A synthesis of multi-taxa management experiments to guide forest biodiversity conservation in Europe

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/ A synthesis of multi-taxa management experiments to guide forest biodiversity conservation in Europe © 2023 The Authors. Published by Elsevier B.V. Published version Tinya, Flóra; Doerfler, Inken; de Groot, Maarten; Heilman-Clausen, Jacob; Kovács, Bence; Mårell, Anders; Nordén, Björn; Aszalós, Réka; Bässler, Claus; Brazaitis, Gediminas; Burrascano, Sabina; Camprodon, Jordi; Chudomelová, Markéta; Čížek, Lukáš; D'Andrea, Ettore; Gossner, Martin; Halme, Panu; Hédl, Radim; Korboulewsky, Nathalie; Kouki, Jari; Kozel, Petr; Lõhmus, Asko; López, Rosana; Máliš, František; Martín, Juan A.; Matteucci, Giorgio; Mattioli, Walter; Mundet, Roser; Müller, Jörg; Nicolas, Manuel; Oldén, Anna; Piqué, Míriam; Preikša, Žydrūnas; Rovira Ciuró, Joan; Remm, Liina; Schall, Peter; Šebek, Pavel; Seibold, Sebastian; Simončič, Primož; Ujházy, Karol; Ujházyová, Mariana; Vild, Ondřej; Vincenot, Lucie; Weisser, Wolfgang; Ódor, Péter Tinya, F., Doerfler, I., de Groot, M., Heilman-Clausen, J., Kovács, B., Mårell, A., Nordén, B., Aszalós, R., Bässler, C., Brazaitis, G., Burrascano, S., Camprodon, J., Chudomelová, M., Čížek, L., D'Andrea, E., Gossner, M., Halme, P., Hédl, R., Korboulewsky, N., . . . Ódor, P. (2023). A synthesis of multi-taxa management experiments to guide forest biodiversity conservation in Europe. Global Ecology and Conservation, 46, Article e02553. https://doi.org/10.1016/j.gecco.2023.e02553 2023 Global Ecology and Conservation 46 (2023) e02553 Available online 23 June 2023 2351-9894/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). A synthesis of multi-taxa management experiments to guide forest biodiversity conservation in Europe Fl´ ora Tinya a , * , Inken Doerfler b , Maarten de Groot c , Jacob Heilman-Clausen d , Bence Kov´ acs a , Anders Mårell e , Bj¨ orn Nord´ en f , R´ eka Aszal´ os a , Claus B¨ assler g , Gediminas Brazaitis h , Sabina Burrascano i , Jordi Camprodon j , k , Mark´ eta Chudomelov´ a l , Luk´ aˇ s ˇ Cíˇ zek m , n , Ettore D’Andrea o , Martin Gossner p , q , Panu Halme r , Radim H´ edl l , s , Nathalie Korboulewsky e , Jari Kouki t , Petr Kozel m , n , Asko L˜ ohmus u , Rosana L´ opez v , Frantiˇ sek M´ aliˇ s w , Juan A. Martín v , Giorgio Matteucci x , Walter Mattioli y , Roser Mundet z , J¨ org Müller aa , ab , Manuel Nicolas ac , Anna Old´ en r , Míriam Piqu´ e ad , ˇ Zydr¯ unas Preikˇ sa ae , Joan Rovira Ciur´ o z , Liina Remm u , Peter Schall af , Pavel ˇ Sebek m , Sebastian Seibold ag , Primoˇ z Simonˇ ciˇ c c , Karol Ujh´ azy w , Mariana Ujh´ azyov´ a ah , Ondˇ rej Vild l , Lucie Vincenot ai , Wolfgang Weisser aj , P´ eter ´ Odor a , ak a Institute of Ecology and Botany, Centre for Ecological Research, Alkotm´ any u. 2–4, H-2163 V´ acr´ at´ ot, Hungary b Institute of Biology and Environmental Science, Vegetation Science & Nature Conservation, University of Oldenburg, Ammerl¨ ander Heerstraße 114–118, 26129 Oldenburg, Germany c Slovenian Forestry Institute, Veˇ cna pot 2, 1000 Ljubljana, Slovenia d Center for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen, Denmark e INRAE, UR EFNO, FR-45290 Nogent-sur-Vernisson, France f Norwegian Institute for Nature Research, Sognsveien 68, 0855 Oslo, Norway g Institute for Ecology, Evolution and Diversity, Conservation Biology, Faculty of Biological Sciences, Goethe University Frankfurt, Max-von-Laue-Str. 13, 60438 Frankfurt am Main, Germany h Department of Forest Sciences, Agriculture Academy, Vytautas Magnus University, Studentu g. 11, Akademija, Kaunas dist. LT-53361, Lithuania i Department of Environmental Biology, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy j Conservation Biology Group (GBiC), Forest Science and Technology Centre of Catalonia (CTFC), Crta. Sant Llorenç de Morunys, Km 2, 25280 Solsona, Spain k Department of Biosciences, University of Vic and Central University of Catalonia (UVic-UCC), Carrer de la Laura, 13, 08500 Vic, Spain l Institute of Botany, Czech Academy of Sciences, Lidick´ a 25/27, 60200 Brno, Czech Republic m Biology Centre of the Czech Academy of Sciences, Branisovska 31, CZ-37005 ˇ Cesk´ e Budˇ ejovice, Czech Republic n Faculty of Science, University of South