Contrasting impacts of forests on cloud cover based on satellite observations

Prediction of Potential Suitable Distribution Areas for an Endangered Salamander in China

Climate change has been considered to pose critical threats for wildlife. During the past decade, species distribution models were widely used to assess the effects of climate change on the distribution of species' suitable habitats. Among all the vertebrates, amphibians are most vulnerable to climate change. This is especially true for salamanders, which possess some specific traits such as cutaneous respiration and low vagility. The Wushan salamander (Liua shihi) is a threatened and protected salamander in China, with its wild population decreasing continuously. The main objective of this study was to predict the distribution of suitable habitat for L. shihi using the ENMeval parameter-optimized MaxEnt model under current and future climate conditions. Our results showed that precipitation, cloud density, vegetation type, and ultraviolet radiation were the main environmental factors affecting the distribution of L. shihi. Currently, the suitable habitats for L. shihi are mainly concentrated in the Daba Mountains, including northeastern Chongqing and western Hubei Provinces. Under the future climate conditions, the area of suitable habitats increased, which mainly occurred in central Guizhou Province. This study provided important information for the conservation of L. shihi. Future studies can incorporate more species distribution models to better understand the effects of climate change on the distribution of L. shihi.

Amazon deforestation causes strong regional warming

Tropical deforestation impacts the climate through complex land-atmosphere interactions causing local and regional warming. However, whilst the impacts of deforestation on local temperature are well understood, the regional (nonlocal) response is poorly quantified. Here, we used remote-sensed observations of forest loss and dry season land-surface temperature during the period 2001 to 2020 to demonstrate that deforestation of the Amazon caused strong warming at distances up to 100 km away from the forest loss. We apply a machine learning approach to show nonlocal warming due to forest loss at 2-100 km length scales increases the warming due to deforestation by more than a factor 4, from 0.16 K to 0.71 K for each 10-percentage points of forest loss. We estimate that rapid future deforestation under a strong inequality scenario could cause dry season warming of 0.96 K across Mato Grosso state in southern Brazil over the period 2020 to 2050. Reducing deforestation could reduce future warming caused by forest loss to 0.4 K. Our results demonstrate the contribution of tropical deforestation to regional climate warming and the potential for reduced deforestation to deliver regional climate adaptation and resilience with important implications for sustainable management of the Amazon.

Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects

Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.

Vegetation restoration thresholds under different vegetation types and altitude gradients in the Sichuan-Yunnan ecological shelter, China

Determining the threshold for the response of ecosystem services (ESs) to vegetation change is critical for ecological restoration, and once the threshold is exceeded, ESs may be inhibited. Vegetation type and altitude are important factors affecting ESs. However, the nonlinear effects of vegetation change on ESs and their threshold under different vegetation types and altitude gradients are not clear. This study selected the Sichuan-Yunnan ecological shelter as the study area. Four ESs (water yield (WY), carbon storage (CS), soil conservation (SC), and water purification (WP)) were quantified by using the Integrated Valuation of Ecosystem Services and Trade-offs model. The differences in ESs among different vegetation types were identified. Variance analysis was used to explore the spatial differences in ESs under different altitude gradients. The inflection point of the promoting effect of vegetation cover on ESs was taken as the threshold, and elastic analysis was used to determine the impact threshold of fractional vegetation cover (FVC) on ESs. The threshold represents the inflection point at which vegetation cover promotes ESs. The results showed that the CS, SC, and WP of the natural forest were higher than those of the plantation, while the WY was lower than that of the plantation. WY, CS, and SC remained higher in the high-altitude regions, while nitrogen export was higher in the low-altitude regions. FVC was positively correlated with nitrogen export in the low-altitude regions and negatively correlated with WY in the high-altitude regions. FVC had a promoting effect on ESs, and the promoting effect was weakened beyond the threshold. The thresholds of FVC promoting ESs were 0.86, 0.79, 0.85, and 0.83 in natural forest, shrub, plantation, and grassland, respectively. The threshold of FVC promoting ESs in low-altitude regions was larger than that in high-altitude regions. This study can provide a theoretical basis for large-scale ecological management and moderate restoration.

Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming

Vegetation change can alter surface energy balance and subsequently affect the local climate. This biophysical impact has been well studied for forestation cases, but the sign and magnitude for persistent earth greening remain controversial. Based on long-term remote sensing observations, we quantify the unidirectional impact of vegetation greening on radiometric surface temperature over 2001-2018. Here, we show a global negative temperature response with large spatial and seasonal variability. Snow cover, vegetation greenness, and shortwave radiation are the major driving factors of the temperature sensitivity by regulating the relative dominance of radiative and non-radiative processes. Combined with the observed greening trend, we find a global cooling of -0.018 K/decade, which slows down 4.6 ± 3.2% of the global warming. Regionally, this cooling effect can offset 39.4 ± 13.9% and 19.0 ± 8.2% of the corresponding warming in India and China. These results highlight the necessity of considering this vegetation-related biophysical climate effect when informing local climate adaptation strategies.

Deforestation intensifies daily temperature variability in the northern extratropics

While the biogeophysical effects of deforestation on average and extreme temperatures are broadly documented, how deforestation influences temperature variability remains largely unknown. To fill this knowledge gap, we investigate the biogeophysical effects of idealized deforestation on daily temperature variability at the global scale based on multiple earth system models and in situ observations. Here, we show that deforestation can intensify daily temperature variability (by up to 20%) in the northern extratropics, particularly in winter, leading to more frequent rapid extreme warming and cooling events. The higher temperature variability can be attributed to the enhanced near-surface horizontal temperature advection and simultaneously is partly offset by the lower variability in surface sensible heat flux. We also show responses of daily temperature variability to historical deforestation and future potential afforestation. This study reveals the overlooked effects of deforestation or afforestation on temperature variability and has implications for large-scale afforestation in northern extratropic countries.

A new study finds that deforestation in the northern extratropics can enhance horizontal temperature advection through biogeophysical processes, leading to higher local daily temperature variability, particularly in winter.

Global forestation and deforestation affect remote climate via adjusted atmosphere and ocean circulation

Forests can store large amounts of carbon and provide essential ecosystem services. Massive tree planting is thus sometimes portrayed as a panacea to mitigate climate change and related impacts. Recent controversies about the potential benefits and drawbacks of forestation have centered on the carbon storage potential of forests and the local or global thermodynamic impacts. Here we discuss how global-scale forestation and deforestation change the Earth's energy balance, thereby affect the global atmospheric circulation and even have profound effects on the ocean circulation. We perform multicentury coupled climate model simulations in which preindustrial vegetation cover is either completely forested or deforested and carbon dioxide mixing ratio is kept constant. We show that global-scale forestation leads to a weakening and poleward shift of the Northern mid-latitude circulation, slows-down the Atlantic meridional overturning circulation, and affects the strength of the Hadley cell, whereas deforestation leads to reversed changes. Consequently, both land surface changes substantially affect regional precipitation, temperature, clouds, and surface wind patterns across the globe. The design process of large-scale forestation projects thus needs to take into account global circulation adjustments and their influence on remote climate.