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Forests host most terrestrial biodiversity and their sustainable management is crucial to halt biodiversity loss. Although scientific evidence indicates that sustainable forest management (SFM) should be assessed by monitoring multi-taxon biodiversity, most current SFM criteria and indicators account only for trees or consider indirect biodiversity proxies. Several projects performed multi-taxon sampling to investigate the effects of forest management on biodiversity, but the large variability of their sampling approaches hampers the identification of general trends, and limits broad-scale inference for designing SFM. Here we address the need of common sampling protocols for forest structure and multi-taxon biodiversity to be used at broad spatial scales. We established a network of researchers involved in 41 projects on forest multi-taxon biodiversity across 13 European countries. The network data structure comprised the assessment of at least three taxa, and the measurement of forest stand structure in the same plots or stands. We mapped the sampling approaches to multi-taxon biodiversity, standing trees and deadwood, and used this overview to provide operational answers to two simple, yet crucial, questions: what to sample? How to sample? The most commonly sampled taxonomic groups are vascular plants (83% of datasets), beetles (80%), lichens (66%), birds (66%), fungi (61%), bryophytes (49%). They cover different forest structures and habitats, with a limited focus on soil, litter and forest canopy. Notwithstanding the common goal of assessing forest management effects on biodiversity, sampling approaches differed widely within and among taxonomic groups. Differences derive from sampling units (plots size, use of stand vs. plot scale), and from the focus on different substrates or functional groups of organisms. Sampling methods for standing trees and lying deadwood were relatively homogeneous and focused on volume calculations, but with a great variability in sampling units and diameter thresholds. We developed a handbook of sampling methods (SI 3) aimed at the greatest possible comparability across taxonomic groups and studies as a basis for European-wide biodiversity monitoring programs, robust understanding of biodiversity response to forest structure and management, and the identification of direct indicators of SFM., This review was funded by the EU Framework Programme Horizon 2020 through the COST Association: COST Action CA18207: BOTTOMSUP- Biodiversity Of Temperate forest Taxa Orienting Management Sustainability by Unifying Perspectives.

A comprehensive biomonitoring programme should integrate several methods distributed along the biomonitoring chain, allowing to detect exposure, threads and impacts. In the case of a municipal solid waste incinerator (MSWI), biomonitoring of air pollution can contribute to source attribution, detection of ongoing processes and assessment of environmental effects. Three different methods were used to assess the biological effects of air pollution around a MSWI using lichens as biomonitors: (1) lichen diversity; (2) bioaccumulation of trace elements; and (3) physiological status (photosynthetic efficiency, cell membrane damage, viability). The first method takes into account the native lichen flora, while the other two were applied to thalli of the lichen Evernia prunastri transplanted for 6 months in the study area. Lichen diversity and physiological parameters reflected the effects of air pollution around the incinerator and the surrounding industrial area. High frequencies of non-nitrophilous species corresponded to sites with higher environmental quality, while high frequencies of nitrophilous species corresponded to sites with higher level of eutrophication. Transplanted samples showed increased cell membrane damage and reduced vitality respect to control samples. Bioaccumulation of trace elements pointed at the atmospheric origin of Hg depositions in the area. These results suggest that an integrated use of lichen-based methods along the biomonitoring chain can provide useful biological outputs for decision-makers to establish correct sustainable waste management policies.