Dynamic phosphorus budget for lake-watershed ecosystems

Lake eutrophication caused by excess phosphorus （P） loading from point sources （PS） and nonpoint sources （NPS） is a persistent and serious ecological problem in China. A phosphorus budget, based on material flow analysis（MFA） and system dynamic （SD）, is proposed and applied for the agriculture-dominated Qionghai Lake watershed located in southwestern China. The MFA-SD approach will not only cover the transporting process of P in the lake-watershed ecosystems, but also can deal with the changes of P budget due to the dynamics of watershed. P inflows include the fertilizer for agricultural croplands, soil losses, domestic sewage discharges, and the atmospheric disposition such as precipitation and dust sinking. Outflows are consisted of hydrologic export, water resources development, fishery and aquatic plants harvesting. The internal P recycling processes are also considered in this paper. From 1988 to 2015, the total P inflows for Lake Qionghai are in a rapid increase from 35.65 to 78.73 t/a, which results in the rising of P concentration in the lake. Among the total P load 2015, agricultural loss and domestic sewage account for 70.60% and 17.27% respectively, directly related to the rapid social-economic development and the swift urbanization. Future management programs designed to reduce P inputs must be put into practices in the coming years to ensure the ecosystem health in the watershed.

Falls Lake水库内溶解物输运模拟

溶解物在水库内的输运过程受人为因素影响较大。为研究水库内物质输运的过程和机制,以美国北卡罗来纳州的Falls Lake水库为研究对象,运用EFDC三维数值模型对物质在水库内的输运过程进行模拟研究,分析示踪物平均年龄和滞留时间的分布以及变化。结果显示:理想状态下,流量决定溶解物的输运过程;实际情况中,除流量外,水库的即时蓄水量是影响输运过程的另一个重要因素;水库结构和径流分布是导致示踪物在各区域局地滞留时间存在差异的主要因素。

Sedimentary dynamics and depositional model for mud accumulation in deep lake basins:A case study in the Upper Triassic Chang-7 Member,Ordos Basin,northern China

Shales in deep lake basins have become the main focus of continental shale oil and gas exploration.In order to highlight the sedimentary dynamics of mud deposition in deep lake basins,a combination of core observation,thin section examination,X-ray diffraction,and QEMSCAN(quantitative evaluation of minerals by scanning electron microscopy)was used to analyze the depositional characteristics of mudrocks in the Chang-7 Member from the Yanchang Formation(Upper Triassic)in Ordos Basin,and to establish a depositional model for mud accumulation in deep lake basins.This study recognizes four mudrock lithofacies in the Chang-7 Member:(1)the laminated silt-bearing mudstone,which generally develops a binary composition of“silt-clay”or a ternary composition of“silt-clay-organic matter”;(2)the graded mudstone,mainly composed of dark gray and gray-black mudstone sandwiched by silt-bearing mudstone;(3)the massive mudstone,internally showing a uniform distribution of quartz,clay,and carbonate minerals,with also a small amount of organic detritus;and(4)the laminated shale,which is generally composed of clay laminae,and organic laminae of the former two.Sediment supply,topographic slope,and flood intensity combine to control the evolution of gravity flows and the transport and deposition of the mudrock in the Chang-7 Member.The influence of orogeny provides terrain gradient,water depth,abundant sediments at source areas,and triggering mechanism for the formation of gravity flows.Floods triggered by wetting events provide the impetus for sediment transport.Mud deposition in the Chang-7 Member was mainly related to the transport and sedimentation of mud by hyperpycnal flows and rapid sedimentation by buoyant plume flocculation.A comprehensive evolutionary model for shale accumulation in the deep lake basin is established by integrating various triggering mechanisms and mud transport sedimentary processes.

History, development and characteristics of lake ecological models

This paper provides some introductory information on the history, development, and characteristics of various lake ecosystem models. The modeling of lake ecological processes began to gain importance in the early 1960s. There are a number of models available today, with varying levels of complexity to cope with the variety of environmental problems found in lake environments, e.g. eutrophication, acidification, oxygen depletion, wetland management, heavy metal and pesticide pollution, as well as hydrodynamic problems. In particular, this paper focuses on lake eutrophication and wetland models, as well as addressing strategies appropriate for the design and development of reliable lake ecological models.

