We present a discrete‐time predator–prey model in which the prey population is assumed to evolve in response to a toxicant. We incorporate frequency‐dependent selection into the prey evolution, assuming that an individual's susceptibility to predation depends on both the trait it possesses and the traits of others in the population. When frequency‐dependent selection is symmetric, we show that the trait equation is unable to track changes in the fitness landscape, that is, the fitness landscape may change while the trait continues to evolve to the same trait value. As a result, evolution may produce unfit prey populations. Meanwhile, we show that asymmetric frequency‐dependence may have a destabilizing effect on the system, resulting in a closed invariant curve via a Neimark–Sacker bifurcation.
{"title":"Frequency‐dependent evolution in a predator–prey system","authors":"Azmy S. Ackleh, A. Veprauskas","doi":"10.1111/nrm.12308","DOIUrl":"https://doi.org/10.1111/nrm.12308","url":null,"abstract":"We present a discrete‐time predator–prey model in which the prey population is assumed to evolve in response to a toxicant. We incorporate frequency‐dependent selection into the prey evolution, assuming that an individual's susceptibility to predation depends on both the trait it possesses and the traits of others in the population. When frequency‐dependent selection is symmetric, we show that the trait equation is unable to track changes in the fitness landscape, that is, the fitness landscape may change while the trait continues to evolve to the same trait value. As a result, evolution may produce unfit prey populations. Meanwhile, we show that asymmetric frequency‐dependence may have a destabilizing effect on the system, resulting in a closed invariant curve via a Neimark–Sacker bifurcation.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12308","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46255539","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}
S. McKelvey, F. Koch, William D. Smith, Kelly R. Hawley
A two‐phase Bayesian model is presented for updating risk assessments for locations susceptible to infection by exotic pathogens. Human transportation from previously infected regions to uninfected regions is the main dispersal mechanism. Information embedded in patterns within the transportation flow are exploited in the update process. We explore the sensitivity of the model's outputs to changes in inputs. A sample application of the model to sudden oak death, using fictitious infection data, is performed.
{"title":"A Bayesian model identifying locations at risk from human‐transported exotic pathogens","authors":"S. McKelvey, F. Koch, William D. Smith, Kelly R. Hawley","doi":"10.1111/nrm.12307","DOIUrl":"https://doi.org/10.1111/nrm.12307","url":null,"abstract":"A two‐phase Bayesian model is presented for updating risk assessments for locations susceptible to infection by exotic pathogens. Human transportation from previously infected regions to uninfected regions is the main dispersal mechanism. Information embedded in patterns within the transportation flow are exploited in the update process. We explore the sensitivity of the model's outputs to changes in inputs. A sample application of the model to sudden oak death, using fictitious infection data, is performed.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12307","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42576412","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}
Air pollution, especially the particulate matter (PM2.5) remains to be a severe problem for the environmental managers and researchers because it causes many respiratory diseases even casualties and huge economic losses. Therefore, it is significant to study the distribution characteristics of regional PM2.5 and analyze the mutual influence relationship between it and some influencing factors including air humidity, wind speed, and atmospheric boundary conditions. Some scholars have studied the relationship between PM2.5 and the atmospheric planetary boundary layer or relative humidity. However, the relationships between air pollution and meteorological conditions in China has been extensively studied in recent years. Therefore, the association between the pollution and precipitation water vapor and wind speed in the northeast of China (e.g., Jilin and Heilongjiang province) could be strengthened. Considering all components in the atmosphere affecting each other and the ability of Weather Research and Forecast (WRF) and WRF‐Chemistry (WRF‐Chem) simulating all of the atmospheric parameters, we utilized the WRF and WRF‐Chem to simulate the precipitable water vapor, wind speed, and PM2.5. Then first, the PM2.5 concentration values predicted from WRF‐Chem are validated with those at the ground stations to evaluate the accuracy of WRF‐Chem model. Second, the relationship analysis between the PM2.5 and wind speed or PWV was done. And the results demonstrate that the wind is helpful to decrease the severe air pollution in winter while the precipitable water vapor plays a small effect on the elimination of the particulate matter. WRF‐Chem is a potential and effective tool for the study of air pollution.
