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No. de sistema: 000037217

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008 _ _ 050824m20059999xx^frzp^^^^^^z0^^^a0eng^d
040 _ _ a| ECO
c| ECO
043 _ _ a| n-mx-cp
044 _ _ a| xx
084 _ _ a| AR/333.75137
b| A6
245 0 0 a| Application of the climafor approach to estimate baseline carbon emissions of a forest conservation project in the Selva Lacandona, Chiapas, Mexico
506 _ _ a| Disponible para usuarios de ECOSUR con su clave de acceso
520 1 _ a| 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.
533 _ _ a| Reproducción electrónica en formato PDF
538 _ _ a| Adobe Acrobat profesional 6.0 o superior
650 _ 4 a| Uso de la tierra
650 _ 4 a| Conservación de bosques
650 _ 4 a| Deforestación
650 _ 4 a| Captura de carbono
650 _ 4 a| Análisis espacial (Estadística)
651 _ 4 a| Selva Lacandona (Chiapas, México)
700 1 _ a| De Jong, Bernardus Hendricus Jozeph
700 1 _ a| Hellier, A.
e| coaut.
700 1 _ a| Castillo Santiago, Miguel Ángel
e| coaut.
700 1 _ a| Tipper, R.
e| coaut.
773 0 _
t| Mitigation and Adaptation Strategies for Global Change
g| Vol. 10, no. 2 (2005), p. 265-278
x| 1381-2386
900 _ _ a| Solicítelo con su bibliotecario/a
902 _ _ a| AMGR/MM/GOG
904 _ _ a| Agosto 2005
905 _ _ a| Artecosur
905 _ _ a| Artfrosur
905 _ _ a| Desastres
905 _ _ a| CRIIS
905 _ _ a| Biblioelectrónica
LNG eng
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*Solicítelo con su bibliotecario/a
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 (autor)
Hellier, A. (autor)
Castillo Santiago, Miguel Ángel (autor)
Tipper, R. (autor)
Nota: Disponible para usuarios de ECOSUR con su clave de acceso
Clasificación: AR/333.75137/A6
Contenido en: Mitigation and Adaptation Strategies for Global Change. Vol. 10, no. 2 (2005), p. 265-278. ISSN: 1381-2386
Bibliotecas:
Campeche , Chetumal , San Cristóbal , Tapachula , Villahermosa
No. de sistema: 37217
Tipo: Artículo


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."

SIBE Campeche
Codigo de barra
Estado
Colección
ECO040002470
(Disponible)
Artículos de investigación ECOSUR
SIBE Chetumal
Codigo de barra
Estado
Colección
ECO030001237
(Disponible)
Artículos de investigación ECOSUR
SIBE San Cristóbal
Codigo de barra
Estado
Colección
ECO010004676
(Disponible)
Artículos de investigación ECOSUR
SIBE Tapachula
Codigo de barra
Estado
Colección
ECO020008246
(Disponible)
Artículos de investigación ECOSUR
SIBE Villahermosa
Codigo de barra
Estado
Colección
ECO050002505
(Disponible)
Artículos de investigación ECOSUR

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