Ecological Modelling最新文献

{"title":"Evaluating the Dynamics of Brazil's soybean trade: a comprehensive emergy analysis of resource dependencies","authors":"Cláudia Leão ,&nbsp;Luiz C. Terra dos Santos ,&nbsp;Biagio F. Giannetti ,&nbsp;Feni Agostinho ,&nbsp;Cecilia M.V.B. Almeida","doi":"10.1016/j.ecolmodel.2025.111202","DOIUrl":"10.1016/j.ecolmodel.2025.111202","url":null,"abstract":"<div><div>This study examines Brazil's soybean trade through the dual lens of economic and environmental considerations, employing emergy synthesis to reveal hidden resource dependencies and costs within production and export processes. It bridges ecological modeling and sustainability science by analyzing Brazil's soybean trade through the interplay of economic and environmental dimensions. By applying emergy-based indices—such as the Emergy Exchange Ratio, Emergy Benefit Ratio, and Opportunity Ratio - the analysis offers a nuanced understanding of trade dynamics between 2015 and 2019, particularly with partners like China and Europe. The trade with China showed an average EER of 0.27, meaning that for every unit of emergy value Brazil exported in raw soybeans, it received substantially more emergy in currency terms. In comparison, trade with European partners, such as Spain and The Netherlands, with EE&gt;1, was notably unfavorable for Brazil. The Opportunity Ratio is another key metric to indicate the potential economic gains from processing raw soybean commodities domestically. The analysis revealed that, on average, domestic processing could potentially lead to a GDP increase of 17 % from the soybean sector. Highlighting the environmental implications of reliance on non-renewable inputs such as fertilizers and pesticides, the study underscores the potential benefits of domestic soybean processing for enhancing GDP, reducing import dependency, and fostering equitable resource use. The research provides insights into sustainability through carefully integrating economic and ecological perspectives, informing strategies for addressing environmental costs while fostering balanced global trade practices.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111202"},"PeriodicalIF":2.6,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204719","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":"Ecological modeling and parameter estimation for predator–prey dynamics in a closed habitat: A case study of Isle Royale","authors":"Long Lee,&nbsp;Ryan W. Foy","doi":"10.1016/j.ecolmodel.2025.111190","DOIUrl":"10.1016/j.ecolmodel.2025.111190","url":null,"abstract":"<div><div>Translating ecological observations into predictive mathematical models presents significant difficulties, which include the complexity of accurately capturing biological processes through simplified models, limited data availability, data measurement noise, and parameter estimation for such models. This paper introduces a stochastic framework to facilitate model selection and regularize the parameter estimation problem for continuous-time predator–prey ecological systems in a closed habitat given scarce discrete-time measurements. We use the historical moose–wolf population data on Isle Royale as a case study to illustrate the modeling process. Ecological studies of the moose–wolf relationship in Isle Royale National Park have been reported annually since 1959. Based on aerial surveys during winter, fluctuations in the abundance of wolves and moose were estimated from 1959 to present. We propose a model-based Markov chain Monte Carlo (MCMC) method and a sequential Monte Carlo (SMC) method, a.k.a. particle filter, to estimate this time series. We start with the classic constant-coefficient Lotka–Volterra model. While the model captures the oscillatory behavior of the data with the MCMC algorithm, it fails to capture finer-scale population changes and dynamics due to the constant parameters. To increase the predictive precision, we pose the time series estimation as an evolution–observation process, where the process function is a varying-coefficient Lotka–Volterra equation. We estimate the stochastic process using a particle filter, which simultaneously estimates the states and coefficients. We also introduce a local optimization state predictor using a least-square optimization method to further improve the estimation accuracy. Compared with the stochastic mean-particle estimator, we show that this local predictor is robust and effective, regardless of the complexity of the state model and the presence of noises. Finally, we explore the framework’s ability to interpret parameters.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111190"},"PeriodicalIF":2.