Terrestrial ecosystem respiration (Re) is a crucial component of the carbon cycle and is expected to increase with anthropogenic warming. The temperature response of Re is typically parameterized using temperature sensitivity Q10, which describes the increase in respiration with a 10oC rise in temperature. The respiration increase largely determines the future direction of the terrestrial-atmosphere carbon balance. However, our current understanding of the mechanisms driving Q10 variation across latitudes and biomes is still insufficient. As a result, it remains difficult to constrain predictions of future Re dynamics. The Michaelis–Menten (MM) kinetics , developed to describe enzyme-catalyzed reactions, is a cornerstone to understand biochemical processes at the cellular and molecular levels. This model effectively captures the relationship between substrate concentration and reaction rates, simplifying complex biochemical interactions into manageable mathematical expressions using the key parameters Vmax (maximum reaction rate) and Km (substrate concentration at half the maximum rate). However, the applicability of this microscopic model to large-scale ecosystem processes can be questioned . Most Earth system models incorporate the Farquhar–von Caemmerer–Berry (FvCB) biochemical model, which is grounded in Michaelis–Menten kinetics, to simulate photosynthesis at ecosystem or larger scales. However, the description of respiration processes over large ecosystem scale still predominantly relies on more empirical models, projecting an exponential temperature response with Arrhenius or Q10 types of functions.

Terrestrial ecosystem respiration increases exponentially with temperature, constituting a positive feedback loop accelerating global warming. However, the response of ecosystem respiration to temperature strongly depends on water availability, yet where and when the water effects are important, is presently poorly constrained, introducing uncertainties in climate-carbon cycle feedback projections. Here, we disentangle the effects of temperature and precipitation (a proxy for water availability) on ecosystem respiration by analysing eddy covariance CO2 flux measurements across 212 globally distributed sites. We reveal a threshold precipitation function, determined by the balance between precipitation and ecosystem water demand, which separates temperature-limited and water-limited respiration. Respiration is temperature limited for precipitation above that threshold function, whereas in drier areas water limitation reduces the temperature sensitivity of respiration and its positive feedback to global warming. If the trend of expansion of water-limited areas with warming climate over the last decades continues, the positive feedback of ecosystem respiration is likely to be weakened and counteracted by the increasing water limitation.

Global soils store more carbon than the atmosphere and terrestrial vegetation combined, with a significant proportion located in colder regions. Earth system models incorporating climate-carbon feedback suggest that a warming climate can potentially destabilize soil carbon storage, leading to carbon release into the atmosphere. However, existing models are based on limited measurements of soil organic carbon (SOC) loss and a comprehensive global-scale climate indices that effectively characterizes climate-SOC relationships is currently lacking. In this study, we present a synthetic analysis that evaluates the effectiveness of different climate indices in estimating SOC stocks using a global compilation of SOC data and the Boltzmann Sigmoidal Model (BSM). Our findings reveal that a climate index, defined as ${\rm TD}\hbox{-}{\rm Index} = {\rm exp}\lpar {-0.002T-0.8D} \rpar$TD-Index=exp(-0.002T-0.8D), where T and D are mean century temperature (MCT) and dryness respectively, serves as the most reliable predictor for SOC stocks. Furthermore, we observed temperature tipping points for SOC, ranging from -4.5 to -3 degrees C for different soil layers. As the temperature transitions from being below to above the tipping point, the SOC shifts from a stable, high state to a rapid decline. An analysis of the projected temperatures for SOC under various future greenhouse gas emissions scenarios showed a northward shift in the northern hemisphere, potentially opening up vast areas of arctic territory to increased SOC loss from the soils, with corresponding emissions of the stored carbon into the atmosphere. Our findings open up new avenues for research on and management strategies for climate-related SOC dynamics.

