Abstract
Tree planting is widely promoted as a cost-effective natural climate solution, yet there are few evaluations of the implementation of tree planting. Our analysis of a unique dataset on tree planting in the Indian Himalayan state of Himachal Pradesh shows that over half of the state's budget for tree planting is wasted on plantations that are unlikely to survive and/or are poorly designed to achieve the state's goal of increasing forest cover. Himachal Pradesh (and India more generally) has been identified as a high potential area for natural climate solutions due to high government capacity, adequate funding, and government agencies with extensive planting experience. We combine data on the location and financial outlay for plantations, which allow us to analyze the relationship between plantations and social and biophysical conditions, with a machine learning model, trained on past land cover change, which predicts the likelihood of future tree cover loss in plantation areas. Our finding that even in this high potential area tree planting programs involve considerable wasted expenditure on ineffective plantations raises questions about optimistic assessments of the potential for tree planting to serve as a cost-effective natural climate solution. We suggest deemphasizing the target-based approaches that dominate present policy-making and high-profile scientific publications, which we argue are the cause of wasted expenditures in Himachal Pradesh. Instead policy-makers and scientists interested in natural climate solutions should focus on developing solutions that respond to local biophysical, social, and economic realities, and are implemented through transparent procedures that increase accountability to and reinforce the rights of forest dependent people.
| Original language | English (US) |
|---|---|
| Article number | 105864 |
| Journal | World Development |
| Volume | 154 |
| DOIs | |
| State | Published - Jun 2022 |
Bibliographical note
Funding Information:We thank anonymous reviewers for comments on an earlier draft of this paper. We are grateful to Himachal Pradesh Forest Department, Shimla for sharing data on forest polygons and tree plantations. We thank participants of NASA-SARI workshop in New Delhi in November 2019 for helpful comments. The participation of PR (a portion of his time), FF and VR on this project was funded by a grant from the NASA LCLUC program (NNX17AK14G).
Funding Information:
We thank anonymous reviewers for comments on an earlier draft of this paper. We are grateful to Himachal Pradesh Forest Department, Shimla for sharing data on forest polygons and tree plantations. We thank participants of NASA-SARI workshop in New Delhi in November 2019 for helpful comments. The participation of PR (a portion of his time), FF and VR on this project was funded by a grant from the NASA LCLUC program (NNX17AK14G).
Publisher Copyright:
© 2022 Elsevier Ltd
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- Forests
- Himalaya
- Machine Learning
- Natural climate solutions
- Tree planting programs
- Wasteful spending
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