This paper derives rational ecological–economic equilibrium outcomes—capital and variable input allocations, harvests, discards, revenue, costs, and stock abundances—in a spatially heterogeneous, multispecies fishery that is regulated with individual fishing quotas (IFQs). The production setting is decentralized; a manager chooses species‐specific, seasonal, and spatially nondelineated quotas. Industry controls all aspects of harvesting operations. We present a solution concept and computational algorithm to solve for equilibrium harvests, discards, and profits across species, space, and time (within the regulatory cycle). The rational equilibrium mapping that we derive, used recursively, can be used to implement management‐preferred bioeconomic outcomes. The model offers an essential IFQ regulation‐to‐outcome mapping that enables more precise implementation of management goals in multiple‐species and heterogeneous fishery settings.
{"title":"A model of rational equilibrium in quota‐regulated multiple‐species fisheries","authors":"Rajesh K. Singh, Quinn Weninger","doi":"10.1111/nrm.12361","DOIUrl":"https://doi.org/10.1111/nrm.12361","url":null,"abstract":"This paper derives rational ecological–economic equilibrium outcomes—capital and variable input allocations, harvests, discards, revenue, costs, and stock abundances—in a spatially heterogeneous, multispecies fishery that is regulated with individual fishing quotas (IFQs). The production setting is decentralized; a manager chooses species‐specific, seasonal, and spatially nondelineated quotas. Industry controls all aspects of harvesting operations. We present a solution concept and computational algorithm to solve for equilibrium harvests, discards, and profits across species, space, and time (within the regulatory cycle). The rational equilibrium mapping that we derive, used recursively, can be used to implement management‐preferred bioeconomic outcomes. The model offers an essential IFQ regulation‐to‐outcome mapping that enables more precise implementation of management goals in multiple‐species and heterogeneous fishery settings.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44654136","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}
Forestland can be managed for timber and environmental goods simultaneously. A conservation contract allows a government agency to pay a landowner for the portion of property rights encumbered in the production of environmental goods. In this study, a theoretical model is developed to examine optimal contract provisions for carbon sequestration on working forests under a budget constraint for the agency. The analyses reveal that a landowner requires a higher payment if more property rights are encumbered in a conservation contract. A landowner whose land can sequester more carbon also requires a more favorable contract arrangement. Assuming a logistic growth path for carbon sequestration, the agency under a budget constraint tends to have a shallower relationship with more landowners, that is, encumbering a smaller portion of property rights from more landowners. This tendency supports the use of conservation contracts with a shorter term and a higher enrollment share in a forest community.
{"title":"Optimal contract arrangements for conservation on working forests","authors":"Changyou Sun, B. Mei, Yanshu Li","doi":"10.1111/nrm.12351","DOIUrl":"https://doi.org/10.1111/nrm.12351","url":null,"abstract":"Forestland can be managed for timber and environmental goods simultaneously. A conservation contract allows a government agency to pay a landowner for the portion of property rights encumbered in the production of environmental goods. In this study, a theoretical model is developed to examine optimal contract provisions for carbon sequestration on working forests under a budget constraint for the agency. The analyses reveal that a landowner requires a higher payment if more property rights are encumbered in a conservation contract. A landowner whose land can sequester more carbon also requires a more favorable contract arrangement. Assuming a logistic growth path for carbon sequestration, the agency under a budget constraint tends to have a shallower relationship with more landowners, that is, encumbering a smaller portion of property rights from more landowners. This tendency supports the use of conservation contracts with a shorter term and a higher enrollment share in a forest community.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46349267","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 accurate evaluation of the relationship between nature reserves and poverty is highly significant for the harmonious coexistence between human and nature. It is widely recognized that the establishment of nature reserves is of great importance to the income poverty of farmers, but less attention has been paid to the impact of different reserves on the multidimensional relative poverty of farmers. Based on the survey data of Panda Nature Reserves in China, we analyze the influence of reserve regulation (or not) and regulation intensity on the multidimensional relative poverty of farmers and its mechanism. Results show that farmers in reserves are more likely to fall into multidimensional relative poverty than those outside the reserves, and there is a U‐shaped relationship between regulation intensity and multidimensional relative poverty. Further, the mechanism analysis show that, on average, the establishment of reserves has no significant impact on farmers' resource utilization capability, but too high or too low regulation intensity will affect farmers' resource utilization capacity, and aggravate their multidimensional relative poverty. The conclusions of this paper are not only conducive to the expansion of theoretical research on regulation and poverty, but also provide policy implications for realizing the coordinated development between biodiversity conservation of nature reserves and rural livelihood.
