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Community forest management in Indonesia: Avoided deforestation in the context of anthropogenic and climate complexities

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TLDR
In this paper, the authors evaluated the extent to which deforestation has been avoided as a result of the Indonesian government's community forestry scheme, Hutan Desa (Village Forest).
Abstract
Community forest management has been identified as a win-win option for reducing deforestation while improving the welfare of rural communities in developing countries. Despite considerable investment in community forestry globally, systematic evaluations of the impact of these policies at appropriate scales are lacking. We assessed the extent to which deforestation has been avoided as a result of the Indonesian government’s community forestry scheme, Hutan Desa (Village Forest). We used annual data on deforestation rates between 2012 and 2016 from two rapidly developing islands: Sumatra and Kalimantan. The total area of Hutan Desa increased from 750 km2 in 2012 to 2500 km2 in 2016. We applied a spatial matching approach to account for biophysical variables affecting deforestation and Hutan Desa selection criteria. Performance was assessed relative to a counterfactual likelihood of deforestation in the absence of Hutan Desa tenure. We found that Hutan Desa management has successfully achieved avoided deforestation overall, but performance has been increasingly variable through time. Hutan Desa performance was influenced by anthropogenic and climatic factors, as well as land use history. Hutan Desa allocated on watershed protection forest or limited production forest typically led to a less avoided deforestation regardless of location. Conversely, Hutan Desa granted on permanent or convertible production forest had variable performance across different years and locations. The amount of rainfall during the dry season in any given year was an important climatic factor influencing performance. Extremely dry conditions during drought years pose additional challenges to Hutan Desa management, particularly on peatland, due to increased vulnerability to fire outbreaks. This study demonstrates how the performance of Hutan Desa in avoiding deforestation is fundamentally affected by biophysical and anthropogenic circumstances over time and space. Our study improves understanding on where and when the policy is most effective with respect to deforestation, and helps identify opportunities to improve policy implementation. This provides an important first step towards evaluating the overall effectiveness of this policy in achieving both social and environmental goals.

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Primates in peril: the significance of Brazil, Madagascar, Indonesia and the Democratic Republic of the Congo for global primate conservation

TL;DR: The anthropogenic pressures each country is facing that place their primate populations at risk are examined and the key challenges faced by the four countries to avert primate extinctions now and in the future are listed.
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Does oil palm agriculture help alleviate poverty? A multidimensional counterfactual assessment of oil palm development in Indonesia

TL;DR: This article examined the association between the development of oil palm plantations and change in objective or material well-being between 2000 and 2014 across villages in Kalimantan, Indonesian Borneo, and found that plantations developed in remote villages with higher forest cover, in which the majority of communities previously relied on subsistence-based livelihoods.
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Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images

TL;DR: In this article, a multi-class oil palm detection approach (MOPAD) was proposed to reap both accurate detection of oil palm trees and accurate monitoring of their growing status from UAV images, which achieved an F1score of 87.91% (Site 1) and 99.04% (site 2) for overall oil palm tree detection, and outperformed other state-of-the-art object detection methods by a remarkable margin of 10.37-17.09% and 8.14-21.32% with respect to the average F1-score for
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Forest landscape restoration for livelihoods and well-being

TL;DR: In this paper, the authors present a simple framework to understand environmental and social effects of forest landscape restoration interventions and review the evidence linking FLR to livelihood and well-being outcomes.
References
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Journal ArticleDOI

A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity

Halbert White
- 01 May 1980 - 
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
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Greedy function approximation: A gradient boosting machine.

TL;DR: A general gradient descent boosting paradigm is developed for additive expansions based on any fitting criterion, and specific algorithms are presented for least-squares, least absolute deviation, and Huber-M loss functions for regression, and multiclass logistic likelihood for classification.
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High-Resolution Global Maps of 21st-Century Forest Cover Change

TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
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The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales

TL;DR: The TRMM Multi-Satellite Precipitation Analysis (TMPA) as discussed by the authors provides a calibration-based sequential scheme for combining precipitation estimates from multiple satellites, as well as gauge analyses where feasible, at fine scales.
Journal ArticleDOI

Propensity score-matching methods for nonexperimental causal studies

TL;DR: In this article, the authors consider causal inference and sample selection bias in nonexperimental settings in which few units in the nonex-experiment comparison group are comparable to the treatment units, and selecting a subset of comparison units similar to treatment units is difficult because units must be compared across a high-dimensional set of pre-treatment characteristics.
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