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Forests contribute to numerous ecosystem functions and services and contain a large proportion of terrestrial biodiversity, but they are being negatively impaced by anthropogenic activities. Forests that have never been clear‐cut and have old growth characteristics, termed "near‐natural," often harbor different and richer species assemblages than managed forests. Alternative management strategies may be able to balance the needs of biodiversity with the demands of forestry, but evaluation efforts are limited by the challenges of measuring biodiversity. Species richness is frequently used as a simple measure of biodiversity, but research indicates that it may not adequately capture community‐level changes. Alternatively, trait‐based measures of biodiversity may prove to be useful, but research is lacking. In this paper, we use a large dataset that includes 339 obligate saproxylic beetle species collected over a decade in the boreal region throughout southern Norway to: (1) establish if there is a difference in beetle community composition between near‐natural and managed forests; and (2) determine which measures of beetle biodiversity best indicate forest naturalness. We arranged the sites in an ordination space and tested for differences in community composition between these forest types. We also tested different measures of biodiversity to determine which were the most predictive of forest naturalness. We found a clear difference in community composition between near‐natural and managed forests. Additionally, three measures of biodiversity were most predictive of forest naturalness: proportional abundance of predators, community weighted mean (CWM) of wing length, and CWM of body roundness. The probability that a forest was near‐natural increased with the proportional abundance of predators but decreased with CWM wing length and body roundness. Although species richness was higher in near‐natural forests, the effect was not significant. Overall, our findings underscore the conservation value of near‐natural forests and highlight the potential of several measures of biodiversity for determining forest quality. [ABSTRACT FROM AUTHOR]

The Bohemian Forest represents the most extensive continuous forest landscape in central Europe. Two neighbouring national parks (NP), the Bavarian Forest NP in Germany and the Šumava NP in Czechia, protecting the most valuable part of this area have been recognized as an important site for monitoring of effect of climate change on central European biodiversity and ecosystem structure. For long time, a hydrological monitoring program in the Große Ohe headwater catchment and complex monitoring of glacial lakes recently recovering from acidification were flagships of long-term transboundary research in the Bohemian Forest. Recently published results of biodiversity research in the Bavarian Forest NP and experiences with monitoring of mires in the Šumava NP supported a necessity of multidisciplinary and transboundary research. To improve the cooperation of both national parks, optimize methodologies, and coordinate research activities in the region a new Interreg project No. 26 "Silva Gabreta Monitoring - Implementation of transboundary monitoring of biodiversity and water regime" was jointly prepared. The aims and monitoring methodologies of three main project activities are presented in this paper: (i) monitoring of forest biodiversity, (ii) monitoring of mires, and (iii) monitoring of aquatic ecosystems. In addition, we briefly present several supplementary project activities and tasks, such as modelling of mesoclimatic conditions, monitoring of effect of deicing salt, project conference and common database. As well as sampling design, methods and strategies, and brief overview of the preliminary results are mentioned. [ABSTRACT FROM AUTHOR]

This study analyzes the distribution of tree species and breeding bird species across the diverse forest habitats of Georgia, utilizing data from the U.S. Forest Inventory and Analysis (FIA) program. We investigate the quantitative relationships between tree species diversity and bird species richness at a county scale, integrating FIA data with multi-source geographic information system (GIS) data to produce detailed spatial maps. Our findings reveal significant associations between the diversity of tree species and the richness of bird species, underscoring the ecological interconnectedness of Georgia’s forest habitats. These results provide valuable insights for conservation planning and biodiversity monitoring, emphasizing the importance of maintaining diverse forest ecosystems to support varied wildlife populations. [ABSTRACT FROM AUTHOR]

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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. [ABSTRACT FROM AUTHOR]