CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America

Dynamic regulation of water potential in Juniperus osteosperma mediates ecosystem carbon fluxes

Some plants exhibit dynamic hydraulic regulation, in which the strictness of hydraulic regulation (i.e. iso/anisohydry) changes in response to environmental conditions. However, the environmental controls over iso/anisohydry and the implications of flexible hydraulic regulation for plant productivity remain unknown. In Juniperus osteosperma, a drought-resistant dryland conifer, we collected a 5-month growing season time series of in situ, high temporal-resolution plant water potential ( Ψ ) and stand gross primary productivity (GPP). We quantified the stringency of hydraulic regulation associated with environmental covariates and evaluated how predawn water potential contributes to empirically predicting carbon uptake. Juniperus osteosperma showed less stringent hydraulic regulation (more anisohydric) after monsoon precipitation pulses, when soil moisture and atmospheric demand were high, and corresponded with GPP pulses. Predawn water potential matched the timing of GPP fluxes and improved estimates of GPP more strongly than soil and/or atmospheric moisture, notably resolving GPP underestimation before vegetation green-up. Flexible hydraulic regulation appears to allow J. osteosperma to prolong soil water extraction and, therefore, the period of high carbon uptake following monsoon precipitation pulses. Water potential and its dynamic regulation may account for why process-based and empirical models commonly underestimate the magnitude and temporal variability of dryland GPP.

Dynamics of carbon and water vapor fluxes in three typical ecosystems of Heihe River Basin, Northwestern China

Understanding the dynamics of carbon and water vapor fluxes in arid inland river basin ecosystems is essential for predicting and assessing the regional carbon-water budget amid climate change. However, studies aiming to unravel the mechanisms driving the variations and coupling process of regional carbon-water budget in a changing environment in arid regions are limited. Here, we used the eddy covariance technique to analyze the relationship between CO2 and H2O fluxes in three typical ecosystems across the upper, middle, and lower reaches of an arid inland river basin in Northwestern China. Our results showed that all ecosystems acted as carbon sinks, with the alpine swamp meadow, cropland, and desert shrubland sequestrating -300.2 ± 0.01, -644.8 ± 2.9, and - 203.7 ± 22.5 g C m-2 yr-1, respectively. Air temperature (Ta) primarily controlled daily gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE) in the irrigated cropland during the growing season, while soil temperature (Ts) and vapor pressure deficit (VPD) regulated these parameters in the alpine swamp meadow and desert shrubland. Additionally, Ta and net radiation (Rn) controlled daily evapotranspiration (ET) in cropland, while Ts and Rn regulated ET at other sites. Consequently, carbon and water vapor fluxes of all three ecosystems tended to be energy-limited during the growing season. The differential responses of carbon and water vapor fluxes in the upper, middle, and lower reaches of these ecosystems to biophysical factors determined their distinct coupling and variations in water use efficiency. Notably, the desert shrub ecosystem in the lower reach of the basin maintained a stable balance between carbon gain and water loss, indicating adaptation to aridity. This study provides valuable insights into the underlying mechanisms behind the changes in carbon and water vapor fluxes and water-use efficiency in arid river basin ecosystems.

Mapping Sub-surface Distribution of Soil Organic Carbon Stocks in South Africa's Arid and Semi-Arid Landscapes: Implications for Land Management and Climate Change Mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Characterization and drivers of water and carbon fluxes dynamics in dune ecosystems of the Horqin Sandy Land

Sandy regions constitute pivotal components of terrestrial ecosystems, exerting significant influences on global ecological equilibrium and security. This study meticulously explored water and carbon fluxes dynamics within a dune ecosystem in the Horqin Sandy Land throughout the growing seasons from 2013 to 2022 by employing an advanced eddy covariance system. The dynamic characteristics of these fluxes and their underlying driving forces were extensively analyzed, with a particular focus on the impact of precipitation. The main results are as follows: (1) During the growing seasons of 2015 and 2016, the dune ecosystem acted as a modest carbon source, while in 2013, 2014, and 2017- 2022, it transformed into a net carbon sink. Notably, the annual mean values of water use efficiency (WUE) and evapotranspiration (ET) were 5.16 gC·kg-1H2O and 255.4 mm, respectively. (2) The intensity, frequency, and temporal distribution of precipitation were found to significantly influence the carbon and water fluxes dynamics. Isolated minor precipitation events did not trigger substantial fluctuations, but substantial and prolonged precipitation events spanning multiple days or consecutive minor precipitation events resulted in notable assimilation delays. (3) Air temperature, soil temperature, and fractional vegetation cover (FVC) were found to be key factors influencing the carbon and water fluxes. Specifically, FVC exhibited a negative logarithmic correlation with net ecosystem CO2 exchange (NEE) and a power function relationship with WUE. (4) The interaction between carbon and water fluxes is exhibited by exponential increases in ecosystem respiration (Reco) and gross primary productivity (GPP) with WUE, while NEE displayed an exponential decrease in relation to WUE. These findings are of high significance in predicting the potential ramifications of climate change on the intricate carbon and water cycles, and enhance our understanding of ecosystem dynamics in sandy environments.

Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012-2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m-2 yr-1, mean ± SD). Annual NEP ranged from -66 to 77 g C m-2 yr-1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr-1 or rainfall dropped below 280 mm yr-1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Plant mycorrhizal associations mediate the zoogeochemical effects of calving subsidies by a forest ungulate

