Reconstructing historical marine ecosystems using food web models: Northern British Columbia from Pre-European contact to present

Mass-balance trophic models (Ecopath with Ecosim) are developed for the marine ecosystem of northern British Columbia (BC) for the historical periods 1750, 1900, 1950 and 2000 AD. Time series data are compiled for catch, fishing mortality and biomass using fisheries statistics and literature values. Using the assembled dataset, dynamics of the 1950-based simulations are fitted to agree with observations over 50 years to 2000 through the manipulation of trophic flow parameters and the addition of climate factors: a primary production anomaly and herring recruitment anomaly. The predicted climate anomalies reflect documented environmental series, most strongly sea surface temperature and the Pacific Decadal Oscillation index. The best-fit predator–prey interaction parameters indicate mixed trophic control of the ecosystem. Trophic flow parameters from the fitted 1950 model are transferred to the other historical periods assuming stationarity in density-dependent foraging tactics. The 1900 model exhibited an improved fit to data using this approach, which suggests that the pattern of trophic control may have remained constant over much of the last century. The 1950 model is driven forward 50 years using climate and historical fishing drivers. The resulting ecosystem is compared to the 2000 model, and the dynamics of these models are compared in a predictive forecast to 2050. The models suggest similar restoration trajectories after a hypothetical release from fishing.     

Mortality and predation in ecosystem models: is it important how these are expressed?

The effects of the form of the grazing and mortality terms used in plankton models are well known. The same cannot be said for ecosystem models. As ecosystem models become more popular more needs to be known about the effects of model formulation on model behaviour and performance. The impact of the form of the grazing response function and mortality terms used in a biogeochemical ecosystem model are considered here. We show that in the large and inter-linked webs used in ecosystem models, model behaviour is far more sensitive to the form of the grazing term than to that of the mortality terms that close the modelled food web.When using biogeochemical ecosystem models in shallow marine ecosystems, the most dynamic and sophisticated functional responses describing grazing require more parameters and validation than the simpler Holling disk equation, but usually still lead to the same general conclusions about the system state and the effects of changes in forcing functions. Thus, the use of more complex functional responses is not necessarily warranted in many cases. Similarly, the extra effort and data required to explicitly represent the top predators (sharks, mammals and birds) is not necessary if they are not the focus of the study. A quadratic mortality term applied to intermediate predators (such as piscivores) is sufficient to achieve plausible model behaviour. It should be noted, however, that some degree of sophistication is required in the grazing and mortality terms. Use of simple linear functional responses and mortality terms is unsuitable for models used to consider a range of nutrient loading or harvesting scenarios.     

Which forcing factors fit? Using ecosystem models to investigate the relative influence of fishing and changes in primary productivity on the dynamics of marine ecosystems

Fishing mortality and primary production (or proxy for) were used to drive the dynamics of fish assemblages in 9 trophodynamic models of contrasting marine ecosystems. Historical trends in abundance were reconstructed by fitting model predictions to observations from stock assessments and fisheries independent survey data. The model fitting exercise derives values for otherwise unknown parameters that specify the relative strength of trophic interactions and, in some instances, a time series anomaly for changes in primary production. We measured how much better or worse were model predictions when bottom-up forcing by primary production were added to top-down forcing by fishing. Searching for cross system patterns, the relative contribution of fishing and changes in primary production, mediated through trophic interactions, are evaluated for the ecosystems as a whole and for selected similar species in different ecosystems. The analysis provides a simple qualitative way to explain which forcing factors have most influence on modeled dynamics. Both fishing and primary production forcing were required to obtain the best model fits to data. Fishing effects more strongly influenced 6 of 9 of the ecosystems, but primary production was more often found to be the main factor influencing the selected pelagic and demersal fish stock trends. Examination of sensitivity to ecological and model parameters suggests that the results are the product of complex food-web interactions rather than simple deterministic responses of the models.     

Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela

‘End-to-end’ models have been adopted in an attempt to capture more of the processes that influence the ecology of marine ecosystems and to make system wide predictions of the effects of fishing and climate change. Here, we develop an end-to-end model by coupling existing models that describe the dynamics of low (ROMS–N₂P₂Z₂D₂) and high trophic levels (OSMOSE). ROMS–N₂P₂Z₂D₂ is a biogeochemical model representing phytoplankton and zooplankton seasonal dynamics forced by hydrodynamics in the Benguela upwelling ecosystem. OSMOSE is an individual-based model representing the dynamics of several species of fish, linked through opportunistic and size-based trophic interactions. The models are coupled through a two-way size-based predation process. Plankton provides prey for fish, and the effects of predation by fish on the plankton are described by a plankton mortality term that is variable in space and time. Using the end-to-end model, we compare the effects of two-way coupling versus one-way forcing of the fish model with the plankton biomass field. The fish-induced mortality on plankton is temporally variable, in part explained by seasonal changes in fish biomass. Inclusion of two-way feedback affects the seasonal dynamics of plankton groups and usually reduces the amplitude of variation in abundance (top-down effect). Forcing and coupling lead to different predicted food web structures owing to changes in the dominant food chain which is supported by plankton (bottom-up effect). Our comparisons of one-way forcing and two-way coupling show how feedbacks may affect abundance, food web structure and food web function and emphasise the need to critically examine the consequences of different model architectures when seeking to predict the effects of fishing and climate change.     