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196275","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":"Mathematical validation of cleaning symbiosis between Macrobrachium lamarrei and Labeo rohita as an effective bio-control method against Argulus bengalensis","authors":"Netri Datta ,&nbsp;Fahad Al Basir ,&nbsp;Sagar Adhurya ,&nbsp;Samar Kumar Saha ,&nbsp;Santanu Ray","doi":"10.1016/j.ecolmodel.2025.111205","DOIUrl":"10.1016/j.ecolmodel.2025.111205","url":null,"abstract":"<div><div>Argulosis, caused by the crustacean (Order- Branchiura) ectoparasite <em>Argulus</em> spp<em>.</em>, poses a significant economic loss in global aquaculture. Recently, a potential bio-control strategy against argulosis was proposed, which involved three taxonomically separate organisms in cohabitation: the client fish <em>Labeo rohita</em> (F), the cleaner prawn <em>Macrobrachium lamarrei</em> (P), and the parasite <em>Argulus bengalensis</em> (A). However, the effectiveness of the association was only proven in a microcosm experiment; no field application was performed. Therefore, to fill this gap, the present interpretation has been directed towards a mathematical validation of this three-species association for its successful large-scale field application. A conceptual model is proposed with the three state variables F, P and A for this purpose. The parametric values, used to formulate the mathematical model, were obtained from the microcosm experiment, field observation and calibration. The experiment was conducted in microcosm maintaining the client, cleaner and parasite ratio as 1:5:100 for acquiring the values of the coefficient of interaction (<span><math><mi>α</mi></math></span>) between the fish and <em>Argulus</em> and the maximum predation rate (<span><math><mi>γ</mi></math></span>) of prawn. However, an ‘ideal’ condition was also created by maintaining this ratio as 1:1:100 to obtain half saturation constant of predation (<span><math><mi>h</mi></math></span>). The values of intrinsic growth rate (r) of fish and carrying capacity (K) of the aquaculture system were determined according to a particular polyculture system where this specific ratio was 1:2:50. The Holling type III equation was used to solve this mathematical model equation. The result demonstrates that the predation rate of the prawn species inversely influences the <em>Argulus</em> population and directly influences the prawn population. Therefore, <em>M. lamarrei</em> can be used as an additional species in composite fish culture to regulate <em>Argulus</em> load in aquaculture systems without compromising the balance of an ecosystem. Moreover, this study is a novel work that considers dual role of the three interacting species for model formation and analysis. So, the current study is important in both the sectors of aquaculture and ecology.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111205"},"PeriodicalIF":2.6,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195931","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 long-term multiparametric analysis of benthic macroinvertebrate responses to anthropogenic stressors, including a novel multimetric index for evaluating the ecological conditions of mountain rivers in Mexico","authors":"Juan José Reyes-Celis ,&nbsp;Angela Caro-Borrero ,&nbsp;Diego R. Macedo ,&nbsp;Javier Carmona-Jiménez","doi":"10.1016/j.ecolmodel.2025.111203","DOIUrl":"10.1016/j.ecolmodel.2025.111203","url":null,"abstract":"<div><div>Assessing the impacts of anthropogenic pressures (e.g., urbanization, agriculture) on riparian ecosystems is key to their sustainable management. The use of multimetric indices (MMIs) based on biological assemblages for assessing such pressures has increased worldwide. Their cost-benefit advantage and the scientific rigor of their development make them efficient bioindication tools for ecosystem diagnosis and conservation. This research aimed to develop an MMI for the Basin of Mexico based on the assemblages of benthic macroinvertebrates (MIB) observed through sampling perennial rivers and springs at 77 sites over a ten-year period. Potential sites were identified from extant government maps and then visited to verify their current state or existence compared to these cartographic records. We began with 80 ecological metrics and filtered these to remove redundancy, evaluating their ability to differentiate between conserved and degraded sites, have temporal stability, adjusting their score values to natural environmental gradients using significant residual values of the MIB metrics at reference sites. Furthermore, the degree of correlation between environmental changes due to anthropogenic activities at the local and catchment scales was assessed. The final MMI was constructed based on five metrics: Total Abundance, Diptera Richness, Crawler Richness, % Scrapers, and % Temporarily Attached Organisms. The index showed significant differences when discriminating between conserved and degraded sites, as well as when responding to environmental changes at the local and catchment scales. The implemented MMI demonstrates methodological replicability, efficiency, and the potential of macroinvertebrate assemblages to be used as bioindicators in Mexico and other countries where aquatic ecosystems are under constant pressures from land-use change.