Shorea albida Sym. does not regenerate in the Badas peat swamp forest, Brunei Darussalam – An assessment using remote sensing technology

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The Badas peat swamp forest, Brunei Darussalam, Borneo, is a large Baram river peatland formation facing pressures from natural and increasingly anthropogenic disturbances. Although the peat forest should regenerate naturally after disturbances, there is little quantitative information documenting this regeneration. Given the impenetrability and remoteness of peatland forests, remote sensing technology can fill the peatland forest regeneration knowledge gap. This paper reports on the findings of a study on the resilience of the Badas peat swamp forest, composed primarily of Shorea albida Sym. We identified the scars caused by logging and caterpillar infestation using photo interpretation and the forest inventory map. We employed the Shuttle Radar Topography Mission (SRTM), TanDEM-X 90 m (TDX) digital elevation products, and AW3D30 m (AW) digital surface model (DSM) to assess the regeneration of disturbed forest scars over 14 years. Through measurements of forest height and other indices, we found that the Badas peat swamp forest did not recover from these past disturbances and the depletion of scars progressed even further. Our findings support other authors' conclusions suggesting irrevocable degradation of Bornean peatland and peat forests. We also introduce an accuracy assessment of the forest biomass estimation relying on a comparison of DSMs and present a detailed morphology of the surface of the Badas peat dome. © 2021 The Author(s) View source
Year

2022

Secondary Title

Forest Ecology and Management

Publisher

Elsevier B.V.

Volume

504

Number

504

Pages

119816

DOI

https://doi.org/10.1016/j.foreco.2021.119816

Keyword(s)

Borneo; DEM; Disturbance; Peat swamp forest; Regeneration; Shorea albida; Peat; Photointerpretation; Reforestation; Remote sensing; Surveying; Topography; Tracking radar; Anthropogenic disturbance; Borneo; DEM; Disturbance; Peat land; Peat swamp forests; Quantitative information; Regeneration; Remote sensing technology; Shorea albidum; Wetlands; accuracy assessment; assessment method; biomass; caterpillar; forest inventory; remote sensing; Shuttle Radar Topography Mission; swamp forest; TanDEM-X; Borneo; Peat; Reforestation; Remote Sensing; Surveying; Topography; Borneo; Brunei Darussalam; Shorea

Classification
Form: Journal Article
Geographical Area: Brunei Darussalam

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