Productivity Of Terrestrial Ecosystems Research Articles

Analyzing the impact of phosphorous and nitrogen on Castanopsis sclerophylla early growth stages

Plant growth elements, particularly nitrogen (N) and phosphorus (P) are vital for their growth and development, particularly for understory vegetation and their excess limits the net productivity of terrestrial ecosystems. This study focuses on the understory vegetation responds and adaptation to key essential nutrients under changing climate scenarios in subtropical evergreen broad-leaved forests, still needs research attention. this, we set up an experiment taking four treatments in a 50-year-old Castanopsis sclerophylla secondary forest under (a) control (CK), (b) N, (c) P, and (d) combined N and P addition, applied to natural forest regeneration seedlings of C. sclerophylla attained similar growth parameters of diameter of 3 cm and 10 cm height. In addition, carbon, N, P, and non-structural carbohydrates (NSC) were determined through the anthrone colorimetric approach in different parts of seedlings. Results show that the combined N + P application enhanced the N and P by 14.48 %−140.55 % in the seedlings in both dry and wet seasons, respectively. However, during wet season, the content of NSC in the plant leaves significantly exceeded under P addition. Remarkably, CK showed increased P in the growing season but lower during the dry season. Furthermore, the root starch content of seedlings showed a significant increase under the application of N and P compared to combined N + P, ranging between 45.60 % and 58.70 %. Overall, the plant growth is attributed to N and P intake. The nutrient addition and seasonal variations have a coupled effect on seedling growth as proved in the in the natural open forest experiment. The study outcomes emphasize that the alterations in NSC allocation in the roots and leaves of C. sclerophylla seedlings under N + P addition could enhance their adaptation to future global climate changes, drought conditions, and high N concentrations.

Reconstruction of temperature and hydroclimate in Serling Co (Central Tibet) since the last deglaciation

Understanding the past climatic conditions and their possible driving mechanism can contribute to better constrain future climate projection, and to provide potential insights into the disputed Holocene temperature variations. In this study, we quantitatively reconstruct the mean annual air temperature (MAAT) of Serling Co since 17.3 cal kyr BP using a novel terrestrial thermometer (ring index of OH-GDGTs, RI-OH), and reconstructed the hydroclimatic evolutionary history in combination with n-alkanes and their associated proxies. Our temperature records indicate that Serling Co experienced a period of reduced temperatures during the Younger Dryas event, approximately 6 °C cooler than the present conditions. Subsequently, there was a rapid warming phase, leading to peak temperatures in the early Holocene, roughly 5.5 °C warmer than the modern MAAT, followed by a protracted cooling trend during the subsequent middle and late Holocene. The temperature and hydroclimate trends at Serling Co exhibit a synchronized evolutionary pattern since the last deglaciation, featuring an optimal hydrothermal combination in the early Holocene. This period witnessed the peak productivity of terrestrial and aquatic ecosystems, followed by a gradual decline. Summer insolation emerges as a primary controlling factor for temperature variations, with Indian Summer Monsoon intensity and internal climate system variability exerting dominance over atmospheric moisture and precipitation variations in the region.

Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset

Remote sensing and process-coupled ecological models are widely used for the simulation of GPP, which plays a key role in estimating and monitoring terrestrial ecosystem productivity. However, most such models do not differentiate the C3 and C4 photosynthetic pathways and neglect the effect of nitrogen content on Vmax and Jmax, leading to considerable bias in the estimation of gross primary productivity (GPP). Here, we developed a model driven by the leaf area index, climate, and atmospheric CO2 concentration to estimate global GPP with a spatial resolution of 0.1° and a temporal interval of 1 day from 2000 to 2022. We validated our model with ground-based GPP measurements at 128 flux tower sites, which yielded an accuracy of 72.3%. We found that the global GPP ranged from 116.4 PgCyear−1 to 133.94 PgCyear−1 from 2000 to 2022, with an average of 125.93 PgCyear−1. We also found that the global GPP showed an increasing trend of 0.548 PgCyear−1 during the study period. Further analyses using the structure equation model showed that atmospheric CO2 concentration and air temperature were the main drivers of the global GPP changes, total associations of 0.853 and 0.75, respectively, while precipitation represented a minor but negative contribution to global GPP.

