Reduction In Gross Primary Productivity Research Articles

Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data

BackgroundDeciduous forests in eastern North America experienced a widespread and intense spongy moth (Lymantria dispar) infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon (C) cycle in forests across the Great Lakes region in Canada, utilizing high-resolution (10 × 10 m2) Sentinel-2 satellite remote sensing images and eddy covariance (EC) flux data. Study results showed a significant reduction in leaf area index (LAI) and gross primary productivity (GPP) values in deciduous and mixed forests in the region in 2021.ResultsRemote sensing derived, growing season mean LAI values of deciduous (mixed) forests were 3.66 (3.18), 2.74 (2.64), and 3.53 (2.94) m2 m−2 in 2020, 2021 and 2022, respectively, indicating about 24 (14)% reduction in LAI, as compared to pre- and post-infestation years. Similarly, growing season GPP values in deciduous (mixed) forests were 1338 (1208), 868 (932), and 1367 (1175) g C m−2, respectively in 2020, 2021 and 2022, showing about 35 (22)% reduction in GPP in 2021 as compared to pre- and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area (178,000 km2), resulted in 21.1 (21.4) Mt of C loss as compared to 2020 (2022), respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes region.ConclusionsThe methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions.

Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes

Abstract. The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic and stomatal) responses to varying meteorological conditions and concentrations of CO2 and ground-level ozone (O3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere–atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2>0.85 and R2>0.8, respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr−1. Application of Monin–Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting an increase of +7 % in global GPP. Present-day O3 concentrations simulated by GEOS-Chem and an O3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions of up to 15 % in eastern China and the eastern USA. Regional correlations are generally unchanged when O3 is present and biases are reduced, especially for regions with high O3 damage. An increase in atmospheric CO2 concentration of 20 ppmv from the level in 2000 to the level in 2010 modestly decreases O3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions.

Divergent responses of subtropical evergreen and deciduous forest carbon cycles to the summer 2022 drought

Ongoing shifts in climate, especially extreme drought, is posing considerable threats to the forest carbon uptake worldwide. In China, summer 2022 was the warmest and driest since the beginning of meteorological measurements. This study synthesized the tower-based carbon fluxes and climate data from two subtropical evergreen and deciduous forest ecosystems to investigate the effects of such summer drought. Interestingly, the net ecosystem production (NEP = −NEE) only exhibited a slight decrease at the deciduous forest while it even enhanced at the evergreen forest during the summer 2022 drought. Further analysis revealed that although reductions in gross primary productivity (GPP) and ecosystem respiration (R e) were found at both sites, larger decrease in R e than GPP at the evergreen forest led to stronger NEP compared to the previous year. However, the NEP of two forest ecosystems sharply reduced in the following 2023, which can be ascribed to the legacy effects of the summer 2022 drought. The results of multiple linear regression revealed that soil water content (SWC) was recognized as the primary driver of GPP and R e, and downwelling shortwave radiation (R g) regulated the variability of NEP during the summer 2022. Across these forest carbon fluxes including GPP, R e and NEP, the deciduous forest exhibited larger resistance, whereas the evergreen forest showed stronger resilience. All analyses emphasized the diverse adaptive strategies among vegetation types, which acted an important role in assessing ecosystem carbon sequestration in face of future climate change.

Widespread reduction in gross primary productivity caused by the compound heat and drought in Yangtze River Basin in 2022

