Spatially explicit database of tree related microhabitats (TreMs)

Daniel Kraus1, Andreas Schuck2, Peter Bebi3, Markus Blaschke4, Rita Bütler3, Martin Flade5, Wilfried Heintz6, Frank Krumm3, Thibault Lachat7, Laurent Larrieu8, Lenka Lehnerova9, Martin Levin10, Ulrich Mergner11, Maciej Pach12, Yoan Paillet8, Patrick Pyttel13, Tomas Rydkvist14, Giovanni Santopuoli15, Kristina Sever16, Knut Sturm17, Kris Vandekerkhove18, Susanne Winter19, Manfred Witz20, Martin Winnock21, Matteo Marcandella22, Isabelle Roth23, Armin Jakob24, Reiner Dickele25, Gerhard Hofmann26, Dirk Ruis-Eckhardt27, Stephan Boschen28, Uwe Schölmerich29, Bertram Leder30, Martin Guericke31, Hubert Merkel32, Dagmar Löffler33, Stephan Schusser34, Monika Runkel35, Alexandra Steinmetz36, Karl Heinz Marx37, Andre Mongelluzzi38, Florian Wilshusen39, Jean-Jacques Boutteaux40, Loic Duchamp41, Nicolas Dericbourg42, Emmanuel Rouyer43, Valeria Csikos44, Ken Sweeny45, Daniel Steichen46, Michel Leytem46, Stefan Konczal47, Krzysztof Stereńczak48, Marko Kazimirovic49, Vladimír Šebeň50, Teresa Baiges Zapater51, Marieke van der Maaten-Theunissen52, Andreas Pommer53, Thomas Nord-Larsen54, Marc Fuhr8, Luc-Olivier Delebeque55, Lidón Martínez Navarro56, David Lasala57, S.M. Waez-Mousavi58, Kiomars Sefidi59, Begoña Abellanas60, Wilfried Heintz8, Sergey Zudin61, Wilfried Heintz62

1 Bavarian State Forest Enterprise Neureichenau, , Germany; 2 European Forest Institute, , Germany; 3 Swiss Federal Institute for Forest, Snow and Landscape Research, , Switzerland; 4 Bayerische Landesanstalt für Wald und Forstwirtschaft, , Germany; 5 Landesamt für Umwelt Brandenburg, , Germany; 6 INRAE, 31326, Castanet-Tolosan, France; 7 Bern University of Applied Sciences, School of Agricultural, Forest and Food Sciences, , Switzerland; 8 INRAE, , France; 9 Ústav pro hospodářskou úpravu lesů, Brandýs nad Labem, , Czechia; 10 City Forest of Göttingen, , Germany; 11 Bavarian State Forest Enterprise Ebrach, , Germany; 12 Department of Silviculture, University of Agriculture, , Poland; 13 Chair of Silviculture, University of Freiburg, , Germany; 14 SCA SKOG AB, , Sweden; 15 Università degli Studi del Molise, , Italy; 16 Slovenia Forestry Institute, , Slovenia; 17 City Forest of Lübeck, , Germany; 18 Research Institute for Nature and Forest, , Belgium; 19 WWF World Wide Fund for Nature Germany, , Germany; 20 Landesforsten Rheinland-Pfalz, , Germany; 21 Inverde, , Belgium; 22 Haute École Provinciale de Hainaut - Condorcet, , Belgium; 23 Stiftung Wildnispark Zürich, , Switzerland; 24 Regierungspräsidium Freiburg, , Germany; 25 Forest District Kandern, , Germany; 26 Forest District Wachenroth, , Germany; 27 City Forest Bensheim, , Germany; 28 Gut Hohenhaus – Gutsverwaltung, , Germany; 29 Wald und Holz NRW - State Forest Enterprise Rhein-Sieg-Erft, , Germany; 30 Wald und Holz NRW – SP Waldbau und Forstvermehrungsgut; Lehr- und Versuchsforstamt Arnsberger Wald, , Germany; 31 Eberswalde University for Sustainable Development, , Germany; 32 Hochschule für Angewandte Wissenschaft und Kunst - Fakultät Ressourcenmanagement, , Germany; 33 HessenForst, Forstamt Wolfhagen, ; 34 Sachsenforst -  Forest District Eibenstock, , Germany; 35 WaldRLP - Forstamt Hachenburg Forstliches Bildungszentrum Rheinland Pfalz, , Germany; 36 Saarforst Landesbetrieb, , Germany; 37 Forest District Tegel, Berlin, , Germany; 38 Amt für Ernährung, Landwirtschaft und Forsten Fürth, , Germany; 39 Forest District Office Hofbieber, , Germany; 40 Unité territoriale d' Auberive, , France; 41 Parc naturel régional des Vosges du Nord, , France; 42 Office national des forêts, , France; 43 Centre Regional Occitante (CNPF) / Centre National de la Propriete Forestiere (CRPF), , France; 44 Bükki Nemzeti Park Igazgatóság / Bukk National Park, , Hungary; 45 Coillte, , Ireland; 46 Le Gouvernement du Grand-Duché de Luxembourg, Ministère de l’Environnement, du Climat et du Développement durable - Administration de la nature et des forêts, , Luxembourg; 47 General Directorate of the State Forests, Nadlesnictwo Woziwoda, , Poland; 48 Instytut Badawczy Leśnictwa, , Poland; 49 University of Belgrade, Faculty of Forestry, , Serbia; 50 National Forest Centre, , Slovakia; 51 Centre de la Propietat Forestal - Departament d'Agricultura, Ramaderia, Pesca i Alimentació, , Spain; 52 Technische Universität Dresden, , Germany; 53 Sachsenforst - Forest District Eibenstock, , Germany; 54 IGN, University of Copenhagen, , Denmark; 55 Centre Regional Occitante / Centre National de la Propriete Forestiere, , France; 56 Forest Conservation and Management Service, Castilla y Leó, , Spain; 57 Agresta S. Coop, , Spain; 58 Gorgan University of Agricultural Sciences and Natural Resources, , Iran (islamic Republic Of); 59 University of Mohaghegh Ardabili, , Iran (islamic Republic Of); 60 University of Cordoba , , Spain; 61 European Forest Institute, , Finland; 62 INRAE, UMR 1201 DYNAFOR 24 Chemin de Borde-Rouge - Auzeville CS 52627, 31326, Castanet-Tolosan, France