Towards a Modeling of the Impacts of Road Verge Management on the Pollination Service Using System Dynamics: A Case Study in France

Several research studies have proven that eliciting and predicting the impact of human activity on ecosystem services will be crucial to support stakeholders’ awareness and to decide how to interact with the environment in a more sustainable manner. In this sense, the ecosystems known as road verges are particularly important because of their length and surface at an international scale, and their role in mitigating the damage done by roads. Plant pollination by insects is one of the most important ecosystem services. Because of its nature and the fact that they extend across a variety of landscapes, roadside can contribute to the maintenance of healthy ecosystems, under the condition of adapted management practices. This research is the first attempt to develop a System Dynamics-based aiming to estimate the ecological and economic impact of maintenance on the road verge pollination service in France. Maintenance strategies of road verges are simulated to compare their performance. The results show that there are ways to improve current maintenance strategies in terms of pollination value, but also that the model needs to consider other ecosystem services and synergistic effects that could further affect pollination to obtain more accurate estimations.

A statistical dynamics model of the marine ecosystem and its application in Jiaozhou Bay

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.

Evaluating innovation ecosystem resiliency using agent-based modeling and systems dynamics

Evaluating the resilience of the innovation ecosystem to maintain its performance,in the sense of resistance to disruption and recovery after it,has recently received more attention.Several studies have been conducted to model different ecosystems and evaluate their resilience.However,modeling the innovation ecosystem from a holistic perspective and performing a quantitative assessment of its resilience have received less attention.This paper models the innovation ecosystem holistically and evaluates its resilience index using a quantitative approach through five main steps.In the first step,a case study related to the innovation ecosystem of Iran's Ministry of Energy,called the Power Innovation Ecosystem,is modeled by combining system dynamics and agent-based modeling.Upon validating the model in the second step,the disruption of the loss of experts is investigated in the third step,and all possible actions to recover each actor are analyzed.In the fourth step,the performance of the ecosystem is simulated before and after the disruption using the data gathered in the previous steps.Finally,resilience is calculated in two different ways in the fifth step.Several improvement solutions are also suggested when considering that the resilience index of the innovation ecosystem is at a medium level.This research may assist policymakers in observing the resilience level of the innovation ecosystem based on the proposed model.By applying strategic changes to this model,they can determine the effects of their policies and make the most appropriate decisions to increase the resilience of the innovation ecosystem.

Modeling dynamic assessment of ecosystem services based on remote sensing technology:A sampling of the Gansu grassland ecosystem

The ecosystem is important because it is the life sustaining system for human survival.Three ecosystem characteristics are:regional particularities,ecosystem complexity and conventional cultural particularities.This paper develops a remote sensing based dynamic model to assess grassland ecosystem service values involving multidisciplinary knowledge.The ecological value of grassland ecosystems is focused on using a remote sensing technique in the model,and setting up the framework for a dynamic assessing model.The grassland ecological services condition and value in 1985 is used as the benchmark.The dynamic model has two adjusting indicators:biomass and price index.The biomass is simulated using the CASA(Carnegie-Ames-Stanford Approach) model.The price index was obtained from statistics data published by the statistical bureau.Results show that the grassland ecosystem value in Gansu Province was 28.36 billion Chinese Yuan in 1985,140.37 billion in 1999 and 130.86 billion in 2002.

