Search

Ecological forecasting is an emerging approach to estimate the future state of an ecological system with uncertainty, allowing society to better manage ecosystem services. Ecological forecasting is a core mission of the U.S. National Ecological Observatory Network (NEON) and several federal agencies, yet, to date, forecasting training has focused on graduate students, representing a gap in undergraduate ecology curricula. In response, we developed a teaching module for the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration; MacrosystemsEDDIE.org) educational program to introduce ecological forecasting to undergraduate students through an interactive online tool built with R Shiny. To date, we have assessed this module, “Introduction to Ecological Forecasting,” at ten universities and two conference workshops with both undergraduate and graduate students (N = 136 total) and found that the module significantly increased undergraduate students’ ability to correctly define ecological forecasting terms and identify steps in the ecological forecasting cycle. Undergraduate and graduate students who completed the module showed increased familiarity with ecological forecasts and forecast uncertainty. These results suggest that integrating ecological forecasting into undergraduate ecology curricula will enhance students’ abilities to engage and understand complex ecological concepts. Published version

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001-2017) of eddy-covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter-annual variability (IAV). The forest was a mean annual carbon sink (252 [+/- 42] gC m-2a-1), and NEP increased at rate +6.4-7.0 gC m-2a-1 (or ca. +2.5% a-1) during the period. This was attributed to the increasing gross-primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a-1, and increase in GPP and NEP outside the main growing season contributed ca. one-third and one-fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long-term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi-layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30-40% of the observed ecosystem GPP increase could be attributed to CO2. The increasing trend in leaf-area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid-rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

While, quantifying trophic interactions is a critical path to understanding and forecasting ecosystem functioning, fitting trophic models to field data remains challenging. It requires flexible statistical tools to combine different sources of information from the literature and fieldwork samples. We present EcoDiet, a hierarchical Bayesian modeling framework to simultaneously estimate food-web topology and diet composition of all consumers in the food web, by combining (i) a priori knowledge from the literature on both food-web topology and diet proportions; (ii) stomach content analyses, with frequencies of prey occurrence used as the primary source of data to update the prior knowledge on the topological food-web structure; (iii) and biotracers data through a mixing model (MM). Inferences are derived in a Bayesian probabilistic rationale that provides a formal way to incorporate prior information and quantifies uncertainty around both the topological structure of the food web and the dietary proportions. EcoDiet was implemented as an open-source R package, providing a user-friendly interface to execute the model as well as examples and guidelines to familiarize with its use. We used simulated data to demonstrate the benefits of EcoDiet and how the framework can improve inferences on diet matrix by comparison with classical network MM. We applied EcoDiet to the Celtic Sea ecosystem, and showed how combining multiple data types within an integrated approach provides a more robust and holistic picture of the food-web topology and diet matrices than the literature or classical MM approach alone. EcoDiet has the potential to become a reference method for building diet matrices as a preliminary step of ecosystem modeling and to improve our understanding of prey-predator interactions.

Ecosystem process models can be used to predict forest response to disturbances at a range of scales. Selection of the spatial class of model should depend on the scale of the research or management question, and model type should depend on the ecosystem attributes of interest. In some cases, multiple classes of models could be used to address a single research question, with evaluations at each scale having potential benefits and drawbacks. This study examines two classes of models relative to how fire return intervals impact carbon and species dynamics in a southeastern U.S. pineland. A model that can be run as a global class model (ED) and a landscape class model (LANDIS‐II) were parameterized with species inventory data from an experimental Pinus Palustris (longleaf pine) forest in southwest Georgia, and simulations were calibrated with literature values, then validated with eddy‐covariance data from the study site. A variety of fire scenarios that included prescribed fire with a 2‐yr return interval, fire exclusion, and three wildfire scenarios (20‐, 50‐, and 100‐yr return intervals) were used for model runs. Results were compared and evaluated with regard to ecosystem carbon and species dynamics. Both models illustrated that prescribed fire provided the greatest carbon sequestration potential and most stable aboveground biomass through time when compared to the wildfire scenarios. The fire exclusion scenario for LANDIS‐II was the only scenario where prescribed fire did not provide the greatest carbon sequestration potential. However, fire exclusion on the order of centuries was a condition of this outcome and the occurrence of such long fire‐free periods is considered unrealistic in this fire‐prone landscape. Differences between models were primarily the result of the underlying characteristics of each model class, namely the spatial resolution and number of species included. In the end, two vastly different scale models supported the conclusion that high frequency prescribed fire in southeastern U.S. pinelands stabilizes carbon and maintains species composition in an ecosystem that is a known ecological hotspot.

Premise The point‐intercept method is one of the most commonly used approaches to measure species cover in ecosystems worldwide. In this approach, multiple points are sampled for presence/absence of a species, and the number of present points divided by the total number of sampled points provides an estimate of percent cover. Our purpose is to mathematically analyze the accuracy of the point‐intercept approach and establish guidelines for its use. Methods We developed formulas that analyze the point‐intercept method and confirmed their effectiveness using simulations. Results We find that a point‐intercept spacing of at least 80% of the largest plant diameter provides the most reliable results. We present a user‐friendly spreadsheet that calculates the number of intercepts needed for fieldwork, as well as the standard deviation, expected deviation, and confidence interval of the collected data. Discussion We provide a variety of guidelines for establishing field protocols based on our results, including dealing with rare species and combining results for multiple species. Quadrat characteristics (intercept spacing, number of point intercepts) can now be easily calculated to guide research design prior to fieldwork; after fieldwork is complete, the accuracy of this technique can (and should) be reported in all future ecological studies in which it is used.

Management strategy evaluation (MSE) is a simulation approach that serves as a “light on the hill” (Smith, 1994) to test options for marine management, monitoring, and assessment against simulated ecosystem and fishery dynamics, including uncertainty in ecological and fishery processes and observations. MSE has become a key method to evaluate trade-offs between management objectives and to communicate with decision makers. Here we describe how and why MSE is continuing to grow from a single species approach to one relevant to multi-species and ecosystem-based management. In particular, different ecosystem modeling approaches can fit within the MSE process to meet particular natural resource management needs. We present four case studies that illustrate how MSE is expanding to include ecosystem considerations and ecosystem models as ‘operating models’ (i.e., virtual test worlds), to simulate monitoring, assessment, and harvest control rules, and to evaluate tradeoffs via performance metrics. We highlight United States case studies related to fisheries regulations and climate, which support NOAA’s policy goals related to the Ecosystem Based Fishery Roadmap and Climate Science Strategy but vary in the complexity of population, ecosystem, and assessment representation. We emphasize methods, tool development, and lessons learned that are relevant beyond the United States, and the additional benefits relative to single-species MSE approaches.

