus) is a small carnivore species facing multiple threats, including habitat destruction, land use changes, and particularly vehicle collisions. We collected data on jungle cat collisions to model jungle cat-vehicle collision risk in the Hyrcanian forests of northern Iran. We also modeled the jungle cat vehicle collision risk in the study area but by creating 1 km and 5 km buffers around the roads and identified high vehicle collision risk areas within the 1 km and 5 km butters. We used the Maxent model to identify most important predictors of collision risk. Our models showed that areas in west of Golestan province, east of Mazandaran province, and in central parts of Gilan province faced highest vehicle collision risk for the jungle cat in the Hyrcanian forests. Human footprint and slope were the most important predictors of the jungle cat vehicle collision, with 48.3% and 17.2% contribution and with positive and negative correlation respectively. Results of variable importance were similar when modeling area was limited to a 5 km buffer zone around the roads. But when modeling area was limited to a 1 km buffer zone around the roads, slope became insignificant. Collisions more likely occur where vegetation grows immediately adjacent to roads, so clearing a roadside strip would reduce potential collisions. We recommend that high collision-risk areas we identified for jungle cat in the Hyrcanian forests be a focus for future monitoring and conservation planning.

ecology↗

bioRxiv2020

Developing snakebite risk model using venomous snake habitat suitability as an indicating factor: An application of species distribution models in public health research

Snakebite envenoming is an important public health problem in Iran, despite its risk not being quantified. This study aims to use venomous snakes habitat suitability as an indicator of snakebite risk, to identify high-priority areas for snakebite management across the country. Thus, an ensemble approach using five distribution modeling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modeling Generalized Linear Models, and Random Forest was applied to produce a spatial snakebite risk model for Iran. To achieve this, four venomous snakes habitat suitability (Macrovipera lebetina, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modeled and then multiplied. These medically important snakes are responsible for the most snakebite incidents in Iran. Multiplying habitat suitability models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi province) has the highest snakebite risk in the country. In addition, villages that were at risk of envenoming from the four snakes were identified. Results revealed that 51,112 villages are at risk of envenoming from M. lebetina, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. This paper demonstrates application of species distribution modeling in public health research and identified potential snakebite risk areas in Iran by using venomous snakes habitat suitability models as an indicating factor. Results of this study can be used in snakebite and human-snake conflict management in Iran. We recommend increasing public awareness of snakebite envenoming and education of local people in areas which identified with the highest snakebite risk.

ecology↗