A 30-m gross primary production dataset from 2016 to 2020 in China

Estimating gross primary production (GPP) of terrestrial ecosystems is important for understanding the terrestrial carbon cycle. However, existed nationwide GPP datasets are primarily driven by coarse spatial resolutions (≥500 m) remotely sensed data, which fails to capture the spatial heterogeneity of GPP across different ecosystem types at land surface. This paper introduces a new GPP dataset, Hi-GLASS GPP v1, with a fine spatial resolution (30-m) and monthly temporal resolution from 2016 to 2020 in China. The Hi-GLASS GPP v1 dataset is generated from 30-m Landsat data using a process based light use efficiency model. The Hi-GLASS GPP v1 model integrates a detailed map of maize plantations, a crucial C4 crop in China known for its higher photosynthetic efficiency compared to C3 crops. This inclusion helps correct the underestimation of GPP that typically occurs when all croplands are categorized as C3. The Hi-GLASS GPP v1 dataset demonstrates a robust correlation with GPP data derived from eddy covariance towers, thereby enabling a more accurate assessment of terrestrial carbon sequestration across China.

Effects of Biophysical Factors on Light Use Efficiency at Multiple Time Scales in a Chinese Cork Oak Plantation Ecosystem

Light use efficiency (LUE) characterizes the efficiency of vegetation in converting photosynthetically active radiation (PAR) into biomass energy through photosynthesis and is a critical parameter for gross primary productivity (GPP) in terrestrial ecosystems. Based on the eddy covariance measurements of a Chinese cork oak plantation ecosystem in northern China, the temporal variations in LUE were investigated, and biophysical factors were examined at time scales ranging from hours to years. Our results show that diurnal LUE first increased sharply before 8:30 and then decreased gradually until 12:00, thereafter increasing gradually and reaching the maximum value at sunset during the growing season. The daily and monthly LUE first increased and then decreased within a year and showed a substantial drop around June. The annual LUE ranged from 0.09 to 0.17 g C mol photon−1, and the multiyear mean maximal LUE was 0.30 g C mol photon−1 during 2006–2019. Only GPP (positive) and clearness index (CI) (negative) had consistent effects on LUE at different time scales, and the effects of the remaining biophysical factors on LUE were different as the time scale changed. The effects of air temperature, vapor pressure deficit, precipitation, evaporative fraction, and normalized difference vegetation index on LUE were mainly indirect (via PAR and/or GPP). When CI decreased, an increased ratio of diffuse PAR to PAR produced a more uniform irradiance in the canopy, which ultimately resulted in a higher LUE. Due to climate change in our study area, the annual LUE may decrease in the future but improving management practices may slow or even reverse this trend in the annual LUE in the studied Chinese cork oak plantation.

Trends in the Research and Development of Soil Nitrogen Mineralization in Forests from 2004 to 2024

Nitrogen (N) is a vital mineral nutrient for plant growth and occupies a pivotal position in biogeochemical systems. Soil nitrogen mineralization (SNM) in forests represents a significant limiting factor in terrestrial ecosystem productivity in the context of global climate change. To understand the research status and development trends of SNM in forests, 3576 articles spanning 2004 to 2024 from the Web of Science (WOS) database were analyzed using CiteSpace software. The results indicated that (1) the mean number of articles published in the recent ten-year period is 193, marking an approximate 17.8% increase compared to the preceding ten-year period (2004–2013), highlighting the continuous development of SNM research; (2) among the sampled articles, Soil Biology and Biochemistry, Forest Ecology and Management, Plant and Soil, and Biogeochemistry emerged as leading international journals that played a key role in shaping the development of the field and laid a solid foundation for future research efforts; (3) the USA and China emerged as the most productive countries in this field, with the Chinese Academy of Sciences standing out as a prominent institution at the forefront of this research domain; and (4) recent research is focusing on understanding the interactions between microbial communities and the environment during SNM. In summary, this study offers valuable insights into the research status and development trends of SNM in forests. It underscores the importance of ongoing interdisciplinary collaboration and innovation to further enhance our understanding of key ecological processes. Future research on SNM in forests is encouraged to delve deeper into its associations with forest productivity, carbon cycling, microbial functions, and global change. Additionally, exploring sustainable land management and process optimization is recommended to promote the healthy and sustainable development of forest ecosystems.

