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Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

Kristensen T, Næsset E, Ohlson M, Bolstad PV, Kolka R - PLoS ONE (2015)

Bottom Line: We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants.Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models.Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway.

ABSTRACT
A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

No MeSH data available.


Related in: MedlinePlus

Relationship between lidar plot data and forest C compartments.Pearson’s correlation (two-tailed) of five forest C compartments and three lidar variables for the plots used in this study (n = 8). Top row show aboveground (filled circles) and belowground (filled triangles) C stocks, second row show mosses (filled squares) and field layer (filled circles) C stocks, while bottom row represent organic layer C stocks (filled triangles). Full line indicate a significant correlation (level of significance is indicated by subscript letter (a: p < 0.01, b: p < 0.05), while the dotted line show non-significant results.
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pone.0138450.g007: Relationship between lidar plot data and forest C compartments.Pearson’s correlation (two-tailed) of five forest C compartments and three lidar variables for the plots used in this study (n = 8). Top row show aboveground (filled circles) and belowground (filled triangles) C stocks, second row show mosses (filled squares) and field layer (filled circles) C stocks, while bottom row represent organic layer C stocks (filled triangles). Full line indicate a significant correlation (level of significance is indicated by subscript letter (a: p < 0.01, b: p < 0.05), while the dotted line show non-significant results.

Mentions: The observed negative association between field layer C and basal area at a plot scale was also captured by a lidar data model using canopy density, explaining 83% of the variability (Table 2, Fig 7). Adding a buffer of 2 m for the computation window did not improve the model notably, while further expansion of the canopy computation window reduced the model fit (results not shown). Other lidar metrics such as canopy height measurements did not provide any significant correlation with the field layer C stock (Fig 7). Overall, the agreement between the model and field data were good; field layer C (r(8) = 0.91 (0.61, 0.99), p = 0.001). The mean differences between the observed and modeled field layer C ranged from -0.10 to 0.08 Mg C ha-1, with a corresponding SD of the differences of 0.07 Mg C ha-1 (10.2%) for field layer C.


Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

Kristensen T, Næsset E, Ohlson M, Bolstad PV, Kolka R - PLoS ONE (2015)

Relationship between lidar plot data and forest C compartments.Pearson’s correlation (two-tailed) of five forest C compartments and three lidar variables for the plots used in this study (n = 8). Top row show aboveground (filled circles) and belowground (filled triangles) C stocks, second row show mosses (filled squares) and field layer (filled circles) C stocks, while bottom row represent organic layer C stocks (filled triangles). Full line indicate a significant correlation (level of significance is indicated by subscript letter (a: p < 0.01, b: p < 0.05), while the dotted line show non-significant results.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4591287&req=5

pone.0138450.g007: Relationship between lidar plot data and forest C compartments.Pearson’s correlation (two-tailed) of five forest C compartments and three lidar variables for the plots used in this study (n = 8). Top row show aboveground (filled circles) and belowground (filled triangles) C stocks, second row show mosses (filled squares) and field layer (filled circles) C stocks, while bottom row represent organic layer C stocks (filled triangles). Full line indicate a significant correlation (level of significance is indicated by subscript letter (a: p < 0.01, b: p < 0.05), while the dotted line show non-significant results.
Mentions: The observed negative association between field layer C and basal area at a plot scale was also captured by a lidar data model using canopy density, explaining 83% of the variability (Table 2, Fig 7). Adding a buffer of 2 m for the computation window did not improve the model notably, while further expansion of the canopy computation window reduced the model fit (results not shown). Other lidar metrics such as canopy height measurements did not provide any significant correlation with the field layer C stock (Fig 7). Overall, the agreement between the model and field data were good; field layer C (r(8) = 0.91 (0.61, 0.99), p = 0.001). The mean differences between the observed and modeled field layer C ranged from -0.10 to 0.08 Mg C ha-1, with a corresponding SD of the differences of 0.07 Mg C ha-1 (10.2%) for field layer C.

Bottom Line: We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants.Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models.Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway.

ABSTRACT
A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

No MeSH data available.


Related in: MedlinePlus