The 5G technology allows telecommunication operators to provide services beyond data broadband for consumers, employing tailored use-cases for enterprise and vertical markets. As a result, there is an increasing need for a collaborative service development through a de-centralized value-chain, along with new business models and shorter time-to-market. In this paper, a novel, use-case driven framework for a modular 5G service design and delivery is proposed. The framework implements agile and as-a-service principles to provide 5G use-case customers access not only to service usage, but also to design and operation. The framework integrates with the $3^{\mathrm {rd}}$ Generation Partnership Project (3GPP) specifications by mapping network-slicing procedures to the designed ecosystem lifecycle operations. The framework allows for the any-technology deployment, utilizing the available foundations for domain-specific automation. A structured collaboration between a 5G operator and a use-case user allows for the customization and improvement of the targeted use-case, where 5G network assets are updated with customer’s vertical components through programmable user-stories. Laboratory testing of a 5G network-slicing for a private-telephony and merchandise-tracking service is performed to validate the effectiveness of the proposed approach for real-world applications.

Coastal erosion and wetland loss are affecting Louisiana to such an extent that the loss of land between 1932 and 2016 was close to 5,000 km2. To mitigate this decline, coastal protection and restoration projects are being planned and implemented by the State of Louisiana, United States. The Louisiana Coastal Master Plan (CMP) is an adaptive management approach that provides a suite of projects that are predicted to build or maintain land and protect coastal communities. Restoring the coast with this 50-year large-scale restoration and risk reduction plan has the potential to change the biomass and distribution of economically and ecologically important fisheries species in this region. However, not restoring the coast may have negative impacts on these species due to the loss of habitat. This research uses an ecosystem model to evaluate the effects of plan implementation versus a future without action (FWOA) on the biomass and distribution of fisheries species in the estuaries over 50 years of model simulations. By simulating effects using a spatially-explicit ecosystem model, not only can the changes in biomass in response to plan implementation be evaluated, but also the distribution of species in response to the planned restoration and risk reduction projects. Simulations are performed under two relative sea level rise (SLR) scenarios to understand the effects of climate change on project performance and subsequent fisheries species biomass and distribution. Simulation output of eight economically important fisheries species shows that the plan mostly results in increases in species biomass, but that the outcomes are species-specific and basin-specific. The SLR scenario highly affects the amount of wetland habitat maintained after 50 years (with higher levels of wetland loss under increased SLR) and, subsequently, the biomass of species depending on that habitat. Species distribution results can be used to identify expected changes for specific species on a regional basis. By making this type of information available to resource managers, precautionary measures of ecosystem management and adaptation can be implemented.

Design, sampling and data interpretation constitute an important challenge for wildlife surveillance of avian influenza viruses (AIV). The aim of this study was to construct a model to improve and enhance identification in both different periods and locations of avian species likely at high risk of contact with AIV in a specific wetland. This study presents an individualbased stochastic model for the Ebre Delta as an example of this appliance. Based on the Monte-Carlo method, the model simulates the dynamics of the spread of AIV among wild birds in a natural park following introduction of an infected bird. Data on wild bird species population, apparent AIV prevalence recorded in wild birds during the period of study, and ecological information on factors such as behaviour, contact rates or patterns of movements of waterfowl were incorporated as inputs of the model. From these inputs, the model predicted those species that would introduce most of AIV in different periods and those species and areas that would be at high risk as a consequence of the spread of these AIV incursions. This method can serve as a complementary tool to previous studies to optimize the allocation of the limited AI surveillance resources in a local complex ecosystem. However, this study indicates that in order to predict the evolution of the spread of AIV at the local scale, there is a need for further research on the identification of host factors involved in the interspecies transmission of AIV

Ocean acidification is one the biggest threats to marine ecosystems worldwide, but its ecosystem wide responses are still poorly understood. This study integrates field and experimental data into a mass balance food web model of a temperate coastal ecosystem to determine the impacts of specific OA forcing mechanisms as well as how they interact with one another. Specifically, we forced a food web model of a kelp forest ecosystem near its southern distribution limit in the California large marine ecosystem to a 0.5 pH drop over the course of 50 years. This study utilizes a modeling approach to determine the impacts of specific OA forcing mechanisms as well as how they interact. Isolating OA impacts on growth (Production), mortality (Other Mortality), and predation interactions (Vulnerability) or combining all three mechanisms together leads to a variety of ecosystem responses, with some taxa increasing in abundance and other decreasing. Results suggest that carbonate mineralizing groups such as coralline algae, abalone, snails, and lobsters display the largest decreases in biomass while macroalgae, urchins, and some larger fish species display the largest increases. Low trophic level groups such as giant kelp and brown algae increase in biomass by 16% and 71%, respectively. Due to the diverse way in which OA stress manifests at both individual and population levels, ecosystem-level effects can vary and display nonlinear patterns. Combined OA forcing leads to initial increases in ecosystem and commercial biomasses followed by a decrease in commercial biomass below initial values over time, while ecosystem biomass remains high. Both biodiversity and average trophic level decrease over time. These projections indicate that the kelp forest community would maintain high productivity with a 0.5 drop in pH, but with a substantially different community structure characterized by lower biodiversity and relatively greater dominance by lower trophic level organisms.

Since 2010, the northern Gulf of Mexico (NGoM) has experienced two unique environmental stressors. First, the 2010 Deepwater Horizon oil spill (DWH) impacted a broad range of taxa and habitats and resulted in declines of small demersal reef fish over the study area (88.5–85.5°W and 29–30.5°N). Then, from 2011 to 2014 the invasive Indo-Pacific lionfish (Pterois volitans) underwent exponential population growth, leading to some of the highest densities in their invaded range. The primary objective of this study was to evaluate the effect of these stressors on reef ecosystems, and specifically how invasive lionfish and fishing may have impacted recovery following DWH. Site-specific datasets on fish density and diet composition were synthesized into an Ecopath with Ecosim food web model of a NGoM reef ecosystem. The model consisted of 63 biomass groups and was calibrated to time series of abundance from 2009 to 2016. The model accounted for mortality from the DWH using forcing functions derived from logistic dose-response curves and oil concentrations. Eight stressor scenarios were simulated, representing all combinations of DWH, lionfish, and fishing. Simulated biomass differed across model groups due to singular and cumulative impacts of stressors and direct and indirect effects arising through food web interactions. Species with high exploitation rates were influenced by fishing more than lionfish following DWH. Several small demersal fish groups were predicted to be strongly influenced by either the cumulative effects of lionfish and DWH or by lionfish alone. A second group of small demersal fish benefited in the stressor scenarios due to reduced top-down predation and competition in the combined stressor scenarios. We conclude that lionfish had a major impact on this ecosystem, based on both empirical data and simulation results. This caused slower recoveries following DWH and lower fish biomass and diversity. Additionally, the lack of recovery for some groups in the absence of lionfish suggests system reorganization may be preventing return to a pre-DWH state. We intended for this work to improve our understanding of how temperate reef ecosystems, like those in the NGoM, respond to broad scale stressors and advance the state of applied ecosystem modeling for resource damage assessment and restoration planning.

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems., Key Points Airborne lidar can be used to inform about degradation‐driven changes in structure to vegetation modelsForest degradation typically depletes evapotranspiration and productivity and increases flammabilityExtreme droughts reduce functional differences between degraded and intact tropical forests

Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.

