Droughts have intensified under climate change, threatening ecosystem stability. While rising atmospheric CO2 concentrations may enhance vegetation drought resistance, the net effect remains uncertain amid concurrent warming. Here we combine ecological modeling with multi-source observations to investigate how CO2 and warming jointly regulate vegetation drought responses on the Qinghai-Tibetan Plateau, a sensitive alpine region exposed to escalating drought threats under changing precipitation regimes. Using factorial scenarios to isolate individual forcings, we show that 40-year CO2 rise mitigated drought-induced productivity losses by 5.7 +/- 0.9% under constant temperature. However, in the presence of warming, rising CO2 intensifies drought stress by 5.2 +/- 0.5%, reflecting increased plant water demand and disrupted regional water supply-demand balance. Permafrost areas experienced the strongest CO2-driven drought alleviation under constant temperature, but also the greatest warming-induced reversal. These findings reveal interacting CO2-warming impacts on alpine vegetation drought responses, highlighting ecological risks for the plateau and other permafrost-dominant regions under future warming.

Drought-induced canopy browning and recovery dynamics threaten ecosystem stability worldwide, with Australia serving as a representative case. This study examined the 2019-2020 drought and subsequent recovery in Eucalyptus forests across two bioregions of the Australian state of New South Wales (NSW): the North Coast and South Eastern Highlands. Canopy browning and recovery were quantified using a 2010-2022 Sentinel-2 time series of Normalized Burn Ratio (NBR), which has been previously identified as the most effective spectral index for detecting drought-related declines in canopy greenness, and were validated with field-measured canopy health. Artificial neural networks were used to link NBR z-scores with climatic (precipitation, temperature, potential evapotranspiration), topographic (Topographic Wetness Index, aspect, slope), soil, and vegetation variables. Lagged and cumulative precipitation and temperature emerged as the dominant drivers of canopy browning, while recovery was influenced by potential evapotranspiration and temperature. Regional contrasts underscored the role of local climate, topography, and vegetation composition in shaping drought impacts and post-drought recovery trajectories.

The Central Himalayas, characterized by one of the most pronounced elevation gradients globally, harbor forest stands of high carbon density. With estimated forest aboveground biomass (AGB) densities of up to 1000 t ha-1, these forests are among the most carbon-rich ecosystems within the Himalayas and high mountain ranges globally. However, existing global and regional models of forest carbon distribution fail to accurately capture the remarkable carbon density observed in these Himalayan forest stands. Our objective was to quantify how fine-scale topoclimatic conditions influence the spatial variability of AGB, with the aim of identifying the environmental factors that contribute to the high carbon density observed in high mountain forests of Nepal. Our analysis focused on quantifying the contribution of terrain-driven variation in climatic energy and water availability in creating favourable site conditions for carbon-dense forests. We found that extreme forest carbon density is associated with distinct topographic settings related to slope, aspect and curvature that provide a combination of adequate levels of both climatic energy and water availability, while forest carbon was reduced in topographic positions associated with high likelihood of disturbance such as avalanches and mass movements. Our findings shed light on the intricate relationship between topoclimatic factors and conditions for carbon storage in high-elevation forests, providing valuable insights for conservation and management strategies in mountainous regions.

BACKGROUND AND AIMS:Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. METHODS:We used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. KEY RESULTS:Optimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for 'light' than 'shaded' leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single 'broadleaf evergreen' functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. CONCLUSIONS:This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