Corresponding author(s): Daniel Kraus (daniel.kraus@baysf.de)Andreas Schuck (andreas.schuck@efi.int)Peter BebiMarkus BlaschkeRita BütlerMartin FladeWilfried Heintz (wilfried.heintz@inrae.fr)Frank KrummThibault LachatLaurent LarrieuLenka LehnerovaMartin LevinUlrich MergnerMaciej PachYoan PailletPatrick PyttelTomas RydkvistGiovanni SantopuoliKristina SeverKnut SturmKris VandekerkhoveSusanne WinterManfred WitzMartin WinnockMatteo MarcandellaIsabelle RothArmin JakobReiner DickeleGerhard HofmannDirk Ruis-EckhardtStephan BoschenUwe SchölmerichBertram LederMartin GuerickeHubert MerkelDagmar LöfflerStephan SchusserMonika RunkelAlexandra SteinmetzKarl Heinz MarxAndre MongelluzziFlorian WilshusenJean-Jacques BoutteauxLoic DuchampNicolas DericbourgEmmanuel RouyerValeria CsikosKen SweenyDaniel SteichenMichel LeytemStefan KonczalKrzysztof StereńczakMarko KazimirovicVladimír ŠebeňTeresa Baiges ZapaterMarieke van der Maaten-TheunissenAndreas PommerThomas Nord-LarsenMarc FuhrLuc-Olivier DelebequeLidón Martínez NavarroDavid LasalaS.M. Waez-MousaviKiomars SefidiBegoña Abellanas, Wilfried Heintz (wilfried.heintz@inrae.fr), Sergey Zudin

Received {date}; Revised {date}; Accepted {date}; Published {date}

Citation: Combination of authors, year of data paper publication (in parentheses), Title, Journal Name, Volume, Issue number (in parentheses), and doi of the data paper.

Resource Citation

Kraus D, Schuck A, Bebi P, Blaschke M, Bütler R, Flade M, Heintz W, Krumm F, Lachat T, Larrieu L, Lehnerova L, Levin M, Mergner U, Pach M, Paillet Y, Pyttel P, Rydkvist T, Santopuoli G, Sever K, Sturm K, Vandekerkhove K, Winter S, Witz M, Winnock M, Marcandella M, Roth I, Jakob A, Dickele R, Hofmann G, Ruis-Eckhardt D, Boschen S, Schölmerich U, Leder B, Guericke M, Merkel H, Löffler D, Schusser S, Runkel M, Steinmetz A, Marx K H, Mongelluzzi A, Wilshusen F, Boutteaux J, Duchamp L, Dericbourg N, Rouyer E, Csikos V, Sweeny K, Steichen D, Leytem M, Konczal S, Stereńczak K, Kazimirovic M, Šebeň V, Baiges Zapater T, van der Maaten-Theunissen M, Pommer A, Nord-Larsen T, Fuhr M, Delebeque L, Navarro L M, Lasala D, Waez-Mousavi S, Sefidi K, Abellanas B (2017): Spatially explicit database of tree related microhabitats (TreMs). v1.19. Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE). Dataset/Occurrence. http://dynids.toulouse.inra.fr:8180/ipt/resource?r=trems_integrate&v=1.19

