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

Gregory P. Asner, Sinan Sousan, David E. Knapp, Paul C. Selmants, Roberta E. Martin, R. Flint Hughes, Christian P. Giardina

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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 (R2 = 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.

Original languageEnglish (US)
Article number1
JournalCarbon Balance and Management
Volume11
Issue number1
DOIs
StatePublished - Jan 8 2016
Externally publishedYes

Fingerprint

archipelago
carbon
satellite data
monitoring
biological invasion
invasive species
data acquisition
native species
environmental change
spatial resolution
drought
canopy
land use

Keywords

  • Carbon stocks
  • Carnegie airborne observatory
  • Forest inventory
  • Invasive species
  • LiDAR
  • Random forest machine learning

ASJC Scopus subject areas

  • Global and Planetary Change
  • Management, Monitoring, Policy and Law
  • Earth and Planetary Sciences (miscellaneous)
  • Earth and Planetary Sciences(all)

Cite this

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.

In: Carbon Balance and Management, Vol. 11, No. 1, 1, 08.01.2016.

Research output: Contribution to journalArticle

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. In: Carbon Balance and Management. 2016 ; Vol. 11, No. 1.
@article{733ffe434b52483a99cb9211473aba06,
title = "Rapid forest carbon assessments of oceanic islands: A case study of the Hawaiian archipelago",
abstract = "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 (R2 = 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.",
keywords = "Carbon stocks, Carnegie airborne observatory, Forest inventory, Invasive species, LiDAR, Random forest machine learning",
author = "Asner, {Gregory P.} and Sinan Sousan and Knapp, {David E.} and Selmants, {Paul C.} and Martin, {Roberta E.} and Hughes, {R. Flint} and Giardina, {Christian P.}",
year = "2016",
month = "1",
day = "8",
doi = "10.1186/s13021-015-0043-4",
language = "English (US)",
volume = "11",
journal = "Carbon Balance and Management",
issn = "1750-0680",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Rapid forest carbon assessments of oceanic islands

T2 - A case study of the Hawaiian archipelago

AU - Asner, Gregory P.

AU - Sousan, Sinan

AU - Knapp, David E.

AU - Selmants, Paul C.

AU - Martin, Roberta E.

AU - Hughes, R. Flint

AU - Giardina, Christian P.

PY - 2016/1/8

Y1 - 2016/1/8

N2 - 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 (R2 = 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.

AB - 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 (R2 = 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.

KW - Carbon stocks

KW - Carnegie airborne observatory

KW - Forest inventory

KW - Invasive species

KW - LiDAR

KW - Random forest machine learning

UR - http://www.scopus.com/inward/record.url?scp=84953395956&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84953395956&partnerID=8YFLogxK

U2 - 10.1186/s13021-015-0043-4

DO - 10.1186/s13021-015-0043-4

M3 - Article

AN - SCOPUS:84953395956

VL - 11

JO - Carbon Balance and Management

JF - Carbon Balance and Management

SN - 1750-0680

IS - 1

M1 - 1

ER -