The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO−3 leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO−3 were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep. Financial support. This research has been supported by the Acknowledgements. The authors gratefully acknowledge financial support by the European Commission through the two FP6 integrated projects CarboEurope Integrated Project (project no. GOCE-CT-2003-505572) and NitroEurope Integrated Project (project no. 017841), the FP7 ECLAIRE project (grant agreement no. 282910), and the ABBA COST Action ES0804. We are also thankful for funding from the French GIP-ECOFOR consortium under the F-ORE-T forest observation and experimentation network, as well as from the MDM-2017-0714 Spanish grant. We are grateful to Christian Bernhofer, Robert Clement, Han Dolman, Axel Don, Eric Dufrêne, Damiano Gianelle, Ruediger Grote, Anders Lindroth, John Moncrieff, Dario Papale, Corinna Rebmann and Alex Vermeulen for the data they provided, as well as to Klau-dia Ziemblińska for her comments on the paper. Computer time for EMEP model runs was supported by the Research Council of Norway through the NOTUR project EMEP (NN2890K). Finalization of the paper was supported by the UK Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering national capability. We also wish to thank two anonymous referees for their constructive criticism of the paper.

For the 21st century, carbon cycle models typically project an increase of terrestrial carbon with increasing atmospheric CO2 and a decrease with the accompanying climate change. However, these estimates are poorly constrained, primarily because they typically rely on a limited number of emission and climate scenarios. Here we explore a wide range of combinations of CO2 rise and climate change and assess their likelihood with the climate change responses obtained from climate models. Our results demonstrate that the terrestrial carbon uptake depends critically on the climate sensitivity of individual climate models, representing a large uncertainty of model estimates. In our simulations, the terrestrial biosphere is unlikely to become a strong source of carbon with any likely combination of CO2 and climate change in the absence of land use change, but the fraction of the emissions taken up by the terrestrial biosphere will decrease drastically with higher emissions. (Less)

Recently it has been show that in some ecosystems fast rates of change of environmental drivers may trigger a critical transition, whereas change of the same magnitude but at slower rates would not. So far, few studies describe this phenomenon of rate-induced tipping, while it is important to understand this phenomenon in the light of the ongoing rapid environmental change. Here, we demonstrate rate-induced tipping in a simple model of cyanobacteria with realistic parameter settings. We explain graphically that there is a range of initial conditions at which a gradual increase in environmental conditions can cause a collapse of the population, but only if the change is fast enough. In addition, we show that a pulse in the environmental conditions can cause a temporary collapse, but that is dependent on both the rate and the duration of the pulse. Furthermore, we study whether the autocorrelation of stochastic environmental conditions can influence the probability of inducing rate-tipping. As both the rate of environmental change, and autocorrelation of the environmental variability are increasing in parts of the climate, the probability for rate-induced tipping to occur is likely to increase. Our results imply that, even though the identification of rate sensitive ecosystems in the real world will be challenging, we should incorporate critical rates of change in our ecosystem assessments and management.

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. © 2017 Elsevier Ltd

The response of ecosystems to different magnitudes of climate warming and corresponding precipitation changes during the last few decades may provide an important reference for predicting the magnitude and trajectory of net primary productivity (NPP) in the future. In this study, a process‐based ecosystem model, Carbon Exchange between Vegetation, Soil and Atmosphere (CEVSA), was used to investigate the response of NPP to warming at both national and subregional scales during 1961–2010. The results suggest that a 1.3°C increase in temperature stimulated the positive changing trend in NPP at national scale during the past 50 years. Regardless of the magnitude of temperature increase, warming enhanced the increase in NPP; however, the positive trend of NPP decreased when warming exceeded 2°C. The largest increase in NPP was found in regions where temperature increased by 1–2°C, and this rate of increase also contributed the most to the total increase in NPP in China's terrestrial ecosystems. Decreasing precipitation depressed the positive trend in NPP that was stimulated by warming. In northern China, warming depressed the increasing trend of NPP and warming that was accompanied by decreasing precipitation led to negative changing trends in NPP in large parts of northern China, especially when warming exceeded 2°C. However, warming stimulated the increase in NPP until warming was greater than 2°C, and decreased precipitation helped to increase the NPP in southern China.

This paper examines the structure and dynamics of the marine ecosystem surrounding Haida Gwaii (an archipelago in the southeastern Gulf of Alaska). Based on previous research, a set of improved mass-balanced models was constructed in Ecopath with Ecosim (EwE) to represent ecosystem states existing circa 1900, 1950, and currently. These models feature increased taxonomic and ecological resolution relative to their predecessors across trophic levels and size classes from zooplankton to whales. A more detailed representation of Pacific herring (Clupea pallasii), including its age structure, predators, and prey, was introduced to permit modeling of the ecosystem role of herring as a forage fish, as well as the ecological impacts of herring fisheries. Gross ecosystem structure and herring trophodynamics were compared across ecosystem states using size spectra and ecological indicators, including mixed trophic impacts. The 1950 model was fitted to a comprehensive set of biomass and catch time series. Dynamic ecosystem simulations evaluated the influence of fishing, predation, other natural mortality, and primary productivity trends on ecosystem behavior since 1950, as well as the relative importance of top-down versus bottom-up forcing. Size spectra and ecosystem indicators suggest that the Haida Gwaii ecosystem has not undergone a radical structural shift since 1900, despite heavy exploitation of numerous marine mammals and fish. Moreover, mixed trophic impacts show that herring constitutes an important mid-trophic level node in the food web, participating in complex interactions with many predators, prey, and competitors. Dynamic ecosystem simulations demonstrate that trends in fishing mortality, trophic interactions, and primary productivity (correlated with the Pacific Decadal Oscillation) are all necessary to explain historical Haida Gwaii ecosystem behavior. These interacting drivers yield a mosaic of top-down and bottom-up trophic control for trophic interactions involving herring and throughout the food web. Simulation results also suggest that production of several herring, salmon, and groundfish stocks may have recently become partially decoupled from primary productivity, perhaps due to changes in copepod guild composition. These results also indicate that a biodiversity decline and “fishing down the food web” occurred off Haida Gwaii since 1950. Finally, the fitted 1950 model provides a robust platform for dynamic ecosystem simulations.

Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies., Author summary Mathematical models of population dynamics are an important tool to advance our understanding of ecosystems, which can be relevant for environmental, clinical, and industrial applications. One sanity check for such models is to virtually split a population into two with identical properties – allegorically, we paint half the individuals of the population in a different color. As we do not change the ecological situation, the outcome of the model should not change either; we call this feature clone consistency. We investigated the mathematical properties of clone-consistent models and deduced simple rules for their form. These rules allow to easily check clone consistency in existing models and ensure it when building new ones. The resulting framework can guide researchers in building models for specific ecosystems and in investigating general properties of ecosystems. We showcase our approach by applying it to models for bacterial communities causing urinary-tract infections. We further discuss that clone inconsistency, which occurs in several prominent models, reflects strong, often implicit, assumptions and it is important to check whether these are justified. Such assumptions may diminish the applicability of these models and the generality of results obtained with them.