This ERL focus collection has published 17 papers that have advanced our understanding of different dimensions of warming-induced tree mortality. Here we summarize these focus collection papers, organized by four topics related to tree mortality: pathogens, droughts/heat waves, fire/bark beetles, and teleconnections/air pollution. This focus collection illustrates a variety of methods in measuring and modeling tree-mortality, and adds significant new research findings into the scientific literature on tree mortality from hotter droughts. Some of these results also are useful for policymakers and forest managers in addressing amplified forest stress and tree mortality as a result of increasingly severe warming-induced climate and weather extremes.

Several cotton experiments have been conducted at the University of Arizona's Maricopa Agricultural Center from which datasets have been obtained documenting cotton responses to elevated CO2 concentrations, water supply, nitrogen fertilizer, and planting density. In particular, these experiments included FACE (free-air CO2 enrichment; CO2, water; 10 treatment-years), AgIIS (Agricultural Irrigation Imaging System, pronounced Ag Eyes; nitrogen fertilizer, water supply; 4 treatment-years), and FISE (FAO-56 Irrigation Scheduling Experiments; irrigation scheduling method, planting density, nitrogen fertilizer; 24 treatment-years). Besides achieving the experimental objectives of determining cotton's response to the several variables, as well as testing remote sensing techniques, the comprehensive datasets are suitable for validating plant growth models because they include weather, soils, management, growth, yield and other data.

A shift to higher temperatures has left the Mediterranean Europe and Northern Africa (MENA) region more vulnerable to drought and land degradation. We used MODIS LAI (leaf area index) and GPP (gross primary production) deficits, the differences between actual and historical-maximum values, to describe vegetation structural and functional changes and consequential landcover change in response to changing climate conditions during 2001–2019 in the area (20° W–45° E, 20° N–45° N). We found that 1) the vegetation responses varied significantly among eight landcover types with the decreasing importance: forests, savannas, a mosaic of cropland and natural vegetation (CNV), croplands, permanent wetlands, urban land, grasslands, and shrublands, each with distinctive yet overlapping signatures over the ranges of the climate conditions considered. 2) Forests, occupying the coolest and wettest niche, showed the strongest response to severe drought with a lag of 1–3 years and a legacy effect for 10 years. Shrubs, occupying the hottest and driest niche, were the most resilient under a hotter and drier climate. 3) The total areas of savannas and CNV increased by 394,994 and 404,592 km2, respectively, while that of forests decreased by 33,091 km2. Shrublands extended by 287,134 km2 while grasslands and croplands retreated by 490,644 and 225,263 km2. The area of wetlands increased by 49,192 km2, and that of urban land increased by 39,570 km2. A total of 57,649 km2 of barren land became vegetated over the years. Along with higher temperature and more extended period of drought, MENA has evolved towards a shrubbier landscape.

: A shift to warmer temperatures has left the Mediterranean Europe and Northern Africa (MENA) region more vulnerable to drought and land degradation. We used LAI and GPP 24 deficit, the difference between actual and historical-maximum values, to describe vegetation 25 structural and functional dynamics and consequential landcover change in response to climate 26 variability during 2001-2019 in the area (20  W-45  E, 20  N-45  N). We found that (1) the 27 vegetation responses varied significantly among eight landcover types with the following ranked 28 importance: forests, savannas, a mosaic of cropland and natural vegetation (CNV), croplands, 29 permanent wetlands, urban land, grasslands, and shrublands, each with distinctive yet 30 overlapping signatures over the spectrums of the climate conditions considered. (2) Forests, 31 occupying the coolest and wettest niche of the MENA region, showed the strongest and most 32 dominating response to severe drought with a lag of 1-3 years and a legacy of 10 years. (3) The 33 total areas of savannas and CNV mosaics in MENA increased by 394,994 km 2 and 404,592 km 2 34 respectively while that of forests decreased by 33,091 km 2 despite of the fertilizer effect of 35 elevated ambient CO 2 . Shrublands, occupying the hottest and driest niche of MENA, extended 36 by 287,134 km 2 while grasslands and croplands retreated by 490,644 km 2 and 225,263 km 2 . The 37 area of permanent wetlands increased by 49,192 km 2 , and that of urban land increased by 39,570 38 km 2 . A net total of 57,649 km 2 of barren land became vegetated over the years. With warmer 39 temperature and more extended period of drought, MENA has evolved towards a shrubbier 40 landscape. 41

Here, we show a discernable increase in temperature variance before a glacial termination by both the Ansari-Bradley test and the moving variance methods plus introduce the idea that there is a correlation between the peak variance and peak temperature increase. The behavior of temperature variance shows potential as a useful tool in analyzing time series data of Earth systems to assess the risk and extent of an upcoming abrupt climate transition.