Animals interact with and impact ecosystem biogeochemical cycling-processes known as zoogeochemistry. While the deposition of various animal materials (e.g. carcasses and faeces) has been shown to create nutrient hotspots and alter nutrient cycling and storage, the inputs from parturition (i.e. calving) have yet to be explored. We examine the effects of ungulate parturition, which often occurs synchronously during spring green-up and therefore aligns with increased plant nitrogen demand in temperate biomes. Impacts of zoogeochemical inputs are likely context-dependent, where differences in material quality, quantity and the system of deposition modulate their impacts. Plant mycorrhizal associations, especially, create different nutrient-availability contexts, which can modify the effects of nutrient inputs. We, therefore, hypothesize that mycorrhizal associations modulate the consequences of parturition on soil nutrient dynamics and nitrogen pools. We established experimental plots that explore the potential of two kinds of zoogeochemical inputs deposited at ungulate parturition (placenta and natal fluid) in forest microsites dominated by either ericoid mycorrhizal (ErM) or ectomycorrhizal (EcM) plants. We assess how these inputs affect rates of nutrient cycling and nitrogen content in various ecosystem pools, using isotope tracers to track the fate of nitrogen inputs into plant and soil pools. Parturition treatments accelerate nutrient cycling processes and increase nitrogen contents in the plant leaf, stem and fine root pools. The ecosystem context strongly modulates these effects. Microsites dominated by ErM plants mute parturition treatment impacts on most nutrient cycling processes and plant pools. Both plant-fungal associations are, however, equally efficient at retaining nitrogen, although retention of nitrogen in the parturition treatment plots was more than two times lower than in control plots. Our results highlight the potential importance of previously unexamined nitrogen inputs from animal inputs, such as those from parturition, in contributing to fine-scale heterogeneity in nutrient cycling and availability. Animal inputs should therefore be considered, along with their interactions with plant mycorrhizal associations, in terms of how zoogeochemical dynamics collectively affect nutrient heterogeneity in ecosystems.

Increased photosynthesis during spring drought in energy-limited ecosystems

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

Soil moisture dominates the variation of gross primary productivity during hot drought in drylands

The frequency and severity of hot drought will increase in the future due to impact of climate change and human activities, threatening the sustainability of terrestrial ecosystems and human societies. Hot drought is a typical type of drought event, high vapor pressure deficit (VPD) and low soil moisture (SM) are its main characteristics of hot drought, with increasing water stress on vegetation and exacerbating hydrological drought and ecosystem risks. However, our understanding of the effects of high VPD and low SM on vegetation productivity is limited, because these two variables are strongly coupled and influenced by other climatic drivers. The southwestern United States experienced one of the most severe hot drought events on record in 2020. In this study, we used SM and gross primary productivity (GPP) datasets from Soil Moisture Active and Passive (SMAP), as well as VPD and other meteorological datasets from gridMET. We decoupled the effects of different meteorological factors on GPP at monthly and daily scales using partial correlation analysis, partial least squares regression, and binning methods. We found that SM anomalies contribute more to GPP anomalies than VPD anomalies at monthly and daily scales. Especially at the daily scale, as the decoupled SM anomalies increased, the GPP anomalies increased. However, there is no significant change in GPP anomalies as VPD increases. For all the vegetation types and arid zones, SM dominated the variation in GPP, followed by VPD or maximum temperature. At the flux tower scale, decoupled soil water content (SWC) also dominated changes in GPP, compared to VPD. In the next century, hot drought will occur frequently in dryland regions, where GPP is one of the highest uncertainties in terrestrial ecosystems. Our study has important implications for identifying the strong coupling of meteorological factors and their impact on vegetation under climate change.

The extreme wet and large precipitation size increase carbon uptake in Eurasian meadow steppes: Evidence from natural and manipulated precipitation experiments

The distribution of seasonal precipitation would profoundly affect the dynamics of carbon fluxes in terrestrial ecosystems. However, little is known about the impacts of extreme precipitation and size events on ecosystem carbon cycle when compared to the effects of average precipitation amount. The study involved an analysis of carbon fluxes and water exchange using the eddy covariance and chamber based techniques during the growing seasons of 2015-2017 in Bayan, Mongolia and 2019-2021 in Hulunbuir, Inner Mongolia, respectively. The components of carbon fluxes and water exchange at each site were normalized to evaluate of relative response among carbon fluxes and water exchange. The investigation delved into the relationship between carbon fluxes and extreme precipitation over five gradients (control, dry spring, dry summer, wet spring and wet summer) in Hulunbuir meadow steppe and distinct four precipitation sizes (0.1-2, 2-5, 5-10, and 10-25 mm d-1) in Bayan meadow steppe. The wet spring and summer showed the greatest ecosystem respiration (ER) relative response values, 76.2% and 73.5%, respectively, while the dry spring (-16.7%) and dry summer (14.2%) showed the lowest values. Gross primary production (GPP) relative response improved with wet precipitation gradients, and declined with dry precipitation gradients in Hulunbuir meadow steppe. The least value in net ecosystem CO2 exchange (NEE) was found at 10-25 mm d-1 precipitation size in Bayan meadow steppe. Similarly, the ER and GPP increased with size of precipitation events. The structural equation models (SEM) satisfactorily fitted the data (χ2 = 43.03, d.f. = 11, p = 0.215), with interactive linkages among soil microclimate, water exchange and carbon fluxes components regulating NEE. Overall, this study highlighted the importance of extreme precipitation and event size in influencing ecosystem carbon exchange, which is decisive to further understand the carbon cycle in meadow steppes.

Diagnosing evapotranspiration responses to water deficit across biomes using deep learning

Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole-column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water-unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage.

Divergent response to abiotic factor determines the decoupling of water and carbon fluxes over an artificial C4 shrub in desert

Knowledge on relationship and determinants of water and carbon dioxide (CO2) exchange is crucial to land managers and policy makers especially for the desertified land restoration. However, there remains highly uncertain in terms of water use and carbon sequestration for artificial plantation in desert. Here, continuous water and carbon fluxes were measured using eddy covariance (EC) in conjunction with hydrometeorological measurements over an artificial C4 shrub, Haloxylon ammodendron (C. A. Mey.) Bunge, from July 2020 to 2021 in Tengger Desert, China. Throughout 2021, evapotranspiration (ET) was 189.5 mm, of which 85% (150 mm) occurred during growing season, that was comparable with the summation of precipitation (132.2 mm), dew (33.5 mm) and potential other sources (e.g. deep subsoil water). This ecosystem was a strong carbon sink with net ecosystem production (NEP) up to 446.4 g C m-2 yr-1, much higher than surrounding sites. Gross primary production (GPP, 598.7 g C m-2 yr-1) in this shrubland was comparable with that of other shrublands, whereas ecosystem respiration (Re, 152.3 g C m-2 yr-1) was lower. Random Forest showed that environmental factors can explain 71.56% and 80.07% variation of GPP and ET, respectively. Interestingly, environmental factors have divergent effect on water and carbon exchange, i.e., soil hydrothermic factors (soil moisture content and soil temperature) determine the magnitude and seasonal pattern of ET and Re, while aerodynamics factors (net radiation, atmospheric temperature and wind speed) determine GPP and NEP. As such, divergent response of abiotic factors resulted in the decoupling of water and carbon exchange. Our results suggest that H. ammodendron is a suitable species for large-scale afforestation in dryland given its low water use but high carbon sequestration. Therefore, we infer that artificial planting H. ammodendron in dryland could provide an opportunity for climate change mitigation, and the long-term time series data is needed to confirm its sustainable role of carbon sequestration in the future.

