Journal articles on the topic 'Large ecosystem models'
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LAWRIE, JOCK. "A METHOD FOR SIMPLIFYING LARGE ECOSYSTEM MODELS." Natural Resource Modeling 21, no. 2 (March 7, 2008): 248–63. http://dx.doi.org/10.1111/j.1939-7445.2008.00011.x.
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Rietkerk, M., V. Brovkin, P. M. van Bodegom, M. Claussen, S. C. Dekker, H. A. Dijkstra, S. V. Goryachkin, et al. "Local ecosystem feedbacks and critical transitions in the climate." Biogeosciences Discussions 6, no. 5 (October 28, 2009): 10121–36. http://dx.doi.org/10.5194/bgd-6-10121-2009.
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Abstract. Global and regional climate models, such as those used in IPCC assessments, are the best tools available for climate predictions. Such models typically account for large-scale land-atmosphere feedbacks. However, these models omit local vegetation-environment feedbacks that are crucial for critical transitions in ecosystems. Here, we reveal the hypothesis that, if the balance of feedbacks is positive at all scales, local vegetation-environment feedbacks may trigger a cascade of amplifying effects, propagating from local to large scale, possibly leading to critical transitions in the large-scale climate. We call for linking local ecosystem feedbacks with large-scale land-atmosphere feedbacks in global and regional climate models in order to yield climate predictions that we are more confident about.
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Meyn, Andrea, Peter S. White, Constanze Buhk, and Anke Jentsch. "Environmental drivers of large, infrequent wildfires: the emerging conceptual model." Progress in Physical Geography: Earth and Environment 31, no. 3 (June 2007): 287–312. http://dx.doi.org/10.1177/0309133307079365.
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Large, infrequent fires (LIFs) can have substantial impacts on both ecosystems and the economy. To better understand LIFs and to better predict the effects of human management and climate change on their occurrence, we must first determine the factors that produce them. Here, we review local and regional literature investigating the drivers of LIFs. The emerging conceptual model proposes that ecosystems can be typified based on climatic conditions that determine both fuel moisture and fuel amount. The concept distinguishes three ecosystem types: (1) biomass-rich, rarely dry ecosystems where fuel moisture rather than fuel amount limits LIFs; (2) biomass-poor, at least seasonally dry ecosystems where fuel amount rather than fuel moisture limits LIFs; and (3) biomass-poor, rarely dry ecosystems where both fuel amount and fuel moisture limit the occurrence of LIFs. Our main goal in this paper is to discuss the drivers of LIFs and the three mentioned ecosystem types in a global context. Further, we will discuss the drivers that are not included within the `fuels' versus `climate' discussion. Finally, we will address the question: what kinds of additional information are needed if models predicting LIFs are to be coupled with global climate models? As with all generalizations, there are local deviations and modifications due to processes such as disturbance interaction or human impact. These processes tend to obscure the general patterns of the occurrence of LIFs and are likely to cause much of the observed controversy and confusion in the literature.
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Lawrie, Jock, and John Hearne. "A method for aggregating state variables in large ecosystem models." Mathematics and Computers in Simulation 79, no. 3 (December 2008): 368–78. http://dx.doi.org/10.1016/j.matcom.2008.01.001.
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Eastaugh, Chris S., and Hubert Hasenauer. "A statistical thinning model for initialising large-scale ecosystem models." Scandinavian Journal of Forest Research 27, no. 6 (September 2012): 567–77. http://dx.doi.org/10.1080/02827581.2012.679679.
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PIETSCH, STEPHAN A., and HUBERT HASENAUER. "Evaluating the self-initialization procedure for large-scale ecosystem models." Global Change Biology 12, no. 9 (July 17, 2006): 1658–69. http://dx.doi.org/10.1111/j.1365-2486.2006.01211.x.
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Thurnher, Christopher, Chris S. Eastaugh, and Hubert Hasenauer. "A thinning routine for large-scale biogeochemical mechanistic ecosystem models." Forest Ecology and Management 320 (May 2014): 56–69. http://dx.doi.org/10.1016/j.foreco.2014.02.028.
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Belo, Ítalo, and Carina Alves. "How to Create a Software Ecosystem? A Partnership Meta-Model and Strategic Patterns." Information 12, no. 6 (June 3, 2021): 240. http://dx.doi.org/10.3390/info12060240.
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Large keystone organizations use partnership models to manage their software ecosystem partners. Although several partnership models have been developed by platform owners, smaller companies willing to create a new ecosystem may experience difficulties to define the appropriate features of partnership models when switching from an independent software product to an ecosystem. This study proposes a partnership meta-model and four strategic patterns to operationalize it. We adopted the Design Science Research (DSR) method. The partnership meta-model was built in the first cycle of DSR, using a Systematic Mapping Study, and validated through case studies of SAP, Eclipse, and Microsoft Azure ecosystems. In the second cycle of DSR, the strategic patterns were defined through a Multivocal Literature Review and validated by using interviews with professionals. The meta-model presents the key characteristics to define partnership models for emerging software ecosystems. The strategic patterns aim to operationalize the meta-model and, consequently, assist the keystone in defining the features that the partnership model will have and select suitable strategies. The meta-model and the strategic patterns help managers creating and evolving software ecosystems from a software product considering the impact of that transition on the partnership model.
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Lippert, Kari J., and Robert Cloutier. "Cyberspace: A Digital Ecosystem." Systems 9, no. 3 (June 26, 2021): 48. http://dx.doi.org/10.3390/systems9030048.
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Cyberspace is a new frontier, not just for hackers, but for engineers. It is a digital ecosystem, the next generation of Internet and network applications, promising a whole new world of distributed and open systems that can interact, self-organize, evolve, and adapt. These ecosystems transcend traditional collaborative environments, such as client-server, peer-to-peer, or hybrid models (e.g., web services), to become a self-organized, evolving, interactive environment. Understanding cyberspace as a system is critical if we are to properly design systems to exist within it. Considering it to be a digital ecosystem, where systems can adapt and evolve, will enable systems engineering to become more effective in the future of networks and the Internet. While most systems engineers have only anecdotal experience with large segments of this ecosystem, in today’s world all of them must come to understand it. Engineering any system, or portion of a system, begins with an understanding of the system. This paper presents two interrelated yet distinct foundational models of the ecosystem of cyberspace: a Systemigram to narrate the cyclical nature of cyber warfare, and a modified predator–prey model, as a mathematical model. Systems engineers can utilize these models to design digital “species” that function and adapt within this ecosystem.
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Angelini, Ronaldo, Angelo Antonio Agostinho, and Luiz Carlos Gomes. "Modeling energy flow in a large Neotropical reservoir: a tool do evaluate fishing and stability." Neotropical Ichthyology 4, no. 2 (June 2006): 253–60. http://dx.doi.org/10.1590/s1679-62252006000200011.
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Recently, there is an increasing perception that the ecosystem approach gives important insights to support fisheries stock assessment and management. This paper aims to quantify energy flows in the Itaipu Reservoir (Brazil) and to simulate increase of the fishing effort of some species, using Ecopath with Ecosim software, which could allow inferences on stability. Therefore, two steady-state Itaipu models were built (1983-87 and 1988-92). Results showed that: a) there are no differences between models, and results on aging trends do not vary over time indicating that fishery does not alter the ecosystem as a whole; b) results of fisheries simulations are approximate to mono-specific stock assessment for the same species and periods; c) many authors believe that tropical ecosystems are environments where biotic and abiotic oscillations are annual and sometimes unexpected, but the results found for the Itaipu Reservoir indicate that stability was met after 16 years.
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Moloney, Coleen L., Astrid Jarre, Hugo Arancibia, Yves-Marie Bozec, Sergio Neira, Jean-Paul Roux, and Lynne J. Shannon. "Comparing the Benguela and Humboldt marine upwelling ecosystems with indicators derived from inter-calibrated models." ICES Journal of Marine Science 62, no. 3 (January 1, 2005): 493–502. http://dx.doi.org/10.1016/j.icesjms.2004.11.009.
