Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022.

Northern ecosystems (≥ 30° N) have been accumulating vegetation biomass carbon in recent decades, but increasing droughts and wildfires threaten this carbon sink. Here, we analyse annual changes in live vegetation biomass in northern ecosystems using low-frequency microwave satellite observations at 25 km spatial resolution from 2010 to 2022. We find that live biomass carbon stocks have undergone a reversal from a positive to a negative trend during the study period with 2016 marking the turning point.

Globally increased cropland soil exposure to climate extremes in recent decades.

Soil quality is fundamental to nutrient-rich food production and the sustainability of terrestrial ecosystems. However, inappropriate agricultural practices often lead to persistent soil exposure to air and sunlight, which increases soil organic matter losses and erosion risks, particularly under climate extremes. Here, we provide a satellite-based mapping of daily soil exposure occurrence across global croplands from 2001 to 2022 and evaluate the associated degradation risks caused by extreme climate events.

Enhancing Climate-Driven Urban Tree Cooling with Targeted Nonclimatic Interventions.

Urban trees play a pivotal role in mitigating heat, yet the global determinants and patterns of their cooling efficiency (CE) remain elusive. Here, we quantify the diel CE of 229 cities across four climatic zones and employ a machine-learning model to assess the influence of variables on CE. We found that for every 10% increase in tree cover, surface temperatures are reduced by 0.

Eddy covariance measurements reveal a decreased carbon sequestration strength 2010-2022 in an African semiarid savanna.

Monitoring the changes of ecosystem functioning is pivotal for understanding the global carbon cycle. Despite its size and contribution to the global carbon cycle, Africa is largely understudied in regard to ongoing changes of its ecosystem functioning and their responses to climate change. One of the reasons is the lack of long-term in situ data.

Boreal tree species diversity increases with global warming but is reversed by extremes.

Tree species diversity is essential to sustaining stable forest ecosystem functioning. However, it remains unclear how boreal tree species diversity has changed in response to climate change and how it is associated with productivity and the temporal stability of boreal forest ecosystems. By combining 5,312 field observations and 55,560 Landsat images, here we develop a framework to estimate boreal tree species diversity (represented by the Shannon diversity index, H') for the years 2000, 2010 and 2020.

Mapping every adult baobab (Adansonia digitata L.) across the Sahel and relationships to rural livelihoods.

The baobab tree (Adansonia digitata L.) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources.

Dominant role of the non-forest woody vegetation in the post 2015/16 El Niño tropical carbon recovery.

The extreme dry and hot 2015/16 El Niño episode caused large losses in tropical live aboveground carbon (AGC) stocks. Followed by climatic conditions conducive to high vegetation productivity since 2016, tropical AGC are expected to recover from large losses during the El Niño episode; however, the recovery rate and its spatial distribution remain unknown. Here, we used low-frequency microwave satellite data to track AGC changes, and showed that tropical AGC stocks returned to pre-El Niño levels by the end of 2020, resulting in an AGC sink of Pg C year during 2014-2020.

Facing the challenge of NDVI dataset consistency for improved characterization of vegetation response to climate variability.

Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019.

Global area boom for greenhouse cultivation revealed by satellite mapping.

Greenhouse cultivation has been expanding rapidly in recent years, yet little knowledge exists on its global extent and expansion. Using commercial and freely available satellite data combined with artificial intelligence techniques, we present a global assessment of greenhouse cultivation coverage and map 1.3 million hectares of greenhouse infrastructures in 2019, a much larger extent than previously estimated.

Changes in vegetation-water response in the Sahel-Sudan during recent decades.

Study Region: The Africa Sahel-Sudan region, defined by annual rainfall between 150 and 1200 mm.

Study Focus: Understanding the mechanism of vegetation response to water availability could help mitigate the potential adverse effects of climate change on global dryland ecosystems. In the Sahel-Sudan region, spatio-temporal changes and drivers of the vegetation-water response remain unclear.

Critical thresholds for nonlinear responses of ecosystem water use efficiency to drought.

Climate change is expected to lead to greater variability in precipitation and drought in different regions. However, the responses of ecosystem carbon and water cycles (i.e.

The success of ecological engineering projects on vegetation restoration in China strongly depends on climatic conditions.

China has implemented extensive ecological engineering projects (EEPs) during recent decades to restore and enhance ecosystem functioning. However, the effectiveness of these interventions can vary due to factors such as local climate and specific project objectives. Here, we used two independent satellite remote sensing datasets, including the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) and vegetation optical depth from Ku-band (Ku-VOD), to investigate the vegetation trends in two hotspot regions of EEPs characterized by different climate conditions, i.

More than one quarter of Africa's tree cover is found outside areas previously classified as forest.

The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year.

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions.

Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown.

Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale.

Sustainable tree resource management is the key to mitigating climate warming, fostering a green economy, and protecting valuable habitats. Detailed knowledge about tree resources is a prerequisite for such management but is conventionally based on plot-scale data, which often neglects trees outside forests. Here, we present a deep learning-based framework that provides location, crown area, and height for individual overstory trees from aerial images at country scale.

Sub-continental-scale carbon stocks of individual trees in African drylands.

The distribution of dryland trees and their density, cover, size, mass and carbon content are not well known at sub-continental to continental scales. This information is important for ecological protection, carbon accounting, climate mitigation and restoration efforts of dryland ecosystems. We assessed more than 9.

Recent decrease of the impact of tropical temperature on the carbon cycle linked to increased precipitation.

The atmospheric CO growth rate (CGR) variability is largely controlled by tropical temperature fluctuations. The sensitivity of CGR to tropical temperature [Formula: see text] has strongly increased since 1960, but here we show that this trend has ceased. Here, we use the long-term CO records from Mauna Loa and the South Pole to compute CGR, and show that [Formula: see text] increased by 200% from 1960-1979 to 1979-2000 but then decreased by 117% from 1980-2001 to 2001-2020, almost returning back to the level of the 1960s.

Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda.

Trees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.

Mapping global lake dynamics reveals the emerging roles of small lakes.

Lakes are important natural resources and carbon gas emitters and are undergoing rapid changes worldwide in response to climate change and human activities. A detailed global characterization of lakes and their long-term dynamics does not exist, which is however crucial for evaluating the associated impacts on water availability and carbon emissions. Here, we map 3.

Estimating herbaceous aboveground biomass in Sahelian rangelands using Structure from Motion data collected on the ground and by UAV.

Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost-efficient way. Structure from Motion (SfM) is an image analysis process that can create a variety of 3D spatial models as well as 2D orthomosaics from a set of images. Computed from Unmanned Aerial Vehicle (UAV) and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study.

Groundwater arsenic content related to the sedimentology and stratigraphy of the Red River delta, Vietnam.

Arsenic (As) is highly toxic and over 100 million people living on the floodplains of Asia are exposed to excessive groundwater As. A very large spatial variability over small distances has been observed in the groundwater As concentrations. Advances in the prediction of the As distribution in aquifers would support drinking water management.

Response to concerns about the African fire trends controlled by precipitation over recent decades.

Croplands expanded in Africa over recent decades, even though the increasing trends are spatially heterogeneous.