Forests regulate global and local climates in ways that impact human well-being. In this Review, we discuss the scale-dependent mechanisms through which forests regulate climate, highlighting their contributions to global mitigation and local adaptation. Locally, forests tend to buffer temperatures, cooling in warm conditions and warming in cold ones. In regions that naturally support dense forest cover, trees contribute to global cooling primarily through carbon uptake, with some offsetting from albedo-related warming. By enhancing rainfall interception, evapotranspiration, and cloud formation, forests also influence the hydrological cycle, lowering flood risks in humid regions but often reducing downstream water availability, especially in drier climates. Collectively, these interacting processes show that the greatest climate benefits occur where forests are native, highlighting their importance for both climate adaptation and mitigation.

Deforestation modifies local surface temperatures, warming warm regions and cooling cooler regions. However, these biophysical effects may shift as the climate warms, limiting our capacity to predict the climatic impacts. Here, using statistical modeling, we quantified changes in the sensitivity of surface temperatures to forest cover change (Delta T/Delta FC) between 2003 and 2012 across 15 million km2 of forest area to predict temporal and spatial shifts in Delta T/Delta FC from 1988 to 2016. In 1988, deforestation had local warming effects on mean land and air surface temperatures in 82.5% (68.4 million km2) and 67.3% (55.8 million km2) of the forest area, respectively. This area increased by 0.6% (0.5 million km2) for mean land surface temperatures and 1.4% (1.2 million km2) for mean air surface temperatures over the next three decades. Our study provides evidence from large-scale observations that climate change is enhancing local warming effects of deforestation, underlining the need to conserve intact biodiverse forests to buffer global warming effects.

Ensuring food security under climate change is a critical challenge for humanity. Edge effects likely play an important role in determining farm yields, as agricultural edges differ in their microenvironmental conditions and ecological processes compared with field interiors. However, the magnitude and spatial variation of such effects remain poorly understood. Here, we used the normalized difference vegetation index (NDVI) as a proxy for crop yield to estimate edge effects for two major US crops, corn and soybeans. We found that crop yields were higher near field edges in the humid eastern US and lower in the drier western US, a pattern likely driven by precipitation and surrounding land cover, especially forests. A counterfactual simulation showed that optimized edge configurations could generate annual gains of nearly 900 million USD for corn and 500 million USD for soybeans, highlighting strategic field-boundary management as an underutilized lever for enhancing yields and economic returns.

Forest fragmentation could reduce carbon sequestration beyond losses caused by declining forest area alone, if smaller patches are intrinsically less productive per unit area than larger ones. Here we analyse 17 million forest patches across the conterminous USA and show that per-area net primary productivity increases systematically with patch size. A hectare embedded within a ~100,000 km2 forest is, on average, 38% more productive than an isolated hectare under comparable environmental conditions. Counterfactual analyses indicate that existing fragmentation has already reduced total annual forest productivity across the conterminous USA by 0.16 GtC yr-1 or 14% relative to an upper-bound configuration of large, contiguous forests. Random forest models identify patch size as a stronger predictor of net primary productivity than topographic and soil variables. Extending the analysis globally with coarser-resolution data, we find consistent positive relationships between patch size and per-area productivity for both net and gross primary productivity. These results demonstrate that forest fragmentation can reduce carbon sequestration without net forest-area loss, highlighting the need to account for fragmentation-not just forest cover-in climate mitigation strategies.

Habitat fragmentation, in which contiguous forests are broken into smaller, isolated patches, threatens biodiversity by disrupting species movement, shrinking populations, and altering ecosystem dynamics. Past assessments suggested declining global fragmentation, but they relied on structure-based metrics that overlook ecological connectivity. We analyzed global forest fragmentation from 2000 to 2020 using complementary metrics that captured patch connectivity, aggregation, and structure. Connectivity-based metrics revealed that 51 to 67% of forests globally-and 58 to 80% of tropical forests-became more fragmented, which is nearly twice the rate suggested by traditional structure-focused methods (30 to 35%). Aggregation-focused metrics confirmed increases in 57 to 83% of forests. Human activities such as agriculture and logging drive this change. Yet protected tropical areas saw up to an 82% reduction in fragmentation, underscoring the potential of targeted conservation.

