Attributing changes in land cover using independent disturbance datasets: a case study of the Yucatan Peninsula, Mexico
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- 作者：Vanessa S. Mascorro ; Nicholas C. Coops ; Werner A. Kurz…
- 关键词：Forest disturbance ; CBM ; CFS3 ; Carbon modeling ; MRV ; Mexico ; REDD+
- 刊名：Regional Environmental Change
- 出版年：2016
- 出版时间：January 2016
- 年：2016
- 卷：16
- 期：1
- 页码：213-228
- 全文大小：7,529 KB
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Nicholas C. Coops (1)
Werner A. Kurz (2)
Marcela Olguín (3)
1. Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada
2. Canadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada
3. Proyecto Mexico-Noruega, Comision Nacional Forestal, Col. del Carmen Coyoacán, CP 04100, Coyoacán, D.F., Mexico - 刊物类别：Earth and Environmental Science
- 刊物主题：Environment
Geoecology and Natural Processes
Geology
Oceanography
Geography
Nature Conservation
Regional Science - 出版者：Springer Berlin / Heidelberg
- ISSN：1436-378X
文摘
Detailed observations of natural and anthropogenic disturbance events that impact forest structure and the distribution of carbon are essential to estimate changes in terrestrial carbon pools and the associated emissions and removals of greenhouse gasses. Recent advances in remote sensing approaches have resulted in annual and decadal estimates of land-cover change derived from observations using broad-scale moderate resolution imaging spectroradiometer (MODIS) 250 m–1 km imagery. These land-use change estimates, however, are often not attributed directly to a cause or activity and are not well validated, especially in tropical areas. Knowledge of the type of disturbance that caused the observed land-cover changes is important, however, for the quantification of the associated impacts on ecosystem carbon stocks and fluxes. In this paper, we provide estimates of the amount of forest land-cover change in a Mexican forested region and propose an approach for attributing the cause of the observed changes to the underlying disturbance driver. To do so, we collate geospatial and remote sensing data from a variety of sources to summarize statistics about the major disturbances within the Yucatan Peninsula, an “early action” region for the reduction of emissions from deforestation and degradation, from 2005 to 2010. We combine the datasets to develop rules to estimate the likely disturbances that caused the observed land-cover changes based on their spatially explicit location. Finally, we compare our observed disturbance rates to those detected using classified land-cover data derived from MODIS. Keywords Forest disturbance CBM-CFS3 Carbon modeling MRV Mexico REDD+