Background: Coarse woody debris(CWD) is very important for forest ecosystems, particularly for biodiversity and carbon storage. Its relevance as a possible reservoir and source of nutrients is less clear, especially i...Background: Coarse woody debris(CWD) is very important for forest ecosystems, particularly for biodiversity and carbon storage. Its relevance as a possible reservoir and source of nutrients is less clear, especially in central Europe.Methods: Based on a chronosequence of known ages of logs, we analyzed the nutrients stored in CWD of Fagus sylvatica, Picea abies, and Pinus sylvestris at different sites in Germany. To quantify nutrient concentrations, we assessed the use of Near Infrared Reflectance Spectroscopy(NIRS) to determine the chemical properties of CWD.Results: NIRS models were suitable to predict concentrations of C, N, P, lignin and extractives. Concentrations of most nutrients increased with mass loss, with the exception of potassium, which decreased for beech and pine and remained relatively constant for spruce. The highest nutrient concentrations(N, P, S, Ca and Mn, except Mg and K) were generally observed in highly decomposed spruce logs. The net effect of decreasing CWD mass and increasing nutrient concentrations was either a decreasing(N, P and K in beech; P, Mg, K and Mn in pine), constant(S, Ca and Mg in beech; N, S and Ca in pine) or increasing amount of nutrients(N, P, S and Ca in spruce; Mn in beech) in the logsover the course of decomposition. The C/N ratio decreased for all tree species, most markedly for spruce from ca. 1000 at the beginning of the decomposition process to 180 at 36 years. The N/P ratio converged to a value of about 30 forall three species. Lignin concentrations increased for spruce and beech and remained constant for pine.Conclusions: Our results indicate that most nutrients remain in CWD for long periods. Nutrients may be used and cycled by microorganisms within CWD, but with the exception of P(in beech), Mg(in pine) and K(in beech and pine), there appears to be little net nutrient export until two thirds of the mass is lost. Instead, N, P, S and Ca were accumulated in spruce logs, indicating that CWD became a net sink rather than a net source of some nutrients for several decades.展开更多
Background: The importance of structurally diverse forests for the conservation of biodiversity and provision of a wide range of ecosystem services has been widely recognised. However, tools to quantify structural div...Background: The importance of structurally diverse forests for the conservation of biodiversity and provision of a wide range of ecosystem services has been widely recognised. However, tools to quantify structural diversity of forests in an objective and quantitative way across many forest types and sites are still needed, for example to support biodiversity monitoring. The existing approaches to quantify forest structural diversity are based on small geographical regions or single forest types, typically using only small data sets.Results: Here we developed an index of structural diversity based on National Forest Inventory(NFI) data of BadenWurttemberg, Germany, a state with 1.3 million ha of diverse forest types in different ownerships. Based on a literature review, 11 aspects of structural diversity were identified a priori as crucially important to describe structural diversity. An initial comprehensive list of 52 variables derived from National Forest Inventory(NFI) data related to structural diversity was reduced by applying five selection criteria to arrive at one variable for each aspect of structural diversity. These variables comprise 1) quadratic mean diameter at breast height(DBH), 2) standard deviation of DBH, 3) standard deviation of stand height, 4) number of decay classes, 5) bark-diversity index, 6) trees with DBH ≥ 40 cm, 7) diversity of flowering and fructification, 8) average mean diameter of downed deadwood, 9) mean DBH of standing deadwood, 10) tree species richness and 11) tree species richness in the regeneration layer. These variables were combined into a simple,additive index to quantify the level of structural diversity, which assumes values between 0 and 1. We applied this index in an exemplary way to broad forest categories and ownerships to assess its feasibility to analyse structural diversity in large-scale forest inventories.Conclusions: The forest structure index presented here can be derived in a similar way from standard inventory variables for most other large-scale forest inventories to provide important information about biodiversity relevant forest conditions and thus provide an evidence-base for forest management and planning as well as reporting.展开更多
