Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are establishe...Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.展开更多
Ecosystem health(EH)assessment is vital for understanding and improving the state of ecosystems.Analyzing the geographical and temporal evolution and predicting future EH trends under land-use changes deepens our unde...Ecosystem health(EH)assessment is vital for understanding and improving the state of ecosystems.Analyzing the geographical and temporal evolution and predicting future EH trends under land-use changes deepens our understanding of regional ecosystem dynamics.This method offers valuable insights for managing and sustaining ecosystems,highlighting the importance of incorporating land-use changes in EH assessments.In this study,the CA-Markov model is used to predict future vegetation and land use in 2030.Additionally,it utilizes the vigor–organization–resilience(VOR)framework to evaluate the current and future health of the Qinghai–Xizang Plateau(QXP)ecosystem.The analysis is based on vegetation and land-use data from 1980 to 2020.展开更多
Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and ...Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.展开更多
To understand the effects of grazing activities and climate change on sandy grassland ecosystems in northem China, a livestock field grazing and enclosure experiment was conducted from 1992 to 2006 in Horqin Sand Land...To understand the effects of grazing activities and climate change on sandy grassland ecosystems in northem China, a livestock field grazing and enclosure experiment was conducted from 1992 to 2006 in Horqin Sand Land, Inner Mongolia. The results showed that sustained heavy grazing resulted in serious degradation of the vegetation; moderate grazing can maintain vegetation stabilization; and light grazing can promote rapid restoration of degraded vegetation. The livestock productivity was the highest in the moderate grazing grassland, and sustained heavy grazing resulted in rapid decrease of the livestock productivity. Heavy grazing can cause a retrogressive succession of grassland vegetation, whereas moderate and light grazing may promote progressive succession of plant species. The effects of changing climate on succession processes were not significant in the short term; a warm-humid climate is favorable to restoration of degraded vegetation, whereas a sustained warm-drought climate may result in degradation of grassland vegetation. Heavy livestock grazing should be stopped for the sustainable use of grassland; the proper grazing intensity for sandy grassland is two to three sheep or sheep equivalents per hectare in Inner Mongolia.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
This paper is a further study of reference [1]. In this paper, we mainly discuss the complicated dynamical behaviors resulting from a simple one-dimensional model of nonlinear ecosystems: fixed point motion, periodic ...This paper is a further study of reference [1]. In this paper, we mainly discuss the complicated dynamical behaviors resulting from a simple one-dimensional model of nonlinear ecosystems: fixed point motion, periodic motion and chaotic motion etc., and briefly discuss the universality of the complicated dynamical behaviors, which can be described by the first and the second M. Feigenbaun. constants. At last, we discuss the 'one-side lowering phenomenon' due to near unstabilization when the nonlinear ecosystem approaches bifurcation points from unbifurcation side. It is of important theoretical and practical meanings both in the development and utilization of ecological resources ar.d in the design and management of artifilial ecosystems.展开更多
A nutrient-phytoplankton-zooplankton-detritus （NPZD） type of marine ecosystem model was developed in this study,and was further coupled to a three-dimensional primitive-equation ocean circulation model with a river ...A nutrient-phytoplankton-zooplankton-detritus （NPZD） type of marine ecosystem model was developed in this study,and was further coupled to a three-dimensional primitive-equation ocean circulation model with a river discharge model and a solar radiation model to reproduce the dynamics of the low nutrition level in the Bohai Sea （BS）.The simulation results were validated by observations and it was shown that the seasonal variation in the phytoplankton biomass could be characterized by the double-peak structure,corresponding to the spring and summer blooms,respectively.It was also found that both nitrogen and phosphate declined to the lowest level after the onset of the summer bloom,since the large amounts of nutrients were exhausted by phytoplankton for photosynthesis,and the concentrations of nutrients could resume in winter after a series of the biogeochemical-physical processes.By calculating the nitrogen/phosphorus （N/P） ratio,it is easy to see that the phytoplankton dynamics is nitrogen-limited as a whole in BS,though the phosphorus limitation may occur in the Yellow River （YR） Estuary where the input of riverine nitrogen is much more than that of phosphate.展开更多
