Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh

Detecting the determinants of spatiotemporal distribution are important, along with the identification of drivers for the decline of the species, for ecological conservation and restoration. Here, we applied maximum entropy (Maxent)-type species-distribution modeling to investigate current and futur...

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Main Authors: Sharmin Shishir, Tanjinul Hoque Mollah, Shiro Tsuyuzaki, Naoya Wada
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:Global Ecology and Conservation
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2351989420307915
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spelling doaj-50021699bc5a4766b0f0f33d62f050a32020-12-31T04:42:22ZengElsevierGlobal Ecology and Conservation2351-98942020-12-0124e01250Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, BangladeshSharmin Shishir0Tanjinul Hoque Mollah1Shiro Tsuyuzaki2Naoya Wada3Graduate School of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan; Corresponding author. Graduate School of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan.Graduate School of Letters, Hokkaido University, Sapporo, Hokkaido, 060-0810, JapanGraduate School of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, JapanCenter for Far Eastern Studies, University of Toyama, Toyama, 930-8555, JapanDetecting the determinants of spatiotemporal distribution are important, along with the identification of drivers for the decline of the species, for ecological conservation and restoration. Here, we applied maximum entropy (Maxent)-type species-distribution modeling to investigate current and future potential distributions of an endangered canopy tree, Shorea robusta C. F. Gaertn. (Dipterocarpaceae) in Purbachal, Bangladesh. The model was constructed using 280 location records covering the entire range of S. robusta, with nine environmental variables related to climate, geography, and soil conditions included. Two scenarios [representative concentration pathways (RCPs): 4.5 and 8.5] were used to predict altered S. robusta distribution due to climate change. The precision of predicted distributions was supported sufficiently by the binomial test of omission (~P = 0.00) and area under the curve analysis (0.79–0.89). The current distributions were mostly determined by precipitation and soil nitrogen. Maxent modeling predicted that the suitable area for S. robusta forests will decline by 21% and 24% (Global Climate Models) and 26% and 28% (Regional Climate Models) relative to the present area according to ACCESS1-0 and CCSM4, respectively, under RCP8.5 by 2070 due to temperature rise, precipitation variability, seasonal dryness, and drought stress. These results showed that precipitation and soil nitrogen are important predictors of the current distribution and conservation of S. robusta forests. Furthermore, our results accentuate the potential negative impact of climate change, thereby encouraging further development of conservation and restoration plans for S. robusta by identifying suitable habitats in the region.http://www.sciencedirect.com/science/article/pii/S2351989420307915MaxentShorea robustaurban growthConservationspecies distributionclimate change
collection DOAJ
language English
format Article
sources DOAJ
author Sharmin Shishir
Tanjinul Hoque Mollah
Shiro Tsuyuzaki
Naoya Wada
spellingShingle Sharmin Shishir
Tanjinul Hoque Mollah
Shiro Tsuyuzaki
Naoya Wada
Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
Global Ecology and Conservation
Maxent
Shorea robusta
urban growth
Conservation
species distribution
climate change
author_facet Sharmin Shishir
Tanjinul Hoque Mollah
Shiro Tsuyuzaki
Naoya Wada
author_sort Sharmin Shishir
title Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
title_short Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
title_full Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
title_fullStr Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
title_full_unstemmed Predicting the probable impact of climate change on the distribution of threatened Shorea robusta forest in Purbachal, Bangladesh
title_sort predicting the probable impact of climate change on the distribution of threatened shorea robusta forest in purbachal, bangladesh
publisher Elsevier
series Global Ecology and Conservation
issn 2351-9894
publishDate 2020-12-01
description Detecting the determinants of spatiotemporal distribution are important, along with the identification of drivers for the decline of the species, for ecological conservation and restoration. Here, we applied maximum entropy (Maxent)-type species-distribution modeling to investigate current and future potential distributions of an endangered canopy tree, Shorea robusta C. F. Gaertn. (Dipterocarpaceae) in Purbachal, Bangladesh. The model was constructed using 280 location records covering the entire range of S. robusta, with nine environmental variables related to climate, geography, and soil conditions included. Two scenarios [representative concentration pathways (RCPs): 4.5 and 8.5] were used to predict altered S. robusta distribution due to climate change. The precision of predicted distributions was supported sufficiently by the binomial test of omission (~P = 0.00) and area under the curve analysis (0.79–0.89). The current distributions were mostly determined by precipitation and soil nitrogen. Maxent modeling predicted that the suitable area for S. robusta forests will decline by 21% and 24% (Global Climate Models) and 26% and 28% (Regional Climate Models) relative to the present area according to ACCESS1-0 and CCSM4, respectively, under RCP8.5 by 2070 due to temperature rise, precipitation variability, seasonal dryness, and drought stress. These results showed that precipitation and soil nitrogen are important predictors of the current distribution and conservation of S. robusta forests. Furthermore, our results accentuate the potential negative impact of climate change, thereby encouraging further development of conservation and restoration plans for S. robusta by identifying suitable habitats in the region.
topic Maxent
Shorea robusta
urban growth
Conservation
species distribution
climate change
url http://www.sciencedirect.com/science/article/pii/S2351989420307915
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