Modeling tools that can demonstrate possible consequences of strategies designed to operationalize ecosystem-based fisheries management (EBFM) should be able to address tradeoffs over a wide suite of considerations representing the scope of marine management objectives. Coupled ecological-economic modeling, where models for ecological and economic subsystems are linked through their inputs and outputs, allows for quantification of such tradeoffs. Here, we link the harvest output from fishery management scenarios implemented in an end-to-end ecosystem model (Atlantis) to an input–output regional economic model for the Northeast United States to calculate changes in socio-economic indicators, including the consequences of management action for regional sales, wages, and employment. We implement three simple scenarios (maintain, decrease, or increase current fishing effort), and compare model-projected values for systematic and sector-specific indicators. Systematic indicators revealed different ecological and economic outcomes, with large ecological responses and clear tradeoffs among the catch and biomass of species groups. Economic indicators for the region responded similarly to fishery yield; however, changes in total sales did not match those in landed catch. Under increased fishing effort, a lower proportional increase in sales relative to total landed catch arose due to increased yield from lower value species groups. Average fisheries income changed little among scenarios, but was highest when effort was maintained at current levels, likely a reflection of fleet and catch stability. Our results serve to demonstrate that consequences of management may be felt disproportionately among species through the region and across different fisheries sectors. With our coupled modeling approach of passing Atlantis ecosystem model outputs to an input–output economic model, we were able to assess effects of fisheries management across a broader suite of indicators that have relevance for policymakers across multiple objectives.

Interannual variability (IAV) in net ecosystem carbon production (NEP) plays an important role in the processes of the carbon cycle, but the long-term trends in NEP and the climatic and biotic control of IAV in NEP still remain unclear in agroecosystems. We investigated interannual variability in NEP, expressed as annual values and anomalies, and its climatic and biotic controls using an eddy-covariance dataset for 2005–2018 for rain-fed spring maize in northeastern China. Average annual NEP was 270±31 g C m−2yr −1, with no significant changes over time. The effects on interannual variability in NEP of gross ecosystem productivity (GEP) that was mainly controlled by soil water content (SWC) and leaf area index (LAI), were more than those of respiration (RE) that was controlled by temperature and LAI. Further, maximum daily NEP (NEPmax) that was dominated by summer vapor pressure deficit explained the largest fraction of annual anomalies in NEP, followed by carbon dioxide uptake period (CUP) that was defined by the beginning date (BDOY) and the end date (EDOY) of CUP. The variability in BDOY was mainly determined by spring precipitation and the effective accumulated temperature, and the variability in EDOY was determined by autumn precipitation, SWC and LAI. NEP may decrease with declining precipitation in the future due to decreasing GEP, NEPmax, or CUP, and irrigation and residues cover may be useful in efforts to maintain current NEP levels. Our results indicate that interannual variability in NEP in agroecosystems may be more sensitive to changes in water conditions (such as precipitation, SWC and VPD) induced by climate changes, while temperature may be an important indirect factor when VPD is dominated.

We apply the Z-control approach to a generalized predator prey system and consider the specific case of indirect control of the prey population. We derive the associated Z-controlled model and investigate its properties from the point of view of the dynamical systems theory. The key role of the design parameter A. for the successful application of the method is stressed and related to specific dynamical properties of the Z-controlled model. Critical values of the design parameter are also found, delimiting the lambda-range for the effectiveness of the Z-method. Analytical results are then numerically validated by the means of two ecological models: the classical Lotka-Volterra model and a model related to a case study of the wolf wild boar dynamics in the Alta Murgia National Park. Investigations on these models also highlight how the Z-control method acts in respect to different dynamical regimes of the uncontrolled model. (C) 2016 The Authors. Published by Elsevier Inc.

© 2015 Elsevier B.V. The quality of gridded weather and soil datasets is one of the main sources of uncertainty in modeling regional scale land-atmosphere carbon exchange. This uncertainty may be assessed by comparing net ecosystem productivity (NEP) modeled for selected grid cells with these datasets against NEP modeled at representative sites within that grid cell for which detailed site scale measurements of weather and soil are available. In this study, a comprehensive mathematical ecosystem model, ecosys, was used to simulate differences in NEP at six eddy covariance (EC) flux tower sites across North America caused by using inputs for weather and soil extracted from 0.25°×0.25° gridded datasets for the grid cells within which the towers were located vs. those measured at each tower site during years with contrasting weather (cool vs. warm and wet vs. dry). NEP differences attributed to gridded vs. measured model inputs varied among sites when tested against EC-derived values. At some sites (e.g. coastal coniferous site in British Columbia), adverse impacts of summer warming on NEP under contrasting weather in 2001 (cooler) vs. 2004 (warmer) were accurately modeled with both inputs, giving R2with EC NEP values >0.80. At other sites, reduced accuracy in NEP modeled with gridded vs. measured inputs was attributed to shallower soil depth in the gridded soil database. This shallower depth caused site NEP in a boreal deciduous stand in Saskatchewan not to be well simulated in 2001 and 2003, the first and third years of a major drought in central North America, due to early soil drying. At yet other sites, reduced accuracy was attributed to overestimates of soil organic nitrogen (SON) calculated from general soil organic carbon (SOC):SON relationships used in the absence of SON values in the gridded soil database. These overestimates caused excessive productivity to be modeled with gridded inputs at a boreal black spruce site in Quebec with unusually large SOC:SON. Gridded weather and soil inputs that caused such differences in NEP would certainly affect regional and global carbon budget model estimates, and so need to be improved in future large scale model input datasets.

International audience; A sequence of one-year combined state–parameter estimation experiments has been conducted in a North Atlantic and Arctic Ocean configuration of the coupled physical–biogeochemical model HYCOM-NORWECOM over the period 2007–2010. The aim is to evaluate the ability of an ensemble-based data assimilation method to calibrate ecosystem model parameters in a pre-operational setting, namely the production of the MyOcean pilot reanalysis of the Arctic biology. For that purpose, four biological parameters (two phyto- and two zooplankton mortality rates) are estimated by assimilating weekly data such as, satellite-derived Sea Surface Temperature, along-track Sea Level Anomalies, ice concentrations and chlorophyll-a concentrations with an Ensemble Kalman Filter. The set of optimized parameters locally exhibits seasonal variations suggesting that time-dependent parameters should be used in ocean ecosystem models. A clustering analysis of the optimized parameters is performed in order to identify consistent ecosystem regions. In the north part of the domain, where the ecosystem model is the most reliable, most of them can be associated with Longhurst provinces and new provinces emerge in the Arctic Ocean. However, the clusters do not coincide anymore with the Longhurst provinces in the Tropics due to large model errors. Regarding the ecosystem state variables, the assimilation of satellite-derived chlorophyll concentration leads to significant reduction of the RMS errors in the observed variables during the first year, i.e. 2008, compared to a free run simulation. However, local filter divergences of the parameter component occur in 2009 and result in an increase in the RMS error at the time of the spring bloom.

Marine protected areas (MPAs) are valuable tools for marine conservation that aim to limit human impacts on marine systems and protect valuable species or habitats. However, as species distributions shift due to ocean warming, acidification, and oxygen depletion from climate change, the areas originally designated under MPAs may bear little resemblance to their past state. Different approaches have been suggested for coping with species on the move in conservation. Here, we test the effectiveness of different MPA designs, including dynamic, network, and different directional orientations on protecting shifting species under climate change through ecosystem modeling in a theoretical ecosystem. Our findings suggest that dynamic MPAs may benefit some species (e.g., whiting and anchovy) and fishing fleets, and these benefits can inform the design or adaptation of MPAs worldwide. In addition, we find that it is important to design MPAs with specific goals and to account for the effects of released fishing pressure and species interactions in MPA design.

