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Zariņš, Mārcis, Andra Blumberga, Māris Klaviņš, and Viesturs Melecis. "Dynamic Modeling for Environmental Processes: A Case Study of Lake Engure." Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences. 68, no. 1-2 (2014): 20–30. http://dx.doi.org/10.2478/prolas-2014-0002.
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Abstract This focus of the study was on system dynamic models that could be useful for modelling environmental processes in Lake Engure. The paper considers the system dynamic model development principles, the most important elements and structure. The aim of the study was to describe possible methods of ecosystem process modelling that allow to represent the actual state of ecosystems and provide opportunities to predict further processes. The methods of ecosystem modelling considered in the paper reveal interactive factors of anthropogenic and environmental processes that influence changes in ecosystems. System dynamic models indicate not only interactions between various factors in the environment but also the most important driving forces. These models are based on flowchart and algorithm systems, which represent changes using mathematical functions in a graphic or tabular form. In the case study of Lake Engure, connections between factors that influence ecosystems in the study area were identified. Specialised software, PowerSim Studio Academic 9.0, was used for modelling. The model consists of qualitative and multifactor data of Lake Engure ecosystems, such as water chemical, physical and hydrological parameters, biological, ornithological and other data collected in the study area. Development of this modelling method will make it possible to evaluate the impact of various processes on biological diversity changes in the study area and to identify the most important problems. Furthermore, this method could improve environmental management practice in the surrounding municipalities, and it will also be possible to make similar models of ecosystem quality in other regions.
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Guseynov, Sharif E., and Jekaterina V. Aleksejeva. "Mathematical Modelling of Aquatic Ecosystem." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (June 16, 2015): 92. http://dx.doi.org/10.17770/etr2015vol3.192.
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<p class="R-AbstractKeywords"><span lang="EN-US">In present paper we consider the complete statements of initial-boundary problems for the modelling of various aspects of aqueous systems in Latvia. All the proposed models are the evolutionary models: all they are nonstationary and continuous qualitative models having the dynamic parameters and aimed at analysis, evaluation and forecast of aqueous systems (reservoirs, lakes and seas). In constructing these mathematical models as research tools classic apparatus of differential equations (both ODE and PDE) as well as apparatus of mathematical physics were used</span><span lang="EN-US">. </span></p>
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Munch, Stephan B., Antoine Brias, George Sugihara, and Tanya L. Rogers. "Frequently asked questions about nonlinear dynamics and empirical dynamic modelling." ICES Journal of Marine Science 77, no. 4 (2019): 1463–79. http://dx.doi.org/10.1093/icesjms/fsz209.
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Abstract Complex nonlinear dynamics are ubiquitous in marine ecology. Empirical dynamic modelling can be used to infer ecosystem dynamics and species interactions while making minimal assumptions. Although there is growing enthusiasm for applying these methods, the background required to understand them is not typically part of contemporary marine ecology curricula, leading to numerous questions and potential misunderstanding. In this study, we provide a brief overview of empirical dynamic modelling, followed by answers to the ten most frequently asked questions about nonlinear dynamics and nonlinear forecasting.
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Daewel, Ute, Solfrid Sætre Hjøllo, Martin Huret, et al. "Predation control of zooplankton dynamics: a review of observations and models." ICES Journal of Marine Science 71, no. 2 (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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Makler-Pick, Vardit, Gideon Gal, James Shapiro, and Matthew R. Hipsey. "Exploring the role of fish in a lake ecosystem (Lake Kinneret, Israel) by coupling an individual-based fish population model to a dynamic ecosystem model." Canadian Journal of Fisheries and Aquatic Sciences 68, no. 7 (2011): 1265–84. http://dx.doi.org/10.1139/f2011-051.
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To explore the role that fish play in aquatic ecosystems, a hydrodynamic–ecological model (DYRESM–CAEDYM) was coupled to a novel fish population model. The coupled model (DYCD–FISH) combined two modelling approaches: a complex dynamic model and an individual-based model. The coupled model simulates fish growth population dynamics and predicts fish impacts on various ecosystem components, including nutrients and lower trophic levels. The model was employed to explore the role of the dominant fish in Lake Kinneret (Israel), Acanthobrama terraesanctae (Kinneret bleak, or in Hebrew, lavnun ha’kinneret; hereafter lavnun). Model results suggested that the lavnun has a significant impact (p < 0.05) on the magnitude of output variables including its prey food (the predatory and microzooplankton), major nutrients such as ammonium (NH4) and phosphate (PO4), and on several phytoplankton species, but not on the seasonality of any of the output variables. Since the model incorporates trophic levels from nutrients to fish, it revealed the nonlinear dynamic impacts of fish on different ecosystem components and in particular has led to quantitative insights into the relative influence of top-down control on water quality attributes. Besides being an ecosystem research tool, DYCD–FISH can also be employed as a fishery management tool, and in particular facilitate ecosystem-based fishery management.
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Harbar, Oleksandr, Іvan Khomiak, Іryna Kotsiuba, Nataliia Demchuk, and Іryna Onyshchuk. "Anthropogenic and Natural Dynamics of Landscape Ecosystems of the Slovechansko-Ovruchsky Ridge (Ukraine)." Socijalna ekologija 30, no. 3 (2021): 347–69. http://dx.doi.org/10.17234/socekol.30.3.1.
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The need for landscape management cannot be satisfied by static data alone. Landscape ecosystems are complex dynamic objects and the successful protection or operation of such areas depends on the quality of monitoring their dynamics and the forecasts built on its basis. Forecasting accuracy also depends on the quality of the modelling and this is why it is necessary to highlight the most universal and key characteristics of ecosystems. The Slovechansko-Ovruchsky ridge, which has a phenomenally high variety of landscapes, is well suited as an object for testing approaches to modelling. The authors singled out 11 territorial parts of the Slovechansko-Ovruchsky ridge at the level of landscapes and tracts. The differentiation of these landscapes was assessed using the synphytoindication method to determine the value of natural and anthropogenic dynamics. This made it possible to build prognostic algorithms for ecosystem changes using geobotanical data and produce prospects to create the best suitable landscape protection strategy or more effective and safe exploitation of landscapes.
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Hjøllo, SS, SM van Leeuwen, and M. Maar. "Marine research and management topics addressed by process-based ecosystem models." Marine Ecology Progress Series 680 (December 9, 2021): 1–6. http://dx.doi.org/10.3354/meps13963.
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The earth’s oceans and ecosystems face climatic changes and multiple anthropogenic stressors. In the face of this, managers of the marine environment are increasingly adopting the ecosystem approach to underpin their decision making. Process-based ecosystem models (frequently referred to as dynamic models) synthesize existing observational and experimental knowledge into a numerical framework, but an obstacle to the incorporation of these models in management is the lack of credibility due to limited control of uncertainty in the results. The 13 papers in this Theme Section highlight how ecosystem models are, or can be, applied as management tools, and the various ways in which they quantify uncertainty and evaluate the skill. The papers span all levels of biological organization from individuals to populations and ecosystems, and cover a wide selection of anthropogenic pressures. Bearing in mind that the interpretation of observations is in fact also a model with representativeness error, we advocate a closer combination of observations and models to bring both methods forward. With the current challenges to the marine ecosystem and our uses of it, the more tools marine managers have in their ‘toolbox’, the better; dynamic modelling is one such very important tool, and its inclusion in ecosystem management should be continuously assessed.