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Abstract Large-scale, mass-balance trophic models have been developed for northern and southern regions of both the Benguela and Humboldt upwelling ecosystems. Four of these Ecopath models were compared and calibrated against one another. A common model structure was established, and a common basis was used to derive poorly known parameter values. The four resulting models represent ecosystems in which the main commercial fish species have been moderately to heavily fished: central-southern Chile (1992), northern-central Peru (1973–1981), South Africa (1980–1989), and Namibia (1995–2000). Quantitative ecosystem indicators derived from these models were compared. Indicators based on large flows (involving low trophic levels) or top predators were not well estimated, because of aggregation problems. Many of the indicators could be contrasted on the basis of differences between the Benguela and Humboldt systems, rather than on the basis of fishing impact. These include integrated values relating to total catches, and trophic levels of key species groups. Indicators based on integrated biomass, total production, and total consumption tended to capture differences between the model for Namibia (where fish populations were severely reduced) and the other models. We conclude that a suite of indicators is required to represent ecosystem state, and that interpretation requires relatively detailed understanding of the different ecosystems.
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Loiselle, S., V. Hull, E. Permingeat, M. Falucci, and C. Rossi. "Qualitative models to predict impacts of human interventions in a wetland ecosystem." Web Ecology 3, no. 1 (July 16, 2002): 56–69. http://dx.doi.org/10.5194/we-3-56-2002.
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Abstract. The large shallow wetlands that dominate much of the South American continent are rich in biodiversity and complexity. Many of these undamaged ecosystems are presently being examined for their potential economic utility, putting pressure on local authorities and the conservation community to find ways of correctly utilising the available natural resources without compromising the ecosystem functioning and overall integrity. Contrary to many northern hemisphere ecosystems, there have been little long term ecological studies of these systems, leading to a lack of quantitative data on which to construct ecological or resource use models. As a result, decision makers, even well meaning ones, have difficulty in determining if particular economic activities can potentially cause significant damage to the ecosystem and how one should go about monitoring the impacts of such activities. While the direct impact of many activities is often known, the secondary indirect impacts are usually less clear and can depend on local ecological conditions. The use of qualitative models is a helpful tool to highlight potential feedback mechanisms and secondary effects of management action on ecosystem integrity. The harvesting of a single, apparently abundant, species can have indirect secondary effects on key trophic and abiotic compartments. In this paper, loop model analysis is used to qualitatively examine secondary effects of potential economic activities in a large wetland area in northeast Argentina, the Esteros del Ibera. Based on interaction with local actors together with observed ecological information, loop models were constructed to reflect relationships between biotic and abiotic compartments. A series of analyses were made to study the effect of different economic scenarios on key ecosystem compartments. Important impacts on key biotic compartments (phytoplankton, zooplankton, ichthyofauna, aquatic macrophytes) and on the abiotic environment (nutrients and sediment resuspension) were observed through model analysis. These models results do not indicate a definite relationship between activity and a possible impact, but a potential impact that can be further studied and modelled. Likewise, the model is not intended to be an end in itself, but as a tool to help focus further ecological study, monitoring and modelling. In the real world of wetland management, it is not always possible to conduct extensive (and expensive) analysis of all the principal ecological compartments. In the same manner, the construction of larger and more complex models for resource management usually needs to be focused to those areas most likely to effect resource quality or ecosystem functioning. In this light, the development of qualitative models was considered as a first step to help researchers and decision makers focus their efforts (and economic resources) in an intensive ecological sampling programme and the construction of predictive models.
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Leminen, Seppo, Mervi Rajahonka, Mika Westerlund, and Robert Wendelin. "The future of the Internet of Things: toward heterarchical ecosystems and service business models." Journal of Business & Industrial Marketing 33, no. 6 (July 2, 2018): 749–67. http://dx.doi.org/10.1108/jbim-10-2015-0206.
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Purpose This study aims to understand their emergence and types of business models in the Internet of Things (IoT) ecosystems. Design/methodology/approach The paper builds upon a systematic literature review of IoT ecosystems and business models to construct a conceptual framework on IoT business models, and uses qualitative research methods to analyze seven industry cases. Findings The study identifies four types of IoT business models: value chain efficiency, industry collaboration, horizontal market and platform. Moreover, it discusses three evolutionary paths of new business model emergence: opening up the ecosystem for industry collaboration, replicating the solution in multiple services and return to closed ecosystem as technology matures. Research limitations/implications Identifying business models in rapidly evolving fields such as the IoT based on a small number of case studies may result in biased findings compared to large-scale surveys and globally distributed samples. However, it provides more thorough interpretations. Practical implications The study provides a framework for analyzing the types and emergence of IoT business models, and forwards the concept of “value design” as an ecosystem business model. Originality/value This paper identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry, and argues that IoT business models follow an evolutionary path from closed to open, and reversely to closed ecosystems, and the value created in the networks of organizations and things will be shareable value rather than exchange value.
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Prato, Giulia, Paolo Guidetti, Fabrizio Bartolini, Luisa Mangialajo, and Patrice Francour. "The importance of high-level predators in marine protected area management: Consequences of their decline and their potential recovery in the Mediterranean context." Advances in Oceanography and Limnology 4, no. 2 (November 20, 2013): 176. http://dx.doi.org/10.4081/aiol.2013.5343.
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High-level predators have been depleted in the oceans worldwide following centuries of selective fishing. There is widespread evidence that high-level predators’ extirpation may trigger trophic cascades leading to the degradation of marine ecosystems. Restoration of large carnivores to former levels of abundance might lead to ecosystem recovery, but very few pristine ecosystems are left as baselines for comparison. Marine protected areas (MPAs) can trigger initial rapid increases of high-level predator abundance and biomass. Nevertheless, long term protection is needed before the ecosystem's carrying capacity for large carnivores is approached and indirect effects on lower trophic levels are observed. The Mediterranean is probably very far from its pristine condition, due to a long history of fishing. Today small to medium-sized consumers (e.g. sea breams) are the most abundant predators shaping coastal benthic communities, while historical reconstructions depict abundant populations of large piscivores and sharks inhabiting coastal areas. Mediterranean MPAs are following a promising trajectory of ecosystem recovery, as suggested by a strong gradient of fish biomass increase. Consistent monitoring methods to assess relative variations of high-level predators, together with food-web models aimed at disentangling the indirect effects of their recovery, could be useful tools to help set up appropriate management strategies of MPAs.
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Schnedler-Meyer, Nicolas Azaña, Patrizio Mariani, and Thomas Kiørboe. "The global susceptibility of coastal forage fish to competition by large jellyfish." Proceedings of the Royal Society B: Biological Sciences 283, no. 1842 (November 16, 2016): 20161931. http://dx.doi.org/10.1098/rspb.2016.1931.
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Competition between large jellyfish and forage fish for zooplankton prey is both a possible cause of jellyfish increases and a concern for the management of marine ecosystems and fisheries. Identifying principal factors affecting this competition is therefore important for marine management, but the lack of both good quality data and a robust theoretical framework have prevented general global analyses. Here, we present a general mechanistic food web model that considers fundamental differences in feeding modes and predation pressure between fish and jellyfish. The model predicts forage fish dominance at low primary production, and a shift towards jellyfish with increasing productivity, turbidity and fishing. We present an index of global ecosystem susceptibility to shifts in fish–jellyfish dominance that compares well with data on jellyfish distributions and trends. The results are a step towards better understanding the processes that govern jellyfish occurrences globally and highlight the advantage of considering feeding traits in ecosystem models.
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Yablonsky, Sergey. "A multidimensional platform ecosystem framework." Kybernetes 49, no. 7 (April 3, 2020): 2003–35. http://dx.doi.org/10.1108/k-07-2019-0447.
