# Tree-related microhabitat assemblages in boreal forests depend more on local environmental conditions and tree species than on tree size

Rita Bütler, Laurent Larrieu, Maxence Martin

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Rita Bütler, Laurent Larrieu, Maxence Martin. Tree-related microhabitat assemblages in boreal forests depend more on local environmental conditions and tree species than on tree size. Scandinavian Journal of Forest Research, 2025, pp.1-11. 10.1080/02827581.2025.2497364. hal-05074915

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# Tree-related microhabitat assemblages in boreal forests depend more on local environmental conditions and tree species than on tree size

Rita Bütler, Laurent Larrieu & Maxence Martin

**To cite this article:** Rita Bütler, Laurent Larrieu & Maxence Martin (30 Apr 2025): Tree-related microhabitat assemblages in boreal forests depend more on local environmental conditions and tree species than on tree size, Scandinavian Journal of Forest Research, DOI: 10.1080/02827581.2025.2497364

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# Tree-related microhabitat assemblages in boreal forests depend more on local environmental conditions and tree species than on tree size

Rita Bütler a, b, Laurent Larrieu c, d and Maxence Martin e

<sup>a</sup>Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Community Ecology Unit, Lausanne, Switzerland; <sup>b</sup>Ecole Polytechnique Fédérale Lausanne, Plant Ecology Research Laboratory PERL, School of Architecture Civil & Environmental Engineering ENAC Lausanne, Switzerland; <sup>c</sup>University of Toulouse, INRAE, UMR DYNAFOR, France; <sup>d</sup>CNPF-CRPF Occitanie, Tarbes, France; <sup>e</sup>Institut de Recherche sur les Forêts, Université du Québec en Abitibi-Témiscamingue, Québec, Canada

## ABSTRACT

Tree-related microhabitats (TreMs) are crucial for biodiversity, supporting thousands of species. Most TreM research has focused on temperate forests, prompting us to evaluate the TreM typology in the boreal biome. We aimed to: (i) identify factors influencing TreM occurrence on living trees, (ii) assess redundancy and complementarity of TreM supply among Scots pine, birch, and aspen in Fennoscandia, (iii) compare TreM occurrence between Fennoscandian and Canadian boreal forests, and (iv) determine the minimum sample size for assessing TreM diversity in large-scale inventories. We inventoried 1515 trees in long unmanaged forests across Fennoscandia and compared results with a Canadian dataset. Findings show that Scots pine, birch, and aspen support distinct and complementary TreM assemblages, emphasizing the importance of mixed stands for biodiversity. Over larger geographic areas, local plot context - including climate, disturbance history, and biotic/abiotic factors - was the main driver of TreM occurrence. Unlike temperate forests, tree diameter was not a significant driver in boreal forests. The variability of TreM assemblages within the boreal biome underscores the need for large sample sizes to accurately assess TreM diversity. Sampling 1000 trees is sufficient to assess the seven TreM forms, while a larger sample is required to capture all fifteen TreM groups.

## ARTICLE HISTORY

Received 11 December 2024
Accepted 17 April 2025

## KEYWORDS

Tree-related microhabitats;
TreMs; boreal forest;
biodiversity; unmanaged
forest; retention forestry

## Introduction

Tree-related microhabitats (TreMs) are a relatively recent eco-logical concept that has attracted growing attention in research, conservation, and forest management (Martin et al. 2022). As defined by Larrieu et al. (2018), TreMs are “distinct, well delineated structures occurring on living or standing dead trees, that constitute particular and essential substrates or life sites for species or species communities during at least a part of their life cycle to develop, feed, shelter or breed”. As essential microhabitats for forest-dwelling species, TreMs are crucial for a broad array of taxa (Stokland et al. 2012; Larrieu et al. 2018) and can be used as indirect indicators for the potential presence of these species (Asbeck et al. 2021; Zeller et al. 2022). They support a wide range of organisms, including vertebrates (e.g. birds, bats, amphibians, and reptiles), diverse invertebrate taxa (gastropods, insects, arachnids, myriapods, and springtails), as well as fungi, lichens, bryophytes, vascular plants, and microscopic animals such as nematodes, rotifers, and tardigrades (Larrieu et al. 2018; Bütler et al. 2024; Majdi et al. 2024). Therefore, the TreM concept provides a holistic approach to forest tree-related biodiversity, aiding in the assessment and

guidance of forest management for biodiversity conservation (Kraus and Krumm 2013). The hierarchic TreM typology published by Larrieu et al. (2018) is a reference tool for harmonized and standardized inventories of temperate and Mediterranean forests. It provides clear definitions and size thresholds for consistent identification of TreMs. Larrieu et al. (2018) describe seven basic forms based on morphological characteristics and biodiversity relevance: (i) cavities *lato sensu*; (ii) tree injuries and exposed wood; (iii) crown deadwood; (iv) excrescences; (v) fruiting bodies of saproxylic fungi and fungi-like organisms; (vi) epiphytic and epixylic structures; and (vii) exudates. These forms are further detailed in 15 groups and 47 types (Supplementary material: Table S1). As each TreM type provides specific environmental conditions (Bouget et al. 2024), TreM assemblages serve as indicators of resource diversity, following the heterogeneity-diversity theory (Tews et al. 2004).

