Abstract
Forests are among essential natural resources having implications over global freshwater distribution, carbon cycle and biodiversity. Forests are characterized by several inherent properties specifically canopy cover density and species diversity which enhance their resilience. These resources have been affected by various climatic and non-climatic stressors for the last few decades. Thus, assessment of inherent forest vulnerability is essential for lessening the forest vulnerability and increasing resilience. We used twelve site-specific factors in Darjeeling district of West Bengal in India, namely forest fragmentation, vegetation types, biological richness, disturbance index, temperature, rainfall, soil types, land use/land cover, geology, geomorphology, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) for assessing their contribution to forest vulnerability. These factors were assigned weights in Analytical Hierarchy Process (AHP) and integrated into the geographical information system (GIS) to prepare the forest vulnerability map. The results revealed that more than half the area of the district (57.3%) was high to very highly vulnerable. Forest fragmentation, NDVI, biological richness and disturbance index were identified as the most influencing factors of inherent forest vulnerability in the study area. Assessment of inherent forest vulnerability may help in articulating effective policy measures for enhancing the forest cover in priority areas. Furthermore, the study may provide a baseline for regional to local level inherent forest vulnerability assessment globally.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aziz NF, Sorooshian S, Mahmud F (2016) MCDM-AHP method in decision makings. ARPN J Eng Appl Sci 11(11):7217–7220
Behera MD, Roy PS (2010) Assessment and validation of biological richness at landscape level in part of the Himalayas and Indo-Burma hotspots using geospatial modeling approach. J Indian Soc Remote Sens 38(3):415–429
Bhattacharya SK (2009) Effect of deforestation on rainfall and runoff over the Terai and adjacent Hills in the Darjeeling district, West Bengal, India. Geograp Rev India, Kolkata 71(2):130–136
BIS (2020) Biological information system. Indian institute of remote sensing (IIRS). National Biodiversity Characterization at Landscape Level, a project jointly sponsored by Department of Biotechnology and Department of Space, Ministry of Science and Technology. https://bis.iirs.gov.in/methodology-and-approach
Chitalea VS, Shresthaa HL, Agrawala NK, Choudhurya D, Gilania H, Dhonjua HK, Murthya MSR (2014) Forest climate change vulnerability and adaptation assessment in Himalayas. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8
Cools N, De Vos B (2013) Forest soil: characterization, sampling, physical, and chemical analyses. In Developments in Environmental Science, Vol. 12, pp. 267–300. Elsevier
Dyson B (2017) Integration of life cycle assessment into decision-analytic approaches for sustainable technologies, pp 81–89. https://doi.org/10.1016/B978-0-12-409548-9.10037-5
ENVIS (2017) Centre on Himalayan ecology. http://gbpihedenvis.nic.in/State_at_glance/Assam%20and%20W.B.%20Hills/Forest_profile.pdf. Accessed on 24 April 2021
Evangelista PH, Kumar S, Stohlgren TJ, Young NE (2011) Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US. For Ecol Manage 262(3):307–316
FAO (2020). The state of world’s forests, 2020. http://www.fao.org/state-of-forests/en/. Accessed on 24th April 2021.
García-Aguirre MC, Álvarez R, Aceves F (2012) Geology and geomorphology in landscape ecological analysis for forest conservation and hazard and risk assessment, illustrated with Mexican case histories. In Earth Sciences. IntechOpen
Government of West Bengal (2021) Darjeeling: Economy. https://darjeeling.gov.in/economy/#:~:text=Present%20Status%20of%20Forests&text=Darjeeling%20district%20had%2011%2C000%20hectare,Takdah%20ranges%20have%20been%20converted. Accessed on 20 April, 2021
Intergovernmental Panel on Climate Change (IPCC) (2018) Global warming of 1.5°C Summary for Policymakers. https://report.ipcc.ch/sr15/pdf/sr15_spm_final.pdf. Accessed 22 April 2021
IUCN (2021) Deforestation and forest degradation. https://www.iucn.org/sites/dev/files/deforestation-forest_degradation_issues_brief_2021.pdf. Accessed on 22 April 2021
Khawas V (2003) Joint forest management in India with special reference to Darjeeling Himalaya. Ahmedabad, India: School of Planning, Center for Environmental Planning and Technology. http://lib.icimod.org/record/11260/files/209.pdf. Accessed on June, 30, 2018
Kumar M, Singh H, Pandey R, Singh MP, Ravindranath NH, Kalra N (2019) Assessing vulnerability of forest ecosystem in the Indian Western Himalayan region using trends of net primary productivity. Biodivers Conserv 28(8):2163–2182
