Despite multiple approaches over the last several decades to harmonize conservation and development goals in the tropics, forest-dependent households remain the poorest in the world. Durable housing and alternatives to fuelwood for cooking are critical needs to reduce multi-dimensional poverty. These improvements also potentially reduce pressure on forests and alleviate forest degradation. We test this possibility in dry tropical forests of the Central Indian Highlands where tribal and other marginalized populations rely on forests for energy, construction materials, and other livelihood needs. Based on a remotely sensed measure of forest degradation and a 5000 household survey of forest use, we use machine learning (causal forests) and other statistical methods to quantify treatment effects of two improved living standards-alternatives to fuelwood for cooking and non-forest-based housing material-on forest degradation in 1, 2, and 5 km buffers around 500 villages. Both improved living standards had significant treatment effects (−0.030 ± 0.078, −0.030 ± 0.023, 95% CI), respectively, with negative values indicating less forest degradation, within 1 km buffers around villages. Treatment effects were lower with increasing distance from villages. Results suggest that improved living standards can both reduce forest degradation and alleviate poverty. Forest restoration efforts can target improved living standards for local communities without conflicts over land tenure or taking land out of production to plant trees.

Ecological restoration is crucial to mitigate climate change and conserve biodiversity, and accurately monitoring responses to restoration is imperative to guide current and future efforts. This study examines the impact of ecological restoration of a tropical dry forest in Central India. Here, the state forest department and a nongovernmental organization work with local communities to remove an invasive shrub, Lantana camara, in the forest, to assist natural regeneration, primarily for the purpose of improving access to forest resources for forest‐dependent people. We used acoustic technology to examine the bird community composition and the acoustic space used (ASU) across comparable restored, unrestored (with L. camara), and naturally low L. camara density (LLD) sites. We found no significant difference in the cumulative number of bird species detected between the site types (median in restored and LLD = 38, unrestored = 41). We found a significant difference in bird community composition across sites (r2 = 0.049, p ≤ 0.001). ASU differs between site types (r2 = 0.023, p ≤ 0.10), with restored sites positively associated with ASU compared to unrestored and LLD sites, which could represent a temporary increase in ASU as animal communities are reorganized after the complete removal of L. camara. Our results suggest that small‐scale restoration efforts that aim to help meet livelihood needs have the potential to contribute to ecological goals in this landscape. However, it is necessary to continue to monitor the regeneration trajectory in restored sites and the possible changes in the ASU.

No abstract

No abstract

Extreme climatic events and variability are on the rise around the world, with varying implications for populations across socio-economic conditions. Effective strategies for climate adaptation and development depend on understanding these differential sensitivities to climatic variability. This study focuses on a vulnerable population living in forest-fringe villages of central India, where seasonal migration is a common livelihood strategy for poor households to supplement their incomes with remittances. We quantify the relative sensitivity of a decision to migrate for the first time to climate and socio-economic variables and how the sensitivities vary for different segments of the population. We surveyed 5000 households in 500 forest-fringe villages to identify patterns of migration from 2013 to 2017. Using a mixed-effects logistic regression model, we predicted the probability of first-time migration of a household member based on climate variables and household- and district-level characteristics. We find that households in more agricultural and prosperous districts experience lower rates of migration but are more sensitive to climatic variability than households in poorer districts. The probability of first-time migration from a household in the most prosperous district increases by approximately 40% with one standard deviation in mean maximum temperature or rainfall from the 1981–2017 mean. However, the probability of migration does not vary as a function of climatic variability for households in the poorest district. We attribute this difference in sensitivities to the greater dependence on agriculture and irrigation in more prosperous districts and poverty-driven dependence on migration regardless of the climate in poorer districts. Households investing remittances from migration in agricultural intensification could become increasingly sensitive to climate variability, particularly with water shortages and projected increases in climate variability in the region. Promotion of non-agricultural livelihood options and climate-resilient agriculture could the reduce sensitivity of migration to climate variability in the study region.