A physical-microbial food web coupled model to study the evolution of the ecological functioning of a new reservoir after its flooding (Sep,Puy de Dôme)

The aim of this paper is to understand the temporal changes in planktonic populations and to highlight some important factors that control the biological functioning and evolution of a recently flooded reservoir, the Sep reservoir (Massif Central, France). To achieve this objective, a 1D vertical coupled physical–biological model was used and developed. It couples relevant physical processes (dispersion, advection and convection) with biological processes taking into account the complexity of interactions within the microbial food web, including the conventional grazing food chain with a microbial loop.     

Cycling in ecosystems: An individual based approach

Cycling index is an important ecological indicator used in ecosystem analysis. The higher the cycling in an ecosystem, the higher the utilization of mass and energy within the system before it is lost due to respiration and other factors. For a stock-flow type ecosystem model at steady state, Finn’s cycling index (FCI) can be computed using simple matrix algebra. However, it is difficult to measure how well this index represents the actual cycling occurring in the system. In this paper, we study cycling in ecological networks using an individual based approach (particle tracking algorithm). This new simulation method provides access to the pathway data of individual particles that flow in the system, therefore one can quantify cycling using this pathway data quite literally. We used particle tracking simulations (PTS) to compute a cycling index using Finn’s idea of flux based cycling. Our simulation based results (using no matrix algebra) agree with Finn’s cycling index, verifying the accuracy of both the PTS, and the original linear algebraic formulation of FCI.     

Comparative network analysis toward characterization of systemic organization for human–environmental sustainability

A preliminary study in comparative ecological network analysis was conducted to identify key assumptions and methodological challenges, test initial hypotheses and explore systemic and network structural characteristics for environmentally sustainable ecosystems. A nitrogen network for the U.S. beef supply chain – a small sub-network of the industrial food system analyzed as a pilot study – was constructed and compared to four non-human carbon and nitrogen trophic networks for the Chesapeake Bay and the Florida Everglades. These non-human food webs served as sustainable reference systems. Contrary to the main original hypothesis, the “window of vitality” and the number of network roles did not clearly differentiate between a human sub-network and the more complete non-human networks. The effective trophic level of humans (a partial estimate of trophic level based on the single food source of beef) was much higher (8.1) than any non-human species (maximum of 4.88). Network connectance, entropy, total dependency coefficients, trophic efficiencies and the ascendency to capacity ratio also indicated differences that serve as hypotheses for future tests on more comprehensive human food webs. The study elucidated important issues related to (1) the steady state assumption, which is more problematic for industrial human systems, (2) the absence or dearth of data on contributions of dead humans and human wastes to feed other species in an integrated food web, (3) the ambiguity of defining some industrial compartments as living versus non-living, and (4) challenges with constructing compartments and trophic transfers in industrial versus non-human food webs. The two main novel results are (1) the progress made toward adapting ecological network analysis (ENA) methodology for analysis of human food networks in industrial cultures and (2) characterizing the critical aspects of comparative ENA for understanding potential causes of the problems, and providing avenues for solutions, for environmental sustainability. Based on this work, construction and comparative network analysis of a more comprehensive industrial human food network seems warranted and likely to provide valuable insights for modifying structures of industrial food networks to be more like natural networks and more sustainable.     

Adding rigor to ecological network models by evaluating a set of pre-balance diagnostics: A plea for PREBAL

The widespread use of ecological network models (e.g., Ecopath, Econetwrk, and related energy budget models) has been laudable for several reasons, chief of which is providing an easy-to-use set of modeling tools that can present an ecosystem context for improved understanding and management of living marine resources (LMR). Yet the ease-of-use of these models has led to two challenges. First, the veritable explosion of the use and application of these network models has resulted in recognition that the content and use of such models has spanned a range of quality. Second, as these models and their application have become more widespread, they are increasingly being used in a LMR management context. Thus review panels and other evaluators of these models would benefit from a set of rigorous and standard criteria from which the basis for all network models and related applications for any given system (i.e., the initial, static energy budget) can be evaluated. To this end, as one suggestion for improving network models in general, here I propose a series of pre-balance (PREBAL) diagnostics. These PREBAL diagnostics can be done, now, in simple spreadsheets before any balancing or tuning is executed. Examples of these PREBAL diagnostics include biomasses, biomass ratios, vital rates, vital rate ratios, total production, and total removals (and slopes thereof) across the taxa and trophic levels in any given energy budget. I assert that there are some general ecological and fishery principles that can be used in conjunction with PREBAL diagnostics to identify issues of model structure and data quality before balancing and dynamic applications are executed. I humbly present this PREBAL information as a simple yet general approach that could be easily implemented, could be considered for further incorporation into these model packages, and as such would ultimately result in a straightforward way to evaluate (and perhaps identify areas for improving) initial conditions in food web modeling efforts.     

From Global to Local: Providing Actionable Flood Forecast Information in a Cloud‐Based Computing Environment

Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high‐resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open‐source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high‐resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre‐computed distributed GSSHA models.     

草海典型高原湿地食物链中汞同位素组成特征

以国家自然保护区贵州草海高原湿地为研究对象,系统采集了不同种群水生生物,通过测定各样品总汞、甲基汞含量、碳氮同位素和汞同位素组成,以探究汞在食物链营养级传递过程中的同位素分馏特征.结果显示,所有样品均发生了汞同位素质量分馏(MDF)和非质量分馏(MIF),且均表现出偏负的δ202Hg (-0.93‰±1.32‰,n=14)以及偏正的Δ199Hg(0.79‰±0.76‰,n=14).除穗状狐尾藻(δ15N=-1.88‰)以外,δ15N和δ202Hg之间存在显著的正相关关系(r=0.58,P0.05),表明汞在食物链的生物富集过程中相对富集偏重的汞同位素.Δ199Hg和δ15N之间也表现出显著正相关性(r=0.67,P0.05),同时Δ199Hg与生物中甲基汞比例(%MeHg)之间存在显著正相关性(r=0.58,P0.05),表明汞的非质量分馏程度随食物链的升高而变大,可能是由于营养传递的过程中生物体内甲基汞的比例升高所致.     

