Abstract

The interactions between climate and land‐use change are dictating the distribution of flora and fauna and reshuffling biotic community composition around the world. Tropical mountains are particularly sensitive because they often have a high human population density, a long history of agriculture, range‐restricted species, and high‐beta diversity due to a steep elevation gradient. Here we evaluated the change in distribution of woody vegetation in the tropical Andes of South America for the period 2001–2014. For the analyses we created annual land‐cover/land‐use maps using MODIS satellite data at 250 m pixel resolution, calculated the cover of woody vegetation (trees and shrubs) in 9,274 hexagons of 115.47 km2, and then determined if there was a statistically significant (p < 0.05) 14 year linear trend (positive—forest gain, negative—forest loss) within each hexagon. Of the 1,308 hexagons with significant trends, 36.6% (n = 479) lost forests and 63.4% (n = 829) gained forests. We estimated an overall net gain of ~500,000 ha in woody vegetation. Forest loss dominated the 1,000–1,499 m elevation zone and forest gain dominated above 1,500 m. The most important transitions were forest loss at lower elevations for pastures and croplands, forest gain in abandoned pastures and cropland in mid‐elevation areas, and shrub encroachment into highland grasslands. Expert validation confirmed the observed trends, but some areas of apparent forest gain were associated with new shade coffee, pine, or eucalypt plantations. In addition, after controlling for elevation and country, forest gain was associated with a decline in the rural population. Although we document an overall gain in forest cover, the recent reversal of forest gains in Colombia demonstrates that these coupled natural‐human systems are highly dynamic and there is an urgent need of a regional real‐time land‐use, biodiversity, and ecosystem services monitoring network.

Highlights

  • Land‐cover change, the distribution of woody vegeta‐ tion, plays a key role in conservation of biodiversity and ecosystem services such as watershed and soil protection, carbon sequestra‐ tion, and food production

  • We focus on the change in woody vegetation above 1,000 m between 2001 and 2014, based on a land‐use classifica‐ tion derived from MODIS satellite data at 250‐m pixel resolution

  • 1,500 m, the domi‐ nant pattern was forest gain mainly due to abandoned pastures and small‐scale agriculture associated with rural–urban migration and woody vegetation densification and encroachment into the montane grasslands and paramo

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Summary

| INTRODUCTION

Land‐cover change, the distribution of woody vegeta‐ tion, plays a key role in conservation of biodiversity and ecosystem services such as watershed and soil protection, carbon sequestra‐ tion, and food production. Andean wetlands are changing in relation to cli‐ mate‐induced glacier recession (Polk et al, 2017) These new abiotic conditions are expected to promote the encroachment of shrubs and trees into tropical montane grasslands and paramos (Helmer et al, 2019). A decrease in forest cover is expected in regions where in‐ creasing temperatures force crops (e.g., coffee or potato) to higher elevations or where socioeconomic conditions promote rural devel‐ opment and new agricultural activity (e.g., Colombian Peace agree‐ ment). At the highest elevations (e.g., tropical alpine grasslands, paramo, puna), increasing temperatures could facilitate the encroachment of trees and shrubs These scenarios highlight the urgent need to understand how the spatiotemporal interactions be‐ tween human and natural systems are changing the distribution of biodiversity, ecosystem services, and socioeconomic environment in the Andes. (1) we determine how the distribution of woody vegeta‐ tion is changing at the scale of the Andes, within each country, and along the elevation gradient; (2) we relate changes in woody vegeta‐ tion with country, elevation, slope, nighttime lights, and population change; and (3) we document the drivers of change in “hotspots” of forest loss and gain based on local expert knowledge, literature, and sources of high resolution imagery (e.g., Google Earth)

| METHODS
Findings
| DISCUSSION
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