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Purpose Ecosystems that support digital businesses maximize the economic value of network connections. This forces a shift toward platforms and ecosystems that are collaborative by nature by applying business models with multiple actors playing multiple roles. The purpose of this study is to show how the main concepts emerging from research on digital platform ecosystems (DPEs) could be organized in a taxonomy-based framework with different levels or dimensions of analysis. This study discusses some of the contingencies at these different levels and argues that future research needs to study DPEs across multiple levels of analysis. While this integrative framework allows the comparison, contrast and integration of various perspectives at different levels of analysis, further theorizing will be needed to advance the DPE research. The multidimensional framework proposed here involves the use of a multimethodological approach that incorporates a synergy of businesses, technological innovations and management methods to provide support for research in interrelationships across platform ecosystems (PEs) on a regular basis. Design/methodology/approach This paper proposes a new PE framework by constructing a formal taxonomy model that explains a vast group of phenomena produced by the PEs. Findings In addition to illustrating the PE taxonomy framework, this study also proposes a clear and precise description and structuring of the information in the ecosystem domain. The PE framework assists in identification, creation, assessment and disclosure research of platform business ecosystems. Research limitations/implications Because of the large number of taxonomy concepts (over 200), only main taxonomy fragments are shown in the paper. Practical implications The outcomes of this research could be used for planning, oversight and control over ecosystem management and the use of ecosystem’s knowledge-related resources for research purposes. Originality/value The PE framework is original and represents an effective tool for observing PEs.
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Daewel, Ute, Solfrid Sætre Hjøllo, Martin Huret, Rubao Ji, Marie Maar, Susa Niiranen, Morgane Travers-Trolet, Myron A. Peck, and Karen E. van de Wolfshaar. "Predation control of zooplankton dynamics: a review of observations and models." ICES Journal of Marine Science 71, no. 2 (August 6, 2013): 254–71. http://dx.doi.org/10.1093/icesjms/fst125.
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Abstract Daewel, U., Hjøllo, S. S., Huret, M., Ji, R., Maar, M., Niiranen, S., Travers-Trolet, M., Peck, M. A., van de Wolfshaar, K. E. 2014. Predation control of zooplankton dynamics: a review of observations and models. – ICES Journal of Marine Science, 71: 254–271. We performed a literature review to examine to what degree the zooplankton dynamics in different regional marine ecosystems across the Atlantic Ocean is driven by predation mortality and how the latter is addressed in available modelling approaches. In general, we found that predation on zooplankton plays an important role in all the six considered ecosystems, but the impacts are differently strong and occur at different spatial and temporal scales. In ecosystems with extreme environmental conditions (e.g. low temperature, ice cover, large seasonal amplitudes) and low species diversity, the overall impact of top-down processes on zooplankton dynamics is stronger than for ecosystems having moderate environmental conditions and high species diversity. In those ecosystems, predation mortality was found to structure the zooplankton mainly on local spatial and seasonal time scales. Modelling methods used to parameterize zooplankton mortality range from simplified approaches with fixed mortality rates to complex coupled multispecies models. The applicability of a specific method depends on both the observed state of the ecosystem and the spatial and temporal scales considered. Modelling constraints such as parameter uncertainties and computational costs need to be balanced with the ecosystem-specific demand for a consistent, spatial-temporal dynamic implementation of predation mortality on the zooplankton compartment.
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Bayer, Anita D., Richard Fuchs, Reinhard Mey, Andreas Krause, Peter H. Verburg, Peter Anthoni, and Almut Arneth. "Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services." Earth System Dynamics 12, no. 1 (March 30, 2021): 327–51. http://dx.doi.org/10.5194/esd-12-327-2021.
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Abstract. Land-use models and integrated assessment models provide scenarios of land-use and land-cover (LULC) changes following pathways or storylines related to different socioeconomic and environmental developments. The large diversity of available scenario projections leads to a recognizable variability in impacts on land ecosystems and the levels of services provided. We evaluated 16 projections of future LULC until 2040 that reflected different assumptions regarding socioeconomic demands and modeling protocols. By using these LULC projections in a state-of-the-art dynamic global vegetation model, we simulated their effect on selected ecosystem service indicators related to ecosystem productivity and carbon sequestration potential, agricultural production and the water cycle. We found that although a common trend for agricultural expansion exists across the scenarios, where and how particular LULC changes are realized differs widely across models and scenarios. They are linked to model-specific considerations of some demands over others and their respective translation into LULC changes and also reflect the simplified or missing representation of processes related to land dynamics or other influencing factors (e.g., trade, climate change). As a result, some scenarios show questionable and possibly unrealistic features in their LULC allocations, including highly regionalized LULC changes with rates of conversion that are contrary to or exceed rates observed in the past. Across the diverging LULC projections, we identified positive global trends of net primary productivity (+10.2 % ± 1.4 %), vegetation carbon (+9.2 % ± 4.1 %), crop production (+31.2 % ± 12.2 %) and water runoff (+9.3 % ± 1.7 %), and a negative trend of soil and litter carbon stocks (−0.5 % ± 0.4 %). The variability in ecosystem service indicators across scenarios was especially high for vegetation carbon stocks and crop production. Regionally, variability was highest in tropical forest regions, especially at current forest boundaries, because of intense and strongly diverging LULC change projections in combination with high vegetation productivity dampening or amplifying the effects of climatic change. Our results emphasize that information on future changes in ecosystem functioning and the related ecosystem service indicators should be seen in light of the variability originating from diverging projections of LULC. This is necessary to allow for adequate policy support towards sustainable transformations.
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Jia, Wantao, Yong Xu, Dongxi Li, and Rongchun Hu. "Stochastic Analysis of Predator–Prey Models under Combined Gaussian and Poisson White Noise via Stochastic Averaging Method." Entropy 23, no. 9 (September 13, 2021): 1208. http://dx.doi.org/10.3390/e23091208.
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In the present paper, the statistical responses of two-special prey–predator type ecosystem models excited by combined Gaussian and Poisson white noise are investigated by generalizing the stochastic averaging method. First, we unify the deterministic models for the two cases where preys are abundant and the predator population is large, respectively. Then, under some natural assumptions of small perturbations and system parameters, the stochastic models are introduced. The stochastic averaging method is generalized to compute the statistical responses described by stationary probability density functions (PDFs) and moments for population densities in the ecosystems using a perturbation technique. Based on these statistical responses, the effects of ecosystem parameters and the noise parameters on the stationary PDFs and moments are discussed. Additionally, we also calculate the Gaussian approximate solution to illustrate the effectiveness of the perturbation results. The results show that the larger the mean arrival rate, the smaller the difference between the perturbation solution and Gaussian approximation solution. In addition, direct Monte Carlo simulation is performed to validate the above results.
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Johnston, Robert J., and Dana Marie Bauer. "Using Meta-Analysis for Large-Scale Ecosystem Service Valuation: Progress, Prospects, and Challenges." Agricultural and Resource Economics Review 49, no. 1 (October 31, 2019): 23–63. http://dx.doi.org/10.1017/age.2019.22.
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AbstractThis article discusses prospects and challenges related to the use of meta-regression models (MRMs) for ecosystem service benefit transfer, with an emphasis on validity criteria and post-estimation procedures given sparse attention in the ecosystem services literature. We illustrate these topics using a meta-analysis of willingness to pay for water quality changes that support aquatic ecosystem services and the application of this model to estimate water quality benefits under alternative riparian buffer restoration scenarios in New Hampshire's Great Bay Watershed. These illustrations highlight the advantages of MRM benefit transfers, together with the challenges and data needs encountered when quantifying ecosystem service values.
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Gnanadesikan, A., J. P. Dunne, and J. John. "What ocean biogeochemical models can tell us about bottom-up control of ecosystem variability." ICES Journal of Marine Science 68, no. 6 (January 1, 2011): 1030–44. http://dx.doi.org/10.1093/icesjms/fsr068.