Deforestation has exacerbated the fragmentation of habitats into smaller, more isolated patches, driving global declines in biodiversity. Yet, a comprehensive global perspective of the trends in forest fragmentation, and its key drivers in relation to forest cover change remains elusive. To provide a comprehensive global overview of recent changes in forest fragmentation, we compare multiple fragmentation metrics, including those that are sensitive to forest cover and those that are not. Our analysis reveals that, according to cover-sensitive metrics that reflect the ecological implications of forest fragmentation, 52% of the world's forests have become more fragmented over the last two decades, a trend that is primarily attributed to increased deforestation in tropical zones. This value is twice as high than estimates from previous research, which estimated that forest fragmentation is declining across 75% of the global forest area. This discrepancy arises from a mathematical artifact, as previous cover-insensitive metrics equate declines in forest cover with decreased fragmentation. By adjusting for this and focusing on metrics that capture the ecologically relevant aspects of forest fragmentation, our study highlights a worrying trend: the ecological integrity of the global forest system has been significantly deteriorating in recent decades. This underscores the importance of using appropriate metrics to accurately assess the ecological impacts of forest fragmentation, especially in the context of global environmental change.

Forests not only regulate the global climate by absorbing carbon dioxide but also shape local biophysical conditions by creating microclimates that buffer temperature extremes. However, ongoing deforestation and fragmentation are transforming forest interiors into edge environments, which may differ markedly in their microclimatic conditions and undermine local climate-regulating functions. Here, we quantify how proximity to forest edges alters thermal conditions across biomes and seasons using global satellite-derived surface temperature data from nearly 13 million sites. We find that forest edges are consistently warmer on average than interiors, with the magnitude of warming varying with biome type and season. During summer months, surface temperature at edges frequently exceeds the optimal temperature for vegetation productivity, particularly in tropical forests. These results suggest that continued loss of interior forest will reduce the capacity of remnant forests to buffer local climate conditions, potentially hampering ecosystem productivity and resilience.

Because of widespread forest fragmentation, 70% of the world's forest area lies within 1 km of an edge. Forest biomass density near edges often differs markedly from biomass density in the interior. In some biomes, these 'edge effects' are responsible for substantial reductions in forest carbon storage. However, there is little consensus on the direction and magnitude of edge effects on forest biomass across the globe, which hampers their consideration in forest carbon stock accounting. Here we examined eight million forested locations to quantify variability in edge effects on biomass at a global scale. We found negative edge effects across 97% of examined areas, with aboveground biomass density on average 16% lower near edges than in interior forests. Higher temperature, precipitation and proportion of agricultural land were linked to more negative edge effects. Along with differences in the spatial scale of analysis, this variation can explain contrasting observations among previous studies. We estimate that edge effects have reduced the total aboveground biomass of forests by 9%, equivalent to a loss of 58 Pg. These findings underscore the substantial impact of forest fragmentation on global biomass stocks and highlight the critical need to account for edge effects in carbon stock assessments.

Soil microbes drive ecosystem function and play a critical role in how ecosystems respond to global change. Research surrounding soil microbial communities has rapidly increased in recent decades, and substantial data relating to phospholipid fatty acids (PLFAs) and potential enzyme activity have been collected and analysed. However, studies have mostly been restricted to local and regional scales, and their accuracy and usefulness are limited by the extent of accessible data. Here we aim to improve data availability by collating a global database of soil PLFA and potential enzyme activity measurements from 12,258 georeferenced samples located across all continents, 5.1% of which have not previously been published. The database contains data relating to 113 PLFAs and 26 enzyme activities, and includes metadata such as sampling date, sample depth, and soil pH, total carbon, and total nitrogen. This database will help researchers in conducting both global- and local-scale studies to better understand soil microbial biomass and function.

Box 1-An LLM suggests 10 simple rules governing its own usage in scienceHere, we ask ChatGPT to generate a list of 10 simple rules for using LLMs in science in order to illustrate its ability to provide detailed, human-like responses to short prompts. Q1:Can you provide me with a list of ten simple rules for using large language models in science?R1 (ChatGPT 3.5): Certainly!Here are ten simple rules for using large language models in science:1. Understand the limitations: Recognize that large language models like GPT-3 are powerful but not infallible.They may produce accurate-sounding information, but they can also generate false or biased content.Exercise caution and critical thinking.2. Validate and verify: Always cross-reference information generated by language models with reliable sources.Verify the accuracy of claims, check for

Forests play a crucial role in regulating the global climate. Yet, forests also influence the local climate conditions through biophysical processes that directly impact human wellbeing. With growing policy emphasis on these climate adaptation effects, we review the scale dependent impacts of forests on climate conditions and their implications for human wellbeing. Generally, existing forests buffer local temperatures, with warming effects in cold regions and cooling effects in hot regions. At a global scale, trees are more conducive to cooling in regions where dense forests would naturally exist. Additionally, forests generally reduce water runoff, which can reduce flooding in wet areas, but it can also limit water availability downstream, especially in drier regions. Together, these findings suggest that climate positive tree effects tend to be most frequent in regions where forests naturally occur, and highlight the growing consensus around the importance of natural forests for climate adaptation.