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Olin, S., M. Lindeskog, T. A. M. Pugh, et al. "Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching." Earth System Dynamics 6, no. 2 (2015): 745–68. http://dx.doi.org/10.5194/esd-6-745-2015.
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Abstract. Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us to investigate trade-offs between these ecosystem services that can be provided from agricultural fields. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP (Representative Concentration Pathway) 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles.
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Brias, Antoine, and Stephan B. Munch. "Ecosystem based multi-species management using Empirical Dynamic Programming." Ecological Modelling 441 (February 2021): 109423. http://dx.doi.org/10.1016/j.ecolmodel.2020.109423.
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Brias, Antoine, and Stephan B. Munch. "Ecosystem based multi-species management using Empirical Dynamic Programming." Ecological Modelling 441 (February 2021): 109423. http://dx.doi.org/10.1016/j.ecolmodel.2020.109423.
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Kazanci, C., and Q. Ma. "Extending ecological network analysis measures to dynamic ecosystem models." Ecological Modelling 242 (September 2012): 180–88. http://dx.doi.org/10.1016/j.ecolmodel.2012.05.021.
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Hidalgo, Manuel, David H. Secor, and Howard I. Browman. "Observing and managing seascapes: linking synoptic oceanography, ecological processes, and geospatial modelling." ICES Journal of Marine Science 73, no. 7 (2016): 1825–30. http://dx.doi.org/10.1093/icesjms/fsw079.
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Abstract The capacity to observe, retrieve, and model the physiographical and hydrographical features of the sea (i.e. seascapes) has surpassed our ability to integrate this information into the assessment and stewardship of marine ecosystems. However, current marine policy that mandates integrated ecosystem assessments demands temporally intensive and spatially extensive predictions of key populations and ecosystem processes and services, particularly those related to habitat use and distribution. In this sense, seascape ecology represents an operational linkage between basic oceanography and applied ecology and management that embraces spatially explicit models of the dynamic distributions of populations, communities and foodwebs through a joint consideration of observational data and ecological processes. For these reasons, the ICES Journal of Marine Science solicited contributions to the article theme set, “Frontiers in seascape ecology”. In this introduction, we present current concepts and developments in seascape ecology, briefly summarize the 10 articles that appear herein, and discuss the most relevant challenges to this nascent discipline. The contributions included in this theme set illustrate the growing relevance of seascape ecology in the multidisciplinary management of marine ecosystems.
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Ariadi, Heri, Tholibah Mujtahidah, Shobrina Silmi Qori Tartila, Muh Azril, and Christian Larbi Ayisi. "Dynamic Modelling Analysis of <i>Vibrio </i>sp. and Plankton Abundance in Intensive Shrimp Pond." Biosaintifika: Journal of Biology & Biology Education 16, no. 3 (2024): 449–63. https://doi.org/10.15294/biosaintifika.v16i3.16465.
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Vibrio sp. and plankton are important microorganisms in shrimp pond ecosystems. The research aims to predict the dynamics of Vibrio sp. and plankton abundance in intensive shrimp pond ecosystems based on causal model analysis. The research method used is an ex-pose facto causal design concept with quantitative descriptive data analysis using causal dynamic modeling. The results showed the water quality in the pond has a high correlation, except Vibrio sp. and alkalinity. In the pond ecosystem 24 genus of plankton from 6 classes. Chlorella sp. is the dominant plankton genus with an abundance of 1.00E+05-4.00E+05 cells/ml. Vibrio sp. abundance in ponds ranged from 1.38E+03 - 1.31E+05 CFU/ml. Based on the results of dynamic modelling, the growth pattern of Vibrio sp. lasted for 30 weeks which was divided into 4 growth phases. The conclusion of this study is that Vibrio sp. will dynamically experience a pure growth rate for 30 weeks with details of the initial growth phase (1-7 weeks), logarithmic growth phase (8-14 weeks), exponential phase (15-21 weeks), and growth declination phase (22-30 weeks). The growth phase of Vibrio sp. has a high degree of similarity to the growth pattern of plankton in the pond water ecosystem correlatively. The novelty of this research lies in the discovery of an estimation model for the abundance of Vibrio sp. and plankton during the shrimp farming cycle. This finding can serve as a fundamental reference for farmers to optimize feeding processes and conduct regular siphoning during the peak abundance of Vibrio sp. and plankton.
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Löw, Markus, and Tatjana Koukal. "Phenology Modelling and Forest Disturbance Mapping with Sentinel-2 Time Series in Austria." Remote Sensing 12, no. 24 (2020): 4191. http://dx.doi.org/10.3390/rs12244191.
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Worldwide, forests provide natural resources and ecosystem services. However, forest ecosystems are threatened by increasing forest disturbance dynamics, caused by direct human activities or by altering environmental conditions. It is decisive to reconstruct and trace the intra- to transannual dynamics of forest ecosystems. National to local forest authorities and other stakeholders request detailed area-wide maps that delineate forest disturbance dynamics at various spatial scales. We developed a time series analysis (TSA) framework that comprises data download, data management, image preprocessing and an advanced but flexible TSA. We use dense Sentinel-2 time series and a dynamic Savitzky–Golay-filtering approach to model robust but sensitive phenology courses. Deviations from the phenology models are used to derive detailed spatiotemporal information on forest disturbances. In a first case study, we apply the TSA to map forest disturbances directly or indirectly linked to recurring bark beetle infestation in Northern Austria. In addition to spatially detailed maps, zonal statistics on different spatial scales provide aggregated information on the extent of forest disturbances between 2018 and 2019. The outcomes are (a) area-wide consistent data of individual phenology models and deduced phenology metrics for Austrian forests and (b) operational forest disturbance maps, useful to investigate and monitor forest disturbances to facilitate sustainable forest management.
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Littleton, Emma W., Kate Dooley, Gordon Webb, et al. "Dynamic modelling shows substantial contribution of ecosystem restoration to climate change mitigation." Environmental Research Letters 16, no. 12 (2021): 124061. http://dx.doi.org/10.1088/1748-9326/ac3c6c.
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Abstract Limiting global warming to a 1.5°C temperature rise requires drastic emissions reductions and removal of carbon-dioxide from the atmosphere. Most modelled pathways for 1.5°C assume substantial removals in the form of biomass energy with carbon capture and storage, which brings with it increasing risks to biodiversity and food security via extensive land-use change. Recently, multiple efforts to describe and quantify potential removals via ecosystem-based approaches have gained traction in the climate policy discourse. However, these options have yet to be evaluated in a systematic and scientifically robust way. We provide spatially explicit estimates of ecosystem restoration potential quantified with a Dynamic Global Vegetation Model. Simulations covering forest restoration, reforestation, reduced harvest, agroforestry and silvopasture were combined and found to sequester an additional 93 Gt C by 2100, reducing mean global temperature increase by ∼0.12°C (5%–95% range 0.06°C–0.21°C) relative to a baseline mitigation pathway. Ultimately, pathways to achieving the 1.5°C goal garner broader public support when they include land management options that can bring about multiple benefits, including ecosystem restoration, biodiversity protection, and resilient agricultural practices.