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111203"},"PeriodicalIF":2.6,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195930","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":"Complementing single-species assessment models with age- and time-varying natural mortality: Insights from holistic ecosystem models","authors":"M. Potier ,&nbsp;M. Robert ,&nbsp;L. Pawlowski ,&nbsp;D. Gascuel ,&nbsp;M. Savina-Rolland","doi":"10.1016/j.ecolmodel.2025.111200","DOIUrl":"10.1016/j.ecolmodel.2025.111200","url":null,"abstract":"<div><div>Integrating information on ecosystem dynamics into single-species stock assessment has been recommended for fisheries management to head towards Ecosystem-Approach to Fisheries Management (EAFM). This paper proposes a sensitivity analysis of single-species assessments in relation to the implementation of time-varying natural mortality (M). Time-varying estimates from a holistic ecosystem model were implemented in exploratory Celtic Sea gadoid stock assessments. Two species were selected to disclose different temporal patterns in M: whiting (<em>Merlangius merlangus</em>) displaying a trend and haddock (<em>Melanogrammus aeglefinus</em>) exhibiting high variability with no trend. Implementing overall higher M levels increases Spawning Stock Biomass (SSB) and decreases average fishing mortality at age (Fbar) in both cases. Here, time-varying values induce reference points modification. Introducing a trend in M improves the assessment quality for whiting, while shifting the stock status from fully exploited to overexploited for several years. Integrating high M variability for haddock induces minimal changes in assessment quality and stock status. In both cases, short term projected sustainable catch level was reduced by 14%. Despite uncertainty around estimates, results suggest that integrating M accounting for a varying predation is crucial, especially when M disclose a trend. Future research should focus on comparing M estimates across various sources, including ecosystem models, and benchmarking the single-species models’ sensitivity to time-varying values.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111200"},"PeriodicalIF":2.6,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185450","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":"Monitoring with multiple goals: Bayesian methods for changing objectives","authors":"Jessie D. Golding ,&nbsp;Kevin S. McKelvey ,&nbsp;Michael K. Schwartz ,&nbsp;Joshua J. Millspaugh ,&nbsp;Jamie S. Sanderlin ,&nbsp;Scott D. Jackson","doi":"10.1016/j.ecolmodel.2025.111196","DOIUrl":"10.1016/j.ecolmodel.2025.111196","url":null,"abstract":"<div><div>Long-term monitoring is essential for wildlife conservation. Most wildlife population attributes require long-term monitoring to evaluate. Over the time for attributes to resolve through monitoring, however, information needs change. Existing frameworks to accommodate information need changes, such as adaptive monitoring and management, are built for large-scale, programmatic changes. Often, smaller, rapid changes are necessary. Fortunately, information needs can change predictably in wildlife monitoring, even when little is known about populations. Predictable changes include the desire to answer: 1) is the species present?; 2) are multiple individuals present?; 3) is breeding occurring?. We suggest long-term monitoring can accommodate these changes. We propose Goal Efficient Monitoring (GEM), an approach that uses a Bayesian integrated population model (BIPM) to accommodate changing information needs through: a BIPM that links population state changes (e.g., present, multiple individuals present) to population dynamics (e.g., abundance, demographic rates); and sampling rules to allocate effort observation effort based on current knowledge. To test the efficacy of a GEM approach, we ask two research questions: 1) can implementing a GEM approach provide robust population estimates?; and 2) do GEM sampling rules in multiple long-term monitoring settings (i.e., population sizes) accommodate changing questions while providing continual, reliable population inference? To answer these questions, we built a BIPM and conducted a simulation study for a rare species in the US, Canada lynx (<em>Lynx canadensis</em>). We simulated lynx populations under five different starting conditions and simulated a GEM approach (10 years of simulated observations with GEM sampling rules), then used our BIPM model to produce estimates and predictions. In 93 % of simulations, 95 % credible intervals for BIMP estimates contained the true value for all biological (abundance of all sexes and age classes, birth events, survival, state transition probabilities) and observation variables (detection probabilities). We demonstrate how a GEM approach can provide reliable long-term inference while being responsive to shifting information needs.