Pub Date : 2025-12-08DOI: 10.1016/j.ecolmodel.2025.111436
Xiaohuan Xie , Qiting Lin , Shengyuan Li , Xin Liu , Zhonghua Gou
Urban expansion in mega-city fringe areas often exacerbates trade-offs between economic development and ecosystem services (ES) degradation. This study introduces a novel integrated modeling framework—System Dynamics (SD)-PLUS-InVEST-Coupling Coordination Degree (CCD)—to simulate and optimize urban expansion rates for balanced economy-ecology outcomes. We develop the Urban Expansion–Ecosystem–Economic Index (UEEEI) as a quantitative metric to evaluate these interactions. Applied to Huadu District, Guangzhou, the framework simulates UEEEI under seven expansion scenarios for 2035: shrinkage (SHRINK), halt (STOP), strong deceleration (SLOW-2), mild deceleration (SLOW-1), baseline (BASED), mild acceleration (FAST-1), and strong acceleration (FAST-2). Model validation shows high accuracy (e.g., PLUS Kappa = 0.82; SD errors <3%). Results reveal an inverted U-shaped relationship between UEEEI and expansion rate (R² = 0.929), with SLOW-2 (0–1.414 km²/yr) yielding optimal coordination (UEEEI = 0.844). The framework provides a transferable tool for multi-scenario simulations in urbanizing regions, advancing ecological modeling by coupling land-use dynamics, ES valuation, and socio-economic feedbacks.
{"title":"Optimal urban expansion rates for balancing ecosystem services and economic development in mega-city fringe areas: A modeling framework applied to Huadu district, Guangzhou","authors":"Xiaohuan Xie , Qiting Lin , Shengyuan Li , Xin Liu , Zhonghua Gou","doi":"10.1016/j.ecolmodel.2025.111436","DOIUrl":"10.1016/j.ecolmodel.2025.111436","url":null,"abstract":"<div><div>Urban expansion in mega-city fringe areas often exacerbates trade-offs between economic development and ecosystem services (ES) degradation. This study introduces a novel integrated modeling framework—System Dynamics (SD)-PLUS-InVEST-Coupling Coordination Degree (CCD)—to simulate and optimize urban expansion rates for balanced economy-ecology outcomes. We develop the Urban Expansion–Ecosystem–Economic Index (UEEEI) as a quantitative metric to evaluate these interactions. Applied to Huadu District, Guangzhou, the framework simulates UEEEI under seven expansion scenarios for 2035: shrinkage (SHRINK), halt (STOP), strong deceleration (SLOW-2), mild deceleration (SLOW-1), baseline (BASED), mild acceleration (FAST-1), and strong acceleration (FAST-2). Model validation shows high accuracy (e.g., PLUS Kappa = 0.82; SD errors <3%). Results reveal an inverted U-shaped relationship between UEEEI and expansion rate (R² = 0.929), with SLOW-2 (0–1.414 km²/yr) yielding optimal coordination (UEEEI = 0.844). The framework provides a transferable tool for multi-scenario simulations in urbanizing regions, advancing ecological modeling by coupling land-use dynamics, ES valuation, and socio-economic feedbacks.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111436"},"PeriodicalIF":3.2,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145748056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1016/j.ecolmodel.2025.111431
Hugo Salinas, Erik J Veneklaas, Elizabeth J Trevenen, Michael Renton
Plant competition can be classified as symmetric when resource acquisition is proportional to plant size, or asymmetric when it is not. Identifying the symmetry of competition has important applications for population management. Many of the approaches that have been used to do this involve measuring growth over time, or through controlled experiments. An approach that uses measurements from a single point in time would be convenient. It is expected that populations under asymmetric competition will be more variable in plant size than those under symmetric competition, thus size variation at a single time could be an indicator of competition symmetry. However, other factors can also affect size variation, and thus it is critical to assess in which conditions size variation could be a good predictor of competition symmetry.
We used a novel combination of simulation modelling and statistical analysis to explore this question. We simulated single species plant populations with varying density, spatial randomness, and initial plant size variation. Based on simulation outputs, we used Bayesian linear models to describe size variation as a function of the mean and standard deviation of the number of plant neighbours in a population, then used these models to study in what conditions size variation is or is not indicative of competition symmetry.