Plant roots represent about a quarter of global plant biomass and constitute a primary source of soil organic carbon (C). Yet, considerable uncertainty persists regarding root litter decomposition and their responses to global change factors (GCFs). Much of this uncertainty stems from a limited understanding of the multifactorial effects of GCFs and it remains unclear how these effects are mediated by litter quality, soil conditions and microbial functionality. Using complementary field decomposition and laboratory incubation approaches, we assessed the relative controls of GCF-mediated changes in root litter traits and soil and microbial properties on fine-root decomposition under warming, nitrogen (N) enrichment, and precipitation alteration. We found that warming and N enrichment accelerated fine-root decomposition by over 10%, and their combination showed an additive effect, while precipitation reduction suppressed decomposition overall by 12%, with the suppressive effect being most significant under warming-alone and N enrichment-alone conditions. Significantly, changes in litter quality played a dominant role and accelerated fine-root decomposition by 15% ~ 18% under warming and N enrichment, while changes in soil and microbial properties were predominant and reduced decomposition by 7% ~ 10% under precipitation reduction and the combined warming and N enrichment. Examining only the decomposition environment or litter properties in isolation can distort global change effects on root decomposition, underestimating precipitation reduction impacts by 38% and overstating warming and N effects by up to 73%. These findings highlight that the net impact of GCFs on root litter decomposition hinges on the interplay between GCF-modulated root decomposability and decomposition environment, as well as on the synergistic or antagonistic relationships among GCFs themselves. Our study emphasizes that integrating the legacy effects of multiple GCFs on root traits, soil conditions and microbial functionality would improve our prediction of C and nutrient cycling under interactive global change scenarios.

1. Low available soil nitrogen (N) limits plant productivity in alpine regions, and alpine plants thus resorb and reallocate N from senescing tissues to conserve this limited N during the non-growing season. However, the destination and extent of N redistribution during plant senescence among above- and below-ground organs, let alone other processes of translocation outside of plants and into the soil components, remain poorly understood.2. Utilizing N-15 stable isotope as a tracer, we quantified N redistribution among above- and below-ground plant organs and different soil components during senescence in an alpine meadow ecosystem, and explored the relationship between N-15 partitioning among plant-soil N pools with seasonal fluctuations of plant functional traits.3.We found a substantial depletion of N-15 in fine roots (-40% +/- 2.8%) and above-ground tissues (-51% +/- 5.1%), and an enhanced N-15 retention primarily in coarse roots (+79% +/- 27%) and soil organic matter (+37% +/- 10%) during plant senescence, indicating a dual role of roots with coarse roots acting as an N sink and fine roots as a source of N recycling during senescence. In parallel, we observed a temporal variation in plant functional traits, representing a shift from more acquisitive to more conservative strategies as the growing season ends, such as higher coarse root N and coarse root to fine root ratio. The seasonal trait variations were highly correlated with the N-15 retention in coarse roots and soil organic matter. Particularly, N-15 retention in particulate and mineral-associated organic matter increased by 30% +/- 12% and 24% +/- 9%, respectively, suggesting a potential pathway through which fine root and microbial mortality contribute to N-15 redistribution into soil N pools during senescence. Synthesis. N redistribution and seasonal plant trait fluctuation facilitate plant N conservation and ecosystem N retention in the alpine system. This study suggests a coupled above-ground-below-ground N conservation strategy that may optimize the temporal coupling between plant N demand and ecosystem N supply in N-limited alpine ecosystems.

