Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to ac...Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.展开更多
Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations i...Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.展开更多
Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In t...Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In this study,we developed a multi-flux global sensitivity discriminant index(D_(sen))by integrating the Biome-BGCMuSo model with eddy covariance flux observations.This index was combined with a Bayesian optimization algorithm to conduct parameter optimization.The results demonstrated that:(1)Sensitivity analysis identified 13 highly sensitive parameters affecting carbon and water fluxes.Among these,the canopy light extinction coefficient(k)and the fraction of leaf N in Rubisco(FLNR)exhibited significantly higher sensitivity to carbon fluxes(GPP,NEE,Reco;D_(sen)>10%)compared to water flux(ET).This highlights the strong dependence of carbon cycle simulations on vegetation physiological parameters.(2)The Bayesian optimization framework efficiently converged 30 parameter spaces within 50 iterations,markedly improving carbon fluxes simulation accuracy.The Kling-Gupta efficiency(KGE)values for Gross Primary Production(GPP),Net Ecosystem Exchange(NEE),and Total Respiration(Reco)increased by 44.94%,69.23%and 123%,respectively.The optimization prioritized highly sensitive parameters,underscoring the necessity of parameter sensitivity stratification.(3)The optimized model effectively reproduced carbon sink characteristics in mountain meadows during the growing season(cumulative NEE=-375 g C/m^(2)).It revealed synergistic carbon-water fluxes interactions governed by coupled photosynthesis-stomatal pathways and identified substrate supply limitations on heterotrophic respiration.This study proposes a novel multi-flux sensitivity index and an efficient optimization framework,elucidating the coupling mechanisms between vegetation physiological regulation(k,FLNR)and environmental stressors(VPD,SWD)in carbonwater cycles.The methodology offers a practical approach for arid ecosystem model optimization and provides theoretical insights for grassland management through canopy structure regulation and water-use efficiency enhancement.展开更多
Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical...Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we展开更多
Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is es...Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.展开更多
Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model...Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.展开更多
Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,th...Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.展开更多
Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human...Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human and environmental pressures remain poorly understood.In this study,we analyzed the spatiotemporal evolution of NEP in the Horqin Sandy Land,China from 2000 to 2020,and observed the variation in NEP across different land use types.We further identified and quantified the effects of human activities,topographical features,climatic conditions,and soil properties on NEP through the application of structural equation modeling(SEM)and boosted regression trees(BRT).The results showed that the multi-year average NEP ranged from–137.79 to 461.96 g C/m^(2) in the Horqin Sandy Land,with 88.21%of the area showing a significant increasing trend.Among different land use types,forestland exhibited the highest NEP values,followed by cropland,grassland,impervious land,and unused land.The NEP in carbon sink areas was primarily regulated by potential evapotranspiration(negatively correlated)and precipitation(positively correlated).Slope was identified as the most significant positive determinant in carbon source areas.Forestland exhibited climate–topography interactions driving NEP,whereas cropland and grassland relied on temperature;unused land and impervious land were susceptible to land use/cover change and human footprint.This study has significant implications for maintaining the carbon sink function and promoting ecological engineering programs that aim to enhance the capacity of terrestrial carbon sinks in the semi-arid agro-pastoral ecotone.展开更多
Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and ...Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.展开更多
This paper’s simple ecological model to simulate the ecosystem variation and the vertical carbon flux in the central part of the East China Sea in spring, inter-reated the phytoplankton, zooplankton,autotrophic and h...This paper’s simple ecological model to simulate the ecosystem variation and the vertical carbon flux in the central part of the East China Sea in spring, inter-reated the phytoplankton, zooplankton,autotrophic and heterotrophic bacterioplankton, nitrate, and dissolved organic carbon (DOC) in a run lasting 90 days. Except for DOC, because of poor observation precision,the major seasonal features of the vertical distribution for these components can be simulated by this model. The results show that spring bloom is just a short period of 1-2 weeks and that deposit carbon flux at the bottom interface is about 200 mg /m2 ·d in the first 20 days and then reaches its maximum of 1500mg/m2·d about 2 months later after the spring bloom.展开更多