创新生态系统不确定性条件下后发企业何以实现颠覆性创新——基于SOR模型的动态能力中介作用

创新生态系统被视为培养颠覆性创新的沃土,其日益增加的不确定性为后发企业提供了实现颠覆性创新的机会窗口。将动态能力细分为认知性动态能力与非认知性动态能力两个维度,利用SOR模型构建“条件刺激—能力构建—颠覆行为”的理论框架,试图打开创新生态系统不确定性条件下后发企业实现颠覆性创新的“黑箱”。基于创新生态系统中376份后发企业的样本数据,研究发现:①创新生态系统不确定性不仅对颠覆性创新有显著正向影响,而且对认知性动态能力和非认知性动态能力也有显著正向影响;②认知性动态能力与非认知性动态能力对颠覆性创新有显著正向影响,并且分别在创新生态系统不确定性与颠覆性创新关系中起部分中介作用;③创新生态系统开放度能够正向调节创新生态系统不确定性与认知性动态能力关系。研究有助于指导面对不确定性的后发企业实现“弯道超车”,并且为创新生态系统突破创新迟滞困境提供新思路。

Improving the accuracy of precipitation estimates in a typical inland arid area of China using a dynamic Bayesian model averaging approach

Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.

Influence of Human Activity Intensity on Habitat Quality in Hainan Tropical Rainforest National Park,China

Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.

湖泊细菌群落构建机制及其对富营养化的响应

细菌是湖泊生态系统的重要组成部分,在驱动湖泊生态系统元素物质循环和调控湖泊水质方面发挥关键性作用。揭示湖泊细菌群落多样性的形成和维持机制,即群落构建机制,是湖泊微生物生态学研究中的核心目标。近年来,微生物组学技术的发展,极大推动了湖泊细菌群落构建机制的研究。富营养化是当前我国湖泊生态系统面临的最大环境挑战之一,也是决定湖泊细菌群落组成和多样性的重要因素。研究综述了湖泊细菌群落构建机制的理论基础和发展脉络。概述了湖泊细菌群落构建机制的主要分析方法。总结了富营养化对湖泊细菌群落构建机制的影响的最新研究进展。针对富营养化影响下湖泊细菌群落构建机制研究所面临的问题,提出了未来的研究展望。

鄱阳湖水利枢纽对江湖洪期水动力过程的影响

鄱阳湖作为通江湖泊,其洪水大小由多因素共同决定,湖区洪灾频繁。鄱阳湖水利枢纽工程建设后将对洪期复杂水动力过程造成影响。为评估其影响,建立了包括鄱阳湖湖区和尾闾以及长江九江到八里江段在内的平面二维水动力模型,对1954年大洪水和1991年倒灌2种灾害型洪期过程进行情景模拟,分析了枢纽对长江和湖区可能造成的影响。结果表明:枢纽工程使湖口出流过程更加平缓,具有一定的削峰作用,对长江洪水位基本无影响;1954年大洪水过程,枢纽使湖区水位升高,代表水文站水位壅高最大值为0.021 m;1991年倒灌过程,枢纽使湖区水位降低,湖区水位变化的趋势与湖口流量变化趋势一致,相位稍滞后于流量过程。研究成果可为江湖水安全管理提供技术支撑。

基于服务簇的沱江流域生态系统服务权衡/协同关系演变

明确流域生态系统服务簇的时空格局以及簇内生态系统服务动态权衡/协同关系对管理和维持流域生态系统结构与功能的稳定性和可持续性有重要意义。基于InVEST模型、土壤流失方程等方法估算2010、2015、2020年3期沱江流域生态系统服务,并使用K-means聚类识别生态系统服务簇,以服务簇视角衡量服务簇内部主要生态系统服务间动态权衡/协同关系,讨论权衡/协同关系及服务簇的时空变化规律,针对不同簇模式提出相应的分区管控建议。结果表明:(1)2010—2020年沱江流域各生态系统服务空间格局稳定,生态系统服务变化各异。生境质量、产水、固碳服务总量上升,粮食生产、水土保持服务总量下降。固碳、水土保持以及生境质量服务高值区表现为在北部及中北部集中分布,产水服务量由南向北减小,粮食生产服务高值区主要集中于流域中北部和南部耕地区,文化娱乐服务高值区呈现出显著的城市及城市间网络状连接趋势。(2)根据聚类结果将流域划分为5种生态系统服务簇,各簇存在时空异质性。粮食生产簇占比为72.9%,以粮食生产、产水服务为主;生态保育簇占比为15.2%,以生境质量、固碳服务为主;文化娱乐簇占比为6.9%,以文化娱乐服务为主;多功能耦合簇占比为4.4%,以生境质量、固碳、水土保持服务为主;水土保持簇占比为0.5%,以水土保持服务为主。(3)宏观而言,沱江流域整体权衡关系多于协同关系,服务簇内部各服务协同关系多于权衡关系,应因地制宜采取管控措施。不同生态系统服务簇内部各服务权衡/协同关系存在相似与差异性,不同服务簇内各相同服务组合的权衡/协同关系强弱不同,服务簇内部各服务协同关系多于权衡关系,流域整体权衡关系多于协同关系。研究成果可为沱江流域区域未来生态系统管理与优化、生态文明建设及可持续性发展提供科学依据。