Our results indicate that the single-time plant size coefficient of variation can be a useful predictor of the symmetry of competition in populations with higher densities and spatial randomness, up to 72 % accurate, but will be less useful in populations with low plant density or low spatial randomness. In such situations, asymmetric competition was often misclassified as symmetric, due to infrequent interactions and low variation in interactions among plants.
This study provides insights into the complex relationships among tree density, spatial distribution, competition intensity, competition symmetry and plant size variation. Our approach has the potential to help understand and even infer competition symmetry in real tree populations.
{"title":"Plant size-variation in conjunction with number of neighbours may be an indicator of competition symmetry","authors":"Hugo Salinas, Erik J Veneklaas, Elizabeth J Trevenen, Michael Renton","doi":"10.1016/j.ecolmodel.2025.111431","DOIUrl":"10.1016/j.ecolmodel.2025.111431","url":null,"abstract":"<div><div>Plant competition can be classified as symmetric when resource acquisition is proportional to plant size, or asymmetric when it is not. Identifying the symmetry of competition has important applications for population management. Many of the approaches that have been used to do this involve measuring growth over time, or through controlled experiments. An approach that uses measurements from a single point in time would be convenient. It is expected that populations under asymmetric competition will be more variable in plant size than those under symmetric competition, thus size variation at a single time could be an indicator of competition symmetry. However, other factors can also affect size variation, and thus it is critical to assess in which conditions size variation could be a good predictor of competition symmetry.</div><div>We used a novel combination of simulation modelling and statistical analysis to explore this question. We simulated single species plant populations with varying density, spatial randomness, and initial plant size variation. Based on simulation outputs, we used Bayesian linear models to describe size variation as a function of the mean and standard deviation of the number of plant neighbours in a population, then used these models to study in what conditions size variation is or is not indicative of competition symmetry.</div><div>Our results indicate that the single-time plant size coefficient of variation can be a useful predictor of the symmetry of competition in populations with higher densities and spatial randomness, up to 72 % accurate, but will be less useful in populations with low plant density or low spatial randomness. In such situations, asymmetric competition was often misclassified as symmetric, due to infrequent interactions and low variation in interactions among plants.</div><div>This study provides insights into the complex relationships among tree density, spatial distribution, competition intensity, competition symmetry and plant size variation. Our approach has the potential to help understand and even infer competition symmetry in real tree populations.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111431"},"PeriodicalIF":3.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-02DOI: 10.1016/j.ecolmodel.2025.111426
Neftalí Sillero , João Alírio , Nuno Garcia , Inês Freitas , João C. Campos , Lia Bárbara Duarte , Isabel Pôças , Ana Cláudia Teodoro , Salvador Arenas-Castro , A.Márcia Barbosa
ecotrends is an R package that provides a comprehensive framework for assessing species vulnerability by analysing temporal trends in habitat suitability. The framework consists of calculating ecological niche models successively on the same species occurrence data over time, using a time series of environmental variables, for any period and periodicity. Then, a trend analysis of habitat suitability is performed with Sen's slope, based on non-parametric Kendall's rank correlation. ecotrends includes functions for automatically gathering a yearly time series of environmental data from TerraClimate, calculating and evaluating Maxent models, assessing temporal trends in habitat suitability, and estimating variable importance. Although the built-in functions facilitate the use of a specific environmental database and modelling method, ecotrends works as well with any variables and models the user may provide. This adaptable framework can be applied to any taxon or guild, study area, spatial scale, or temporal resolution, as long as the required data are available. ecotrends offers a valuable tool for estimating species vulnerability over time and for supporting the evaluation of conservation measures. ecotrends allows the analysis of habitat suitability trends over time, requiring only species occurrence data and a time series of environmental data.