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Bocharova, Julia Yurevna. "Modelling Ecosystems of Pedagogical Education in the Postnonclassical Paradigm." Siberian Pedagogical Journal, no. 5 (November 6, 2022): 7–15. http://dx.doi.org/10.15293/1813-4718.2205.01.
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The problem of modelling open systems in education, in which non-linear processes take place, requires the use of postnonclassical methodology. Reflection of the reality of pedagogical education which exists in the form of an ecosystem of formal institutions, urban educational formats, educational platforms and communities of practice playing an important role in the development of a future teacher, is possible when building a dynamic model for the development of a professional community and a teacher in it. Research methodology and methods: social constructionism and synergetics as a general scientific methodology of postnonclassical science, analogy, action research, interviews, network analysis, modelling, mathematical description of a model. The purpose of the article is to characterize the application of modelling as a particular methodology in the postnonclassical paradigm of the study of pedagogical education and to propose a prototype of mathematical description of the local (regional) ecosystem of open pedagogical education. The results were obtained during constructing the model in a temporary research team by modelling in action (by the Action Research type) on the local system of engineering and technology education in Krasnoyarsk. Attractors-competences and lead functions have been identified, mathematical coefficients have been developed to track the dynamics of the development in the ecosystem of pedagogical education based on the growth of diversity in the system. In conclusion, specific characteristics of modelling pedagogical education in the postnonclassical paradigm have been highlighted.
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Stasinopoulos, Nikolaos, Michail Chalaris, Anastasia Tezari, and Kalliopi Kravari. "The Endless Possibilities of Modelling of Toxic Chemical Warfare Agents and Possible Impacts of Their Release in Water Sensitive Areas." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 19 (October 10, 2023): 998–1007. http://dx.doi.org/10.37394/232015.2023.19.94.
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Nerve agents are chemical compounds that constitute chemical weapons with many effects on human health as well as the environment. In this work, an analysis of the properties of several nerve agents and their dispersion in aquatic ecosystems is proposed, by exploring the possibilities of state-of-the-art computational methods, such as molecular dynamic simulations, quantitative structure-activity relationship models such and other simple computational models for the simulation of a water ecosystem.
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Davoudkhani, Mohsen, Francesco Rubino, Christopher J. Creevey, et al. "Integrating microbial abundance time series with fermentation dynamics of the rumen microbiome via mathematical modelling." PLOS ONE 19, no. 3 (2024): e0298930. http://dx.doi.org/10.1371/journal.pone.0298930.
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The rumen represents a dynamic microbial ecosystem where fermentation metabolites and microbial concentrations change over time in response to dietary changes. The integration of microbial genomic knowledge and dynamic modelling can enhance our system-level understanding of rumen ecosystem’s function. However, such an integration between dynamic models and rumen microbiota data is lacking. The objective of this work was to integrate rumen microbiota time series determined by 16S rRNA gene amplicon sequencing into a dynamic modelling framework to link microbial data to the dynamics of the volatile fatty acids (VFA) production during fermentation. For that, we used the theory of state observers to develop a model that estimates the dynamics of VFA from the data of microbial functional proxies associated with the specific production of each VFA. We determined the microbial proxies using CowPi to infer the functional potential of the rumen microbiota and extrapolate their functional modules from KEGG (Kyoto Encyclopedia of Genes and Genomes). The approach was challenged using data from an in vitro RUSITEC experiment and from an in vivo experiment with four cows. The model performance was evaluated by the coefficient of variation of the root mean square error (CRMSE). For the in vitro case study, the mean CVRMSE were 9.8% for acetate, 14% for butyrate and 14.5% for propionate. For the in vivo case study, the mean CVRMSE were 16.4% for acetate, 15.8% for butyrate and 19.8% for propionate. The mean CVRMSE for the VFA molar fractions were 3.1% for acetate, 3.8% for butyrate and 8.9% for propionate. Ours results show the promising application of state observers integrated with microbiota time series data for predicting rumen microbial metabolism.
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Fulton, Elizabeth A., Nicholas J. Bax, Rodrigo H. Bustamante, et al. "Modelling marine protected areas: insights and hurdles." Philosophical Transactions of the Royal Society B: Biological Sciences 370, no. 1681 (2015): 20140278. http://dx.doi.org/10.1098/rstb.2014.0278.
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Models provide useful insights into conservation and resource management issues and solutions. Their use to date has highlighted conditions under which no-take marine protected areas (MPAs) may help us to achieve the goals of ecosystem-based management by reducing pressures, and where they might fail to achieve desired goals. For example, static reserve designs are unlikely to achieve desired objectives when applied to mobile species or when compromised by climate-related ecosystem restructuring and range shifts. Modelling tools allow planners to explore a range of options, such as basing MPAs on the presence of dynamic oceanic features, and to evaluate the potential future impacts of alternative interventions compared with ‘no-action’ counterfactuals, under a range of environmental and development scenarios. The modelling environment allows the analyst to test if indicators and management strategies are robust to uncertainties in how the ecosystem (and the broader human–ecosystem combination) operates, including the direct and indirect ecological effects of protection. Moreover, modelling results can be presented at multiple spatial and temporal scales, and relative to ecological, economic and social objectives. This helps to reveal potential ‘surprises', such as regime shifts, trophic cascades and bottlenecks in human responses. Using illustrative examples, this paper briefly covers the history of the use of simulation models for evaluating MPA options, and discusses their utility and limitations for informing protected area management in the marine realm.
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Daewel, Ute, Corinna Schrum, and Jed I. Macdonald. "Towards end-to-end (E2E) modelling in a consistent NPZD-F modelling framework (ECOSMO E2E_v1.0): application to the North Sea and Baltic Sea." Geoscientific Model Development 12, no. 5 (2019): 1765–89. http://dx.doi.org/10.5194/gmd-12-1765-2019.