Abstract Terrestrial ecosystems play a pivotal role in the global carbon sequestration process, and their photosynthetic capacity is highly susceptible to fluctuations in climate conditions. In 2022, the Yangtze River Basin (YRB) in China experienced an extensive and severe compounded heat and drought event. Compared with the past two decades, our results revealed that the temperature increased by approximately 0.78 ± 0.45 °C and precipitation decreased by about 45.20 ± 30.10 mm from July to October 2022 over the whole YRB. Region I (west from the Sichuan Basin and east to the easternmost of the basin) experienced a more severe temperature increase (0.98 ± 0.35 °C) and precipitation decrease (−60.27 ± 23.75 mm) compared to the other regions in the YRB. Changes in temperature and precipitation resulted in an increase of 0.14 ± 0.06 kPa in vapor pressure deficit (VPD) and a decrease of 5.28 ± 2.09 m3 m−3 in soil moisture, ultimately leading to a total loss of 26.12 ± 16.09 Tg C (about −6.08% compared to the 2001–2021 mean) in gross primary productivity (GPP) of July to October in 2022. It is noteworthy that broadleaf forests, which comprise 12.03% of the natural vegetation in region I, contributed only 6.46% of the GPP loss between July and October compared to other vegetation types, showing greater resistance to this climate event. Our findings from multiple linear regressions highlight that high temperatures and reduced soil moisture together contribute up to 94% photosynthesis loss in July–October in natural vegetation in region I, while the contribution of reduced VPD is minimal. In the future, we will further explore the impacts of compound heat and drought events on the coupled carbon and water cycles across different ecosystems, in order to better understand the ecosystem response mechanisms to extreme climates.

Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins

Terrestrial gross primary production (GPP) changes due to impervious surfaces significantly impact ecosystem services in watersheds. Understanding the asymmetric response of vegetation GPP to impervious surface expansion is essential for regional development planning and ecosystem management. However, the asymmetric response of vegetation GPP to the impacts of impervious surface expansion is unknown in different watersheds. This paper selected the Yellow River and Yangtze River basins as case studies. We characterized the overall change in GPP based on changes in impervious surface ratio (ISR), determined impervious surface expansion's direct and indirect impacts on GPP in the two watersheds, and further analyzed the asymmetric response of the compensatory effects of indirect influences on the impervious surface expansion in different watersheds. The results showed that: (1) The vegetation GPP decreased with increasing ISR in the Yangtze River Basin, while that in the Yellow River Basin first increased and then reduced. (2) The direct impacts of increased ISR reduced vegetation GPP, while the indirect impacts both had a growth-compensating effect. Growth compensation stabilized at approximately 0.40 and 0.30 in the Yellow and Yangtze River Basins. (3) When the ISR was 0.34–0.56, the growth compensation could offset the reduction of GPP due to direct impact and ensure that the background vegetation GPP was not damaged in the Yellow River Basin. In contrast, the background vegetation GPP was inevitably impaired with increased ISR in the Yangtze River Basin. Therefore, this study suggests that the ISR should be ensured to be between 0.34 and 0.56 to maximize the impervious surface of the Yellow River Basin without compromising the background vegetation GPP. While pursuing impervious surface expansion in the Yangtze River Basin, other programs should be sought to compensate for the loss to GPP.

Coordination of rooting, xylem, and stomatal strategies explains the response of conifer forest stands to multi-year drought in the southern Sierra Nevada of California

Abstract. Extreme droughts are a major determinant of ecosystem disturbance that impacts plant communities and feeds back into climate change through changes in plant functioning. However, the complex relationships between aboveground and belowground plant hydraulic traits and their role in governing plant responses to drought are not fully understood. In this study, we use a model, the Functionally Assembled Terrestrial Ecosystem Simulator in a configuration that includes plant hydraulics (FATES-Hydro), to investigate ecosystem responses to the 2012–2015 California drought in comparison with observations at a site in the southern Sierra Nevada that experienced widespread tree mortality during this drought. We conduct a sensitivity analysis to explore how different plant water sourcing and hydraulic strategies lead to differential responses during normal and drought conditions. The analysis shows the following. Deep roots that sustain productivity through the dry season are needed for the model to capture observed seasonal cycles of evapotranspiration (ET) and gross primary productivity (GPP) in normal years, and deep-rooted strategies are nonetheless subject to large reductions in ET and GPP when the deep soil reservoir is depleted during extreme droughts, in agreement with observations. Risky stomatal strategies lead to greater productivity during normal years as compared to safer stomatal control, but they also lead to a high risk of xylem embolism during the 2012–2015 drought. For a given stand density, stomatal and xylem traits have a stronger impact on plant water status than on ecosystem-level fluxes. Our study highlights the significance of resolving plant water sourcing strategies to represent drought impacts on plants and consequent feedbacks in models.