A mass-balanced model was constructed to determine the flow-energy in a community of fishes and invertebrates in the Beibu Gulf, northern South China Sea using Ecopath and Ecosim software. Input parameters were taken ...A mass-balanced model was constructed to determine the flow-energy in a community of fishes and invertebrates in the Beibu Gulf, northern South China Sea using Ecopath and Ecosim software. Input parameters were taken from the literature, except for the biomass of fish groups which was obtained from trawl surveys during October 1997 to May 1999 in the study area. The model consisted of 16 functional groups （boxes）, including one marine mammal and seabirds, each representing organisms with a similar role in the food web, and only covered the main trophic flow in the Beibu Gulf ecosystem. The results showed that the food web of Beibu Gulf was dominated by the detrital path and benthic invertebrates played a significant role in transferring energy from the detritus to higher trophic levels; phytoplankton was a primary producer and most utilized as a food source. Fractional trophic levels ranged from 1.0 to 4.08 with marine mammals occupying the highest trophic level. Using network analysis, the system network was mapped into a linear food chain and six discrete trophic levels were found with a mean transfer efficiency of 16.7% from the detritus, 16.2% from the primary producer within the ecosystem. The biomass density of the commercially utilized species estimated by the model is 8.46 t/km^2, only O. 48% of the net primary production.展开更多
Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and short...Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and shortcomings of urban expansion management strategies. A three-step method was applied to Yinchuan Plain in the northwestern of China, including(1)analyzing the relationship between landscape pattern and ecosystem service values through mathematical statistics;(2) predicting landscape pattern and ecosystem services change under different scenarios based on cellular automaton model(SLEUTH-3r model); and(3) designing and validating optimized scenario through integrating historical analysis experiments and future multi-comparison suggestions. Results have suggested that landscape composition and configuration can significantly affect regional ecosystem service values, especially the connectivity and shape of landscape. Compact urban growth policy and medium environment protection policy are the appropriate setting for urban expansion plan. Optimization validation of the combined designed scenario implied the reliability of this method. Our results highlighted the significance of integrating application of landscape pattern analysis, ecosystem service value evaluation,model simulation and multi-scenario prediction in urban planning.展开更多
For ecological restoration and reconstruction of the degraded area, it is an important premise to correctly understand the degradation factors of the ecosystem in the arid-hot valleys. The factors including vegetation...For ecological restoration and reconstruction of the degraded area, it is an important premise to correctly understand the degradation factors of the ecosystem in the arid-hot valleys. The factors including vegetation degradation, land degradation, arid climate, policy failure, forest fire, rapid population growth, excessive deforestation, overgrazing, steep slope reclamation, economic poverty, engineering construction, lithology, slope, low cultural level, geological hazards, biological disaster, soil properties etc, were selected to study the Yuanmou arid-hot valleys. Based on the interpretative structural model （ISM）, it has found out that the degradation factors of the Yuanmou arid-hot valleys were not at the same level but in a multilevel hierarchical system with internal relations, which pointed out that the degradation mode of the arid-hot valleys was ＂straight （appearance）-penetrating-background＂. Such researches have important directive significance for the restoration and reconstruction of the arid-hot valleys ecosystem.展开更多
This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosys-tem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models ...This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosys-tem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models are also introduced. To illustrate the application of the adjoint technique and its merits, a 4-variable ecosystem model coupled with a 3-D physical model is established for the Bohai Sea and the Yellow Sea. The chlorophyll concentration data derived from the SeaWiFS o-cean colour data are assimilated in the model with the technique. Some results are briefly presented.展开更多
Based on experiment data of the Sino-German comprehensive investigations in the Bohai Sea in 1998 and 1999, a simple coupled pelagic-benthic ecosystem multi-box model is used to simulate the ecosystem seasonal variati...Based on experiment data of the Sino-German comprehensive investigations in the Bohai Sea in 1998 and 1999, a simple coupled pelagic-benthic ecosystem multi-box model is used to simulate the ecosystem seasonal variation. The pelagic sub-model consists of seven state variables： phytoplankton, zooplankton, TIN, TIP, DOC, POC and dissolved oxygen （DO）. The benthic sub-model includes macro-benthos, meiobenthos, bacteria, detritus, TIN and TIP in the sediment. Besides the effects of solar radiation, water temperature and the nutrient from sea bottom exudation, land-based inputs are considered. The impact of the advection terms between the boxes is also considered. Meanwhile, the effects of the micro- bial-loop are introduced with a simple parameterization. The seasonal variations and the horizontal distributions of the ecosystem state variables of the Bohai Sea are simulated. Compared with the observations, the results of the multi-box model are reasonable. The modeled results show that about 13% of the photosynthesis primary production goes to the main food loop, 20% transfers to the benthic domain, 44% is consumed by the respiration of phytoplankton, and the rest goes to DOC. Model results also show the importance of the microbial food loop in the ecosystem of the Bohai Sea, and its contribution to the annual zooplankton production can be 60%-64%.展开更多
Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations...Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.展开更多
Some simplified dynamic models of grass field ecosystem are developed and investigated. The maximum simplified one consists of two variables, living grass biomass and soil wetness. The analyses of such models show tha...Some simplified dynamic models of grass field ecosystem are developed and investigated. The maximum simplified one consists of two variables, living grass biomass and soil wetness. The analyses of such models show that there exists only desert regime without grasses if the precipitation p is less than a critical value pc; the grass biomass continuously depends on p if the interaction between grass biomass and the soil wetness is weak, but the strong interaction results in the bifurcation of grass biomass in the vicinity of pc: the grass biomass is rich as p > pc, but it becomes desertification as p<pc. Periodic solutions also exist in the model, if the seasonal cycle of model's parameters is introduced. An improved model consists of three variables, i.e. the living grass biomass x, the nonliving grass biomass accumulated on the ground surface y and the soil wetness z. The behaviours of such three variables model are more complicated. The initial values of y and z play a very important role.展开更多
Allometric equations developed for the Lama forest, located in southern Benin, West Africa, were applied to estimate carbon stocks of three vegetation types：undisturbed forest, degraded forest, and fallow. Carbon sto...Allometric equations developed for the Lama forest, located in southern Benin, West Africa, were applied to estimate carbon stocks of three vegetation types：undisturbed forest, degraded forest, and fallow. Carbon stock of the undisturbed forest was 2.7 times higher than that in the degraded forest and 3.4 times higher than that in fallow. The structure of the forest suggests that the individual species were generally concentrated in lower diameter classes. Carbon stock was positively correlated to basal area and negatively related to tree density, suggesting that trees in higher diameter classes contributed significantly to the total carbon stock. The study demonstrated that large trees constitute an important component to include in the sampling approach to achieve accurate carbon quantification in forestry. Historical emissions from deforestation that converted more than 30% of the Lama forest into cropland between the years 1946 and 1987 amounted to 260,563.17 tons of carbon per year（t CO2/year） for the biomass pool only. The study explained the application of biomass models and ground truth data to estimate reference carbon stock of forests.展开更多
Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas.As the impacts of climate change and human disturbance intensify across time,uncertainties in both water resour...Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas.As the impacts of climate change and human disturbance intensify across time,uncertainties in both water resource supplies and demands increase in arid and semi-arid areas.Taking a typical arid region in China,Xinjiang Uygur Autonomous Region,as an example,water yield depth(WYD)and water utilization depth(WUD)from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model and socioeconomic data.The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference(WSDD)and water supply rate(WSR).The internal factors in changes of WYD and WUD were explored using the controlled variable method.The results show that the supplydemand relationships of water resources in Xinjiang were in a slight deficit,but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation.WYD generally experienced an increasing trend,and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin.WUD had a downward trend with a decline of 20.70%,especially in oasis areas.Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased.The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang,and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×10^(8)m^(3).This study analyzed water resource supplies and demands from a perspective of ecosystem services,which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation.The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.展开更多
Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM ski...Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization(PO), which is an important step in model calibration. An effi cient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the effi ciency of model calibration by analyzing and estimating the goodness-of-fi t of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confi dence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientifi c and normative technical framework for the improvement of MEDM skill.展开更多
基金supported by the National Natural Science Foundation of China(42101382 and 41901342)the Shandong Provincial Natural Science Foundation(ZR2020QD016)the National Key Research and Development Program of China(2016YFD0300101).
文摘Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.
基金supported by the National Key Research and Development Program of China(2016YFD0300101,and 2016YFD0300110)the National Natural Science Foundation of China(41871253 and 31671585)+1 种基金the“Taishan Scholar”Project of Shandong Province,Chinathe Key Basic Research Project of Shandong Natural Science Foundation,China(ZR2017ZB0422)。
文摘Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.
