基于管理目标的湖泊生态系统动力学

基于生态系统管理的目标,在对相关研究分析的基础上,依据生态系统生态学、淡水生态学的理论,提出了湖泊生态系统动力学研究的2个理论基础：生态系统管理和生态系统特征.在此基础上,分析得到湖泊生态系统动力学的研究方法体系,主要包括研究内容与技术路线、关键问题识别和动力学模拟、湖泊生态系统的适应性管理决策等部分.其中,湖泊生态系统结构和过程、湖泊中食物网营养动力学研究、生源要素循环、湖泊中关键过程的生态作用以及湖泊生态系统动力学模拟是研究的核心问题.此后,以P为主要的生源要素,将生态系统分为3个子过程：入流、出流和内部反馈,并以此建立了湖泊生态系统动力学的模型框架,以辅助于湖泊的生态系统管理.     

湖泊的水生态模型

由于城市化进程的不断加快,大量的污染物排放到湖泊中,打破了湖泊的生态平衡.湖泊的水生态模型不仅能够研究湖泊的富营养化现象,而且还可以模拟工业毒物等污染物对湖泊生态系统的影响,是湖泊管理的有力工具.本文从分析湖泊的污染现状以及污染趋势出发,介绍了湖泊水生态模型的研究现状,并根据模型的模拟对象和空间模拟能力对湖泊水生态模型进行了分类.在此基础上介绍了AQUATOX、PAMOLARE、CAEDYM、WASP、OOMAS等比较成熟的模拟湖泊生态系统的模型软件,阐述了它们的产生、发展、主要特点以及应用,总结了当今湖泊水生态模型在模拟过程中遇到的问题,并对水生态模型的发展趋势进行了展望.本文为湖泊水生态模型的选择提供了建议.     

城市生态系统的动力学演化模型研究进展

从系统分析出发,对城市生态系统的动力学演化模型的发展历程、建模的方法和步骤过程、软件开发方法和目前的模型软件等进行了总结。归纳了城市生态系统的动力学演化建模的方法,主要包括模型定义、模拟、实现、验证、分析和应用等六大步骤。目前国内外用于城市生态系统动力学演化模型的主要方法有：基于数理模型的方法、生态控制论和灵敏度模型、系统动力学模型、多目标规划法等。已经开发的用于城市生态系统的动力学模拟的软件可以划分为两类：基于土地利用和交通规划的专业模型和基于系统动力学和灵敏度模型的一般软件。总结了常用的城市演化模型软件,讨论了模型的研究对象和应用范围。分析了城市生态系统的动力学演化模型建模的不确定性的来源,并指出：向宏观和微观两极化发展是城市生态系统动力学演化模型的发展趋势之一,而与人工智能和地理信息系统等新方法的集成是发展的另一趋势。城市生态系统动力学演化模型的开发前景在于对不确定性问题的定性、定量分析,而多模型的耦合和集成是发展的必然趋势。     

考虑气候因子变化的湖泊富营养化模型研究进展

气候因子是影响湖泊营养状态和进程的主要自然因素.在全球气候变化的趋势下,将气候因子的变化纳入湖泊富营养化模型中,可以为湖泊演化趋势分析和环境管理决策提供技术支持.本文首先分析了气温、降水、光照和大气等气候因子对湖泊富营养化的影响,进而对考虑气候因子变化的数理统计与分析模型、生态动力学模型、系统生态学模型及智能算法等的研究进行了综述.在此基础上,对完善气候因子变化下湖泊营养状态变化的模型研究进行了展望：1)加强气候因子作用于湖泊营养状态的机理研究;2)选择合适的气候模拟模型,合理设置气候变化情景,在不同模型嵌套时保证时空尺度的匹配;3)以水动力学模型为基础,耦合生态模型及智能算法等,并结合良好的气候模拟模型,以精确模拟预测气候变化下湖泊富营养化的演化过程和趋势.     

