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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

Individual tree age and C stock.The relationship between mean tree C stocks (filled circles) and median (triangles) for age groups (n = 805). Error bars indicate 95% confidence interval around mean. Bars indicate number of stems in each age bin.
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pone.0138450.g004: Individual tree age and C stock.The relationship between mean tree C stocks (filled circles) and median (triangles) for age groups (n = 805). Error bars indicate 95% confidence interval around mean. Bars indicate number of stems in each age bin.

Mentions: The number of trees per ha-1 varied from 270 to 688 (Table 1), containing a total tree C stock ranging from 54.23 to 106.63 Mg C ha-1 (Fig 3). From 30 to 47% of the estimated tree C were found in the stems, while branches and needles accounted for 22 to 33% (data not shown). The fraction of root (> 2 mm) C in total tree C, 26 to 30%, reveals the importance of reporting the below ground tree compartment when presenting estimates of forest C. There was a negative correlation between mean plot dbh and stem density (r(8) = -0.96 (95% CI: -0.79, -0.99), p < 0.001), with lower stem densities in stands with higher mean stem circumference. We were unable to associate above- and below-ground tree C stock with stem density (Ca r(8) = -0.48 (-0.89, 0.34), p = 0.23, Cb r(8) = -0.57 (-0.90, 0.22), p = 0.14), and mean stand age (Ca r(8) = -0.47 (-0.89, 0.34), p = 0.24, Cb r(8) = -0.33 (-0.84, 0.49), p = 0.43). On an individual tree basis, tree age was positively correlated with both dbh (r(805) = 0.48 (0.42, 0.53), p < 0.001) and tree C (r(805) = 0.38 (0.32, 0.44) p < 0.001) (Fig 4).


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)

Individual tree age and C stock.The relationship between mean tree C stocks (filled circles) and median (triangles) for age groups (n = 805). Error bars indicate 95% confidence interval around mean. Bars indicate number of stems in each age bin.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0138450.g004: Individual tree age and C stock.The relationship between mean tree C stocks (filled circles) and median (triangles) for age groups (n = 805). Error bars indicate 95% confidence interval around mean. Bars indicate number of stems in each age bin.
Mentions: The number of trees per ha-1 varied from 270 to 688 (Table 1), containing a total tree C stock ranging from 54.23 to 106.63 Mg C ha-1 (Fig 3). From 30 to 47% of the estimated tree C were found in the stems, while branches and needles accounted for 22 to 33% (data not shown). The fraction of root (> 2 mm) C in total tree C, 26 to 30%, reveals the importance of reporting the below ground tree compartment when presenting estimates of forest C. There was a negative correlation between mean plot dbh and stem density (r(8) = -0.96 (95% CI: -0.79, -0.99), p < 0.001), with lower stem densities in stands with higher mean stem circumference. We were unable to associate above- and below-ground tree C stock with stem density (Ca r(8) = -0.48 (-0.89, 0.34), p = 0.23, Cb r(8) = -0.57 (-0.90, 0.22), p = 0.14), and mean stand age (Ca r(8) = -0.47 (-0.89, 0.34), p = 0.24, Cb r(8) = -0.33 (-0.84, 0.49), p = 0.43). On an individual tree basis, tree age was positively correlated with both dbh (r(805) = 0.48 (0.42, 0.53), p < 0.001) and tree C (r(805) = 0.38 (0.32, 0.44) p < 0.001) (Fig 4).

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