Both costs and benefits must be considered when implementing marine protected areas (MPAs), particularly those associated with fishing effort displaced by potential closures. The Southern Ocean offers a case study in understanding such tradeoffs, where MPAs are actively being discussed to achieve a range of protection and sustainable use objectives. Here, we evaluated the possible impacts of two MPA scenarios on the Antarctic krill (Euphausia superba) fishery and krill-dependent predators in the Scotia Sea, explicitly addressing the displacement of fishing from closed areas. For both scenarios, we employed a minimally realistic, spatially explicit ecosystem model and considered three alternative redistributions of displaced fishing. We projected both MPAs to provide positive outcomes for many krill-dependent predators, especially when closed areas included at least 50–75% of their foraging distributions. Further, differences between the scenarios suggest ways to improve seal and penguin protection in the Scotia Sea. MPA scenarios also projected increases in total fishery yields, but alongside risks of fishing in areas where relatively low krill densities could cause the fishery to suspend operations. The three alternatives for redistributing displaced fishing had little effect on benefits to predators, but did matter for the fishery, with greater differences in overall catch and risk of fishing in areas of low krill density when displaced fishing was redistributed evenly among the open areas. Collectively, results suggest a well-designed MPA in the Scotia Sea may protect krill-dependent predators, even with displaced fishing, and preclude further spatial management of the krill fishery outside the MPA. More broadly, outcomes denote the importance of delineating fishing and predator habitat, spatial scales, and the critical trade-offs inherent in MPA development.

A marine ecosystem box model was developed to reproduce the seasonal variations nutrient concentrations and phytoplankton biomasses in Jiaozhou Bay (JZB) of China. Then, by removing each of the external sources of nutrients (river input, aquaculture, wastewater discharge, and atmospheric deposition) in the model calculation, we quantitatively estimated its influences on nutrient structure and the phytoplankton community. Removing the river input of nutrients enhanced silicate (SIL) limitation to diatoms (DIA) and decreased the ratio of DIA to flagellates (FLA), removing the aquaculture input of nutrients decreased FLA biomass because it provided less dissolved inorganic nitrogen (DIN) but more dissolved inorganic phosphate (DIP) as compared to the Redfield ratio, removing the wastewater input of nutrients changed the DIN concentration dramatically, but had a relatively weaker impact on the phytoplankton community than removing the aquaculture input, removing atmospheric deposition had a negligible influence on the model results. Based on these results, we suppose that the change in the external nutrients sources in the past several decades can explain the long-term variations in nutrient structure and phytoplankton community. Actually, the simulations for the 1960s, 1980s, and 2000s in JZB demonstrated the shift of limiting nutrients from DIP to SIL. A reasonable scenario for this is the decrease in riverine SIL and increase in DIP from aquaculture that has reduced DIA biomass, promoted the growth of FLA, and led to the miniaturization of the phytoplankton.

Using end-to-end models for ecosystem-based management requires knowledge of the structure, uncertainty and sensitivity of the model. The Norwegian and Barents Seas (NoBa) Atlantis model was implemented for use in ‘what if’ scenarios, combining fisheries management strategies with the influences of climate change and climate variability. Before being used for this purpose, we wanted to evaluate and identify sensitive parameters and whether the species position in the foodweb influenced their sensitivity to parameter perturbation. Perturbing recruitment, mortality, prey consumption and growth by +/- 25% for nine biomass-dominating key species in the Barents Sea, while keeping the physical climate constant, proved the growth rate to be the most sensitive parameter in the model. Their trophic position in the ecosystem (lower trophic level, mid trophic level, top predators) influenced their responses to the perturbations. Top-predators, being generalists, responded mostly to perturbations on their individual life-history parameters. Mid-level species were the most vulnerable to perturbations, not only to their own individual life-history parameters, but also to perturbations on other trophic levels (higher or lower). Perturbations on the lower trophic levels had by far the strongest impact on the system, resulting in biomass changes for nearly all components in the system. Combined perturbations often resulted in non-additive model responses, including both dampened effects and increased impact of combined perturbations. Identifying sensitive parameters and species in end-to-end models will not only provide insights about the structure and functioning of the ecosystem in the model, but also highlight areas where more information and research would be useful—both for model parameterization, but also for constraining or quantifying model uncertainty.

Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. Thus, we suggest that disagreements among the ecosystem models will not impede their use for providing strategic advice on how to reach management objectives that go beyond the traditional maximum yield targets and for informing on the potential consequences of pursuing such objectives. This is especially true for scenarios aiming at exploiting forage fish sprat and herring, for which the agreement was the largest among our models. However, the quantitative response to altering fishing pressure differed among models. This was due to the diverse environmental covariates and the different number of trophic relationships and their functional forms considered in the models. This suggests that ecosystem models can be used to provide quantitative advice only after more targeted research is conducted to gain a deeper understanding into the relationship between trophic links and fish population dynamics in the Baltic Sea.

Increasing vapor pressure deficit (VPD) increases atmospheric demand for water. While increased evapotranspiration (ET) in response to increased atmospheric demand seems intuitive, plants are capable of reducing ET in response to increased VPD by closing their stomata. We examine which effect dominates the response to increasing VPD: atmospheric demand and increases in ET or plant response (stomata closure) and decreases in ET. We use Penman‐Monteith, combined with semiempirical optimal stomatal regulation theory and underlying water use efficiency, to develop a theoretical framework for assessing ET response to VPD. The theory suggests that depending on the environment and plant characteristics, ET response to increasing VPD can vary from strongly decreasing to increasing, highlighting the diversity of plant water regulation strategies. The ET response varies due to (1) climate, with tropical and temperate climates more likely to exhibit a positive ET response to increasing VPD than boreal and arctic climates; (2) photosynthesis strategy, with C3 plants more likely to exhibit a positive ET response than C4 plants; and (3) plant type, with crops more likely to exhibit a positive ET response, and shrubs and gymniosperm trees more likely to exhibit a negative ET response. These results, derived from previous literature connecting plant parameters to plant and climate characteristics, highlight the utility of our simplified framework for understanding complex land‐atmosphere systems in terms of idealized scenarios in which ET responds to VPD only. This response is otherwise challenging to assess in an environment where many processes coevolve together., Key Points We derive a simplified analytical model for ecosystem‐scale evapotranspiration response to changes in vapor pressure deficitEcosystems exhibit a range of behavior, from reductions to increases in evapotransipration, in response to increasing vapor pressure deficitThe choice of stomatal conductance model fundamentally alters the relationship between evapotranspiration and vapor pressure deficit

We have developed a mechanistic model of aquatic microbial metabolism and growth, where we apply fundamental ecological theory to simulate the simultaneous influence of multiple potential metabolic reactions on system biogeochemistry. Software design was based on an anticipated cycle of adaptive hypothesis testing, requiring that the model implementation be highly modular, quickly extensible, and easily coupled with hydrologic models in a shared state space. Model testing scenarios were designed to assess the potential for competition over dissolved organic carbon, oxygen, and inorganic nitrogen in simulated batch reactors. Test results demonstrated that the model appropriately weights metabolic processes according to the amount of chemical energy available in the associated biochemical reactions, and results also demonstrated how simulated carbon, nitrogen, and sulfur dynamics were influenced by simultaneous microbial competition for multiple resources. This effort contributes an approach to generalized modeling of microbial metabolism that will be useful for a theoretically and mechanistically principled approach to biogeochemical analysis.

