Motivated by the Feline immunodeficiency virus, the virus that causes AIDS in cat populations, we use discrete‐time infectious disease models with demographic strong Allee effect to examine the impact of the fatal susceptible‐infected (SI) infections on two different types of growth functions: Holling type III or modified Beverton–Holt per‐capita growth function (compensatory density dependence), and Ricker per‐capita growth function with mating (overcompensatory density dependence). The occurrence of the strong Allee effect in the disease‐free equation renders the SI population model bistable, where the two coexisting locally asymptotically stable equilibrium points are either the origin (catastrophic extinction state) and the second fixed point (compensatory dynamics) or the origin and an intrinsically generated demographic period k > 1 population cycle (overcompensatory dynamics). We use the basic reproduction number, ℛ 0 , and the spectral radius, λ k , to examine the structures of the coexisting attractors. In particular, we use MATLAB simulations to show that the fatal disease is not only capable of enlarging or shrinking the basin of attraction of the catastrophic extinction state, but it is also capable of fracturing the basins of attraction into several disjoint sets. Thus, making it difficult to specify the asymptotic zoonotic SI disease outcome in terms of all initial infections. The complexity of the basins of attractions appears to increase with an increase in the period of the intrinsically generated demographic population cycles.
{"title":"Strong Allee effect and basins of attraction in a discrete‐time zoonotic infectious disease model","authors":"A. Yakubu, Najat Ziyadi","doi":"10.1111/nrm.12310","DOIUrl":"https://doi.org/10.1111/nrm.12310","url":null,"abstract":"Motivated by the Feline immunodeficiency virus, the virus that causes AIDS in cat populations, we use discrete‐time infectious disease models with demographic strong Allee effect to examine the impact of the fatal susceptible‐infected (SI) infections on two different types of growth functions: Holling type III or modified Beverton–Holt per‐capita growth function (compensatory density dependence), and Ricker per‐capita growth function with mating (overcompensatory density dependence). The occurrence of the strong Allee effect in the disease‐free equation renders the SI population model bistable, where the two coexisting locally asymptotically stable equilibrium points are either the origin (catastrophic extinction state) and the second fixed point (compensatory dynamics) or the origin and an intrinsically generated demographic period k > 1 population cycle (overcompensatory dynamics). We use the basic reproduction number, ℛ 0 , and the spectral radius, λ k , to examine the structures of the coexisting attractors. In particular, we use MATLAB simulations to show that the fatal disease is not only capable of enlarging or shrinking the basin of attraction of the catastrophic extinction state, but it is also capable of fracturing the basins of attraction into several disjoint sets. Thus, making it difficult to specify the asymptotic zoonotic SI disease outcome in terms of all initial infections. The complexity of the basins of attractions appears to increase with an increase in the period of the intrinsically generated demographic population cycles.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46867391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Iman Saeedi, Alireza Mikaeili Tabrizi, A. Bahremand, A. Salmanmahiny
Green Infrastructure Development (GID) is a well‐known method for dealing with runoff control and mitigating the urbanization effects on hydrological cycles. Other than hydrological factors, GID is obviously intertwined with many socioeconomic, environmental, and aesthetic considerations, constraints, and drivers. Human perceptions are valuable resources to distinguish these considerations and can be derived from unstructured information using a systematic method. The purpose of this article is to exhibit how the perceptions of stakeholders were derived in Tehran for a conceptual model of green infrastructure development. For this, we applied a combination of Soft Systems Methodology (SSM) and Interpretive Structural Modeling (ISM). The results revealed the main stakeholders, their relationships and responsibility, main obstacles for GID, and the conceptual system of activities for GIs development in Tehran. Based on the results, actions for improving the current situation were proposed and categorized in 10 main components including: further research, regulation, financial support, negotiation with stakeholders, evaluation and monitoring, enhancing stakeholders' interactions, providing comprehensive database, acculturalization, managerial reform, and training of stakeholders. ISM was performed to obtain a visible, ordered, and well‐defined model of the relationships among the main components. The results revealed that the item “further research” plays the main role in actualizing three components “regulation,” “financial support,” and “negotiation with stakeholders” in the process of GID in Tehran while the realization of the rest of the components depends on the former three components.
