Ecological Modelling最新文献

{"title":"Coupling and interaction of ecological civilization subsystems in the Pearl River Delta: A \"production-living-ecological\" systems perspective","authors":"Qing Guo,&nbsp;Xiangyang Teng","doi":"10.1016/j.ecolmodel.2026.111512","DOIUrl":"10.1016/j.ecolmodel.2026.111512","url":null,"abstract":"<div><div>As a national strategic core region, the Pearl River Delta Region (PRD) faces inherent tensions between ecological preservation and high-quality development amid rapid urbanization and industrial transformation. This study establishes a three-dimensional synergistic framework encompassing Production- Living-Ecological systems, employing an integrated methodology combining entropy-weighted TOPSIS model, coupling coordination degree (CCDM) model, kernel density estimation (KDE) model, and panel vector autoregression (PVAR) method. Through systematic investigation of spatiotemporal patterns and multidimensional interaction mechanisms in ecological civilization system coordination from 2011 to 2020, the research reveals: <strong>(1) Production System (PS), Living System (LS), and ecological system (ES) in the Pearl River Delta demonstrated steady growth, with LS lagging behind in composite index; (2) Regional CCD exhibited long-term inefficiency, marked divergence among core cities, and coordination collapse under multiple shocks; (3) The systems lacked robust synergistic interactions, with notably weak contributions from LS and ES, overall characterized by “production-dominance, ecological-bearing and life-feedback.”</strong> The findings inform targeted policy recommendations for sustainable regional development.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"515 ","pages":"Article 111512"},"PeriodicalIF":3.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191927","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}

{"title":"Why should models talk to each other? A multipronged modelling strategy as an operational framework to guide adaptive watershed management in the Bay of Quinte Basin, Ontario, Canada","authors":"Carlos Alberto Arnillas,&nbsp;Aisha Javed,&nbsp;Alex Neumann,&nbsp;Lamees Shah,&nbsp;George B. Arhonditsis","doi":"10.1016/j.ecolmodel.2026.111506","DOIUrl":"10.1016/j.ecolmodel.2026.111506","url":null,"abstract":"<div><div>Environmental modelling has been one of the pillars of the adaptive watershed management process. It provides a way for scientists, managers, and other stakeholders to assess the existing understanding of the managed system and the knowledge gaps we seek to answer through monitoring and research. However, current watershed modelling and restoration efforts often fail to consider the role of different sources of aleatory and epistemic uncertainty surrounding the effectiveness of management practices. Estimating effectiveness is difficult because of poor spatial delineation of nutrient “hot-spots” at the regional planning level, misrepresentation of critical hydrological and biogeochemical processes at the watershed level, and several unaccounted factors operating at the individual farm or field levels, among others. Here, we outline an ongoing multi-pronged modelling approach for the Bay of Quinte that has been supporting the management in the area over the last ten years with the active participation of local stakeholders. The framework encompasses (<em>i</em>) regional assessment of high risk for nutrient export in time and space using mass-balance and semi-empirical nutrient loading models, (<em>ii</em>) mechanistic representations of watershed processes, and (<em>iii</em>) process-based representations of field dynamics. We summarize the key results from more than a dozen of research projects in that region and propose a coherent approach to integrate the information provided by them to improve modelling and monitoring. This framework specifies questions, methods, and data requirements relevant to each of its components, and the way they complement each other. This experience can provide a blueprint for adaptive watershed management worldwide.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"515 ","pages":"Article 111506"},"PeriodicalIF":3.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191614","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}