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Abstract Gnanadesikan, A., Dunne, J. P., and John, J. 2011. What ocean biogeochemical models can tell us about bottom-up control of ecosystem variability. – ICES Journal of Marine Science, 68: 1030–1044. Processes included in earth system models amplify the impact of climate variability on phytoplankton biomass and, therefore, on upper trophic levels. Models predict much larger relative interannual variability in large phytoplankton biomass than in total phytoplankton biomass, supporting the goal of better constraining size-structured primary production and biomass from remote sensing. The largest modelled variability in annually averaged large phytoplankton biomass is associated with changes in the areal extent of relatively productive regions. Near the equator, changes in the areal extent of the high-productivity zone are driven by large-scale shifts in nutrient fields, as well as by changes in currents. Along the poleward edge of the Subtropical Gyres, changes in physical mixing dominate. Finally, models indicate that high-latitude interannual variability in large phytoplankton biomass is greatest during spring. Mechanisms for producing such variability differ across biomes with internal ocean processes, such as convection complicating efforts to link ecosystem variability to climate modes defined using sea surface temperature alone. In salinity-stratified subpolar regions, changes in bloom timing driven by salinity can produce correlations between low surface temperatures and high productivity, supporting the potential importance of using coupled atmosphere–ocean reanalyses, rather than simple forced ocean reanalyses, for attributing past ecosystem shifts.
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de Paoli, Hélène, Tjisse van der Heide, Aniek van den Berg, Brian R. Silliman, Peter M. J. Herman, and Johan van de Koppel. "Behavioral self-organization underlies the resilience of a coastal ecosystem." Proceedings of the National Academy of Sciences 114, no. 30 (July 10, 2017): 8035–40. http://dx.doi.org/10.1073/pnas.1619203114.
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Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.
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Varkey, Divya, Cameron H. Ainsworth, and Tony J. Pitcher. "Modelling Reef Fish Population Responses to Fisheries Restrictions in Marine Protected Areas in the Coral Triangle." Journal of Marine Biology 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/721483.
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Marine ecosystem models are used to investigate marine protected area (MPA) benefits for coral reef ecosystems located in Raja Ampat, in the heart of the Coral Triangle. Field data from an integrated and diverse research project is used to develop a spatial ecosystem model using Ecopath, Ecosim, and Ecospace modelling software. The ecological and fisheries responses of a reef ecosystem to different levels of fishing effort restrictions inside MPAs are explored. The trade-offs of allowing some fisheries to operate inside the MPAs versus designating the MPAs as no-take zones are highlighted. The results show that rapid rebuilding of reef fish populations, especially the large charismatic species, requires no-take areas. Distinct trade-offs in spillover benefits are observed between partially fished and no-take MPAs.
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Xiao, Wei. "Information Technology in Environment Digital Design Based on CAD." Advanced Materials Research 1014 (July 2014): 387–90. http://dx.doi.org/10.4028/www.scientific.net/amr.1014.387.
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Spatial structure of landscape ecology is composed by different ecosystems, the interaction function and dynamics. It is to the entire landscape as the research object, emphasizing the interaction between the protection and management of large areas of population ecology, management of environmental resources and human activities spatial heterogeneity of the maintenance and development, ecosystem and its components on the landscape impact. This paper presents several models of several computer-aided digital design environments, and the depth of the concrete application of various models.
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Dafforn, K. A., E. L. Johnston, A. Ferguson, C. L. Humphrey, W. Monk, S. J. Nichols, S. L. Simpson, M. G. Tulbure, and D. J. Baird. "Big data opportunities and challenges for assessing multiple stressors across scales in aquatic ecosystems." Marine and Freshwater Research 67, no. 4 (2016): 393. http://dx.doi.org/10.1071/mf15108.
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Aquatic ecosystems are under threat from multiple stressors, which vary in distribution and intensity across temporal and spatial scales. Monitoring and assessment of these ecosystems have historically focussed on collection of physical and chemical information and increasingly include associated observations on biological condition. However, ecosystem assessment is often lacking because the scale and quality of biological observations frequently fail to match those available from physical and chemical measurements. The advent of high-performance computing, coupled with new earth observation platforms, has accelerated the adoption of molecular and remote sensing tools in ecosystem assessment. To assess how emerging science and tools can be applied to study multiple stressors on a large (ecosystem) scale and to facilitate greater integration of approaches among different scientific disciplines, a workshop was held on 10–12 September 2014 at the Sydney Institute of Marine Sciences, Australia. Here we introduce a conceptual framework for assessing multiple stressors across ecosystems using emerging sources of big data and critique a range of available big-data types that could support models for multiple stressors. We define big data as any set or series of data, which is either so large or complex, it becomes difficult to analyse using traditional data analysis methods.
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Schramski, John R., Anthony I. Dell, John M. Grady, Richard M. Sibly, and James H. Brown. "Metabolic theory predicts whole-ecosystem properties." Proceedings of the National Academy of Sciences 112, no. 8 (January 26, 2015): 2617–22. http://dx.doi.org/10.1073/pnas.1423502112.
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Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude—from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers—as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.
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Large, Scott I., Gavin Fay, Kevin D. Friedland, and Jason S. Link. "Defining trends and thresholds in responses of ecological indicators to fishing and environmental pressures." ICES Journal of Marine Science 70, no. 4 (July 1, 2013): 755–67. http://dx.doi.org/10.1093/icesjms/fst067.
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Abstract Large, S. I., Fay, G., Friedland, K. D., and Link, J. S. 2013. Defining trends and thresholds in responses of ecological indicators to fishing and environmental pressures. – ICES Journal of Marine Science, 70: 755–767. Both fishing and environmental forces can influence the structure of marine ecosystems. To further understand marine ecosystems and to implement ecosystem-based fisheries management (EBFM), an evaluation of ecosystem indicators is warranted. In this context, it is particularly important to identify thresholds where fishing and environmental pressures significantly influence ecological indicators. We empirically determined numerical values of environmental forces and fishing pressure that significantly altered the response of ecological indicators for the Northeast Shelf Large Marine Ecosystem. Generalized additive models predicted a non-linear relationship for each pressure–response pairing. With this smoother, 95% confidence intervals (CI) for estimated first and second derivatives for each relationship were determined via parametric bootstrap. A significant trend or threshold was noted when the CI for the first or second derivative was greater or less than zero, delineating the level at which pressure variables influence the rate and direction of ecosystem indicator responses. We identify reference levels where environmental forces and fishing pressure result in ecosystem change by collectively examining the responses of multiple ecological indicators. Individual indicators showed unique responses to pressures, however, similar values for the pressures were associated with significant changes for multiple indicators. These reference levels establish a foundation for implementation of EBFM.
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Solé, Ricard V., José M. Montoya, and Douglas H. Erwin. "Recovery after mass extinction: evolutionary assembly in large–scale biosphere dynamics." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1421 (May 29, 2002): 697–707. http://dx.doi.org/10.1098/rstb.2001.0987.
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Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low–diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three–level ecosystems.
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Kurota, Hiroyuki, Murdoch K. McAllister, Eric A. Parkinson, and N. T. Johnston. "Evaluating the influence of predator–prey interactions on stock assessment and management reference points for a large lake ecosystem." Canadian Journal of Fisheries and Aquatic Sciences 73, no. 9 (September 2016): 1372–88. http://dx.doi.org/10.1139/cjfas-2014-0414.