{"title":"Ecotrends: an R package for estimating habitat suitability trends over time","authors":"Neftalí Sillero , João Alírio , Nuno Garcia , Inês Freitas , João C. Campos , Lia Bárbara Duarte , Isabel Pôças , Ana Cláudia Teodoro , Salvador Arenas-Castro , A.Márcia Barbosa","doi":"10.1016/j.ecolmodel.2025.111426","DOIUrl":"10.1016/j.ecolmodel.2025.111426","url":null,"abstract":"<div><div>ecotrends is an R package that provides a comprehensive framework for assessing species vulnerability by analysing temporal trends in habitat suitability. The framework consists of calculating ecological niche models successively on the same species occurrence data over time, using a time series of environmental variables, for any period and periodicity. Then, a trend analysis of habitat suitability is performed with Sen's slope, based on non-parametric Kendall's rank correlation. ecotrends includes functions for automatically gathering a yearly time series of environmental data from TerraClimate, calculating and evaluating Maxent models, assessing temporal trends in habitat suitability, and estimating variable importance. Although the built-in functions facilitate the use of a specific environmental database and modelling method, ecotrends works as well with any variables and models the user may provide. This adaptable framework can be applied to any taxon or guild, study area, spatial scale, or temporal resolution, as long as the required data are available. ecotrends offers a valuable tool for estimating species vulnerability over time and for supporting the evaluation of conservation measures. ecotrends allows the analysis of habitat suitability trends over time, requiring only species occurrence data and a time series of environmental data.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111426"},"PeriodicalIF":3.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ecolmodel.2025.111429
Rafael Araújo Nacimento , Mario Duarte Canever , Fábio José Muneratti Ortega , Luiz Carlos Terra dos Santos , Regis Augusto Ely , Augusto Hauber Gameiro , Feni Agostinho , Cecília Almeida , Biagio Fernando Giannetti
Food security is often linked to economic exchange, but it involves broader dynamics and can also be achieved through non-market pathways. Recognizing this complexity, the Emergy Exchange Ratio (EER) was proposed—a ratio between the emergy of food acquired and that of money spent—as a complementary indicator to assess food security. In this study, we examined the relationship between the EER and the four dimensions of food security using indicators from the Global Food Security Index (GFSI). Machine learning models, particularly Ridge Regression, were employed to predict EER values for Brazil from 2012 to 2022. The Ridge model showed strong performance (R² = 0.89; MAE = 0.035), indicating good explanatory power. Among 25 GFSI indicators, “food security and access policy commitments” (∼16 %) and “sufficiency of supply” (∼14 %) were the top predictors of EER variation. These results suggest that the EER is sensitive to public policies and food supply dynamics, indicating its relationship with food security. Limitations include the focus on Brazilian data and data quality constraints. Still, EER offers a systemic, biophysical lens on food access grounded in Odum’s emergy theory.
{"title":"Integrating emergy theory and food security: An examination of the emergy exchange ratio","authors":"Rafael Araújo Nacimento , Mario Duarte Canever , Fábio José Muneratti Ortega , Luiz Carlos Terra dos Santos , Regis Augusto Ely , Augusto Hauber Gameiro , Feni Agostinho , Cecília Almeida , Biagio Fernando Giannetti","doi":"10.1016/j.ecolmodel.2025.111429","DOIUrl":"10.1016/j.ecolmodel.2025.111429","url":null,"abstract":"<div><div>Food security is often linked to economic exchange, but it involves broader dynamics and can also be achieved through non-market pathways. Recognizing this complexity, the Emergy Exchange Ratio (EER) was proposed—a ratio between the emergy of food acquired and that of money spent—as a complementary indicator to assess food security. In this study, we examined the relationship between the EER and the four dimensions of food security using indicators from the Global Food Security Index (GFSI). Machine learning models, particularly Ridge Regression, were employed to predict EER values for Brazil from 2012 to 2022. The Ridge model showed strong performance (R² = 0.89; MAE = 0.035), indicating good explanatory power. Among 25 GFSI indicators, “food security and access policy commitments” (∼16 %) and “sufficiency of supply” (∼14 %) were the top predictors of EER variation. These results suggest that the EER is sensitive to public policies and food supply dynamics, indicating its relationship with food security. Limitations include the focus on Brazilian data and data quality constraints. Still, EER offers a systemic, biophysical lens on food access grounded in Odum’s emergy theory.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111429"},"PeriodicalIF":3.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ecolmodel.2025.111433
K.J. Challis
We develop an aggregate potential landscape description of a specific agent-based model of social-ecological tipping-point dynamics. The landscape model is two dimensional, incorporating dynamics in social opinions and biomass availability, with nonseparable coupling potentials to describe exploitation and perception. We find that the landscape model successfully captures key features of the agent-based model, including collective tipping points and transition pathways, but differs in ecological recovery timescales and final states. These results demonstrate how an aggregate potential landscape model can be implemented for social-ecological dynamics, while emphasising the need for detailed models of two-way feedback and path dependence.