AmeriFlux BASE data pipeline to support network growth and data sharing

AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.

As above, not so below: Long-term dynamics of net primary production across a dryland transition zone

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long-term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one-time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long-term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.

Persistent and enhanced carbon sequestration capacity of alpine grasslands on Earth's Third Pole

The carbon sequestration capacity of alpine grasslands, composed of alpine meadows and steppes, in the Tibetan Plateau has an essential role in regulating the regional carbon cycle. However, inadequate understanding of its spatiotemporal dynamics and regulatory mechanisms restricts our ability to determine potential climate change impacts. We assessed the spatial and temporal patterns and mechanisms of the net ecosystem exchange (NEE) of carbon dioxide in the Tibetan Plateau. The carbon sequestration of the alpine grasslands ranged from 26.39 to 79.19 Tg C year^-1 and had an increasing rate of 1.14 Tg C year^-1 between 1982 and 2018. While alpine meadows were relatively strong carbon sinks, the semiarid and arid alpine steppes were nearly carbon neutral. Alpine meadow areas experienced strong increases in carbon sequestration mainly because of increasing temperatures, while alpine steppe areas had weak increases mainly due to increasing precipitation. Carbon sequestration capacity of alpine grasslands on the plateau has undergone persistent enhancement under a warmer and wetter climate.

Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands

The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.

A stronger advance of urban spring vegetation phenology narrows vegetation productivity difference between urban settings and natural environments

Climate change is posing dramatic effects on terrestrial vegetation dynamics. The links between vegetation phenology or vegetation activity (growth) and climate change have been widely reported, yet, less is known about the impacts of phenological shifts on vegetation growth. Urban settings characterized by urban heat island and CO₂ dome are often used as ideal natural laboratories to understand how vegetation responds to global climate change. Here we assessed the impacts of phenology changes on vegetation growth in China using satellite phenology metrics and gross primary production (GPP) data from 2003 to 2018 and urban-natural contrast analysis. Compared with natural environments, phenological metrics (e.g., start/end of growing season (SOS/EOS), and the length of growing season (GSL), etc.) were observed to change more dramatically in urban environments. Furthermore, we found that GPP in both settings increased over time but with a higher increment in the urban environments, and the urban-natural vegetation productivity gap had been diminishing at a rate of 16.9 ± 6.76 g C m^-2 y^-1. The narrowing of the urban-natural GPP difference over time can be attributed to a more advanced SOS and extended GSL in urban settings than their natural counterparts, particularly SOS shift. These findings suggested that the distinct urban phenological shifts would become increasingly important in offsetting the loss of vegetation productivity induced by urbanization.

Changes and net ecosystem productivity of terrestrial ecosystems and their influencing factors in China from 2000 to 2019

Changes in net ecosystem productivity (NEP) in terrestrial ecosystems in response to climate warming and land cover changes have been of great concern. In this study, we applied the normalized difference vegetation index (NDVI), average temperature, and sunshine hours to drive the C-FIX model and to simulate the regional NEP in China from 2000 to 2019. We also analyzed the spatial patterns and the spatiotemporal variation characteristics of the NEP of terrestrial ecosystems and discussed their main influencing factors. The results showed that (1) the annual average NEP of terrestrial ecosystems in China from 2000 to 2019 was 1.08 PgC, exhibiting a highly significant increasing trend with a rate of change of 0.83 PgC/10 y. The terrestrial ecosystems in China remained as carbon sinks from 2000 to 2019, and the carbon sink capacity increased significantly. The NEP of the terrestrial ecosystem increased by 65% during 2015-2019 compared to 2000-2004 (2) There was spatial differences in the NEP distribution of the terrestrial ecosystems in China from 2000-2019. Taking the line along the Daxinganling-Yin Mountains-Helan Mountains-Transverse Range as the boundary, the NEP was significantly higher in the eastern part than in the western part. Among them, the NEP was positive (carbon sink) in northeastern, central, and southern China, and negative (carbon source) in parts of northwestern China and the Tibet Autonomous Region. The spatial variation of NEP in terrestrial ecosystems increased from 2000 to 2009. The areas with a significant increase accounted for 45.85% and were mainly located in the central and southwestern regions. (3) The simulation results revealed that vegetation changes and CO2 concentration changes both contributed to the increase in the NEP in China, contributing 85.96% and 36.84%, respectively. The vegetation changes were the main factor causing the increase in the NEP. The main contribution of this study is to further quantify the NEP of terrestrial ecosystems in China and identify the influencing factors that caused these changes.

The role of climate, vegetation, and soil factors on carbon fluxes in Chinese drylands

Drylands dominate the trend and variability of the land carbon (C) sink. A better understanding of the implications of climate-induced changes in the drylands for C sink-source dynamics is urgently needed. The effect of climate on ecosystem C fluxes (gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem productivity (NEP)) in drylands has been extensively explored, but the roles of other concurrently changing factors, such as vegetation conditions and nutrient availability, remain unclear. We used eddy-covariance C-flux measurements from 45 ecosystems with concurrent information on climate (mean annual temperature (MAT) and mean annual precipitation (MAP)), soil (soil moisture (SM) and soil total nitrogen content (soil N)), and vegetation (leaf area index (LAI) and leaf nitrogen content (LNC)) factors to assess their roles in C fluxes. The results showed that the drylands in China were weak C sinks. GPP and ER were positively correlated with MAP, while they were negatively correlated with MAT. NEP first decreased and then increased with increasing MAT and MAP, and 6.6 °C and 207 mm were the boundaries for the NEP response to MAT and MAP, respectively. SM, soil N, LAI, and MAP were the main factors affecting GPP and ER. However, SM and LNC had the most important influence on NEP. Compared with climate and vegetation factors, soil factors (SM and soil N) had a greater impact on C fluxes in the drylands. Climate factors mainly affected C fluxes by regulating vegetation and soil factors. To accurately estimate the global C balance and predict the response of ecosystems to environmental change, it is necessary to fully consider the discrepant effects of climate, vegetation, and soil factors on C fluxes, as well as the cascade relationships between different factors.

Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems

Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO₂) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO₂ increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.

Temporal heterogeneity in photosystem II photochemistry in Artemisia ordosica under a fluctuating desert environment

Acclimation strategies in xerophytic plants to stressed environmental conditions vary with temporal scales. Our understanding of environmentally-induced variation in photosystem II (PSII) processes as a function of temporal scales is limited, as most studies have thus far been based on short-term, laboratory-controlled experiments. In a study of PSII processes, we acquired near-continuous, field-based measurements of PSII-energy partitioning in a dominant desert-shrub species, namely Artemisia ordosica, over a six-year period from 2012-2017. Continuous-wavelet transformation (CWT) and wavelet coherence analyses (WTC) were employed to examine the role of environmental variables in controlling the variation in the three main PSII-energy allocation pathways, i.e., photochemical efficiency and regulated and non-regulated thermal dissipation, i.e., Φ _PSII, Φ _NPQ, and Φ _NO, respectively, across a time-frequency domain from hours to years. Convergent cross mapping (CCM) was subsequently used to isolate cause-and-effect interactions in PSII-energy partitioning response. The CWT method revealed that the three PSII-energy allocation pathways all had distinct daily periodicities, oscillating abruptly at intermediate timescales from days to weeks. On a diurnal scale, WTC revealed that all three pathways were influenced by photosynthetically active radiation (PAR), air temperature (T _a), and vapor pressure deficit (VPD). By comparing associated time lags for the three forms of energy partitioning at diurnal scales, revealed that the sensitivity of response was more acutely influenced by PAR, declining thereafter with the other environmental variables, such that the order of influence was greatest for T _a, followed by VPD, and then soil water content (SWC). PSII-energy partitioning on a seasonal scale, in contrast, displayed greater variability among the different environmental variables, e.g., Φ _PSII and Φ _NO being more predisposed to changes in T _a, and Φ _NPQ to changes in VPD. CCM confirmed the causal relationship between pairings of PSII-energy allocation pathways, according to shrub phenology. A. ordosica is shown to have an innate ability to (i) repair damaged PSII-photochemical apparatus (maximum quantum yield of PSII photochemistry, with F _v/F _m > 0.78), and (ii) acclimatize to excessive PAR, dry-air conditions, and prolonged drought. A. ordosica is relatively sensitive to extreme temperature and exhibits photoinhibition.

Exceptional heat and atmospheric dryness amplified losses of primary production during the 2020 U.S. Southwest hot drought

Earth's ecosystems are increasingly threatened by "hot drought," which occurs when hot air temperatures coincide with precipitation deficits, intensifying the hydrological, physiological, and ecological effects of drought by enhancing evaporative losses of soil moisture (SM) and increasing plant stress due to higher vapor pressure deficit (VPD). Drought-induced reductions in gross primary production (GPP) exert a major influence on the terrestrial carbon sink, but the extent to which hotter and atmospherically drier conditions will amplify the effects of precipitation deficits on Earth's carbon cycle remains largely unknown. During summer and autumn 2020, the U.S. Southwest experienced one of the most intense hot droughts on record, with record-low precipitation and record-high air temperature and VPD across the region. Here, we use this natural experiment to evaluate the effects of hot drought on GPP and further decompose those negative GPP anomalies into their constituent meteorological and hydrological drivers. We found a 122 Tg C (>25%) reduction in GPP below the 2015-2019 mean, by far the lowest regional GPP over the Soil Moisture Active Passive satellite record. Roughly half of the estimated GPP loss was attributable to low SM (likely a combination of record-low precipitation and warming-enhanced evaporative depletion), but record-breaking VPD amplified the reduction of GPP, contributing roughly 40% of the GPP anomaly. Both air temperature and VPD are very likely to continue increasing over the next century, likely leading to more frequent and intense hot droughts and substantially enhancing drought-induced GPP reductions.

Assessing the Impact of Extreme Droughts on Dryland Vegetation by Multi-Satellite Solar-Induced Chlorophyll Fluorescence

Satellite-estimated solar-induced chlorophyll fluorescence (SIF) is proven to be an effective indicator for dynamic drought monitoring, while the capability of SIF to assess the variability of dryland vegetation under water and heat stress remains challenging. This study presents an analysis of the responses of dryland vegetation to the worst extreme drought over the past two decades in Australia, using multi-source spaceborne SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) and TROPOspheric Monitoring Instrument (TROPOMI). Vegetation functioning was substantially constrained by this extreme event, especially in the interior of Australia, in which there was hardly seasonal growth detected by neither satellite-based observations nor tower-based flux measurements. At a 16-day interval, both SIF and enhanced vegetation index (EVI) can timely capture the reduction at the onset of drought over dryland ecosystems. The results demonstrate that satellite-observed SIF has the potential for characterizing and monitoring the spatiotemporal dynamics of drought over water-limited ecosystems, despite coarse spatial resolution coupled with high-retrieval noise as compared with EVI. Furthermore, our study highlights that SIF retrieved from TROPOMI featuring substantially enhanced spatiotemporal resolution has the promising capability for accurately tracking the drought-induced variation of heterogeneous dryland vegetation.

A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems

It is well documented that energy balance and other remote sensing-based evapotranspiration (ET) models face greater uncertainty over water-limited tree-grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass-dominated understory and tree-dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy-limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal-based three-source energy balance (3SEB) model, accommodating an additional vegetation source within the well-known two-source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy-covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m² ; MSG: LE RMSD ~90 W/m² ), improving over both TSEB and seasonally changing TSEB (TSEB-2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.