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Ecosystem models are thought to offer advantages over single-species models in terms of management policy analysis. This hypothesis has proven difficult to test because of underlying system complexities, coupled with short time series and minimal contrast in environmental conditions or management policies. This paper presents a Bayesian statistical catch-at-age model to compare ecosystem models and test hypotheses about the management of a recreational fishery based on a predator–prey system using a relatively simple and data-rich ecosystem in a large lake, Kootenay Lake, British Columbia, where kokanee (Oncorhynchus nerka) are the prey and piscivorous rainbow trout (Oncorhynchus mykiss) are the predator. A model that explicitly incorporates the predator–prey interaction explained long-term data of field and fishery surveys much better than single-species models without any interactions. Minimally realistic multispecies models that treated predation identically but differed in their representation of the effects of prey abundance on predator mortality produced quite different results. Management reference points, for example, differed considerably between the models. Our study thus emphasizes that the choice of a management approach for this type of fishery will depend strongly on the model form and should take into consideration results from empirically based models that include species interactions.
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Reum, Jonathan C. P., P. Sean McDonald, Bridget E. Ferriss, Dara M. Farrell, Chris J. Harvey, and Phillip S. Levin. "Qualitative network models in support of ecosystem approaches to bivalve aquaculture." ICES Journal of Marine Science 72, no. 8 (July 11, 2015): 2278–88. http://dx.doi.org/10.1093/icesjms/fsv119.
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Abstract Predicting the effects of aquaculture development for coastal ecosystems remains challenging, particularly for data-limited systems, and tools that account for complex ecological interactions are needed to support ecosystem approaches to aquaculture. Here, we used qualitative network models (QNMs) to examine the potential community effects of increasing bivalve aquaculture in South Puget Sound, a large estuarine system in Washington, United States. QNMs are formalized conceptual models that require only a qualitative understanding of how variables composing a system interact (that is, the sign of interactions: +, –, and 0) and are therefore well-suited to data-limited systems. Specifically, we examined community-wide responses to scenarios in which bivalve cultivation effort increased for three different bivalve species (Manila clam Venerupis philippinarum, Pacific oyster Crassostrea gigas, and geoduck Panopea generosa). Further, we evaluated community-wide responses to the removal of benthic bivalve predators, a future increase in nutrient loadings, and combinations of these scenarios acting simultaneously. The scenarios enabled identification of potential trade-offs between increased aquaculture and shifts in the abundance of community members and assessment of the possible effects of different management actions. We also analysed the QNM to identify key interactions that influence the sign outcome of community responses to press perturbations, highlighting potential points for management intervention and linkages deserving of more focused quantitative study. QNMs are mathematically robust and highly flexible, but remain underutilized. We suggest that they may serve as valuable tools for supporting ecosystem approaches to aquaculture.
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Henehan, Michael J., Pincelli M. Hull, Donald E. Penman, James W. B. Rae, and Daniela N. Schmidt. "Biogeochemical significance of pelagic ecosystem function: an end-Cretaceous case study." Philosophical Transactions of the Royal Society B: Biological Sciences 371, no. 1694 (May 19, 2016): 20150510. http://dx.doi.org/10.1098/rstb.2015.0510.
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Pelagic ecosystem function is integral to global biogeochemical cycling, and plays a major role in modulating atmospheric CO 2 concentrations ( p CO 2 ). Uncertainty as to the effects of human activities on marine ecosystem function hinders projection of future atmospheric p CO 2 . To this end, events in the geological past can provide informative case studies in the response of ecosystem function to environmental and ecological changes. Around the Cretaceous–Palaeogene (K–Pg) boundary, two such events occurred: Deccan large igneous province (LIP) eruptions and massive bolide impact at the Yucatan Peninsula. Both perturbed the environment, but only the impact coincided with marine mass extinction. As such, we use these events to directly contrast the response of marine biogeochemical cycling to environmental perturbation with and without changes in global species richness. We measure this biogeochemical response using records of deep-sea carbonate preservation. We find that Late Cretaceous Deccan volcanism prompted transient deep-sea carbonate dissolution of a larger magnitude and timescale than predicted by geochemical models. Even so, the effect of volcanism on carbonate preservation was slight compared with bolide impact. Empirical records and geochemical models support a pronounced increase in carbonate saturation state for more than 500 000 years following the mass extinction of pelagic carbonate producers at the K–Pg boundary. These examples highlight the importance of pelagic ecosystems in moderating climate and ocean chemistry.
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Yool, A., E. E. Popova, and T. R. Anderson. "Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain." Geoscientific Model Development 4, no. 2 (May 10, 2011): 381–417. http://dx.doi.org/10.5194/gmd-4-381-2011.
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Abstract. The ongoing, anthropogenically-driven changes to the global ocean are expected to have significant consequences for plankton ecosystems in the future. Because of the role that plankton play in the ocean's "biological pump", changes in abundance, distribution and productivity will likely have additional consequences for the wider carbon cycle. Just as in the terrestrial biosphere, marine ecosystems exhibit marked diversity in species and functional types of organisms. Predicting potential change in plankton ecosystems therefore requires the use of models that are suited to this diversity, but whose parameterisation also permits robust and realistic functional behaviour. In the past decade, advances in model sophistication have attempted to address diversity, but have been criticised for doing so inaccurately or ahead of a requisite understanding of underlying processes. Here we introduce MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification), a new "intermediate complexity" plankton ecosystem model that expands on traditional nutrient-phytoplankton-zooplankton-detritus (NPZD) models, and remains amenable to global-scale evaluation. MEDUSA-1.0 includes the biogeochemical cycles of nitrogen, silicon and iron, broadly structured into "small" and "large" plankton size classes, of which the "large" phytoplankton class is representative of a key phytoplankton group, the diatoms. A full description of MEDUSA-1.0's state variables, differential equations, functional forms and parameter values is included, with particular attention focused on the submodel describing the export of organic carbon from the surface to the deep ocean. MEDUSA-1.0 is used here in a multi-decadal hindcast simulation, and its biogeochemical performance evaluated at the global scale.
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Donoso, Isabel, Matthias Schleuning, Daniel García, and Jochen Fründ. "Defaunation effects on plant recruitment depend on size matching and size trade-offs in seed-dispersal networks." Proceedings of the Royal Society B: Biological Sciences 284, no. 1855 (May 31, 2017): 20162664. http://dx.doi.org/10.1098/rspb.2016.2664.
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Defaunation by humans causes a loss of large animals in many ecosystems globally. Recent work has emphasized the consequences of downsizing in animal communities for ecosystem functioning. However, no study so far has integrated network theory and life-history trade-offs to mechanistically evaluate the functional consequences of defaunation in plant–animal networks. Here, we simulated an avian seed-dispersal network and its derived ecosystem function seedling recruitment to assess the relative importance of different size-related mechanisms. Specifically, we considered size matching (between bird size and seed size) and size trade-offs, which are driven by differences in plant or animal species abundance (negative size–quantity relationship) as well as in recruitment probability and disperser quality (positive size–quality relationship). Defaunation led to impoverished seedling communities in terms of diversity and seed size, but only if models accounted for size matching. In addition, size trade-off in plants, in concert with size matching, provoked rapid decays in seedling abundance in response to defaunation. These results underscore a disproportional importance of large animals for ecosystem functions. Downsizing in ecological networks will have severe consequences for ecosystem functioning, especially in interaction networks that are structured by size matching between plants and animals.
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Park, Jong-Yeon, Charles A. Stock, John P. Dunne, Xiaosong Yang, and Anthony Rosati. "Seasonal to multiannual marine ecosystem prediction with a global Earth system model." Science 365, no. 6450 (July 18, 2019): 284–88. http://dx.doi.org/10.1126/science.aav6634.
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Climate variations have a profound impact on marine ecosystems and the communities that depend upon them. Anticipating ecosystem shifts using global Earth system models (ESMs) could enable communities to adapt to climate fluctuations and contribute to long-term ecosystem resilience. We show that newly developed ESM-based marine biogeochemical predictions can skillfully predict satellite-derived seasonal to multiannual chlorophyll fluctuations in many regions. Prediction skill arises primarily from successfully simulating the chlorophyll response to the El Niño–Southern Oscillation and capturing the winter reemergence of subsurface nutrient anomalies in the extratropics, which subsequently affect spring and summer chlorophyll concentrations. Further investigations suggest that interannual fish-catch variations in selected large marine ecosystems can be anticipated from predicted chlorophyll and sea surface temperature anomalies. This result, together with high predictability for other marine-resource–relevant biogeochemical properties (e.g., oxygen, primary production), suggests a role for ESM-based marine biogeochemical predictions in dynamic marine resource management efforts.
