Open Access
Geocarto International, volume 37, issue 27, pages 15235-15251
Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory
Publication type: Journal Article
Publication date: 2022-07-07
Journal:
Geocarto International
Quartile SCImago
Q1
Quartile WOS
Q2
Impact factor: 3.8
ISSN: 10106049, 17520762
Water Science and Technology
Geography, Planning and Development
Abstract
This paper presents an approach to studying rangeland degradation by using remote sensing data, geographic information systems, and ecological niche theory. The role of environmental factors and land use in the spatial distribution of degraded rangelands in the Central Caucasus was assessed. Degradation stages were modelled in R using ENVIREM predictors, VIF test to select noncorrelated variables, ENMeval package to select the optimal model parameters, and the Maxent method to develop distribution models in the dismo package. Selected models had AUCtest, AUCtrain and CBI values close to 1, deltaAICc and AUCdiff values close to 0, and quite low AICc values. Environmental predictors of climate type (Thornthwaite aridity index and Emberger’s pluviothermic quotient) were explanatory variables for least disturbed rangelands, while topography (Terrain roughness index) largely explained the distribution of most disturbed grasslands. Quantitative (Schoener’s D) and graphical (Kernel density estimation, analysis of predictive maps) assessment revealed a significant overlap of ‘ecological niches’ and potential ranges of grasslands at different degradation stages, which indirectly supports the hypothesis of the important role of overgrazing in their degradation. Livestock management is likely to help restore disturbed mountain meadow steppes to steppe grasslands. Restoration of the arid shrub ecosystems to steppe grasslands or meadow steppes probably requires additional agricultural practices.
Citations by journals
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1
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Journal of Fungi
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Journal of Fungi
1 publication, 33.33%
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Environmental Monitoring and Assessment
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Environmental Monitoring and Assessment
1 publication, 33.33%
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Ecological Indicators
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Ecological Indicators
1 publication, 33.33%
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1
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Citations by publishers
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1
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
1 publication, 33.33%
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Springer Nature
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Springer Nature
1 publication, 33.33%
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Elsevier
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Elsevier
1 publication, 33.33%
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1
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- We do not take into account publications that without a DOI.
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- Statistics recalculated weekly.
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Chadaeva V., Pshegusov R. Kh. Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory // Geocarto International. 2022. Vol. 37. No. 27. pp. 15235-15251.
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Chadaeva V., Pshegusov R. Kh. Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory // Geocarto International. 2022. Vol. 37. No. 27. pp. 15235-15251.
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TY - JOUR
DO - 10.1080/10106049.2022.2096701
UR - https://doi.org/10.1080%2F10106049.2022.2096701
TI - Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory
T2 - Geocarto International
AU - Chadaeva, Victoria
AU - Pshegusov, R Kh
PY - 2022
DA - 2022/07/07 00:00:00
PB - Taylor & Francis
SP - 15235-15251
IS - 27
VL - 37
SN - 1010-6049
SN - 1752-0762
ER -
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@article{2022_Chadaeva,
author = {Victoria Chadaeva and R Kh Pshegusov},
title = {Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory},
journal = {Geocarto International},
year = {2022},
volume = {37},
publisher = {Taylor & Francis},
month = {jul},
url = {https://doi.org/10.1080%2F10106049.2022.2096701},
number = {27},
pages = {15235--15251},
doi = {10.1080/10106049.2022.2096701}
}
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MLA
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Chadaeva, Victoria, and R Kh Pshegusov. “Identification of degradation factors in mountain semiarid rangelands using spatial distribution modelling and ecological niche theory.” Geocarto International, vol. 37, no. 27, Jul. 2022, pp. 15235-15251. https://doi.org/10.1080%2F10106049.2022.2096701.