Bohemia, Branisovska 31, CZ-37005 ˇ Cesk´ e Budˇ ejovice, Czech Republic o Research Institute on Terrestrial Ecosystems, National Research Council of Italy (CNR IRET), Viale Guglielmo Marconi, 2, 05010 Porano, TR, Italy p Forest Entomology, Swiss Federal Research Institute of Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903 Birmensdorf, Switzerland q Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zurich, Universitaetstrasse 16, 8092 Zurich, Switzerland r Department of Biological and Environmental Science, University of Jyv¨ askyl¨ a, Survontie 9C (Ambiotica), FI-40014, Finland s Department of Botany, Faculty of Science, Palacký University in Olomouc, ˇ Slechtitelů 27, 78371 Olomouc, Czech Republic t School of Forest Sciences, University of Eastern Finland, PO Box 111 (Yliopistokatu 7), 80101 Joensuu, Finland u Institute of Ecology and Earth Sciences, University of Tartu, Liivi 2, EE-50409 Tartu, Estonia v Departamento de Sistemas y Recursos Naturales, Universidad Polit´ ecnica de Madrid, C. Jos´ e Antonio Novais 10, 28040 Madrid, Spain w Faculty of Forestry, Technical University in Zvolen, T. G. Masaryka 24, SK-96001 Zvolen, Slovakia * Corresponding author. E-mail address: [email protected] (F. Tinya). Contents lists available at ScienceDirect Global Ecology and Conservation journal homepage: www.elsevier.com/locate/gecco https://doi.org/10.1016/j.gecco.2023.e02553 Received 6 March 2023; Received in revised form 2 June 2023; Accepted 21 June 2023 Global Ecology and Conservation 46 (2023) e02553 2 x Institute of BioEconomy, National Research Council of Italy (CNR-IBE), Via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy y Research Centre for Forestry and Wood, Council for Agricultural Research and Economics (CREA), Via Valle della Quistione, 27, 00166 Rome, Italy z Forestry Consortium of Catalonia, C. Jacint Verdaguer, nº 3, 17430 Santa Coloma de Farners, Spain aa University of Würzburg, Glashüttenstraße 5, 96181 Rauhenebrach, Germany ab Bavarian Forest Nationalpark, Freyunger Str. 2, 94481 Grafenau, Germany ac D´ epartement RDI, Office National des Forˆ ets, Boulevard de Constance, 77300 Fontainebleau, France ad Joint Research Unit CTFC-AGROTECNIO-CERCA, Crta. Sant Llorenç de Morunys, Km 2, 25280 Solsona, Spain ae Department of Environment and Ecology, Agriculture Academy, Vytautas Magnus University, Studentu g. 11, Akademija, Kaunas dist. LT-53361, Lithuania af Silviculture and Forest Ecology of the Temperate Zones, University of G¨ ottingen, Büsgenweg 1, D-37077 G¨ ottingen, Germany ag Ecosystem Dynamics and Forest Management Research Group, School of Life Sciences, Department of Life Science Systems, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany ah Faculty of Ecology and Environmental Sciences, Technical University in Zvolen, T. G. Masaryka 24, SK-96001 Zvolen, Slovakia ai Lab ECODIV USC INRAE 1499, Normandie Universit´ e, UNIROUEN, 76000 Rouen, France aj Terrestrial Ecology Research Group, School of Life Sciences, Department of Life Science Systems, Technical University of Munich, Hans-Carl-vonCarlowitz-Platz 2, 85354 Freising, Germany ak Institute of Environmental Protection and Nature Conservation, University of Sopron, Bajcsy-Zsilinszky u. 4, H-9400 Sopron, Hungary ARTICLE INFO Keywords: Deadwood Forestry treatment Gap cutting Microhabitat enrichment Multi-taxon Thinning ABSTRACT Most European forests are used for timber production. Given the limited extent of unmanaged (and especially primary) forests, it is essential to include commercial forests in the conservation of forest biodiversity. In order to develop ecologically sustainable forest management practices, it is important to understand the management impacts on forest-dwelling organisms. Experiments allow testing the effects of alternative management strategies, and monitoring of multiple taxa informs us on the response range across forest-dwelling organisms. To provide a representative picture of the currently available information, metadata on 28 multi-taxa forest management experiments were collected from 14 European countries. We demonstrate the potential of compiling these experiments in a single network to upscale results from the local to continental level and indicate directions for future research. Among the different forest types, temperate