{"title":"Reserve regulation and multidimensional relative poverty of farmers: Evidence from the Panda Nature Reserves in China","authors":"Chao-Ching Lin, Lan Gao","doi":"10.1111/nrm.12358","DOIUrl":"https://doi.org/10.1111/nrm.12358","url":null,"abstract":"The accurate evaluation of the relationship between nature reserves and poverty is highly significant for the harmonious coexistence between human and nature. It is widely recognized that the establishment of nature reserves is of great importance to the income poverty of farmers, but less attention has been paid to the impact of different reserves on the multidimensional relative poverty of farmers. Based on the survey data of Panda Nature Reserves in China, we analyze the influence of reserve regulation (or not) and regulation intensity on the multidimensional relative poverty of farmers and its mechanism. Results show that farmers in reserves are more likely to fall into multidimensional relative poverty than those outside the reserves, and there is a U‐shaped relationship between regulation intensity and multidimensional relative poverty. Further, the mechanism analysis show that, on average, the establishment of reserves has no significant impact on farmers' resource utilization capability, but too high or too low regulation intensity will affect farmers' resource utilization capacity, and aggravate their multidimensional relative poverty. The conclusions of this paper are not only conducive to the expansion of theoretical research on regulation and poverty, but also provide policy implications for realizing the coordinated development between biodiversity conservation of nature reserves and rural livelihood.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45631069","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}
Marie‐Catherine Riekhof, L. C. Kluger, R. Salvatteci, Lotta Siebert, Rudi Voss
We introduce six steps to define a “Window of Tipping Point Analysis” which serves as a framework to increase the understanding of processes and tipping points in social‐ecological systems. We apply the Window of Tipping Point Analysis to a mathematical model and two case studies (i.e., Baltic Sea and the Humboldt Current Upwelling system), focusing on three aspects. In “to tip or be tipped” we look at agency in preventing (or driving) tipping. In “to be tipped or not to be tipped” we discuss intertemporal developments and chosen time periods for delineating regime shifts. In “to tip or not to tip” we discuss the desirability of states and their relation to the elements included. We argue that agency in tipping‐point management, the occurrence of tipping points, and desirable states depend on the window chosen for the analysis.
{"title":"To tip or not to tip: The Window of Tipping Point Analysis for social‐ecological systems","authors":"Marie‐Catherine Riekhof, L. C. Kluger, R. Salvatteci, Lotta Siebert, Rudi Voss","doi":"10.1111/nrm.12357","DOIUrl":"https://doi.org/10.1111/nrm.12357","url":null,"abstract":"We introduce six steps to define a “Window of Tipping Point Analysis” which serves as a framework to increase the understanding of processes and tipping points in social‐ecological systems. We apply the Window of Tipping Point Analysis to a mathematical model and two case studies (i.e., Baltic Sea and the Humboldt Current Upwelling system), focusing on three aspects. In “to tip or be tipped” we look at agency in preventing (or driving) tipping. In “to be tipped or not to be tipped” we discuss intertemporal developments and chosen time periods for delineating regime shifts. In “to tip or not to tip” we discuss the desirability of states and their relation to the elements included. We argue that agency in tipping‐point management, the occurrence of tipping points, and desirable states depend on the window chosen for the analysis.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42140147","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}
Seong‐Hoon Cho, James C. Mingie, Nawon Kang, G. Zhu, Sreedhar Upendram
The purpose of this study is to understand how solutions from single‐ and multiobjective optimization for the conservation of multiple species are different and what impacts these differences. We identify optimal conservation investment allocations maximizing expected species' habitat ranges for multiple pairs of species using two approaches in the central and southern Appalachian region. We find that disparities between the two approaches are affected by differences in the involved species' expected habitat ranges (i.e., contrasting and similar) and their correlation pattern (i.e., positive, negative, and insignificant). Using a single metric by aggregating species' habitats for multiple species to carry out single‐objective optimization is shown to favor the species with a larger habitat distribution more if the involved species' expected habitat distributions are negatively correlated and their distribution difference is larger. Framing multiple metrics of species' habitats separately using multiobjective optimization for the same set of multiple species, in contrast, does not show such a drastic disparity.