{"title":"An aggregate potential landscape description of an agent-based exploitation-perception model for social-ecological tipping-point dynamics","authors":"K.J. Challis","doi":"10.1016/j.ecolmodel.2025.111433","DOIUrl":"10.1016/j.ecolmodel.2025.111433","url":null,"abstract":"<div><div>We develop an aggregate potential landscape description of a specific agent-based model of social-ecological tipping-point dynamics. The landscape model is two dimensional, incorporating dynamics in social opinions and biomass availability, with nonseparable coupling potentials to describe exploitation and perception. We find that the landscape model successfully captures key features of the agent-based model, including collective tipping points and transition pathways, but differs in ecological recovery timescales and final states. These results demonstrate how an aggregate potential landscape model can be implemented for social-ecological dynamics, while emphasising the need for detailed models of two-way feedback and path dependence.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111433"},"PeriodicalIF":3.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ecolmodel.2025.111423
Katsumi Matsumoto , Ziyu Guo , Amy E. Maas
Understanding how the ecological stoichiometry of plankton is related to the broader carbon cycle is one of the major questions in ecology and biogeochemistry. However, the role that stoichiometric imbalance between marine phytoplankton and zooplankton play in driving their interaction is not well understood. Here, we use a simple food web model set in idealized, 0- and 1-dimensional model domains in subtropical conditions to study how zooplankton selectivity for a higher food quality prey can shift the plankton community, stoichiometry, and carbon export production. In the model, a single class of zooplankton, whose stoichiometry is close to the Redfield C:N:P ratio, has two prey types: eukaryotic phytoplankton and cyanobacteria. As observed, the cyanobacteria type in the model is a gleaner, has a higher C:N:P ratio, and is thus more nutritionally unbalanced than the eukaryote type. We find that as zooplankton grazing becomes more selective based on food quality, it drives down the eukaryote biomass, allows cyanobacteria to flourish, depletes the ambient nutrient levels, elevates the phytoplankton and organic matter C:N:P ratio, and increases carbon export production. In the 1-dimensional model, these general trends are modulated as the euphotic zone and the mixed layer depths change seasonally. In a novel and important finding, this work indicates that the stoichiometric modulation of grazing can have a direct link to carbon export in the ocean. A more realistic modeling effort, combined with model-data comparison, is needed to confirm this finding.
{"title":"Stoichiometric modulation of zooplankton grazing on ocean organic matter biogeochemistry: Results from idealized food web modeling","authors":"Katsumi Matsumoto , Ziyu Guo , Amy E. Maas","doi":"10.1016/j.ecolmodel.2025.111423","DOIUrl":"10.1016/j.ecolmodel.2025.111423","url":null,"abstract":"<div><div>Understanding how the ecological stoichiometry of plankton is related to the broader carbon cycle is one of the major questions in ecology and biogeochemistry. However, the role that stoichiometric imbalance between marine phytoplankton and zooplankton play in driving their interaction is not well understood. Here, we use a simple food web model set in idealized, 0- and 1-dimensional model domains in subtropical conditions to study how zooplankton selectivity for a higher food quality prey can shift the plankton community, stoichiometry, and carbon export production. In the model, a single class of zooplankton, whose stoichiometry is close to the Redfield C:N:P ratio, has two prey types: eukaryotic phytoplankton and cyanobacteria. As observed, the cyanobacteria type in the model is a gleaner, has a higher C:N:P ratio, and is thus more nutritionally unbalanced than the eukaryote type. We find that as zooplankton grazing becomes more selective based on food quality, it drives down the eukaryote biomass, allows cyanobacteria to flourish, depletes the ambient nutrient levels, elevates the phytoplankton and organic matter C:N:P ratio, and increases carbon export production. In the 1-dimensional model, these general trends are modulated as the euphotic zone and the mixed layer depths change seasonally. In a novel and important finding, this work indicates that the stoichiometric modulation of grazing can have a direct link to carbon export in the ocean. A more realistic modeling effort, combined with model-data comparison, is needed to confirm this finding.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111423"},"PeriodicalIF":3.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-29DOI: 10.1016/j.ecolmodel.2025.111425
Rui Zhao, Xuefeng Min, Yang Yu, Wenjie Xu, Shi Yang, Lianghan Zhu, Qin Mou