Non-stomatal processes are responsible for the decrease in gross primary production of a potato crop during edaphic drought

Soil water stress is one of the main constraints on agrosystem functioning, causing a reduction in gross primary production (GPP). It is a key factor for the selection of drought-tolerant plant varieties and the adaptation of irrigation management strategies. Therefore, identifying the physiological factors limiting GPP is crucial. Land surface models commonly implement a beta (β) stress function to reproduce the effects of drought on GPP. It is still unclear whether GPP limitations originate from a direct stomatal response (SOL) or from other non-stomatal causes (NSOL). Moreover, the shape and thresholds of the β function are a major cause of uncertainty in LSMs. This study investigated the effects of edaphic drought on GPP limitations of a potato crop by using eddy covariance data from the Lonzée ICOS station (BE-Lon) in Belgium for four years (2006, 2010, 2014 and 2018) and by calibrating the β function on NSOL and SOL.The decrease in the relative extractable water in the soil (REW) induced a decline in the apparent maximum carboxylation rate (NSOL) from similar REW thresholds for all growing seasons of potato crops. A sensitivity analysis showed that the non-inclusion of REW decrease on NSOL in the modeling of GPP led to important overestimations of carbon sequestration from a threshold corresponding to 46 % of the maximum available soil water. The stomatal sensitivity to photosynthesis (SOL) remained constant or even increased in 2010 and 2018. The carbon and water fluxes were decoupled when REW decreased, exhibiting a strict control of NSOL on hourly dynamics of GPP. This study provides REW thresholds to identify drought stress episodes and to help for designing irrigation management strategies. Our results advocate for a better representation of the influence of drought on photosynthesis processes of potato crops to improve the accuracy of model predictions during drought.

Response of Grassland Vegetation Growth to Drought in Inner Mongolia of China from 2002 to 2020

Drought poses a significant environmental risk and can deeply affect the growth of grasslands. However, there is still uncertainty regarding the precise impact of varying levels of drought on grassland growth. To address this gap, we utilized several key indicators, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Global Orbiting Carbon Observatory-2-based Solar-induced Chlorophyll Fluorescence (GOSIF), and Gross Primary Productivity (GPP), in conjunction with drought indices (the Standardized Precipitation Evapotranspiration Index (SPEI) and soil moisture (SM). Our study aimed to comprehensively assess the consistency of spatiotemporal patterns in grassland vegetation and its responsiveness to different drought levels in the Inner Mongolia region from 2002 to 2020. The results indicated that NDVI, EVI, GOSIF, and GPP in grassland vegetation across Inner Mongolia exhibited significant increasing trends from 2002 to 2020. Specifically, NDVI, EVI, GOSIF, and GPP all displayed consistent spatial patterns, with 25.83%, 21.18%, 22.65%, and 48.13% of the grassland area showing significant increases, respectively. Drought events, as described through SPEI and SM, from June 2007 to September 2007 and June 2017 to July 2017 were selected to evaluate the response of grassland vegetation to drought. The drought events of 2007 and 2017 resulted in reductions in NDVI, EVI, GOSIF, and GPP relative to the multi-year average (2002–2020). GOSIF exhibited a more intense response to drought, suggesting that GOSIF may reflect the inhibition of water stress on grassland photosynthesis better than NDVI and EVI for the drought in 2007 and 2017. The reductions in NDVI, EVI, GOSIF, and GPP in grassland increased significantly across different drought levels, with the sharpest reductions observed during extreme drought. Under the severe and extreme drought events, the most substantial reductions in NDVI, EVI, GOSIF, and GPP were observed in the temperate steppe (TS). Moreover, the effects of different drought severity levels within the same grassland type varied, with the most significant reductions in NDVI, EVI, GOSIF, and GPP observed during extreme drought. Our results provide new perspectives for developing and implementing effective strategies to address grassland carbon cycling management and climate change in Inner Mongolia.