In recent years, integrative forestry - which includes the retention of TreM-bearing trees (also known as habitat trees; Bütler et al. 2013) and deadwood - has garnered considerable attention in Central and Western Europe (Bollmann et al. 2020; Kraus and Krumm 2013; Krumm et al. 2020). Research evidence

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has highlighted the ecological value of these trees (e.g. Winter and Möller 2008; Larrieu et al. 2018; Bütler et al. 2021a; Müller and Bütler 2010; Stokland et al. 2012), which in turn has played a pivotal role in the adoption of retention practices in Europe's temperate regions. Furthermore, society's growing preference for biodiversity and diverse ecosystem services over timber production alone in recent decades has accelerated the adoption of these practices (Gustafsson et al. 2020). Currently, many forest services in temperate Europe use the TreM typology outlined by Larrieu et al. (2018) to select habitat trees or retention patches, employing user-friendly tools customized for this purpose (Bütler et al. 2020; Bütler et al. 2021a; Bütler et al. 2021b; Bütler and Larrieu 2023). The above tools are primarily designed for temperate and Mediterranean forests and are rarely, if ever, used in the boreal forests of Europe and North America, despite the prevalence of intensive forest management.

At present, most of the TreM-related knowledge is derived from temperate forests in Western Europe (Martin et al. 2022). In contrast, comprehensive studies on TreMs within boreal and hemiboreal biomes remain limited (e.g. Lilja and Kuulu-vainen 2005; Korkjas et al. 2021a; Martin et al. 2021a; Torres-García et al. 2024), although certain TreM groups, such as woodpecker cavities (e.g. Pakkala et al. 2018), rot-holes (e.g. Wetherbee et al. 2022), and fruiting bodies of fungi (e.g. Jonsell et al. 2001; Komonen et al. 2001) have been extensively investigated.

Although retention forestry has been practiced for several decades in clearcut systems across Fennoscandia and the Baltic States (Gustafsson et al. 2013), adopting the TreM concept could further refine and strengthen retention approaches. In North America, existing routine forestry practices may facilitate the rapid incorporation of TreMs into both research frameworks and forest management strategies (Martin et al. 2022). Nevertheless, the applicability of the TreM typology in boreal forests may be questioned, due to key ecological differences from temperate forests, including smaller tree dimensions, slower growth rates, colder climatic conditions, and distinct natural disturbance regimes. Targeted research within boreal contexts is therefore critical to evaluate the typology's relevance and ecological robustness.

Previous studies in temperate forests have identified tree species, diameter at breast height, and status (i.e. living versus standing dead) as key factors influencing TreM occurrence and abundance at the tree level (Larrieu et al. 2022; Larrieu and Cabanettes 2012; Paillet et al. 2019; Vuidot et al. 2011; Winter and Möller 2008). In addition, the plot context – combining local environmental conditions, past and current management legacies, and local biotic features – has been found to have high explanatory power for predicting TreM occurrence, with site effects sometimes being substantial (Larrieu et al. 2022; Courbaud et al. 2022). Observational evidence suggests that most TreMs have reduced formation rates in managed forests compared to unmanaged ones where no logging has occurred for at least 100 years, and early-successional species tend to display different TreMs than mid- and late-successional species (Courbaud et al. 2022).

Given this context, the present study investigates TreM assemblages in long-unharvested Fennoscandian and

Canadian primary boreal forests. To address the specificities of boreal forests, we used an adapted TreM typology (Bütler et al. 2024) and worked across a broad geographic gradient to assess potential effects of the local environmental conditions. Specifically, we sought to: (i) identify key factors for TreM occurrence on living trees; (ii) assess redundancy and complementarity in TreM supply among three characteristic boreal tree species; (iii) compare TreM occurrence patterns between Fennoscandian and Canadian boreal forests; and (iv) determine the minimum tree sample size required to reliably assess TreM diversity in large-scale boreal forest inventories.