We have integrated the observational capability of satellite remote sensing with plot-scale tree-ring data to upscale the evaluation of forest responses to drought. Satellite data, such as the normalized difference vegetation index (NDVI), can provide a spatially continuous measure with limited temporal coverage, while tree-ring width index (RWI) provides an accurate assessment with a much longer time series at local scales. Here, we explored the relationship between RWI and NDVI of three dominant species in the Southwestern United States (SWUS) and predicted RWI spatial distribution from 2001 to 2017 based on Moderate Resolution Imaging Spectroradiometer (MODIS) 1-km resolution NDVI data with stringent quality control. We detected the optimum time windows (around June–August) during which the RWI and NDVI were most closely correlated for each species, when the canopy growth had the greatest effect on growth of tree trunks. Then, using our upscaling algorithm of NDVI-based RWI, we were able to detect the significant impact of droughts in 2002 and in 2011–2014, which supported the validity of this algorithm in quantifying forest response to drought on a large scale.

How are the survival and growth of trees under severe drought affected by their size? While some studies have shown that large trees are more vulnerable to drought than smaller trees, others found that small trees are the more vulnerable. We explored the potential relationships between canopy height and forest responses to drought indicated by tree mortality, tree ring width index (RWI), and normalized difference vegetation index (NDVI) in the southwestern United States (SWUS) in 2002. In that year many trees had zero tree ring growth due to mortality and dieback, presumably related to drought-stress. With RWI data from a tree ring data base and climate data co-located with the field measurements, we found size-dependent linear correlations between these forest responses and canopy height in SWUS under severe drought condition. During that drought period, both trunk growth (RWI) and leaf growth (NDVI) were positively correlated with canopy height of the smaller trees (less than 18 m) and negatively correlated with canopy height of greater than 18 m. Tree mortality was negatively correlated with canopy height up to 15 m. Both local-scale and regional-scale data are consistent in showing that forests with medium canopy height (around 18 meters) showed the greatest resistance to severe drought. We suggest that negative impacts of severe drought on forests could be modified with active management of canopy structure.

Several lines of evidence suggest that forest growth in many regions is declining as a consequence of changing climate. To predict the fate of forests in the future, a quantitative understanding of how the key climate variables (insolation, precipitation and temperature) interact with forests to cause the decline is a pressing need. Here we use a regionally-averaged tree-ring width index (RWIr) to quantify forest growth in the Southwest United States (SWUS). We show that over a period of 90 years, SWUS RWIr bifurcated into forest stands with enhanced (healthy) and reduced (declining) branches when regressed on shortwave-radiation and temperature, respectively. The reduced branch was controlled overwhelmingly by drought as measured with a regionally-averaged precipitationevapotranspiration index (SPEIr). As SPEIr approached -1.6 (previously shown as a tipping-point for SWUS conifer forest growth), RWIr approached zero and in extreme drought years, wide spread tree mortality has been observed. Modeled trends in SPEI based on four IPCC-GHG scenarios predict SWUS SPEIr falling below -1.6 more or less continuously within a few decades. With drought expanding north- and eastward over larger areas, tree mortality may become a semi-continental phenomenon with coniferous forests transitioning to more xeric ecosystems. Our results provide insights into how to differentiate functions of climate impacts on forest growth and how to identify tipping-point control parameters for forest regime transitions.