Basin-wide pollutant load allocation is essential for integrated pollution control, but current approaches often overlook future pollutant discharge, rely on single policy instruments, and neglect multi-stakeholder interactions. To address these limitations, this study proposes a Bi-Level Game Dynamic Allocation Model (BLG-DAM) that synergistically integrates pollutant transport processes, stakeholder interactions, and environmental tax responses. Driven by meteorological data fusion from the China Meteorological Assimilation Driving Datasets (CMADS) and the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) datasets, the SWAT model achieves high-fidelity simulation of pollutant transport. Incorporating system dynamics enables the bi-level game to capture strategic stakeholder interactions across governance levels while facilitating dynamic information transfer between decision-makers and implementers. Applied to the ecologically sensitive Meishan reach of China’s Minjiang River Basin, which subject to intense urban-rural pollution pressures, the model quantified 2020 annual loads at 7690.25 tons NH3N, 8759.11 tons TN, and 9387.29 tons TP. Optimization results demonstrate that the proposed BLG-DAM can achieve reductions in NH₃-N, TN, and TP loads by 43.77 %, 32.48 %, and 35.79 %, respectively, by 2025. Under an environmental tax rate of 14 CNY per pollution equivalent, the model is projected to generate a total basin revenue of 2.15 billion CNY, while also increasing cooperation among control units from 25 % to 90 %. These outcomes indicate a successful alignment of economic incentives with water-quality targets, underscoring the model’s utility as a practical and scalable tool for supporting sustainable watershed management.
{"title":"A bi-level game model for dynamic pollutant load allocation integrating pollutant transport processes and stakeholder interaction","authors":"Rui Zhao, Xuefeng Min, Yang Yu, Wenjie Xu, Shi Yang, Lianghan Zhu, Qin Mou","doi":"10.1016/j.ecolmodel.2025.111425","DOIUrl":"10.1016/j.ecolmodel.2025.111425","url":null,"abstract":"<div><div>Basin-wide pollutant load allocation is essential for integrated pollution control, but current approaches often overlook future pollutant discharge, rely on single policy instruments, and neglect multi-stakeholder interactions. To address these limitations, this study proposes a Bi-Level Game Dynamic Allocation Model (BLG-DAM) that synergistically integrates pollutant transport processes, stakeholder interactions, and environmental tax responses. Driven by meteorological data fusion from the China Meteorological Assimilation Driving Datasets (CMADS) and the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) datasets, the SWAT model achieves high-fidelity simulation of pollutant transport. Incorporating system dynamics enables the bi-level game to capture strategic stakeholder interactions across governance levels while facilitating dynamic information transfer between decision-makers and implementers. Applied to the ecologically sensitive Meishan reach of China’s Minjiang River Basin, which subject to intense urban-rural pollution pressures, the model quantified 2020 annual loads at 7690.25 tons NH<sub>3</sub><sub><img></sub>N, 8759.11 tons TN, and 9387.29 tons TP. Optimization results demonstrate that the proposed BLG-DAM can achieve reductions in NH₃-N, TN, and TP loads by 43.77 %, 32.48 %, and 35.79 %, respectively, by 2025. Under an environmental tax rate of 14 CNY per pollution equivalent, the model is projected to generate a total basin revenue of 2.15 billion CNY, while also increasing cooperation among control units from 25 % to 90 %. These outcomes indicate a successful alignment of economic incentives with water-quality targets, underscoring the model’s utility as a practical and scalable tool for supporting sustainable watershed management.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111425"},"PeriodicalIF":3.2,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-29DOI: 10.1016/j.ecolmodel.2025.111424
Konrad Matyja
Mechanistic models can be used to simulate, optimize, and control bioprocesses. The accuracy and reliability of their predictions strongly depend on the uncertainty of model parameters. The quality of estimates is therefore a crucial feature of the model used. There are many methods of experimental design, often based on linear regression and simple statistical reasoning; however, there is a lack of methods dedicated to designing experiments that provide optimal data sets for kinetic model calibration. It appears that parameters-to-data sensitivity coefficients (PSCs) can be used to determine when dependent variables need to be measured to achieve a good model fit. Therefore, in this study, various methods for determining PSCs and evaluating their properties were assessed to propose a new experimental design procedure. The new method enables a reduction in the number of measurements and the uncertainty of estimated parameters. It can be used to reduce the time and costs of experiments.