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Cogan, Christopher B., Brian J. Todd, Peter Lawton, and Thomas T. Noji. "The role of marine habitat mapping in ecosystem-based management." ICES Journal of Marine Science 66, no. 9 (August 6, 2009): 2033–42. http://dx.doi.org/10.1093/icesjms/fsp214.
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Abstract Cogan, C. B., Todd, B. J., Lawton, P., and Noji, T. T. 2009. The role of marine habitat mapping in ecosystem-based management. – ICES Journal of Marine Science, 66: 2033–2042. Ecosystem-based management (EBM) and the related concept of large marine ecosystems (LMEs) are sometimes criticized as being too broad for many management and research applications. At the same time, there is a great need to develop more effectively some substantive scientific methods to empower EBM. Marine habitat mapping (MHM) is an example of an applied set of field methods that support EBM directly and contribute essential elements for conducting integrated ecosystem assessments. This manuscript places MHM practices in context with biodiversity models and EBM. We build the case for MHM being incorporated as an explicit and early process following initial goal-setting within larger EBM programmes. Advances in MHM and EBM are dependent on evolving technological and modelling capabilities, conservation targets, and policy priorities within a spatial planning framework. In both cases, the evolving and adaptive nature of these sciences requires explicit spatial parameters, clear objectives, combinations of social and scientific considerations, and multiple parameters to assess overlapping viewpoints and ecosystem functions. To examine the commonalities between MHM and EBM, we also address issues of implicit and explicit linkages between classification, mapping, and elements of biodiversity with management goals. Policy objectives such as sustainability, ecosystem health, or the design of marine protected areas are also placed in the combined MHM–EBM context.
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Yool, A., E. E. Popova, and T. R. Anderson. "<i>MEDUSA</i>: a new intermediate complexity plankton ecosystem model for the global domain." Geoscientific Model Development Discussions 3, no. 4 (October 29, 2010): 1939–2019. http://dx.doi.org/10.5194/gmdd-3-1939-2010.
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Abstract. The ongoing, anthropogenically-driven changes to the global ocean are expected to have significant consequences for plankton ecosystems in the future. Because of the role that plankton play in the ocean's "biological pump", changes in abundance, distribution and productivity will likely have additional consequences for the wider carbon cycle. Just as in the terrestrial biosphere, marine ecosystems exhibit marked diversity in species and functional types of organisms. Predicting potential change in plankton ecosystems therefore requires the use of models that are suited to this diversity, but whose parameterisation also permits robust and realistic functional behaviour. In the past decade, advances in model sophistication have attempted to address diversity, but have been criticised for doing so inaccurately or ahead of a requisite understanding of underlying processes. Here we introduce MEDUSA (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification), a new "intermediate complexity" plankton ecosystem model that expands on traditional nutrient-phytoplankton-zooplankton-detritus (NPZD) models, and remains amenable to global-scale evaluation. MEDUSA includes the biogeochemical cycles of nitrogen, silicon and iron, broadly structured into "small" and "large" plankton size classes, of which the "large" phytoplankton class is representative of a key phytoplankton group, the diatoms. A full description of MEDUSA's state variables, differential equations, functional forms and parameter values is included, with particular attention focused on the submodel describing the export of organic carbon from the surface to the deep ocean. MEDUSA is used here in a multi-decadal hindcast simulation, and its biogeochemical performance evaluated at the global scale.
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Jacobsen, Nis S., Timothy E. Essington, and Ken H. Andersen. "Comparing model predictions for ecosystem-based management." Canadian Journal of Fisheries and Aquatic Sciences 73, no. 4 (April 2016): 666–76. http://dx.doi.org/10.1139/cjfas-2014-0561.
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Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (EwE)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects of forage fisheries removal. In both cases, the differences are due to the presumed degree of trophic overlap between juveniles of large-bodied fish and adult stages of forage fish. These differences highlight how each model’s emphasis on distinct details of ecological processes affects its predictions, underscoring the importance of incorporating knowledge of model assumptions and limitation, possibly through using model ensembles, when providing model-based scientific advice to policy makers.
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Laufkötter, C., M. Vogt, N. Gruber, M. Aita-Noguchi, O. Aumont, L. Bopp, E. Buitenhuis, et al. "Drivers and uncertainties of future global marine primary production in marine ecosystem models." Biogeosciences Discussions 12, no. 4 (February 27, 2015): 3731–824. http://dx.doi.org/10.5194/bgd-12-3731-2015.
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Abstract. Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean and mostly ignored the large inter-model differences. Here, we analyze model simulated changes of NPP for the 21st century under IPCC's high emission scenario RCP8.5 using a suite of nine coupled carbon–climate Earth System Models with embedded marine ecosystem models with a focus on the spread between the different models and the underlying reasons. Globally, five out of the nine models show a decrease in NPP over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between −25 and +40%. In this region, the inter-quartile range of the differences between the 2012–2031 average and the 2081–2100 average is up to 3 mol C m-2 yr-1. These large differences in future change mirror large differences in present day NPP. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification and reduced upwelling. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduces NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while the remaining model simulates changes of less than 0.5%. While there is more consistency in the modeled increase in NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their development.
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Yu, Tong, and Qianlai Zhuang. "Modeling biological nitrogen fixation in global natural terrestrial ecosystems." Biogeosciences 17, no. 13 (July 13, 2020): 3643–57. http://dx.doi.org/10.5194/bg-17-3643-2020.
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Abstract. Biological nitrogen fixation plays an important role in the global nitrogen cycle. However, the fixation rate has been usually measured or estimated at a particular observational site. To quantify the fixation amount at the global scale, process-based models are needed. This study develops a biological nitrogen fixation model to quantitatively estimate the nitrogen fixation rate by plants in a natural environment. The revised nitrogen module better simulates the nitrogen cycle in comparison with our previous model that has not considered the fixation effects. The new model estimates that tropical forests have the highest fixation rate among all ecosystem types, which decreases from the Equator to the polar region. The estimated nitrogen fixation in global terrestrial ecosystems is 61.5 Tg N yr−1 with a range of 19.8–107.9 Tg N yr−1 in the 1990s. Our estimates are relatively low compared to some early estimates using empirical approaches but comparable to more recent estimates that involve more detailed processes in their modeling. Furthermore, the contribution of nitrogen made by biological nitrogen fixation depends on ecosystem type and climatic conditions. This study highlights that there are relatively large effects of biological nitrogen fixation on ecosystem nitrogen cycling. and the large uncertainty of the estimation calls for more comprehensive understanding of biological nitrogen fixation. More direct observational data for different ecosystems are in need to improve future quantification of fixation and its impacts.
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Anderson, Thomas R., and Wendy C. Gentleman. "Remembering John Steele and his models for understanding the structure and function of marine ecosystems." Journal of Plankton Research 41, no. 5 (September 2019): 609–20. http://dx.doi.org/10.1093/plankt/fbz042.
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Abstract John Steele (1926–2013) is remembered for his ecosystem modelling studies on the role of biological interactions and environment on the structure and function of marine ecosystems, including consequences for fish production and fisheries management. Here, we provide a scientific tribute to Steele focusing on, by means of example, his modelling of plankton predation [Steele and Henderson (1992) The role of predation in plankton models. J. Plankton Res., 14, 157–172] that showed that differences in ecosystem dynamics between the subarctic Pacific and North Atlantic oceans can be explained solely on the basis of zooplankton mortality. The study highlights Steele’s artistry in simplifying the system to a tractable minimal model while paying great attention to the precise functional forms used to parameterize mortality, grazing and other biological processes. The success of this and other works by Steele was in large part due to his effective communication with the rest of the scientific community (especially non-modellers) resulting from his enthusiasm, use of an experiment-like (hypothesis driven) approach to applying his models and by describing simplifications and assumptions in scrupulous detail. We also intend our contribution to remember Steele as the consummate gentleman, notably his humble, behind-the-scenes attitude, his humour and his dedication to enhancing the careers of others.
