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 展开更多
Background: To increase ecosystem resilience and biodiversity, the maintenance and improvement of structural and compositional diversity of forests has become an important goal in forest management for many forest own...Background: To increase ecosystem resilience and biodiversity, the maintenance and improvement of structural and compositional diversity of forests has become an important goal in forest management for many forest owners and jurisdictions. At the same time, future harvesting intensity (HI) may increase to meet the demand for woody biomass by an increasing bioeconomy sector. Yet, the influence of HI on forest structural diversity is largely unknown. Here, we address this issue by analyzing the relationship between HI and structural diversity based on large-scale national forest inventory (NFI) data, where the latter is quantified using a previously developed Forest Structure Index and HI is expressed as wood volume removal during the period 2002-2012 for the same inventory plots. Results: Our results show a surprisingly small impact of harvesting intensity on changes in structural diversity for most of the analysed types of forests. Only intense harvesting (> 80%-90% of initial growing stock) led to a significant reduction in structural diversity. At low to moderate HI most aspects of structural diversity were positively influenced. Only the quadratic mean DBH and the volume of large trees (≥ 40 cm DBH) were substantially negatively influenced at HI > 60% and 70% of initial growing stock, respectively. Conclusions: In several forest types, HI could be increased without a reduction in overall structural diversity. Hence, structural diversity in these selectively managed forests appears to be a very resistant forest property in relation to HI. Other indicators at stand and landscape scale may be needed to adjust levels of HI that are suited to maintain forest biodiversity.展开更多
Structural diversity is the key attribute of a stand. A set of biodiversity measures in ecology was introduced in forest management for describing stand structure, of which Shannon information entropy (Shannon index) ...Structural diversity is the key attribute of a stand. A set of biodiversity measures in ecology was introduced in forest management for describing stand structure, of which Shannon information entropy (Shannon index) has been the most widely used measure of species diversity. It is generally thought that tree size diversity could serve as a good proxy for height diversity. However, tree size diversity and height diversity for stand structure is not completely consistent. Stand diameter cannot reflect height information completely. Either tree size diversity or height diversity is one-dimensional information entropy measure. This paper discussed the method of multiple-dimensional information entropy measure with the concept of joint entropy. It is suggested that joint entropy is a good measure for describing overall stand structural diversity.展开更多
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
基金supported by a grant from the Ministry of Science,Research and the Arts of Baden-Württemberg(7533-10-5-78)to Jürgen Bauhussupport through the BBW For Werts Graduate Program
文摘Background: To increase ecosystem resilience and biodiversity, the maintenance and improvement of structural and compositional diversity of forests has become an important goal in forest management for many forest owners and jurisdictions. At the same time, future harvesting intensity (HI) may increase to meet the demand for woody biomass by an increasing bioeconomy sector. Yet, the influence of HI on forest structural diversity is largely unknown. Here, we address this issue by analyzing the relationship between HI and structural diversity based on large-scale national forest inventory (NFI) data, where the latter is quantified using a previously developed Forest Structure Index and HI is expressed as wood volume removal during the period 2002-2012 for the same inventory plots. Results: Our results show a surprisingly small impact of harvesting intensity on changes in structural diversity for most of the analysed types of forests. Only intense harvesting (> 80%-90% of initial growing stock) led to a significant reduction in structural diversity. At low to moderate HI most aspects of structural diversity were positively influenced. Only the quadratic mean DBH and the volume of large trees (≥ 40 cm DBH) were substantially negatively influenced at HI > 60% and 70% of initial growing stock, respectively. Conclusions: In several forest types, HI could be increased without a reduction in overall structural diversity. Hence, structural diversity in these selectively managed forests appears to be a very resistant forest property in relation to HI. Other indicators at stand and landscape scale may be needed to adjust levels of HI that are suited to maintain forest biodiversity.
基金National Natural Science Foundation of China (Grant No. 30371157)
文摘Structural diversity is the key attribute of a stand. A set of biodiversity measures in ecology was introduced in forest management for describing stand structure, of which Shannon information entropy (Shannon index) has been the most widely used measure of species diversity. It is generally thought that tree size diversity could serve as a good proxy for height diversity. However, tree size diversity and height diversity for stand structure is not completely consistent. Stand diameter cannot reflect height information completely. Either tree size diversity or height diversity is one-dimensional information entropy measure. This paper discussed the method of multiple-dimensional information entropy measure with the concept of joint entropy. It is suggested that joint entropy is a good measure for describing overall stand structural diversity.
