Quantifying understorey vegetation in the US Lake States: a proposed framework to inform regional forest carbon stocks
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Abstract
The contribution of understorey vegetation (UVEG) to forest ecosystem biomass and carbon (C) across diverse forest types has, to date, eluded quantification at regional and national scales. Efforts to quantify UVEG C have been limited to field-intensive studies or broad-scale modelling approaches lacking field measurements. Although large-scale inventories of UVEG C are not common, species- and community-level inventories of vegetation structure are available and may prove useful in quantifying UVEG C stocks. This analysis developed a general framework for estimating UVEG C stocks by employing per cent cover estimates of UVEG from a region-wide forest inventory coupled with an estimate of maximum UVEG C across the US Lake States (i.e. Michigan, Minnesota and Wisconsin). Estimates of UVEG C stocks from this approach reasonably align with expected C stocks in the study region, ranging from 0.86 ± 0.06 Mg ha-1 in red pine-dominated to 1.59 ± 0.06 Mg ha-1 for aspen/birch-dominated forest types. Although the data employed here were originally collected to assess broad-scale forest structure and diversity, this study proposes a framework for using UVEG inventories as a foundation for estimating C stocks in an often overlooked, yet important ecosystem C pool.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Quantifying understorey vegetation in the US Lake States: a proposed framework to inform regional forest carbon stocks |
| Series title | Forestry |
| DOI | 10.1093/forestry/cpu023 |
| Volume | 87 |
| Issue | 5 |
| Year Published | 2014 |
| Language | English |
| Publisher | Institute of Chartered Foresters |
| Publisher location | London, England |
| Contributing office(s) | Southwest Biological Science Center |
| Description | 10 p. |
| First page | 629 |
| Last page | 638 |
| Online Only (Y/N) | N |
| Additional Online Files (Y/N) | N |
| Google Analytic Metrics | Metrics page |