Greater tree diversity often increases forest productivity by increasing the fraction of light captured and the effectiveness of light use at the community scale. However, light may shape forest function not only as a source of energy or a cause of stress but also as a context cue: Plant photoreceptors can detect specific wavelengths of light, and plants use this information to assess their neighborhoods and adjust their patterns of growth and allocation. These cues have been well documented in laboratory studies, but little studied in diverse forests. Here, we examined how the spectral profile of light (350–2200 nm) transmitted through canopies differs among tree communities within three diversity experiments on two continents (200 plots each planted with one to 12 tree species, amounting to roughly 10,000 trees in total), laying the groundwork for expectations about how diversity in forests may shape light quality with consequences for forest function. We hypothesized—and found—that the species composition and diversity of tree canopies influenced transmittance in predictable ways. Canopy transmittance—in total and in spectral regions with known biological importance—principally declined with increasing leaf area per ground area (LAI) and, in turn, LAI was influenced by the species composition and diversity of communities. For a given LAI, broadleaved angiosperm canopies tended to transmit less light with lower red‐to‐far‐red ratios than canopies of needle‐leaved gymnosperms or angiosperm‐gymnosperm mixtures. Variation among communities in the transmittance of individual leaves had a minor effect on canopy transmittance in the visible portion of the spectrum but contributed beyond this range along with differences in foliage arrangement. Transmittance through mixed species canopies often deviated from expectations based on monocultures, and this was only partly explained by diversity effects on LAI, suggesting that diversity effects on transmittance also arose through shifts in the arrangement and optical properties of foliage. We posit that differences in the spectral profile of light transmitted through diverse canopies serve as a pathway by which tree diversity affects some forest ecosystem functions.

Livestock grazing contributes to greenhouse gas (GHG) emissions, soil degradation and erosion, and loss of biodiversity. Regenerative pasture management includes improvements such as sowing high-diversity seed mixtures with legumes and other deep-rooted forbs in addition to C3 and C4 grasses, alternating intensive grazing with rest periods, bio-based fertilizers, etc. These improvements may alleviate degradation and restore multiple ecosystem services, including soil carbon sequestration and heat wave mitigation. Predictive understanding of management impacts requires process-based models that accurately simulate herbaceous growth and allocation in response to grazing and irrigation events. Moreover, accurate and timely model forecasts depend on well-validated data collected at appropriate temporal and spatial scales, delivered with low latency. We used four years of eddy covariance data in combination with vegetation indices and a process-based model to improve estimates of Net Ecosystem Production (NEP) and energy balance in response to livestock and wildlife grazing in an area with fluctuating soil moisture availability. The enhanced vegetation index (EVI) for the degraded pasture, grazed mainly by native wildlife (kangaroos), demonstrated wide seasonal variations of 0.2 to 0.6, whereas EVI was maintained more consistently close to 0.5 for an improved pasture, grazed intermittently by cattle or sheep. Across three wet years, NEP for the improved pasture averaged 12% higher compared to the degraded one (153 vs. 137 g C m-2 y-1), associated with average 20% greater gross primary production (GPP; 1822 vs. 1521 g C m-2 y-1). However, NEP on the improved pasture was lower than on the degraded pasture in two of those three years, possibly due to grazing-related differences in biomass removal. Sensible heat fluxes were higher from the degraded pasture, especially during hot/dry periods. Ongoing analyses are evaluating soil C storage for benchmarking flux data. Model predictions are also being improved by validating representation of productivity by C3 and C4 species and carbon allocation to roots and crowns. This work contributes to enhancing environmental sustainability in managed grasslands with near-real-time forecasting ability for grazing and irrigation management.

Droughts present a significant global challenge, particularly to forest ecosystems in regions such as eastern New South Wales, Australia, which is known for its dry climate and frequent, intense droughts. Recent studies have indicated a notable increase in tree mortality and canopy browning across this area, especially during the recent extreme drought period culminating in the Black Summer of 2019–2020. Our study investigates the impacts of drought on eucalypt forests by leveraging remote sensing and field observation data to detect and analyse vegetation health and stress indicators. Utilising data from Sentinel-2, alongside historical Landsat observations, we applied multiple spectral vegetation indices, namely the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Burn Ratio (NBR), and Tasseled Cap Transformation, to assess the extent of drought impacts. We found NBR to show the most consistent agreement with ground-based observations of drought-related tree mortality. Additionally, by integrating ground-based data from the “Dead Tree Detective” citizen science project, we were able to validate the remote sensing outcomes with a 90.22% consistency, providing confirmation of the extensive spatial distribution and severity of the inferred impacts. Our findings reveal that 13.16% of eucalypt forests and woodlands across eastern New South Wales experienced severe stress associated with drought during the 2019–2020 Black Summer drought. This study demonstrates the utility of satellite-derived drought indicators in monitoring forest health and highlights the necessity for continuous monitoring and research to understand the factors that trigger tree vitality loss.

