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Projecting landscape changes in southern Chile: Simulation of human and natural processes driving land transformation

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  • Marín, Sandra L.
  • Nahuelhual, Laura
  • Echeverría, Cristian
  • Grant, William E.

Abstract

We describe a simulation model representing the most important human and natural factors driving land use and cover changes (LUCC) in southern Chile. We evaluate the model by examining its ability to simulate LUCC observed over the past three decades, conduct a sensitivity analysis of simulated trends to changes in important model parameters, and use the model to project likely landscape transformations over the next decade under “as usual,” “pessimistic,” and four “optimistic” scenarios. The model consists of five submodels representing LUCC on two distinct soil formations (volcanic ash and gleysols) and four major land use categories: native forest, agricultural land, shrubland, and urban land. Land use and cover sub-categories include old growth forests, secondary forests, and low and flooded shrubland. The model simulated well general historic trends in forest cover, agricultural land, shrubland, and urban land: from a forest-dominated landscape in 1976 to a landscape dominated by shrubland and agricultural land by 2007. Forest loss, forest degradation by logging and clearing for agriculture were the most important direct drivers of LUCC: forest logging and clearing were most important from 1976 to 1985, whereas after 1985 logging for firewood, driven by population growth, was most important. Sensitivity analysis indicated that model projections of general trends in the main land use and cover categories were not overly sensitive to changes in important model parameters, although further study is necessary to improve our estimates of the proportion of pasture requirements supplied by clearing low shrubland. Projections of LUCC suggested that a reduced amount of secondary forest would be left by 2017 if no actions are taken to reduce forest loss (“as usual”). Increasing population (“pessimistic scenario”) resulted in similar trajectories than those predicted by the as usual scenario, whereas reducing logging for firewood and increasing forest recruitment from shrubland could reduce loss of native forest by nearly one-third (“optimistic scenarios”). Surprisingly, shrubland exhibited the most complex and influential dynamics in all scenarios, being the immediate outcome of forest loss and the main long-term source of land for agriculture, urban expansion, and forest recovery. Few studies in Chile, or elsewhere, have considered the importance of this intermediate successional stage. Of the scenarios simulated, financial incentives targeted toward channeling shrubland into regenerated forest seemed most promising, although obstacles to such a management strategy exist.

Suggested Citation

  • Marín, Sandra L. & Nahuelhual, Laura & Echeverría, Cristian & Grant, William E., 2011. "Projecting landscape changes in southern Chile: Simulation of human and natural processes driving land transformation," Ecological Modelling, Elsevier, vol. 222(15), pages 2841-2855.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:15:p:2841-2855
    DOI: 10.1016/j.ecolmodel.2011.04.026
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    References listed on IDEAS

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    1. Helen Briassoulis, 2000. "Analysis of Land Use Change: Theoretical and Modeling Approaches," Wholbk, Regional Research Institute, West Virginia University, number 17, Fall.
    2. Barrett, Gene & Caniggia, Mauricio I. & Read, Lorna, 2002. ""There are More Vets than Doctors in Chiloe": Social and Community Impact of the Globalization of Aquaculture in Chile," World Development, Elsevier, vol. 30(11), pages 1951-1965, November.
    3. Echeverria, Cristian & Coomes, David A. & Hall, Myrna & Newton, Adrian C., 2008. "Spatially explicit models to analyze forest loss and fragmentation between 1976 and 2020 in southern Chile," Ecological Modelling, Elsevier, vol. 212(3), pages 439-449.
    4. repec:rri:bkchap:17 is not listed on IDEAS
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    Cited by:

    1. Fengqiang Wu & Caijian Mo & Xiaojun Dai, 2022. "Analysis of the Driving Force of Land Use Change Based on Geographic Detection and Simulation of Future Land Use Scenarios," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    2. Thinh An Nguyen & Phuong Minh Thi Le & Tam Minh Pham & Huong Thi Thu Hoang & Minh Quang Nguyen & Hoa Quynh Ta & Hanh Thi My Phung & Ha Thi Thu Le & Luc Hens, 2019. "Toward a sustainable city of tomorrow: a hybrid Markov–Cellular Automata modeling for urban landscape evolution in the Hanoi city (Vietnam) during 1990–2030," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(1), pages 429-446, February.
    3. de Souza, Rodrigo Antônio & De Marco, Paulo, 2018. "Improved spatial model for Amazonian deforestation: An empirical assessment and spatial bias analysis," Ecological Modelling, Elsevier, vol. 387(C), pages 1-9.

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