Effects of a chronic impact on Cymodocea nodosa community carbon metabolism and dissolved organic carbon fluxes

Seagrass communities have been degraded worldwide experiencing elevated shoot density reduction by anthropogenic chronic pressures. This study aims to assess how a chronic (i.e., low intensity but long-lasting) impact that promotes reduced shoot density in a temperate seagrass population may affect community components and functioning. To this end, shoot density was reduced (0, 40, and 75 %) for three months in contrasting seasons (winter and summer), and assessed its effects on biotic components (i.e., seagrasses, macroalgae, macrofauna, and microphytobenthos), as well as on community carbon metabolism, dissolved organic carbon (DOC) fluxes and sediment organic matter (OM) content. Lower shoot densities enhanced the presence of macroalgae and microphytobenthos in the community, while macrofauna remained unchanged. Net community production was significantly reduced with the simulated reduction in shoot density in both seasons (up to 10-fold lower), which shifted the community in winter from being largely autotrophic (CO2 sink) to heterotrophic (CO2 source). This was due to the expected reduction in gross primary production, but also to the unexpected increase in community respiration (up to 2.2-fold higher). Since OM in the sediment was reduced in the simulated shoot density reduction treatments, the increase in sediment bacterial activity may help explain the increase in community respiration. DOC fluxes were also greatly reduced in both seasons (up to 5.5-fold lower), which coupled with the reduced net community production and loss of OM in the sediment may have a continued silent effect on blue carbon capture and storage capacity in this chronically stressed community. This study therefore highlights the importance of chronic impacts that promote the degradation of seagrass communities that may reduce their ability to provide highly valuable ecological services, including the ability to cope with the effects of climate change.

Inner Mongolia grasslands act as a weak regional carbon sink: A new estimation based on upscaling eddy covariance observations

Clarifying temporal and spatial variations of carbon exchanges of arid and semi-arid grasslands, the most widespread terrestrial ecosystem in the Northern China, is critical to evaluate regional and national carbon balance. However, estimating the carbon sequestration capability of arid and semi-arid grasslands still remains a challenge due to large interannual variability and high sensitivity to human activities. In this study, based on 696 site-months of long-term eddy covariance observations from 7 sites, we estimated the regional carbon fluxes of the arid and semi-arid grasslands in Inner Mongolia, China with the random forest (RF) approach. The estimated carbon fluxes encompassed net ecosystem productivity (NEP), gross primary productivity (GPP) and ecosystem respiration (ER), at a spatial resolution of 0.1°×0.1°. We found that Inner Mongolia grasslands acted as a weak carbon sink with a mean NEP of 2.43 ± 6.71 Tg C y−1 from 1982 to 2018. Fluctuations of precipitation during the peak growing season and leaf area index were the most important drivers for the interannual variations of regional carbon fluxes. During the dry period of 1999 to 2011, the grasslands switched from carbon sink to source resulting from a great drought-induced reduction in GPP than ER. Comparison of our RF carbon fluxes with the global datasets (FLUXCOM, CMIP6 models, and atmospheric inversion data of JenaCO2) showed that these products had limited agreement in terms of spatial and temporal variations, particularly for interannual variabilities of carbon fluxes, which highlights the importance of local long-term observations for regional evaluation and simulation of carbon budget.

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy‐Covariance Observations

AbstractAlthough there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy‐covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi‐arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non‐linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep‐rooted plants when only using surface‐layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points.

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate-plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012-2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011-2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012-2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states-showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.