{"title":"Modeling impacts of N sources on N2O emissions in long-term crop rotation system in Brazil’s Cerrado using DNDCv.CAN","authors":"Johnny Rodrigues Soares ,&nbsp;Antônio Carlos Reis de Freitas ,&nbsp;Bruno José Rodrigues Alves ,&nbsp;Ward Smith ,&nbsp;Brian Grant ,&nbsp;Craig F. Drury ,&nbsp;Claudia Pozzi Jantalia ,&nbsp;Maria da Conceição Santana Carvalho ,&nbsp;Beata Emoke Madari","doi":"10.1016/j.ecolmodel.2026.111513","DOIUrl":"10.1016/j.ecolmodel.2026.111513","url":null,"abstract":"<div><div>Predicting N₂O emissions can help identify crop production practices and environmental conditions for mitigation. The objectives were to calibrate and validate the DeNitrification-DeComposition (DNDCv.CAN) model to simulate N₂O emission in crop rotation (CR) systems in Brazil’s Cerrado biome, using different N fertilizer sources. Field data were obtained from a CR experiment with maize and common beans cultivated under no-till for 10 years. Treatments were: Zero-N, calcium ammonium nitrate (CAN), urea (UR), and ammonium sulfate (AS), with 5 replicates. Measured data including N₂O fluxes, NH₃ volatilization, soil NH₄⁺ and NO₃^-, water-filled pore space (WFPS), and grain yields were used to calibrate and validate the DNDCv.CAN. The model acceptably captured the daily N₂O emissions associated with different N sources, although episodic peaks were over or under-predicted. Correlation coefficient was 0.62 during calibration, with a mean absolute error of 17 g N₂O-N ha^-1 day^-1, close to average measured (18 g ha^-1 d^-1), and simulated (17 g ha^-1 day^-1) emissions. Accumulated measured N₂O-N emissions were 1.19, 4.38, 3.17, and 2.56 kg N₂O-N ha^-1 for Zero-N, CAN, UR, and AS, respectively, whereas the simulated were 1.13, 3.44, 2.24, and 3.32 kg N₂O-N ha^-1. The NH₃, NH₄⁺, NO₃^-, WFPS, and yields were also fairly simulated. Soil hydrologic parameters were adjusted in the model using a built in pedotransfer function to improve the simulations, which should be further investigated. The DNDCv.CAN effectively simulated cumulative N₂O emissions from different N sources applied to CR under tropical conditions, making it valuable for evaluating potential emissions and mitigation strategies.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"515 ","pages":"Article 111513"},"PeriodicalIF":3.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191929","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}

{"title":"Emergy quantification of economic-social-ecological losses under water supply-demand dual regulation during mega-droughts","authors":"Xi Guo,&nbsp;Weijing Wang,&nbsp;Cuimei Lv,&nbsp;Chentao He,&nbsp;Qianqian Cao","doi":"10.1016/j.ecolmodel.2026.111508","DOIUrl":"10.1016/j.ecolmodel.2026.111508","url":null,"abstract":"<div><div>Scientifically quantifying the losses caused by supply-demand dual regulation measures under extreme drought conditions constitutes the fundamental basis for effectively addressing urban mega-droughts and mitigating their disaster impacts. To address the quantification of the comprehensive losses in regional ecological-economic systems resulting from bidirectional water supply-demand regulation under extreme drought conditions, this study introduces emergy theory to construct a loss quantification framework based on this approach. Specifically, on the supply side, it primarily considers the costs of tapping potential water sources and the resulting ecological and environmental damage, while on the demand side, it focuses mainly on the socio-economic losses due to water shortages and the negative ecological and environmental impacts caused by water use reduction. The framework is applied and validated using the case of the 2011 extreme drought in Chuxiong Prefecture, Yunnan Province. The results indicate that in Chuxiong Prefecture, the supply-side regulation cost was 4.76 × 10²⁰sej, equivalent to 1.356 billion EmCNY based on the emergy/money ratio, while the demand-side water restriction loss was 3.58 × 10²⁰ sej, equivalent to 1.019 billion EmCNY. The total economic-social-ecological loss from dual supply-demand regulation reached 2.375 billion EmCNY. In conclusion, the quantitative assessment of economic-social-ecological losses under dual-directional supply-demand regulation provides scientific support for extreme drought risk evaluation, government emergency response planning, and post-disaster recovery/reconstruction decision-making, thereby enhancing disaster prevention and mitigation capabilities.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111508"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078630","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}