Based on the simulation of a marine ecosystem dynamical model in the Bohai Sea, the Yellow Sea and the East China Sea, chlorophyll data are assimilated to study the spatially varying control parameters （CPs） by usin...Based on the simulation of a marine ecosystem dynamical model in the Bohai Sea, the Yellow Sea and the East China Sea, chlorophyll data are assimilated to study the spatially varying control parameters （CPs） by using the adjoint method. In this study, the CPs at some grid points are selected as the independent CPs, while the CPs at other grid points can be obtained through linear interpolation with the independent CPs. The independent CPs are uniformly selected from each 30′ × 30′area, and we confirm that the optimal influence radius is 1.2° by a twin experiment. In the following experiments, when only the maximum growth rate of phytoplankton （Vm） is estimated by two given types of spatially varying CPs, the mean relative errors of Vm are 1.22% and 0.94% while the decrease rates of the mean error of chlorophyll in the surface are 94.6% and 95.8%, respectively. When the other four CPs are estimated respectively, the results are also satisfactory, which indicates that the adjoint method has a strong ability of optimizing the prescribed CP with spatial variations. However, when all these five most important CPs are estimated simultaneously, the collocation of the changing trend of each parameter influences the estimation results remarkably. Only when the collocation of the changing trend of each parameter is consistent with the ecological mechanisms which influence the growth of the phytoplankton in marine ecosystem, could the five most important CPs be estimated more accurately.展开更多
The vegetation of the Caatinga, present in the dry areas of the Brazilian Semi-arid region has been little studied, when it relates to population dynamics of their species. The objective of this study was to evaluate ...The vegetation of the Caatinga, present in the dry areas of the Brazilian Semi-arid region has been little studied, when it relates to population dynamics of their species. The objective of this study was to evaluate the mortality and recruitment rates of a Croton blanchetianus Baill. population in a two-year interval (January/2013 to January/2015), in area of caatinga in the semi-arid Paraiba. Monitoring of structural changes in the vegetation was carried out in 96 10 × 10 m contiguous plots. The phytosociological survey conducted in January 2013 sampled 1078 individuals of C. blanchetianus, occurring in the 96 plots studied. The years of 2012 and 2013 had rainfall below the annual average. Take into consideration the evaluation period;there was a high mortality rate (M = 47.33% year-1) and a low recruitment rate (R = 0.18% year-1) for the population of C. blanchetianus. The real gain (RG) of the population was significantly negative (-93.91% year-1) since the number of dead individuals was much higher than the recruited ones in the population. The highest height class, composed of individuals of 4.1 to 5.0 m height, was the most tolerant to water scarcity, resulting in 53.85% of surviving individuals. Therefore, the results demonstrated that periodic droughts compromise the recruitment, development, survival, and establishment of individuals in natural systems in the Brazilian semi-arid region.展开更多
Mesozooplankton are critical components of marine ecosystems,acting as key intermediaries between primary producers and higher trophic levels by grazing on phytoplankton and influencing fish populations.They play pivo...Mesozooplankton are critical components of marine ecosystems,acting as key intermediaries between primary producers and higher trophic levels by grazing on phytoplankton and influencing fish populations.They play pivotal roles in the pelagic food web and export production,affecting the biogeochemical cycling of carbon and nutrients.Therefore,accurately modeling and visualizing mesozooplankton community dynamics is essential for understanding marine ecosystem patterns and informing effective management strategies.However,modeling these dynamics remains challenging due to the complex interplay among physical,chemical,and biological factors,and the detailed parameterization and feedback mechanisms are not fully understood in theory-driven models.Graph neural network(GNN)models offer a promising approach to forecast multivariate features and define correlations among input variables.The high interpretive power of GNNs provides deep insights into the structural relationships among variables,serving as a connection matrix in deep learning algorithms.However,there is insufficient understanding of how interactions between input variables affect model outputs during training.Here we investigate how the graph structure of ecosystem dynamics used to train GNN models affects their forecasting accuracy for mesozooplankton species.We find that forecasting accuracy is closely related to interactions within ecosystem dynamics.Notably,increasing the number of nodes does not always enhance model performance;closely connected species tend to produce similar forecasting outputs in terms of trend and peak timing.Therefore,we demonstrate that incorporating the graph structure of ecosystem dynamics can improve the accuracy of mesozooplankton modeling by providing influential information about species of interest.These findings will provide insights into the influential factors affecting mesozooplankton species and emphasize the importance of constructing appropriate graphs for forecasting these species.展开更多
A three-dimensional （3-D） coupled physical and biological model was used to investigate the physical processes and their influence on the ecosystem dynamics of the Bohai Sea of China. The physical processes include ...A three-dimensional （3-D） coupled physical and biological model was used to investigate the physical processes and their influence on the ecosystem dynamics of the Bohai Sea of China. The physical processes include M2 tide, time - varying wind forcing and river discharge. Wind records from 1 to 31 May in 1993 were selected to force the model. The biological model is based on a simple, nitrate and phosphate limited, lower trophic food web system. The simulated results showed that variation of residual currents forced by M2 tide, fiver discharge and time-varying wind had great impact on the distribution of phytoplankton biomass in the Laizhou Bay. High phytoplankton biomass appeared in the upwelling region. Numerical experiments based on the barotropic model and baroclinic model with no wind and water discharge were also conducted. Differences in the results by the baroclinic model and the barotropic model were significant： more patches appeared in the baroclinic model comparing with the barotropic model. And in the baroclinic model, the subsurface maximum phytoplankton biomass patches formed in the stratified water.展开更多