{"title":"A soft systems methodology and interpretive structural modeling framework for Green infrastructure development to control runoff in Tehran metropolis","authors":"Iman Saeedi, Alireza Mikaeili Tabrizi, A. Bahremand, A. Salmanmahiny","doi":"10.1111/nrm.12339","DOIUrl":"https://doi.org/10.1111/nrm.12339","url":null,"abstract":"Green Infrastructure Development (GID) is a well‐known method for dealing with runoff control and mitigating the urbanization effects on hydrological cycles. Other than hydrological factors, GID is obviously intertwined with many socioeconomic, environmental, and aesthetic considerations, constraints, and drivers. Human perceptions are valuable resources to distinguish these considerations and can be derived from unstructured information using a systematic method. The purpose of this article is to exhibit how the perceptions of stakeholders were derived in Tehran for a conceptual model of green infrastructure development. For this, we applied a combination of Soft Systems Methodology (SSM) and Interpretive Structural Modeling (ISM). The results revealed the main stakeholders, their relationships and responsibility, main obstacles for GID, and the conceptual system of activities for GIs development in Tehran. Based on the results, actions for improving the current situation were proposed and categorized in 10 main components including: further research, regulation, financial support, negotiation with stakeholders, evaluation and monitoring, enhancing stakeholders' interactions, providing comprehensive database, acculturalization, managerial reform, and training of stakeholders. ISM was performed to obtain a visible, ordered, and well‐defined model of the relationships among the main components. The results revealed that the item “further research” plays the main role in actualizing three components “regulation,” “financial support,” and “negotiation with stakeholders” in the process of GID in Tehran while the realization of the rest of the components depends on the former three components.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47890858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
In this article, a nonlinear mathematical model is constructed to investigate the conservation of depleted forest resources due to the increase of population and associated pressures. Fundamental equations governing the dynamics of the system are defined by the set of highly nonlinear ordinary differential equations and solved numerically. The model is analyzed by using the nature of stability analysis theory of dynamical system. The numerical solutions and simulations of the system are carried out using ODE45 subroutine of MATLAB. Presentations of results are revealed using graphs and interpreted biologically. It is noted that the increase of population density and associated pressures causes the depletion of forestry resources. However, forest resources can be conserved by controlling man made fire, toxicant activities, applying economical incentives and technological efforts.
{"title":"Mathematical modeling on conservation of depleted forestry resources","authors":"Masitawal Demsie Goshu, M. Endalew","doi":"10.1111/nrm.12338","DOIUrl":"https://doi.org/10.1111/nrm.12338","url":null,"abstract":"In this article, a nonlinear mathematical model is constructed to investigate the conservation of depleted forest resources due to the increase of population and associated pressures. Fundamental equations governing the dynamics of the system are defined by the set of highly nonlinear ordinary differential equations and solved numerically. The model is analyzed by using the nature of stability analysis theory of dynamical system. The numerical solutions and simulations of the system are carried out using ODE45 subroutine of MATLAB. Presentations of results are revealed using graphs and interpreted biologically. It is noted that the increase of population density and associated pressures causes the depletion of forestry resources. However, forest resources can be conserved by controlling man made fire, toxicant activities, applying economical incentives and technological efforts.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45035854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Komeyl Baghizadeh, N. Cheikhrouhou, K. Govindan, Mahboubeh Ziyarati
Due to the nature of the agricultural and food industry, the management of production, storage, transportation, waste disposal and environmental effects of their production, are of great importance. To deal with the sustainability issues linked to their supply chains, we propose in this study a mathematical model to design a sustainable supply chain of highly perishable agricultural product (strawberry). The model is a multiperiod, multiproduct multiobjective MINLP mathematical program that takes into consideration economic, social and environmental objectives to cover all aspects of sustainability. In addition, a G/M/S/M queuing system is developed for the transportation of harvested products between facilities for the first time. Since real‐world problems related to industries such as food and agriculture are inherently uncertain, in this model, the important parameters of the problem are considered uncertain using fuzzy sets theory and a hybrid robust possibilistic programming model is developed. In addition, the Epsilon constraint approach converts the multiobjective mathematical model into a single‐objective one and the Lagrangian relaxation method is used to effectively solve the model on a large scale. A case study in Iran is provided to investigate the results and discuss the solutions. Finally, a sensitivity analysis is performed to identify the impacts of important parameters on the solution. According to the analysis, equipping greenhouses with drip irrigation system and using solar panels in greenhouses, respectively, have the greatest impact on improving all target functions.
