scholarly journals Using GIS-based, regional extent habitat suitability modeling to identify conservation priority areas: A case study of the Louisiana black bear in east Texas

2013 ◽  
Vol 77 (8) ◽  
pp. 1639-1649 ◽  
Author(s):  
Dan J. Kaminski ◽  
Christopher E. Comer ◽  
Nathan P. Garner ◽  
I-Kuai Hung ◽  
Gary E. Calkins
2019 ◽  
Vol 17 ◽  
pp. e00426 ◽  
Author(s):  
Fernando C.G. Bonfim ◽  
Paulo H.C. Cordeiro ◽  
Carlos A. Peres ◽  
Gustavo R. Canale ◽  
Christine S.S. Bernardo

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Huiyi Su ◽  
Manjit Bista ◽  
Mingshi Li

AbstractHabitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.


2020 ◽  
Vol 32 (1) ◽  
pp. 153-172
Author(s):  
Yun-Jin Shim ◽  
Yong-Su Park ◽  
Rae-Ha Jang ◽  
Young-Jun Yoon ◽  
Sun- Ryoung Kim ◽  
...  

2021 ◽  
Vol 124 ◽  
pp. 553-566
Author(s):  
Yi Wang ◽  
Xiaofeng Wang ◽  
Lichang Yin ◽  
Xiaoming Feng ◽  
Chaowei Zhou ◽  
...  

2021 ◽  
Vol 42 (3(SI)) ◽  
pp. 806-811
Author(s):  
N.F. Khodri ◽  
◽  
T. Lihan ◽  
M.A. Mustapha ◽  
T.M. Taher ◽  
...  

Aim: This research assessed the distribution of leopard to predict the habitat suitability in Taman Negara National Park and adjacent forest area. Methodology: Environmental factors for habitat suitability were derived from geographical information system (GIS) data such as elevation, slope, land-use, distance from urban and distance from river. Leopard presence data from 1993 to 2008 were integrated with the environmental parameters using maximum entropy (MaxEnt) modeling to assess habitat suitability across the study area. Results: The results showed that distance from river contributed the most (39.3%) in the habitat suitability modeling followed by distance from urban (31.4%), elevation (12.3%), land use types (10.1%), and slope (6.9%). Distance from river and urban showed highest contribution that influenced leopard distribution in which most suitable habitat occurred in proximity with river and further from urban. Habitat suitability of leopard were distributed among 48% over 2,218,389 ha of the study area. Interpretation: The findings of this study provides knowledge on how the species move and exploit different habitat niches for more effective conservation management. It provide models for future wildlife conservation and urban planning.


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