Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory

Чадаева, В. А.; Pshegusov, Rustam

doi:10.1080/10106049.2022.2096701

Cited by 3 publications

(1 citation statement)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Second, our model included a set of 16 climate and two topographic variables (the ENVIREM dataset downloaded from http://envirem.github.io (accessed on 20 January 2023); Table 1), many of which were likely to have direct relevance to ecological or physiological processes determining species distributions [49][50][51][52]. The included topographic variables were potentially important as well because they could modify the effect of the climate descriptors.…”

Section: Methodsmentioning

confidence: 99%

Modeling the Distribution of the Chytrid Fungus Batrachochytrium dendrobatidis with Special Reference to Ukraine

Tytar

Nekrasova

Pupins

et al. 2023

JoF

View full text Add to dashboard Cite

Amphibians are the most threatened group of vertebrates. While habitat loss poses the greatest threat to amphibians, a spreading fungal disease caused by Batrachochytrium dendrobatidis Longcore, Pessier & D.K. Nichols 1999 (Bd) is seriously affecting an increasing number of species. Although Bd is widely prevalent, there are identifiable heterogeneities in the pathogen’s distribution that are linked to environmental parameters. Our objective was to identify conditions that affect the geographic distribution of this pathogen using species distribution models (SDMs) with a special focus on Eastern Europe. SDMs can help identify hotspots for future outbreaks of Bd but perhaps more importantly identify locations that may be environmental refuges (“coldspots”) from infection. In general, climate is considered a major factor driving amphibian disease dynamics, but temperature in particular has received increased attention. Here, 42 environmental raster layers containing data on climate, soil, and human impact were used. The mean annual temperature range (or ‘continentality’) was found to have the strongest constraint on the geographic distribution of this pathogen. The modeling allowed to distinguish presumable locations that may be environmental refuges from infection and set up a framework to guide future search (sampling) of chytridiomycosis in Eastern Europe.

show abstract

Section: Methodsmentioning

confidence: 99%