基金jointly funded by the National Natural Science Foundation of China(Grant No.42161024)the Central Financial Forestry and Grassland Science and Technology Extension Demonstration Project(2025)(Grant No.Xin[2025]TG 09)。
文摘Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In this study,we developed a multi-flux global sensitivity discriminant index(D_(sen))by integrating the Biome-BGCMuSo model with eddy covariance flux observations.This index was combined with a Bayesian optimization algorithm to conduct parameter optimization.The results demonstrated that:(1)Sensitivity analysis identified 13 highly sensitive parameters affecting carbon and water fluxes.Among these,the canopy light extinction coefficient(k)and the fraction of leaf N in Rubisco(FLNR)exhibited significantly higher sensitivity to carbon fluxes(GPP,NEE,Reco;D_(sen)>10%)compared to water flux(ET).This highlights the strong dependence of carbon cycle simulations on vegetation physiological parameters.(2)The Bayesian optimization framework efficiently converged 30 parameter spaces within 50 iterations,markedly improving carbon fluxes simulation accuracy.The Kling-Gupta efficiency(KGE)values for Gross Primary Production(GPP),Net Ecosystem Exchange(NEE),and Total Respiration(Reco)increased by 44.94%,69.23%and 123%,respectively.The optimization prioritized highly sensitive parameters,underscoring the necessity of parameter sensitivity stratification.(3)The optimized model effectively reproduced carbon sink characteristics in mountain meadows during the growing season(cumulative NEE=-375 g C/m^(2)).It revealed synergistic carbon-water fluxes interactions governed by coupled photosynthesis-stomatal pathways and identified substrate supply limitations on heterotrophic respiration.This study proposes a novel multi-flux sensitivity index and an efficient optimization framework,elucidating the coupling mechanisms between vegetation physiological regulation(k,FLNR)and environmental stressors(VPD,SWD)in carbonwater cycles.The methodology offers a practical approach for arid ecosystem model optimization and provides theoretical insights for grassland management through canopy structure regulation and water-use efficiency enhancement.
文摘Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we
文摘Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.
文摘Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.
基金National Key R&D Program of China,No.2022YFF1302401National Natural Science Foundation of China,No.42271007。
文摘Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.
基金funded by the National Major Science and Technology Program for Water Pollution Control and Treatment(2017ZX07101-002)the Discipline Construction Program of ZHANG Huayong,Distinguished Professor of School of Life Sciences,Shandong University(61200082363001).
文摘Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human and environmental pressures remain poorly understood.In this study,we analyzed the spatiotemporal evolution of NEP in the Horqin Sandy Land,China from 2000 to 2020,and observed the variation in NEP across different land use types.We further identified and quantified the effects of human activities,topographical features,climatic conditions,and soil properties on NEP through the application of structural equation modeling(SEM)and boosted regression trees(BRT).The results showed that the multi-year average NEP ranged from–137.79 to 461.96 g C/m^(2) in the Horqin Sandy Land,with 88.21%of the area showing a significant increasing trend.Among different land use types,forestland exhibited the highest NEP values,followed by cropland,grassland,impervious land,and unused land.The NEP in carbon sink areas was primarily regulated by potential evapotranspiration(negatively correlated)and precipitation(positively correlated).Slope was identified as the most significant positive determinant in carbon source areas.Forestland exhibited climate–topography interactions driving NEP,whereas cropland and grassland relied on temperature;unused land and impervious land were susceptible to land use/cover change and human footprint.This study has significant implications for maintaining the carbon sink function and promoting ecological engineering programs that aim to enhance the capacity of terrestrial carbon sinks in the semi-arid agro-pastoral ecotone.
基金supported by the International Science & Technology Cooperation Program of China (2010DFA92720-10)the "Hundred Talents Program" of the Chinese Academy of Sciences (Y174131001)supported by the National Basic Research Program of China (2009CB825105)
文摘Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.
文摘This paper’s simple ecological model to simulate the ecosystem variation and the vertical carbon flux in the central part of the East China Sea in spring, inter-reated the phytoplankton, zooplankton,autotrophic and heterotrophic bacterioplankton, nitrate, and dissolved organic carbon (DOC) in a run lasting 90 days. Except for DOC, because of poor observation precision,the major seasonal features of the vertical distribution for these components can be simulated by this model. The results show that spring bloom is just a short period of 1-2 weeks and that deposit carbon flux at the bottom interface is about 200 mg /m2 ·d in the first 20 days and then reaches its maximum of 1500mg/m2·d about 2 months later after the spring bloom.