Land degradation has emerged as a significantly pressing environmental concern, contributing to the decline of soil properties in both arid and semiarid regions. Despite this, there is limited understanding of how degradation and subsequent long-term restoration efforts impact enzymatic stoichiometry in soils of the Brazilian semiarid area. Therefore, our study aimed to quantify C-, N-, and P-acquiring enzymes in soil samples from the Caatinga, a Brazilian semiarid region. We compared three different conditions: (a) Native Caatinga vegetation, primarily dominated by Fabaceae species; (b) Restored land, resulting from two decades of grazing exclusion; and (c) Degraded land due to overgrazing, characterized by high-intensity grazing practices. A total of 54 soil samples were collected at depths of 0-10 cm during both dry and rainy seasons to evaluate the levels of C-, N-, and Pacquiring enzymes and their respective stoichiometries. Our findings revealed that, overall, C- and N-enzymes showed higher and similar levels between native and restored land, whereas these enzyme levels significantly decreased (approximately 60% for C-enzymes and 80% for N-enzymes) in degraded land. Moreover, P-acquiring enzymes exhibited a notable decrease (approximately 70%) in degraded land specifically during the dry season. The degraded land exhibited a higher C/N ratio (8.5) during the rainy season compared to native land (4.8). Conversely, higher values of C/P and N/P ratios (both during rainy seasons) were observed in native land (0.3 and 0.07, respectively). Redundancy analysis showed that native and restored lands clustered with all acquiring enzymes and were notably influenced by key soil properties such as organic C, microbial biomass C, and nutrients. In contrast, degraded land showed correlations with Al3+ and Na+. Our results provide substantial evidence that Caatinga soils affected by degradation may be microbially P-limited. This underscores the necessity of integrating P-enriched amendments or fertilizers and implementing long-term restoration practices.

Although microbes are the major agent of wood decomposition - a key component of the carbon cycle - the degree to which microbial community dynamics affect this process is unclear. One key knowledge gap is the extent to which stochastic variation in community assembly, e.g. due to historical contingency, can substantively affect decomposition rates. To close this knowledge gap, we manipulated the pool of microbes dispersing into laboratory microcosms using rainwater sampled across a transition zone between two vegetation types with distinct microbial communities. Because the laboratory microcosms were initially identical this allowed us to isolate the effect of changing microbial dispersal directly on community structure, biogeochemical cycles and wood decomposition. Dispersal significantly affected soil fungal and bacterial community composition and diversity, resulting in distinct patterns of soil nitrogen reduction and wood mass loss. Correlation analysis showed that the relationship among soil fungal and bacterial community, soil nitrogen reduction and wood mass loss were tightly connected. These results give empirical support to the notion that dispersal can structure the soil microbial community and through it ecosystem functions. Future biogeochemical models including the links between soil microbial community and wood decomposition may improve their precision in predicting wood decomposition.

Soil contains immense stocks of carbon, which may accelerate climate change if released. Soil microbes affect these carbon stocks by producing decomposition-catalyzing enzymes, a capacity varying across different microbial groups. Consequently, establishing links between global variation in microbial communities and functions should substantially enhance future projections of soil carbon. To this end, we here reveal global patterns in soil microbial community function using nearly 13,000 observations of microbial biomass, community structure, and enzyme activities (>100,000 measurements). We find total biomass and fungal and Gram-negative bacterial dominance increase with latitude, whereas Gram-positive bacteria predominate near the equator. Enzyme stoichiometry correspondingly suggests greater nitrogen and carbon limitation at higher latitudes. Comparing microbial and enzyme patterns, fungal biomass indicates nitrogen limitation, whereas Gram-negative bacterial biomass indicates carbon limitation. Together, microbial community structure explains significant variation in enzyme profile uncaptured by climate, soil properties, or landcover. Soil microbial communities dominated by fungi and Gram-negative bacteria exhibit less enzyme activity per unit biomass, with two- to four-fold variation in temperature- and biomass-normalized activity rate observed across the Earth. Significant functional differences thus arise with global turnover in microbial communities, indicating that community structure merits a central position in process-based soil models.

1) Context: The resilience of the Earth's vegetation is changing heterogeneously, making it a challenge to unveil what causes these resilience changes. Understanding the driving forces of these changes can help us make informed management decisions to protect and restore ecosystems. Here, we address this gap by identifying the drivers that have caused the resilience of ecosystems to change during the last two decades.2) Methods: We globally measured two complementary aspects of resilience, namely sensitivity and autocorrelation, which are respectively associated with the resisting and recovering ability of ecosystems. We used a machine learning approach to identify the main environmental, climatic, and anthropogenic drivers of changes in resilience between two periods (the period 2000-2010 vs. that of 2010-2020).3) Results: We found that in 26% of regions worldwide, vegetation exhibits signs of resilience loss. Moreover, ecosystem’s properties (aridity, elevation, anthropization) affect the way vegetation resilience has changed over time. When controlling for these properties, different biomes (forest, grasslands, and savannas) will exhibit similar responses to changes in climate conditions. Regions experiencing intense warming (>0.2ºC/decade) have shown a major loss in vegetation resilience. Decreasing productivity is associated with reduced resilience and interacts with warming, exacerbating resilience loss of less productive lands (potentially showing signs of degradation). 4) Conclusions: Warming and degradation appear as major drivers of losses in vegetation resilience across vegetation types. These results raise concerns about the persistence of ecosystems under continued climate change and expected intensification of human activities which, highlights the importance of maintaining the resilience of ecosystems under changing environmental conditions.

