Spatial database of planted forests in East Asia.

Planted forests are critical to climate change mitigation and constitute a major supplier of timber/non-timber products and other ecosystem services. Globally, approximately 36% of planted forest area is located in East Asia. However, reliable records of the geographic distribution and tree species composition of these planted forests remain very limited. Here, based on extensive in situ and remote sensing data, as well as an ensemble modeling approach, we present the first spatial database of planted forests for East Asia, which consists of maps of the geographic distribution of planted forests and associated dominant tree genera. Of the predicted planted forest areas in East Asia (948,863 km2), China contributed 87%, most of which is located in the lowland tropical/subtropical regions, and Sichuan Basin. With 95% accuracy and an F1 score of 0.77, our spatially-continuous maps of planted forests enable accurate quantification of the role of planted forests in climate change mitigation. Our findings inform effective decision-making in forest conservation, management, and global restoration projects.

Rates and drivers of aboveground carbon accumulation in global monoculture plantation forests.

Restoring forest cover is a key action for mitigating climate change. Although monoculture plantations dominate existing commitments to restore forest cover, we lack a synthetic view of how carbon accumulates in these systems. Here, we assemble a global database of 4756 field-plot measurements from monoculture plantations across all forested continents. With these data, we model carbon accumulation in aboveground live tree biomass and examine the biological, environmental, and human drivers that influence this growth. Our results identify four-fold variation in carbon accumulation rates across tree genera, plant functional types, and biomes, as well as the key mediators (e.g., genus of tree, endemism of species, prior land use) of variation in these rates. Our nonlinear growth models advance our understanding of carbon accumulation in forests relative to mean annual rates, particularly during the next few decades that are critical for mitigating climate change.

Protecting biodiversity and economic returns in resource-rich tropical forests.

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. Here we demonstrate that conservation solutions that effectively balance the protection of biodiversity and economic revenues are possible in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimise the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon, across a range of opportunity costs (i.e. sacrifices of extractive profit). For such an optimisation, giving up 5% of a year's oil profits (US$ 221 million) allows for a protected area network that retains of an average of 65% of the extent of each species/ecosystem. This performance far exceeds that of the network produced by simple land area optimisation which requires a sacrifice of approximately 40% of annual oil profits (US$ 1.7 billion), and uses only marginally less land, to achieve equivalent levels of ecological protection. Applying spatial statistics to remotely sensed, historic deforestation data, we further focus the optimisation to areas most threatened by imminent forest loss. We identify Emergency Conservation Targets: areas that are essential to a cost-effective conservation reserve network and at imminent risk of destruction, thus requiring urgent and effective protection. Governments should employ the methods presented here when considering extractive led development options, to responsibly manage the associated ecological-economic trade-offs and protect natural capital. Article Impact Statement: Governments controlling resource extraction from tropical forests can arrange production and conservation to retain biodiversity and profits. This article is protected by copyright. All rights reserved.