Substantial nitrogen abatement accompanying decarbonization suppresses terrestrial carbon sinks in China

China faces challenges in reaching its carbon neutrality goal by the year 2060 to meet the Paris Agreement and improving air quality simultaneously. Dramatic nitrogen emission reductions will be brought by this ambitious target, yet their impact on the natural ecosystem is not clear. Here, by combining two atmospheric chemistry models and two process-based terrestrial ecosystem models constrained using nationwide measurements, we show that atmospheric nitrogen deposition in China’s terrestrial land will decrease by 44–57% following two emission control scenarios including one aiming at carbon neutrality. They consequently result in a pronounced shrinkage in terrestrial net ecosystem production, by 11–20% depending on models and emission scenarios. Our results indicate that the nitrogen emission reductions accompanying decarbonization would undermine natural carbon sinks and in turn set back progress toward carbon neutrality. This unintended impact calls for great concern about the trade-offs between nitrogen management and carbon neutrality.

Tracing of fire‐induced soil phosphorus transformations using phosphate oxygen isotope ratio

AbstractThis study demonstrates that phosphate oxygen isotope (δ18OPO4) analysis effectively detects and monitors fire‐induced transformation in soil phosphorus (P). Fires increase bioavailable P, potentially limiting primary production in terrestrial ecosystems. However, understanding the effects of fire on soil P dynamics in the field remains challenging due to the interaction between fire spread and soil properties with high spatial heterogeneity. Soil burning experiments were conducted using a surface soil sample collected in central Japan. The soil was burned in an electric furnace from 50 to 550°C for 3 h, and P concentrations and δ18OPO4 values were determined. The results revealed that high temperatures (>350°C) depleted the soil of organic P (Po) and increased labile and stable inorganic P (Pi) concentrations while significantly decreasing δ18OPO4 values. By contrast, low temperatures (150°C) increased labile Pi and Po concentrations without isotopic shift, indicating that low‐intensity fires could increase bioavailable P while conserving soil organic matter. These findings indicate that δ18OPO4 analysis can provide insight into the relationship between P transformations and fire intensity and track subsequent changes in P dynamics over time. Our research highlights the potential of δ18OPO4 in predicting and managing postfire ecological and agricultural impacts.

Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia

Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia

Global increase in the optimal temperature for the productivity of terrestrial ecosystems

Vegetation growth may adapt to climate warming by adjusting the relationship between photosynthetic capacity and temperature. However, changes in the optimal temperature for ecosystem productivity during recent decades of warming remain uncertain. Here we provide empirical evidence that global optimal temperature increased at a rate of 0.017 ± 0.002 °C y−1 from 1982 to 2016, using multiple datasets of satellite-derived productivity and climate variables. Model simulations show that the optimal temperature will increase by 0.027 ± 0.001 °C y−1 until the end of 21st century. The global increasing optimal temperature is consistent with increasing mean air temperatures and model simulations further confirm the key role of temperature in regulating changes in optimal temperature, while being co-regulated by other factors, such as CO2 and precipitation. These results suggest that vegetation is acclimating to warming and that the negative impacts of climate change on ecosystem productivity may be less severe than previously thought.

Variations of Terrestrial Net Ecosystem Productivity in China Driven by Climate Change and Human Activity from 2010 to 2020

Net ecosystem productivity (NEP) plays an important role in the quantitative evaluation of carbon source/sinks in terrestrial ecosystems. This study used Theil–Sen median trend analysis, the Mann–Kendall method, and the Geodetector model to analyze the variation patterns and its dominant factors of NEP from 2010 to 2020. The results showed the following: (1) During 2010–2020, the spatial distribution of carbon sinks in China’s terrestrial ecosystems showed a pattern of high in the southeast and low in the northwest. The area with NEP < 0 accounted for 44.74% of the total area, while the area with NEP > 0 accounted for 55.26%. (2) The northwest region belonged to the significant carbon source, while the other regions belonged to significant carbon sinks. (3) The annual average NEP in different sub-regions showed an increasing trend. During 2010–2020, the overall NEP in China showed a trend in shifting from low-level to high-level, indicating that the NEP of terrestrial ecosystems in China increased during the past 11 years. (4) The NEP gravity center in Northeast China showed a trend in moving southward and then northward, while that of the NEP gravity center in East China showed a circular migration trend of ‘northwest-southwest–northeast–southeast’. The gravity center of NEP in Northwest China was moving northeastward. The migration trajectory of the NEP gravity center in Southwest China presented a “Z” shape. The change in the gravity center of NEP in the central and southern regions had a strong circuitous nature, and the overall trend was to migrate southward. (5) The combined actions of climate change and human activities were the main reason for the change in NEP in China’s terrestrial ecosystem from 2010 to 2020. (6) There were obvious differences in the dominant driving factors of NEP evolution in different regions and different periods in the past 40 years.