{"title":"Reducing parameter uncertainty in kinetic models: A new strategy for experimental design","authors":"Konrad Matyja","doi":"10.1016/j.ecolmodel.2025.111424","DOIUrl":"10.1016/j.ecolmodel.2025.111424","url":null,"abstract":"<div><div>Mechanistic models can be used to simulate, optimize, and control bioprocesses. The accuracy and reliability of their predictions strongly depend on the uncertainty of model parameters. The quality of estimates is therefore a crucial feature of the model used. There are many methods of experimental design, often based on linear regression and simple statistical reasoning; however, there is a lack of methods dedicated to designing experiments that provide optimal data sets for kinetic model calibration. It appears that parameters-to-data sensitivity coefficients (PSCs) can be used to determine when dependent variables need to be measured to achieve a good model fit. Therefore, in this study, various methods for determining PSCs and evaluating their properties were assessed to propose a new experimental design procedure. The new method enables a reduction in the number of measurements and the uncertainty of estimated parameters. It can be used to reduce the time and costs of experiments.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111424"},"PeriodicalIF":3.2,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-29DOI: 10.1016/j.ecolmodel.2025.111417
Henry Amorocho-Daza , Janez Sušnik , Jill H. Slinger , Pieter van der Zaag
Managing natural resources in transboundary river basins is a complex task in which societal needs and environmental impact are intertwined. The nexus paradigm engages with such a challenge by analysing synergies and trade-offs across Water-Energy-Food-Ecosystems (WEFE) sectors. We present a WEFE nexus operationalisation using a participatory modelling approach in the transboundary Lielupe river basin, shared between Latvia and Lithuania. Using a modelling cycle approach, we illustrate a stakeholder-driven pathway from generic and qualitative to increasingly quantitative system tools useful for basin-scale policy analysis. Stakeholders prioritised agricultural nutrient pollution as a critical nexus issue strongly linked to land-use. Three policy alternatives to address this issue were co-identified with stakeholders from both riparian countries: (i) implementing nature-based solutions; (ii) transitioning to organic agriculture; and (iii) promoting arable land-use transitions to former native landscapes. The long-term effect of such policies is explored using a System Dynamics simulation model. Results highlight the importance of promoting active transboundary cooperation for water quality control, as unilateral action hampers the effect of long-term ambitious policies. Even highly ambitious unilateral action can delay the achievement of river basin quality objectives in the order of a decade, a critical finding for the wider Baltic region and the achievement of EU water quality objectives. Based on an exploratory analysis, we found that implementing basin-scale solutions for nutrient control would reduce nitrogen concentration by around 30 % with a 2 % co-benefit of increasing vegetation stocks, yet at the cost of decreasing cereal production by 8 %. This work illustrates the capabilities of a tailor-made simulation model crafted to answer locally relevant policy questions with a nexus perspective in a transboundary river basin. Developing and using a simulation model in a participatory way can explore policy futures while fostering dialogue among riparian stakeholders. This is a promising way to promote cooperation towards solving critical socio-environmental issues in transboundary rivers.
