Vista normal Vista MARC

Application of the climafor approach to estimate baseline carbon emissions of a forest conservation project in the Selva Lacandona, Chiapas, Mexico

De Jong, Bernardus Hendricus Jozeph | Hellier, A [autor/a] | Castillo Santiago, Miguel Ángel [autor/a] | Tipper, R [autor/a].
Tipo de material: Artículo impreso(a) y electrónico Artículo impreso(a) y electrónico Tema(s): Uso de la tierra | Conservación de bosques | Deforestación | Captura de carbono | Análisis espacial (Estadística)Descriptor(es) geográficos: Selva Lacandona (Chiapas, México) Clasificación: AR/333.75137 / A6 Nota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso En: Mitigation and Adaptation Strategies for Global Change. volumen 10, número 2 (2005), páginas 265-278. --ISSN: 1381-2386Número de sistema: 37217Resumen:
Inglés

We present a methodology for testing and applying a regional baseline for carbon (C) emissions from land-use change, using a spatial modelling approach (hereafter called the Climafor approach). The methodology is based on an analysis of causal factors of previous land-use change(Castillo et al. 2005). Carbon risk matrices constructed from the spatial correlation analysis between observed deforestation and driving factors (Castillo et al. 2005), are used to estimate future carbonemissions within acceptable limits for a forest conservation project. The performance of two risk matrices were tested by estimating carbon emissions between 1975 and 1996 from randomly selected sample plots of sizes varying from 1,600 to 10,000 ha and comparing the results of the observed emissions from these sample plots with the model estimations. Expected emissions from continued land-use change was estimated for the community applying the risk matrices to the current land cover. The methodology provides an objective means of constructing baseline scenarios including confidence intervals, using the sum of variances of the various data sources, such as measured carbon densities, classification errors, errors in the risk matrices, and differences between the model prediction and observed emissions of sample plots due to sample size. The procedures applied in this study also give an indication of the impact of the variance in the various data sources on the size of the confidence intervals, which allows project developers to decide what data sources are essential to improve his baseline. The modelling approach to estimate the deforestation pattern is based on readily available cartographic and census data, whereas data on carbon densities are required to assess the potential for forest conservation projects to offset carbon emissions.

Recurso en línea: https://link.springer.com/article/10.1007/s11027-005-7132-8
Etiquetas de esta biblioteca: No hay etiquetas de esta biblioteca para este título. Ingresar para agregar etiquetas.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Info Vol Estado Fecha de vencimiento Código de barras
Artículos Biblioteca Campeche

Texto en la configuración de la biblioteca Campeche

Artículos (AR) 		ECOSUR AR 333.75137 A6 005 Disponible ECO040002470
Artículos Biblioteca Chetumal

Texto en configuración de biblioteca Chetumal

Artículos (AR) 		ECOSUR AR 333.75137 A6 004 Disponible ECO030001237
Artículos Biblioteca Electrónica
Recursos en línea (RE) 		ECOSUR Recurso digital ECO400372171404
Artículos Biblioteca San Cristóbal

Texto en la configuración de la biblioteca San Cristóbal

Artículos (AR) 		ECOSUR AR 333.75137 A6 002 Disponible ECO010004676
Artículos Biblioteca Tapachula

Texto colocado en la configuración de la biblioteca Tapachula

Artículos (AR) 		ECOSUR AR 333.75137 A6 001 Disponible ECO020008246
Artículos Biblioteca Villahermosa

Texto en la configuración de la biblioteca Villahermosa

Artículos (AR) 		ECOSUR AR 333.75137 A6 003 Disponible ECO050002505

Disponible para usuarios de ECOSUR con su clave de acceso

We present a methodology for testing and applying a regional baseline for carbon (C) emissions from land-use change, using a spatial modelling approach (hereafter called the Climafor approach). The methodology is based on an analysis of causal factors of previous land-use change(Castillo et al. 2005). Carbon risk matrices constructed from the spatial correlation analysis between observed deforestation and driving factors (Castillo et al. 2005), are used to estimate future carbonemissions within acceptable limits for a forest conservation project. The performance of two risk matrices were tested by estimating carbon emissions between 1975 and 1996 from randomly selected sample plots of sizes varying from 1,600 to 10,000 ha and comparing the results of the observed emissions from these sample plots with the model estimations. Expected emissions from continued land-use change was estimated for the community applying the risk matrices to the current land cover. The methodology provides an objective means of constructing baseline scenarios including confidence intervals, using the sum of variances of the various data sources, such as measured carbon densities, classification errors, errors in the risk matrices, and differences between the model prediction and observed emissions of sample plots due to sample size. The procedures applied in this study also give an indication of the impact of the variance in the various data sources on the size of the confidence intervals, which allows project developers to decide what data sources are essential to improve his baseline. The modelling approach to estimate the deforestation pattern is based on readily available cartographic and census data, whereas data on carbon densities are required to assess the potential for forest conservation projects to offset carbon emissions. eng

Disponible en línea

Adobe Acrobat profesional 6.0 o superior

Con tecnología Koha