5 research outputs found

    Litter Fall in a Primary and Two Logged-over Lowland Tropical Rainforests in Pasirmayang, Jambi.

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    Litter accumulation in a primary and a logged-over lowland dipterocarp forest at Pasirmayang, Jambi was measured using the litter trap method. In the primary forest, traps were placed in four distinct areas, reflecting the succession stages of the forest from building to maturation. In the logged-over forest, litter production was measured at two different sites, one cut in 1979/1980 and the second in 1983/1984. In the primary forest, average litter production during the observation period was 925 g m"2yr'. In the logged-over forest, average litter production was 721 g m'2 yr1 for the site cut in 1979/1980 and 706 g m'2 yr1 for the site cut in 1983/1984. Leaves comprised the major contributor of litter with 67% of total litter produced in the primary forest, 67% of total litter in the 1979/1980 cut logged-over forest, and 65% of total litter in the 1983/1984 cut logged-over forest. The purpose of the study was to use litter fall as a measure of forest productivity to assess the recovery of logged-over forests and, to provide a basis for comparison of forest-derived land practices for appropriate forest management strategies

    Spectral and Textural Characteristics of the Lowland Tropical Rain Forest of Jambi, Sumatera

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    Analyses of Landsat TM and SPOT multispectral data were performed with a very detailed description of the vegetation cover in the field to get a relevancy and consistency of digital image classification in a semi-automatic approach. Three main vegetation types, i.e. primary forest, logged-over forest and secondary forest after clear cut were analyzed and the microclimatic parameters were also measured to describe the ecological condition of the vegetation. Spectral and textural analysis of data obtained from field measurements and spectral reflectance values of the remote sensing data are the main topic of this report as one aspect of study on the Digital Method of Detection and Monitoring on Forest Ecosystem Change Using High Resolution Satellite Data funded by the Indonesian National Research Council. This study shows that spectral reflectance values alone cannot differentiate the logged-over forest from the primary forest, but it is very sharply distinguished from the secondary forest. As for the texture analysis, it is possible to distinguish the logged-over forest from the primary forest, as shown by different values of degree of Entropy, although spatially, it is still doubtful

    LBNL-61463 Assessment Of Carbon Leakage In Multiple Carbon-Sink Projects: A Case Study In Jambi Province, Indonesia

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    Abstract. Rehabilitation of degraded forest land through implementation of carbon sink projects can increase terrestrial carbon stock. However, carbon emissions outside the project boundary, which is commonly referred to as leakage, may reduce or negate the sequestration benefits. This study assessed leakage from carbon sink projects that could potentially be implemented in the study area comprised of eleven sub-districts in the Batanghari District, Jambi Province, Sumatra, Indonesia. The study estimates the probability of a given land use/cover being converted into other uses/cover, by applying a logit model. The predictor variables were: proximity to the center of the land use area, distance to transportation channel (road or river), area of agricultural land, unemployment (number of job seekers), job opportunities, population density and income. Leakage was estimated by analyzing with and without carbon sink projects scenarios. Most of the predictors were estimated as being significant in their contribution to land use cover change. The results of the analysis show that leakage in the study area can be large enough to more than offset the project's carbon sequestration benefits during the period 2002-2012. However, leakage results are very sensitive to changes of carbon density of the land uses in the study area. By reducing C-density of lowland and hill forest by about 10% for the baseline scenario, the leakage becomes positive. Further data collection and refinement is therefore required. Nevertheless, this study has demonstrated that regional analysis is a useful approach to assess leakage
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