湖泊水库结构生态动态模型

综述了湖泊水库结构生态动态模型的研究进展及其在湖泊水库环境生态模拟中的应用。结果表明,热力学理论为获取湖泊水库生态系统的特性提供了一条整体性的途径,热力学概念“Ｙｏｎｇ”可将生态学理论（达尔文理论）和热力学理论（最大Ｙｏｎｇ原理）很好地联系起来。引入Ｙｏｎｇ后,许多重要模型参数的目标函数可根据最大Ｙｏｎｇ原理获得,达尔文“达者生存”理论可被定量为一个生态约束条件用于发展湖泊水库结构生态结构模型,从     

湖泊富营养化模型研究进展

自多湖泊富营养化引起人类注意以来,科学家们就设法通过使用数学模型来模拟湖泊富营养化的发生,预测湖泊对不同管理措施的响应,以便批出合理的治理措施。总的来说,湖泊富营养化模型大概经历了以下三个发展阶段：（1）单限制因子模型,如磷模型;（2）多限制因子模型,如浮游植物初级生产力估测模型;（3）生态－动力学模型,它是目前也是以后发展的主不充。随着人们对湖泊生态系统认识的提高和计算机技术的发展,生态与水动力耦合模型、面向对象模型和神经网络模型等具有良好的发展前景。     

宏观植物生态模型的研究现状与展望

概述了3种主要植物生态模型的发展现状1)种群动态模型,主要模拟在一个生态系统中单个种的植物个体发芽、成长和死亡过程,及其种内竞争和种间相互作用,是研究开发最早的一类生态模型之一.该类模型主要应用于分析植物种群之间相互作用.2)演替模型,主要模拟植物种类(动物与此相伴)在整个生态系统发展过程的变化,包括植被类型的转变和相关的生物地球化学循环过程的改变.可用于研究生物群落对气候变化的响应.3)生态系统模型,是把生态系统当作一个功能整体来模拟的一类模型,主要有以下3类(1)SVAT模型,主要模拟地表生态系统过程,以BATS、SiB、SiB2和LEAF为代表,多用于气候研究;(2)BGC模型,主要模拟3个关键循环碳,水和营养物质循环.常用的BGC模型有FOREST-BGC、BIOME-BGC、CENTURY、TEM、DOLY以及由它们衍生而来的整合模型组;(3)BG模型,模拟群落、生物群区中植物分布,比较具有代表性的 BGMs包括BIOME2和MAPSS,它们主要用于研究因气候变化而引起的生物分布的变迁.最后,结合我们的实际工作展望了生态模型在未来几年内的几个发展方向1)与基础学科相结合,比如把物候学引入生态模型研究中来,以寻求新的支撑点;2)与现代非线性理论相结合,重新评价模型的假设基础;3)与现代科学技术相结合,利用3S技术和计算机技术为模型的发展提供更强大的技术支持;4)在研究方法上,从还原论转向整体论,尽可能地把生态系统当作一个功能整体来模拟研究.     

湖泊湿地生态服务监测指标与监测方法

湖泊湿地生态系统为人类提供了维持生存发展的多种生态系统服务,是社会经济可持续发展的重要基础。然而,全国范围内的湖泊湿地资源被大量开发利用,极大地削弱了湖泊湿地提供生态系统服务的能力,人类自身福祉也受到严重威胁。开展湖泊湿地生态系统服务动态监测能减少生态系统服务重复计算、推动生态系统服务管理实践。本文在分析湖泊湿地生态系统服务监测必要性的基础上,探讨了湖泊湿地生态系统服务监测指标选取的原则和思路,并初步构建了适宜于我国湖泊湿地生态系统服务动态评估、权衡分析和生态生产函数构建的最终服务和生态特征监测指标体系。最终服务是与人类效益有直接关联的生态功能量,生态特征指标是产生生态系统最终服务的关键指标,主要包括生态结构、生态过程和生态功能指标。供给服务和文化服务一般是最终服务,而调节服务既可以是中间服务(生态功能)又可以是最终服务,支持服务是中间服务(生态过程)。针对调节服务和文化服务评估的困难性及调节服务的重复计算问题,本研究提出通过宏观监测(3S技术监测)和典型湖泊湿地定位监测相结合的多尺度湖泊湿地生态系统服务监测方法,构建湿地监测项目开展生态系统最终服务和生态特征指标数据监测。本研究对构建生态生产函数、开展湖泊湿地生态系统服务动态评估和权衡分析具有重要意义,是生态系统服务从认知走向管理实践的重要基础。     

