Ecological niche modelling for predicting the habitat suitability of endangered tree species Taxus contorta Griff. in Himachal Pradesh (Western Himalayas, India)

Chauhan, Saurav; Ghoshal, S. K.; Kanwal, K. S.; Sharma, Vikas; Ravikanth, G.

doi:10.1007/s42965-021-00200-2

Cited by 7 publications

(2 citation statements)

References 41 publications

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“…To match the spatial resolution of the bioclimatic layers (30 arc s), topographic data (elevation, slope, aspect, and landcover) were resampled using the bilinear interpolation technique. The selected bioclimatic and topographic parameters were tested for multicollinearity using Pearson’s correlation, and the parameters with a very strong correlation coefficient (with a value ≥ ±0.75) were excluded from further evaluation for better interpretation and generalization [ 47 ]. The processed data were then used to predict habitat suitability using ENM.…”

Section: Methodsmentioning

confidence: 99%

“…Further subtraction of specificity from 1 allows these metrics to proceed in the same direction [ 19 , 49 ]. A model with the most accurate prediction generates a curve proximal to the left axis and towards the topmost direction, whereas a model with random prediction will chase the 1:1 line [ 47 ]. Thus, the accuracy of the generated models was assessed based on the AUC value.…”

Section: Methodsmentioning

confidence: 99%

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Projected Impacts of Climate Change on the Range Expansion of the Invasive Straggler Daisy (Calyptocarpus vialis) in the Northwestern Indian Himalayan Region

Lal,

Chauhan,

Kaur

et al. 2023

Plants

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Human-induced climate change modifies plant species distribution, reorganizing ecologically suitable habitats for invasive species. In this study, we identified the environmental factors that are important for the spread of Calyptocarpus vialis, an emerging invasive weed in the northwestern Indian Himalayan Region (IHR), along with possible habitats of the weed under current climatic scenarios and potential range expansion under several representative concentration pathways (RCPs) using MaxEnt niche modeling. The prediction had a high AUC (area under the curve) value of 0.894 ± 0.010 and a remarkable correlation between the test and expected omission rates. BIO15 (precipitation seasonality; 38.8%) and BIO1 (annual mean temperature; 35.7%) had the greatest impact on the probable distribution of C. vialis, followed by elevation (11.7%) and landcover (6.3%). The findings show that, unlike the current situation, “high” and “very high” suitability areas would rise while less-suited habitats would disappear. All RCPs (2.6, 4.5, 6.0, and 8.5) indicate the expansion of C. vialis in “high” suitability areas, but RCP 4.5 predicts contraction, and RCPs 2.6, 6.0, and 8.5 predict expansion in “very high” probability areas. The current distribution of C. vialis is 21.59% of the total area of the state, with “medium” to “high” invasion suitability, but under the RCP 8.5 scenario, it might grow by 10% by 2070. The study also reveals that C. vialis may expand its niche at both lower and higher elevations. This study clarifies how bioclimatic and topographic factors affect the dispersion of invasive species in the biodiverse IHR. Policymakers and land-use managers can utilize the data to monitor C. vialis hotspots and develop scientifically sound management methods.

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Section: Methodsmentioning

confidence: 99%