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Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala

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  • López-Carr, David
  • Davis, Jason
  • Jankowska, Marta M.
  • Grant, Laura
  • López-Carr, Anna Carla
  • Clark, Matthew

Abstract

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human–natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of place-based hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001 to 2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human–environment interactions.

Suggested Citation

  • López-Carr, David & Davis, Jason & Jankowska, Marta M. & Grant, Laura & López-Carr, Anna Carla & Clark, Matthew, 2012. "Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala," Ecological Modelling, Elsevier, vol. 229(C), pages 64-75.
  • Handle: RePEc:eee:ecomod:v:229:y:2012:i:c:p:64-75
    DOI: 10.1016/j.ecolmodel.2011.08.020
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    1. Fondevilla, Cristian & Àngels Colomer, M. & Fillat, Federico & Tappeiner, Ulrike, 2016. "Using a new PDP modelling approach for land-use and land-cover change predictions: A case study in the Stubai Valley (Central Alps)," Ecological Modelling, Elsevier, vol. 322(C), pages 101-114.
    2. Wenseslao Plata-Rocha & Sergio Alberto Monjardin-Armenta & Carlos Eduardo Pacheco-Angulo & Jesus Gabriel Rangel-Peraza & Cuauhtemoc Franco-Ochoa & Zuriel Dathan Mora-Felix, 2021. "Proximate and Underlying Deforestation Causes in a Tropical Basin through Specialized Consultation and Spatial Logistic Regression Modeling," Land, MDPI, vol. 10(2), pages 1-18, February.
    3. Shengwang Bao & Fan Yang, 2022. "Spatio-Temporal Dynamic of the Land Use/Cover Change and Scenario Simulation in the Southeast Coastal Shelterbelt System Construction Project Region of China," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    4. Rubén Ferrer Velasco & Margret Köthke & Melvin Lippe & Sven Günter, 2020. "Scale and context dependency of deforestation drivers: Insights from spatial econometrics in the tropics," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-32, January.
    5. Sarah Turner & Thi-Thanh-Hiên Pham, 2015. "“Nothing Is Like It Was Before”: The Dynamics between Land-Use and Land-Cover, and Livelihood Strategies in the Northern Vietnam Borderlands," Land, MDPI, vol. 4(4), pages 1-30, November.
    6. 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.
    7. Romanovs Andrejs & Lektauers Arnis & Soshko Oksana & Zelentsov Viacheslav, 2013. "Models of the Monitoring and Control of Natural and Technological Objects," Information Technology and Management Science, Sciendo, vol. 16(1), pages 121-130, December.
    8. Yafei Li & Gaohuan Liu, 2017. "Characterizing Spatiotemporal Pattern of Land Use Change and Its Driving Force Based on GIS and Landscape Analysis Techniques in Tianjin during 2000–2015," Sustainability, MDPI, vol. 9(6), pages 1-26, May.

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