{"title":"Sustainable agriculture supply chain network design considering water‐energy‐food nexus using queuing system: A hybrid robust possibilistic programming","authors":"Komeyl Baghizadeh, N. Cheikhrouhou, K. Govindan, Mahboubeh Ziyarati","doi":"10.1111/nrm.12337","DOIUrl":"https://doi.org/10.1111/nrm.12337","url":null,"abstract":"Due to the nature of the agricultural and food industry, the management of production, storage, transportation, waste disposal and environmental effects of their production, are of great importance. To deal with the sustainability issues linked to their supply chains, we propose in this study a mathematical model to design a sustainable supply chain of highly perishable agricultural product (strawberry). The model is a multiperiod, multiproduct multiobjective MINLP mathematical program that takes into consideration economic, social and environmental objectives to cover all aspects of sustainability. In addition, a G/M/S/M queuing system is developed for the transportation of harvested products between facilities for the first time. Since real‐world problems related to industries such as food and agriculture are inherently uncertain, in this model, the important parameters of the problem are considered uncertain using fuzzy sets theory and a hybrid robust possibilistic programming model is developed. In addition, the Epsilon constraint approach converts the multiobjective mathematical model into a single‐objective one and the Lagrangian relaxation method is used to effectively solve the model on a large scale. A case study in Iran is provided to investigate the results and discuss the solutions. Finally, a sensitivity analysis is performed to identify the impacts of important parameters on the solution. According to the analysis, equipping greenhouses with drip irrigation system and using solar panels in greenhouses, respectively, have the greatest impact on improving all target functions.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45318035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Since 1995, the Resource Modeling Association (RMA) has organized the World Conference on Natural Resource Modeling (WCNRM), an annual meeting that brings together scientists, stakeholders and students interested in the mathematical modeling of renewable and exhaustible resources. For the first time in South America, and just before the pandemic began, WCNRM was held in January 2020 in Valparaíso, Chile, organized by the Universidad Técnica Federico Santa María and the Universidad de Chile. Participants from 20 countries presented novelties on different topics related to natural resources and specifically on the conference theme: “Decision support methods for natural systems at risk.” This special issue collects a selection of papers and ideas presented during WCNRM 2020. Topics covered in this collection include: A modeling approach for evaluating the interplay between global warming and body size in fish stocks, providing important messages to mid‐ and long‐term if current temperature trends continue; A probabilistic model for detecting locations at risk from human‐ transported pathogens, methodology that can be applied to a wide class of problems, and it is illustrated with a very nice example on the sudden oak death; A crop choice model for estimating future returns from the irrigated land under different scenarios, concluding that financial and technical assistant to farmers for conserving groundwater would be sustainable and efficient from a cost–benefit viewpoint, conclusion obtained from a case study on the Mississippi River Alluvial Aquifer; A dynamical model for a terrestrial ecosystem whose analysis shows how biodiversity conservation can reduce infectious diseases; A generalization of a multivariate spatial variables methodology to provide a common effective sample size when all variables have been measured at the same locations, with concrete applications such as a soil contamination data set; A quantitative analysis of an epidemiological model of HIV/AIDS using Bayesian inference, for which the basic reproductive number was estimated based on the estimation of the model parameters; And the characterization of the set of robust sustainable thresholds for a discrete‐time controlled dynamic system, which provides useful information to users and decision‐makers as it illustrates the trade‐offs between the achievement of different objectives in fishery management. We would like to thank the authors who submitted their papers to this special issue and all the reviewers for their invaluable job during these unusual pandemic times. We are also indebted to the Editor‐in‐Chief, Shandelle Henson, for her support during the whole process.