Katherine Possin and colleagues report on the implementation, development, and early findings of the Care Ecosystem, an adaptive, personalized, and scalable dementia care program.

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes. Funding for this research was provided by NSF DEB EF-1340270 and the Climate Mitigation Initiative at the Princeton Environmental Institute, Princeton University. SL acknowledges financial support from the China Scholarship Council (CSC). VRD acknowledges funding from Ramón y Cajal fellowship (RYC-2012-10970). BTW was supported by the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. DJC acknowledges funding from the National Science Centre, Poland (NN309 713340). WRLA was supported in part by NSF DEB 1714972.

Technology evolution describes a change in a technology performance over time. The modeling of technology evolution is crucial for designers, entrepreneurs, and government officials to set reasonable R&D targets, invest in promising technology, and develop effective incentive policies. Scientists and engineers have developed several mathematical functions such as logistic function and exponential function (Moore's Law) to model technology evolution. However, these models focus on how a technology evolves in isolation and do not consider how the technology interacts with other technologies. Here, we extend the Lotka-Volterra equations from community ecology to model a technology ecosystem with system, component, and fundamental layers. We model the technology ecosystem of passenger aircraft using the Lotka-Volterra equations. The results show limited trickle-down effect in the technology ecosystem, where we refer to the impact from an upper layer technology to a lower layer technology as a trickle-down effect. The limited trickle-down effect suggests that the advance of the system technology (passenger aircraft) is not able to automatically promote the performance of the component technology (turbofan aero-engine) and the fundamental technology (engine blade superalloy) that constitute the system. Our research warns that it may not be effective to maintain the prosperity of a technology ecosystem through government incentives on system technologies only. Decision makers should consider supporting the innovations of key component or fundamental technologies.

Benthic--pelagic coupling plays a pivotal role in aquatic ecosystems but the effects of fishery driven interactions on its functioning has been largely overlooked. Disentangling the benthic--pelagic links including effects of mixed fisheries, however, needs sketching a whole description of ecosystem interactions using quantitative tools. A holistic food web model has been here developed in order to understand the interplay between the benthicpelagic coupling and mixed fisheries in a Mediterranean system such as the Strait of Sicily. The reconstruction of the food web required review and integration of a vast set of local and regional biological information from bacteria to large pelagic species that were aggregated into 72 functional groups. Fisheries were described by 18 fleet segments resulting from combination of fishing gears and fishing vessel size. The input-output analysis on the food web of energy pathways allowed identifying effects of biological and fishery components. Results showed that the structure of the Strait of Sicily food web is complex. Similarly to other Mediterranean areas, the food web of the Strait of Sicily encompasses 4.5 trophic levels (TLs) with the highest TLs reached by bluefin tuna, swordfish and large hake and largely impacted by bottom trawling and large longline. Importantly, benthic-pelagic coupling is affected by direct and indirect impacts among groups of species, fleets and fleets-species through the whole trophic spectrum of the food web. Moreover, functional groups able to move on large spatial scales or life history of which is spent between shelf and slope domains play a key role in linking subsystems together and mediate interactions in the Mediterranean mixed fisheries.

Ocean acidification (OA) results in reduced seawater pH and aragonite saturation state (Ωarag), but also reduced seawater buffer capacity. As buffer capacity decreases, diel variation in seawater chemistry increases. However, a variety of ecosystem feedbacks can modulate changes in both average seawater chemistry and diel seawater chemistry variation. Here we model these effects for a coastal, reef flat ecosystem. We show that an increase in offshore pCO2 and temperature (to 900 µatm and + 3 °C) can increase diel pH variation by as much as a factor of 2.5 and can increase diel pCO2 variation by a factor of 4.6, depending on ecosystem feedbacks and seawater residence time. Importantly, these effects are different between day and night. With increasing seawater residence time and increasing feedback intensity, daytime seawater chemistry becomes more similar to present-day conditions while nighttime seawater chemistry becomes less similar to present-day conditions. Recent studies suggest that carbonate chemistry variation itself, independent of the average chemistry conditions, can have important effects on marine organisms and ecosystem processes. Better constraining ecosystem feedbacks under global change will improve projections of coastal water chemistry, but this study shows the importance of considering changes in both average carbonate chemistry and diel chemistry variation for organisms and ecosystems.

In Europe and around the world, the approach to management of the marine environment has developed from the management of single issues (e.g., species and/or pressures) toward holistic Ecosystem Based Management (EBM) that includes aims to maintain biological diversity and protect ecosystem functioning. Within the European Union, this approach is implemented through the Marine Strategy Framework Directive (MSFD, 2008/56/EC). Integrated Ecosystem Assessment is required by the Directive in order to assess Good Environmental Status (GES). Ecological modeling has a key role to play within the implementation of the MSFD, as demonstrated here by case studies covering a range of spatial scales and a selection of anthropogenic threats. Modeling studies have a strong role to play in embedding data collected at limited points within a larger spatial and temporal scale, thus enabling assessments of pelagic and seabed habitat. Furthermore, integrative studies using food web and ecosystem models are able to investigate changes in food web functioning and biological diversity in response to changes in the environment and human pressures. Modeling should be used to: support the development and selection of specific indicators; set reference points to assess state and the achievement of GES; inform adaptive monitoring programs and trial management scenarios. The modus operandi proposed shows how ecological modeling could support the decision making process leading to appropriate management measures and inform new policy., This manuscript is a result of DEVOTES (DEVelopment Of innovative Tools for understanding marine biological diversity and assessing good Environmental Status) project, funded by the European Union under the 7th Framework Programme, “The Ocean of Tomorrow” Theme (grant agreement no. 308392), www.devotes-project.eu.

We present a comprehensive analysis of estimation of fisheries Maximum Sustainable Yield (MSY) reference points using an ecosystem model built for Mille Lacs Lake, the second largest lake within Minnesota, USA. Data from single-species modelling output, extensive annual sampling for species abundances, annual catch-survey, stomach-content analysis for predatory-prey interactions, and expert opinions were brought together within the framework of an Ecopath with Ecosim (EwE) ecosystem model. An increase in the lake water temperature was observed in the last few decades; therefore, we also incorporated a temperature forcing function in the EwE model to capture the influences of changing temperature on the species composition and food web. The EwE model was fitted to abundance and catch time-series for the period 1985 to 2006. Using the ecosystem model, we estimated reference points for most of the fished species in the lake at single-species as well as ecosystem levels with and without considering the influence of temperature change; therefore, our analysis investigated the trophic and temperature effects on the reference points. The paper concludes that reference points such as MSY are not stationary, but change when (1) environmental conditions alter species productivity and (2) fishing on predators alters the compensatory response of their prey. Thus, it is necessary for the management to re-estimate or re-evaluate the reference points when changes in environmental conditions and/or major shifts in species abundance or community structure are observed.

