• Energy Research

AbstractTropical forests modify the conditions they depend on through feedbacks at different spatial scales. These feedbacks shape the hysteresis (history-dependence) of tropical forests, thus controlling their resilience to deforestation and response to climate change. Here, we determine the emergent hysteresis from local-scale tipping points and regional-scale forest-rainfall feedbacks across the tropics under the recent climate and a severe climate-change scenario. By integrating remote sensing, a global hydrological model, and detailed atmospheric moisture tracking simulations, we find that forest-rainfall feedback expands the geographic range of possible forest distributions, especially in the Amazon. The Amazon forest could partially recover from complete deforestation, but may lose that resilience later this century. The Congo forest currently lacks resilience, but is predicted to gain it under climate change, whereas forests in Australasia are resilient under both current and future climates. Our results show how tropical forests shape their own distributions and create the climatic conditions that enable them.

Abstract Forest restoration is increasingly applied as a climate change mitigation measure. Apart from sequestering carbon, the large-scale addition of trees on Earth may enhance global precipitation levels. Here we estimate the global precipitation effects of the global forest potential by estimating its effects on evaporation and simulating the downwind precipitation effect of the moisture added to the atmosphere. We find that maximum forestation would on average increase evaporation by 0.6 mm d−1 and that two-thirds of that additional evaporation would rain out over land, especially during the growing season. Next, by excluding natural grasslands and prioritizing precipitation enhancement above areas that are projected to become drier due to global climate change, we establish where on Earth forest restoration would have the greatest precipitation benefits. Our results thus provide a first step towards forest restoration programs as double climate-change mitigation efforts.

AbstractAtmospheric moisture recycling effectively increases the amount of usable water over land as the water can undergo multiple precipitation–evapotranspiration cycles. Differences in land cover and climate regulate the evapotranspiration flux. Forests can have deep roots that access groundwater facilitating transpiration throughout the dry season independent of precipitation. This stable transpiration buffers the forest against precipitation variability. However, it is not known whether the buffering effect, already modeled for tropical forests, is common to all forests globally. Here we apply a state‐of‐the‐art Lagrangian moisture tracking model (UTrack) to study whether forest land cover in the upwind precipitationshed can lead to a reduction in monthly precipitation variability downwind. We found a significant buffering effect of forests in the precipitation variability of 10 out of 14 biomes globally. On average, if 50% of precipitation originates from forest, then we find a reduction in the coefficient of variation of monthly precipitation of 60%. We also observed that a high fraction of precipitation from non‐forest land sources tends to have the opposite effect, that is, no buffering effect. The average variation of monthly precipitation was 69% higher in areas where 50% of precipitation originates from non‐forest land sources in the precipitationshed. Our results emphasize the importance of land cover composition in the precipitationshed to buffer precipitation variability downwind, in particular forest cover. Understanding the influence of land cover in a precipitationshed on atmospheric moisture transport is key for evaluating an area's water‐climate regulatory ecosystem services and may become increasingly important due to continued changes in land cover and climate change.

AbstractThe possibility that the Amazon forest system could soon reach a tipping point, inducing large-scale collapse, has raised global concern1–3. For 65 million years, Amazonian forests remained relatively resilient to climatic variability. Now, the region is increasingly exposed to unprecedented stress from warming temperatures, extreme droughts, deforestation and fires, even in central and remote parts of the system1. Long existing feedbacks between the forest and environmental conditions are being replaced by novel feedbacks that modify ecosystem resilience, increasing the risk of critical transition. Here we analyse existing evidence for five major drivers of water stress on Amazonian forests, as well as potential critical thresholds of those drivers that, if crossed, could trigger local, regional or even biome-wide forest collapse. By combining spatial information on various disturbances, we estimate that by 2050, 10% to 47% of Amazonian forests will be exposed to compounding disturbances that may trigger unexpected ecosystem transitions and potentially exacerbate regional climate change. Using examples of disturbed forests across the Amazon, we identify the three most plausible ecosystem trajectories, involving different feedbacks and environmental conditions. We discuss how the inherent complexity of the Amazon adds uncertainty about future dynamics, but also reveals opportunities for action. Keeping the Amazon forest resilient in the Anthropocene will depend on a combination of local efforts to end deforestation and degradation and to expand restoration, with global efforts to stop greenhouse gas emissions.

Recent work has indicated that tropical forest and savanna can be alternative stable states under a range of climatic conditions. However, dynamical systems theory suggests that in case of strong spatial interactions between patches of forest and savanna, a boundary between both states is only possible at conditions in which forest and savanna are equally stable, called the ‘Maxwell point.’ Frequency distributions of MODIS tree-cover data at 250 m resolution were used to estimate such Maxwell points with respect to the amount and seasonality of rainfall in both South America and Africa. We tested on a 0.5° scale whether there is a larger probability of local coexistence of forests and savannas near the estimated Maxwell points. Maxwell points for South America and Africa were estimated at 1760 and 1580 mm mean annual precipitation and at Markham’s Seasonality Index values of 50 and 24 %. Although the probability of local coexistence was indeed highest around these Maxwell points, local coexistence was not limited to the Maxwell points. We conclude that critical transitions between forest and savanna may occur when climatic changes exceed a critical value. However, we also conclude that spatial interactions between patches of forest and savanna may reduce the hysteresis that can be observed in isolated patches, causing more predictable forest-savanna boundaries than continental-scale analyses of tree cover indicate. This effect could be less pronounced in Africa than in South America, where the forest-savanna boundary is substantially affected by rainfall seasonality.