{"title":"Understanding the differences between single‐ and multiobjective optimization for the conservation of multiple species","authors":"Seong‐Hoon Cho, James C. Mingie, Nawon Kang, G. Zhu, Sreedhar Upendram","doi":"10.1111/nrm.12356","DOIUrl":"https://doi.org/10.1111/nrm.12356","url":null,"abstract":"The purpose of this study is to understand how solutions from single‐ and multiobjective optimization for the conservation of multiple species are different and what impacts these differences. We identify optimal conservation investment allocations maximizing expected species' habitat ranges for multiple pairs of species using two approaches in the central and southern Appalachian region. We find that disparities between the two approaches are affected by differences in the involved species' expected habitat ranges (i.e., contrasting and similar) and their correlation pattern (i.e., positive, negative, and insignificant). Using a single metric by aggregating species' habitats for multiple species to carry out single‐objective optimization is shown to favor the species with a larger habitat distribution more if the involved species' expected habitat distributions are negatively correlated and their distribution difference is larger. Framing multiple metrics of species' habitats separately using multiobjective optimization for the same set of multiple species, in contrast, does not show such a drastic disparity.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":"36 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41726730","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}
Many natural resources around the world are being overexploited (FAO Fisheries Department, 2022; IPBES, 2019), sometimes to the extent that ecosystems are on the brink of collapse. This is especially true for marine systems where overfishing is a continuous and globally increasing ecological and economic issue, also resulting in impacts on society and culture. Marine ecosystems are threatened to cross tipping points, leading to abrupt changes in recruitment, biomass, and consequently in catches (Möllmann et al., 2021). In the past years, tipping point analysis has spread to various interdisciplinary fields such as natural resource modeling. A historic example is found in the shallow lakes theory where several stable states have been shown to exist and to reverse tipping from a healthy ecosystem to a eutrophicated state may require more than just nutrient removal (Scheffer, 1997). The optimal management of these systems requires interdisciplinary approaches that account for the vulnerability of ecosystems to tipping but also to consider multiple economic costs and benefits (Voss & Quaas, 2021). In an integrated perspective of natural resource systems that takes the feedbacks between ecological and socioeconomic processes into account, tipping points in the system are not necessarily a bad thing. These systems may be on an unsustainable path, and achieving sustainability may require to shift the system toward another domain of attraction (Derissen & Quaas, 2013). The aim of the 2021 World Conference on Natural Resource Modeling was to discuss how to change ecological‐economic system dynamics toward long‐term sustainability. As worldwide pandemic restrictions were in place it was the first fully virtual conference of the Resource Modeling Association. Owing to low costs and sessions convenient to all time zones the conference became a particularly inclusive event, with a wide range of papers and topics from all over the world. The collection of papers in this special issue represents a selection of contributions toward the fields of tipping point analysis and the management of coupled ecological socioeconomic systems. In “To tip or not to tip: The Window of Tipping Point Analysis for social‐ecological systems” Riekhof et al. (2022) introduce a new framework to increase the understanding of processes and tipping points in social‐ecological systems and discuss the desirability of alternative stable states. In “A stylized model of stochastic ecosystems with alternative stable states” Stecher and Baumgärtner (2022) advance the field of multistability by introducing stochasticity in the ecosystem state and identifying a multitude of important applications. Finally, in “Joint management of marine mammals and a fish species: The case of cod and grey seals in the Nordic‐Baltic Sea countries” Blomquist et al. (2022) point out the importance of taking multiple costs and benefits of predators and harvested prey in a managed marine ecosystem into account. We wo
{"title":"Editorial","authors":"F. Meier, Hanna Schenk","doi":"10.1111/nrm.12359","DOIUrl":"https://doi.org/10.1111/nrm.12359","url":null,"abstract":"Many natural resources around the world are being overexploited (FAO Fisheries Department, 2022; IPBES, 2019), sometimes to the extent that ecosystems are on the brink of collapse. This is especially true for marine systems where overfishing is a continuous and globally increasing ecological and economic issue, also resulting in impacts on society and culture. Marine ecosystems are threatened to cross tipping points, leading to abrupt changes in recruitment, biomass, and consequently in catches (Möllmann et al., 2021). In the past years, tipping point analysis has spread to various interdisciplinary fields such as natural resource modeling. A historic example is found in the shallow lakes theory where several stable states have been shown to exist and to reverse tipping from a healthy ecosystem