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Abstract. Coupled physical–biological models usually resolve only parts of the trophic food chain; hence, they run the risk of neglecting relevant ecosystem processes. Additionally, this imposes a closure term problem at the respective “ends” of the trophic levels considered. In this study, we aim to understand how the implementation of higher trophic levels in a nutrient–phytoplankton–zooplankton–detritus (NPZD) model affects the simulated response of the ecosystem using a consistent NPZD–fish modelling approach (ECOSMO E2E) in the combined North Sea–Baltic Sea system. Utilising this approach, we addressed the above-mentioned closure term problem in lower trophic ecosystem modelling at a very low computational cost; thus, we provide an efficient method that requires very little data to obtain spatially and temporally dynamic zooplankton mortality. On the basis of the ECOSMO II coupled ecosystem model we implemented one functional group that represented fish and one group that represented macrobenthos in the 3-D model formulation. Both groups were linked to the lower trophic levels and to each other via predator–prey relationships, which allowed for the investigation of both bottom-up processes and top-down mechanisms in the trophic chain of the North Sea–Baltic Sea ecosystem. Model results for a 10-year-long simulation period (1980–1989) were analysed and discussed with respect to the observed patterns. To understand the impact of the newly implemented functional groups for the simulated ecosystem response, we compared the performance of the ECOSMO E2E to that of a respective truncated NPZD model (ECOSMO II) applied to the same time period. Additionally, we performed scenario tests to analyse the new role of the zooplankton mortality closure term in the truncated NPZD and the fish mortality term in the end-to-end model, which summarises the pressure imposed on the system by fisheries and mortality imposed by apex predators. We found that the model-simulated macrobenthos and fish spatial and seasonal patterns agree well with current system understanding. Considering a dynamic fish component in the ecosystem model resulted in slightly improved model performance with respect to the representation of spatial and temporal variations in nutrients, changes in modelled plankton seasonality, and nutrient profiles. Model sensitivity scenarios showed that changes in the zooplankton mortality parameter are transferred up and down the trophic chain with little attenuation of the signal, whereas major changes in fish mortality and fish biomass cascade down the food chain.
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Keenan, T., R. García, A. D. Friend, S. Zaehle, C. Gracia, and S. Sabate. "Improved understanding of drought controls on seasonal variation in Mediterranean forest canopy CO<sub>2</sub> and water fluxes through combined in situ measurements and ecosystem modelling." Biogeosciences Discussions 6, no. 1 (2009): 2285–329. http://dx.doi.org/10.5194/bgd-6-2285-2009.
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Abstract. Water stress is a defining characteristic of Mediterranean ecosystems, and is likely to become more severe in the coming decades. However, our current understanding of how soil moisture controls ecosystem functioning is not sufficient to adequately constrain model parameterisations. Canopy-scale flux data from four forest ecosystems with Mediterranean-type climates were analysed in order to determine the physiological controls on carbon and water flues through the year. Stomatal and non-stomatal limitations on photosynthesis were separated, and new parameterisations were derived and implemented in two independent modelling approaches. The effectiveness of the two approaches to ecosystem process-based modelling, one a dynamic global vegetation model (ORCHIDEE), and the other a forest growth model (GOTILWA+), was assessed and modelled canopy responses to seasonal changes in soil moisture were analysed with respect to in situ flux measurements. In contrast to commonly held assumptions, we find that stomatal control does not dominate photosynthesis under natural seasonally-developing soil moisture stress. However, applying a soil moisture dependency to photosynthetic capacity results in accurate prediction of both carbon and water fluxes under all soil moisture levels encountered in the field. The new parameterisation has important consequences for simulated responses of carbon and water fluxes to seasonal soil moisture stress, and will greatly improve our ability to anticipate future impacts of climate changes on the functioning of Mediterranean ecosystems.
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Olin, S., M. Lindeskog, T. A. M. Pugh, et al. "Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching." Earth System Dynamics Discussions 6, no. 1 (2015): 1047–100. http://dx.doi.org/10.5194/esdd-6-1047-2015.
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Abstract. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.
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Omwenga, Vincent O., Vaishnav Madhumati, Kumar Vinay, Sathyanarayan Srikanta, and Navakanta Bhat. "Mathematical Modelling of Combined Intervention Strategies for the Management and Control of Plasma Glucose of a Diabetes Mellitus Patient: A System Dynamic Modelling Approach." Mathematics 11, no. 2 (2023): 306. http://dx.doi.org/10.3390/math11020306.
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With the rapid increase of diabetes mellitus cases in the world, management and control of the disease has become a complex and highly dynamic process. This challenge requires a multifaceted approach to manage and control the complications associated with the hyperglycaemia or hypoglycaemia conditions. This paper presents a mathematical model for determining the influence of combined intervention strategies in the management and control for the plasma glucose of the type II diabetes. System dynamics (SD) techniques were used in modelling the sub-compartments of biological systems of an Identifiable Patient (IP). The system dynamic model developed gave an illustration on how typical glucose-insulin dynamics occur at different intervention strategies involving varying amounts of carbohydrates taken, intensity of physical exercises, stress levels and the amount of exogenous insulin administered. The model was conceptualized within a semi-closed loop system representing the patient ecosystem by extending the Bergman Minimal Model. Stochastic differential equations (SDE) were used to capture the non-linear, continuous time varying interactions of the measurements associated with plasma glucose-insulin dynamics. The estimated results from the model showed combined intervention strategies of reduced amounts of carbohydrates intake, reduced stress levels and varying moderately high-to-low exercise intensity at a constant unit of exogenous insulin produced good plasma glucose levels control.
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Zanchi, Giuliana, and Mark V. Brady. "Evaluating the contribution of forest ecosystem services to societal welfare through linking dynamic ecosystem modelling with economic valuation." Ecosystem Services 39 (October 2019): 101011. http://dx.doi.org/10.1016/j.ecoser.2019.101011.
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Ouyang, Xinyu, and Xiangyu Luo. "Models for Assessing Urban Ecosystem Services: Status and Outlooks." Sustainability 14, no. 8 (2022): 4725. http://dx.doi.org/10.3390/su14084725.
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Urban ecosystem services provide many benefits for human beings. Given the dramatic increase of urbanization, maintaining sustainability of cities relies heavily on ecosystem services, and it is crucial for quantifying, managing, and optimizing urban ecosystem services to promote social and ecological sustainable development. This study presents the review of models for assessing urban ecosystem services through gathering the pertinent literatures which were published recent years. The main types of approaches for assessing urban ecosystem services were summarized, and the model simulation approach was detailed. From modelling techniques to the existing models, it was found that a process-based model is, relatively, a better way to detect the mechanism of urban ecological processes and simulate the future dynamic changes of urban ecosystem services. Three key limitations of existing products and frameworks were identified: (1) lacking understanding of multiple urban ecosystem services interactions, (2) ignoring accounting the socioeconomic factors into dynamics of urban ecosystem, and (3) lacking considerations of feedback effects between social system and urban ecosystem. The study concludes with outlooks that a comprehensive social-ecosystem model based on the social-ecological framework is helpful to reveal the relationships and interactions among various urban ecosystem services, and can better assess how human-induced urban growth affects ecosystem services, and better describe the feedback effect between the social environment and urban ecosystem services, as well as dynamically predict the changes of urban ecosystem services under different scenarios in future long time series.
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Lambin, Eric F. "Modelling and monitoring land-cover change processes in tropical regions." Progress in Physical Geography: Earth and Environment 21, no. 3 (1997): 375–93. http://dx.doi.org/10.1177/030913339702100303.
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Transformations in terrestrial ecosystems are increasingly regarded as an important element of global change. Quantitative data on where, when and why land-cover changes take place globally are still incomplete. This article reviews recent approaches to the monitoring and modelling of deforestation and dryland degradation in tropical regions. The review highlights the requirement to tailor the investigation method to the specific research question of interest. Different techniques to monitor land-cover changes at regional scales are analysed. The following modelling scenarios are discussed and illustrated by specific studies: projection of future land- cover changes with descriptive models, explanation of land-cover changes with empirical models, projection of future spatial patterns of changes with spatial statistical models, test of scenarios on future changes in land-cover with dynamic ecosystem models, and design of policy interventions with economic models. The article stresses the needs for a better integration of social science knowledge in land-cover change models and for a comprehensive theory of land-use changes.