Light-use efficiency (LUE) is at the core of mechanistic modeling of global gross primary production (GPP). However, most LUE estimates in global models are satellite based and coarsely measured with emphasis on environmental variables. Others are from eddy covariance towers with much greater spatial and temporal data quality and emphasis on mechanistic processes, but in a limited number of sites. In this study, we conducted a comprehensive global study of tower-based LUE from 237 FLUXNET towers, and scaled up LUEs from in situ tower level to global biome level. We integrated the tower-based LUE estimates with key environmental and biological variables at 0.5 degrees 9 0.5 degrees grid-cell resolutions, using a random forest regression (RFR) approach. Then, we developed a RFR-LUE-GPP model using the grid-cell LUE data. In order to calibrate the LUE model, we developed a data-driven RFR-GPP model using RFR method only. Our results showed LUE varies largely with latitude. We estimated a global area-weighted average of LUE at 1.23 +/- 0.03 g C. m(- 2) .MJ(-1) APAR, which led to an estimate of global GPP of 107.5 +/- 2.5 Gt C/yr from 2001 to 2005. Large uncertainties existed in GPP estimations over sparsely vegetated areas covered by savannas and woody savannas at middle to low latitude (i. e., 20 degrees S-40 degrees S and 5 degrees N-40 degrees N) due to the lack of available data. Model results were improved by incorporating Koppen climate types to represent climate/meteorological information in machine-learning modeling. This brought a new understanding to the recognized problem of climate dependence of spring onset of photosynthesis and the challenges in accurately modeling the biome GPP of evergreen broadleaf forests (EBF). The divergent responses of GPP to temperature and precipitation at middle to high latitudes and at middle to low latitudes echo the necessity of modeling GPP separately by latitudes.

This study generated eddy covariance data to investigate atmospheric dynamics leeward of a small, forested hillside in upstate New York. The causes and effects of recirculation eddies were examined to support the larger goal of improving measurement of the exchange of energy, moisture, and trace gases between the terrestrial biosphere and the atmosphere over complex terrain. Sensors operated at five different altitudes on two separate towers—one at the top of the hill and one down the slope to the east—for approximately 8 weeks in the spring of 2013. During the experiment, the vertical potential temperature gradient was found to be the primary factor for determining whether winds interacting with the terrain features caused a recirculating eddy leeward of the hill. The study found evidence that the recirculation influenced carbon dioxide flux and caused the air column to be vertically well mixed.

Three young northern temperate forest communities in the north‐central United States were exposed to factorial combinations of elevated carbon dioxide (CO2) and tropospheric ozone (O3) for 11 years. Here, we report results from an extensive sampling of plant biomass and soil conducted at the conclusion of the experiment that enabled us to estimate ecosystem carbon (C) content and cumulative net primary productivity (NPP). Elevated CO2 enhanced ecosystem C content by 11%, whereas elevated O3 decreased ecosystem C content by 9%. There was little variation in treatment effects on C content across communities and no meaningful interactions between CO2 and O3. Treatment effects on ecosystem C content resulted primarily from changes in the near‐surface mineral soil and tree C, particularly differences in woody tissues. Excluding the mineral soil, cumulative NPP was a strong predictor of ecosystem C content (r2 = 0.96). Elevated CO2 enhanced cumulative NPP by 39%, a consequence of a 28% increase in canopy nitrogen (N) content (g N m−2) and a 28% increase in N productivity (NPP/canopy N). In contrast, elevated O3 lowered NPP by 10% because of a 21% decrease in canopy N, but did not impact N productivity. Consequently, as the marginal impact of canopy N on NPP (∆NPP/∆N) decreased through time with further canopy development, the O3 effect on NPP dissipated. Within the mineral soil, there was less C in the top 0.1 m of soil under elevated O3 and less soil C from 0.1 to 0.2 m in depth under elevated CO2. Overall, these results suggest that elevated CO2 may create a sustained increase in NPP, whereas the long‐term effect of elevated O3 on NPP will be smaller than expected. However, changes in soil C are not well‐understood and limit our ability to predict changes in ecosystem C content.