{"title":"Relationships of wind speed and precipitable water vapor with regional PM2.5 based on WRF‐Chem model","authors":"Yuan-Kai Liu","doi":"10.1111/nrm.12306","DOIUrl":"https://doi.org/10.1111/nrm.12306","url":null,"abstract":"Air pollution, especially the particulate matter (PM2.5) remains to be a severe problem for the environmental managers and researchers because it causes many respiratory diseases even casualties and huge economic losses. Therefore, it is significant to study the distribution characteristics of regional PM2.5 and analyze the mutual influence relationship between it and some influencing factors including air humidity, wind speed, and atmospheric boundary conditions. Some scholars have studied the relationship between PM2.5 and the atmospheric planetary boundary layer or relative humidity. However, the relationships between air pollution and meteorological conditions in China has been extensively studied in recent years. Therefore, the association between the pollution and precipitation water vapor and wind speed in the northeast of China (e.g., Jilin and Heilongjiang province) could be strengthened. Considering all components in the atmosphere affecting each other and the ability of Weather Research and Forecast (WRF) and WRF‐Chemistry (WRF‐Chem) simulating all of the atmospheric parameters, we utilized the WRF and WRF‐Chem to simulate the precipitable water vapor, wind speed, and PM2.5. Then first, the PM2.5 concentration values predicted from WRF‐Chem are validated with those at the ground stations to evaluate the accuracy of WRF‐Chem model. Second, the relationship analysis between the PM2.5 and wind speed or PWV was done. And the results demonstrate that the wind is helpful to decrease the severe air pollution in winter while the precipitable water vapor plays a small effect on the elimination of the particulate matter. WRF‐Chem is a potential and effective tool for the study of air pollution.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63504110","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}
Because fish stocks often straddle state, national, and international boundaries, there is a need to coordinate fishery management across jurisdictions. This is particularly important when the abundance or spatial distribution of the stock varies through time. This is best achieved when management objectives and strategies align, and there is coordinated decision‐making and catch accounting among jurisdictions such that each fish stock is managed over its full geographic range. However, legal constraints or differing management objectives may not permit such coordinated decision making and policy development. This study introduces a framework for effectively simulating fleet dynamics, fishery quota allocation, and the implications of alternative management strategies while allowing for determination of economically optimal management approaches at the community level. As a case study, an agent‐based model (ABM) was developed to examine the interplay between transboundary management scenarios on the economic viability of a nascent Alaska state‐waters trawl fishery for walleye pollock (Gadus chalcogrammus) in the Gulf of Alaska, given a longstanding federally managed fishery. Under conditions characteristic of the recent past, the management strategy that produced the best overall improvements, relative to status quo, involved a scenario that allows for community‐based cooperatives in federal‐waters and an open access strategy in state‐waters. This case study allows us to demonstrate more generally how using an ABM allows for quantifying the impacts of and informing managers on anticipated, and novel, results of alternative management strategies for complex socioecological systems before implementation.
{"title":"An agent‐based model to optimize transboundary management for the walleye pollock (Gadus chalcogrammus) fishery in the Gulf of Alaska","authors":"Benjamin C. Williams, K. Criddle, G. Kruse","doi":"10.1111/nrm.12305","DOIUrl":"https://doi.org/10.1111/nrm.12305","url":null,"abstract":"Because fish stocks often straddle state, national, and international boundaries, there is a need to coordinate fishery management across jurisdictions. This is particularly important when the abundance or spatial distribution of the stock varies through time. This is best achieved when management objectives and strategies align, and there is coordinated decision‐making and catch accounting among jurisdictions such that each fish stock is managed over its full geographic range. However, legal constraints or differing management objectives may not permit such coordinated decision making and policy development. This study introduces a framework for effectively simulating fleet dynamics, fishery quota allocation, and the implications of alternative management strategies while allowing for determination of economically optimal management approaches at the community level. As a case study, an agent‐based model (ABM) was developed to examine the interplay between transboundary management scenarios on the economic viability of a nascent Alaska state‐waters trawl fishery for walleye pollock (Gadus chalcogrammus) in the Gulf of Alaska, given a longstanding federally managed fishery. Under conditions characteristic of the recent past, the management strategy that produced the best overall improvements, relative to status quo, involved a scenario that allows for community‐based cooperatives in federal‐waters and an open access strategy in state‐waters. This case study allows us to demonstrate more generally how using an ABM allows for quantifying the impacts of and informing managers on anticipated, and novel, results of alternative management strategies for complex socioecological systems before implementation.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47295001","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}
This paper develops an integrated framework for modeling payment for ecosystem services (PES) mechanisms that deliver multiple environmental services. Specifically, under a community‐led PES, forest conservation is promoted to deliver carbon and stream water benefits. The upstream community is paid for avoided fuelwood harvesting through a United Nations programme on reducing emissions from deforestation and forest degradation (REDD) program, whereas additional income is generated from water sales to the downstream communities. A bio‐economic model derives optimal level of fuelwood harvesting, which in conjunction with the changing species composition of forests, streamflow hydrology and fire risks, impacts on the carbon and water generation potential of the PES project. Results indicate that forest conservation outcomes are better when water and carbon services are combined, however overall cost to the program is lower under a carbon‐based PES. Changing species composition of forests creates tradeoffs between water and carbon benefits. Forest fires further challenge the viability of PES schemes through reducing streamflow and carbon sequestration potential.