Climate change will make assessing and managing crop-pest systems in the Mediterranean Basin more difficult than elsewhere on the globe. The Basin is in many ways a hot spot of global change, as higher than average projected climate change threatens an extremely rich and intertwined biological and cultural diversity, and increases its vulnerability to biological invasions. As a consequence, pest problems in this hot spot will require a holistic approach to deconstruct the elusive complex interactions that are the underpinning basis for sound decision making at the field level. Building on 30+ years of multidisciplinary progress inspired by pioneering work at University of California, the ENEA GlobalChangeBiology project in collaboration with CASAS Global is developing an interdisciplinary tool to mechanistically describe (i.e., model), analyze and manage agro-ecological problems based on the unifying paradigm that all organisms including humans acquire and allocate resources by analogous processes – the paradigm of ecological analogies that is holistic by design. Recent analyses using this approach show how the tool provided and will continue to provide governmental agencies with the scientific basis for building eco-social resilience to climate warming into agricultural systems across the Mediterranean Basin and elsewhere.

Predictions of how forest productivity and carbon sequestration will respond to climate change are essential for making forest management decisions and adapting to future climate. However, current predictions can include considerable uncertainty that is not well quantified. To address the need for better quantification of uncertainty, we calculated and compared ecosystem model parameter, ecosystem model process, climate model, and climate scenario uncertainty for predictions of Southeastern U.S. pine forest productivity. We applied a data assimilation using Metropolis-Hastings Markov Chain Monte Carlo to fuse diverse datasets with the Physiological Principles Predicting Growth model. The spatially and temporally diverse data sets allowed for novel constraints on ecosystem model parameters and allowed for the quantification of uncertainty associated with parameterization and model structure (process). Overall, we found that the uncertainty is higher for parameter and process model uncertainty than the climate model uncertainty. We determined that climate change will result in a likely increase in terrestrial carbon storage and that higher emission scenarios increase the uncertainty in our predictions. In addition, we determined regional variations in biomass accumulation due to a response to the change in frost days, temperature, and vapor pressure deficit. Since the uncertainty associated with ecosystem model parameter and process uncertainty was larger than the uncertainty associated with climate predictions, our results indicate that better constraining parameters in ecosystem models and improving the mathematical structure of ecosystem models can improve future predictions of forest productivity and carbon sequestration. Master of Science

End-to-end ecosystem modeling platforms, including OSMOSE, are key tools for informing ecosystem based fisheries management (EBFM). End-to-end models ideally implement two-way interactions between model components, yet two-way interactions between high trophic level (HTL) functional groups and humans (fisheries managers and fishers) are currently missing in OSMOSE. We developed a management strategy evaluation (MSE) framework for OSMOSE, which allows for feedback between HTL functional groups and fisheries managers. This framework couples OSMOSE to a management procedure integrating decision rules and accounting for scientific uncertainty and the acceptable risk of overfishing. We applied the MSE framework to the OSMOSE model of the West Florida Shelf, so as to conduct an evaluation of total allowable catch (TAC) strategies for red grouper (Epinephelus mono) in a context of episodic events of natural mortality. Our simulations indicate that TAC strategies that assume higher scientific uncertainty and/or lower acceptable risk of overfishing result in higher biomass-related metrics for red grouper. However, the levels of scientific uncertainty and acceptable risk of overfishing impose a trade-off between biomass-related and catch-related metrics for red grouper. Our simulations also indicate that updating red grouper TAC more frequently in a context of episodic events of natural mortality does not have a large impact on biomass-related and catch-related metrics for red grouper and other functional groups. The MSE we conducted for red grouper is strategic, and its outcomes, which were obtained under a specific set of assumptions, must be considered preliminary. We discuss how future research could help enhance understanding of the possible impacts of TAC strategies for red grouper. The MSE framework designed for OSMOSE links the dynamics of HTL functional groups to that of fisheries managers, thereby allowing OSMOSE to be better suited for informing EBFM. This framework is an invaluable asset in assessing the performance of fisheries management strategies, but could also be used for other purposes, such as the evaluation of research monitoring programs.

The present study describes the food web and evaluates the effects of a marine pro- tected area (MPA), the Port-Cros National Park (NW Mediterranean Sea), on the marine eco - system inside the reserve and its potential to sustain resources outside the reserve. We built an Ecopath model of the Port-Cros MPA which comprised 41 functional groups and represented an average situation for the period 1998 to 2008. At a high trophic level, fish were dominated by the amberjacks and large dusky grouper groups, 2 abundant top predators playing a central role in the ecosystem in terms of keystone species and trophic cascades. The biomass accumulation rate estimated with Ecopath could reach 10% yr �1 for large dusky groupers, which is consistent with field observations, suggesting that the MPA succeeded in protecting the species. The total export from the MPA was estimated at a maximum of about 100 tons yr �1 , which limits the benefits at a local scale. EcoTroph fishing scenarios showed that the current state of the ecosystem inside the reserve was close to the unexploited state, and that current fishing practices had an insignificant impact. The major effects of the MPA were to protect the high trophic level groups and thus to maintain the functional biodiversity within the reserve. In summary, trophic modeling seems to be a relevant approach to study the effects of MPAs and to improve their management.

cited By (since 1996)5; International audience; The emergy algebra is based on four rules, the use of which is sometimes confusing or reserved only to the experts of the domain. The emergy computation does not obey conservation logic (i.e. emergy computation does not obey Kirchoff-like circuit law). In this paper the authors propose to reformulate the emergy rules into three axioms which provide (i) a rigourous mathematical framework for emergy computation and (ii) an exact recursive algorithm to compute emergy within a system of interconnected processes at steady state modeled by an oriented graph named the emergy graph.Because emergy algebra follows a logic of memorization, the evaluation principles deal with paths in the emergy graph. The underlying algebraic structure is the set of non-negative real numbers operated on by three processes, the maximum (max), addition (+) and multiplication (*). The maximum is associated with the co-product problem. Addition is linked with the split problem or with the independence of two emergy flows. And multiplication is related to the logic of memorization. The axioms describe how to use the different operators max, + and * to combine flows without any confusion or ambiguity. The method is tested on five benchmark emergy examples. © 2012 Elsevier B.V.

A three-dimensional coupled physical-biological model involving variational adjoint assimilation was applied to the Bohai Sea and the North Yellow Sea (BNYS), utilizing real chlorophyll data from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS). The coupled model consists of a simple three-dimensional Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model and a primitive-equation physical model. There are 12 ecological parameters in the NPZD model. All these parameters are assumed to be time-varying. By using the data assimilation technique, the optimal values of these parameter were estimated, and the seasonal variabilities of these parameters were reconstructed. We find that some parameters are highly correlated, and they may have some internal relations. The time variances of most parameters seem reasonable. And the annual cycles of the estimated parameters may help us to improve the performance of the model. The comparison between simulation and observation shows that after assimilation of SeaWiFS data the output of the NPZD model agrees better with the observation.