deciduous beech and oak-dominated forests are the best represented in the multi-taxa management experiments. Of all the experimental treatments, innovative ways of traditional management techniques (e.g., gap cutting and thinning) and conservation-oriented interventions (e.g., microhabitat enrichment) provide the best opportunity for large-scale analyses. Regarding the organism groups, woody regeneration, herbs, fungi, beetles, bryophytes, birds and lichens offer the largest potential for addressing management–biodiversity relationships at the European level. We identified knowledge gaps regarding boreal, hemiboreal and broadleaved evergreen forests, the treatments of large herbivore exclusion, prescribed burning and forest floor or water manipulations, and the monitoring of soil-dwelling organisms and some vertebrate classes, e.g., amphibians, reptiles and mammals. To improve multi-site comparisons, design of future experiments should be fitted to the set-up of the ongoing projects and standardised biodiversity sampling is suggested. However, the network described here opens the way to learn lessons on the impact on forest biodiversity of different management techniques at the continental level, and thus, supports biodiversity conservation in managed forests. 1. Introduction Forests cover 35 % of Europe’s land area and are home to a major part of Europe’s terrestrial biodiversity, whose conservation represents an increasing challenge and responsibility (European Commission, 2021). Moreover, forests are significant for the economy and society, as they provide timber and many other economically valuable goods and ecosystem services (Forest Europe, 2020). Despite the recent increase in forest cover, millennia of human land use in Europe have considerably decreased forest cover and structural and compositional heterogeneity in extant forests (Kaplan et al., 2009). Although 24 % of Europe’s forests are protected (Forest Europe, 2020), most of these are also managed for timber production. Only about 3 % of Europe’s forests (excluding Russia) retain their primary condition (FAO, 2020). Notwithstanding the indisputable value of primary forests (Bruun and Heilmann-Clausen, 2021; Schall et al., 2021), their limited area points to the crucial role of close-to-nature forest management and forest restoration in the conservation of Europe’s terrestrial biodiversity (Bauhus et al., 2013). Forest management influences the levels of biodiversity basically by changing habitat structure, habitat availability and abiotic circumstances. Hence, exploring the effects of management and the alteration of stand structure and abiotic conditions on biodiversity is essential for the elaboration of sustainable timber production that integrates conservation and economical aspects (Kraus and Krumm, 2013). Revealing these relationships is also necessary for the development of conservation-oriented forest management, which aims at increasing forest biodiversity without timber production purposes (Bauhus et al., 2013). Relying on a diverse group of taxa, rather than on single indicators has a key role in assessing the biodiversity sustainability of forest F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 3 management since it increases representativeness of the forest biota (Burrascano et al., 2018), and may help to counter the taxonomic bias in conservation research (Clark and May, 2002). Multi-taxa studies are more likely to include taxa that are highly species-rich and hold great significance for forest ecosystem functioning such as fungi and arthropods (Halme et al., 2017), or taxa with a high share of species of high conservation concern, such as saproxylic beetles (C´ alix et al., 2018) or several groups of vertebrates (EEA, 2010). Moreover, linking the diverse range of responses of multiple taxa to environmental changes sheds light on various ecosystem processes (Aubin et al., 2013). In this view, numerous multi-taxa studies have been published regarding the management effects on forest biodiversity in Europe in recent years (Seibold et al., 2015; de Groot et al., 2016; Schall et al., 2018; Lelli et al., 2019). Experiments allow for disentangling the correlating factors and isolating single effects and thus are useful tools in identifying underlying