A three-dimension ecological dynamic model was established to numerically study the relationship of HAB and environmental conditions.The numerical experiments showed that the growth of diatom,the dominant HAB specie,w...A three-dimension ecological dynamic model was established to numerically study the relationship of HAB and environmental conditions.The numerical experiments showed that the growth of diatom,the dominant HAB specie,was mainly restricted by phosphate and silicate.If the concentrations of phosphate and silicate reach 17-25 μg/L and 300-375 μg/L respectively,the water is in a state of eutrophication.When phosphate and silicate up to 26-32 μg/L and 350-500 μg/L respectively,HAB could be induced.The major regions of HAB occurrence are Jiaozhou Bay mouth,coastal bays,and coastal area from Maidao to Shilaoren.To avoid HAB occurrence,concentration of phosphate and silicate should not exceed 17-20 μg/L and 300 μg/L as a whole.Reasonable control of pollutant discharge is a key point to prevent water eutrophication and HAB occurrence.展开更多
The climate,mainly the water availability and temperature,drives the renewal of biomass inseasonal forest ecosystem,and the greenness and leaf area of its canopy are responsive climate variations.This study verified ...The climate,mainly the water availability and temperature,drives the renewal of biomass inseasonal forest ecosystem,and the greenness and leaf area of its canopy are responsive climate variations.This study verified models to explain the phenomenon of leaf production and deciduousness by time,with LAI（Leaf Area Index）,NDVI（Normalized Difference VegetationIndex）and climate variables,on period 2011-2016. The data were obtained in satellite images and in plots installed at forestmonitoring sites,visited monthly.The analysis incorporated the water balance.Three equations were compared,two alreadypublished and the equation that was adjusted in this work.The model was improved and validated with new variables and data.It is possible to estimate the fall and renew of leaves biomass in semideciduous forests with reasonable precision.展开更多
Subject Code:D01With the support by the National Natural Science Foundation of China,a collaborative study by Prof.Wang Xinping(王新平)from the Northwest Institute of Eco-Environment and Resources,Chinese Academy of S...Subject Code:D01With the support by the National Natural Science Foundation of China,a collaborative study by Prof.Wang Xinping(王新平)from the Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences and the research group led by Prof.Ignacio Rodriguez-Iturbe from展开更多
Spartina alterniflora is ecologically important in its original habitat; however, it has caused controversy since it was introduction into China(now it has been spreading rapidly on the Jiangsu, Shanghai, Zhejiang and...Spartina alterniflora is ecologically important in its original habitat; however, it has caused controversy since it was introduction into China(now it has been spreading rapidly on the Jiangsu, Shanghai, Zhejiang and Fujian coasts). The purpose of the present contribution is, on the basis of an analysis and synthesis of existing data sets, to evaluate the environmental-ecological effects of S. alterniflora, and to identify the relevant scientific problems that require further research in the future. Investigations have shown that, by reducing the near-bed shear stress associated with tidal currents, S. alterniflora can enhance the settling flux of suspended sediment and deposition rate on the tidal flats over the region. Further, field survey and analysis indicate that the S. alterniflora salt-marsh has a high primary production and provides a new type of habitat for the native benthic fauna. Some macro-, meio- and micro-fauna that used to live in the native salt-marshes have adapted to the S. alterniflora salt-marsh, forming a new ecosystem. Under the influences of a number of background factors, such as latitude variations and the coastal type, the environmental-ecological changes induced by Spartine have regional differentiations. To the north of Hangzhou Bay, with a high position of the pre-Holocene stratum base, a large width of the tidal flats, and a gentle bed slope, only a small part of the intertidal zone is occupied by the S. alterniflora salt-marsh. Here, the S. alterniflora salt-marshes mainly play a positive role in coastal protection and ecosystem functioning. In contrary, to the South of Hangzhou Bay, The pre-Holocene deposits are situated in relatively deeo waters, and the width of the tidal flats formed within coastal embayments is relatively narrow. As such, the expansion of S. alterniflora has squeezed the living space of other intertidal organisms, thus has a negative ecological effect. Therefore, the regional differentiation of the Spartina effects should be sufficiently considered in coastal development and management. Furthermore, in order to predict the future evolution of the S. alterniflora wetlands over the region, in addition to in situ monitoring and measurements, an ecosystem dynamic model should be established, taking into account the coupling of the rerrestrial and marine environmental-ecological processes.展开更多
Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Det...Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Detection and Ranging),i.e.,Global Ecosystem Dynamics Investigation(GEDI),can map canopy height,but whether this observation reflects tree height composition remains untested.In this study,we firstly conduct numerical simulations to explore to what extent tree height composition can be obtained from GEDI waveform signals.We simulate waveforms for diverse forest scenarios using GEDI simulator coupled with LESS(LargE-Scale remote sensing data and image Simulation),a state-of-the-art radiative transfer model.We devise a minimalistic model,Tree generation based on Asymmetric generalized Gaussian(TAG),for customizing tree objects to accelerate forest scene creation.The results demonstrate that tree objects generated by TAG perform similarly in LiDAR simulation with objects from commercial 3-dimensional software.Results of simulated GEDI waveforms reasonably respond to the variation of crown architectures in even-aged forests.GEDI waveforms have an acceptable ability to identify different height layers within multi-layer forests,except for fir forests with a cone-shaped crown.The shape metric of waveforms reflects the height of each layer,while retrieval accuracy decreases with the increases in height variations within each layer.A 5-m interval between layers is the minimum requirement so that the different height layers can be separated.A mixture of different tree species reduces the retrieval accuracy of tree height layers.We also utilize real GEDI observations to retrieve tree heights in multi-height-layer forests.The findings indicate that GEDI waveforms are also efficient in identifying tree height composition in practical forest scenarios.Overall,results from this study demonstrate that GEDI waveforms can reflect the height composition within typical forest stands.展开更多
Global,fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss.The Group on Earth Observations Biodiversity Observation Network(GEO-BON)provided a...Global,fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss.The Group on Earth Observations Biodiversity Observation Network(GEO-BON)provided an expert-based definition of the biological properties that should be monitored,the Essential Biodiversity Variables(EBVs).Initiatives to provide indicators for EBVs rely on global,freely available remote sensing(RS)products in combination with empirical models and field data,and are invaluable for decision making.In this study,we provide alternatives for the expansion and improvement of the EBV indicators,by suggesting current and future data from the European Space Agencýs COPERNICUS and explore the potential of RS-integrated Dynamic Global Vegetation Models(DGVMs)for the estimation of EBVs.Our review found that mainly due to the inclusion of the Sentinel constellation,Copernicus products have similar or superior potential for EBV indicator estimation in relation to their NASA counterparts.DGVMs simulate the ecosystem level EBVs(ecosystem function and structure),and when integrated with remote sensing data have great potential to not only offer improved estimation of current states but to provide projection of ecosystem impacts.We suggest that focus on producing EBV relevant outputs should be a priority within the research community,to support biodiversity preservation efforts.展开更多
Terrestrial net primary production(NPP)is of fundamental importance to food security and ecosystem sustainability.However,little is known about how terrestrial NPP in African ecosystems has responded to recent changes...Terrestrial net primary production(NPP)is of fundamental importance to food security and ecosystem sustainability.However,little is known about how terrestrial NPP in African ecosystems has responded to recent changes in climate and other environmental factors.Here,we used an integrated ecosystem model(the dynamic land ecosystem model;DLEM)to simulate the dynamic variations in terrestrial NPP of African ecosystems driven by climate and other environmental factors during 1980-2009.We estimate a terrestrial NPP of 10.22(minimum-maximum range of 8.9-11.3)Pg C/yr during the study period.Our results show that precipitation variability had a significant effect on terrestrial NPP,explaining 74%of interannual variations in NPP.Over the 30-yr period,African ecosystems experienced an increase in NPP of 0.03 Pg C/yr,resulting from the combined effects of climate variability,elevated atmospheric CO_(2)concentration,and nitrogen deposition.Our further analyses show that there is a difference in NPP of 1.6 Pg C/yr between wet and dry years,indicating that interannual climatic variations play an important role in determining the magnitude of terrestrial NPP.Central Africa,dominated by tropical forests,was the most productive region and accounted for 50%of the carbon sequestered as NPP in Africa.Our results indicate that warmer and wetter climatic conditions,together with elevated atmospheric CO_(2)concentration and nitrogen deposition,have resulted in a significant increase in African terrestrial NPP during 1980-2009,with the largest contribution from tropical forests.展开更多
基金Supported by the National Basic Research Program of China (973 Program) (No. 2010CB428703)Oceanic Science Fund for Young Scholar of SOA (Nos. 2010225, 2010118)+1 种基金Public Science and Technology Research Funds Projects of Ocean of China (Nos. 201005008, 201005009)Open Fund of MOIDAT (No. 201011)
文摘Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.