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Zador, Stephani G., Kirstin K. Holsman, Kerim Y. Aydin, and Sarah K. Gaichas. "Ecosystem considerations in Alaska: the value of qualitative assessments." ICES Journal of Marine Science 74, no. 1 (August 20, 2016): 421–30. http://dx.doi.org/10.1093/icesjms/fsw144.
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The application of ecosystem considerations, and in particular ecosystem report cards, in federal groundfish fisheries management in Alaska can be described as an ecosystem approach to fisheries management (EAFM). Ecosystem information is provided to managers to establish an ecosystem context within which deliberations of fisheries quota occur. Our goal is to make the case for the need for qualitative ecosystem assessments in EAFM, specifically that qualitative synthesis has advantages worthy to keep a permanent place at the fisheries management table. These advantages include flexibility and speed in responding to and synthesizing new information from a variety of sources. First, we use the development of indicator-based ecosystem report cards as an example of adapting ecosystem information to management needs. Second, we review lessons learned and provide suggestions for best practices for applying EAFM to large and diverse fisheries in multiple marine ecosystems. Adapting ecosystem indicator information to better suit the needs of fisheries managers resulted in succinct report cards that summarize ecosystem trends, complementing more detailed ecosystem information to provide context for EAFM. There were several lessons learned in the process of developing the ecosystem report cards. The selection of indicators for each region was influenced by geography, the extent of scientific knowledge/data, and the particular expertise of the selection teams. Optimizing the opportunity to qualitatively incorporate ecosystem information into management decisions requires a good understanding of the management system in question. We found that frequent dialogue with managers and other stakeholders leads to adaptive products. We believe that there will always be a need for qualitative ecosystem assessment because it allows for rapid incorporation of new ideas and data and unexpected events. As we build modelling and predictive capacity, we will still need qualitative synthesis to capture events outside the bounds of current models and to detect impacts of the unexpected.
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Kirschbaum, Miko U. F., Guillaume Simioni, Belinda E. Medlyn, and Ross E. McMurtrie. "On the importance of including soil nutrient feedback effects for predicting ecosystem carbon exchange." Functional Plant Biology 30, no. 2 (2003): 223. http://dx.doi.org/10.1071/fp02152.
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To grow, plants need both carbon, which is fixed in photosynthesis, and inorganic nutrients, which are generally obtained from the soil. Much interest currently exists in trying to understand the uptake and storage of carbon by terrestrial ecosystems. This paper investigates to what extent carbon gain and storage are modified by soil nutrient availability. This issue is investigated in relation to both short-term carbon fluxes on the time scale of interannual variability and long-term ecosystem carbon stocks on time scales of several thousand years.We conclude from simulations with an ecosystem model (CenW) that interannual variations in carbon gain can be significantly affected by feedback effects through the nutrient cycle. This feedback effect operates principally through an imbalance between carbon and nutrient dynamics. In years that allow high carbon gain, nutrient supply typically does not match the increased carbon supply so that foliar nutrient concentrations are reduced. This lowers productivity below that which could be expected if foliar nutrient concentration remained the same. The importance of these feedback effects is shown to be greatest at intermediate levels of water availability and nutrient supply, and is relatively more important for net ecosystem carbon exchange than for net primary production.We conclude that the long-term build-up of carbon stocks in ecosystems is often controlled by the rate at which nutrients can be gained. This conclusion is based on data from published studies showing that the slow build-up of carbon matches the gain in nitrogen, phosphorus and sulfur, and on our simulations of system carbon stocks in response to fertiliser addition.The paper concludes with a discussion of the importance and feasibility of including these processes into models at different scales, including the broad continental scale. For modelling net ecosystem exchange for Australia, it is regarded as feasible and desirable to use models that are constrained by these system-internal feedback effects. Such models have already been used for large-scale simulations in Australia and other countries.
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Kimmins, J. P., R. S. Rempel, C. V. J. Welham, B. Seely, and K. C. J. Van Rees. "Biophysical sustainability, process-based monitoring and forest ecosystem management decision support systems." Forestry Chronicle 83, no. 4 (August 1, 2007): 502–14. http://dx.doi.org/10.5558/tfc83502-4.
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Sustainability is a key concept in resource management and environmental issues, but implementation is fraught with difficulty due to lack of agreement as to what it means. Because of the ubiquity of disturbance, ecosystem sustainability inevitably involves change. We define stand-level biophysical sustainability as non-declining patterns of change over at least three cycles of disturbance, and landscape-level sustainability as a shifting mosaic of non-declining stand change, the overall character of which remains within acceptable limits over time. Simple empirical assessment (i.e., monitoring) of this concept of sustainability is generally not practical in forestry because of the long time and large spatial scales involved. Adaptive management (AM), another key resource management concept, involves monitoring to assess the consequences of management actions. It requires forecasts of expected change in sustainably managed, post-disturbance ecosystems against which to assess monitoring data. Without these forecasts, which constitute temporal fingerprints of sustainable change, short-term monitoring data cannot be used reliably as a basis from which to assess longer-term sustainability. A comprehensive monitoring system to address biophysical sustainability locally and at the landscape scale for a large management unit over a rotation-length time scale would involve the key elements of ecosystem structure and function and the effects thereon of management and climate change. This would be prohibitively expensive and demanding of human resources and the results would not be available until the end of the rotation. A strategy that honours the intent of AM is an intimate linkage between predictive monitoring and process-based ecosystem management decision support systems—ecosystem process-based monitoring—the emphasis of which is on temporal patterns of indicator change rather than comparisons between static indicators and audits of current ecosystem conditions (the certification approach). It involves a combination of monitoring and ecosystem management modeling that reduces the long-term cost of monitoring and increases the utility of the data collected for the assessment of sustainability and for the design of policy and adaptive practice in forestry. Key words: prediction, process-based monitoring, sustainability, forest ecosystems, biophysical indicators, temporal fingerprints, adaptive management, ecosystem management models
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Zhu, Q., Q. Zhuang, D. Henze, K. Bowman, M. Chen, Y. Liu, Y. He, et al. "Constraining terrestrial ecosystem CO<sub>2</sub> fluxes by integrating models of biogeochemistry and atmospheric transport and data of surface carbon fluxes and atmospheric CO<sub>2</sub> concentrations." Atmospheric Chemistry and Physics Discussions 14, no. 16 (September 3, 2014): 22587–638. http://dx.doi.org/10.5194/acpd-14-22587-2014.
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Abstract. Regional net carbon fluxes of terrestrial ecosystems could be estimated with either biogeochemistry models by assimilating surface carbon flux measurements or atmospheric CO2 inversions by assimilating observations of atmospheric CO2 concentrations. Here we combine the ecosystem biogeochemistry modeling and atmospheric CO2 inverse modeling to investigate the magnitude and spatial distribution of the terrestrial ecosystem CO2 sources and sinks. First, we constrain a terrestrial ecosystem model (TEM) at site level by assimilating the observed net ecosystem production (NEP) for various plant functional types. We find that the uncertainties of model parameters are reduced up to 90% and model predictability is greatly improved for all the plant functional types (coefficients of determination are enhanced up to 0.73). We then extrapolate the model to a global scale at a 0.5° × 0.5° resolution to estimate the large-scale terrestrial ecosystem CO2 fluxes, which serve as prior for atmospheric CO2 inversion. Second, we constrain the large-scale terrestrial CO2 fluxes by assimilating the GLOBALVIEW-CO2 and mid-tropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) into an atmospheric transport model (GEOS-Chem). The transport inversion estimates that: (1) the annual terrestrial ecosystem carbon sink in 2003 is −2.47 Pg C yr−1, which agrees reasonably well with the most recent inter-comparison studies of CO2 inversions (−2.82 Pg C yr−1); (2) North America temperate, Europe and Eurasia temperate regions act as major terrestrial carbon sinks; and (3) The posterior transport model is able to reasonably reproduce the atmospheric CO2 concentrations, which are validated against Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) CO2 concentration data. This study indicates that biogeochemistry modeling or atmospheric transport and inverse modeling alone might not be able to well quantify regional terrestrial carbon fluxes. However, combining the two modeling approaches and assimilating data of surface carbon flux as well as atmospheric CO2 mixing ratios might significantly improve the quantification of terrestrial carbon fluxes.