Quantifying biodiversity across the globe is critical for transparent reporting and assessment under the Kunming-Montreal Global Biodiversity Framework. Understanding the full complexity of biodiversity requires consideration of the variation of life across genetic, species and ecosystem levels. Achieving this in a globally-standardized way remains a key international challenge for biodiversity monitoring efforts. Here, we present the Sustainable Ecology and Economic Development (SEED) framework, which consolidates multiple dimensions of biodiversity into a single measure of biocomplexity as a holistic estimate of the current state of nature at a given location. The SEED framework continuously integrates state-of-the-art datasets and maps of the biological variation in plants, microbes, animals, and ecosystems to estimate the local biocomplexity across the planet relative to a comparable, minimally-disturbed ‘reference’ ecosystem. The SEED framework allows an assessment of ecological health in response to positive and negative human impacts, and informs decision makers who strive to improve the global state of nature.

Context: Changes in ecosystem resilience have been recently studied on various scales using remote sensing data, revealing various regions exhibiting decreasing resilience. However, the drivers of these changes have not been identified yet. Our study aims at filling this gap by exploring the factors that have caused the resilience of ecosystems to change during the last two decades. Methods: We investigate changes in vegetation resilience at the planetary scale, by quantifying two complementary aspects of resilience, namely sensitivity and autocorrelation, which are respectively associated with resistance and recovery abilities of ecosystems. We use a machine learning approach to identify the main environmental, climatic, and anthropogenic drivers of changes in resilience between two periods (the period 2000-2010 vs that of 2010-2020). Results: We find that in 26% of ecosystems worldwide, vegetation exhibits signs of resilience loss, and that the changes in climate conditions as well as the ecosystem’s intrinsic properties (aridity, elevation, anthropization) affect the way vegetation resilience has changed over time. Different biomes (forest, grasslands, and savannas) exhibit similar responses to their changing environment. Regions experiencing intense warming (>0.2ºC/decade) have shown a major loss in vegetation resilience. Decreasing productivity is associated with reduced resilience, and interacts with warming, exacerbating resilience loss of degraded lands. This shows that global warming and human activities are major drivers of losses in vegetation resilience across vegetation types. Conclusions: We reveal a decline in the capacity of a number of ecosystems to withstand perturbations, which should be accounted for in the management of vulnerable areas. Our results raise concerns about the persistence of ecosystems due to projected warming and expected intensification of human activities.

To conserve limiting nitrogen (N) in alpine ecosystems, herbaceous plants resorb and reallocate N from senescing tissues. However, the extent of N resorption and reallocation in aboveground tissues, coarse roots, fine roots and their relative contributions to whole-plant N conservation and ecosystem N retention remain poorly understood. Utilizing N stable isotope (15N) as a tracer, we quantified N partitions and N retranslocation efficiencies (NRE, % of N changes for each N pool) during senescence among different plant organs in a Tibetan alpine system. We found that compared to the N pools at the peak biomass stage, substantial 15N infine roots (FR, 39.93%) and aboveground tissues (shoot, 50.94%) was retranslocated primarily to coarse roots (CR, an increase of 79.02% in 15N) and non-extractable soil organic matter (an increase of 37.39% in 15N), corresponding to a temporal shift of plant trait syndrome from poor conservation to strong conservation during senescence. 15N in particulate organic matter and mineral-associated organic matter fractions during the senescence stage increased by 29.80% and 24.30%, respectively, but microbial biomass 15N significantly decreased. Our results illustrate the key role of N retranslocation to coarse roots and organic matter in N retention and the dual role of plant roots and organic matter as N sink and source in the plant-microbe-soil system. These findings suggest that plant N retranslocation and seasonal trait alternation facilitate the spatial and temporal coupling between plant N demand and bioavailable N supply in N-limiting alpine systems.