Vegetation-type conversion of evergreen chaparral shrublands to savannahs dominated by exotic annual herbs: causes and consequences for ecosystem function

Woody, evergreen shrublands are the archetypal community in mediterranean-type ecosystems, and these communities are profoundly changed when they undergo vegetation-type conversion (VTC) to become annual, herb-dominated communities. Recently, VTC has occurred throughout southern California chaparral shrublands, likely with changes in important ecosystem functions. The mechanisms that lead to VTC and subsequent changes to ecosystem processes are important to understand as they have regional and global implications for ecosystem services, climate change, land management, and policy. The main drivers of VTC are altered fire regimes, aridity, and anthropogenic disturbance. Some changes to ecosystem function are certain to occur with VTC, but their magnitudes are unclear, whereas other changes are unpredictable. I present two hypotheses: (1) VTC leads to warming that creates a positive feedback promoting additional VTC, and (2) altered nitrogen dynamics create negative feedbacks and promote an alternative stable state in which communities are dominated by herbs. The patterns described for California are mostly relevant to the other mediterranean-type shrublands of the globe, which are biodiversity hotspots and threatened by VTC. This review examines the extent and causes of VTC, ecosystem effects, and future research priorities.

A bibliometric analysis of carbon exchange in global drylands

Drylands refer to regions with an aridity index lower than 0.65, and billions of people depend on services provided by the critically important ecosystems in these areas. How ecosystem carbon exchange in global drylands (CED) occurs and how climate change affects CED are critical to the global carbon cycle. Here, we performed a comprehensive bibliometric study on the fields of annual publications, marked journals, marked institutions, marked countries, popular keywords, and their temporal evolution to understand the temporal trends of CED research over the past 30 a (1991-2020). We found that the annual scientific publications on CED research increased significantly at an average growth rate of 7.93%. Agricultural Water Management ranked first among all journals and had the most citations. The ten most productive institutions were centered on drylands in America, China, and Australia that had the largest number and most citations of publications on CED research. "Climate change" and climate-related (such as "drought", "precipitation", "temperature", and "rainfall") research were found to be the most popular study areas. Keywords were classified into five clusters, indicating the five main research focuses on CED studies: hydrological cycle, effects of climate change, carbon and water balance, productivity, and carbon-nitrogen-phosphorous coupling cycles. The temporal evolution of keywords further showed that the areas of focus on CED studies were transformed from classical pedology and agricultural research to applied ecology and then to global change ecological research over the past 30 a. In future CED studies, basic themes (such as "water", "yield", and "salinity") and motor themes (such as "climate change", "sustainability", and "remote sensing") will be the focus of research on CED. In particular, multiple integrated methods to understand climate change and ecosystem sustainability are potential new research trends and hotspots.

Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands

Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this 'temporal sensitivity' varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure. We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA. Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts. The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.

Drought and heat wave impacts on grassland carbon cycling across hierarchical levels

Droughts and heat waves are increasing in magnitude and frequency, altering the carbon cycle. However, understanding of the underlying response mechanisms remains poor, especially for the combination (hot drought). We conducted a 4-year field experiment to examine both individual and interactive effects of drought and heat wave on carbon cycling of a semiarid grassland across individual, functional group, community and ecosystem levels. Drought did not change below-ground biomass (BGB) or above-ground biomass (AGB) due to compensation effects between grass and non-grass functional groups. However, consistently decreased BGB under heat waves limited such compensation effects, resulting in reduced AGB. Ecosystem CO₂ fluxes were suppressed by droughts, attributed to stomatal closure-induced reductions in leaf photosynthesis and decreased AGB of grasses, while CO₂ fluxes were little affected by heat waves. Overall the hot drought produced the lowest leaf photosynthesis, AGB and ecosystem CO₂ fluxes although the interactions between heat wave and drought were usually not significant. Our results highlight that the functional group compensatory effects that maintain community-level AGB rely on feedback of root system responses, and that plant adjustments at the individual level, together with shifts in composition at the functional group level, co-regulate ecosystem carbon sink strength under climate extremes.

An Assessment of the Hydrological Trends Using Synergistic Approaches of Remote Sensing and Model Evaluations over Global Arid and Semi-Arid Regions

Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of remotely sensed and physical process-based numerical modeling (e.g., Global Land Data Assimilation System (GLDAS) and Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) models) data. Interaction between hydrological and ecological indicators including precipitation, evapotranspiration, surface soil moisture and vegetation indices are presented in the global four types of arid and semi-arid areas. The trends followed by precipitation, evapotranspiration and surface soil moisture over the decade are also mapped using harmonic analysis. This study also shows that some hotspots in these global drylands, which exhibit different processes of land cover change, demonstrate strong coherency with noted groundwater variations. Various types of statistical measures are computed using the satellite and model derived values over global arid and semi-arid regions. Comparisons between satellite- (NASA-USDA Surface Soil Moisture and MODIS Evapotranspiration data) and model (FLDAS and GLDAS)-derived values over arid regions (BSh, BSk, BWh and BWk) have shown the over and underestimation with low accuracy. Moreover, general consistency is apparent in most of the regions between GLDAS and FLDAS model, while a strong discrepancy is also observed in some regions, especially appearing in the Nile Basin downstream hyper-arid region. Data-driven modelling approaches are thus used to enhance the models’ performance in this region, which shows improved results in multiple statistical measures ((RMSE), bias (ψ), the mean absolute percentage difference (|ψ|)) and the linear regression coefficients (i.e., slope, intercept, and coefficient of determination (R2)).