Locatelli B, Kanninen M, Brockhaus M, Colfer CP, Murdiyarso D, Santoso H (2008) Facing an uncertain future: How forests and people can adapt to climate change
Madalcho AB, Mena MM, Badeso BB (2020) Causes and impacts of deforestation and forest degradation at DugunaFango Woreda. Int J Nat Res Ecol Manag 5(1):14
Manners R, Varela-Ortega C (2017) Analysing Latin American and Caribbean forest vulnerability from socio-economic factors. J Integr Environ Sci 14(1):109–130
Ministry of MSME (2019) District Industrial Profile 2018–19: DARJEELING. MSME-Development Institute Kolkata. www.msmedikolkata.gov.in. Accessed 22 April, 2021
Naeem M, Liu M, Huang J, Ding G, Potapov G, Jung C, An J (2019) Vulnerability of East Asian bumblebee species to future climate and land cover changes. Agr Ecosyst Environ 277:11–20
Nurdiana A, Risdiyanto I (2015) Indicator determination of forest and land fires vulnerability using Landsat-5 TM data (case study: Jambi Province). Procedia Environ Sci 24:141–151
Pokhriyal P, Rehman S, Areendran G, Raj K, Pandey R, Kumar M, ... Sajjad H (2020) Assessing forest cover vulnerability in Uttarakhand, India using analytical hierarchy process. Model Earth Syst Environ 1–11
Roy PS, Behera MD, Murthy MSR, Roy A, Singh S, Kushwaha SPS, ... Gupta S (2015) New vegetation type map of India prepared using satellite remote sensing: comparison with global vegetation maps and utilities. Int J Appl Earth Observ Geoinfor 39:142–159. https://doi.org/10.1016/j.jag.2015.03.003
Roy PS, Kushwaha SPS, Roy A, Karnataka H, Saran S (2013) Biodiversitycharacterizationatlandscapelevelusinggeospatialmodel. Anais XVI Simpósio Brasileiro de Sensoriamento Remoto–SBSR, Foz do Iguacu, PR, Brasil, 3321–3328
Sharma J, Ravindranath NH (2019) Applying IPCC 2014 framework for hazard-specific vulnerability assessment under climate change. Environ Res Commun 1(5):051004
Sharma J, Chaturvedi RK, Bala G, Ravindranath NH (2015) Assessing “inherent vulnerability” of forests: a methodological approach and a case study from Western Ghats, India. Mitig Adapt Strat Glob Change 20(4):573–590
Sharma J, Chaturvedi RK, Bala G, Ravindranath NH (2013) Challenges in vulnerability assessment of forests under climate change. Carbon Management 4(4):403–411
Sharma J, Upgupta S, Kumar R, Chaturvedi RK, Bala G, Ravindranath NH (2017) Assessment of inherent vulnerability of forests at landscape level: a case study from Western Ghats in India. Mitig Adapt Strat Glob Change 22(1):29–44
Singha C (2021) Marginal value of sub-watershed treatment on profit in Darjeeling district, India. Land Use Policy 101:105089. https://doi.org/10.1016/j.landusepol.2020.105089
Souissi D, Zouhri L, Hammami S, Msaddek MH, Zghibi A, Dlala M (2020) GIS-based MCDM–AHP modeling for flood susceptibility mapping of arid areas, southeastern Tunisia. Geocarto Int 35(9):991–1017
Spruce J, Bolten J, Mohammed IN, Srinivasan R, Lakshmi V (2020) Mapping land use land cover change in the Lower Mekong Basin from 1997 to 2010. Front Environ Sci 8:21
Susaeta A, Adams DC, Gonzalez-Benecke C (2017) Economic vulnerability of southern US slash pine forests to climate change. J Forest Econ 28:18–32
Thakur S, Negi VS, Pathak R, Dhyani R, Durgapal K, Rawal RS (2020) Indicator based integrated vulnerability assessment of community forests in Indian west Himalaya. For Ecol Manage 457:117674
Tse-ring K, Sharma E, Chettri N, Shrestha AB (2010) Climate change vulnerability of mountain ecosystems in the Eastern Himalayas. International centre for integrated mountain development (ICIMOD)
Upgupta S, Singh PK (2017) Impacts of coal mining: a review of methods and parameters used in India. Curr World Environ 12(1):142
Upgupta S, Sharma J, Jayaraman M, Kumar V, Ravindranath NH (2015) Climate change impact and vulnerability assessment of forests in the Indian western himalayan region: a case study of Himachal Pradesh, India. Clim Risk Manag 10:63–76
Wan JZ, Wang CJ, Qu H, Liu R, Zhang ZX (2018) Vulnerability of forest vegetation to anthropogenic climate change in China. Sci Total Environ 621:1633–1641
WWF (2018) Forests. https://explore.panda.org/forests. Accessed on 22nd April 2021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Roshani, Rahaman, H., Masroor, Rehman, S., Sajjad, H. (2022). Indicator-Based Inherent Forest Vulnerability Using Multicriteria Decision-Making Analysis in the Darjeeling District of West Bengal. In: Rani, M., Chaudhary, B.S., Jamal, S., Kumar, P. (eds) Towards Sustainable Natural Resources. Springer, Cham. https://doi.org/10.1007/978-3-031-06443-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-031-06443-2_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-06442-5
Online ISBN: 978-3-031-06443-2
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)