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Predicting the current and future potential spatial distribution of endangered Rucervus eldii eldii (Sangai) using MaxEnt model

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Abstract

Ecological factors that control the species distribution patterns at various spatiotemporal scales will get affected by climate change. To combat the situation, in the past few decades geographical information system (GIS) and remote sensing have been widely used by the researchers in the field of wildlife and habitat suitability modeling. The main objective of this study is to map and predict the current and future habitat suitability potential of Rucervus eldii eldii in Keibul Lamjao National Park (KLNP) using MaxEnt. Presence location data of the species, topographic factors, and bio-climatic variables were used as input in the MaxEnt software to map current habitat suitability potential. To map the habitat suitability potential for future, two representative concentration pathway (RCP) scenarios RCP 2.6 and RCP 8.5 for the years 2050 and 2070 were used. The model returned an average AUC value of 0.944 which indicates the model to be sensitive and descriptive. Isothermality and precipitation in the wettest quarter were found to be two most significant variables. The suitable range of precipitation in the wettest quarter for Rucervus eldii eldii varies from 1365 to 1410 mm with an optimal value of 1405 mm and isothermality from 46.43 to 46.6% with an optimal value of 46.5%. Current habitat suitability results of the model show 0.45 km2 of the area under no potential, 29.25 km2 of the area under least potential, 8.29 km2 of the area under moderate potential, 9.21 km2 of the area under good potential, and 8.82 km2 of the area under high potential. Both RCPs for the years 2050 and 2070 show the decreasing trend in the area under high suitability potential and increasing trend under no suitability potential. The results of this study can provide aid in the management and protection of Rucervus eldii eldii.

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Data availability

The datasets used during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors express their heartfelt gratitude to the National Remote Sensing Centre (NRSC), WorldClim and Forest Department, Government of Manipur, for providing the valuable database.

Funding

The research outcome of this study was funded in form of project under the third phase of Technical Education Quality Improvement Programme (TEQIP-III), National Institute of Technology, Manipur (NIT-M).

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Manipur, Imphal, India, 795004

    Vicky Anand, Bakimchandra Oinam & Irom Hamilton Singh

Authors
  1. Vicky Anand
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  2. Bakimchandra Oinam
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  3. Irom Hamilton Singh
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Contributions

BO and VA conceived the idea and designed the experiment. IHS collected and compiled the field data. Writing and editing was done by VA. Both VA and BO analyzed the result. All the authors read and approved the manuscript.

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Correspondence to Vicky Anand.

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Anand, V., Oinam, B. & Singh, I.H. Predicting the current and future potential spatial distribution of endangered Rucervus eldii eldii (Sangai) using MaxEnt model. Environ Monit Assess 193, 147 (2021). https://doi.org/10.1007/s10661-021-08950-1

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