{"title":"Generalized EPICS (gEPICS): Handling species extinctions in predicting microbial community structures using effective pairwise interactions","authors":"Aadhil Basith A ,&nbsp;Gayathri Sambamoorthy ,&nbsp;Kartikeya Aditya ,&nbsp;Aamir Faisal Ansari ,&nbsp;Bharat Cheviti ,&nbsp;Yugandhar B.S. Reddy ,&nbsp;Janhavi Raut ,&nbsp;Narendra M. Dixit","doi":"10.1016/j.ecolmodel.2026.111505","DOIUrl":"10.1016/j.ecolmodel.2026.111505","url":null,"abstract":"<div><div>Predicting the structures of multispecies microbial communities requires knowledge of the underlying interspecies interactions. EPICS, an efficient and scalable method, employs steady-state data from monocultures and leave-one-out subcommunities together with mathematical modelling to estimate effective pairwise interactions between species and accurately predicts community structures. A limitation, however, is its inability to handle scenarios wherein some species become extinct in leave-one-out subcommunities, restricting its scope. Here, we develop a generalization of EPICS (gEPICS) that overcomes this limitation. We reformulate the mathematical model in EPICS, built using the generalized Lotka-Volterra (GLV) equations, by accounting for missing species. This yields an under-determined system of equations in the unknown effective pairwise interaction coefficients. We estimate the coefficients using the Moore-Penrose pseudo-inverse. With these coefficients, we apply the model to predict community structures. We test gEPICS on a large number of <em>in silico</em> communities and find that it robustly predicts community structures. Its accuracy decreases with the number of missing species but increases with the total number of species involved, rendering it particularly suited to large communities. We apply it to two experimental systems from the literature, an 8-species synthetic soil microbial community and a 12-species synthetic gut microbial community. gEPICS accurately captures the structures of both the communities, demonstrating its applicability to diverse settings. gEPICS would serve as a useful tool to estimate interspecies interactions and engineer multispecies microbial communities.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111505"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078733","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}

{"title":"Theoretical insights from functional-response modeling of green sea turtle aggregation on seagrass","authors":"Naoto K. Inoue","doi":"10.1016/j.ecolmodel.2026.111493","DOIUrl":"10.1016/j.ecolmodel.2026.111493","url":null,"abstract":"<div><div>Long-term conservation efforts have contributed to the recovery of green sea turtle (<em>Chelonia mydas</em>) populations in many regions, highlighting the need to reassess conservation plans within a broader ecosystem context. In some areas, localized high turtle densities can impose strong grazing pressure on seagrass meadows. Two measures have been suggested to mitigate such impacts: (i) enhancing seagrass growth through nutrient or symbiotic algae supplementation, and (ii) managing turtle populations by predator protection or localized commercial use. However, model-based studies focusing on seagrass-turtle interactions remain limited, and the resulting effects of the measures on system dynamics are not well understood. To address the gap, the author developed a simple seagrass-turtle model that incorporates turtle aggregation in seagrass patches. By assuming that turtles move to the most seagrass-rich patch and applying simple distributions for seagrass shoot numbers per patch and the number of accessible patches, turtle aggregation was modeled as a simple functional response. The constructed model revealed that turtle aggregation causes positive density dependence in seagrass and negative density dependence in turtles, leading to destabilization through increased seagrass growth and stabilization through turtle population management. Extending the model to incorporate additional ecological factors, such as alternative turtle food resources or spatially heterogeneous environments, alongside empirical assessments of turtle mortality and its causes, could inform future management strategies.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111493"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978008","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}

{"title":"Balancing fishing effort along the tropical tuna abundance-size spectrum","authors":"Alex Tidd,&nbsp;Mariana Travassos Tolotti,&nbsp;Patrice Guillotreau,&nbsp;Nicolas Barrier,&nbsp;Laurent Dagorn","doi":"10.1016/j.ecolmodel.2026.111495","DOIUrl":"10.1016/j.ecolmodel.2026.111495","url":null,"abstract":"<div><div>The ecosystem approach to fisheries is widely recognised as a key management goal, yet its definition and implementation remain debated. Most fisheries management relies on single-species strategies with technical measures to reduce bycatch. However, selective removals disrupt species composition, affecting ecosystem dynamics and resilience. We present a proof-of-concept model based on balanced harvesting that allocates fishing pressure proportionally across three tuna stocks—yellowfin (<em>Thunnus albacares</em>), skipjack (<em>Katsuwonus pelamis</em>), and bigeye tuna (<em>Thunnus obesus</em>)—in the Indian Ocean according to their size-biomass ratios. The model optimises fishing effort by gear using a predefined objective function based on length-based population dynamics, ensuring a balanced harvest while maintaining each tuna species' biomass within its maximum sustainable yield (B_MSY) limit. By assigning fishing mortality (F-multiplier) to each fleet, the model aims to maintain, within the bounds of B_MSY for each stock, the ecosystem structure (based on size-abundance relationships) over a 20-year simulation. Results indicate significant reductions in fishing mortality across gears relative to 2020 levels. While some gears, such as purse seine free-school, show increased catches and revenues (146%), others, like purse seine log-school, experience declines (-22%). Overall, fishing at B_MSY improves total revenues and catches by 51% and 34%, respectively, compared to 2020. This work demonstrates that it is possible to maintain each tuna stock within B_MSY bounds by managing fishing fleets while preserving ecosystem structure, a significant goal of the ecosystem approach to fisheries.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111495"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038200","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}