湖泊生态服务受益者分析及生态生产函数构建

生态系统服务管理作为生态系统管理的优化方式,是生态学研究的前沿方向。湖泊生态系统服务管理是指综合利用生态学、经济学、社会学和管理学等学科知识,对影响湖泊生态系统结构、过程、功能的关键因子进行调控,提高湖泊生态系统服务供给水平和供给能力的过程。近年来国内外学者针对湖泊生态系统服务内涵、分类、经济价值评估等方面开展了大量研究,极大地促进了湖泊生态系统服务从认知走向管理实践。然而,现有研究在开展湖泊生态系统服务价值评估时多忽略生态系统服务受益者和生态系统特征对生态系统服务的边际影响分析,无法揭示生态系统服务空间流动和转移特征及生态系统服务时空权衡关系,制约了生态系统服务研究与管理决策和政策设计结合。在综述湖泊生态系统服务定量评估方法的基础上,认为通过生态系统服务受益者分析确定湖泊生态系统最终服务,并通过构建生态生产函数确定湖泊生态系统服务权衡关系及湖泊生态系统特征对生态系统最终服务的边际影响,是生态系统服务走向管理实践和政策设计的科学依据,可以确保生态、社会、经济可持续发展。     

水动力条件下藻类动态模拟

藻类动态变化是其内部生理特征和外部驱动因素综合作用的结果。除了藻类自身生理因素及光、温度、营养盐等因素,水动力作用使底泥发生再悬浮所造成的营养盐的内源释放对藻类的影响也非常重要。1999年5月8日~6月24日在太湖湖泊生态系统研究站大型生态实验槽中进行了模拟水动力条件下的太湖藻类动态实验,并应用国外先进的PHREEQC软件从生物化学和生态动力学角度建立了藻类生态动力学模型。模型不仅考虑了氮循环及磷循环,还考虑了水动力条件引起的内源释放问题,根据2003年4月26~4月30日在河海大学环形水槽所做的底泥释放实验结果建立了水流和各形态氮磷营养盐释放的定量化关系。由于目前太湖的野外监测资料存在较明显的时空不一致性,模型参数率定的精度受到了较大影响。从室内模拟实验出发,通过对生态槽实验结果的模拟,确定和验证了模型的各参数值,计算结果显示模拟值能较好地拟合实验测量值,表明所建藻类生态动力学模型能较好地描述藻类及各种营养盐的动态变化,这对揭示藻类“水华”暴发机理有一定的意义。     

浅水湖泊生态系统稳态转换的阈值判定方法

浅水湖泊生态系统对人类干扰的反应会随着干扰力度的改变或增强而出现突然的变化,即发生稳态转换;对其机理和驱动机制的揭示将有助于对湖泊富营养化的控制及恢复.基于“多稳态”理论的稳态转换研究已广泛开展,但对浅水湖泊生态系统稳态转换的驱动机制结论各异,采用的阈值判定方法相差很大,主要有实验观测、模型模拟和统计分析3种.实验观测多关注少数特定指标,指标筛选过程复杂且工作量大;模型模拟虽能从较为全面的尺度上理解生态系统稳态变化的特征和主要机理过程,但在模型误差和不确定性的处理等问题上尚存在不足;统计分析方法基于对长时间序列数据的统计变化规律分析,用以判断或者预警稳态转换现象的发生,是目前最为常用的方法.目前稳态转换领域的研究大都是对已发生的稳态转换进行机制分析或过程反演,对未来预测与预警的问题仍然亟需加强.     

A modeling approach for calcium carbonate precipitation in a hypersaline environment: A case study from a shallow,alkaline lake