文摘A mass-balanced model was constructed to determine the flow-energy in a community of fishes and invertebrates in the Beibu Gulf, northern South China Sea using Ecopath and Ecosim software. Input parameters were taken from the literature, except for the biomass of fish groups which was obtained from trawl surveys during October 1997 to May 1999 in the study area. The model consisted of 16 functional groups （boxes）, including one marine mammal and seabirds, each representing organisms with a similar role in the food web, and only covered the main trophic flow in the Beibu Gulf ecosystem. The results showed that the food web of Beibu Gulf was dominated by the detrital path and benthic invertebrates played a significant role in transferring energy from the detritus to higher trophic levels; phytoplankton was a primary producer and most utilized as a food source. Fractional trophic levels ranged from 1.0 to 4.08 with marine mammals occupying the highest trophic level. Using network analysis, the system network was mapped into a linear food chain and six discrete trophic levels were found with a mean transfer efficiency of 16.7% from the detritus, 16.2% from the primary producer within the ecosystem. The biomass density of the commercially utilized species estimated by the model is 8.46 t/km^2, only O. 48% of the net primary production.
基金supported by the National Natural Science Foundation of China [Grant number 41371176]the Fundamental Research Funds for the Central Universities[Grant number lzujbky_2017_it91]
文摘Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and shortcomings of urban expansion management strategies. A three-step method was applied to Yinchuan Plain in the northwestern of China, including(1)analyzing the relationship between landscape pattern and ecosystem service values through mathematical statistics;(2) predicting landscape pattern and ecosystem services change under different scenarios based on cellular automaton model(SLEUTH-3r model); and(3) designing and validating optimized scenario through integrating historical analysis experiments and future multi-comparison suggestions. Results have suggested that landscape composition and configuration can significantly affect regional ecosystem service values, especially the connectivity and shape of landscape. Compact urban growth policy and medium environment protection policy are the appropriate setting for urban expansion plan. Optimization validation of the combined designed scenario implied the reliability of this method. Our results highlighted the significance of integrating application of landscape pattern analysis, ecosystem service value evaluation,model simulation and multi-scenario prediction in urban planning.
基金the National Basic Research Program of China (973 Program) ( 2007CB407206)the National Key Technologies Research and Develop-ment Program in the Eleventh Five-Year Plan of China (2006BAC01A11)
文摘For ecological restoration and reconstruction of the degraded area, it is an important premise to correctly understand the degradation factors of the ecosystem in the arid-hot valleys. The factors including vegetation degradation, land degradation, arid climate, policy failure, forest fire, rapid population growth, excessive deforestation, overgrazing, steep slope reclamation, economic poverty, engineering construction, lithology, slope, low cultural level, geological hazards, biological disaster, soil properties etc, were selected to study the Yuanmou arid-hot valleys. Based on the interpretative structural model （ISM）, it has found out that the degradation factors of the Yuanmou arid-hot valleys were not at the same level but in a multilevel hierarchical system with internal relations, which pointed out that the degradation mode of the arid-hot valleys was ＂straight （appearance）-penetrating-background＂. Such researches have important directive significance for the restoration and reconstruction of the arid-hot valleys ecosystem.
文摘This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosys-tem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models are also introduced. To illustrate the application of the adjoint technique and its merits, a 4-variable ecosystem model coupled with a 3-D physical model is established for the Bohai Sea and the Yellow Sea. The chlorophyll concentration data derived from the SeaWiFS o-cean colour data are assimilated in the model with the technique. Some results are briefly presented.
基金supported by the National Natural Science Foundation of China(Nos.G49790010 and 40476045).