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111196"},"PeriodicalIF":2.6,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178813","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":"The return of the Caracal Caracal caracal: 56 Years of Population Changes in Israel","authors":"Ezra Hadad ,&nbsp;Jakub Z. Kosicki ,&nbsp;Reuven Yosef","doi":"10.1016/j.ecolmodel.2025.111197","DOIUrl":"10.1016/j.ecolmodel.2025.111197","url":null,"abstract":"<div><div>Long-term studies of mesopredator populations are essential for understanding the factors driving their demographic changes and developing evidence-based conservation strategies in dynamic landscapes. Here, we present a 56-year assessment of caracal population trends in Israel. This extended period was chosen to capture long-term trends and to account for potential cyclical patterns in the population dynamics, integrating historical records with statistical modeling to examine temporal and geographical variability in abundance and habitat use. Our results reveal distinct population fluctuations, including periods of increase in the 1970s, a subsequent decline during the 1980s and 1990s, and a marked resurgence over the last two decades. However, regionally focused analyses indicate a significant long-term decline in highly urbanized areas such as Judea, suggesting that local pressures can affect abundance trends over wide spatial domains.</div><div>Species distribution modeling indicates that caracals predominantly occupy areas below 1000 m elevation, favoring grasslands, semi-arid zones, and mosaics of cultivated fields while generally avoiding urban environments. Their preference for mixed habitats not only enhances the species’ resilience but also underscores their adaptability to changing landscapes. The episodes of population decline, while concerning, also highlight the potential for recovery and the importance of conservation efforts in maintaining these mixed habitats.</div><div>Our findings underscore the importance of conserving heterogeneous habitats that can sustain caracals in the face of ongoing environmental variability. By integrating long-term population analyses with spatial modeling, this study provides a robust framework for refining protection strategies that address the species’ dynamic ecological requirements. This knowledge empowers us to make informed decisions and contribute valuable insights for broader mesopredator conservation in rapidly changing ecosystems.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111197"},"PeriodicalIF":2.6,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170336","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":"Combating over-commercialization in ecotourism through collaborative governance: A game-theoretic modeling analysis","authors":"Yong Sun ,&nbsp;Lixia Tang ,&nbsp;Xingling Jiang","doi":"10.1016/j.ecolmodel.2025.111194","DOIUrl":"10.1016/j.ecolmodel.2025.111194","url":null,"abstract":"<div><div>Although over-commercialization brings economic benefits, it results in ecological damage and disrupts ecosystem services at ecotourism destinations. This paper addresses the phenomenon of over-commercialization in ecotourism by constructing an evolutionary game model involving the government, companies, and tourists, and simulates their cooperative strategies under various influencing factors. The findings suggest that addressing over-commercialization in ecotourism requires collaborative governance efforts. Specifically, local governments are more motivated to regulate over-commercialization when the regulatory costs are lower, the political benefits from the central government are higher, and environmental remediation costs are greater. Additionally, when local governments impose higher penalties on companies for over-commercialization, and when the profits from non-over-commercialized tourism are greater, companies are more likely to reduce their over-commercialization practices. Over-commercialization in ecotourism may be appealing, but avoiding over-commercialization can enhance the value of ecotourism products, which can attract tourists and reduce their support for over-commercialization. Tourists’ preference for environmental conservation plays a crucial role in restraining the over-commercialization behaviors of companies involved in ecotourism projects. To mitigate the impacts of over-commercialization on ecosystems, governments should strengthen regulatory efforts, increase the costs associated with over-commercialization for companies, and promote tourists’ preferences for ecological conservation.