{"title":"Editorial","authors":"P. Gajardo, H. Ramírez","doi":"10.1111/nrm.12335","DOIUrl":"https://doi.org/10.1111/nrm.12335","url":null,"abstract":"Since 1995, the Resource Modeling Association (RMA) has organized the World Conference on Natural Resource Modeling (WCNRM), an annual meeting that brings together scientists, stakeholders and students interested in the mathematical modeling of renewable and exhaustible resources. For the first time in South America, and just before the pandemic began, WCNRM was held in January 2020 in Valparaíso, Chile, organized by the Universidad Técnica Federico Santa María and the Universidad de Chile. Participants from 20 countries presented novelties on different topics related to natural resources and specifically on the conference theme: “Decision support methods for natural systems at risk.” This special issue collects a selection of papers and ideas presented during WCNRM 2020. Topics covered in this collection include: A modeling approach for evaluating the interplay between global warming and body size in fish stocks, providing important messages to mid‐ and long‐term if current temperature trends continue; A probabilistic model for detecting locations at risk from human‐ transported pathogens, methodology that can be applied to a wide class of problems, and it is illustrated with a very nice example on the sudden oak death; A crop choice model for estimating future returns from the irrigated land under different scenarios, concluding that financial and technical assistant to farmers for conserving groundwater would be sustainable and efficient from a cost–benefit viewpoint, conclusion obtained from a case study on the Mississippi River Alluvial Aquifer; A dynamical model for a terrestrial ecosystem whose analysis shows how biodiversity conservation can reduce infectious diseases; A generalization of a multivariate spatial variables methodology to provide a common effective sample size when all variables have been measured at the same locations, with concrete applications such as a soil contamination data set; A quantitative analysis of an epidemiological model of HIV/AIDS using Bayesian inference, for which the basic reproductive number was estimated based on the estimation of the model parameters; And the characterization of the set of robust sustainable thresholds for a discrete‐time controlled dynamic system, which provides useful information to users and decision‐makers as it illustrates the trade‐offs between the achievement of different objectives in fishery management. We would like to thank the authors who submitted their papers to this special issue and all the reviewers for their invaluable job during these unusual pandemic times. We are also indebted to the Editor‐in‐Chief, Shandelle Henson, for her support during the whole process.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46309551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Depletion and deforestation of forest resources are mainly due to industrialization, population, pollution, forest fire, improper commercial logging, and illegal logging in the world. In this paper, we consider two dynamic models. A mathematical Model 1 is proposed considering the forest biomass density x ( t ) , the density of wood‐based industries y ( t ) with unknown parameter h . Model 2 is an extension of Model 1 with the density of illegal logging z ( t ) with unknown parameter n . It is assumed that the density of forest biomass grows logistically in the absence of wood‐based industries and illegal logging. In the proposed models, the controlling parameters h and n are crucial parameters for the local stable conditions of the equilibrium points and system control. We also show in this paper that it is possible to control illegal logging by increasing the level of logging by selecting system parameters efficiently and effectively.
{"title":"Modeling and control of Mongolian forest utilization: Impact of illegal logging","authors":"Battur Gompil, B. Tseveen, Janerke Almasbek","doi":"10.1111/nrm.12333","DOIUrl":"https://doi.org/10.1111/nrm.12333","url":null,"abstract":"Depletion and deforestation of forest resources are mainly due to industrialization, population, pollution, forest fire, improper commercial logging, and illegal logging in the world. In this paper, we consider two dynamic models. A mathematical Model 1 is proposed considering the forest biomass density x ( t ) , the density of wood‐based industries y ( t ) with unknown parameter h . Model 2 is an extension of Model 1 with the density of illegal logging z ( t ) with unknown parameter n . It is assumed that the density of forest biomass grows logistically in the absence of wood‐based industries and illegal logging. In the proposed models, the controlling parameters h and n are crucial parameters for the local stable conditions of the equilibrium points and system control. We also show in this paper that it is possible to control illegal logging by increasing the level of logging by selecting system parameters efficiently and effectively.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46952305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Historical patterns of the Eastern Baltic cod stock recruitment show a shift from a regime with high reproductive potential before the early 1980s to a regime with low reproductive potential since then. This shift can be attributed to increasingly unfavorable environmental conditions for cod reproduction at that time: critical salinity and oxygen levels, needed for successful egg and larval development, deteriorated. Yet, significant inflows of salt‐ and oxygen‐rich water from the North Sea or improved eutrophication management might trigger a shift back to a more productive regime. Coupling a statistical recruitment model to a state‐of‐the‐art, age‐structured bio‐economic model of the Eastern Baltic cod fishery, we study how optimal management depends on the uncertainty about the future productivity regime. We extend the predominantly theoretical literature on optimal management of a natural resource with a potential regime shift by analyzing an empirical model of age‐structured population dynamics and by allowing for the possibility of a back‐shift from a “bad” into a “good” regime. We find that with a higher probability of a shift back to the more productive regime the optimal management of the fishery becomes more conservative in the short run. We conclude that these benefits for the fishery warrant strong action reducing eutrophication to increase the probability of a regime shift back to high reproductive potential of the Eastern Baltic cod fishery.