长江下游河湖水系连通的生态效应与联合调度

现行的水系连通工程规划和实施普遍侧重于水资源调度、防洪抗旱和航运畅通等需求,对连通河湖水生态环境质量的影响机制和协同管理措施仍不明确。引江济太等水系连通工程在恢复长江下游水系连通性的同时,会引起河湖水位、水动力、水沙输移、水质等要素变化,促使水体和底质生境条件改变,导致河湖关键生物种群、生态系统结构及“清水草型”/“浊水藻型”生态类型动态演替,从而深刻影响河湖生态环境。在梳理河湖水系连通联合调度方法的基础上,提出开展长江下游河湖水系连通工程的科学调控,需将水文水动力联动、生境条件变化、生态系统响应、水系连通动态调控有机结合起来,系统分析水系连通下相连河湖的生态响应机理,建立水动力-水质-水生态耦合模型进行仿真模拟,提出保障防洪安全、生态流量、循环畅通的多目标联合调度方案,充分发挥其在水网建设、河湖生态环境复苏等方面的成效。

基于PLUS-InVEST模型的“两湖一库”流域水质净化时空演变

探讨土地利用变化所引发的水质净化演变,对于保护和改善水质,实现可持续发展具有重要意义。以“两湖一库”流域为例,运用PLUS(patch-level land use simulation)模型和InVEST(integrated valuation of ecosystem services and tradeoffs)模型生态系统服务水质净化模块,基于2000年、2010年和2020年土地利用数据,模拟流域在未来自然发展情景和生态保护情景下的用地类型时空格局变化以及水质净化特征。定量揭示土地利用变化与水质净化功能的响应关系。结果表明:“两湖一库”流域土地类型以耕地为主,2030年在自然发展情景下耕地、林地、草地面积呈下降趋势,建设用地呈上升趋势,生态保护情景可有效保护流域耕地、林地等空间分布和面积;“两湖一库”流域TN、TP输出量以低强度输出为主,2000—2020年TN输出量先增加后减少,TP输出量逐年增加,水质净化能力呈稳中变好的趋势;2030年自然发展情境下TN输出量持续减少,TP输出量呈向上浮动,生态保护情景下TN、TP输出量较自然发展情景下减少,生态保护情景可以增加水质净化能力。生态用地类型可以有效截留N、P进入水体,生态保护情景下有效降低生态用地类型的变化速度,减少TN、TP的输出量,“两湖一库”流域未来规划中应增加生态用地的占比,增加土地类型对TN、TP的截留能力。

A two-dimensional numerical model for eutrophication in Baiyangdian Lake

Hydrodynamic, physical, and biochemical processes in the Baiyangdian Lake water environment were analyzed comprehensively. An eutrophication eco- dynamics model including the effects of reed resistance on flow was coupled with the hydrodynamics governing equations. An improvement on the Water Quality Analysis Simulation Program （WASP, a modeling system intro- duced by the US Environmental Protection Agency） is established, which uses the zooplankton kinetic equation. The model simulates water quality constituents associated with eutrophication in the lake, including phytoplankton, zooplankton, nitrogen, phosphorus, dissolved oxygen, and others. Various kinetic coefficients were calibrated using measured data or information from relevant literature, to study eutrophication in the lake. The values calculated by the calibrated model agree well with field data, including ammonia nitrogen, total nitrogen, total phosphorus and dissolved oxygen. Changes related to nutrition and dissolved oxygen during the processes were simulated. The present model describes the temporal variation of water quality in Baiyangdian Lake with reasonable accuracy. Deviations between model-simulated and observed values are discussed. As an ideal tool for environmental management of the lake, this model can be used to predict its water quality, and be used in research to examine the eutrophication process.