On maturation and spawning in some penaeid prawns of the Arabian Gulf

A mathematical model is presented of the ecosystem in the upper layers of the marine pelagic zone. The model has been constructed on the basis of presumed connections between biotic and abiotic ecosystem parameters typical of the Black Sea. Details on total model relations as well as on model analysis and construction may be obtained after gaining more insight into the behaviour of models constructed for the upper pelagic ecosystem of different marine aquatoria. The model is characterized by a rather complex behaviour. Realization of the model on the electronic computer is made by employing the method of random trajectories. As a result, a qualitative picture of model behaviour under different conditions is revealed and statistical characteristics of the parameters are obtained.     

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO₂ concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009-2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO₂ concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO₂ concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009-2099 under the constant climate scenario (i.e. using mean climate condition of 1951-2006 and CO₂ concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.     

土壤微生物呼吸热适应性与微生物群落及多样性对全球气候变化响应研究

土壤微生物呼吸热适应性被认为是决定陆地生态系统对全球变暖反馈作用的潜在重要机制,可能显著改变未来的气候变化趋势,然而,土壤微生物群落结构变化如何引起土壤微生物呼吸热适应性的研究目前尚存争议.该文针对气候变化对土壤微生物呼吸的影响研究,梳理了当前对土壤微生物呼吸的热适应性是否存在的争议和不同观点与结论,综述了气候变化对土...     

Model-based analysis of the influence of ecological processes on forest point pattern formation—A case study

Many different spatio-temporal individual-based models (IBM) for forests have been developed for studying the development of trees in space and time. Such models typically depend on various numerical parameters that represent the ecological processes of growth (G), inter-plant competition (C) and birth-and-death (B&D; also called regeneration and mortality). Until now little work has been done to systematically trace the influence of these processes and their model parameters on the spatial structure of forest ecosystems.This paper attempts to fill this gap by addressing an important aspect of forest structure, spatial variability, characterised by the mark variogram as a summary characteristic. The model used was inspired by components of various well-established IBMs including a shot-noise competition field. Time series data from monospecies forests in three different countries of the northern hemisphere provided ecological reference scenarios. Though a case study, the paper's methodology is rather general and can be applied to any model and forest ecosystem.Methods of sensitivity analysis revealed that only a small number of model parameters is crucial for forming spatial variability. Particularly important is the range of competition between trees; with increasing range the variability increases. Growth processes have considerable importance particularly with short observation periods and in young forests, whereas mortality processes become more influential in the long-term. Naturally, these statements depend upon the initial structure and on the length of the observation period.     

Application of a coupled ecosystem-chemical equilibrium model, DayCent-Chem, to stream and soil chemistry in a Rocky Mountain watershed

Atmospheric deposition of sulfur and nitrogen species have the potential to acidify terrestrial and aquatic ecosystems, but nitrate and ammonium are also critical nutrients for plant and microbial productivity. Both the ecological response and the hydrochemical response to atmospheric deposition are of interest to regulatory and land management agencies. We developed a non-spatial biogeochemical model to simulate soil and surface water chemistry by linking the daily version of the CENTURY ecosystem model (DayCent) with a low temperature aqueous geochemical model, PHREEQC. The coupled model, DayCent-Chem, simulates the daily dynamics of plant production, soil organic matter, cation exchange, mineral weathering, elution, stream discharge, and solute concentrations in soil water and stream flow. By aerially weighting the contributions of separate bedrock/talus and tundra simulations, the model was able to replicate the measured seasonal and annual stream chemistry for most solutes for Andrews Creek in Loch Vale watershed, Rocky Mountain National Park. Simulated soil chemistry, net primary production, live biomass, and soil organic matter for forest and tundra matched well with measurements. This model is appropriate for accurately describing ecosystem and surface water chemical response to atmospheric deposition and climate change.     

