Demographic changes have also been important to forest recovery. Although Nepali villagers have migrated to India for seasonal and military work for centuries, migration to Gulf countries, Southeast Asia and beyond has exploded since the 1990s.

Migrants’ families often abandon marginal farmland because they lack the manpower to use it, allowing forests to naturally regenerate. Likewise, the families often harvest fewer forest products, like firewood, because they have more money to purchase alternatives, such as LPG. Fox’s team found that areas of Nepal where people receive the most remittances have also experienced greatest reforestation.

The data also indicate that Nepal’s forest gains have been concentrated in the midhills. This is not surprising, because community forests are widespread in this region and outmigration and agricultural land abandonment are increasingly common. The data also show that forests have expanded in the Tarai, despite greater population growth, fewer community forests and more conflicts over resources there. However, gains in the Tarai — and in the mountains — have been smaller than in the midhills.

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Importantly, forest extent is not the same thing as ecological value, which can vary greatly from forest to forest. For example, young, dry, and isolated forests do not provide as good wildlife habitat as old-growth and riverine forests, or forests located along wildlife corridors. Similarly, a forest on a steep slope helps reduce soil erosion, giving it conservation value that a forest in a flat area may not have.

Fox’s team is not the first to analyse Nepal’s forest cover change using satellite imagery. A group at the University of Maryland (GlobalForestWatch.org) has monitored forest change globally since 2000. In Nepal, its data show there has been forest loss — the opposite of Fox’s team’s findings. This data has been cited by numerous academic studies and the media, including this newspaper.

Both the old and new data were generated using computer algorithms that look at historical satellite images to determine — based on the colour and shade of pixels in each photograph — what is forest and what is not. Forests are considered to be any area with at least 50% canopy cover — meaning that, looking from the air, at least half of the ground is obscured by trees. (This may not sound like much, but the FAO standard is only 10%.)

While the Maryland team used algorithms designed for application around the world, Fox’s team have created algorithms specifically tailored for Nepal. Alex Smith, a member of Fox’s team who is also a PhD candidate at Oregon State University and a current Fulbright-Hays scholar in Kathmandu, says that image-analysis algorithms designed for worldwide use can be inaccurate in Nepal because of the mountainous terrain.

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