基金supported by the Second TP Scientific Expedition and Research Program(STEP)(grant number 2019QZKK0608)
文摘Ecosystem health(EH)assessment is vital for understanding and improving the state of ecosystems.Analyzing the geographical and temporal evolution and predicting future EH trends under land-use changes deepens our understanding of regional ecosystem dynamics.This method offers valuable insights for managing and sustaining ecosystems,highlighting the importance of incorporating land-use changes in EH assessments.In this study,the CA-Markov model is used to predict future vegetation and land use in 2030.Additionally,it utilizes the vigor–organization–resilience(VOR)framework to evaluate the current and future health of the Qinghai–Xizang Plateau(QXP)ecosystem.The analysis is based on vegetation and land-use data from 1980 to 2020.
基金funded by the National Key Research and Development Program(Grants No.2023YFE0207900)。
文摘Accurate reconstruction of understory terrain is essential for environmental monitoring and resource management.This study integrates 1:10,000 Digital Elevation Model,Global Ecosystem Dynamics Investigation(GEDI),and AW3D30 Digital Surface Model data,combined with three machine learning algorithms—Random Forest(RF),Back Propagation Neural Network(BPNN),and Extreme Gradient Boosting(XGBoost)—to evaluate the performance of canopy height inversion and understory terrain reconstruction.The analysis emphasizes the impact of topographic and vegetation-related factors on model accuracy.Results reveal that slope is the most influential variable,contributing three to five times more to model performance than other features.In low-slope areas,understory terrain tends to be underestimated,whereas high-slope areas often result in overestimation.Moreover,the Normalized Difference Vegetation Index(NDVI)and land cover types,particularly forests and grasslands,significantly affect prediction accuracy,with model performance showing heightened sensitivity to vegetation characteristics in these regions.Among the models tested,XGBoost demonstrated superior performance,achieving a canopy height bias of-0.06 m,a root mean square error(RMSE)of 4.69 m for canopy height,and an RMSE of 9.82 m for understory terrain.Its ability to capture complex nonlinear relationships and handle high-dimensional data underlines its robustness.While the RF model exhibited strong stability and resistance to noise,its accuracy lagged slightly behind XGBoost.The BPNN model,by contrast,struggled in areas with complex terrain.This study offers valuable insights into feature selection and optimization in remote sensing applications,providing a reference framework for enhancing the accuracy and efficiency of environmental monitoring practices.
基金funded by a Chinese National Key Project for Basic Scientific Research (2009CB421303)a Chinese National Fund Project (30972422)
文摘To understand the effects of grazing activities and climate change on sandy grassland ecosystems in northem China, a livestock field grazing and enclosure experiment was conducted from 1992 to 2006 in Horqin Sand Land, Inner Mongolia. The results showed that sustained heavy grazing resulted in serious degradation of the vegetation; moderate grazing can maintain vegetation stabilization; and light grazing can promote rapid restoration of degraded vegetation. The livestock productivity was the highest in the moderate grazing grassland, and sustained heavy grazing resulted in rapid decrease of the livestock productivity. Heavy grazing can cause a retrogressive succession of grassland vegetation, whereas moderate and light grazing may promote progressive succession of plant species. The effects of changing climate on succession processes were not significant in the short term; a warm-humid climate is favorable to restoration of degraded vegetation, whereas a sustained warm-drought climate may result in degradation of grassland vegetation. Heavy livestock grazing should be stopped for the sustainable use of grassland; the proper grazing intensity for sandy grassland is two to three sheep or sheep equivalents per hectare in Inner Mongolia.
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.
基金Supported by the Youth Science Fundation of Chinese Academia SinicaYouth Fundation of Lanzhou Unviersity
文摘This paper is a further study of reference [1]. In this paper, we mainly discuss the complicated dynamical behaviors resulting from a simple one-dimensional model of nonlinear ecosystems: fixed point motion, periodic motion and chaotic motion etc., and briefly discuss the universality of the complicated dynamical behaviors, which can be described by the first and the second M. Feigenbaun. constants. At last, we discuss the 'one-side lowering phenomenon' due to near unstabilization when the nonlinear ecosystem approaches bifurcation points from unbifurcation side. It is of important theoretical and practical meanings both in the development and utilization of ecological resources ar.d in the design and management of artifilial ecosystems.
基金supported by Key Subject Fund of Shanghai Education Committee (No. J50702)Open Foundation of the Key Subject in Environmental Engineering of Shanghai Ocean University(No. B820609000404)Initial Foundation for Ph. D. of ShanghaiOcean University (No. B820607000402)
文摘A nutrient-phytoplankton-zooplankton-detritus （NPZD） type of marine ecosystem model was developed in this study,and was further coupled to a three-dimensional primitive-equation ocean circulation model with a river discharge model and a solar radiation model to reproduce the dynamics of the low nutrition level in the Bohai Sea （BS）.The simulation results were validated by observations and it was shown that the seasonal variation in the phytoplankton biomass could be characterized by the double-peak structure,corresponding to the spring and summer blooms,respectively.It was also found that both nitrogen and phosphate declined to the lowest level after the onset of the summer bloom,since the large amounts of nutrients were exhausted by phytoplankton for photosynthesis,and the concentrations of nutrients could resume in winter after a series of the biogeochemical-physical processes.By calculating the nitrogen/phosphorus （N/P） ratio,it is easy to see that the phytoplankton dynamics is nitrogen-limited as a whole in BS,though the phosphorus limitation may occur in the Yellow River （YR） Estuary where the input of riverine nitrogen is much more than that of phosphate.