文摘Based on experiment data of the Sino-German comprehensive investigations in the Bohai Sea in 1998 and 1999, a simple coupled pelagic-benthic ecosystem multi-box model is used to simulate the ecosystem seasonal variation. The pelagic sub-model consists of seven state variables： phytoplankton, zooplankton, TIN, TIP, DOC, POC and dissolved oxygen （DO）. The benthic sub-model includes macro-benthos, meiobenthos, bacteria, detritus, TIN and TIP in the sediment. Besides the effects of solar radiation, water temperature and the nutrient from sea bottom exudation, land-based inputs are considered. The impact of the advection terms between the boxes is also considered. Meanwhile, the effects of the micro- bial-loop are introduced with a simple parameterization. The seasonal variations and the horizontal distributions of the ecosystem state variables of the Bohai Sea are simulated. Compared with the observations, the results of the multi-box model are reasonable. The modeled results show that about 13% of the photosynthesis primary production goes to the main food loop, 20% transfers to the benthic domain, 44% is consumed by the respiration of phytoplankton, and the rest goes to DOC. Model results also show the importance of the microbial food loop in the ecosystem of the Bohai Sea, and its contribution to the annual zooplankton production can be 60%-64%.
基金This research was funded by the National Natural Science Foundation of China(Grant Nos.31870426).
文摘Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.
文摘Some simplified dynamic models of grass field ecosystem are developed and investigated. The maximum simplified one consists of two variables, living grass biomass and soil wetness. The analyses of such models show that there exists only desert regime without grasses if the precipitation p is less than a critical value pc; the grass biomass continuously depends on p if the interaction between grass biomass and the soil wetness is weak, but the strong interaction results in the bifurcation of grass biomass in the vicinity of pc: the grass biomass is rich as p > pc, but it becomes desertification as p<pc. Periodic solutions also exist in the model, if the seasonal cycle of model's parameters is introduced. An improved model consists of three variables, i.e. the living grass biomass x, the nonliving grass biomass accumulated on the ground surface y and the soil wetness z. The behaviours of such three variables model are more complicated. The initial values of y and z play a very important role.
基金conducted as part of the project ‘‘Pilot site:quantification and modelling of forest carbon stocks in Benin’’ funded by the Global Climate Change Alliance and the European Union(No.00009 CILSS/SE/UAM-AFC/2013)
文摘Allometric equations developed for the Lama forest, located in southern Benin, West Africa, were applied to estimate carbon stocks of three vegetation types：undisturbed forest, degraded forest, and fallow. Carbon stock of the undisturbed forest was 2.7 times higher than that in the degraded forest and 3.4 times higher than that in fallow. The structure of the forest suggests that the individual species were generally concentrated in lower diameter classes. Carbon stock was positively correlated to basal area and negatively related to tree density, suggesting that trees in higher diameter classes contributed significantly to the total carbon stock. The study demonstrated that large trees constitute an important component to include in the sampling approach to achieve accurate carbon quantification in forestry. Historical emissions from deforestation that converted more than 30% of the Lama forest into cropland between the years 1946 and 1987 amounted to 260,563.17 tons of carbon per year（t CO2/year） for the biomass pool only. The study explained the application of biomass models and ground truth data to estimate reference carbon stock of forests.
基金supported by the National Natural Science Foundation of China(41875122)the Western Talents(2018XBYJRC004)+2 种基金the Guangdong Top Young Talents(2017TQ04Z359)the Introducing Talents to Western China Project of Chinese Academy of Sciences(Y932121)the Natural Science Foundation of Guangdong Province,China(2021A1515011429)。
文摘Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas.As the impacts of climate change and human disturbance intensify across time,uncertainties in both water resource supplies and demands increase in arid and semi-arid areas.Taking a typical arid region in China,Xinjiang Uygur Autonomous Region,as an example,water yield depth(WYD)and water utilization depth(WUD)from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model and socioeconomic data.The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference(WSDD)and water supply rate(WSR).The internal factors in changes of WYD and WUD were explored using the controlled variable method.The results show that the supplydemand relationships of water resources in Xinjiang were in a slight deficit,but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation.WYD generally experienced an increasing trend,and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin.WUD had a downward trend with a decline of 20.70%,especially in oasis areas.Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased.The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang,and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×10^(8)m^(3).This study analyzed water resource supplies and demands from a perspective of ecosystem services,which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation.The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.
基金Supported by the National Natural Science Foundation of China(Nos.41206111,41206112)
文摘Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization(PO), which is an important step in model calibration. An effi cient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the effi ciency of model calibration by analyzing and estimating the goodness-of-fi t of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confi dence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientifi c and normative technical framework for the improvement of MEDM skill.