mechanisms, and multi-taxa forestry experiments are key complements to observational studies of the management–biodiversity relationships (Burrascano et al., 2020). The starting point for the present study is that there are several such experiments at the local or national levels across Europe, but no overview of these have been published yet, however, their joint analyses would allow for generalising the results of individual studies at the European scale. Such compiled evidence could help enhance the development of European-level guidelines for sustainable and conservation-oriented forest management. We aim to provide an overview of recent experimental field studies in Europe dealing with the effects of various forestry treatments on multi-taxa biodiversity. Here, we describe them by reporting on i) geographical and habitat representation; ii) broad treatment types; iii) representation of different taxonomic groups; and iv) environmental variables. We aimed to: 1) map the information from multi-taxa forestry experiments regarding forest categories, treatments and organism groups; 2) explore the potential of the existing information for addressing management-related questions at the European level; 3) identify knowledge gaps (issues not covered by the existing experiments) concerning the forest and management type and biodiversity coverage. 2. Methods 2.1. Data collection We compiled information on experiments according to the following criteria: i) experiments were established in European closed forests (i.e., pre-treatment canopy cover >40%); ii) experiments included both manipulation and control sampling units; iii) treatments comprised interventions that changed the forest structure (canopy, understory, or microhabitats) or influenced the forest floor or water conditions. Interventions could have commercial and/or conservation-oriented purposes. iv) Minimum of three replicates per treatment were applied; v) a minimum of three taxonomic groups were sampled, representing at least two of the kingdoms Plantae, Fungi and Animalia; vi) detailed information on study design, treatments, sampling protocols and coordinates of sites was available. The search for experiments followed multiple pathways. It was initiated in the framework of the BOTTOMS-UP COST Action (https://www.bottoms-up.eu/en/) involving forest ecologists from 28 European countries who searched for appropriate experiments within their network and country. Besides, we scanned the list of LIFE projects (https://ec.europa.eu/environment/life/project/ Projects/index.cfm) related to forests and searched for relevant publications on the Web of Science (https://www.webofscience. com, applied search strings: “forest”, “experiment”, “biodiversity”, “Europe”). Experiments in the metadatabase by Bernes et al. (2015) about the effect of conservation-oriented forest management on biodiversity fitting the above criteria were also incorporated. Projects that were merely in the planning stage were also included. At first, we collected detailed structured descriptions of the projects. The description forms were filled by one or several custodians associated with each experiment, providing general information about the experiment, metadata about the sites, description of the applied treatments, investigated taxa, environmental variables, functions and processes (see the blank form and instruction guide in Appendix 1). 2.2. Data standardisation and interpretation In order to make the highly heterogeneous setups of the experiments comparable, several terms were defined and applied consequently across the projects, even if it resulted in some simplifications. The lowest level of analysis, even within complex sampling procedures were defined as ‘experimental units’. ‘Blocks’ were determined as areas for replicates of the complete set of treatments. ‘Sites’ were determined as homogenous geographical areas to which discrete abiotic (topography, macroclimate and bedrock) and homogeneous stand structural parameters were assigned. Sites were delimited by the experiment custodians, and their spatial scale highly varied between the different projects, thus – contrary to the terms ‘experimental unit’, ‘number of replications’ and ‘block’ – this term could not be handled uniformly across the