基金The State Ministry of Science and Technology of China under contract No. 2007AA09Z118the National Natural Science Foundation of China under contract No. 41076006the Ministry of Education’s 111 Project under contract No. B07036
文摘Based on the simulation of a marine ecosystem dynamical model in the Bohai Sea, the Yellow Sea and the East China Sea, chlorophyll data are assimilated to study the spatially varying control parameters （CPs） by using the adjoint method. In this study, the CPs at some grid points are selected as the independent CPs, while the CPs at other grid points can be obtained through linear interpolation with the independent CPs. The independent CPs are uniformly selected from each 30′ × 30′area, and we confirm that the optimal influence radius is 1.2° by a twin experiment. In the following experiments, when only the maximum growth rate of phytoplankton （Vm） is estimated by two given types of spatially varying CPs, the mean relative errors of Vm are 1.22% and 0.94% while the decrease rates of the mean error of chlorophyll in the surface are 94.6% and 95.8%, respectively. When the other four CPs are estimated respectively, the results are also satisfactory, which indicates that the adjoint method has a strong ability of optimizing the prescribed CP with spatial variations. However, when all these five most important CPs are estimated simultaneously, the collocation of the changing trend of each parameter influences the estimation results remarkably. Only when the collocation of the changing trend of each parameter is consistent with the ecological mechanisms which influence the growth of the phytoplankton in marine ecosystem, could the five most important CPs be estimated more accurately.
文摘The vegetation of the Caatinga, present in the dry areas of the Brazilian Semi-arid region has been little studied, when it relates to population dynamics of their species. The objective of this study was to evaluate the mortality and recruitment rates of a Croton blanchetianus Baill. population in a two-year interval (January/2013 to January/2015), in area of caatinga in the semi-arid Paraiba. Monitoring of structural changes in the vegetation was carried out in 96 10 × 10 m contiguous plots. The phytosociological survey conducted in January 2013 sampled 1078 individuals of C. blanchetianus, occurring in the 96 plots studied. The years of 2012 and 2013 had rainfall below the annual average. Take into consideration the evaluation period;there was a high mortality rate (M = 47.33% year-1) and a low recruitment rate (R = 0.18% year-1) for the population of C. blanchetianus. The real gain (RG) of the population was significantly negative (-93.91% year-1) since the number of dead individuals was much higher than the recruited ones in the population. The highest height class, composed of individuals of 4.1 to 5.0 m height, was the most tolerant to water scarcity, resulting in 53.85% of surviving individuals. Therefore, the results demonstrated that periodic droughts compromise the recruitment, development, survival, and establishment of individuals in natural systems in the Brazilian semi-arid region.
基金supported by the Ministry of Science and ICT(MSIT)through a Sejong Science Fellowship funded by the National Research Foundation of Korea(NRF)(No.2022R1C1C2003649).
文摘Mesozooplankton are critical components of marine ecosystems,acting as key intermediaries between primary producers and higher trophic levels by grazing on phytoplankton and influencing fish populations.They play pivotal roles in the pelagic food web and export production,affecting the biogeochemical cycling of carbon and nutrients.Therefore,accurately modeling and visualizing mesozooplankton community dynamics is essential for understanding marine ecosystem patterns and informing effective management strategies.However,modeling these dynamics remains challenging due to the complex interplay among physical,chemical,and biological factors,and the detailed parameterization and feedback mechanisms are not fully understood in theory-driven models.Graph neural network(GNN)models offer a promising approach to forecast multivariate features and define correlations among input variables.The high interpretive power of GNNs provides deep insights into the structural relationships among variables,serving as a connection matrix in deep learning algorithms.However,there is insufficient understanding of how interactions between input variables affect model outputs during training.Here we investigate how the graph structure of ecosystem dynamics used to train GNN models affects their forecasting accuracy for mesozooplankton species.We find that forecasting accuracy is closely related to interactions within ecosystem dynamics.Notably,increasing the number of nodes does not always enhance model performance;closely connected species tend to produce similar forecasting outputs in terms of trend and peak timing.Therefore,we demonstrate that incorporating the graph structure of ecosystem dynamics can improve the accuracy of mesozooplankton modeling by providing influential information about species of interest.These findings will provide insights into the influential factors affecting mesozooplankton species and emphasize the importance of constructing appropriate graphs for forecasting these species.