Our understanding of how photosynthetic capacity varies among C4 species and across growth and measurement conditions remains limited. We collated 1696 CO2 response curves of net CO2 assimilation rate (A/Ci curves) from C4 species grown and measured at various environmental conditions and used these data to estimate the apparent maximum carboxylation activity of phosphoenolpyruvate carboxylase (VpmaxA) and CO2-saturated net photosynthetic rate (Amax), two key parameters describing photosynthetic capacity. We examined how VpmaxA and Amax vary with species-specific traits, growth and measurement conditions. We found little systematic variation of VpmaxA and Amax across the classical C4 biochemical subtypes or growth forms, but showed that growth temperature and measurement conditions are major factors determining C4 photosynthetic capacity. We found no evidence that common C4 model species (e.g. maize, sorghum and Setaria viridis) differ in photosynthetic capacity from other C4 species when grown in controlled environments. However, C4 model species showed up to twice the photosynthetic capacity of other C4 species when grown in the field. Our multivariate model accounts for 47-51% of the variation reported in VpmaxA and Amax, and we argue that environmental conditions have a greater influence on C4 photosynthetic capacity than biochemical subtypes or growth forms.

Accurate aboveground woody biomass (AGB) estimates are crucial for assessing the impact of elevated CO2 (eCO(2)) on net carbon sequestration in trees. Estimating AGB essentially involves developing allometric models using destructively harvested data. Due to the costs and restrictions of harvesting, models from other regions are often used. In the past two decades, terrestrial laser scanning (TLS) has become a widely accepted, non-destructive method for measuring tree structure. We provide new TLS-based allometric AGB models for Eucalyptus tereticornis, the dominant tree species at EucFACE, a replicated, ecosystem-scale mature forest free-air CO2 enrichment (FACE) experiment in Australia. Based on TLS-derived diameter at breast height (DBH), tree height (H), and crown area (CA) of 116 trees, we developed both an AGB:DBH model and an AGB:(CAxH) model. Our TLS-based AGB:DBH model (uncertainty = 19 %, bias <-1 %), shows substantially larger AGB growth compared to the previously-used allometric model at EucFACE. Although this new model does not change previous conclusions about the impact of eCO(2) on tree-level AGB increments at EucFACE, it does indicate a notable increase in AGB increment, particularly for larger trees. This highlights the need to recalculate net primary productivity and carbon partitioning at EucFACE. Additionally, we present a TLS-based AGB:(CAxH) model (uncertainty = 27 %, bias <1 %). These models improve accuracy in assessing carbon storage at EucFACE and offer scalable methods for monitoring AGB in E. tereticornis across broader landscapes. By enabling reliable, landscape-level carbon estimates, this work supports targeted forest management and conservation strategies under rising CO2 conditions.

Studies of plant responses to temperature often focus on rates photosynthesis and respiration. However, within-plant utilisation and allocation of carbon are also strongly affected. It is unclear how much each of these processes contribute to determining the overall temperature response of growth. We applied a data assimilation framework to a glasshouse experiment with detailed physiological and growth measurements to investigate the relative contribution of different physiological processes to the overall temperature response of tree seedling growth. We found that both short-term effects of temperature and acclimatory responses of photosynthesis and respiration had a significant impact on the temperature response of growth. However, the effect of temperature on biomass allocation patterns to different tissues, non-structural carbohydrate utilisation and C losses to other unmeasured losses were also substantial in determining the temperature response of growth, particularly at sub-optimal temperatures. Our work demonstrates that the growth response to warming cannot be predicted using only the direct effect of temperature on photosynthesis and respiration and emphasizes the importance of temperature acclimation of photosynthesis, respiration and other C balance processes. Our results provide new guidance for process-based models to correctly describe the temperature effects on tree growth.