experiments. The experimental units and replicates of an experiment could be located in different sites or within one site. Several variables of the experiments, where standardisation was possible and meaningful, were merged into two metadata tables at the experimentand site levels separately. Since the experiments varied widely in their spatial scale and data accuracy, in many cases, only ranges were available for numerical characteristics of the sites (e.g., altitude, stand age, or canopy openness), or just the same approximate value was given for all sites. Forest compositional categories and types were defined based on the EEA classification (EEA, 2007); in many cases, more than one compositional type was assigned to a single site. We defined six main intervention categories with subcategories (hereafter ‘types’, Table 1). For cuttings, we separated types according to the approach of the canopy opening. If cutting was based on an individual tree or stem selection, we called it ‘thinning’, F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 4 while aggregated cuttings based on a defined size area were categorised as ‘gap cutting’ or ‘clearcutting’. We defined the area threshold between ‘gap cutting’ and ‘clearcutting’ as 2000 m 2 , based the separation on their potential effect on site conditions, even if the boundary between them would not be sharp (Muscolo et al., 2014). In some cases, an experiment could include more than one treatment category and/or type. The definition of organism groups was based on their taxonomic categories; however, the studied groups spanned across different taxonomic levels (family and higher). Some taxonomically identical groups were considered as two independent groups, typically ‘woody regeneration’ and ‘herbs’. Likewise, ‘Carabidae’ were often studied independently from other groups of beetles (‘Coleoptera’), thus we handled them separately. Similarly, ‘Chiroptera’ were treated separately from the other mammals (‘Mammalia’). On the other hand, taxa with ecologically similar functions were merged (Bryophyta and Marchantiophyta into ‘bryophytes’, lichenised fungi, as a paraphyletic, but morphologically and functionally well-isolable group to ‘lichens’). Our ‘Fungi’ group covers mainly macrofungi detected by the naked eye, but in some cases, it also contains a wide range of fungi determined by environmental DNA sequencing. Notwithstanding the heterogeneous ranks and the multiple exceptions, for the sake of simplicity, thereafter we call all groups ‘taxa’. In many projects, only subgroups of a given taxon were sampled. In such cases, the list of subgroups was also provided. Occasionally, these were taxonomic groups, but they often covered functional groups or groups that can be collected by special sampling methods. The nomenclature for high-rank taxonomic groups follows Roskov et al. (2019). Arthropod traps collected numerous taxa, among which only a few have been identified and analysed in a given project. However, the other collected taxa have the potential to be identified and used in the future; therefore, besides the investigated taxa, the applied collecting methods for arthropods were also listed. Figures were created in R 3.6.1. (R Development Core Team, 2019) with the package ggplot2 (Wickham, 2016). 3. Results 3.1. General description of the experiments The established network comprised 28 experiments conducted over 14 European countries (Fig. 1, Table 2), each with a comprehensive list of metadata (Appendices 2 and 3) and a detailed textual description (Appendix 4). The experiments covered not only a broad latitudinal and longitudinal range but also varied greatly in altitude (5–1850 m above sea level). Overall they covered 29 EEA forest compositional types from 12 compositional categories (EEA, 2007). Comparing the frequency of the compositional categories in the network to their total area in Europe (Barbati et al., 2014), Mesophytic deciduous forests, Beech forests and Mountainous beech forests were overrepresented among the experiments, as well as Mediterranean coniferous forests. Some relatively common compositional categories as boreal and hemiboreal forests and the other categories were underrepresented (Fig. 2). The experimental design and spatial scale of the survey were rather variable