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Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago

BACKGROUND: Spatially explicit forest carbon (C) monitoring aids conservation and climate change mitigation efforts, yet few approaches have been developed specifically for the highly heterogeneous landscapes of oceanic island chains that continue to undergo rapid and extensive forest C change. We d...

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Autores principales: Asner, Gregory P., Sousan, Sinan, Knapp, David E., Selmants, Paul C., Martin, Roberta E., Hughes, R. Flint, Giardina, Christian P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4705141/
https://www.ncbi.nlm.nih.gov/pubmed/26793270
http://dx.doi.org/10.1186/s13021-015-0043-4
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author Asner, Gregory P.
Sousan, Sinan
Knapp, David E.
Selmants, Paul C.
Martin, Roberta E.
Hughes, R. Flint
Giardina, Christian P.
author_facet Asner, Gregory P.
Sousan, Sinan
Knapp, David E.
Selmants, Paul C.
Martin, Roberta E.
Hughes, R. Flint
Giardina, Christian P.
author_sort Asner, Gregory P.
collection PubMed
description BACKGROUND: Spatially explicit forest carbon (C) monitoring aids conservation and climate change mitigation efforts, yet few approaches have been developed specifically for the highly heterogeneous landscapes of oceanic island chains that continue to undergo rapid and extensive forest C change. We developed an approach for rapid mapping of aboveground C density (ACD; units = Mg or metric tons C ha(−1)) on islands at a spatial resolution of 30 m (0.09 ha) using a combination of cost-effective airborne LiDAR data and full-coverage satellite data. We used the approach to map forest ACD across the main Hawaiian Islands, comparing C stocks within and among islands, in protected and unprotected areas, and among forests dominated by native and invasive species. RESULTS: Total forest aboveground C stock of the Hawaiian Islands was 36 Tg, and ACD distributions were extremely heterogeneous both within and across islands. Remotely sensed ACD was validated against U.S. Forest Service FIA plot inventory data (R(2) = 0.67; RMSE = 30.4 Mg C ha(−1)). Geospatial analyses indicated the critical importance of forest type and canopy cover as predictors of mapped ACD patterns. Protection status was a strong determinant of forest C stock and density, but we found complex environmentally mediated responses of forest ACD to alien plant invasion. CONCLUSIONS: A combination of one-time airborne LiDAR data acquisition and satellite monitoring provides effective forest C mapping in the highly heterogeneous landscapes of the Hawaiian Islands. Our statistical approach yielded key insights into the drivers of ACD variation, and also makes possible future assessments of C storage change, derived on a repeat basis from free satellite data, without the need for additional LiDAR data. Changes in C stocks and densities of oceanic islands can thus be continually assessed in the face of rapid environmental changes such as biological invasions, drought, fire and land use. Such forest monitoring information can be used to promote sustainable forest use and conservation on islands in the future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13021-015-0043-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-47051412016-01-18 Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago Asner, Gregory P. Sousan, Sinan Knapp, David E. Selmants, Paul C. Martin, Roberta E. Hughes, R. Flint Giardina, Christian P. Carbon Balance Manag Research BACKGROUND: Spatially explicit forest carbon (C) monitoring aids conservation and climate change mitigation efforts, yet few approaches have been developed specifically for the highly heterogeneous landscapes of oceanic island chains that continue to undergo rapid and extensive forest C change. We developed an approach for rapid mapping of aboveground C density (ACD; units = Mg or metric tons C ha(−1)) on islands at a spatial resolution of 30 m (0.09 ha) using a combination of cost-effective airborne LiDAR data and full-coverage satellite data. We used the approach to map forest ACD across the main Hawaiian Islands, comparing C stocks within and among islands, in protected and unprotected areas, and among forests dominated by native and invasive species. RESULTS: Total forest aboveground C stock of the Hawaiian Islands was 36 Tg, and ACD distributions were extremely heterogeneous both within and across islands. Remotely sensed ACD was validated against U.S. Forest Service FIA plot inventory data (R(2) = 0.67; RMSE = 30.4 Mg C ha(−1)). Geospatial analyses indicated the critical importance of forest type and canopy cover as predictors of mapped ACD patterns. Protection status was a strong determinant of forest C stock and density, but we found complex environmentally mediated responses of forest ACD to alien plant invasion. CONCLUSIONS: A combination of one-time airborne LiDAR data acquisition and satellite monitoring provides effective forest C mapping in the highly heterogeneous landscapes of the Hawaiian Islands. Our statistical approach yielded key insights into the drivers of ACD variation, and also makes possible future assessments of C storage change, derived on a repeat basis from free satellite data, without the need for additional LiDAR data. Changes in C stocks and densities of oceanic islands can thus be continually assessed in the face of rapid environmental changes such as biological invasions, drought, fire and land use. Such forest monitoring information can be used to promote sustainable forest use and conservation on islands in the future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13021-015-0043-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-01-08 /pmc/articles/PMC4705141/ /pubmed/26793270 http://dx.doi.org/10.1186/s13021-015-0043-4 Text en © Asner et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Asner, Gregory P.
Sousan, Sinan
Knapp, David E.
Selmants, Paul C.
Martin, Roberta E.
Hughes, R. Flint
Giardina, Christian P.
Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title_full Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title_fullStr Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title_full_unstemmed Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title_short Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago
title_sort rapid forest carbon assessments of oceanic islands: a case study of the hawaiian archipelago
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4705141/
https://www.ncbi.nlm.nih.gov/pubmed/26793270
http://dx.doi.org/10.1186/s13021-015-0043-4
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