Quantifying forest structural diversity based on large-scale inventory data: a new approach to support biodiversity monitoring

Abstract

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 Baden-Württemberg, 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.

Assessing the influence of harvesting intensities on structural diversity of forests in south-west Germany

“…This index ('FSI' -Forest Structure Index) combines many forest attributes that cover important habitat components of forest dwelling species; see 2.2. Results showed an increase of structural diversity (FSI-score) for most of the analysed types of forests in Baden-Württemberg (Storch et al 2018).…”

“…An additional criterion for selection of NFI plots for our analysis was the presence of merchantable trees with a diameter at breast height (DBH) larger than 7 cm at NFI 2002 . The selected plots were distributed over the whole state of Baden-Württemberg and included 97.7% of all sampled plots in NFI 2002 (Storch et al 2018). Further information about the inventory (systematic grid, sampling design and background of this inventory) can be found at BMEL (2013) (https://www.bundeswaldinventur.de).…”

“…Based on data of NFI 2002 and NFI 2012 for the state of Baden-Württemberg, an index to assess the level of structural diversity of forests was developed (Storch et al 2018) following the approach described by McElhinny et al (2006b) and modifications suggested by Sabatini et al (2015). Eleven variables, each representing different aspects of structural diversity, were applied to calculate the FSI in a simple additive way, without weightings of individual variables (Storch et al 2018). These variables representing important habitat components, comprising the presence of standing and downed deadwood, different decay classes, the occurrence of large living trees, species richness of trees in the stand and the regeneration layer, quadratic mean diameter at breast height (DBH), standard deviation of DBH and stand height, as well as the diversity of bark types and flowering trees.…”

“…Here, we used harvesting intensity calculated on the basis of NFI data as the main predictor variable to analyse changes in structural diversity of forests over large areas. Based on data of the German National Forest Inventory for the state of Baden-Württemberg (SW-Germany, NFI 2002 and NFI 2012 ), an index has been developed to assess the level of structural diversity of forests comprehensively (Storch et al 2018). This index ('FSI' -Forest Structure Index) combines many forest attributes that cover important habitat components of forest dwelling species; see 2.2.…”

Understory vegetation in planted pine forests governs bird community composition and diversity in the eastern Mediterranean region

“…Thus, forest biodiversity is important to support human existence and well-being (Osem et al 2014). Indeed, the first priority of forest management policy in Israel nowadays is to offer recreational and outdoor activity (Osem et al 2014;Storch et al 2018). However, forest ecosystems worldwide provide many additional services, including conservation, supply of wood, improving soil quality (Fox 2000) and air quality (through air filtration), rainwater drainage (Bolund and Hunhammar 1999), climate regulation, carbon storage and natural pest control (for example, by providing night shelter for insectivorous birds) (Nasi et al 2002).…”