Integrated model projections of climate change impacts on a North American lake

Climate change is likely to impact terrestrial and aquatic ecosystems via numerous physical and biological mechanisms. This study outlines a framework for projecting potential impacts of climate change on lakes using linked environmental models. Impacts of climate drivers on catchment hydrology and thermal balance in Onondaga Lake (New York State) are simulated using mechanistic models HSPF and UFILS4. Outputs from these models are fed into a lake ecosystem model, developed in AQUATOX. Watershed simulations project increases in the magnitude of peak flows and consequent increases in catchment nutrient export as the magnitude of extreme precipitation events increases. This occurs concurrently with a decrease in annual stream discharge as a result of increased evapotranspiration. Simulated lake water temperatures increase by as much as 5 °C during the 2040-2069 time period, accompanied by a prolonging of the duration of summer stratification. Projected changes include shifts in the timing of nutrient cycling between lake sediments and water column. Plankton taxa projected to thrive under climate change include green algae and Bosmina longirostris. Responses for species at higher trophic levels are mixed. Benthic macroinvertebrates may either prosper (zebra mussels) or decline (chironomids), while fish (e.g., gizzard shad) exhibit high seasonal variability without any clear trend.     

Development of the gap model ZELIG-CFS to predict the dynamics of North American mixed forest types with complex structures

When the development of gap models began about three decades ago, they became a new category of forest productivity models. Compared with traditional growth and yield models, which aim at deriving empirical relationships that best fit data, gap models use semi-theoretical relationships to simulate biotic and abiotic processes in forest stands, including the effects of photosynthetic active radiation interception, site fertility, temperature and soil moisture on tree growth and seedling establishment. While growth and yield models are appropriate to predict short-term stemwood production, gap models may be used to predict the natural course of species replacement for several generations. Because of the poor availability of historical data and knowledge on species-specific allometric relationships, species replacement and death rate, it has seldom been possible to develop and evaluate the most representative algorithms to predict growth and mortality with a high degree of accuracy. For this reason, the developers of gap models focused more on developing simulation tools to improve the understanding of forest succession than predicting growth and yield accurately.In a previous study, the predictions of simulations in two southeastern Canadian mixed ecosystem types using the ZELIG gap model were compared with long-term historical data. This exercise highlighted model components that needed modifications to improve the predictive capacity of ZELIG. The updated version of the model, ZELIG-CFS, includes modifications in the modelling of crown interaction effects, survival rate and regeneration. Different algorithms representing crown interactive effects between crowns were evaluated and species-specific model components that compute individual-tree mortality probability rate were derived. The results of the simulations were compared using long-term remeasurement data obtained from sample plots located in La Mauricie National Park of Canada in Quebec. In the present study, three forest types were studied: (1) red spruce-balsam fir-yellow birch, (2) yellow birch-sugar maple-balsam fir, and (3) red spruce-balsam fir-white birch mixed ecosystems. Among the seven algorithms that represented individual crown interactions, two better predicted the changes in basal area and individual-tree growth: (1) the mean available light growing factor (ALGF), which is computed from the proportion of light intercepted at different levels of individual crowns adjusted by the species-specific shade tolerance index, and (2) the ratio of mean ALGF to crown width. The long-term predicted patterns of change in basal area were consistent with the life history of the different species.     

陆地生态系统臭氧干沉降的观测和模拟研究进展

近地层臭氧(O³)会对植物的生长和产量均产生一定的负效应。由于人类活动引起的不断升高的近地层O³浓度已经威胁到世界粮食安全。O³主要以干沉降的方式沉降到陆地生态系统,所以需要定量确定陆地生态系统中O³通量、干沉降速率和不同沉降通道的沉降过程,预测其对植物的潜在影响。介绍了目前O³干沉降的主要观测方法及其模拟模型,从4个方面(O³通量和干沉降速率的季节变化、日变化、气象因子等对O³干沉降的影响、不同O³沉降通道的沉降过程)重点评述了不同陆地生态系统O³干沉降观测和模拟的研究进展现状,并对未来的研究工作进行了展望,以期为我国未来开展相关研究工作提供借鉴。     

陆地生态系统臭氧干沉降的观测和模拟研究进展

近地层臭氧(O_3)会对植物的生长和产量均产生一定的负效应。由于人类活动引起的不断升高的近地层O_3浓度已经威胁到世界粮食安全。O_3主要以干沉降的方式沉降到陆地生态系统,所以需要定量确定陆地生态系统中O_3通量、干沉降速率和不同沉降通道的沉降过程,预测其对植物的潜在影响。介绍了目前O_3干沉降的主要观测方法及其模拟模型,从4个方面(O_3通量和干沉降速率的季节变化、日变化、气象因子等对O_3干沉降的影响、不同O_3沉降通道的沉降过程)重点评述了不同陆地生态系统O_3干沉降观测和模拟的研究进展现状,并对未来的研究工作进行了展望,以期为我国未来开展相关研究工作提供借鉴。     

Increased spatial variance accompanies reorganization of two continental shelf ecosystems