南水北调中线干渠生态系统结构与功能分析

为分析和掌握南水北调中线干渠生态系统结构与功能的特征参数,根据2015~2019年中线干渠鱼类资源调查数据及实测的鱼类生物学参数数据,应用Ecopath with Ecosim 6.6软件构建了Ecopath食物网模型.模型由18个功能组组成,包括了初级生产者、初级消费者、主要鱼类和有机碎屑等.结果显示：中线干渠生态系统规模总流量、总生产量和总消耗量分别为19186.330,8947.857和1106.002（t/（km²·a））,食物网主要由4个整合营养级（1.00~3.71）构成,最高营养级为大型肉食性鱼类鱤（3.71）.食物网能量传递主要有两条途径,分别为牧食食物链和碎屑食物链,两者传递的能量相当,但牧食食物链传递效率是碎屑食物链的近两倍.交互营养分析结果表明,捕食者对其饵料生物的影响一般为抑制作用,碎屑生物量的增加对大部分功能组的影响为正效应,小型上层鱼类对浮游动物生物量起抑制作用.从各功能组之间的生态位重叠来看,各功能组间捕食者生态位重叠现象不普遍,重叠指数适中,部分肉食性鱼类的捕食者生态位重叠指数达到1.对生态系统总体特征分析发现,中线干渠生态系统的总初级生产量与总呼吸量的比值（P/R）、总初级生产量与总生物量的比值（P/B）、Finn's循环指数（FCI）和Finn's平均路径长度（FML）都表明该生态系统处于发展的幼态期,抵抗外界干扰的能力差.此外,中线干渠生态系统对初级生产力的利用率很低,导致过多的营养物质未进入更高营养级的食物链中进行循环,造成系统能量流动的滞缓.因此,根据生物操纵理论,可通过优化和完善鱼类群落结构,增强对系统初级生产力的利用效率,促进物质循环和能量流动,维持生态系统稳定.     

多溴联苯醚在典型电子垃圾污染区域水生食物链上的生物富集特征

为调查电子垃圾回收活动对当地水生生物造成的多溴联苯醚(PBDEs)污染,测定了广东某电子垃圾回收地附近水库中水生生物样品(水蛇、鱼类、草虾和田螺)和对照区样品(鲮鱼)中18种PBDEs含量,通过对样品氮同位素的测定,探讨了PBDEs在该地淡水食物链上的生物富集特征.研究结果显示,∑PBDEs(总PBDEs含量)在水蛇、鱼类、草虾和田螺中分别为39.6～186、1.82～75.7、4.60～17.1和7.26～17.0μg·g-1(脂重),比华南地区鱼体中∑PBDEs的平均含量高3个数量级,表明电子垃圾回收活动已对当地水生生物造成了PBDEs的严重污染.除BDE66、BDE99、BDE153、BDE183和BDE209外,其他13种PBDE单体在食物链上均存在着生物放大效应,但生物放大能力(B值)与正辛醇-水分配系数logKOW相关性不明显,可能是由于某些PBDE单体在生物体内存在代谢作用.以上结果表明,由电子垃圾回收活动导致的PBDEs污染存在较大的生态风险,应该引起高度关注.     

南水北调中线干渠生态系统结构与功能分析

为分析和掌握南水北调中线干渠生态系统结构与功能的特征参数,根据2015~2019年中线干渠鱼类资源调查数据及实测的鱼类生物学参数数据,应用Ecopath with Ecosim 6.6软件构建了Ecopath食物网模型.模型由18个功能组组成,包括了初级生产者、初级消费者、主要鱼类和有机碎屑等.结果显示：中线干渠生态系统规模总流量、总生产量和总消耗量分别为19186.330,8947.857和1106.002（t/（km²·a））,食物网主要由4个整合营养级（1.00~3.71）构成,最高营养级为大型肉食性鱼类鱤（3.71）.食物网能量传递主要有两条途径,分别为牧食食物链和碎屑食物链,两者传递的能量相当,但牧食食物链传递效率是碎屑食物链的近两倍.交互营养分析结果表明,捕食者对其饵料生物的影响一般为抑制作用,碎屑生物量的增加对大部分功能组的影响为正效应,小型上层鱼类对浮游动物生物量起抑制作用.从各功能组之间的生态位重叠来看,各功能组间捕食者生态位重叠现象不普遍,重叠指数适中,部分肉食性鱼类的捕食者生态位重叠指数达到1.对生态系统总体特征分析发现,中线干渠生态系统的总初级生产量与总呼吸量的比值（P/R）、总初级生产量与总生物量的比值（P/B）、Finn's循环指数（FCI）和Finn's平均路径长度（FML）都表明该生态系统处于发展的幼态期,抵抗外界干扰的能力差.此外,中线干渠生态系统对初级生产力的利用率很低,导致过多的营养物质未进入更高营养级的食物链中进行循环,造成系统能量流动的滞缓.因此,根据生物操纵理论,可通过优化和完善鱼类群落结构,增强对系统初级生产力的利用效率,促进物质循环和能量流动,维持生态系统稳定.