Atmospheric water demand dominates terrestrial ecosystem productivity in China

Vegetation production is critical for carbon sequestration in terrestrial ecosystems. However, the relative contribution of soil moisture (SM) and vapor pressure deficit (VPD) to vegetation production in ecosystems remains debated. This study combined SM and VPD data with satellite observations of solar-induced fluorescence (SIF) from 2003 to 2018 to examine the contribution of SM and VPD to long-term variations in vegetation production using binning approach. Constraint lines based on restricted cubic splines were established to investigate the threshold for the responses of vegetation production potential to VPD and SM. The results revealed that VPD had greater impacts on vegetation production in Chinese terrestrial ecosystems than SM, with VPD-dominated and SM-dominated areas accounting for approximately 84 % and 16 % of the total national area, respectively. The mean values of SIF changes under the independent influence of SM and VPD were 0.034 mWm−2nm−1sr−1 and 0.130 mWm−2nm−1sr−1, respectively, indicating higher sensitivity of SIF to VPD. The effects of SM and VPD on ecosystem production varied across aridity gradients, with VPD making a significant contribution to forest ecosystem production. However, determining the relative effects of SM and VPD in ecosystems with low vegetation cover was difficult. Further exploration revealed that the maximum potential for terrestrial ecosystem production increased with VPD, peaking at a VPD of about 1.275 ± 0.068 kPa. Beyond this range, the maximum production potential declined. Our study confirms that VPD has a stronger and more extensive influence on the trend and variability of ecosystem production in China than SM.

Causal inference reveals the dominant role of interannual variability of carbon sinks in complicated environmental-terrestrial ecosystems

Climate factors (CFs) are key variables shaping the interannual variability (IAV) of terrestrial ecosystem carbon sinks. However, the dominant CFs influencing the IAV of terrestrial carbon sinks remains debated, as CFs are coupled via land-atmosphere interactions. Here, the dominant factors influencing the IAV of global terrestrial net ecosystem production (NEP) were quantified using the convergent cross-mapping (CCM) technique. This analysis was conducted with distinct global terrestrial NEP datasets deriving from process-based ecosystem models, machine learning techniques, and eddy covariance flux towers. Results revealed that the spatial patterns of IAV of global terrestrial NEP were dominated by water availability (WA) and temperature (Ts). Ts mainly controlled the IAV of terrestrial NEP in mid to high-latitude regions of the Northern Hemisphere (NH), while WA exerted dominance over low and mid-latitude regions in both the NH and the Southern Hemisphere. Moreover, the energy limitation and water limitation explained the spatial pattern of Ts and WA dominant on NEP. Further analysis found that WA and Ts also played a dominant role in gross primary productivity (GPP) and terrestrial ecosystem respiration (TER), proving that WA and Ts were the dominant factors affecting NEP. In addition, we found a weakening trend in causal linkages of CFs to NEP in the temporal domain. This study used causal analysis to reveal the spatial patterns of water and heat dominating the NEP, providing support for improved assessment and prediction of terrestrial carbon sinks under climate change.

Nitrogen deposition differentially regulates the sensitivity of gross primary productivity to extreme drought versus wetness.

Global hydroclimatic variability is increasing with more frequent extreme dry and wet years, severely destabilizing terrestrial ecosystem productivity. However, what regulates the consequence of precipitation extremes on productivity remains unclear. Based on a 9-year field manipulation experiment on the Qinghai-Tibetan Plateau, we found that the responses of gross primary productivity (GPP) to extreme drought and wetness were differentially regulated by nitrogen (N) deposition. Over increasing N deposition, extreme dry events reduced GPP more. Among the 12 biotic and abiotic factors examined, this was mostly explained by the increased plant canopy height and proportion of drought-sensitive species under N deposition, making photosynthesis more sensitive to hydraulic stress. While extreme wet events increased GPP, their effect did not shift over N deposition. These site observations were complemented by a global synthesis derived from the GOSIF GPP dataset, which showed that GPP sensitivity to extreme drought was larger in ecosystems with higher N deposition, but GPP sensitivity to extreme wetness did not change with N deposition. Our findings indicate that intensified hydroclimatic variability would lead to a greater loss of land carbon sinks in the context of increasing N deposition, due to that GPP losses during extreme dry years are more pronounced, yet without a synchronous increase in GPP gains during extreme wet years. The study implies that the conservation and management against climate extremes merit particular attention in ecosystems subject to N deposition.