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Chaudhary, Nitin, Paul A. Miller, and Benjamin Smith. "Modelling past, present and future peatland carbon accumulation across the pan-Arctic region." Biogeosciences 14, no. 18 (2017): 4023–44. http://dx.doi.org/10.5194/bg-14-4023-2017.
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Abstract. Most northern peatlands developed during the Holocene, sequestering large amounts of carbon in terrestrial ecosystems. However, recent syntheses have highlighted the gaps in our understanding of peatland carbon accumulation. Assessments of the long-term carbon accumulation rate and possible warming-driven changes in these accumulation rates can therefore benefit from process-based modelling studies. We employed an individual-based dynamic global ecosystem model with dynamic peatland and permafrost functionalities and patch-based vegetation dynamics to quantify long-term carbon accumulation rates and to assess the effects of historical and projected climate change on peatland carbon balances across the pan-Arctic region. Our results are broadly consistent with published regional and global carbon accumulation estimates. A majority of modelled peatland sites in Scandinavia, Europe, Russia and central and eastern Canada change from carbon sinks through the Holocene to potential carbon sources in the coming century. In contrast, the carbon sink capacity of modelled sites in Siberia, far eastern Russia, Alaska and western and northern Canada was predicted to increase in the coming century. The greatest changes were evident in eastern Siberia, north-western Canada and in Alaska, where peat production hampered by permafrost and low productivity due the cold climate in these regions in the past was simulated to increase greatly due to warming, a wetter climate and higher CO2 levels by the year 2100. In contrast, our model predicts that sites that are expected to experience reduced precipitation rates and are currently permafrost free will lose more carbon in the future.
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Dragon, Anne-Cécile, Inna Senina, Olivier Titaud, et al. "An ecosystem-driven model for spatial dynamics and stock assessment of North Atlantic albacore." Canadian Journal of Fisheries and Aquatic Sciences 72, no. 6 (2015): 864–78. http://dx.doi.org/10.1139/cjfas-2014-0338.
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An application of the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM) is developed for the North Atlantic albacore (Thunnus alalunga) population. We investigate the spatiotemporal dynamics of this species, distinguishing the influences of environment and international fishing. Incorporating historical data (1960–2008), a maximum likelihood approach allows the estimation of biological parameters (thermal and oxygen tolerance) and stock spatial distribution varying over time. Juvenile albacore are predicted in warm surface waters, whereas adults inhabit cooler and deeper waters. Positive correlations between juveniles and tropical large-scale climate indices highlight the importance of environmental drivers when estimating stock recruitment biology and spatiotemporal distribution. A methodology is proposed to use SEAPODYM outputs to estimate stock abundance and maximum sustainable yield (MSY). MSY is computed taking into account the spatial dynamics of the species and the environmental variability and is based on a mechanistic modelling of larval recruitment. MSY estimates converge towards an asymptotic value (15 997 t) of the same magnitude than standard stock assessment estimates conducted for the international tuna commission. In agreement with all assessment studies, the stock status is estimated from overfished in the 1990s to recovered in the 2000s. Our results show that the stock recovery results both from fishing actions, including total allowable catches established in the 2000s, and from the beginning of a North Atlantic Oscillation warm phase, leading to more favourable recruitment conditions. Following a parsimonious ecosystemic approach, SEAPODYM offers a faithful and spatially dynamic modelling framework that now includes direct tools for spatialized management advice and for distinction between environmental and fishing effects.
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Scolozzi, Rocco, Uta Schirpke, and Davide Geneletti. "Enhancing Ecosystem Services Management in Protected Areas Through Participatory System Dynamics Modelling." Landscape Online 73 (August 26, 2019): 1–17. http://dx.doi.org/10.3097/lo.201973.
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Ecosystem services (ES) depend on coupled ecological and socioeconomic processes. We propose participatory modelling as a tool for sharing and co-creating knowledge about processes supporting (or eroding) local ES. The proposal consists of an open library of introductory ES dynamic models to be tailored for each case study. Such a library is illustrated by two ES examples and five models, published in an open-access web-platform. The results can contribute to the improvement of both analysis and deliberation, helping managers to design better policies and stakeholders to better formulate expectations.
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Akoglu, E., S. Libralato, B. Salihoglu, T. Oguz, and C. Solidoro. "EwE-F 1.0: an implementation of Ecopath with Ecosim in Fortran 95/2003 for coupling and integration with other models." Geoscientific Model Development 8, no. 8 (2015): 2687–99. http://dx.doi.org/10.5194/gmd-8-2687-2015.
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Abstract. Societal and scientific challenges foster the implementation of the ecosystem approach to marine ecosystem analysis and management, which is a comprehensive means of integrating the direct and indirect effects of multiple stressors on the different components of ecosystems, from physical to chemical and biological and from viruses to fishes and marine mammals. Ecopath with Ecosim (EwE) is a widely used software package, which offers capability for a dynamic description of the multiple interactions occurring within a food web, and, potentially, a crucial component of an integrated platform supporting the ecosystem approach. However, being written for the Microsoft .NET framework, seamless integration of this code with Fortran-based physical and/or biogeochemical oceanographic models is technically not straightforward. In this work we release a re-coding of EwE in Fortran (EwE-F). We believe that the availability of a Fortran version of EwE is an important step towards setting up coupled/integrated modelling schemes utilising this widely adopted software because it (i) increases portability of the EwE models and (ii) provides additional flexibility towards integrating EwE with Fortran-based modelling schemes. Furthermore, EwE-F might help modellers using the Fortran programming language to get close to the EwE approach. In the present work, first fundamentals of EwE-F are introduced, followed by validation of EwE-F against standard EwE utilising sample models. Afterwards, an end-to-end (E2E) ecological representation of the Gulf of Trieste (northern Adriatic Sea) ecosystem is presented as an example of online two-way coupling between an EwE-F food web model and a biogeochemical model. Finally, the possibilities that having EwE-F opens up are discussed.
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Akoglu, E., S. Libralato, B. Salihoglu, T. Oguz, and C. Solidoro. "EwE-F 1.0: an implementation of Ecopath with Ecosim in Fortran 95/2003 for coupling." Geoscientific Model Development Discussions 8, no. 2 (2015): 1511–37. http://dx.doi.org/10.5194/gmdd-8-1511-2015.