基于InVEST模型的新济洲国家湿地公园生态系统服务动态变化研究

对2019和2022年的Sentinel-2卫星遥感影像进行解译,分析新济洲湿地公园的土地利用/覆被动态变化情况,并基于InVEST模型分析新济洲湿地公园生境质量和碳储量变化,探究湿地公园生态系统服务情况及其管理建设效果;同时探究生态系统服务之间的协同/权衡关系。结果表明:2019—2022年新济洲湿地公园土地利用/覆被变化较大,其中,林地和草地呈现增加趋势,农田呈现减少趋势。2019—2022年新济洲湿地公园碳储量增加了3.09万t,碳储量较高的区域主要分布在新济洲岛和新生洲岛;平均生境质量上升了0.11,变化较大的区域主要位于再生洲岛。新济洲湿地公园碳储量与生境质量存在较强的协同关系。新济洲湿地公园的管理建设取得了一定成效,明显提升了湿地公园的生态系统服务功能。

基于SolVES模型的东湖风景区社会价值评估及提升策略

城市湖泊型风景区具有良好的生态系统服务社会价值,是城市规划关注的热点。对当前的城市湖泊型风景区,少有从生态系统服务社会价值方面进行评估和研究。以武汉东湖风景区为例,通过SolVES模型对其生态系统服务社会价值及其影响因素进行评估,结果表明:游客对武汉东湖风景区美学价值、生命可持续价值、生物多样性价值、科研教育价值和康养价值评价较高;美学价值、康养价值和科研教育价值主要集中在磨山、听涛及落雁景区的主要旅游景点,生物多样性和生命可持续价值在各景区广泛分布;水体、植被覆盖度、公共设施、旅游景点、科教文化设施、交通设施的建设会影响游客对社会价值的偏好。根据研究结果对武汉东湖风景区生态系统服务社会价值提出了提升策略。

创新生态系统视角下战略性新兴产业成长仿真研究

战略性新兴产业内部创新要素之间的动态复杂关系尚未得以充分揭示。为进一步分析不同因素对产业成长的影响程度,促进中国的战略性新兴产业在创新生态系统模式下实现高质量发展,基于创新生态系统研究视角,运用系统动力学的研究方法构建战略性新兴产业系统动力学模型,通过有关年鉴和企业财务报表以及政府部门官方网站收集2015—2021年中国新一代信息技术产业相关统计数据,综合运用线性回归法、层次分析法、经验公式法、建立表函数等多种方法建立方程进行仿真模拟分析。结果表明:(1)战略性新兴产业创新生态系统包含5个状态变量、5个速率变量、24个辅助变量及13个常量,其成长动力机制主要包括创新供给子系统、成长需求子系统、环境支撑子系统,各子系统之间相互作用,共同影响产业成长;(2)2015—2021年中国新一代信息技术产业的产值和专利数量模拟数据与实际数据的误差绝对值都在5%以内,可以比较准确模拟产业成长的实际情况;(3)需求变动、科研经费投入变动、政府财政支出变动是中国新一代信息技术产业成长的关键影响因素,其中政府消费影响因子、居民消费影响因子、R&D资金投入系数、R&D人员投入系数、政府研发投入系数、教育投入系数等对产业成长都具有正向影响,而教育投入系数的影响程度最高,且多种参数变动带来的效果远比单一因素变动的效果更显著;(4)产业增加值、产业增加值占地区生产总值的比重、专利数量、新产品销售收入等这些指标在未来都将呈现较好的增长趋势。据此,得出进一步加大科研经费投入、加快培育技术人才和加强产学研政介合作等相关管理启示。