{"title":"A participatory system dynamics approach to assess transboundary nutrient pollution: modelling the water-energy-food-ecosystems nexus in the Lielupe River Basin, Lithuania and Latvia","authors":"Henry Amorocho-Daza , Janez Sušnik , Jill H. Slinger , Pieter van der Zaag","doi":"10.1016/j.ecolmodel.2025.111417","DOIUrl":"10.1016/j.ecolmodel.2025.111417","url":null,"abstract":"<div><div>Managing natural resources in transboundary river basins is a complex task in which societal needs and environmental impact are intertwined. The nexus paradigm engages with such a challenge by analysing synergies and trade-offs across Water-Energy-Food-Ecosystems (WEFE) sectors. We present a WEFE nexus operationalisation using a participatory modelling approach in the transboundary Lielupe river basin, shared between Latvia and Lithuania. Using a modelling cycle approach, we illustrate a stakeholder-driven pathway from generic and qualitative to increasingly quantitative system tools useful for basin-scale policy analysis. Stakeholders prioritised agricultural nutrient pollution as a critical nexus issue strongly linked to land-use. Three policy alternatives to address this issue were co-identified with stakeholders from both riparian countries: (i) implementing nature-based solutions; (ii) transitioning to organic agriculture; and (iii) promoting arable land-use transitions to former native landscapes. The long-term effect of such policies is explored using a System Dynamics simulation model. Results highlight the importance of promoting active transboundary cooperation for water quality control, as unilateral action hampers the effect of long-term ambitious policies. Even highly ambitious unilateral action can delay the achievement of river basin quality objectives in the order of a decade, a critical finding for the wider Baltic region and the achievement of EU water quality objectives. Based on an exploratory analysis, we found that implementing basin-scale solutions for nutrient control would reduce nitrogen concentration by around 30 % with a 2 % co-benefit of increasing vegetation stocks, yet at the cost of decreasing cereal production by 8 %. This work illustrates the capabilities of a tailor-made simulation model crafted to answer locally relevant policy questions with a nexus perspective in a transboundary river basin. Developing and using a simulation model in a participatory way can explore policy futures while fostering dialogue among riparian stakeholders. This is a promising way to promote cooperation towards solving critical socio-environmental issues in transboundary rivers.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111417"},"PeriodicalIF":3.2,"publicationDate":"2025-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-28DOI: 10.1016/j.ecolmodel.2025.111428
Carlos Victor Dantas Araújo , Fábio Luiz Usberti , Emily Brito de Oliveira , Laura Silva de Assis , Celso Cavellucci
This study introduces a multi-agent-based simulation (MABS) methodology for modeling the transmission spread of the dengue virus. The proposed methodology provides a flexible and adaptable approach to simulate the spread of dengue, accounting for the complex interactions between human populations, mosquitoes, and the environment. By leveraging agent-based modeling techniques, we can capture the stochastic nature of disease transmission and explore the impact of various factors, such as human behavior and vector control interventions. The model’s ability to generate realistic scenarios, even in the face of limited data, makes it a valuable tool for understanding the epidemiology of dengue and informing public health strategies, thus, this approach can also serve as a visualization and decision-support tool. The effectiveness of the proposed MABS framework is validated through its application to the cities of Alto Santo and Limoeiro, Brazil. However, it is easy to adapt to other cities using basic geographic information and historical data to determine optimal parameters.
{"title":"Multi-agent simulation for dengue spread forecast: A case study for two Brazilian cities","authors":"Carlos Victor Dantas Araújo , Fábio Luiz Usberti , Emily Brito de Oliveira , Laura Silva de Assis , Celso Cavellucci","doi":"10.1016/j.ecolmodel.2025.111428","DOIUrl":"10.1016/j.ecolmodel.2025.111428","url":null,"abstract":"<div><div>This study introduces a multi-agent-based simulation (MABS) methodology for modeling the transmission spread of the dengue virus. The proposed methodology provides a flexible and adaptable approach to simulate the spread of dengue, accounting for the complex interactions between human populations, mosquitoes, and the environment. By leveraging agent-based modeling techniques, we can capture the stochastic nature of disease transmission and explore the impact of various factors, such as human behavior and vector control interventions. The model’s ability to generate realistic scenarios, even in the face of limited data, makes it a valuable tool for understanding the epidemiology of dengue and informing public health strategies, thus, this approach can also serve as a visualization and decision-support tool. The effectiveness of the proposed MABS framework is validated through its application to the cities of Alto Santo and Limoeiro, Brazil. However, it is easy to adapt to other cities using basic geographic information and historical data to determine optimal parameters.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"513 ","pages":"Article 111428"},"PeriodicalIF":3.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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