基金This work was supported by the National Natural Science Foundation of China under contract Nos 40531006 and 40376039； LOPSO Open Fund of the Second Institute of Oceanography of State Oceanic Administration；Part of the work was conducted at the Marine Department of University of Georgia USA.
文摘A three-dimensional （3-D） coupled physical and biological model was used to investigate the physical processes and their influence on the ecosystem dynamics of the Bohai Sea of China. The physical processes include M2 tide, time - varying wind forcing and river discharge. Wind records from 1 to 31 May in 1993 were selected to force the model. The biological model is based on a simple, nitrate and phosphate limited, lower trophic food web system. The simulated results showed that variation of residual currents forced by M2 tide, fiver discharge and time-varying wind had great impact on the distribution of phytoplankton biomass in the Laizhou Bay. High phytoplankton biomass appeared in the upwelling region. Numerical experiments based on the barotropic model and baroclinic model with no wind and water discharge were also conducted. Differences in the results by the baroclinic model and the barotropic model were significant： more patches appeared in the baroclinic model comparing with the barotropic model. And in the baroclinic model, the subsurface maximum phytoplankton biomass patches formed in the stratified water.
基金The Qingdao Ocean and Fishery Office funded project-HAB prewarning of Qingdao Olympics sailing field under contract No. HB2007002
文摘A three-dimension ecological dynamic model was established to numerically study the relationship of HAB and environmental conditions.The numerical experiments showed that the growth of diatom,the dominant HAB specie,was mainly restricted by phosphate and silicate.If the concentrations of phosphate and silicate reach 17-25 μg/L and 300-375 μg/L respectively,the water is in a state of eutrophication.When phosphate and silicate up to 26-32 μg/L and 350-500 μg/L respectively,HAB could be induced.The major regions of HAB occurrence are Jiaozhou Bay mouth,coastal bays,and coastal area from Maidao to Shilaoren.To avoid HAB occurrence,concentration of phosphate and silicate should not exceed 17-20 μg/L and 300 μg/L as a whole.Reasonable control of pollutant discharge is a key point to prevent water eutrophication and HAB occurrence.
文摘The climate,mainly the water availability and temperature,drives the renewal of biomass inseasonal forest ecosystem,and the greenness and leaf area of its canopy are responsive climate variations.This study verified models to explain the phenomenon of leaf production and deciduousness by time,with LAI（Leaf Area Index）,NDVI（Normalized Difference VegetationIndex）and climate variables,on period 2011-2016. The data were obtained in satellite images and in plots installed at forestmonitoring sites,visited monthly.The analysis incorporated the water balance.Three equations were compared,two alreadypublished and the equation that was adjusted in this work.The model was improved and validated with new variables and data.It is possible to estimate the fall and renew of leaves biomass in semideciduous forests with reasonable precision.
文摘Subject Code:D01With the support by the National Natural Science Foundation of China,a collaborative study by Prof.Wang Xinping(王新平)from the Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences and the research group led by Prof.Ignacio Rodriguez-Iturbe from
基金supported financially by the Basic Research Project in Jiangsu Province (Grant No. SBK2011012)an National Natural Science Foundation of China (Grant No. 40476041)
文摘Spartina alterniflora is ecologically important in its original habitat; however, it has caused controversy since it was introduction into China(now it has been spreading rapidly on the Jiangsu, Shanghai, Zhejiang and Fujian coasts). The purpose of the present contribution is, on the basis of an analysis and synthesis of existing data sets, to evaluate the environmental-ecological effects of S. alterniflora, and to identify the relevant scientific problems that require further research in the future. Investigations have shown that, by reducing the near-bed shear stress associated with tidal currents, S. alterniflora can enhance the settling flux of suspended sediment and deposition rate on the tidal flats over the region. Further, field survey and analysis indicate that the S. alterniflora salt-marsh has a high primary production and provides a new type of habitat for the native benthic fauna. Some macro-, meio- and micro-fauna that used to live in the native salt-marshes have adapted to the S. alterniflora salt-marsh, forming a new ecosystem. Under the influences of a number of background factors, such as latitude variations and the coastal type, the environmental-ecological changes induced by Spartine have regional differentiations. To the north of Hangzhou Bay, with a high position of the pre-Holocene stratum base, a large width of the tidal flats, and a gentle bed slope, only a small part of the intertidal zone is occupied by the S. alterniflora salt-marsh. Here, the S. alterniflora salt-marshes mainly play a positive role in coastal protection and ecosystem functioning. In contrary, to the South of Hangzhou Bay, The pre-Holocene deposits are situated in relatively deeo waters, and the width of the tidal flats formed within coastal embayments is relatively narrow. As such, the expansion of S. alterniflora has squeezed the living space of other intertidal organisms, thus has a negative ecological effect. Therefore, the regional differentiation of the Spartina effects should be sufficiently considered in coastal development and management. Furthermore, in order to predict the future evolution of the S. alterniflora wetlands over the region, in addition to in situ monitoring and measurements, an ecosystem dynamic model should be established, taking into account the coupling of the rerrestrial and marine environmental-ecological processes.