Observations of drought-driven damage to vegetation are widespread but, until recently, large-scale terrestrial models used to study climate-vegetation interactions did not capture the contrasting sensitivities of plants to drought. This is changing with the advent of a generation of models that consider plant hydraulics. Plant hydraulics link plant water status to pedoclimatic conditions; as such, explicit consideration of plant hydraulics should make models more mechanistic and predictive. Models, however, diverge in how they represent the plant water transport pathway and relate it to other plant functions (e.g., photosynthesis), so they further diverge in their parameterisation approach for hydraulic processes. Only at the most basic level do plant hydraulic implementations converge on a common set of measurable traits or parameters: two that describe a hydraulic vulnerability curve (e.g., P12 and P50, the water potentials at which 12% and 50% of a plant’s hydraulic conductivity are lost, respectively), and one that quantifies the efficiency of water movement within the plant (e.g., maximum hydraulic conductance). Regrettably, we do not yet know how to obtain regional- or global-scale hydraulic parameters from local-scale measurements, nor how to connect them to other plant traits. In this study, we propose strategies to leverage cross-species hydraulic diversity when scaling traits from the species level into model parameters. We also emphasise the importance of accounting for (i) within-species trait variability across space (e.g., interactions between hydraulic traits and their environment) and (ii) cross-functional trait covariation (i.e., interactions – or lack thereof – among traits that characterise different functional axes). Beyond advancing regional and global plant hydraulic modelling, efforts to address the suggested strategies would ready models for simulations that capture the resilience of vegetation communities worldwide.

The capacity for terrestrial ecosystems to sequester additional carbon (C) with rising CO2 concentrations depends on soil nutrient availability1,2. Previous evidence suggested that mature forests growing on phosphorus (P)-deprived soils had limited capacity to sequester extra biomass under elevated CO2 (refs. 3-6), but uncertainty about ecosystem P cycling and its CO2 response represents a crucial bottleneck for mechanistic prediction of the land C sink under climate change7. Here, by compiling the first comprehensive P budget for a P-limited mature forest exposed to elevated CO2, we show a high likelihood that P captured by soil microorganisms constrains ecosystem P recycling and availability for plant uptake. Trees used P efficiently, but microbial pre-emption of mineralized soil P seemed to limit the capacity of trees for increased P uptake and assimilation under elevated CO2 and, therefore, their capacity to sequester extra C. Plant strategies to stimulate microbial P cycling and plant P uptake, such as increasing rhizosphere C release to soil, will probably be necessary for P-limited forests to increase C capture into new biomass. Our results identify the key mechanisms by which P availability limits CO2 fertilization of tree growth and will guide the development of Earth system models to predict future long-term C storage.

The forest–atmosphere exchange of carbon and water is regulated by meteorological conditions as well as canopy properties such as leaf area index (LAI, m2 m−2), photosynthetic capacity (PC μmol m−2 s−1), or surface conductance in optimal conditions (Gs,opt, mmol m−2 s−1), which can vary seasonally and inter-annually. This variability is well understood for deciduous species but is poorly characterized in evergreen forests. Here, we quantify the seasonal dynamics of a temperate evergreen eucalypt forest with estimates of LAI, litterfall, carbon and water fluxes, and meteorological conditions from measurements and model simulations. We merged MODIS Enhanced Vegetation Index (EVI) values with site-based LAI measurements to establish a 17-year sequence of monthly LAI. We ran the Community Atmosphere Biosphere Land Exchange model (CABLE-POP (version r5046)) with constant and varying LAI for our site to quantify the influence of seasonal canopy dynamics on carbon and water fluxes. We observed that the peak of LAI occurred in late summer–early autumn, with a higher and earlier peak occurring in years when summer rainfall was greater. Seasonality in litterfall and allocation of net primary productivity (FNPP) to leaf growth (af, 0–1) drove this pattern, suggesting a complete renewal of the canopy before the timing of peak LAI. Litterfall peaked in spring, followed by a high af in summer, at the end of which LAI peaked, and PC and Gs,opt reached their maximum values in autumn, resulting from a combination of high LAI and efficient mature leaves. These canopy dynamics helped explain observations of maximum gross ecosystem production (FGEP) in spring and autumn and net ecosystem carbon loss in summer at our site. Inter-annual variability in LAI was positively correlated with Net Ecosystem Production (FNEP). It would be valuable to apply a similar approach to other temperate evergreen forests to identify broad patterns of seasonality in leaf growth and turnover. Because incorporating dynamic LAI was insufficient to fully capture the dynamics of FGEP, observations of seasonal variation in photosynthetic capacity, such as from solar-induced fluorescence, should be incorporated in land surface models to improve ecosystem flux estimates in evergreen forests.