基金funded through a grant by the German Science Foundation(DFG-BA 2821/4-1)to J.Bauhus
文摘Background: Coarse woody debris(CWD) is very important for forest ecosystems, particularly for biodiversity and carbon storage. Its relevance as a possible reservoir and source of nutrients is less clear, especially in central Europe.Methods: Based on a chronosequence of known ages of logs, we analyzed the nutrients stored in CWD of Fagus sylvatica, Picea abies, and Pinus sylvestris at different sites in Germany. To quantify nutrient concentrations, we assessed the use of Near Infrared Reflectance Spectroscopy(NIRS) to determine the chemical properties of CWD.Results: NIRS models were suitable to predict concentrations of C, N, P, lignin and extractives. Concentrations of most nutrients increased with mass loss, with the exception of potassium, which decreased for beech and pine and remained relatively constant for spruce. The highest nutrient concentrations(N, P, S, Ca and Mn, except Mg and K) were generally observed in highly decomposed spruce logs. The net effect of decreasing CWD mass and increasing nutrient concentrations was either a decreasing(N, P and K in beech; P, Mg, K and Mn in pine), constant(S, Ca and Mg in beech; N, S and Ca in pine) or increasing amount of nutrients(N, P, S and Ca in spruce; Mn in beech) in the logsover the course of decomposition. The C/N ratio decreased for all tree species, most markedly for spruce from ca. 1000 at the beginning of the decomposition process to 180 at 36 years. The N/P ratio converged to a value of about 30 forall three species. Lignin concentrations increased for spruce and beech and remained constant for pine.Conclusions: Our results indicate that most nutrients remain in CWD for long periods. Nutrients may be used and cycled by microorganisms within CWD, but with the exception of P(in beech), Mg(in pine) and K(in beech and pine), there appears to be little net nutrient export until two thirds of the mass is lost. Instead, N, P, S and Ca were accumulated in spruce logs, indicating that CWD became a net sink rather than a net source of some nutrients for several decades.
基金supported by a grant from the Ministry of Science,Research and the Arts of Baden-Württemberg(7533-10-5-78)to Jürgen BauhusFelix Storch received additional support through the BBW ForWerts Graduate Program
文摘Background: The importance of structurally diverse forests for the conservation of biodiversity and provision of a wide range of ecosystem services has been widely recognised. However, tools to quantify structural diversity of forests in an objective and quantitative way across many forest types and sites are still needed, for example to support biodiversity monitoring. The existing approaches to quantify forest structural diversity are based on small geographical regions or single forest types, typically using only small data sets.Results: Here we developed an index of structural diversity based on National Forest Inventory(NFI) data of BadenWurttemberg, Germany, a state with 1.3 million ha of diverse forest types in different ownerships. Based on a literature review, 11 aspects of structural diversity were identified a priori as crucially important to describe structural diversity. An initial comprehensive list of 52 variables derived from National Forest Inventory(NFI) data related to structural diversity was reduced by applying five selection criteria to arrive at one variable for each aspect of structural diversity. These variables comprise 1) quadratic mean diameter at breast height(DBH), 2) standard deviation of DBH, 3) standard deviation of stand height, 4) number of decay classes, 5) bark-diversity index, 6) trees with DBH ≥ 40 cm, 7) diversity of flowering and fructification, 8) average mean diameter of downed deadwood, 9) mean DBH of standing deadwood, 10) tree species richness and 11) tree species richness in the regeneration layer. These variables were combined into a simple,additive index to quantify the level of structural diversity, which assumes values between 0 and 1. We applied this index in an exemplary way to broad forest categories and ownerships to assess its feasibility to analyse structural diversity in large-scale forest inventories.Conclusions: The forest structure index presented here can be derived in a similar way from standard inventory variables for most other large-scale forest inventories to provide important information about biodiversity relevant forest conditions and thus provide an evidence-base for forest management and planning as well as reporting.