Drying, more than warming, alters ecosystem functioning in streams with different energy pathways

Abstract Empirical evidence and theory suggest that climate warming and an increase in the frequency and duration of drying events will alter the metabolic balance of freshwater ecosystems. However, the impacts of climate change on ecosystem metabolism may depend on whether energy inputs are of autochthonous or allochthonous origin. To date, few studies have examined how warming and drying may interact to alter stream metabolism, much less how their impacts may depend on the energy‐base of the food web. To address this research gap, we conducted a multi‐factorial experiment using outdoor mesocosms to investigate the individual and synergistic effects of warming and drought on metabolic processes in stream mesocosms with green (algal‐based) vs. mixed (algal‐ and detritus‐based) vs. brown (detritus‐based) energy pathways. We set up 48 mesocosms with one of three different levels of shade and leaf litter input combinations to create mesocosms with different primary energy channels. In addition, we warmed half of the mesocosms by ~2–3°C. We assessed changes in ecosystem respiration (ER), gross primary production (GPP), net ecosystem production (NEP) and organic matter biomass in warmed and ambient temperature mesocosms before a 24 day drying event and after rewetting. Surprisingly, experimental warming had little effect on metabolic processes. Drying, however, led to decreased rates of ER and GPP and led to an overall reduction in NEP. Although the effects of drying were similar across energy channel treatments, reductions in ER and GPP were primarily driven by decreases in biomass of benthic and filamentous algae. Overall, we demonstrate that drying led to lower rates of NEP in mesocosms regardless of energy inputs. While warming showed little effect in our study, our results suggest that an increase in the frequency of stream drying events could greatly alter the metabolic balance of many aquatic ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

Increased salinity decreases annual gross primary productivity at a Northern California brackish tidal marsh

Tidal marshes sequester 11.4–87.0 Tg C yr−1 globally, but climate change impacts can threaten the carbon capture potential of these ecosystems. Tidal marshes occur across a wide range of salinity, with brackish marshes (0.5–18 ppt (parts per thousand)) dominating global tidal marsh extents. A diverse mix of freshwater- and saltwater-tolerant plant and microbial communities has led researchers to predict that carbon cycling in brackish wetlands may be less sensitive to changes in salinity than fresh- or saltwater wetlands. Rush Ranch, a well-monitored brackish tidal wetland of the San Francisco Bay National Estuarine Research Reserve, experiences highly variable annual salinity regimes. Within a five-year period (2014–2018), Rush Ranch experienced particularly extreme drought-induced salinization during the 2014 and 2015 growing seasons. During drought years, tidal channel salinity rose from a 15 year baseline of 4.7 ppt to growing season peaks of 10.3 ppt and 12.5 ppt. Continuous eddy covariance data from 2014 to 2018 demonstrate that during drought summers, gross primary productivity (GPP) decreased by 24%, whereas ecosystem respiration remained similar among all five years. Stepwise linear regression revealed that salinity, not air temperature or tidal height, was the dominant driver of annual GPP. A random forest model trained to predict GPP based on environmental data from low salinity years (i.e. naive to salinization) significantly over predicted GPP in drought years. When growing season salinities were doubled, annual estimates of net ecosystem exchange of CO2 decreased by up to 30%. These results provide ecosystem-scale evidence that increased salinity influences CO2 fluxes dominantly through reductions in GPP. This relationship provides a starting point for incorporating the effect of changes in salinity in wetland carbon models, which could improve wetland carbon forecasting and management for climate resilience.