Advanced precipitation enhances vegetation primary productivity in Central Asia

Climate change is reshaping the seasonal distribution of precipitation patterns across Central Asia, affecting not only the total accumulation but also the timing of precipitation events. However, how seasonal precipitation timing (i.e., precipitation seasonality) shift and may influence dryland ecosystem responses have rarely been considered. Here we utilized gross primary productivity (GPP) data derived from satellite observations over 2001–2022 and a proxy of precipitation timing (precipitation center time index, PCT) to elucidate changes in precipitation timing and assess its impact on vegetation productivity along bioclimate gradients in Central Asia. Our findings revealed that, from southwest to northeast, the precipitation season gradually extended from spring (PCT ≤ 5.0) to summer (PCT ≥ 6.0). Notably, approximately 74.4 % of the study area exhibited a trend of advanced precipitation, particularly evident in regions characterized by earlier precipitation onset. Changes in precipitation timing were found to induce variations in vegetation productivity, albeit with spatial heterogeneity. About 82.0 % of the vegetated areas showed positive GPP anomalies with advanced precipitation, especially in the eastern drylands, while delayed precipitation depressed productivity, leading to negative GPP anomalies in nearly 65.9 % of the vegetation zones. Vegetation in arid regions demonstrated heightened susceptibility to altered precipitation timing, whereas this sensitivity diminished in humid regions characterized by greater moisture availability. More precipitation distributed in early growing season would be more favorable to increase GPP, especially in xeric sparse vegetation, grassland, rained cropland, and shrubland. Our study highlight that it is necessary to pay more attention to the effects of altered precipitation timing on changes in terrestrial ecosystem productivity related to carbon cycle, especially in dryland.

Grassland productivity in arid Central Asia depends on the greening rate rather than the growing season length

Climate change has induced substantial impact on the gross primary productivity (GPP) of terrestrial ecosystems by affecting vegetation phenology. Nevertheless, it remains unclear which among the mean rates of grass greening (RG), yellowing (RY), and the length of growing season (LOS) exhibit stronger explanatory power for GPP variations, and how RG and RY affect GPP variations under warming scenarios. Here, we explored the relationship between RG, RY, LOS, and GPP in arid Central Asia (ACA) from 1982 to 2019, elucidating the response mechanisms of RG, RY, and GPP to the mean temperature (TMP), vapor pressure deficit (VPD), precipitation (PRE), and soil moisture (SM). The results showed that the multi-year average length of greening (LG) in ACA was 22.7 days shorter than that of yellowing (LY) and the multi-year average GPP during LG (GPPlg) was 38.28 g C m−2 d −1 more than that of during LY (GPPly). RG and RY were positively correlated with GPPlg and GPPly, although the degree of correlation between RG and GPPlg was higher than that between RY and GPPly. Increases in RG and RY contributed to an increase in GPPlg (55.44 % of annual GPP) and GPPly (35.44 % of annual GPP). The correlation between RG and GPPlg was the strongest (0.49), followed by RY and GPPly (0.33), and LOS and GPP was the weakest (0.21). TMP, VPD, PRE, and SM primarily affected GPP by influencing RG and RY, rather than direct effects. The positive effects of TMP during LG (TMPlg), PRE during LG (PRElg), and SM during LG (SMlg) facilitated increases in RG and GPPlg, and higher VPD during LY (VPDly) and lower PRE during LY (PREly) accelerated increases in RY. Our study elucidated the impact of vegetation growth rate on GPP, thus providing an alternate method of quantifying the relationship between vegetation phenology and GPP.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit.