Phase transitions between alternate stable states in marine ecosystems lead to disruptive changes in ecosystem services, especially fisheries productivity. We used trawl survey data spanning phase transitions in the North Pacific (Gulf of Alaska) and the North Atlantic (Scotian Shelf) to test for increases in ecosystem variability that might provide early warning of such transitions. In both time series, elevated spatial variability in a measure of community composition (ratio of cod [Gadus sp.] abundance to prey abundance) accompanied transitions between ecosystem states, and variability was negatively correlated with distance from the ecosystem transition point. In the Gulf of Alaska, where the phase transition was apparently the result of a sudden perturbation (climate regime shift), variance increased one year before the transition in mean state occurred. On the Scotian Shelf, where ecosystem reorganization was the result of persistent overfishing, a significant increase in variance occurred three years before the transition in mean state was detected. However, we could not reject the alternate explanation that increased variance may also have simply been inherent to the final stable state in that ecosystem. Increased variance has been previously observed around transition points in models, but rarely in real ecosystems, and our results demonstrate the possible management value in tracking the variance of key parameters in exploited ecosystems.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

湿地生态系统硅生物地球化学循环研究进展

硅在地壳中的丰度仅次于氧,是地球表面大多数土壤和岩石的一种基本成分,也是水生植物（特别是硅藻类）以及多种作物生长所必需的营养元素,还是控制陆地、海洋、沿海和内陆水生态系统机能的重要营养元素。目前关于全球硅的生物地球化学循环的研究多集中在陆地和海洋两大生态系统,而湿地生态系统中硅的循环过程、储存量尚不清楚。虽然在河口湿地开展一些关于硅的相关研究,但是硅在湿地的循环机制研究不够全面,尤其相比碳、氮、磷等元素,硅素研究甚少。而且,国内关于硅的相关研究更为匮乏。本文在总结国内外关于湿地生态系统硅素研究的基础上,综述硅在湿地生态系统的存在形态与分布特征,阐述硅在湿地生态系统中的基本循环过程,列举影响硅在湿地生态系统中循环的主要因素,如：湿地类型、水淹时间、季节变化、人类干扰等;提出在今后研究工作中应进一步探索硅在湿地生态系统中迁移、转化的机制,加深研究人类活动对湿地生态系统硅循环的影响,特别是应该加强研究河口潮汐湿地和沿海湿地生态系统硅的生物地球化学循环过程和储存量,有助于明确湿地生态系统对于硅的截留量;并弄清湿地中碳与硅含量之间的关系,从水文学角度分析湿地中排水、蒸发、洪期及滞留时间等因素对硅循环的影响,从而试图建立湿地硅循环模型,有助于预测湿地生态系统硅循环对沿海地区赤潮等富营养化现象和全球气候变化的影响。     

One Hundred Questions of Importance to the Conservation of Global Biological Diversity

Abstract:  We identified 100 scientific questions that, if answered, would have the greatest impact on conservation practice and policy. Representatives from 21 international organizations, regional sections and working groups of the Society for Conservation Biology, and 12 academics, from all continents except Antarctica, compiled 2291 questions of relevance to conservation of biological diversity worldwide. The questions were gathered from 761 individuals through workshops, email requests, and discussions. Voting by email to short-list questions, followed by a 2-day workshop, was used to derive the final list of 100 questions. Most of the final questions were derived through a process of modification and combination as the workshop progressed. The questions are divided into 12 sections: ecosystem functions and services, climate change, technological change, protected areas, ecosystem management and restoration, terrestrial ecosystems, marine ecosystems, freshwater ecosystems, species management, organizational systems and processes, societal context and change, and impacts of conservation interventions. We anticipate that these questions will help identify new directions for researchers and assist funders in directing funds.     

A simulation model to explore the response of the Gulf of Maine food web to large-scale environmental and ecological changes

A dynamic simulation model was constructed using outputs from a balanced Gulf of Maine (GOM) energy budget model as the initial parameter set. The model was structured to provide a recipient control set of dynamics, largely based off of flows to and from different biological groups. The model was used to produce Monte Carlo simulations that were compared (percent change in biomass) with basecase simulations for a variety of scenarios. Changes in primary production, large increases in pelagic and demersal fish biomass, increases in fishing mortality, and large increases in top predators such as baleen whales and pinnepids were simulated. These scenarios roughly simulated the potential impacts of climate change, altered fishing pressure, additional protected species mitigations, and combinations thereof. Results suggest that the GOM system is primarily influenced by bottom-up processes involving phytoplankton, zooplankton, and bacterial biomass. Pelagic and demersal fish were important in determining trends in some of the scenarios. Marine mammals, large pelagic fish, and seabirds have a minor role in the GOM system in terms of biomass flows among the ecosystem components. The system is resilient to large-scale change due, in part to many predator–prey linkages. However, major alterations could occur from sustained climate change, high fishing rates, and by combinations of these types of external forcing mechanisms.