Abstract

‘Tree – tree’ interactions are important structuring mechanisms for forest community dynamics. Forest management takes advantage of competition effects on tree growth by removing or retaining trees to achieve management goals. Both competition and silviculture have thus a strong effect on density and distribution of tree related microhabitats (TreMs) which are key features for forest taxa at the stand scale (e.g. Bouget et al. 2013, 2014). In particular, spatially explicit data to understand patterns and mechanisms of TreM formation in forest stands are rare. To train and eventually improve decision making capacities related to the integration of biodiversity aspects into forest management to date more than 100 usually 1 ha (100 m x 100m) permanent plots were established in different forest communities of Europe. Due to their demonstration character the selection of plots was non-systematic. They do, however, cover a broad range of forest types (e.g. beech-oak, beech-fir (-spruce), oak-hornbeam, pine-spruce, etc.), altitudinal gradients (from 25 m – 1850 m) and site conditions (e.g. oligotrophic Luzulo-Fagetum or Vaccinio-Pinetum to mesotrophic Galio-Fagetum or Milio-Fagetum). For each plot the following data is collected: (1) tree location as polar coordinates (stem base map), (2) tree species, (3) forest mensuration data (dbh in [cm], tree height in [m]), (4) tree related microhabitats (TreMs) and (5) tree status (living or standing dead). In addition to the spatial dendrometric data we provide information on plot establishment, forest type, plot location (state, region, country), elevation, means for annual precipitation and temperature, and the natural forest community (Kraus et al., 2018).

Keywords: Forest ecosystem, spatially explicit, demonstration plots, tree species, tree related microhabitat occurrences, taxonomic biodiversity, saproxylic, Occurrence, Observation

General description

Purpose: The demonstration plots to date were/are being established in the course of the projects Integrate+, Informar and FoReSite. Focus is given on showing good practice examples of integrative forest management concepts. The plots are designed following the marteloscope approach which allows to perform virtual tree selection exercises based on different scenarios and forest management strategies. Immediate feedback on decisions is given in terms of ecological and economic impacts with the help of a software that runs on hand held devises. Particular attention is given to tree related microhabitats as these structures are home to many, also endangered species. Retaining and restoring such habitats in managed forests can be well integrated into the work portfolio of forest managers and thus be a direct contribution to biodiversity conservation in managed forests. TreM recording and the development of the tree microhabitat field catalogue aims at providing individual habitat values for each tree to make harvesting impacts visible in the course of training exercises (Krumm et al, 2019). The plots and the corresponding data themselves proved also a valuable resource for different research questions. In particular, the database with the spatially explicit information on trees and TreMs can support e.g. our understanding of TreM formation and development and their spatial distribution.
Additional information: The  first version of the database was compiled and published in 2017 by the European Forest Institute in the course of the Integrate+ project (2013-2017; supported by the German Federal Ministry for Food and Agriculture). The database contained at the time 15191 records. 
The second, updated version of the database was compiled and published in 2020 in the course of the FoReSite project (2020-2022; supported by the German Federal Ministry for Food and Agriculture) by the European Forest Institute in its role as secretariat for the European Integrate network (https://integratenetwork.org/). The database now contains 42078 records.

Project details

Project title: Project 'Establishing a European network of demonstration sites for the integration of biodiversity conservation into forest management (Integrate+)',  Project 'Integrated forest management learning architecture (Informar)' and 'Managing forests for resilience and biodiversity – bridging policy, practice, science and education (FoReSite)'
Personnel: Andreas Schuck, Daniel Kraus, Sergey Zudin, Frank Krumm
Funding: The projects 'Integrate+', 'Informar' and 'FoReSite' were/are supported by the German Federal Ministry of Food and Agriculture (BMEL).
Study area descriptions/descriptor: Study Area: European Union countries and wider Europe; open to countries outside Europe 
Design description: See sampling methods

Data published through GBIF: http://dynids.toulouse.inra.fr:8180/ipt/resource?r=trems_integrate