{"title":"Forest wildfire emissions using the Canadian Fire Effects Model within the Generic Carbon Budget Model","authors":"C. Smyth ,&nbsp;M. Fellows ,&nbsp;A. Cantin","doi":"10.1016/j.ecolmodel.2026.111490","DOIUrl":"10.1016/j.ecolmodel.2026.111490","url":null,"abstract":"<div><div>This study integrated the Canadian Fire Effects Model (CanFIRE) within the Generic Carbon Budget Model (GCBM) to improve greenhouse gas (GHG) emissions from future wildfires. The new framework estimates wildland fire combustion emissions and mortality using species-specific algorithms for 11 tree species. We tested this framework on a national forest carbon simulation and compared the results to a previous study that used general combustion and mortality impacts for different regions. Our findings indicate that the new framework results in higher emissions estimates, mainly from the soil organic horizon. This framework is available as a GCBM module, offering a tool for wildfire and carbon studies in dynamic landscapes and analyzing wildfire management strategies and their potential to reduce GHG emissions</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111490"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978009","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}

{"title":"Interpretability of graph neural networks to assess effects of global change drivers on ecological networks","authors":"Emre Anakok ,&nbsp;Pierre Barbillon ,&nbsp;Colin Fontaine ,&nbsp;Elisa Thebault","doi":"10.1016/j.ecolmodel.2025.111472","DOIUrl":"10.1016/j.ecolmodel.2025.111472","url":null,"abstract":"<div><div>Pollinators play a crucial role for plant reproduction, either in natural ecosystem or in human-modified landscape. Global change drivers, including climate change or land use modifications, can alter the plant–pollinator interactions. To assess the potential influence of global change drivers on pollination, large-scale interactions, climate and land use data are required. While recent machine learning methods, such as graph neural networks (GNNs), allow the analysis of such datasets, interpreting their results can be challenging. We explore existing methods for interpreting GNNs in order to highlight the effects of various environmental covariates on pollination network connectivity. An extensive simulation study is performed to confirm whether these methods can detect the interactive effect between a covariate and a genus of plant on connectivity, and whether the application of debiasing techniques influences the estimation of these effects. An application on the Spipoll dataset, with and without accounting for sampling effects, highlights the potential impact of land use on network connectivity and shows that accounting for sampling effects partially alters the estimation of these effects.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111472"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978007","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}

{"title":"A mechanistic approach to understanding birth timing, calf growth, and residency of southern right whale mother–calf pairs on their calving ground","authors":"Fredrik Christiansen ,&nbsp;Shane Dickeson ,&nbsp;Kate R. Sprogis","doi":"10.1016/j.ecolmodel.2026.111500","DOIUrl":"10.1016/j.ecolmodel.2026.111500","url":null,"abstract":"<div><div>Understanding residency patterns provides valuable insights into animal life history and is fundamental for establishing protected areas. Southern right whales (<em>Eubalaena australis</em>) are migratory capital breeders, with females accumulating energy reserves on summer feeding grounds to sustain late gestation and early lactation while fasting on winter calving grounds. On these oligotrophic calving grounds, mothers must grow their calves to a size suitable for migration without depleting their finite energy stores. To better understand this trade-off, we developed a mechanistic model to estimate the residency duration of mother–calf pairs at Australia’s largest calving aggregation. By linking maternal body size and condition to key reproductive traits, including birth timing, size at birth, calf growth rate, and departure timing, we quantified the effect of maternal phenotype on residency duration. Maternal size and condition positively influenced both calf birth size and growth rate. Absolute calf size was the primary driver of departure, with pairs leaving once the calf reached approximately 8 m in length, which likely improves calf locomotor performance and reduces predation risk. Larger, better-conditioned mothers could grow their calves more rapidly, enabling earlier departure and a shorter residency period. This, in turn, allowed mothers to return to feeding grounds sooner and replenish depleted energy reserves. Our findings highlight how the early lactation phase in SRWs is shaped by the energetic constraints of capital breeding and the demands of migration and underscore the importance of maternal traits in determining residency duration on calving grounds.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"514 ","pages":"Article 111500"},"PeriodicalIF":3.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038198","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}