Handbook of field sampling for multi-taxon biodiversity studies in European forests
Abstract
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 the diversity of multiple taxonomic groups, 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 their heterogeneous sampling approaches hamper broad-scale inference for designing SFM. The COST Action BOTTOMS-UP (CA18207) addressed the need of common sampling protocols for European forest structure and multi-taxon biodiversity. We established a network of researchers involved in 41 projects on European forest multi-taxon biodiversity across 13 European countries. These projects comprised the assessment of at least three taxonomic groups, 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? Here we comprehensively address these questions for nine different taxonomic groups and for the sampling of standing trees and lying deadwood. For each of these forest components, we provide two standards that differ in spatial scale and effort. Both standards were specifically designed towards the greatest possible comparability across taxonomic groups and studies. This handbook represents a pragmatic synthesis and an important step forward to direct monitoring of forest biodiversity, in Europe and elsewhere. It gives the state of the art to build on in the future: it derives from an effort of networking and synthesis aimed at defining standard approaches for forest monitoring to ensure sampling robustness and comparability. We are certain it can contribute to more efficient monitoring of biodiversity response to forest management.