Montane forest productivity across a semiarid climatic gradient

High-elevation montane forests are disproportionately important to carbon sequestration in semiarid climates where low elevations are dry and characterized by low carbon density ecosystems. However, these ecosystems are increasingly threatened by climate change with seasonal implications for photosynthesis and forest growth. As a result, we leveraged eddy covariance data from six evergreen conifer forest sites in the semiarid western United States to extrapolate the status of carbon sequestration within a framework of projected warming and drying. At colder locations, the seasonal evolution of gross primary productivity (GPP) was characterized by a single broad maximum during the summer that corresponded to snow melt-derived moisture and a transition from winter dormancy to spring activity. Conversely, winter dormancy was transient at warmer locations, and GPP was responsive to both winter and summer precipitation such that two distinct GPP maxima were separated by a period of foresummer drought. This resulted in a predictable sequence of primary limiting factors to GPP beginning with air temperature in winter and proceeding to moisture and leaf area during the summer. Due to counteracting winter (positive) and summer (negative) GPP responses to warming, leaf area index and moisture availability were the best predictors of annual GPP differences across sites. Overall, mean annual GPP was greatest at the warmest site due to persistent vegetation photosynthetic activity throughout the winter. These results indicate that the trajectory of this region's carbon sequestration will be sensitive to reduced or delayed summer precipitation, especially if coupled to snow drought and earlier soil moisture recession, but summer precipitation changes remain highly uncertain. Given the demonstrated potential for seasonally offsetting responses to warming, we project that decadal semiarid montane forest carbon sequestration will remain relatively stable in the absence of severe disturbance.

Topography influences species-specific patterns of seasonal primary productivity in a semiarid montane forest

Semiarid forests in the southwestern USA are generally restricted to mountain regions where complex terrain adds to the challenge of characterizing stand productivity. Among the heterogeneous features of these ecosystems, topography represents an important control on system-level processes including snow accumulation and melt. This basic relationship between geology and hydrology affects radiation and water balances within the forests, with implications for canopy structure and function across a range of spatial scales. In this study, we quantify the effect of topographic aspect on primary productivity by observing the response of two codominant native tree species to seasonal changes in the timing and magnitude of energy and water inputs throughout a montane headwater catchment in Arizona, USA. On average, soil moisture on north-facing aspects remained higher during the spring and early summer compared with south-facing aspects. Repeated measurements of net carbon assimilation (Anet) showed that Pinus ponderosa C. Lawson was sensitive to this difference, while Pseudotsuga menziesii (Mirb.) Franco was not. Irrespective of aspect, we observed seasonally divergent patterns at the species level where P. ponderosa maintained significantly greater Anet into the fall despite more efficient water use by P. menziesii individuals during that time. As a result, this study at the southern extent of the geographical P. menziesii distribution suggests that this species could increase water-use efficiency as a response to future warming and/or drying, but at lower rates of production relative to the more drought-adapted P. ponderosa. At the sub-landscape scale, opposing aspects served as a mesocosm of current versus anticipated climate conditions. In this way, these results also constrain the potential for changing carbon sequestration patterns from Pinus-dominated landscapes due to forecasted changes in seasonal moisture availability.

Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China

As an important component to quantify the carbon budget, accurate evaluation of terrestrial gross primary production (GPP) is crucial for large-scale applications, especially in dryland ecosystems. Based on the in situ data from six flux sites in northwestern China from 2014 to 2016, this study compares seasonal and interannual dynamics of carbon fluxes between these arid and semi-arid ecosystems and the atmosphere. Meanwhile, the reliability of multiple remotely-derived GPP products in representative drylands was examined, including the Breathing Earth System Simulator (BESS), the Moderate Resolution Imaging Spectroradiometer (MODIS) and data derived from the OCO-2 solar-induced chlorophyll fluorescence (GOSIF). The results indicated that the carbon fluxes had clear seasonal patterns, with all ecosystems functioning as carbon sinks. The maize cropland had the highest GPP with 1183 g C m−2 y−1. Although the net ecosystem carbon exchange (NEE) in the Tamarix spp. ecosystem was the smallest among these flux sites, it reached 208 g C m−2 y−1. Furthermore, distinct advantages of GOSIF GPP (with R2 = 0.85–0.98, and RMSE = 0.87–2.66 g C m−2 d−1) were found with good performance. However, large underestimations in three GPP products existed during the growing seasons, except in grassland ecosystems. The main reasons can be ascribed to the uncertainties in the key model parameters, including the underestimated light use efficiency of the MODIS GPP, the same coarse land cover product for the BESS and MODIS GPP, the coarse gridded meteorological data, and distribution of C3 and C4 plants. Therefore, it still requires more work to accurately quantify the GPP across these dryland ecosystems.

A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands

Geo-spatial technologies (i.e., remote sensing (RS) and Geographic Information Systems (GIS)) offer the means to enable a rapid assessment of terrestrial carbon stock (CS) over large areas. The utilization of an integrated RS-GIS approach for above ground biomass (AGB) estimation and precision carbon management is a timely and cost-effective solution for implementing appropriate management strategies at a localized and regional scale. The current study reviews various RS-related techniques used in the CS assessment, with emphasis on arid lands, and provides insight into the associated challenges, opportunities and future trends. The study examines the traditional methods and highlights their limitations. It explores recent and developing techniques, and identifies the most significant RS variables in depicting biophysical predictors. It further demonstrates the usefulness of geo-spatial technologies for assessing terrestrial CS, especially in arid lands. RS of vegetation in these ecosystems is constrained by unique challenges specific to their environmental conditions, leading to high inaccuracies when applying biomass estimation techniques developed for other ecosystems. This study reviews and highlights advantages and limitations of the various techniques and sensors, including optical, RADAR and LiDAR, that have been extensively used to estimate AGB and assess CS with RS data. Other new methods are introduced and discussed as well. Finally, the study highpoints the need for further work to fill the gaps and overcome limitations in using these emerging techniques for precision carbon management. Geo-spatial technologies are shown to be a valuable tool for estimating carbon sequestered especially in difficult and remote areas such as arid land.