{"title":"Fisheries management and tipping points: Seeking optimal management of Eastern Baltic cod under conditions of uncertainty about the future productivity regime","authors":"Rudi Voss, M. Quaas","doi":"10.1111/nrm.12336","DOIUrl":"https://doi.org/10.1111/nrm.12336","url":null,"abstract":"Historical patterns of the Eastern Baltic cod stock recruitment show a shift from a regime with high reproductive potential before the early 1980s to a regime with low reproductive potential since then. This shift can be attributed to increasingly unfavorable environmental conditions for cod reproduction at that time: critical salinity and oxygen levels, needed for successful egg and larval development, deteriorated. Yet, significant inflows of salt‐ and oxygen‐rich water from the North Sea or improved eutrophication management might trigger a shift back to a more productive regime. Coupling a statistical recruitment model to a state‐of‐the‐art, age‐structured bio‐economic model of the Eastern Baltic cod fishery, we study how optimal management depends on the uncertainty about the future productivity regime. We extend the predominantly theoretical literature on optimal management of a natural resource with a potential regime shift by analyzing an empirical model of age‐structured population dynamics and by allowing for the possibility of a back‐shift from a “bad” into a “good” regime. We find that with a higher probability of a shift back to the more productive regime the optimal management of the fishery becomes more conservative in the short run. We conclude that these benefits for the fishery warrant strong action reducing eutrophication to increase the probability of a regime shift back to high reproductive potential of the Eastern Baltic cod fishery.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43956835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
In this study, we address the problem of fitting a mathematical model to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) data. We present a quantitative analysis of the formulated mathematical model by using Bayesian inference. The mathematical model consists of a suitable simple system of ordinary differential equations. We perform a local and global sensitivity analysis of parameters to determine which parameters of the model are the most relevant for the transmission and prevalence of the disease. We formulate the inverse problem associated to the parameter estimation of the model, and solve it using Bayesian statistics. Then, we estimate the basic reproductive number of the disease based on the estimation of the parameters of the model and its comparison with one is tested through hypothesis tests. The data set consist of HIV and AIDS data from Luxembourg, Czech Republic, Japan, Croatia, United Kingdom, and Mexico.
{"title":"Current forecast of HIV/AIDS using Bayesian inference","authors":"K. Prieto, Jhoana P. Romero–Leiton","doi":"10.1111/nrm.12332","DOIUrl":"https://doi.org/10.1111/nrm.12332","url":null,"abstract":"In this study, we address the problem of fitting a mathematical model to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) data. We present a quantitative analysis of the formulated mathematical model by using Bayesian inference. The mathematical model consists of a suitable simple system of ordinary differential equations. We perform a local and global sensitivity analysis of parameters to determine which parameters of the model are the most relevant for the transmission and prevalence of the disease. We formulate the inverse problem associated to the parameter estimation of the model, and solve it using Bayesian statistics. Then, we estimate the basic reproductive number of the disease based on the estimation of the parameters of the model and its comparison with one is tested through hypothesis tests. The data set consist of HIV and AIDS data from Luxembourg, Czech Republic, Japan, Croatia, United Kingdom, and Mexico.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46401713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
W. Campillay-Llanos, V. Saldaña‐Núñez, Fernado Córdova‐Lepe, F. N. Moreno‐Gómez
Environmental temperature and body size influence the life cycle of the species, with consequences for population size. In addition, it has been reported that increased temperature can lead to a decrease in body size. In the context of a resource‐stock, whose abundance is diminished by the action of an endothermic predator and also by small‐scale fishing activity, we analysed a Schaefer‐type fishery model that incorporates parametric variables associated with thermal performance, metabolic theory, and warming. We project the biomass of the resource in a thermal tolerance range with an increasing temperature trend obtained from current data. In the short term there could be an increase in biomass. However, over time the stock will decline rapidly, in association with the intensity of temperature increase and fishing effort.
{"title":"Fish catch management strategies: Evaluating the interplay between body size and global warming","authors":"W. Campillay-Llanos, V. Saldaña‐Núñez, Fernado Córdova‐Lepe, F. N. Moreno‐Gómez","doi":"10.1111/nrm.12331","DOIUrl":"https://doi.org/10.1111/nrm.12331","url":null,"abstract":"Environmental temperature and body size influence the life cycle of the species, with consequences for population size. In addition, it has been reported that increased temperature can lead to a decrease in body size. In the context of a resource‐stock, whose abundance is diminished by the action of an endothermic predator and also by small‐scale fishing activity, we analysed a Schaefer‐type fishery model that incorporates parametric variables associated with thermal performance, metabolic theory, and warming. We project the biomass of the resource in a thermal tolerance range with an increasing temperature trend obtained from current data. In the short term there could be an increase in biomass. However, over time the stock will decline rapidly, in association with the intensity of temperature increase and fishing effort.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47214916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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