Carbonates are widespread occurrences in various environmental conditions. Particularly, microbial induced and/or controlled carbonate formations are considered significant archives for recording critical environmental conditions that can be used not only to reconstruct paleo-environments, but also to gain valuable information about evidence of life in environments. Therefore, deciphering carbonate precipitation mechanisms, and the factors controlling these processes, particularly in extreme environments, hold significant insights for industrial applications, and for searching life in extra-terrestrial environments. In the scope of these contexts, we tried to model carbonate precipitation mechanism and possible biological influences in a hypersaline lake, known as an extreme environment in Turkey, in terms of its water chemistry. The aim of this research is to model CaCO₃ precipitation in the Acıgöl Lake, using water quality data from the field, and meteorological data obtained from the Turkish State Meteorological Service for the years 2013 and 2015. To achieve this, AQUATOX model is utilized. The model is calibrated for nine stations of the lake using parameters related to water quality, site characteristics, inflow loadings and lake hydrodynamics. Calibration dataset is obtained from the field measurements and meteorological data, for the year 2013. Model validation is conducted both using experimental data, and field observations, obtained in August, 2015. An integrated modeling approach is undertaken by coupling a geochemical reaction model and a process-based ecosystem model, AQUATOX; using field, experimental and meteorological data. Model results suggest that the amount of CaCO₃ precipitation in the system ranges from 35.16 to 128.48 mg L⁻¹ d^–1. Temperature, photosynthesis rate, depth and pH are found to be the most significant variables that govern the biogeochemical processes responsible for CaCO₃ precipitation. The model showed a strong relationship between calcite precipitation and certain cyanobacteria species such as Anabaena and Aphanizomenon sp. Results also indicate that the model was successful in representing the relationships between calcite precipitation variations, and phosphate and pH. The Nash-Sutcliffe model efficiency coefficient and NRMSE are found to be 0.93 and 0.29, respectively.     

Modeling the spring blooms of ciliates in a deep lake

In contrast to the macro/mesozooplankton, microzooplankton has received much less attention in ecosystem models. In many modeling studies, microzooplankton has been either entirely neglected, or else, data were often not available for validation, or agreement between the observed and the simulated abundances was rather poor. In this study, we compare the simulation results from several alternative models considering different formulations of ciliate growth in a hydrodynamically driven 1D nutrient-phytoplankton–multiple zooplankton model, with long-term datasets from the deep, monomictic Lake Constance. We show that the parameterization of the limitation of ciliate growth with a constant specific mortality rate and/or predation by copepods leads to uncontrolled ciliate blooms. In contrast, implementation of a density-dependent mortality rate enables reproduction of algae–ciliate dynamics over a variety of environmental settings encompassed by the 14-year dataset spanning 21 years in a lake undergoing oligotrophication. Considering the numerous processes that can be responsible for the dampening of ciliate blooms, our findings suggest that employing a simple density-dependent mortality term offers a pragmatic solution for the challenge of including the microzooplankton, characterized by an overwhelming complexity of trophic interactions, in ecosystem models.     

A general one-dimensional vertical ecosystem model of Lake Shira (Russia,Khakasia): description,parametrization and analysis

A one-dimensional ecological model of the meromictic brackish Lake Shira (Russia, Khakasia) was developed. The model incorporates state-of-the-art knowledge about the functioning of the lake ecosystem using the most recent field observations and ideas from PCLake, a general ecosystem model of shallow freshwater lakes. The model of Lake Shira presented here takes into account the vertical dynamics of biomasses of the main species of algae, zooplankton and microbial community, as well as the dynamics of oxygen, detritus, nutrients and hydrogen sulphide from spring to autumn. Solar radiation, temperature and diffusion are modelled using real meteorological data. The parameters of the model were calibrated to the field data, after applying different methods of sensitivity analysis to the model. The resulting patterns of phytoplankton and nutrients dynamics show a good qualitative and quantitative agreement with the field observations during the whole summer season. Results are less satisfactory with respect to the vertical distribution of zooplankton biomass. We hypothesize that this is due to the fact that the current model does not take the sex and age structure of zooplankton into account. The dynamics of oxygen, hydrogen sulphide and the modelled positions of the chemocline and thermocline are again in good agreement with field data. This resemblance confirms the validity of the approach we took in the model regarding the main physical, chemical and ecological processes. This general model opens the way for checking various hypotheses on the functioning of the Lake Shira ecosystem in future investigations and for analysing options for management of this economically important lake.     

Living within dynamic social-ecological freshwater systems: System parameters and the role of ecological engineering

The objective of ecological engineering is to design sustainable ecosystems that integrate human communities and their natural environment for the benefit of both. In this paper, we illustrate how social-ecological modeling can be used as a tool to clarify this objective at a landscape scale for freshwater systems. Coupled social-ecological systems (SESs) are open, dynamic systems subject to both ecological and socioeconomic perturbations. Here we demonstrate the interactive effects of social and technological uncertainties on SES dynamics over time. Additionally, we integrate research on ecosystem stability, social-ecological modeling, and ecological engineering to offer guidance for research at the human-environment interface. Based on a case study of Lake Erie's Sandusky watershed, we use an integrated human-biophysical model to investigate the influence of two parameters on SES dynamics: (1) regional societal preferences that impact watershed management and (2) technological innovation that alters agricultural nutrient efficiency. Our results illustrate ways in which SES dynamics and optimum management strategies depend on societal preferences within the region, indicating a key area of uncertainty for future investigation. As guidance for SES restoration, our model results also illustrate the conditions under which technological change that increases nutrient efficiency on farms can and cannot create a win-win, or increase both human welfare and SES resistance to eutrophication simultaneously. Using these results, we elucidate the value of ecological engineering and offer guidance for assessments of ecological engineering projects using social-ecological modeling.     