Plant Traits Help Explain the Tight Relationship between Vegetation Indices and Gross Primary Production

Remotely-sensed Vegetation Indices (VIs) are often tightly correlated with terrestrial ecosystem CO2 uptake (Gross Primary Production or GPP). These correlations have been exploited to infer GPP at local to global scales and over half-hour to decadal periods, though the underlying mechanisms remain incompletely understood. We used satellite remote sensing and eddy covariance observations at 10 sites across a California climate gradient to explore the relationships between GPP, the Enhanced Vegetation Index (EVI), the Normalized Difference Vegetation Index (NDVI), and the Near InfraRed Vegetation (NIRv) index. EVI and NIRv were linearly correlated with GPP across both space and time, whereas the relationship between NDVI and GPP was less general. We explored these interactions using radiative transfer and GPP models forced with in-situ plant trait and soil reflectance observations. GPP ultimately reflects the product of Leaf Area Index (LAI) and leaf level CO2 uptake (Aleaf); a VI that is sensitive mainly to LAI will lack generality across ecosystems that differ in Aleaf. EVI and NIRv showed a strong, multiplicative sensitivity to LAI and Leaf Mass per Area (LMA). LMA was correlated with Aleaf, and EVI and NIRv consequently mimic GPP’s multiplicative sensitivity to LAI and Aleaf, as mediated by LMA. NDVI was most sensitive to LAI, and was relatively insensitive to leaf properties over realistic conditions; NDVI lacked EVI and NIRv’s sensitivity to both LAI and Aleaf. These findings carry implications for understanding the limitations of current VIs for predicting GPP, and also for devising strategies to improve predictions of GPP.

Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records

The rate of change in atmospheric CO₂ is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001-2016) in a 55 year old 30 km² pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover ~18% of the global land area. The forest accumulated 145-160 g C m^-2  year^-1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m^-2  year^-1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m² and 372 g N/m² . Carbon accumulated mostly in the soil (~71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester ~0.4 Pg C/year over several decades.

Allometric Relationships for Predicting Aboveground Biomass and Sapwood Area of Oneseed Juniper (Juniperus monosperma) Trees

Across the semiarid ecosystems of the southwestern USA, there has been widespread encroachment of woody shrubs and trees including Juniperus species into former grasslands. Quantifying vegetation biomass in such ecosystems is important because semiarid ecosystems are thought to play an important role in the global land carbon (C) sink, and changes in plant biomass also have implications for primary consumers and potential bioenergy feedstock. Oneseed juniper (Juniperus monosperma) is common in desert grasslands and pinyon-juniper rangelands across the intermountain region of southwestern North America; however, there is limited information about the aboveground biomass (AGB) and sapwood area (SWA) for this species, causing uncertainties in estimates of C stock and transpiration fluxes. In this study, we report on canopy area (CA), stem diameter, maximum height, and biomass measurements from J. monosperma trees sampled from central New Mexico. Dry biomass ranged between 0.4 kg and 625 kg, and cross-sectional SWA was measured on n = 200 stems using image analysis. We found a strong linear relationship between CA and AGB (r² = 0.96), with a similar slope to that observed in other juniper species, suggesting that this readily measured attribute is well suited for upscaling studies. There was a 9% bias between different approaches to measuring CA, indicating care should be taken to account for these differences to avoid systematic biases. We found equivalent stem diameter (ESD) was a strong predictor of biomass, but that existing allometric models underpredicted biomass in larger trees. We found SWA could be predicted from individual stem diameter with a power relationship, and that tree-level SWA should be estimated by summing the SWA predictions from individual stems rather than ESD. Our improved allometric models for J. monosperma support more accurate and robust measurements of C storage and transpiration fluxes in Juniperus-dominated ecosystems.

Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability

Dryland regions cover >40% of the Earth's land surface, making these ecosystems the largest biome in the world. Ecosystems in these areas play an important role in determining the interannual variability of the global terrestrial carbon sink. Examining carbon fluxes of various types of dryland ecosystems and their responses to climatic variability is essential for improving projections of the carbon cycle in these regions. In this study, we made use of observations from a regional flux tower observation network in a typical arid endorheic basin, the Heihe river basin (HRB). As a representative area of both the arid region of China and the entire region of central Asia, the HRB includes the main ecosystems in arid regions. We compared the spatial variations of carbon fluxes of five terrestrial ecosystems (i.e., grassland, cropland, desert, wetland, and forest ecosystems) and explored the responses of ecosystem carbon fluxes to climatic factors across different ecosystems. We found that our region exhibits a carbon sink ranging from 85.9 to 508.7 gC/m²/yr for different ecosystems, and the water availability is critical to the spatial variability of carbon fluxes in arid regions. Carbon fluxes across all sites exhibited weak correlations with temperature and precipitation. Marked differences in precipitation effects were observed between the sites within oases and those outside of oases. Irrigation and groundwater recharge were of great importance to the variations in carbon fluxes for the sites within oases. Evapotranspiration (ET) exhibited strong relationships with carbon fluxes, indicating that ET was a better metric of soil water availability than was precipitation in driving the spatial variability of carbon fluxes in arid regions. This study has implications for better understanding the carbon budget of terrestrial ecosystems and informing ecological management in dryland regions.

Ecological responses to heavy rainfall depend on seasonal timing and multi-year recurrence

Heavy rainfall events are expected to increase in frequency and severity in the future. However, their effects on natural ecosystems are largely unknown, in particular with different seasonal timing of the events and recurrence over multiple years. We conducted a 4 yr manipulative experiment to explore grassland response to heavy rainfall imposed in either the middle of, or late in, the growing season in Inner Mongolia, China. We measured hierarchical responses at individual, community and ecosystem levels. Surprisingly, above-ground biomass remained stable in the face of heavy rainfall, regardless of seasonal timing, whereas heavy rainfall late in the growing season had consistent negative impacts on below-ground and total biomass. However, such negative biomass effects were not significant for heavy rainfall in the middle of the growing season. By contrast, heavy rainfall in the middle of the growing season had greater positive effects on ecosystem CO₂ exchanges, mainly reflected in the latter 2 yr of the 4 yr experiment. This two-stage response of CO₂ fluxes was regulated by increased community-level leaf area and leaf-level photosynthesis and interannual variability of natural precipitation. Overall, our study demonstrates that ecosystem impacts of heavy rainfall events crucially depend on the seasonal timing and multiannual recurrence. Plant physiological and morphological adjustment appeared to improve the capacity of the ecosystem to respond positively to heavy rainfall.

