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Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

Rosso A, Neitlich P, Smith RJ - PLoS ONE (2014)

Bottom Line: We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples.We also found that the point count method provided little to no improvement over ocular methods, despite increased effort.We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

View Article: PubMed Central - PubMed

Affiliation: National Park Service, Winthrop, Washington, United States of America.

ABSTRACT
Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

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Biomass-volume relations and bulk density distributions for dominant forage lichen taxa in northwestern Alaska.Regressions were fitted using either single-taxon sampling (top two rows) or multi-taxa samples (bottom two rows). Lines indicate fitted model slopes (see Table 2 for estimates), while grey polygons indicate 95% confidence intervals. In the bottom panel, the distribution of estimated bulk density (all methods, grey boxes) for 144 lichen samples from northwestern Alaska is shown, where dark bars in boxes are median values, boxes represent the interquartile range of data values, and whiskers are the maxima/minima within each group. Mean bulk density differs among all species groups (F-test p<0.0001) except the pairwise comparisons among Bryoria – Cetraria and Cladonia – C. stellaris (for all others, p<0.05 or less from Tukey HSD test).
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pone-0103739-g003: Biomass-volume relations and bulk density distributions for dominant forage lichen taxa in northwestern Alaska.Regressions were fitted using either single-taxon sampling (top two rows) or multi-taxa samples (bottom two rows). Lines indicate fitted model slopes (see Table 2 for estimates), while grey polygons indicate 95% confidence intervals. In the bottom panel, the distribution of estimated bulk density (all methods, grey boxes) for 144 lichen samples from northwestern Alaska is shown, where dark bars in boxes are median values, boxes represent the interquartile range of data values, and whiskers are the maxima/minima within each group. Mean bulk density differs among all species groups (F-test p<0.0001) except the pairwise comparisons among Bryoria – Cetraria and Cladonia – C. stellaris (for all others, p<0.05 or less from Tukey HSD test).

Mentions: “Method” column summarizes either ocular or point count methods of estimating volume, both of these, or height only. “Slope coefficient” is in units of g cm−3 unless otherwise noted, and is a measure of lichen mat bulk density; uncertainty of each estimate is presented graphically as 95% confidence intervals in Fig. 3. “Difference” between the ocular and point count method is expressed as a proportion of the ocular method. Model goodness-of-fit was determined by likelihood-based methods: better models have values closer to zero for Bayesian Information Criterion (BIC) values and greater log-likelihood values. Log-likelihood ratios (LLR) were calculated holding ocular method as the hypothesis, therefore, more strongly negative values indicate better fit for models using the ocular method. Each LLR test was significant (p<0.0001).


Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

Rosso A, Neitlich P, Smith RJ - PLoS ONE (2014)

Biomass-volume relations and bulk density distributions for dominant forage lichen taxa in northwestern Alaska.Regressions were fitted using either single-taxon sampling (top two rows) or multi-taxa samples (bottom two rows). Lines indicate fitted model slopes (see Table 2 for estimates), while grey polygons indicate 95% confidence intervals. In the bottom panel, the distribution of estimated bulk density (all methods, grey boxes) for 144 lichen samples from northwestern Alaska is shown, where dark bars in boxes are median values, boxes represent the interquartile range of data values, and whiskers are the maxima/minima within each group. Mean bulk density differs among all species groups (F-test p<0.0001) except the pairwise comparisons among Bryoria – Cetraria and Cladonia – C. stellaris (for all others, p<0.05 or less from Tukey HSD test).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4117546&req=5

pone-0103739-g003: Biomass-volume relations and bulk density distributions for dominant forage lichen taxa in northwestern Alaska.Regressions were fitted using either single-taxon sampling (top two rows) or multi-taxa samples (bottom two rows). Lines indicate fitted model slopes (see Table 2 for estimates), while grey polygons indicate 95% confidence intervals. In the bottom panel, the distribution of estimated bulk density (all methods, grey boxes) for 144 lichen samples from northwestern Alaska is shown, where dark bars in boxes are median values, boxes represent the interquartile range of data values, and whiskers are the maxima/minima within each group. Mean bulk density differs among all species groups (F-test p<0.0001) except the pairwise comparisons among Bryoria – Cetraria and Cladonia – C. stellaris (for all others, p<0.05 or less from Tukey HSD test).
Mentions: “Method” column summarizes either ocular or point count methods of estimating volume, both of these, or height only. “Slope coefficient” is in units of g cm−3 unless otherwise noted, and is a measure of lichen mat bulk density; uncertainty of each estimate is presented graphically as 95% confidence intervals in Fig. 3. “Difference” between the ocular and point count method is expressed as a proportion of the ocular method. Model goodness-of-fit was determined by likelihood-based methods: better models have values closer to zero for Bayesian Information Criterion (BIC) values and greater log-likelihood values. Log-likelihood ratios (LLR) were calculated holding ocular method as the hypothesis, therefore, more strongly negative values indicate better fit for models using the ocular method. Each LLR test was significant (p<0.0001).

Bottom Line: We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples.We also found that the point count method provided little to no improvement over ocular methods, despite increased effort.We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

View Article: PubMed Central - PubMed

Affiliation: National Park Service, Winthrop, Washington, United States of America.

ABSTRACT
Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

Show MeSH
Related in: MedlinePlus