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Geotechnologies on the phosphorus stocks determination in tropical soils: General impacts on society

Phosphorus (P) is a critical nutrient for primary production in terrestrial and aquatic ecosystems. As P mineral reserves are finite and non-renewable, there is an increasing discussion on its sustainable utilization to safeguard food security for future generations. Understanding the spatial distribution of soil P is central in advancing effective phosphorus management and fostering sustainable agricultural practices. This study aims to digitally map the stocks of available P (AP) and total P (TP) in Brazil at a fine resolution (30 m). Using the Random Forest machine learning algorithm and a database of topsoil (0-20 cm) with 28,572 samples for AP and 3154 for TP, we predicted P stocks based on environmental covariates related to soil formation processes. By dividing Brazil into two sub-regions, representing areas with native coverage and anthropogenic ones, we built independent predictive models for each sub-region. Our results show that Brazil has a TP stock of 531 Tg and an AP stock of 17.4 Tg. The largest soil TP stocks are in the Atlantic Forest biome (73.8 g.m2), likely due to higher organic carbon stocks in this biome. The largest AP stocks were in the Caatinga biome (2.51 g.m2) because of younger soils with low P adsorption capacity. We also found that fertilizer use significantly increased AP stocks in agricultural areas compared to native ones. Our results indicated that AP stocks strongly influenced Brazil's agricultural production, with a correlation coefficient ranging from 0.20 for coffee crops to 0.46 for soybean. The maps generated in this study are expected to contribute to the sustainable use of P in agriculture and environmental systems.

Rising plant demand strengthens nitrogen limitation in tidal marsh.

Nitrogen (N) is a limiting nutrient for primary productivity in most terrestrial ecosystems, but whether N limitation is strengthening or weakening remains controversial because both N sources and sinks are increasing in magnitude globally. Temperate marshes are exposed to greater amounts of external N inputs than most terrestrial ecosystems and more than in preindustrial times owing to their position downstream of major sources of human-derived N runoff along river mouths and estuaries. Simultaneously, ecosystem N demand may also be increasing owing to other global changes such as rising atmospheric [CO2]. Here, we used interannual variability in external drivers and variables related to exogenous supply of N, along with detailed assessments of plant growth and porewater biogeochemistry, to assess the severity of N-limitation, and to determine its causes, in a 14-year N-addition × elevated CO2 experiment. We found substantial interannual variability in porewater [N], plant growth, and experimental N effects on plant growth, but the magnitude of N pools through time varied independently of the strength of N limitation. Sea level, and secondarily salinity, related closely to interannual variability in growth of the dominant plant functional groups which drove patterns in N limitation and in porewater [N]. Experimental exposure of plants to elevated CO2 and years with high flooding strengthened N limitation for the sedge. Abiotic variables controlled plant growth, which determined the strength of N limitation for each plant species and for ecosystem productivity as a whole. We conclude that in this ecosystem, which has an open N cycle and where N inputs are likely greater than in preindustrial times, plant N demand has increased more than supply.

Assessing the spatiotemporal dynamics of water and carbon fluxes in subtropical forest of Xin’an River Basin using an improved Biome-BGC model

Extreme climate occurred frequently in subtropical region, which seriously affects carbon and water fluxes such as evapotranspiration (ET) and gross primary productivity (GPP) of terrestrial ecosystems. The process-based biome biogeochemical cycles (Biome-BGC) model is widely used for simulating carbon and water fluxes of forest ecosystems. However, the lack of the interaction information of climate, vegetation and soil, such as the hysteresis effect, canopy stratification on photosynthesis, impedes better simulations of the ecohydrological processes. Here, we tended to improve the simulation accuracy of Biome-BGC model at a subtropical forest on the Xin’an River in Southeastern China by reconstructing the precipitation series, modifying the ET and canopy multilayers modules, and optimizing the parameters. The spatiotemporal patterns of GPP, ET, water use efficiency (WUE) and their response to environmental factors across the Xin’an River Basin from 1982 to 2018 were further explored. The results showed that the improved model performed well, with the determination coefficient, root means square error and mean absolute error being 0.730, 1.522 gC/m2/d and 1.218 gC/m2/d for GPP, 0.857, 1.082 mm/d and 0.838 mm/d for ET, respectively. Basin-averaged GPP, ET and WUE increased during 1982–2018 and these increasing trends were more pronounced during 1999–2018. Significant positive trends of WUE occurred in the northeast corner. The increasing air temperature and precipitation respectively dominated the increase in GPP and ET, the increasing CO2 concentration and NDVI mitigated the negative effect of extreme precipitation on WUE. Given that human activities such as afforestation have effectively reduced the extent of damage to forest ecosystems from extreme precipitation, we highlight an urgent need to formulate adaptation strategies aimed at reducing the risk of extreme climate in humid regions.