Quantifying ecosystem services in urban areas is complex. However, existing ecosystem service typologies and ecosystem modeling can provide a means towards understanding some key biophysical links between urban forests and ecosystem services. This project addresses broader concepts of sustainability by assessing the urban park system in Phoenix, Arizona&rsquo, s hot urban climate. This project aims to quantify and demonstrate the multiple ecosystem services provided by Phoenix&rsquo, s green infrastructure (i.e., urban park system), including its air pollution removal values, carbon sequestration and storage, avoided runoff, structural value, and the energy savings it provides for city residents. Modeling of ecosystem services of the urban park system revealed around 517,000 trees within the system, representing a 7.20% tree cover. These trees remove about 3630 tons (t) of carbon (at an associated value of $285,000) and about 272 t of air pollutants (at an associated value of $1.16 million) every year. Trees within Phoenix&rsquo, s urban park system are estimated to reduce annual residential energy costs by $106,000 and their structural value is estimated at $692 million. The findings of this research will increase our knowledge of the value of green infrastructure services provided by different types of urban vegetation and assist in the future design, planning and management of green infrastructure in cities. Thus, this study has implications for both policy and practice, contributing to a better understanding of the multiple benefits of green infrastructure and improving the design of green spaces in hot arid urban climates around the globe.

In this paper the results from a workshop of the OSPAR Intersessional Correspondence Group on Eutrophication Modelling (ICG-EMO) held in Lowestoft in 2007 are presented. The aim of the workshop was to compare the results of a number of North Sea ecosystem models under different reduction scenarios. In order to achieve comparability of model results the participants were requested to use a minimum spin-up time, common boundary conditions which were derived from a wider-domain model, and a set of common forcing data, with special emphasis on a complete coverage of river nutrient loads. Based on the OSPAR requirements river loads were derived, taking into account the reductions already achieved between 1985 and 2002 for each country. First, for the year 2002, for which the Comprehensive Procedure was applied, the different horizontal distributions of net primary production are compared. Furthermore, the differences in the net primary production between the hindcast run and the 50% nutrient reduction runs are displayed. In order to compare local results, the hindcast and reduction runs are presented for selected target areas and scored against the Comprehensive Procedure assessment levels for the parameters DIN, DIP and chlorophyll. Finally, the temporal development of the assessment parameter bottom oxygen concentration from several models is compared with data from the Dutch monitoring station Terschelling 135. The conclusion from the workshop was that models are useful to support the application of the OSPAR Comprehensive Procedure. The comparative exercise formulated specifically for the workshop required models to be evaluated for pre-defined target areas previously classified as problem areas according to the first application of the Comprehensive Procedure. The responsiveness of the modelled assessment parameters varied between different models but in general the parameter showed a larger response in coastal rather than in offshore waters, which in some cases lead to the goal to achieve a non-problem status. Therefore, the application of the Comprehensive Procedure on model results for parameter assessment opens a new potential in testing eutrophication reduction measures within the North Sea catchment. As a result of the workshop further work was proposed to confirm and bolster confidence in the results. One general field of difficulty appeared to be the model forcing with SPM data in order to achieve realistic levels of light attenuation. Finally, effects of the prescribed spin-up procedure are compared against a long-term run over many years and consequences on the resulting initial nutrient concentrations are highlighted. (C) 2010 Elsevier B.V. All rights reserved.

Ecosystem-based fisheries management (EBFM) was developed to move beyond single species management by incorporating ecosystem considerations for the sustainable utilization of marine resources. Due to the wide range of fishery characteristics, including different goals of fisheries management across regions and species, theoretical best practices for EBFM vary greatly. Here we highlight the lack of consensus in the interpretation of EBFM amongst professionals in marine science and its implementation. Fisheries policy-makers and managers, stock assessment scientists, conservationists, and ecologists had very different opinions on the degree to which certain management strategies would be considered EBFM. We then assess the variability of the implementation of EBFM, where we created a checklist of characteristics typifying EBFM and scored fisheries across different regions, species, ecosystems, and fishery size and capacity. Our assessments show fisheries are unlikely to meet all the criteria on the EBFM checklist. Consequentially, it is unnecessary for management to practice all the traits of EBFM, as some may be disparate from the ecosystem attributes or fishery goals. Instead, incorporating some ecosystem-based considerations to fisheries management that are context-specific is a more realistic and useful way for EBFM to occur in practice.

Forest degradation due to land use change is a severe problem in Ethiopian Afromontane Forests. We investigated such degradation effects by comparing degraded agricultural land (previously covered with forest) with neighboring natural forests, 40 to 50 years after conversion. We selected four different study areas to cover the eco-climatic conditions of the Amhara region in Northwestern Ethiopia. For a paired-stand comparison we collected soil data on both land use types. We calculated forest biomass to evaluate the biogeochemical-mechanistic ecosystem model Biome-BGC, which is used as a diagnostic tool to assess the site and management impacts on productivity as well as ecosystem carbon and nitrogen accumulation. We applied Biome-BGC to assess rehabilitation options on such degraded land. Afromontane forests in the highlands of Ethiopia showed high soil C stocks, resulting from long lasting biomass accumulation. Removing the tree cover and converting forest areas to crop- or grassland, has led to a loss of 40–85% of the soil C stocks and thus a loss in soil fertility within only 40 to 50 years. Rehabilitation efforts by replanting trees will improve soil fertility, but may require over a thousand years to achieve a similar level in biomass and soil fertility versus the situation prior to the land use change.

The idea that many processes in arid and semi-arid ecosystems are dormant until activated by a pulse of rainfall, and then decay from a maximum rate as the soil dries, is widely used as a conceptual and mathematical model, but has rarely been evaluated with data. This paper examines soil water, evapotranspiration (ET), and net ecosystem CO2 exchange measured for 5 years at an eddy covariance tower sited in an Acacia–Combretum savanna near Skukuza in the Kruger National Park, South Africa. The analysis characterizes ecosystem flux responses to discrete rain events and evaluates the skill of increasingly complex “pulse models”. Rainfall pulses exert strong control over ecosystem-scale water and CO2 fluxes at this site, but the simplest pulse models do a poor job of characterizing the dynamics of the response. Successful models need to include the time lag between the wetting event and the process peak, which differ for evaporation, photosynthesis and respiration. Adding further complexity, the time lag depends on the prior duration and degree of water stress. ET response is well characterized by a linear function of potential ET and a logistic function of profile-total soil water content, with remaining seasonal variation correlating with vegetation phenological dynamics (leaf area). A 1- to 3-day lag to maximal ET following wetting is a source of hysteresis in the ET response to soil water. Respiration responds to wetting within days, while photosynthesis takes a week or longer to reach its peak if the rainfall was preceded by a long dry spell. Both processes exhibit nonlinear functional responses that vary seasonally. We conclude that a more mechanistic approach than simple pulse modeling is needed to represent daily ecosystem C processes in semiarid savannas. Electronic supplementary material The online version of this article (doi:10.1007/s00442-009-1405-y) contains supplementary material, which is available to authorized users.