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Abstract. Societal and scientific challenges foster the implementation of the ecosystem approach to marine ecosystem analysis and management, which is a comprehensive means of integrating the direct and indirect effects of multiple stressors on the different components of ecosystems, from physical to chemical and biological and from viruses to fishes and marine mammals. Ecopath with Ecosim (EwE) is a widely used software package, which offers great capability for a dynamic description of the multiple interactions occurring within a food web, and potentially, a crucial component of an integrated platform supporting the ecosystem approach. However, being written for the Microsoft .NET framework, seamless integration of this code with Fortran-based physical oceanographic and/or biogeochemical models is technically not straightforward. In this work we release a re-coding of EwE in Fortran (EwE-F). We believe that the availability of a Fortran version of EwE is an important step towards setting-up integrated end-to-end (E2E) modelling schemes utilising this widely adopted software because it (i) increases portability of the EwE models, (ii) provides greater flexibility towards integrating EwE with Fortran-based modelling schemes. Furthermore, EwE-F might help modellers using Fortran programming language to get close to the EwE approach. In the present work, first the fundamentals of EwE-F are introduced, followed by validation of EwE-F against standard EwE utilising sample models. Afterwards, an E2E ecological representation of the Trieste Gulf (Northern Adriatic Sea) ecosystem is presented as an example of online two-way coupling between an EwE-F food web model and a biogeochemical model. Finally, the possibilities that having EwE-F opens up for are discussed.
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Kirsta, Yu B. "Time-dynamic quantization of molecular-genetic, photosynthesis and ecosystem hierarchical levels of the biosphere." Ecological Modelling 62, no. 4 (1992): 259–74. http://dx.doi.org/10.1016/0304-3800(92)90002-v.
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Novita Susiang, Maria Imelda. "Business Incubators In The Entrepreneurship Ecosystem In Indonesia Mediated By Government Support And Intellectual Capital." Commercium : Journal of Business and Management 2, no. 2 (2024): 67–81. http://dx.doi.org/10.61978/commercium.v2i2.215.
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This research looks at the dynamic interplay in Indonesia's entrepreneurial ecosystem between government funding, intellectual capital, and the success of business incubators. Using quantitative methods, we surveyed 150 business owners involved with several incubators, investigating the intricacies of government programmes, intellectual capital dynamics, and the perceived effectiveness of these incubators. Structural Equation Modelling with Partial Least Squares (SEM-PLS) was used to examine the survey data, uncovering complex correlations and explaining the mediating role of intellectual capital. Our findings have practical consequences for policy makers, incubator managers, and entrepreneurs aiming for sustainable firm growth. These findings also provide additional insights to the theoretical framework that directs entrepreneurship research in the implications of these results.
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Gong, Jinnan, Nigel Roulet, Steve Frolking, et al. "Modelling the habitat preference of two key <i>Sphagnum</i> species in a poor fen as controlled by capitulum water content." Biogeosciences 17, no. 22 (2020): 5693–719. http://dx.doi.org/10.5194/bg-17-5693-2020.
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Abstract. Current peatland models generally treat vegetation as static, although plant community structure is known to alter as a response to environmental change. Because the vegetation structure and ecosystem functioning are tightly linked, realistic projections of peatland response to climate change require the inclusion of vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. Moss community composition primarily follows habitat moisture conditions. The known species habitat preference along the prevailing moisture gradient might not directly serve as a reliable predictor for future species compositions, as water table fluctuation is likely to increase. Hence, modelling the mechanisms that control the habitat preference of Sphagna is a good first step for modelling community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), which simulates the community dynamics of the peatland moss layer. PMS is a process-based model that employs a stochastic, individual-based approach for simulating competition within the peatland moss layer based on species differences in functional traits. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via the capitulum water content. The model was tested by predicting the habitat preferences of Sphagnum magellanicum and Sphagnum fallax – two key species representing dry (hummock) and wet (lawn) habitats in a poor fen peatland (Lakkasuo, Finland). PMS successfully captured the habitat preferences of the two Sphagnum species based on observed variations in trait properties. Our model simulation further showed that the validity of PMS depended on the interspecific differences in the capitulum water content being correctly specified. Neglecting the water content differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of the capitulum water content with respect to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Thus, studies of peatland responses to changing environmental conditions need to include capitulum water processes as a control on moss community dynamics. Our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems.
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Krivoguz, Denis, Sergey Chernyi, and Artur Manukov. "New Approach for Analyzing Marine Ecosystem Structure Using Bayesian Networks." Russian Journal of Earth Sciences 21, no. 6 (2021): 1–8. http://dx.doi.org/10.2205/2021es000782.
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Aquatic ecosystems of the Black Sea are complex multiparametric systems with a hierarchical structure. Thus, the main goal of our research was to investigate possibilities of using Bayesian networks to study the structure fo the natural systems in the Black Sea. We used CMEMS Black Sea environmental dataset, which consists of 7 different variables, that, in our opinion, can describe structural relations in the Black Sea ecosystem -- sea surface temperature and salinity, concentrations of nitrates and phosphates, amount of chlorophyll-a and net primary production and also dissolved oxygen concentration. We think, that these variables can generally define interactions in water environment of the Black Sea, organisms, that live there and human activity. As a modelling result, we receive a structure of environmental variables interactions. At the top of this structure is a dissolved oxygen, as a final result of the ecosystem functioning. Further, we think it's more appropriate to use Dynamic Bayesian networks for investigation of spatio-temporal changes to distinguish main drivers of changes and provide more balanced management of natural territories.
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Barrios-Crespo, Esther, Saúl Torres-Ortega, and Pedro Díaz-Simal. "Developing a Dynamic Model for Assessing Green Infrastructure Investments in Urban Areas." International Journal of Environmental Research and Public Health 18, no. 20 (2021): 10994. http://dx.doi.org/10.3390/ijerph182010994.
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In recent decades, cities have been experiencing accelerated population growth, associated with an increase in the scales of production and consumption. This fact, combined with deficient management of resources and waste, has led to the loss of biological diversity, compromising the generation of ecosystem services, with disastrous consequences for human health and well-being, but also for the economic system. In the field of civil engineering, the predominance of artificialisation and impermeabilization of cities (called “grey engineering”) is being questioned to be replaced or complemented with new types of infrastructures that represent a transformative change to achieving more sustainable cities. Through system dynamics applied to the economic modelling of the city of Santander (Spain), the aim of this study is to analyse the profitability of investment in ecosystem restoration and in both green and blue infrastructure, and of the implementation of environmental policies based on the relationships of affection established in the model, which represent the interactions between the main actors in urban dynamics. As a main conclusion, it is found that investing in green infrastructures and ecosystem restoration, and environmental policies is highly profitable: EUR 1 spent can produce up to EUR 100 as a benefit.
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Mukaetov, Dusko Mukaetov, Ivan Blinkov, and Hristina Poposka. "DYNAMIC OF LAND DEGRADATION NEUTRALITY BASELINE INDCATORS IN THE REPUBLIC OF MACEDONIA." Contributions, Section of Natural, Mathematical and Biotechnical Sciences 40, no. 1 (2019): 39. http://dx.doi.org/10.20903/csnmbs.masa.2019.40.1.130.