across projects, with a broad range of both in terms of number (1–89) and the area of sites (0.16–30 000 ha) per experiment. The number of experimental units varied as well (15–272, and an exception, where 1170 logs were the experimental units). The replication number of the treatments ranged from three to 90. A block design was applied in 18 out of the 28 experiments. Before-After-Control-Impact design was implemented in 25 projects, while the other three experiments had only a Control-Impact design. After-treatment data collection was heterogeneous regarding the total number of samplings and the temporal frequency of the samplings of different taxa. 3.2. Treatments Cutting was the most commonly applied experimental treatment (52 %), but microhabitat enrichment and large herbivore exclusion were also applied in several projects (26 % and 9 %, respectively) (Fig. 3). Forest floor manipulation and prescribed burning were scarce, and water manipulation was performed only in one experiment. Thinning and gap cutting were the most common cutting Table 1 The applied treatment categories and types in the collected experiments. Treatment category Category abbreviation Treatment type Type abbreviation Cutting CUT Clearcutting CC Forest-open field mosaic creation FOM Gap cutting GC Green tree retention GTR Thinning THI Undergrowth removal UGR Exclusion of large herbivores EXC Exclusion of large herbivores EXC Forest floor manipulation FLO Fertilisation FRT Litter raking LR Mechanical damage of ground layer MCH Microhabitat enrichment MH Deadwood enrichment DW Habitat tree manipulation HT Prescribed burning BUR Prescribed burning BUR Water manipulation WAT Ditch filling DF F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 5 types, while the most frequent microhabitat treatment was deadwood enrichment. The median number of treatment types within an experiment was two, ranging from one to five different treatment types. The number of temporal repetitions of the interventions varied between one and 10. 3.3. Investigated taxa Altogether a total of 29 taxa were studied in the analysed experiments (Fig. 4). The median number of taxa per experiment was seven, ranging from three to 16. Woody regeneration and herbs were studied in almost all experiments (27 and 26 cases, respectively). Fungi, Coleoptera, bryophytes, Carabidae and Aves were sampled in more than 10 experiments. In the case of Fungi, Coleoptera, Hymenoptera, Diptera, Hemiptera, Annelida and Mammalia, only various subgroups within the higher taxon were sampled in most of the experiments. In most cases, arthropods were sampled by flight interception trap (17 projects) and pitfall trap (14 projects), while soil coring was used in five cases. 3.4. Structural and environmental co-variables Stand structural data were available for all experiments although their quality and range were variable (Fig. 5). Tree diameter and species were determined in most of the experiments (in 25 projects), and data on basal area, tree height, standing or lying deadwood, Fig. 1. The location of the multi-taxa forest management experiments analysed in this study. Black dots: sites; red circles: centroids of experiments with multiple sites, or positions of experiments with only one site (labels: experiment ID reported in Table 2). Green background: forest areas (EEA and Copernicus Land Monitoring Service, 2021). F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 6 Table 2 Overview of the analysed experiments: forest compositional categories (EEA, 2007), number of replications and experimental units, treatment categories and investigated taxa. Experiment ID EEA codes Replications Experimental units Treatments Taxa EX01_CZ 5 6 36 CUT EX02_CZ 5 5 15 CUT EX03_CZ 5 15 45 FLO EX04_DE 6 various 69 MH EX05_DE 2, 5, 6, 7 29 116 CUT, MH EX06_DK 6 5 25 CUT, MH EX07_EE 11 8 64 CUT, WAT EX08_ES 10 various 272 CUT, BUR, MH EX09_ES 7 12 24 CUT, EXC EX10_ES-FR 5, 9, 10 5–14 24 CUT, MH EX11_FI 1 6–12 43 CUT EX12_FI 1 3 24 CUT, BUR, MH, EXC (continued on next page) F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 7 Table 2 (continued) Experiment ID EEA codes Replications Experimental units Treatments Taxa EX13_DE 7 5 190 CUT, MH EX14_FR 2, 3, 5, 6, 7, 10, 14 89 178 EXC EX15_FR 6 3 33 CUT, EXC EX16_HU 5 6 36 CUT