At biome-scale, terrestrial carbon uptake is controlled mainly by weather variability. Observational data from a global monitoring network indicate that the sensitivity of terrestrial carbon sequestration to mean annual temperature ( T ) breaks down at a threshold value of 16°C, above which terrestrial CO 2 fluxes are controlled by dryness rather than temperature. Here we show that since 1948 warming climate has moved the 16°C T latitudinal belt poleward. Land surface area with T > 16°C and now subject to dryness control rather than temperature as the regulator of carbon uptake has increased by 6% and is expected to increase by at least another 8% by 2050. Most of the land area subjected to this warming is arid or semiarid with ecosystems that are highly vulnerable to drought and land degradation. In areas now dryness-controlled, net carbon uptake is ~27% lower than in areas in which both temperature and dryness ( T < 16°C) regulate plant productivity. This warming-induced extension of dryness-controlled areas may be triggering a positive feedback accelerating global warming. Continued increases in land area with T > 16°C has implications not only for positive feedback on climate change, but also for ecosystem integrity and land cover, particularly for pastoral populations in marginal lands.

Several lines of evidence suggest that the warming climate plays a vital role in driving certain types of extreme weather. The impact of warming and of extreme weather on forest carbon assimilation capacity is poorly known. Filling this knowledge gap is critical towards understanding the amount of carbon that forests can hold. Here, we used a perfect-deficit approach to identify forest canopy photosynthetic capacity (CPC) deficits and analyze how they correlate to climate extremes, based on observational data measured by the eddy covariance method at 27 forest sites over 146 site-years. We found that droughts severely affect the carbon assimilation capacities of evergreen broadleaf forest (EBF) and deciduous broadleaf forest. The carbon assimilation capacities of Mediterranean forests were highly sensitive to climate extremes, while marine forest climates tended to be insensitive to climate extremes. Our estimates suggest an average global reduction of forest CPC due to unfavorable climate extremes of 6.3 Pg C (∼5.2% of global gross primary production) per growing season over 2001–2010, with EBFs contributing 52% of the total reduction.

Temperature sensitivity of soil respiration (Q10) is a critical parameter in carbon cycle models with important implications for climate-carbon feedbacks in the 21st century. The common assumption of a constant Q10, usually with a value of 2.0, was shown to be invalid by a previous model-data fusion study that reported biome-specific values of this parameter. We extend the previous analysis by demonstrating that these biome-level values of Q10 also are a function of dryness (R2 = 0.54). When tundra and cultivated lands are excluded, the correlation is much stronger (R2 = 0.92). Therefore dryness is the primary driver for variability in respiration-temperature sensitivity in forest and grassland ecosystems. This finding has important implications for the response of the terrestrial carbon cycle to climate change, as it implies that the increasing dryness would potentially accelerate the respiration temperature sensitivity feedback.

The considerable interannual variability (IAV) (∼5 PgC yr−1) observed in atmospheric CO2 is dominated by variability in terrestrial productivity. Among terrestrial ecosystems, grassland productivity IAV is greatest. Relationships between grassland productivity IAV and climate drivers are poorly explained by traditional multiple-regression approaches. We propose a novel method, the perfect-deficit approach, to identify climate drivers of grassland IAV from observational data. The maximum daily value of each ecological or meteorological variable for each day of the year, over the period of record, defines the ‘perfect’ annual curve. Deficits of these variables can be identified by comparing daily observational data for a given year against the perfect curve. Links between large deficits of ecosystem activity and extreme climate events are readily identified. We applied this approach to five grassland sites with 26 site-years of observational data. Large deficits of canopy photosynthetic capacity and evapotranspiration derived from eddy-covariance measurements, and leaf area index derived from satellite data occur together and are driven by a local-dryness index during the growing season. This new method shows great promise in using observational evidence to demonstrate how extreme climate events alter yearly dynamics of ecosystem potential productivity and exchanges with atmosphere, and shine a new light on climate–carbon feedback mechanisms.