Taxonomic coverage

General taxonomic coverage description: Included are all tree species that occurred at least once in any of the plots.
Taxonomic ranks
Species: Fagus sylvatica, Fagus orientalis, Quercus robur, Quercus petraea, Quercus pubescens, Quercus rubra, Picea abies, Pinus sylvatica, Pinus nigra, Pinus cembra, Pinus mugo, Abies alba, Acer platanoides, Acer pseudoplatanus, Acer campestre, Fraxinus excelsior, Carpinus betulus, Tilia cordata, Tilia platyphylla, Ulmus glabra, Larix decidua, Betula pendula, Betula pubescens, Populus tremula, Prunus avium, Prunus padus, Alnus glutinosa, Sorbus torminalis, Sorbus domestica, Sorbus aucuparia, Sorbus aria, Taxus baccata, Salix caprea, Corylus avellana, Pseudotsuga menziesii, Quercus cerris, Acer opalus, Acer lobelii, Ulmus minor, Ulmus laevis, Crateagus monogyna, Prunus serotina, Abies grandis, Acer tataricum, Aesculus hippocastanum, Alnus incana, Castanea sativa, Cornus mas, Corylus maxima, Frangula alnus, Fraxinus ornus, Ilex aquifolium, Juglans regia, Larix kaempferi, Malus sylvestris, Ostrya carpinifolia, Paulownia tomentosa, Picea sitchensis, Pinus strobus, Prunus spinosa, Quercus faginea, Quercus frainetto, Robinia pseudoacacia, Sambucus nigra, Tilia tomentosa, Tsuga heterophylla, Ulmus canescens, Acer cappadocicum , Acer velutinum, Aextoxicon punctatum, Alnus subcordata, Amomyrtus luma, Araucaria araucana, Caldcluvia paniculata, Diospyros lotus, Eucryphia cordifolia, Gevuina avellana, Juniperus oxycedrus, Laureliopsis philippiana, Laurelia sempervirens, Nothofagus alpina, Nothofagus dombeyi, Parrotia persica, Persea lingue, Pinus pinaster, Podocarpus nubigena, Quercus castaneifolia, Quercus ilex, Tilia begonifolia, Weinmannia trichosperma
Common names: Common beech, Oriental beech, Pedunculate oak, Sessile oak, Downy oak, Champion oak, Norway spruce, Scots pine, Black pine, Swiss stone pine, Swiss mountain pine, Silver fir, Norway maple, Sycamore maple, Field maple, Common ash, Hornbeam, Small-leaved lime, Large-leaved lime, Scots elm, European larch, Silver birch, Downy birch, Common aspen, Wild cherry, Bird cherry, Common alder, Wild service tree, True service tree, Rowan, Common whitebeam, European yew, Goat willow, Common hazel, Douglas fir, Turkey oak, Italian maple, Lobel's maple, Field elm, European white elm, Common hawthorn, Black cherry, Grand fir, Tatar maple, Horse chestnut, Grey alder, Sweet chestnut, Cornelian cherry, Large filbert, Alder buckthorn, Manna ash, Holly, Common walnut, Japanese larch, European crab apple, European hop-hornbeam, Princess tree, Sitka spruce, Eastern white pine, Blackthorn, Portuguese oak, Hungarian oak, Black locust, Black elder, Silver lime, Western hemlock, Grey elm, Cappadocian maple, Persian maple, Olivillo, Caucasian alder, Luma, Monkey puzzle tree / Chilean pine, Tiaca, Caucasian persimmon, Ulmo, Chilean hazelnut, Cade juniper, Tepa, Peruvian nutmeg, Raulí beech, Dombey's beech, Persian ironwood, n.a., Maritime pine, n.a., Chestnut-leaved oak, Holm oak, n.a., Tineo

Spatial coverage

General spatial coverage: Europe: Belgium, Bosnia and Herzegovina, Czech Republic, Denmark, France, Germany, Hungary, Ireland, Italy, Luxembourg, Poland, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland. The network of marteloscopes continues to grow due to an ongoing interest of institutions from Europe but also other world regions. A few plots in this database are located in Chile and Iran.
Coordinates: 30°45'3,6''S and 69°21'36''N Latitude; 72°4'12''W and 57°18'18''E Longitude 

Temporal coverage: 1 mars 2014 - 1 décembre 2020

Natural collections description

Collection name: Spatially explicit database of tree related microhabitats (TreMs), 2020.

Methods

Method step description: Plot selection: The permanent plots are selected non-systematically based on criteria, such as representative silvicultural systems for a region, accessibility or the availability of TreMs. Further plot selection was limited also by availability of forest stands which could ensure that tree removals would not take place within the next 5 to 10 years.