基金supported by the National Science Foun-dation of China(42141005)supported by the High-performance Computing Platform of Peking University.
文摘Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Detection and Ranging),i.e.,Global Ecosystem Dynamics Investigation(GEDI),can map canopy height,but whether this observation reflects tree height composition remains untested.In this study,we firstly conduct numerical simulations to explore to what extent tree height composition can be obtained from GEDI waveform signals.We simulate waveforms for diverse forest scenarios using GEDI simulator coupled with LESS(LargE-Scale remote sensing data and image Simulation),a state-of-the-art radiative transfer model.We devise a minimalistic model,Tree generation based on Asymmetric generalized Gaussian(TAG),for customizing tree objects to accelerate forest scene creation.The results demonstrate that tree objects generated by TAG perform similarly in LiDAR simulation with objects from commercial 3-dimensional software.Results of simulated GEDI waveforms reasonably respond to the variation of crown architectures in even-aged forests.GEDI waveforms have an acceptable ability to identify different height layers within multi-layer forests,except for fir forests with a cone-shaped crown.The shape metric of waveforms reflects the height of each layer,while retrieval accuracy decreases with the increases in height variations within each layer.A 5-m interval between layers is the minimum requirement so that the different height layers can be separated.A mixture of different tree species reduces the retrieval accuracy of tree height layers.We also utilize real GEDI observations to retrieve tree heights in multi-height-layer forests.The findings indicate that GEDI waveforms are also efficient in identifying tree height composition in practical forest scenarios.Overall,results from this study demonstrate that GEDI waveforms can reflect the height composition within typical forest stands.
基金The authors would like to acknowledge the European Commission‘Horizon 2020 Program’that funded ERA-PLANET/GEOEssential(Grant Agreement no.689443)project.H2020 Societal Challenges.
文摘Global,fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss.The Group on Earth Observations Biodiversity Observation Network(GEO-BON)provided an expert-based definition of the biological properties that should be monitored,the Essential Biodiversity Variables(EBVs).Initiatives to provide indicators for EBVs rely on global,freely available remote sensing(RS)products in combination with empirical models and field data,and are invaluable for decision making.In this study,we provide alternatives for the expansion and improvement of the EBV indicators,by suggesting current and future data from the European Space Agencýs COPERNICUS and explore the potential of RS-integrated Dynamic Global Vegetation Models(DGVMs)for the estimation of EBVs.Our review found that mainly due to the inclusion of the Sentinel constellation,Copernicus products have similar or superior potential for EBV indicator estimation in relation to their NASA counterparts.DGVMs simulate the ecosystem level EBVs(ecosystem function and structure),and when integrated with remote sensing data have great potential to not only offer improved estimation of current states but to provide projection of ecosystem impacts.We suggest that focus on producing EBV relevant outputs should be a priority within the research community,to support biodiversity preservation efforts.
基金This study was partially supported by NSF Decadal and Regional Climate Prediction using Earth System Models(AGS-1243220).
文摘Terrestrial net primary production(NPP)is of fundamental importance to food security and ecosystem sustainability.However,little is known about how terrestrial NPP in African ecosystems has responded to recent changes in climate and other environmental factors.Here,we used an integrated ecosystem model(the dynamic land ecosystem model;DLEM)to simulate the dynamic variations in terrestrial NPP of African ecosystems driven by climate and other environmental factors during 1980-2009.We estimate a terrestrial NPP of 10.22(minimum-maximum range of 8.9-11.3)Pg C/yr during the study period.Our results show that precipitation variability had a significant effect on terrestrial NPP,explaining 74%of interannual variations in NPP.Over the 30-yr period,African ecosystems experienced an increase in NPP of 0.03 Pg C/yr,resulting from the combined effects of climate variability,elevated atmospheric CO_(2)concentration,and nitrogen deposition.Our further analyses show that there is a difference in NPP of 1.6 Pg C/yr between wet and dry years,indicating that interannual climatic variations play an important role in determining the magnitude of terrestrial NPP.Central Africa,dominated by tropical forests,was the most productive region and accounted for 50%of the carbon sequestered as NPP in Africa.Our results indicate that warmer and wetter climatic conditions,together with elevated atmospheric CO_(2)concentration and nitrogen deposition,have resulted in a significant increase in African terrestrial NPP during 1980-2009,with the largest contribution from tropical forests.