Sixty years of environmental change in the world's largest freshwater lake – Lake Baikal, Siberia

High-resolution data collected over the past 60 years by a single family of Siberian scientists on Lake Baikal reveal significant warming of surface waters and long-term changes in the basal food web of the world's largest, most ancient lake. Attaining depths over 1.6 km, Lake Baikal is the deepest and most voluminous of the world's great lakes. Increases in average water temperature (1.21 °C since 1946), chlorophyll a (300% since 1979), and an influential group of zooplankton grazers (335% increase in cladocerans since 1946) may have important implications for nutrient cycling and food web dynamics. Results from multivariate autoregressive (MAR) modeling suggest that cladocerans increased strongly in response to temperature but not to algal biomass, and cladocerans depressed some algal resources without observable fertilization effects. Changes in Lake Baikal are particularly significant as an integrated signal of long-term regional warming, because this lake is expected to be among those most resistant to climate change due to its tremendous volume. These findings highlight the importance of accessible, long-term monitoring data for understanding ecosystem response to large-scale stressors such as climate change.     

Hydrological regulation drives regime shifts: evidence from paleolimnology and ecosystem modeling of a large shallow Chinese lake

Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such ‘regime shifts’ can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long‐term dynamics of shallow lake ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and ecosystem modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake ecosystem dynamics, and it highlights the urgency of using multi‐objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic ecosystems around the globe.     

Lakes in the era of global change: moving beyond single-lake thinking in maintaining biodiversity and ecosystem services

The Anthropocene presents formidable threats to freshwater ecosystems. Lakes are especially vulnerable and important at the same time. They cover only a small area worldwide but harbour high levels of biodiversity and contribute disproportionately to ecosystem services. Lakes differ with respect to their general type (e.g. land-locked, drainage, floodplain and large lakes) and position in the landscape (e.g. highland versus lowland lakes), which contribute to the dynamics of these systems. Lakes should be generally viewed as ‘meta-systems’, whereby biodiversity is strongly affected by species dispersal, and ecosystem dynamics are contributed by the flow of matter and substances among locations in a broader waterscape context. Lake connectivity in the waterscape and position in the landscape determine the degree to which a lake is prone to invasion by non-native species and accumulation of harmful substances. Highly connected lakes low in the landscape accumulate nutrients and pollutants originating from ecosystems higher in the landscape. The monitoring and restoration of lake biodiversity and ecosystem services should consider the fact that a high degree of dynamism is present at local, regional and global scales. However, local and regional monitoring may be plagued by the unpredictability of ecological phenomena, hindering adaptive management of lakes. Although monitoring data are increasingly becoming available to study responses of lakes to global change, we still lack suitable integration of models for entire waterscapes. Research across disciplinary boundaries is needed to address the challenges that lakes face in the Anthropocene because they may play an increasingly important role in harbouring unique aquatic biota as well as providing ecosystem goods and services in the future.     

湖泊-流域生态系统管理的内容与方法

在流域生态系统管理研究综述的基础上,对湖泊一流域生态系统管理的概念进行了界定,对水环境管理、综合流域管理与流域生态系统管理之间的差异进行了对比分析。确定了生态系统生态学、流域生态学、生态系统健康和流域方法为湖泊．流域生态系统管理的理论基础,生态系统方法和流域分析为其方法学基础。在上述分析的基础上,提出了湖泊．流域生态系统管理的6个主要步骤：研究范围界定、基础信息收集与基本生态学问题的分析和评价、管理目标设定、系统综合、生态系统综合评价、适应性管理;识别出湖泊-流域生态系统管理中的3个关键问题：①生态系统管理中的不确定性和障碍分析;②流域土地利用变化对湖泊水质和生态系统的影响;③流域生态子系统与社会子系统的关联。