Plot establishment: The plots are usually 1 hectare in size (100 m x 100 m) and of rectangular shape. Some of them, however, deviate in size and outline due to local site conditions, availability of resources or high tree numbers. Our standard approach is to divide the plot into 4 quadrants to facilitate orientation and the use of data subsets. All corners and centre points (incl. the centre points of each quadrant) are permanently marked. All trees with more than 7 cm diameter measured at breast height (dbh 1.30 m) are recorded and numbered.

Data collection: All standing living and dead trees are recorded above a dbh of 7 cm. So is the species, spatial position, tree height and crown base height and the abundance of TreMs. Height measurements can e.g. be conducted with a digital hypsometer (VERTEX IV, Haglöf, Sweden), dbh usually with a measuring tape. Tree locations are determined e.g. by using a compass and the distance function of the Vertex digital hypsometer as a standard. In some plots the measurements were/are carried out using a specialized inventory software (Fieldmap, Czech Republic). In other plots tree coordinates were recorded using a GPS Trimble Geo7x. Note that a few trees with a dbh above 7 cm miss coordinates. They are still made available in this dataset to ensure completeness of all trees in the plots. Coordinates for those trees are labelled N/A. TreM recording in the field is based on the catalogue of tree microhabitats (see also quality control).
Study extent description: Plots were established based on interest to participate resulting in now more than 100 plots. They are mainly located in public and community forests, but also in forests owned by the church or private owners. They were selected by the forest owners based on either site availability or representing a particular forest management type (no systematic selection). Also the number of plots differs widely between countries e.g. from one to more than 35.
Sampling description: Tree location: polar coordinates
Tree species: scientific name (Note: tree species was also recorded for standing dead trees as far as possible; in the case of late decay stages or stands with a wide variety of trees species this was not done. The tree species was then recorded as “0”).
Diameter breast height (dbh): in [cm] at 1.3 meters height
Tree height: in [m]
Tree related microhabitats: 64 saproxylic and epixylic tree related microhabitat types are defined and described in detail within a hierarchical structure (published as a field guide; see: quality control for reference).
Quality control description: Set-up of Marteloscope and data collection:
Schuck, A., Krumm, F., Kraus, D., 2015. Integrate+ Marteloscopes - Description of parameters and assessment procedures. Integrate+ Technical Paper No. 18. 16 p.

Tree related microhabitat assessment field guide:
Kraus, D., Bütler, R., Krumm, F., Lachat, T., Larrieu, L., Mergner, U., Paillet, Y., Rydkvist, T., Schuck, A., and Winter, S., 2016. Catalogue of tree microhabitats – Reference field list. Integrate+ Technical Paper 13. 16 p.
The catalogue of tree microhabitats is available in 17 languages: Czech, Danish, Dutch, English, Farsi, Finnish, French, German, Hungarian, Italian, North Macedonian, Portuguese, Romanian, Slovenian, Spanish, Turkish and Ukrainian (http://iplus.efi.int/documentation.html)

Datasets

Dataset description
Object name: Darwin Core Archive Spatially explicit database of tree related microhabitats (TreMs)
Character encoding: UTF-8
Format name: Darwin Core Archive format
Format version: 1.0
Distribution: http://dynids.toulouse.inra.fr:8180/ipt/archive.do?r=trems_integrate
Publication date of data: 2021-05-05
Language: English
Licences of use: Creative Commons Attribution (CC-BY) 4.0 License

Metadata language: English
Date of metadata creation: 2017-02-08
Hierarchy level: Dataset

References
Kraus, D., Bütler, R., Krumm, F., Lachat, T., Larrieu, L., Mergner, U., Paillet, Y., Rydkvist, T., Schuck, A., and Winter, S., 2016. Catalogue of tree microhabitats – Reference field list. Integrate+ Technical Paper 13. 16 p.
Larrieu, L., Paillet, Y, Winter, S., Bütler, R., Kraus, D., Krumm, F, Lachat, T, Michel, A., Regnery, B., Vandekerkhove, K. 2018. Tree related microhabitats in temperate and Mediterranean European forests: A hierarchical typology for inventory standardization. Ecological Indicators 84: 194–207
Kraus, D., Schuck, A., Krumm, F., Bütler, R., Cosyns, H., Courbaud, B., Larrieu, L., Mergner, U., Pyttel, P., Varis, S., Wilhelm, G., Witz, M., Zenner, E. and Zudin, S., 2018. Seeing is building better understanding - the Integrate+ Marteloscopes. Integrate+ Technical Report. Marteloscopes (2018) 26:3
Krumm, F., Lachat T., Schuck, A., Bütler, R., Kraus, D., 2019. Marteloskope als Trainingstools zur Förderung und Erhaltung von Habitatbäumen im Wald. Schweizerische Z. Forstwes. 170 (2019) 2: 86-93.