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Tropical Deciduous Forests of South Asia: Monitoring Degradation and Assessing Impacts of Urbanization
Project Start Date
04/01/2017
Project End Date
03/31/2022
Grant Number
NNX17AI24G
Project Call Name
Regional_Initiative_Name
Region
Solicitation
default

Team Members:

Person Name Person role on project Affiliation
Ruth DeFries Principal Investigator Columbia University, New York, US
Pinki Mondal Co-Investigator University of Delaware, Newark,, US
Johannes Urpelainen Co-Investigator Johns Hopkins University School of Advanced International Studies , Director and Prince Sultan bin Abdulaziz Professor of Energy, Resources and Environment, Washington DC, US
Harini Nagendra Collaborator Azim Premji University, Bangalore, India
Q. Qureshi Collaborator Wildlife Institute of India, Dehradun, India
Abstract

This project proposes to 1) develop remote-sensing methods to monitor forest degradation and regeneration in tropical deciduous forests of South Asia and 2) assess how off-farm employment associated with urbanization alters uses of forest resources that lead to degradation. While remote sensing to map deforestation are now welldeveloped, methods for mapping degradation (i.e. reduction in biomass or canopy cover) and regeneration are more complex and less mature. Moreover, considerable research has examined urban demands for agricultural commodities on deforestation. But the impact on forest resources of increasing urban migration and off-farm employment in South Asia, where rural populations rely heavily on forests for energy, fodder and incomegeneration from non-timber forest products, is not well understood. We will focus on a study region in central India, a globally important landscape for tiger conservation and home to millions of people whose livelihoods depend on forest resources. The region covers 250,000 sq. km. (approximately 8 percent of Indias land area). Remaining patches of tropical deciduous forests, the native vegetation, provide crucial connectivity for large mammals to travel between protected areas. Similar to other places in South Asia, rapid urbanization is generating off-farm employment that is changing resource use in rural households. Consequences for forest degradation and regeneration are not currently known. For example, increased income from off-farm employment could exacerbate grazing pressures through increased cattle ownership or alleviate pressures through reduced reliance on fuelwood. The project builds on our experience in the study region, prior work on remote sensing of forests, and household surveys on resource use in India. Initial efforts to map changes in biomass in the study region using L-band ALOS PALSAR and Landsat data show moderate success. Recently available radar (e.g., ALOS PALSAR 2, Sentinel 1 C-band) and optical (Sentinel 2, Quickbird and other very high resolution sensors) open opportunities to further develop methods for mapping forest degradation and regeneration. We will collect approximately 100 biomass measurements across the landscape to test multiple algorithms to predict biomass. We will interpret optical data to identify visible signs of degradation such as footpaths. The goal of the remote sensing analysis is to identify the data sources and algorithms to monitor forest degradation and regeneration efficiently, accurately, and with as minimal data processing as possible. The ultimate objective is to establish an operational monitoring system, maintained by Indian scientists, which will enable targeting efforts to reduce degradation, such as alternative livelihood projects, evaluate effectiveness of such efforts, and monitor progress towards reforestation goals. The social science aspect of the project will identify how rapid urbanization is changing demand for forest products and hence altering patterns of forest degradation and regeneration. We will develop a sampling strategy for 5,000 household surveys in 500 villages to cover the range of conditions across the study region. The surveys will quantify cattle ownership, dependence on fuelwood for energy, and collection of nontimber forest products in relation to off-farm employment and migration of family members to urban areas. We will test whether resource use is statistically related to employment of household members in urban areas (controlling for confounding factors). Results will indicate whether future urbanization is likely to alleviate pressures and lead to forest regeneration or to exacerbate pressures and lead to further degradation.

Project Research Area

Project Documents

Year Authors Type Title
2021 Publications Baquie, S., J. Urpelainen, S. Khanwilkar, C. Galletti, N. Velho, P. Mondal, H. Nagendra, and R. DeFries. "Migration, Assets, and Forest Degradation in a Tropical Deciduous Forest of South Asia." Ecological Economics 106887 (2020).
2021 Ruth DeFries Meghna Agarwala Publications DeFries, R., Agarwala, M., Baquie, S., Choksi, P., Khanwilkar, S., Mondal, P., Nagendra, H., & Uperlainen, J. (2021). Improved household living standards can restore dry tropical forests. Biotropica, 00, btp.12978. https://doi.org/10.1111/btp.12978
2021 Publications Choksi, P., D. Singh, J. Singh, P. Mondal, H. Nagendra, J. Urpelainen, and R. DeFries. "Sensitivity of Seasonal Migration to Climatic Variability in Central India." Environmental Research Letters (submitted).
2021 Sarika Khanwilkar Publications Khanwilkar, S., C. Gould, R. DeFries, B. Habib, and J. Urpelainen. "LPG Adoption by Marginalized, Forest-Fringe Populations in Central India." Energy Policy (in press).
2020 Pinki Mondal Publications Mondal, Pinki, Sonali Shukla McDermid, and Abdul Qadir. "A Reporting Framework for Sustainable Development Goal 15: Multi-Scale Monitoring of Forest Degradation Using Modis, Landsat and Sentinel Data." Remote Sensing of Environment 237 (2020): 111592.
2020 Ruth DeFries Sandra Basque Publications DeFries, R., Agarwala, M., Baquie, S., Choksi, P., Dogra, N., Preetha, G.S., Khanwilkar, S., Mondal, P., Nagendra, H., ; Urpelainen, J. , Post-lockdown spread of COVID-19 from cities to vulnerable forest-fringe villages in Central India , Curr. Sci. ; 1(119): 52-58, 20200710.