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Land degradation neutrality (LDN) is defined as a "state whereby the amount and quality of land resources nec-essary to support ecosystem functions and services and enhance food security remain stable or increase within specified temporal and spatial scales and ecosystems". The baseline is expressed as the initial (t0) estimated value of each of the three indicators, used as proxies of land-based natural capital and the ecosystem services that flow from that land base: land cover/land use change, land productivity status and trends, soil organic carbon status and trends. The baseline of LDN was calculated with estimation of the average values across the 10 years baseline period of the following indica-tors: Land Cover/Land Cover change (LC/LCC), Land Productivity Dynamics (LPD) and Soil Organic Carbon (SOC). Three tier approaches for computation of the selected indicators were used: Tier 1: Global/regional Earth observation, geospatial information and modelling; Tier 2: National statistics (only for LC/LCC) and Tier 3: Field survey. Most sig-nificant changes in LC for the period 2000/2012 are in the categories of Forest land and Shrubs/grasslands. According the global data sets used for analysis of LPD, the total affected area with depletion of Land productivity for the period 2000/2010 is identified on a only 2.35 % of the country territory. The available global data sets gives a model SOC lev-els for the period 2000/2010. According these data, the total loss of SOC in our country is estimated on 3951 t.
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Varga, Monika, Laszlo Berzi-Nagy, Bela Csukas, and Gergo Gyalog. "Long-term dynamic simulation of environmental impacts on ecosystem-based pond aquaculture." Environmental Modelling & Software 134 (December 2020): 104755. http://dx.doi.org/10.1016/j.envsoft.2020.104755.
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Kroon, F. J., and J. Brodie. "Catchment management and health of coastal ecosystems: synthesis and future research." Marine and Freshwater Research 60, no. 11 (2009): 1196. http://dx.doi.org/10.1071/mf09228.
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Globally, many coastal ecosystems are threatened by a decline in water quality from land-based runoff. However, dynamic and complex biophysical and socioeconomic interdependencies often hamper the reversal of this decline in water quality. This Special Issue illustrates an integrated approach to address deteriorating water quality from land-based runoff in the Tully basin to the Great Barrier Reef (GBR), Australia. Nitrate was identified as the key pollutant, and was mainly derived from sugarcane and banana farms. To achieve GBR water quality targets for chlorophyll a, the dissolved inorganic nitrogen (DIN) load needs to be reduced by at least 80%. Modelling shows that financially beneficial changes to management of sugarcane results in a 50% reduction in DIN load. However, larger reductions would come at a significant cost. An adaptive approach is proposed as a framework to assess (i) the efficacy of implementing the recommended management practices, and (ii) progress against set targets. Quantification of linkages between catchment management and coastal ecosystem health will help inform management strategies based on ecosystem performance measures. Verification of the efficacy of existing and exploration of innovative management strategies, as well as spatial and temporal prioritisation of their implementation, remain critical to achieve coastal ecosystem rehabilitation, including water quality improvement.
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Liu, Hao. "Development and application of a marine ecosystem dynamic model." International Journal of Automation and Computing 8, no. 2 (2011): 154–60. http://dx.doi.org/10.1007/s11633-011-0568-2.
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Carroll, Noel. "Modelling the Dynamics of Trust across a Cloud Brokerage Environment." Information Resources Management Journal 28, no. 1 (2015): 17–37. http://dx.doi.org/10.4018/irmj.2015010102.
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The globalised nature of cloud computing presents us with new challenges towards the development of effective business relationships across a dynamic service ecosystem. While availing of additional service capabilities, organisations are tasked with managing unfamiliar relationships with unfamiliar cloud service providers to generate increased business value. This calls for more attention towards the concept of trust within a cloud service environment. Cloud computing presents new economic and flexible business and technological models which supports the co-creation nature of service quality and ultimately business value. This research examined various methods to assess service quality and service capability assessment. During the course of this work, the author has identified the need to revisit the concept of ‘trust' within a cloud computing context and prescribe a method to model its complexity. The objective of this paper is to argue that, while cloud computing allows organisations to avail of increased service capabilities; it challenges the concept of trust. To support this argument the author presents the Cloud Services Trust Model to explain the dynamics of trust. In doing so, it introduces a notion of a distributed relational structure in service value co-creation. The paper also draws on theoretical developments to highlight the fundamental changes in the nature of service provision and how they impact on the assessment of service value and service quality. The author supports the need for greater transparency in the move towards greater accountability in the cloud ecosystem. The paper applies social network analysis (SNA) to model the trust relationships of a cloud brokerage environment.
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Sava, Nina, and Galina Marusic. "DIGITAL TECHNIQUES FOR WATER POLLUTION CONTROL." Journal of Engineering Science XXVIII, no. 2 (2021): 138–48. http://dx.doi.org/10.52326/jes.utm.2021.28(2).12.
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This paper is a detailed description and analysis of the most popular techniques digital for water quality control nowadays. It is illustrated how these techniques can be applied to solve problems that have arisen as a result of water pollution of aquatic ecosystems in different countries of the world. The advantages and disadvantages of using dynamic simulation software tools are presented and are based on an analysis of their operation. For each software product are highlighted the water quality parameters that can be simulated. It also presents the analysis of software products regarding the type of simulated aquatic ecosystem, as well as spatiotemporal modelling. The realization of these techniques is based on mathematical models. The development of digital techniques at the regional level may take into account certain characteristics specific to a particular aquatic ecosystem. The models can only cover a limited number of pollutants. In the process of selecting the parameters for the model, pollutants must be chosen which are a concern in themselves and which would also represent a wider set of substances that cannot be modelled in detail. Although the digital techniques examined to provide a particularly accurate estimate of water quality, the behaviour of pollutants in aquatic ecosystems remains an area of active and current research.
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Beringer, Jason, Ian McHugh, Lindsay B. Hutley, Peter Isaac, and Natascha Kljun. "Technical note: Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO)." Biogeosciences 14, no. 6 (2017): 1457–60. http://dx.doi.org/10.5194/bg-14-1457-2017.
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Abstract. Standardised, quality-controlled and robust data from flux networks underpin the understanding of ecosystem processes and tools necessary to support the management of natural resources, including water, carbon and nutrients for environmental and production benefits. The Australian regional flux network (OzFlux) currently has 23 active sites and aims to provide a continental-scale national research facility to monitor and assess Australia's terrestrial biosphere and climate for improved predictions. Given the need for standardised and effective data processing of flux data, we have developed a software suite, called the Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO), that enables gap-filling and partitioning of the primary fluxes into ecosystem respiration (Fre) and gross primary productivity (GPP) and subsequently provides diagnostics and results. We outline the processing pathways and methodologies that are applied in DINGO (v13) to OzFlux data, including (1) gap-filling of meteorological and other drivers; (2) gap-filling of fluxes using artificial neural networks; (3) the u* threshold determination; (4) partitioning into ecosystem respiration and gross primary productivity; (5) random, model and u* uncertainties; and (6) diagnostic, footprint calculation, summary and results outputs. DINGO was developed for Australian data, but the framework is applicable to any flux data or regional network. Quality data from robust systems like DINGO ensure the utility and uptake of the flux data and facilitates synergies between flux, remote sensing and modelling.
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Hayashida, Hakase, James R. Christian, Amber M. Holdsworth, et al. "CSIB v1 (Canadian Sea-ice Biogeochemistry): a sea-ice biogeochemical model for the NEMO community ocean modelling framework." Geoscientific Model Development 12, no. 5 (2019): 1965–90. http://dx.doi.org/10.5194/gmd-12-1965-2019.