to a eutrophicated state may require more than just nutrient removal (Scheffer, 1997). The optimal management of these systems requires interdisciplinary approaches that account for the vulnerability of ecosystems to tipping but also to consider multiple economic costs and benefits (Voss & Quaas, 2021). In an integrated perspective of natural resource systems that takes the feedbacks between ecological and socioeconomic processes into account, tipping points in the system are not necessarily a bad thing. These systems may be on an unsustainable path, and achieving sustainability may require to shift the system toward another domain of attraction (Derissen & Quaas, 2013). The aim of the 2021 World Conference on Natural Resource Modeling was to discuss how to change ecological‐economic system dynamics toward long‐term sustainability. As worldwide pandemic restrictions were in place it was the first fully virtual conference of the Resource Modeling Association. Owing to low costs and sessions convenient to all time zones the conference became a particularly inclusive event, with a wide range of papers and topics from all over the world. The collection of papers in this special issue represents a selection of contributions toward the fields of tipping point analysis and the management of coupled ecological socioeconomic systems. In “To tip or not to tip: The Window of Tipping Point Analysis for social‐ecological systems” Riekhof et al. (2022) introduce a new framework to increase the understanding of processes and tipping points in social‐ecological systems and discuss the desirability of alternative stable states. In “A stylized model of stochastic ecosystems with alternative stable states” Stecher and Baumgärtner (2022) advance the field of multistability by introducing stochasticity in the ecosystem state and identifying a multitude of important applications. Finally, in “Joint management of marine mammals and a fish species: The case of cod and grey seals in the Nordic‐Baltic Sea countries” Blomquist et al. (2022) point out the importance of taking multiple costs and benefits of predators and harvested prey in a managed marine ecosystem into account. We wo","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41610545","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}
We consider the problem of optimal harvesting of a renewable resource whose dynamics are governed by logistic growth and whose payoff is proportional to the harvest. We consider both the case of a finite and an infinite time horizon and analyse the structure of the optimal solutions and their dependence on the parameters of the model. We show that the optimal policy can only have one of three structures: (1) maximal harvesting effort until the resource is depleted, (2) zero harvesting during an initial time interval followed by a subsequent switch to maximal harvesting effort, or (3) a singular solution, which corresponds to an intermediate level of harvesting, accompanied by the most rapid approach path. All three scenarios emerge, with minor variations, with finite and infinite time horizons, depending on the particular combination of parameters of the system. We characterize the conditions under which the singular solution is optimal and present suggestions for designing an optimal and sustainable harvesting strategy.
{"title":"The structure of optimal solutions for harvesting a renewable resource","authors":"Thorsten Upmann, D. Gromov","doi":"10.1111/nrm.12355","DOIUrl":"https://doi.org/10.1111/nrm.12355","url":null,"abstract":"We consider the problem of optimal harvesting of a renewable resource whose dynamics are governed by logistic growth and whose payoff is proportional to the harvest. We consider both the case of a finite and an infinite time horizon and analyse the structure of the optimal solutions and their dependence on the parameters of the model. We show that the optimal policy can only have one of three structures: (1) maximal harvesting effort until the resource is depleted, (2) zero harvesting during an initial time interval followed by a subsequent switch to maximal harvesting effort, or (3) a singular solution, which corresponds to an intermediate level of harvesting, accompanied by the most rapid approach path. All three scenarios emerge, with minor variations, with finite and infinite time horizons, depending on the particular combination of parameters of the system. We characterize the conditions under which the singular solution is optimal and present suggestions for designing an optimal and sustainable harvesting strategy.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":"36 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63504218","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}
Using a fossil fuel extraction model that treats the atmosphere as a depletable resource, we study the optimal price of carbon in the presence of endogenous uncertainty around a climatic regime shift. We find that the optimal carbon tax should account an uncertainty‐adjusted cost term associated with the environment's scarcity. This term is shown to be sensitive to the natural sequestration rate of the atmosphere and to the probability surrounding a climate tail event. Our analysis also shows that in the presence of uncertainty, the shadow price of the environment should grow at a faster rate. Lastly, compared to the endogenous uncertainty case, we find that if the probability surrounding a regime shift is exogenously given, this shadow price should even grow at a higher rate.
