{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/24147"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/24147","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Increasing forest cover amidst expanding commercial agriculture: An agent-based simulation of markets and rural livelihoods in the Indian Himalayas","abstract":"In contrast to many studies that link commercial agriculture with deforestation, analysis of household survey data and forest measurements in a group of 17 neighboring villages in the Indian Himalayas revealed a positive correlation between the level of commercial agriculture and forest cover. Commercial agriculture channels resources away from cattle-raising, which is heavily dependent on forests for grazing. Unlike many of the cases where deforestation is a direct outcome of commercial agriculture expansion, there is a complementary relationship between the centralized enforcement of the state forest department and the decentralized enforcement of households who depend on the forests for various livelihood activities. By exercising flexibility toward forest dependence activities while strongly enforcing against outright deforestation and degradation, state forest guards cultivate common interests in forest outcomes. Households are stakeholders in the condition of forests on which they depend, and they reinforce the efforts of forest guards to enforce laws against tree felling and encroachment. When the pressures of large-scale deforestation are contained, the more subtle effects of reduced grazing pressure can be observed. To better understand the drivers of commercial crop cultivation, a dynamic, agent-based model was designed to assess the relationship between household crop choices and market dynamics. Households were modeled as “consumers of choices” who evaluate and select choices with the best outcomes. Rather than focusing exclusively on market signals, the model introduces more complex elements of household decision-making like diversification and social norms. As households often converge on a common crop choice in shared land units, the model results reveal that social norms act as a buffer against the influence of market signals. Household choices respond weakly to market fluctuations unless the fluctuations reach a critical level that triggers tipping points in the decision-making process. Sustained, weak market fluctuations have less impact on long-term crop choices than short-term, strong fluctuations. Market dynamics are not the only potential triggers of tipping points. Changes related to climate change may also be significant. Higher temperatures could make sowing and harvest dates occur sooner in the year. If harvest dates for peas occur two weeks sooner than normal, the model predicts that pea cultivation will increase by 10% because households will take advantage of seasonal price variations. Assessing future commercial cropping levels and their associated impacts on forest cover requires careful study of potential triggers of tipping points. These include strong or volatile market signals, as well as other major changes to harvest schedules or productivity.","abstract_html":"In contrast to many studies that link commercial agriculture with deforestation, analysis of household survey data and forest measurements in a group of 17 neighboring villages in the Indian Himalayas revealed a positive correlation between the level of commercial agriculture and forest cover. Commercial agriculture channels resources away from cattle-raising, which is heavily dependent on forests for grazing. Unlike many of the cases where deforestation is a direct outcome of commercial agriculture expansion, there is a complementary relationship between the centralized enforcement of the state forest department and the decentralized enforcement of households who depend on the forests for various livelihood activities. By exercising flexibility toward forest dependence activities while strongly enforcing against outright deforestation and degradation, state forest guards cultivate common interests in forest outcomes. Households are stakeholders in the condition of forests on which they depend, and they reinforce the efforts of forest guards to enforce laws against tree felling and encroachment. When the pressures of large-scale deforestation are contained, the more subtle effects of reduced grazing pressure can be observed. To better understand the drivers of commercial crop cultivation, a dynamic, agent-based model was designed to assess the relationship between household crop choices and market dynamics. Households were modeled as “consumers of choices” who evaluate and select choices with the best outcomes. Rather than focusing exclusively on market signals, the model introduces more complex elements of household decision-making like diversification and social norms. As households often converge on a common crop choice in shared land units, the model results reveal that social norms act as a buffer against the influence of market signals. Household choices respond weakly to market fluctuations unless the fluctuations reach a critical level that triggers tipping points in the decision-making process. Sustained, weak market fluctuations have less impact on long-term crop choices than short-term, strong fluctuations. Market dynamics are not the only potential triggers of tipping points. Changes related to climate change may also be significant. Higher temperatures could make sowing and harvest dates occur sooner in the year. If harvest dates for peas occur two weeks sooner than normal, the model predicts that pea cultivation will increase by 10% because households will take advantage of seasonal price variations. Assessing future commercial cropping levels and their associated impacts on forest cover requires careful study of potential triggers of tipping points. These include strong or volatile market signals, as well as other major changes to harvest schedules or productivity.","abstract_has_math":false,"creators":["Burton, Greg P."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Geography","degree_department":null,"school":null,"contributors":["Chhatre, Ashwini"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-25T14:58:39Z","date_published":"2011-05-25T14:58:39Z","updated_at":"2026-07-22T22:25:23Z","subjects":["commercial agriculture","reforestation","deforestation","cash crops","agent-based model","utility maximization","India","rural livelihoods","household decision-making","enforcement","opportunity cost of labor"],"languages":["en"],"rights":["Copyright 2011 Greg P. 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Unlike many of the cases where deforestation is a direct outcome of commercial agriculture expansion, there is a complementary relationship between the centralized enforcement of the state forest department and the decentralized enforcement of households who depend on the forests for various livelihood activities. By exercising flexibility toward forest dependence activities while strongly enforcing against outright deforestation and degradation, state forest guards cultivate common interests in forest outcomes. Households are stakeholders in the condition of forests on which they depend, and they reinforce the efforts of forest guards to enforce laws against tree felling and encroachment. When the pressures of large-scale deforestation are contained, the more subtle effects of reduced grazing pressure can be observed. To better understand the drivers of commercial crop cultivation, a dynamic, agent-based model was designed to assess the relationship between household crop choices and market dynamics. Households were modeled as “consumers of choices” who evaluate and select choices with the best outcomes. Rather than focusing exclusively on market signals, the model introduces more complex elements of household decision-making like diversification and social norms. As households often converge on a common crop choice in shared land units, the model results reveal that social norms act as a buffer against the influence of market signals. Household choices respond weakly to market fluctuations unless the fluctuations reach a critical level that triggers tipping points in the decision-making process. Sustained, weak market fluctuations have less impact on long-term crop choices than short-term, strong fluctuations. Market dynamics are not the only potential triggers of tipping points. Changes related to climate change may also be significant. Higher temperatures could make sowing and harvest dates occur sooner in the year. If harvest dates for peas occur two weeks sooner than normal, the model predicts that pea cultivation will increase by 10% because households will take advantage of seasonal price variations. Assessing future commercial cropping levels and their associated impacts on forest cover requires careful study of potential triggers of tipping points. 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To better understand the drivers of commercial crop cultivation, a dynamic, agent-based model was designed to assess the relationship between household crop choices and market dynamics. Households were modeled as “consumers of choices” who evaluate and select choices with the best outcomes. Rather than focusing exclusively on market signals, the model introduces more complex elements of household decision-making like diversification and social norms. As households often converge on a common crop choice in shared land units, the model results reveal that social norms act as a buffer against the influence of market signals. Household choices respond weakly to market fluctuations unless the fluctuations reach a critical level that triggers tipping points in the decision-making process. Sustained, weak market fluctuations have less impact on long-term crop choices than short-term, strong fluctuations. Market dynamics are not the only potential triggers of tipping points. Changes related to climate change may also be significant. Higher temperatures could make sowing and harvest dates occur sooner in the year. If harvest dates for peas occur two weeks sooner than normal, the model predicts that pea cultivation will increase by 10% because households will take advantage of seasonal price variations. Assessing future commercial cropping levels and their associated impacts on forest cover requires careful study of potential triggers of tipping points. 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