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Abstract. Process-based numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in ice-covered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new sea-ice biogeochemical model, has been developed and embedded into the Nucleus for European Modelling of the Ocean (NEMO) modelling system. This model consists of a three-compartment (ice algae, nitrate, and ammonium) sea-ice ecosystem and a two-compartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem and sulfur-cycle models at the sea-ice–ocean interface. In addition to biological and chemical sources and sinks, the model simulates the horizontal transport of biogeochemical state variables within sea ice through a one-way coupling to a dynamic-thermodynamic sea-ice model (LIM2; the Louvain-la-Neuve Sea Ice Model version 2). The model results for 1979 (after a decadal spin-up) are presented and compared to observations and previous model studies for a brief discussion on the model performance. Furthermore, this paper provides discussion on technical aspects of implementing the sea-ice biogeochemistry and assesses the model sensitivity to (1) the temporal resolution of the snowfall forcing data, (2) the representation of light penetration through snow, (3) the horizontal transport of sea-ice biogeochemical state variables, and (4) light attenuation by ice algae. The sea-ice biogeochemical model has been developed within the generic framework of NEMO to facilitate its use within different configurations and domains, and can be adapted for use with other NEMO-based sub-models such as LIM3 (the Louvain-la-Neuve Sea Ice Model version 3) and PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies).
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Gottstein, Willi, Brett G. Olivier, Frank J. Bruggeman, and Bas Teusink. "Constraint-based stoichiometric modelling from single organisms to microbial communities." Journal of The Royal Society Interface 13, no. 124 (2016): 20160627. http://dx.doi.org/10.1098/rsif.2016.0627.
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Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and cross-feeding. Although considerable scientific progress has been made towards mapping and modelling species-level metabolism, elucidating the metabolic exchanges between microorganisms and steering the community dynamics remain an enormous scientific challenge. In view of the complexity, computational models of microbial communities are essential to obtain systems-level understanding of ecosystem functioning. This review discusses the applications and limitations of constraint-based stoichiometric modelling tools, and in particular flux balance analysis (FBA). We explain this approach from first principles and identify the challenges one faces when extending it to communities, and discuss the approaches used in the field in view of these challenges. We distinguish between steady-state and dynamic FBA approaches extended to communities. We conclude that much progress has been made, but many of the challenges are still open.
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Hu, Jie, Juan Liu, Peter Yuen, Fuzhong Li, and Linqiang Deng. "Modelling of a seasonally perturbed competitive three species impulsive system." Mathematical Biosciences and Engineering 19, no. 3 (2022): 3223–41. http://dx.doi.org/10.3934/mbe.2022149.
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<abstract><p>The population of biological species in the ecosystem is known sensitive to the periodic fluctuations of seasonal change, food resources and climatic conditions. Research in the ecological management discipline conventionally models the behavior of such dynamic systems through specific impulsive response functions, but the results of such research are applicable only when the environments conform exactly to the conditions as defined by the specific response functions that have been implemented for specific scenarios. This means that the application of previous work may be somewhat limited. Moreover, the intra and inter competitions among species have been seldom studied for modelling the prey-predator ecosystem. To fill in the gaps this paper models the delicate balance of two-prey and one-predator system by addressing three main areas of: ⅰ) instead of using the specific impulse response this work models the ecosystem through a more general response function; ⅱ) to include the effects due to the competition between species and ⅲ) the system is subjected to the influences of seasonal factors. The seasonal factor has been implemented here in terms of periodic functions to represent the growth rates of predators. The sufficient condition for the local and global asymptotic stability of the prey-free periodic solution and the permanence of the system have been subsequently obtained by using the Comparison techniques and the Floquet theorems. Finally, the correctness of developed theories is verified by numerical simulation, and the corresponding biological explanation is given.</p></abstract>
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Uusitalo, Laura, Maciej T. Tomczak, Bärbel Müller-Karulis, Ivars Putnis, Neda Trifonova, and Allan Tucker. "Hidden variables in a Dynamic Bayesian Network identify ecosystem level change." Ecological Informatics 45 (May 2018): 9–15. http://dx.doi.org/10.1016/j.ecoinf.2018.03.003.
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Power, S. A., C. G. Barker, E. A. Allchin, M. R. Ashmore, and J. N. B. Bell. "Habitat Management: A Tool to Modify Ecosystem Impacts of Nitrogen Deposition?" Scientific World JOURNAL 1 (2001): 714–21. http://dx.doi.org/10.1100/tsw.2001.379.
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Atmospheric nitrogen deposition has been shown to affect both the structure and the function of heathland ecosystems. Heathlands are semi-natural habitats and, as such, undergo regular management by mowing or burning. Different forms of management remove more or less nutrients from the system, so habitat management has the potential to mitigate some of the effects of atmospheric deposition. Data from a dynamic vegetation model and two field experiments are presented. The first involves nitrogen addition following different forms of habitat management. The second tests the use of habitat management to promote heathland recovery after a reduction in nitrogen deposition. Both modelling and experimental approaches suggest that plant and microbial response to nitrogen is affected by management. Shoot growth and rates of decomposition were lowest in plots managed using more intensive techniques, including mowing with litter removal and a high temperature burn. Field data also indicate that ecosystem recovery from prolonged elevated inputs of nitrogen may take many years, or even decades, even after the removal of plant and litter nitrogen stores which accompanies the more intensive forms of habitat management.
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Lehodey, Patrick. "The pelagic ecosystem of the tropical Pacific Ocean: dynamic spatial modelling and biological consequences of ENSO." Progress in Oceanography 49, no. 1-4 (2001): 439–68. http://dx.doi.org/10.1016/s0079-6611(01)00035-0.
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Zhang, Chongliang, Yong Chen, and Yiping Ren. "Assessing uncertainty of a multispecies size-spectrum model resulting from process and observation errors." ICES Journal of Marine Science 72, no. 8 (2015): 2223–33. http://dx.doi.org/10.1093/icesjms/fsv086.
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AbstractEcosystem models, specifically multispecies dynamic models, have been increasingly used to project impacts of fishing activity on the trophodynamics of ecosystems to support ecosystem-based fisheries management. Uncertainty is unavoidable in modelling processes and needs to be recognized and properly quantified before models are utilized. Uncertainty was assessed in this study for a multispecies size-spectrum model that quantifies community structure and ecological characteristics. The uncertainty was assumed to result from errors in fish life-history and metabolic scale parameters, environmental variability, fishing variability, and sampling errors. Given the same level of imprecision, metabolic scale parameters had the dominant influence on the uncertainty of the size spectrum modelling results, followed by life-history parameters. Both types of errors led to “scenario uncertainty”, suggesting the possible existence of alternative states of community structure. Environmental variability, fishing variability, and observation errors resulted in “statistical uncertainty”, implying that such uncertainty can be described adequately in statistical terms. The results derived from such a simulation study can provide guidance for identifying research priorities to help narrow the gap in scientific knowledge and reduce the uncertainty in fisheries management.