{"title":"Polluting resource extraction and climate risk","authors":"Israa Hashem, Walid Marrouch","doi":"10.1111/nrm.12354","DOIUrl":"https://doi.org/10.1111/nrm.12354","url":null,"abstract":"Using a fossil fuel extraction model that treats the atmosphere as a depletable resource, we study the optimal price of carbon in the presence of endogenous uncertainty around a climatic regime shift. We find that the optimal carbon tax should account an uncertainty‐adjusted cost term associated with the environment's scarcity. This term is shown to be sensitive to the natural sequestration rate of the atmosphere and to the probability surrounding a climate tail event. Our analysis also shows that in the presence of uncertainty, the shadow price of the environment should grow at a faster rate. Lastly, compared to the endogenous uncertainty case, we find that if the probability surrounding a regime shift is exogenously given, this shadow price should even grow at a higher rate.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44709436","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}
Timothée Audinot, H. Wernsdörfer, G. Le Moguédec, J. Bontemps
Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug‐in option to any inventory‐based initial condition. Forty‐year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority.
{"title":"Modeling and propagating inventory‐based sampling uncertainty in the large‐scale forest demographic model “MARGOT”","authors":"Timothée Audinot, H. Wernsdörfer, G. Le Moguédec, J. Bontemps","doi":"10.1111/nrm.12352","DOIUrl":"https://doi.org/10.1111/nrm.12352","url":null,"abstract":"Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug‐in option to any inventory‐based initial condition. Forty‐year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43519007","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}
Land use land cover (LULC) dynamics have long been recognized as a significant driver of natural resource change. As a result, understanding the spatial and temporal variation of LULC in the watershed is essential for effective natural resource management and long‐term development. This study attempts to analyze the dynamics and change drivers from 1990 to 2020 and predict the situation for 2035 and 2050 in the Ajora‐Woybo watershed. ArcGIS 10.3 and ERDAS 2015 were used to analyze quantitative data from Landsat imagery. For supervised image classification, a Maximum‐Likelihood classification algorithm was used. To identify driver variables, focus groups and key informants' interviews were done. TerrSet 18.31 software was used to predict LULC utilizing the Multi‐Layer Perceptron Neural Network and Cellular Automata‐Markov Chain models incorporated in Land Change Modeler. Six LULC classes were discovered: cultivated land, built‐up, shrub land, forest land, bare land, and water body. Cultivated land, built‐up area, and bare land have increased at the expense of shrub land and forest land over the last three decades. Trends in water bodies show both decreasing and increasing trends. According to the predicted outcomes, cultivated land, built‐up and bare land has increased, while shrub land and forest land have declined. Finally, agricultural expansion, population growth, wood extraction, resettlement, urbanization, and lack of environmental consideration were identified as the major drivers of LULC change. The study demonstrated that there have been significant changes in the watershed LULC. As a result, reversing the predicted conditions is critical to ensuring the watershed long‐term viability.
{"title":"Historical and future dynamics of land use land cover and its drivers in Ajora‐Woybo watershed, Omo‐Gibe basin, Ethiopia","authors":"M. B. Toma, Mulugeta Dadi Belete, M. Ulsido","doi":"10.1111/nrm.12353","DOIUrl":"https://doi.org/10.1111/nrm.12353","url":null,"abstract":"Land use land cover (LULC) dynamics have long been recognized as a significant driver of natural resource change. As a result, understanding the spatial and temporal variation of LULC in the watershed is essential for effective natural resource management and long‐term development. This study attempts to analyze the dynamics and change drivers from 1990 to 2020 and predict the situation for 2035 and 2050 in the Ajora‐Woybo watershed. ArcGIS 10.3 and ERDAS 2015 were used to analyze quantitative data from Landsat imagery. For supervised image classification, a Maximum‐Likelihood classification algorithm was used. To identify driver variables, focus groups and key informants' interviews were done. TerrSet 18.31 software was used to predict LULC utilizing the Multi‐Layer Perceptron Neural Network and Cellular Automata‐Markov Chain models incorporated in Land Change Modeler. Six LULC classes were discovered: cultivated land, built‐up, shrub land, forest land, bare land, and water body. Cultivated land, built‐up area, and bare land have increased at the expense of shrub land and forest land over the last three decades. Trends in water bodies show both decreasing and increasing trends. According to the predicted outcomes, cultivated land, built‐up and bare land has increased, while shrub land and forest land have declined. Finally, agricultural expansion, population growth, wood extraction, resettlement, urbanization, and lack of environmental consideration were identified as the major drivers of LULC change. The study demonstrated that there have been significant changes in the watershed LULC. As a result, reversing the predicted conditions is critical to ensuring the watershed long‐term viability.","PeriodicalId":49778,"journal":{"name":"Natural Resource Modeling","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46163284","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：