2021 February Texas Ice Storm Induced Spring GPP Reduction Compensated by the Higher Precipitation

AbstractClimate extremes are more frequent and affect the carbon cycle. On 10–20 February, an exceptional winter storm in Texas brought severe ecological and economic effects. However, its impacts on vegetation activities and the carbon cycle are unclear. This study evaluated the early 2021 ice storm effects on spring phenology and the carbon cycle. The results showed that the ice storm led to a significant later vegetation spring phenology and a reduction of 42.32 Tg C in gross primary production (GPP) and a reduction of 34. 47 Tg C net ecosystem production (NEP) in spring. In the 2021 spring, Texas became a carbon source from the carbon sink. More precipitation in late spring and summer precipitation recharged the rootzone soil moisture, which enhanced summer vegetation GPP and NEP and compensated for the effects of the ice storm on spring carbon uptake. The summer GPP enhancement offset all the spring GPP reduction, and thus GPP was increased by 4.97% during 2021. 91.47% of the spring NEP reduction was compensated by summer NEP enhancement due to higher root zone soil moisture. Due to the NEP enhancement during autumn, NEP did not decrease as well and increased by 10.88% during 2021. This observation‐based research highlights the seasonal compensation effects on the interactions between extreme climate events and the biosphere.

Regional differences in the response of California’s rangeland production to climate and future projection

Rangelands support many important ecosystem services and are highly sensitive to climate change. Understanding temporal dynamics in rangeland gross primary production (GPP) and how it may change under projected future climate, including more frequent and severe droughts, is critical for ranching communities to cope with future changes. Herein, we examined how climate regulates the interannual variability of GPP in California’s diverse annual rangeland, based on the contemporary records of satellite derived GPP at 500 m resolution since 2001. We built Gradient Boosted Regression Tree models for 23 ecoregion subsections, relating annual GPP with 30 climatic variables, to disentangle the partial dependence of GPP on each climate variable. The machine learning results showed that GPP was most sensitive to growing season (GS) precipitation, with a reduction in GPP up to 200 g cm−2 yr−1 when GS precipitation decreased from 400 to 100 mm yr−1 in one of the driest subsections. We also found that years with more evenly distributed GS precipitation had higher GPP. Warmer winter minimum air temperature enhanced GPP in approximately two-thirds of the subsections. In contrast, average GS air temperatures showed a negative relationship with annual GPP. When the pre-trained models were forced by downscaled future climate projections, changes in the predicted rangeland productivity by mid- and end of century were more remarkable at the ecoregion subsection scale than at the state level. Our machine learning-based analysis highlights key regional differences in GPP vulnerability to climate and provides insights on the intertwining and potentially counteracting effects of seasonal temperature and precipitation regimes. This work demonstrates the potential of using remote sensing to enhance field-based rangeland monitoring and, combined with machine learning, to inform adaptive management and conservation within the context of weather extremes and climate change.

Quantifying the impacts of land cover change on gross primary productivity globally

Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m−2 yr−1 forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m−2 yr−1, respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency, thereby improving projections of land-based climate mitigation potentials.

Empirical analysis of the influences of meteorological factors on the interannual variations in carbon fluxes of a Quercus variabilis plantation

Influences of meteorological factors on the carbon fluxes of a forest ecosystem can vary with time scales. While many studies were made on daily to annual variations of measured carbon flux of forest ecosystems, few were conducted on the variations of observed carbon fluxes over longer (decadal or more) time scale. This study quantified the influences of meteorological variables on the measured carbon fluxes in a Quercus variabilis plantation from 2006 to 2021 using principal component analysis (PCA) and cluster analysis (CA). PCA was used to identify the most important meteorological variables. They are monthly mean daily maximum global radiation (Rg), monthly effective accumulated temperature (Tac), monthly mean daily maximum vapor pressure deficit (VPD), and monthly precipitation (PP). CA was used to group 192 observed months into four groups based on those four meteorological variables and their effects on the observed carbon fluxes. Structural equation modeling (SEM) was then used to quantify the relative importance and direct or indirect effects of those four meteorological factors on carbon fluxes at the interannual timescale in each of the four groups. The results showed that air temperature had dominant influence on net ecosystem productivity (NEP) and ecosystem respiration (Re) with its relative importance measured by standardized coefficients (SC) of 0.59 and 0.97, respectively. PP directly impacted gross primary production (GPP) with an SC of 0.40 and indirectly influenced NEP and Re. The importance of a given meteorological factor on carbon fluxes and the dominant meteorological factors varied among the four groups. Tac mainly influenced Re with a SC of 0.79 in Group 1 (the nongrowing season). The direct effects of PP on NEP and GPP and indirect effects on Re were most prominent in Group 2 (the transition stage between the nongrowing season and the growing season). Tac and PP had greater influences than other two variables in Group 3 (the transitional stage of early growth and vigorous growth and the transitional stage of steady growth and dormant period). NEP increased with Tac, while excessive rainy weather accompanied by a decrease in temperature and radiation reduced Re and GPP in Group 4 (the wet season). The short-term seasonal droughts with warm air temperatures but little precipitation (mainly in June) led to significant reductions in both GPP and NEP of the Quercus variabilis plantation ecosystem in the warm-temperate continental monsoon climate zone. Our results can be used to guide managing forest plantations in temperate region in China to maximize their carbon sequestration.