{"title":"Can combining two environmental services under a single PES program result in better environmental outcomes and lower costs?","authors":"R. Ranjan","doi":"10.1111/nrm.12303","DOIUrl":"https://doi.org/10.1111/nrm.12303","url":null,"abstract":"This paper develops an integrated framework for modeling payment for ecosystem services (PES) mechanisms that deliver multiple environmental services. Specifically, under a community‐led PES, forest conservation is promoted to deliver carbon and stream water benefits. The upstream community is paid for avoided fuelwood harvesting through a United Nations programme on reducing emissions from deforestation and forest degradation (REDD) program, whereas additional income is generated from water sales to the downstream communities. A bio‐economic model derives optimal level of fuelwood harvesting, which in conjunction with the changing species composition of forests, streamflow hydrology and fire risks, impacts on the carbon and water generation potential of the PES project. Results indicate that forest conservation outcomes are better when water and carbon services are combined, however overall cost to the program is lower under a carbon‐based PES. Changing species composition of forests creates tradeoffs between water and carbon benefits. Forest fires further challenge the viability of PES schemes through reducing streamflow and carbon sequestration potential.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46617897","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}
Junyan Duan, Mykhaylo M. Malakhov, J. J. Pellett, I. Phadke, J. Barber, J. Blackwood
The fungal pathogen Pseudogymnoascus destructans (Pd) causes white‐nose syndrome (WNS), an emerging disease that affects North American bat populations during hibernation. Pd has rapidly spread throughout much of the continent, leading to mass mortality and threatening extinction in several bat species. While previous studies have proposed treatment methods, little is known about the impact of metapopulation dynamics on these interventions. We investigate how the movement of bats between populations could affect the success of five WNS control strategies by posing and analyzing a two‐population disease model. Our results demonstrate that vaccination will benefit from greater bat dispersal, but the effectiveness of treatments targeting fungal growth or disease progression can be expected to diminish. We confirm that successful control depends on the relative contributions of bat‐to‐bat and environment‐to‐bat contact to Pd transmission, and additionally find that the route of transmission can influence whether interpopulation exchange increases or decreases control efficacy.
{"title":"Management efficacy in a metapopulation model of white‐nose syndrome","authors":"Junyan Duan, Mykhaylo M. Malakhov, J. J. Pellett, I. Phadke, J. Barber, J. Blackwood","doi":"10.1111/nrm.12304","DOIUrl":"https://doi.org/10.1111/nrm.12304","url":null,"abstract":"The fungal pathogen Pseudogymnoascus destructans (Pd) causes white‐nose syndrome (WNS), an emerging disease that affects North American bat populations during hibernation. Pd has rapidly spread throughout much of the continent, leading to mass mortality and threatening extinction in several bat species. While previous studies have proposed treatment methods, little is known about the impact of metapopulation dynamics on these interventions. We investigate how the movement of bats between populations could affect the success of five WNS control strategies by posing and analyzing a two‐population disease model. Our results demonstrate that vaccination will benefit from greater bat dispersal, but the effectiveness of treatments targeting fungal growth or disease progression can be expected to diminish. We confirm that successful control depends on the relative contributions of bat‐to‐bat and environment‐to‐bat contact to Pd transmission, and additionally find that the route of transmission can influence whether interpopulation exchange increases or decreases control efficacy.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45722238","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}
The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.
{"title":"Effect of plantation of genetically modified trees on the control of atmospheric carbon dioxide: A modeling study","authors":"Maitri Verma, A. Verma","doi":"10.1111/nrm.12300","DOIUrl":"https://doi.org/10.1111/nrm.12300","url":null,"abstract":"The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44600390","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}
Rainfall data series with adequate quality and length are often incomplete or nonexistent. Thus, filling in rainfall gaps becomes necessary to complete databases. This article proposes the use of satellite products (TRMM—Tropical Rainfall Measuring Mission, CHIRPS—Climate Hazards Group InfraRed Precipitation with Stations and CMORPH—CPC Morphing Technique) to fill gaps in the rainfall historical series. The simple regression method, using satellite rainfall estimates, was tested to fill the missing data from 164 rainfall gauge stations in the Amazon region. Large dispersions were observed between rainfall data, with R2 ranging from 0.383 to 0.844, the best results were found in areas with less rainfall. As well, the greatest performance of the products was verified in the dry period, with r and d higher than 0.899 and 0.950, respectively. The product with the best representation in the region was CHIRPS, which had the lowest monthly values of mean absolute error (0.979 mm) and root mean square error (3.656 mm). The results confirm that the satellite estimates satisfactorily represent the seasonal variation of rainfall in the region, despite presenting cases of overestimation and underestimation of data. The higher performance of CHIRPS can be explained by the higher spatial resolution (0.05°), allowing for more accurate weather forecasts. In fact, CHIRPS has the CHPclim model, which adds other factors to the good product performance. These characteristics justify the better performance of the CHIRPS product for filling gaps in daily rainfall data in the Amazon region, favoring the best monthly rainfall estimates for each region state analyzed.