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Bystrov, A. V., T. O. Tolstykh, and A. G. Radaykin. "Cross-Industry Ecosystem as an Organizational and Economic Model for the Development of High-Tech Industries." Economics and Management 26, no. 6 (August 25, 2020): 564–76. http://dx.doi.org/10.35854/1998-1627-2020-6-564-576.
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The presented study examines the fundamental prerequisites for the emergence of digital platforms, which would provide a global view of the role that platforms play in creating a new organizational model — an ecosystem of high-tech industries.Aim. In the context of industrial digitalization, the study aims to substantiate the creation of a modern mechanism for coordinating high-tech market participants within a single economic and organizational space — an ecosystem based on a cross-industry digital platform.Tasks. The authors analyze the international experience of implementing digital platforms, identify problems and provide recommendations for solving them in the context of digital platform implementation in the Russian industry.Methods. This study uses general scientific methods of cognition in various aspects to analyze the current vector of industrial development driven by the introduction of ecosystems as a new organizational and economic model; describe the principles of their formation, possible structure, and main differences from traditional cluster and network models; substantiate that an ecosystem model allows its participants to achieve a positive synergistic effect in the implementation of their strategic development goals in the context of digital transformation.Results. The issues of using the tools of an industrial digital platform to facilitate the interaction between participants within an ecosystem are considered. Platform solutions in the industry show great promise in terms of analyzing large amounts of data, reducing transaction costs, and obtaining “perfect information”. The direction for the implementation of cross-industry digital platforms and creation of ecosystems in the near future is characterized.Conclusions. Digital cross-industry interaction within the framework of a common platform will expand external communications and promotion channels, making it possible to introduce digital business models and diversify production, but also requiring compatibility between the systems of industrial enterprises and a functioning digital platform and cloud environment.
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Hudiburg, Tara W., Philip E. Higuera, and Jeffrey A. Hicke. "Fire-regime variability impacts forest carbon dynamics for centuries to millennia." Biogeosciences 14, no. 17 (August 31, 2017): 3873–82. http://dx.doi.org/10.5194/bg-14-3873-2017.
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Abstract. Wildfire is a dominant disturbance agent in forest ecosystems, shaping important biogeochemical processes including net carbon (C) balance. Long-term monitoring and chronosequence studies highlight a resilience of biogeochemical properties to large, stand-replacing, high-severity fire events. In contrast, the consequences of repeated fires or temporal variability in a fire regime (e.g., the characteristic timing or severity of fire) are largely unknown, yet theory suggests that such variability could strongly influence forest C trajectories (i.e., future states or directions) for millennia. Here we combine a 4500-year paleoecological record of fire activity with ecosystem modeling to investigate how fire-regime variability impacts soil C and net ecosystem carbon balance. We found that C trajectories in a paleo-informed scenario differed significantly from an equilibrium scenario (with a constant fire return interval), largely due to variability in the timing and severity of past fires. Paleo-informed scenarios contained multi-century periods of positive and negative net ecosystem C balance, with magnitudes significantly larger than observed under the equilibrium scenario. Further, this variability created legacies in soil C trajectories that lasted for millennia. Our results imply that fire-regime variability is a major driver of C trajectories in stand-replacing fire regimes. Predicting carbon balance in these systems, therefore, will depend strongly on the ability of ecosystem models to represent a realistic range of fire-regime variability over the past several centuries to millennia.
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Churkina, G., S. Zaehle, J. Hughes, N. Viovy, Y. Chen, M. Jung, B. W. Heumann, N. Ramankutty, M. Heimann, and C. Jones. "Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe." Biogeosciences 7, no. 9 (September 20, 2010): 2749–64. http://dx.doi.org/10.5194/bg-7-2749-2010.
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Abstract. European ecosystems are thought to take up large amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more that 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C yr−1. The extents of forest and grasslands have increased with the respective rates of 5800 km2 yr−1 and 1100 km2 yr−1 as agricultural land has been abandoned at a rate of 7000 km2 yr−1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. The models suggest that European ecosystems sequester carbon at a rate of 56 TgC yr−1 (mean of four models for 1951–2000) with strong interannual variability (±88 TgC yr−1, average across models) and substantial inter-model uncertainty (±39 TgC yr−1). Decadal budgets suggest that there has been a continuous increase in the mean net carbon storage of ecosystems from 85 TgC yr−1 in 1980s to 108 TgC yr−1 in 1990s, and to 114 TgC yr−1 in 2000–2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are suggested as an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.
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Li, Zhijie, Qiuwen Chen, Qiang Xu, and Koen Blanckaert. "Generalized Likelihood Uncertainty Estimation Method in Uncertainty Analysis of Numerical Eutrophication Models: Take BLOOM as an Example." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/701923.
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Uncertainty analysis is of great importance to assess and quantify a model's reliability, which can improve decision making based on model results. Eutrophication and algal bloom are nowadays serious problems occurring on a worldwide scale. Numerical models offer an effective way to algal bloom prediction and management. Due to the complex processes of aquatic ecosystem, such numerical models usually contain a large number of parameters, which may lead to important uncertainty in the model results. This research investigates the applicability of generalized likelihood uncertainty estimation (GLUE) to analyze the uncertainty of numerical eutrophication models that have a large number of intercorrelated parameters. The 3-dimensional primary production model BLOOM, which has been broadly used in algal bloom simulations for both fresh and coastal waters, is used.
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del Río-Mena, Trinidad, Louise Willemen, Anton Vrieling, and Andy Nelson. "Understanding Intra-Annual Dynamics of Ecosystem Services Using Satellite Image Time Series." Remote Sensing 12, no. 4 (February 21, 2020): 710. http://dx.doi.org/10.3390/rs12040710.
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Landscape processes fluctuate over time, influencing the intra-annual dynamics of ecosystem services. However, current ecosystem service assessments generally do not account for such changes. This study argues that information on the dynamics of ecosystem services is essential for understanding and monitoring the impact of land management. We studied two regulating ecosystem services (i. erosion prevention, ii. regulation of water flows) and two provisioning services (iii. provision of forage, iv. biomass for essential oil production) in thicket vegetation and agricultural fields in the Baviaanskloof, South Africa. Using models based on Sentinel-2 data, calibrated with field measurements, we estimated the monthly supply of ecosystem services and assessed their intra-annual variability within vegetation cover types. We illustrated how the dynamic supply of ecosystem services related to temporal variations in their demand. We also found large spatial variability of the ecosystem service supply within a single vegetation cover type. In contrast to thicket vegetation, agricultural land showed larger temporal and spatial variability in the ecosystem service supply due to the effect of more intensive management. Knowledge of intra-annual dynamics is essential to jointly assess the temporal variation of supply and demand throughout the year to evaluate if the provision of ecosystem services occurs when most needed.
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Bond-Lamberty, B., J. P. Fisk, J. A. Holm, V. Bailey, G. Bohrer, and C. M. Gough. "Moderate forest disturbance as a stringent test for gap and big-leaf models." Biogeosciences 12, no. 2 (January 27, 2015): 513–26. http://dx.doi.org/10.5194/bg-12-513-2015.
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Abstract. Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.