EX17_HU 5 6 30 CUT, EXC EX18_HU 5, 8 8–14 22 CUT, MH EX19_IT 3, 6, 7, 8 3–11 49 CUT, MH EX20_IT 7 various 33 CUT, MH, EXC EX21_LT 1, 2 NA 70 CUT, FLO, MH, BUR EX22_SW 2 25 50 CUT EX23_SW-NO 2 26 52 CUT EX24_SI 7 9 27 CUT (continued on next page) F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 8 Table 2 (continued) Experiment ID EEA codes Replications Experimental units Treatments Taxa EX25_SK 5 5 40 CUT, FLO EX26_DE 2, 6, 7 90 1170 MH EX27_CZ 4 10 20 CUT EX28_DE 6 8 72 CUT, MH Experiment ID: identification number of the experiment and the code of the country. EEA codes: 1. Boreal forest, 2. Hemiboreal forest and nemoral coniferous and mixed broadleaved-coniferous forest, 3. Alpine coniferous forest, 4. Acidophilous oak forest, 5. Mesophytic deciduous forest, 6. Beech forest, 7. Mountainous beech forest, 8. Thermophilous deciduous forest, 9. Broadleaved evergreen forest, 10. Coniferous forest of the Mediterranean, Anatolian and Macaronesian regions, 11. Mire and swamp forest, 14. Plantations and self-sown exotic forests. Treatments: BUR =prescribed burning, CUT =cutting, EXC =exclusion of large herbivores, FLO =forest floor manipulation, MH =microhabitat enrichment, WAT =water manipulation. Taxa: Acari, Amphibia, Annelida, Araneae, Aves, Bacteria, Bryophyta, Carabidae, Chiroptera, Collembola, 9Coleoptera (except Carabidae), Diptera, Fungi, Herbivorous insects, Hemiptera, Herbs, Hymenoptera, Isopoda, Lepidoptera, Lichens, Mammalia (except Chiroptera), Mollusca, Myriapoda, Nematoda, Neuroptera, Protista, Pseudoscorpiones, Reptilia, Woody regeneration. Fig. 2. Frequency of the experiments according to forest compositional categories (EEA, 2007), compared to the respective share of the area of these categories in Europe. One experiment may contain forests of multiple categories. F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 15 experiments (Fig. 7). More representation of boreal and Mediterranean broadleaved forests would increase the spatial representativeness of the results and our knowledge about the management effects on biodiversity. Zonal forests are usually well studied, while the – primarily water-determined – edaphic forests are less known with knowledge gaps. Despite the lower conservation value of plantations, their high contribution in terms of the total area in Europe urges their more intensive investigation. Tree cuttings – which usually have economical relevance – are well studied. However, forest management and conservation also operate with other interventions like prescribed burning, forest floor or water manipulation. The effects of these interventions are relatively less explored and thus more evidence is essential to formulate best practices. Large herbivore exclusion is widely applied in large areas and for the long term, thus it would be especially relevant to understand its effect not only on the well-studied understory but also on other components of forest biodiversity. Soil-dwelling organisms are extremely species-rich components of forest ecosystems, with important ecological functions such as decomposition. To better assess the management effects on these processes, the inclusion of soil organisms in experiments is highly recommended. In the same context, Diptera and Hymenoptera are rarely studied species-rich groups, because of their complex identification. However, metabarcoding may facilitate their inclusion in experiments in the future. Amphibians, reptiles and mammals, as characteristic vertebrate elements of forest biota, also constitute knowledge gaps. We think that the current overview would promote fitting the design of future experiments to the set-up of these projects and using standardised biodiversity sampling (see Burrascano et al., 2021) to enable multi-site comparisons and generalisation of results on a transregional scale. CRediT authorship contribution statement Fl´ ora Tinya: Conceptualization, Methodology, Formal analysis, Writing – original draft, Data curation, Writing – review & editing. Inken Doerfler: Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Maarten de Groot: Formal analysis, Data curation, Writing - original draft, Writing - review & editing. Jacob Heilman-Clausen: Formal analysis, Data curation, Writing – review & editing. Bence Kov´ acs: Conceptualization, Methodology, Visualization, Data curation, Writing – review & editing. Anders Mårell: Formal analysis, Writing – original draft, Data curation, Writing – review & editing. Bj¨ orn Nord´ en: Formal analysis, Data curation, Writing – review & editing. R´ eka Aszal´ os: Data curation, Writing – review & editing. Claus B¨ assler: Data curation, Writing – review & editing. Gediminas Brazaitis: Data curation, Writing – review & editing. Sabina Burrascano: Data curation, Writing – review & editing. Jordi Camprodon: Data curation, Writing – review & editing. Mark´ eta Chudomelov´ a: Data curation, Writing – review & editing. Luk´ aˇ s ˇ Cíˇ zek: Data curation, Writing – review & editing. Ettore D’Andrea: Data curation, Writing – review & editing. Martin Gossner: Data curation, Writing – review & editing. Panu Halme: Data curation, Writing – review & editing. Radim H´ edl: Data curation, Writing – review & editing. Nathalie Korboulewsky: Data curation, Writing – review & editing. Jari Kouki: Data curation, Writing – review & editing. Petr Kozel: Data curation, Writing – review & editing. Asko L˜ ohmus: Data curation, Writing – review & editing. Rosa Ana L´ opez Rodríguez: Data curation, Writing – review & editing. Frantiˇ sek M´ aliˇ s: Data curation, Writing – review & editing. Juan A. Martín: Data curation, Writing – review & editing. Giorgio Matteucci: Data curation, Writing – review & editing. Walter Mattioli: Data curation, Writing – review & editing. Roser Mundet: Data curation, Writing – review & editing. J¨ org Müller: Data curation, Writing – review & editing. Manuel Nicolas: Data curation, Writing – review & editing. Anna Old´ en: Data curation, Writing – review & editing. Míriam Piqu´ e: Data curation, Writing – review & editing. ˇ Zydr¯ unas Preikˇ sa: Data curation, Writing – review & editing. Joan Rovira Ciur´ o: Data curation, Writing – review & editing. Liina Remm: Data curation, Writing – review & editing. Peter Schall: Data curation, Writing – review & editing. Pavel ˇ Sebek: Data curation, Writing – review & editing. Sebastian Seibold: Data curation, Writing – review & editing. Primoˇ z Simonˇ ciˇ c: Data curation, Writing – review & editing. Karol Ujh´ azy: Data curation, Writing – review & editing. Mariana Ujh´ azyov´ a: Data curation, Writing – review & editing. Ondˇ rej Vild: Data curation, Writing – review & editing. Lucie Vincenot: Data curation, Writing – review & editing. Wolfgang Weisser: Data curation, Writing – review & editing. P´ eter ´ Odor: Conceptualization, Methodology, Writing – original draft, Data curation, Writing – review & editing. Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Sabina Burrascano reports financial support was provided by EU Framework Programme Horizon 2020. Fl´ ora Tinya reports financial support was provided by National Research, Development and Innovation Fund of Hungary. Fl´ ora Tinya reports financial support was provided by Hungarian Academy of Sciences. Mark´ eta Chudomelov´ a, Radim H´ edl, Ondˇ rej Vild reports financial support was provided by Czech Academy of Sciences. Frantiˇ sek M´ aliˇ s, Karol Ujh´ azy, Mariana Ujh´ azyov´ a reports financial support was provided by Slovak Research and Development Agency. Data Availability No data was used for the research described in the article. Acknowledgements This review was funded by the EU Framework Programme Horizon 2020 through the COST Association (www.cost.eu): COST F. Tinya et al. Global Ecology and Conservation 46 (2023) e02553 16 Action CA18207: BOTTOMS-UP – Biodiversity Of Temperate forest Taxa Orienting Management Sustainability by Unifying Perspectives. The authors are thankful to all experts contributing to the experiments here reviewed. F.T. was supported by the National Research, Development and Innovation Fund of Hungary (NKFIA PD134302) and by the J´ anos Bolyai Research Scholarship of the Hungarian Academy of Sciences. M.C., R.H. and O.V. were funded by the Czech Academy of Sciences (Nr RVO 67985939). F.M., K.U. and M.U. were supported by Slovak Research and Development Agency under Grant APVV-19-0319. Appendix A. Supporting information Supplementary data associated with this article can be found in the online version at doi:10.1016/j.gecco.2023.e02553. 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