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111194"},"PeriodicalIF":2.6,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170337","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":"Statistical detection of density dependent parameter variation in growth curve models","authors":"Md Aktar Ul Karim ,&nbsp;Hardik Kiran Balsaraf ,&nbsp;Aryan Anurag Tibrewala ,&nbsp;Amiya Ranjan Bhowmick","doi":"10.1016/j.ecolmodel.2025.111176","DOIUrl":"10.1016/j.ecolmodel.2025.111176","url":null,"abstract":"<div><div>Growth curve models are widely employed to analyze and interpret the dynamics of biological, ecological, epidemiological, and industrial processes. A fundamental challenge in growth modeling lies in the assumption of constant parameters, which may not reflect realistic growth mechanisms. While recent studies have developed methods to detect time-dependent parameter variation, the possibility of density-dependent changes, where model parameters vary as a function of population size or system state, has received limited statistical attention. Motivated by empirical evidence and theoretical developments in ecological modeling, this paper presents a novel statistical methodology for detecting density-dependent variation in growth model parameters. The proposed framework extends the interval-specific rate parameter (ISRP) estimation technique based on localized maximum likelihood methods to determine whether parameter variation is driven by population density. The method is validated through simulation experiments and applied to three real-world datasets: population growth data in the United States, cumulative COVID-19 cases in Germany, and a bio-ethanol production system. The results show that incorporating density-dependent parameter variation substantially improves model fit and captures nuanced system dynamics often overlooked in traditional approaches. This work provides a robust statistical foundation for identifying and quantifying density-regulated effects in growth models and offers broad applicability across domains where dynamic systems are influenced by feedback from population or system size.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"507 ","pages":"Article 111176"},"PeriodicalIF":2.6,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154418","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 multi-scale approach for integrating species distribution models with landscape connectivity to identify critical linkage zones for African savanna elephants (Loxodonta africana)","authors":"Lei Song ,&nbsp;Amy E. Frazier ,&nbsp;Anna Bond Estes ,&nbsp;Lyndon Despard Estes","doi":"10.1016/j.ecolmodel.2025.111198","DOIUrl":"10.1016/j.ecolmodel.2025.111198","url":null,"abstract":"<div><div>The populations of African savanna elephants have declined by an estimated 60 % since the 1970s, which can be attributed to a mixture of poaching and habitat loss. Human activities and environmental changes have caused unprecedented loss and fragmentation of elephant natural habitats, resulting in the isolation of elephant populations. Preserving habitat connectivity is thus increasingly important to conserve remaining elephants' populations and maintain ecological functions. A major challenge in large-scale connectivity modeling is data availability constraints. To tackle this issue, we developed an integrated modeling approach that leverages multiple, publicly available occurrence datasets, which vary in format and quality, with a multi-scale SDM to estimate spatial suitability of African savanna elephants. Two SDMs, based on polygon-based observations and presence-only occurrences, were separately calibrated using the Isolation Forest algorithm and then ensembled using Bayes fusion. Particularly, we included multiple landscape metrics derived from a high-resolution (∼5 m) land cover map as environmental predictors in the SDMs to characterize the landscape structure influencing elephant movement. The resulting environmental suitability was then used to map landscape connectivity through circuit theory, implemented in Circuitscape. Using species distribution modeling (SDM) and graph-based landscape connectivity modeling, we aimed to understand population connectivity and target vital corridors across Tanzania, one of the most important elephant range states. Shapley value-based variable analysis in SDM revealed that human modifications strongly influence elephant distribution at broad scales, while habitat fragmentation and connectivity impact their activities. Connectivity results further highlighted that both long- and short-distance connectivity are currently facing significant threats from intensive human activities (e.g., agriculture) in Tanzania and identified critical linkage zones that should be targeted for connectivity conservation efforts.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"507 ","pages":"Article 111198"},"PeriodicalIF":2.6,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138343","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}