Interannual and seasonal relationships between photosynthesis and summer soil moisture in the Ili River basin, Xinjiang, 2000–2018

Soil moisture (SM) is essential for controlling terrestrial carbon uptake, as it directly provides moisture for photosynthesis, especially in arid and semiarid regions. We selected the arid and semiarid Ili River basin (IRB) of Xinjiang as the study area, and investigated the spatial and temporal characteristics and interrelationships with SM and photosynthesis from 2000 to 2018 using the ERA5 products and solar-induced chlorophyll fluorescence (SIF). SM and photosynthesis showed a decreasing trend during the study period. Compared with those in spring and autumn, the variation of summer SM and SIF was more consistent with the interannual variation. Anomaly analysis showed that negative SM anomalies were most profound in 2012–2015, 2008, and 2014. Additionally, we quantified the effect of seasonal SM deficits on photosynthesis by performing model-based experiments. The results indicated that the gross primary productivity (GPP) simulated by the P-model could capture the characteristics of photosynthesis in the IRB, which had a high correlation with SIF (R2 = 0.82, p < 0.001). In 2012–2015, 2008, and 2014, SM deficits caused more GPP reduction in the summers than in the springs or the autumns. The trends were mainly visible in the northern IRB, where GPP was below 40 % of the multi-year mean, and SM was below 23 %. GPP decreased more significantly in grassland than in the forest under the influence of SM deficit. This study reveals seasonal differences in the effects of SM deficit on photosynthesis and emphasizes that the summer SM deficit was the main factor responsible for decreases in GPP in the IRB during the study period. These findings contribute to a better understanding of the relationships between photosynthesis and environmental factors, and provide a reference for an accurate assessment of the regional carbon cycle.

Contrasting drought legacy effects on gross primary productivity in a mixed versus pure beech forest

Abstract. Droughts affect terrestrial ecosystems directly and concurrently and can additionally induce lagged effects in subsequent seasons and years. Such legacy effects of drought on vegetation growth and state have been widely studied in tree ring records and satellite-based vegetation greenness, while legacies on ecosystem carbon fluxes are still poorly quantified and understood. Here, we focus on two ecosystem monitoring sites in central Germany with a similar climate but characterised by different species and age structures. Using eddy covariance measurements, we detect legacies on gross primary productivity (GPP) by calculating the difference between random forest model estimates of potential GPP and observed GPP. Our results showed that, at both sites, droughts caused significant legacy effects on GPP at seasonal and annual timescales, which were partly explained by reduced leaf development. The GPP reduction due to drought legacy effects is of comparable magnitude to the concurrent drought effects but differed between two neighbouring forests with divergent species and age structures. The methodology proposed here allows the quantification of the temporal dynamics of legacy effects at the sub-seasonal scale and the separation of legacy effects from model uncertainties. The application of the methodology at a larger range of sites will help us to quantify whether the identified lag effects are general and on which factors they may depend.