{"title":"Assessment of satellite products for filling rainfall data gaps in the Amazon region","authors":"Adria Lorena Moraes Cordeiro, C. Blanco","doi":"10.1111/nrm.12298","DOIUrl":"https://doi.org/10.1111/nrm.12298","url":null,"abstract":"Rainfall data series with adequate quality and length are often incomplete or nonexistent. Thus, filling in rainfall gaps becomes necessary to complete databases. This article proposes the use of satellite products (TRMM—Tropical Rainfall Measuring Mission, CHIRPS—Climate Hazards Group InfraRed Precipitation with Stations and CMORPH—CPC Morphing Technique) to fill gaps in the rainfall historical series. The simple regression method, using satellite rainfall estimates, was tested to fill the missing data from 164 rainfall gauge stations in the Amazon region. Large dispersions were observed between rainfall data, with R2 ranging from 0.383 to 0.844, the best results were found in areas with less rainfall. As well, the greatest performance of the products was verified in the dry period, with r and d higher than 0.899 and 0.950, respectively. The product with the best representation in the region was CHIRPS, which had the lowest monthly values of mean absolute error (0.979 mm) and root mean square error (3.656 mm). The results confirm that the satellite estimates satisfactorily represent the seasonal variation of rainfall in the region, despite presenting cases of overestimation and underestimation of data. The higher performance of CHIRPS can be explained by the higher spatial resolution (0.05°), allowing for more accurate weather forecasts. In fact, CHIRPS has the CHPclim model, which adds other factors to the good product performance. These characteristics justify the better performance of the CHIRPS product for filling gaps in daily rainfall data in the Amazon region, favoring the best monthly rainfall estimates for each region state analyzed.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41645570","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}
Vahedberdi Sheikh, H. Salmani, Abdolrassoul Salman Mahiny, M. Ownegh, A. Fathabadi
This study aims to present an efficient methodology for land use optimization based on minimization of runoff and sediment and maximization of economic benefits, occupational opportunities, and land use suitability in the Tilabad watershed in northeast of Iran. The land use map of the area was prepared using the Landsat satellite images and field surveys. The amounts of runoff and sediment were estimated via SWAT model. The TOPSIS multicriteria decision‐making (MCDM) approach was applied on the results of the multiobjective optimization (MOO) based on non‐dominated sorting genetic algorithm II (NSGA II) to choose the final optimal solution among the Pareto solutions front generated by MOO. The results indicated that the area of agriculture and rangelands should decrease, and the area of forests should increase to achieve the defined objectives. Overall, results indicated that integration of MOO and MCDM provides an efficient procedure for land use optimization in a complex watershed.
{"title":"Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)","authors":"Vahedberdi Sheikh, H. Salmani, Abdolrassoul Salman Mahiny, M. Ownegh, A. Fathabadi","doi":"10.1111/nrm.12301","DOIUrl":"https://doi.org/10.1111/nrm.12301","url":null,"abstract":"This study aims to present an efficient methodology for land use optimization based on minimization of runoff and sediment and maximization of economic benefits, occupational opportunities, and land use suitability in the Tilabad watershed in northeast of Iran. The land use map of the area was prepared using the Landsat satellite images and field surveys. The amounts of runoff and sediment were estimated via SWAT model. The TOPSIS multicriteria decision‐making (MCDM) approach was applied on the results of the multiobjective optimization (MOO) based on non‐dominated sorting genetic algorithm II (NSGA II) to choose the final optimal solution among the Pareto solutions front generated by MOO. The results indicated that the area of agriculture and rangelands should decrease, and the area of forests should increase to achieve the defined objectives. Overall, results indicated that integration of MOO and MCDM provides an efficient procedure for land use optimization in a complex watershed.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/nrm.12301","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43482617","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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