A long-scale biodiversity monitoring methodology for Spanish national forest inventory. Application to Álava region

Abstract

Aim of study: In this study, a methodology has been designed to assess biodiversity in the frame of the Spanish National Forest Inventory with the aim of evaluating the conservation status of Spanish forests and their future evolution. This methodology takes into account the different national and international initiatives together with the different types and characteristics of forests in Spain.Area of study: Álava province (Basque country, Spain). Material and methods:To analyse the contribution of each of the different indices to the biodiversity assessment, a statistical analysis using PCA multivariate techniques was performed for structure, composition and dead wood indicators.Main results: The selected biodiversity indicators (based on field measurements) are presented along with an analysis of the results from four representative forest types in Álava by way of an example of the potential of this methodology.Research highlights: The statistical analysis revealed the important information contribution of Mingling index to the composition indicators. Regarding the structure indicators, it is remarkable the interest of using standard deviations and skewness of height and diameter as indicators. Finally it is interesting to point out the interest of assessing dead saplings since they provide additional information and their volume is a particularly useful parameter for analyzing the success of regeneration.

The role of European National Forest Inventories for international forestry reporting

“…The availability of relevant forest information is essential to the decision making process undertaken by forest managers and policy makers (Alberdi et al 2014). NFIs are the primary source of forest information for most countries (Fig.…”

The Spanish National Forest Inventory: history, development, challenges and perspectives

“…Furthermore, under the auspices of Cost Action E43 in 2010, the need to harmonize forest indicators and definitions worldwide led not only to comparable estimates but also to the implementation of new field assessments, which were integrated into SNFI3 methodology. SNFI3 field work ended in 2007, and the SNFI4 started in 2008 and is currently ongoing, with field data collection and data processing work progressing simultaneously (Table 1, based on Alberdi et al, 2014). Although the primary objectives of the NFIs have changed over the years, the current aim of the Spanish NFI is to provide information at national and regional levels about the state and evolution of forests through the analysis of growing stock, carbon pools, development of forest resources, forest health, risks and forest biodiversity.…”

Tree-Level Harvest Optimization for Structure-Based Forest Management Based on the Species Mingling Index

“…However, it seems that any number of neighbors (n) can be used to develop a stand-level average species mingling index. While often used alone to help assess the diversity of forest species within a forest [11], the species mingling index has been widely used as a nearest neighbor statistic to describe the spatial structure of a forest [7,21]. The basic premise of the index, to assess whether marks of the locations of pairs of trees are within a certain distance, also informs second-order characteristics, such as the mark mingling function, which can help one determine the extent of the spatial correlation between forest characteristics, such as tree species interspersion or structural diversity [17].…”

“…Natural development of some forests in the absence of major disturbances can lead to increases in the species mingling index, and thus, the structural development of unmanaged forests might be used as a reference for planning [4]. While generally applied to live trees, the mingling concept has also been applied to the presence of snags (dead trees) in an assessment of the natural condition of forests [9] and would seem to complement other resource measurements regarding the ecological characteristics of forests [10] and to help assess forest biodiversity [11].…”