Seasonal and interannual variations in carbon fluxes in East Asia semi-arid grasslands

Semiarid regions have substantial interannual variation in carbon exchange between terrestrial ecosystem and atmosphere but the diverse responses of carbon fluxes to climate variability are poorly known. We compared carbon exchange processes and the responses to environmental factors in a meadow steppe at Tongyu (TY) and a typical steppe at Maodeng (MD) using long-term continuous eddy covariance measurements. TY precipitation was 25% greater than MD. Both grasslands had interannual fluctuations of carbon sink and source and acted as weak carbon sinks averagely (-22.9 ± 41.0 gCm^-2 yr^-1 for TY and - 11.8 ± 45.0 gCm^-2 yr^-1 for MD). The seasonal dynamics of carbon fluxes were significantly related to water availability at MD but more strongly related to air temperature at TY. During dry years, the controlling effect of water availability on carbon fluxes increased. Summer precipitation and soil moisture played key roles in the interannual variations in carbon fluxes in both grasslands. At MD, net carbon uptake was negatively related to summer air temperature likely because warming induced water deficit decreased photosynthesis. Greenness index derived from PhenoCam images captured key phenological phases and diverse magnitude of canopy dynamics. The index was correlated with seasonal and annual variations in carbon fluxes at both grasslands, suggesting the potential of PhenoCam for monitoring the spatial and temporal variations in canopy dynamics in different semiarid grasslands.

Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach

Accurate and continuous monitoring of the production of arid ecosystems is of great importance for global and regional carbon cycle estimation. However, the magnitude of carbon sequestration in arid regions and its contribution to the global carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in arid ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product provides worldwide high-frequency monitoring of terrestrial GPP. While there have been a large number of studies to validate the MODIS GPP product with ground-based measurements over a range of biome types. Few studies have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems, especially for the newly released Collection 6 GPP products, whose resolution have been improved from 1000 m to 500 m. Thus, this study examined the performance of MODIS-derived GPP by compared with eddy covariance (EC)-observed GPP at different timescales for the main ecosystems in arid and semi-arid regions of China. Meanwhile, we also improved the estimation of MODIS GPP by using in situ meteorological forcing data and optimization of biome-specific parameters with the Bayesian approach. Our results revealed that the current MOD17A2H GPP algorithm could, on the whole, capture the broad trends of GPP at eight-day time scales for the most investigated sites. However, GPP was underestimated in some ecosystems in the arid region, especially for the irrigated cropland and forest ecosystems (with R2 = 0.80, RMSE = 2.66 gC/m2/day and R2 = 0.53, RMSE = 2.12 gC/m2/day, respectively). At the eight-day time scale, the slope of the original MOD17A2H GPP relative to the EC-based GPP was only 0.49, which showed significant underestimation compared with tower-based GPP. However, after using in situ meteorological data to optimize the biome-based parameters of MODIS GPP algorithm, the model could explain 91% of the EC-observed GPP of the sites. Our study revealed that the current MODIS GPP model works well after improving the maximum light-use efficiency (εmax or LUEmax), as well as the temperature and water-constrained parameters of the main ecosystems in the arid region. Nevertheless, there are still large uncertainties surrounding GPP modelling in dryland ecosystems, especially for desert ecosystems. Further improvements in GPP simulation in dryland ecosystems are needed in future studies, for example, improvements of remote sensing products and the GPP estimation algorithm, implementation of data-driven methods, or physiology models.

Semiarid ecosystem sensitivity to precipitation extremes: weak evidence for vegetation constraints

In semiarid regions, vegetation constraints on plant growth responses to precipitation (PPT) are hypothesized to place an upper limit on net primary productivity (NPP), leading to predictions of future shifts from currently defined linear to saturating NPP-PPT relationships as increases in both dry and wet PPT extremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing season PPT (GSP, n = 11 levels, n = 4 replicates), ranging from the driest to wettest conditions in the 75-yr climate record, within a semiarid grassland. We focused on responses of two key ecosystem processes: aboveground NPP (ANPP) and soil respiration (R_s ). ANPP and R_s both exhibited greater relative responses to wet vs. dry GSP extremes, with a linear relationship consistently best explaining the response of both processes to GSP. However, this responsiveness to GSP peaked at moderate levels of extremity for both processes, and declined at the most extreme GSP levels, suggesting that greater sensitivity of ANPP and R_s to wet vs. dry conditions may diminish under increased magnitudes of GSP extremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover as GSP transitioned to extreme wet conditions. This compositional shift increased the magnitude of ANPP responses to wet GSP extremes, as well as the slope and variability explained in the ANPP-GSP relationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes in GSP extremes.

Dynamic responses of tree-ring growth to multiple dimensions of drought

Droughts, which are characterized by multiple dimensions including frequency, duration, severity, and onset timing, can impact tree stem radial growth profoundly. Different dimensions of drought influence tree stem radial growth independently or jointly, which makes the development of accurate predictions a formidable challenge. Measurement-based tree-ring data have obvious advantages for studying the drought responses of trees. Here, we explored the use of abundant tree-ring records for quantifying regional response patterns to key dimensions of drought. Specifically, we designed a series of regional-scaled "natural experiments," based on 357 tree-ring chronologies from Southwest USA and location-matched monthly water balance anomalies, to reveal how tree-ring responds to each dimension of drought. Our results showed that tree-ring was affected significantly more by the water balance condition in the current hydrological year than that in the prior hydrological year. Within the current hydrological year, increased drought frequency (number of dry months) and duration (maximum number of consecutive dry months) resulted in "cumulative effects" which amplified the impacts of drought on trees and reduced the drought resistance of trees. Drought events that occurred in the pregrowing seasons strongly affected subsequent tree stem radial growth. Both the onset timing and severity of drought increased "legacy effects" on tree stem radial growth, which reduced the drought resilience of trees. These results indicated that the drought impact on trees is a dynamic process: even when the total water deficits are the same, differences among the drought processes could lead to considerably different responses from trees. This study thus provides a conceptual framework and probabilistic patterns of tree-ring growth response to multiple dimensions of drought regimes, which in turn may have a wide range of implications for predictions, uncertainty assessment, and forest management.

Quantifying soil moisture impacts on light use efficiency across biomes

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.