Allocation of non-structural carbohydrates to storage allows plants to maintain a carbon pool in anticipation of future stress. However, to do so, plants must forego use of the carbon for growth, creating a trade-off between storage and growth. It is possible that plants actively regulate the storage pool to maximize fitness in a stress-prone environment. Here, we attempt to identify the patterns of growth and storage that would result during drought stress under the hypothesis that plants actively regulate carbon storage. We use optimal control theory to calculate the optimal allocation to storage and utilization of stored carbon over a single drought stress period. We examine two fitness objectives representing alternative life strategies: prioritization of growth and prioritization of storage, as well as the strategies in between these extremes. We find that optimal carbon storage consists of three discrete phases: 'growth', 'storage without growth' and the 'stress' phase where there is no carbon source. This trajectory can be defined by the time point when the plant switches from growth to storage. Growth-prioritizing plants switch later and fully deplete their stored carbon over the stress period, while storage-prioritizing plants either do not grow or switch early in the drought period. The switch time almost always occurs before the soil water is depleted, meaning that growth stops before photosynthesis. We conclude that the common observation of increasing carbon storage during drought could be interpreted as an active process that optimizes plant performance during stress.

Droughts of increasing severity and frequency are a primary cause of forest mortality associated with climate change. Yet, fundamental knowledge gaps regarding the complex physiology of trees limit the development of more effective management strategies to mitigate drought effects on forests. Here, we highlight some of the basic research needed to better understand tree drought physiology and how new technologies and interdisciplinary approaches can be used to address them. Our discussion focuses on how trees change wood development to mitigate water stress, hormonal responses to drought, genetic variation underlying adaptive drought phenotypes, how trees 'remember' prior stress exposure, and how symbiotic soil microbes affect drought response. Next, we identify opportunities for using research findings to enhance or develop new strategies for managing drought effects on forests, ranging from matching genotypes to environments, to enhancing seedling resilience through nursery treatments, to landscape-scale monitoring and predictions. We conclude with a discussion of the need for co-producing research with land managers and extending research to forests in critical ecological regions beyond the temperate zone.

In the Central Himalayas, where environmental conditions vary greatly, understanding the biophysical limitations on forest carbon is crucial for accurately determining the region’s forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using field-observed plot-level carbon pool estimates from Nepal’s national forest inventory and structural equation modeling, we explore the relationship between forest carbon stocks and proxies of environmental constraints. The forest AGC and SOC models explained 25 % and 59 % of the observed spatial variation in forest AGC and SOC, respectively. The climatic availability of water and energy in broad-scale gradients combined with the fine-scale gradients of terrain and disturbance intensity were found to influence forest carbon stocks, but the sign and strength of the statistical relationships differ for forest AGC and SOC. While AGC showed a negative relationship to disturbance, SOC was impacted by the availability of climatic energy. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high-elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results have important implications for forest carbon management and conservation in the Central Himalayas.

The high elevation forests of the Central Himalayas include stands with an exceptional abundance of aboveground biomass, standing as some of the most carbon-rich forests in the entire Himalayan range and beyond. National or regional models, however, are inadequate in capturing this extreme concentration of biomass observed in select forest inventory plots. We aimed to identify factors contributing to the significant variability of biomass and thus, aboveground forest carbon in the high mountain forests of Nepal. By comparing the utilization of pantropical and Nepali allometric equations, we evaluated whether the elevational gradients in forest biomass were robust to changes in the allometric models used to predict plot biomass. Irrespective of the model employed, the highest biomass values were found in high elevation plots. The diverse distribution of forest biomass reinforces established size-density relationships, attributing observed variations to the interplay between tree size and density. Our results contribute valuable insights into these high biomass forests, affirming observed elevational gradients, quantifying the impact of tree species and structure, and elucidating factors influencing biomass sites concerning allometric models.