# Methods

## Study area and TreM sampling

We selected ten study sites in Fennoscandia in four climatic areas, between 59.5° and 70.2° latitude and 10.5° and 24.8° longitude (Figure 1 and Supplementary material: Table S2). All the forests had been unmanaged for a long time, i.e. without any signs of harvesting or other silvicultural interventions. To understand the natural dynamics of TreMs, it's best to study them in unlogged old-growth forests, giving them time to develop and avoiding human selection bias. At each site, we sampled live birch *Betula* spp. (n = 561), Scots pine *Pinus sylvestris* (n = 637), and aspen *Populus tremula* (n = 317) trees along a transect line (1515 trees in total; Supplementary material: Table S2). As TreMs occur more frequently on large trees than on smaller ones (e.g. Asbeck et al. 2019; Paillet et al. 2019; Przepiora and Ciach 2022; Acloque et al. 2023; Vuidot et al. 2011), we set the inventory threshold at a diameter at breast height (dbh) ≥ 11 cm and sampled only 10% of trees with a dbh < 20 cm to avoid too many "null samples" (i.e. trees without TreMs). Each tree was inspected for TreMs according to the typology of Larrieu et al. (2018), once for the lower part of the trunk and a second time, at a greater distance, for the crown. We applied the minimum size limits recommended by Larrieu et al. (2018), adapting them for some TreMs to suit boreal forests (Supplementary material: Table S3). We recorded TreM types as binary data (presence or absence), meaning that each TreM type was counted only once per tree. Data analysis was performed at the level of seven TreM forms and 15 TreM groups, as described by Larrieu et al. 2018. For comparisons between the Fennoscandian and Canadian contexts, we used a dataset from Martin et al. (2021a and 2021c) (Supplementary material: Table S2 and Figure S3).

## Key factors for TreM occurrence

To quantify the predictive power of the features we used the Fennoscandia dataset of 1515 living trees. For each of the seven TreM forms and the fifteen TreM groups, we built a Generalized Linear Mixed Model (GLMM) that described the presence/absence of the TreM in relation to the tree diameter at breast height (dbh), tree species and site. Tree dbh was used as fixed effect. As variables with random effect, we used dbh in function of transect context (i.e. local
explanatory factor in the total model in turn to quantify its effects in terms of the proportion of variance explained with respect to the total model: dbh, transect context and tree-species. The GLMM models were fitted with a Bernoulli structure (binomial distribution and logit link) to describe presence/absence using the BRMS Package (Bürkner 2021) and thus Stan was used as the Markov chain Monte Carlo algorithm. The model considered potential correlation among random effects, with an a priori of no correlation. We used 1000 iterations for the burn in, 2000 iterations for the estimations with four chains in parallel.

For each explanatory variable, the proportion of variance explained was calculated as the variance explained by the model without including that given feature in the corresponding model, divided by the total variance in the presence/ absence of the particular TreM. So, a feature that has led to a big loss of explained variance when excluded is an important feature for the model.

We used the same analysis procedure for the comparison between the Fennoscandian and Canadian contexts.

## Redundancy and complementarity of tree species for TreM supply

Characteristic TreMs were identified for each tree species using the Indicator Value method (Dufrene and Legendre 1997). This method combines measures of specificity (abundance) and fidelity (frequency of occurrence) and provides an indicator value (IndVal) for TreMs as a percentage. Following Dufrene and Legendre (1997), a random reallocation procedure of tree species among tree species groups was used to test the significance of the IndVal measures for each TreM and a threshold level of 25% for the index was accepted.

Since the sample sites were geographically distributed into six patches (Figure 1), we identified six zones using the longitude records. Following the same idea, we identified four classes of dbh values by using quartiles (<20; 20-30; 30-40; > 40 cm). Then, we used these six zones and these four dbh classes to make cross-sections of tree species-zone and tree species-dbh.

## How many trees are enough to be observed in the field to assess TreM diversity?

From the Fennoscandian dataset, we used a sampling procedure with a given size of 100-1000 trees (with a step of 100 trees), repeated 1000 times. The aims were to highlight (i) the number of samples required to have a high probability of detecting all the TreM forms or groups really present in the field, and; (ii) the mean and range of the sample size required to determine whether the most (or least) frequent TreM form or group in the field can be captured, i.e. correctly classify them by relative abundance.

## Results

We detected 1353 TreMs on 1515 inventoried living trees, within all of the seven TreM forms and fifteen groups (Table 1). The most common TreM forms were epiphytic and

<table><caption>**Table 1.** TreM frequency in Fennoscandian boreal forests. Proportion of living trees (n = 1515) bearing a given TreM form or group.</caption><thead><tr><th>TreM level</th><th>TreM</th><th>TreM_full_name</th><th>% of trees</th></tr></thead><tbody><tr><td>Form</td><td>CAV</td><td>Cavities</td><td>8.8</td></tr><tr><td>Form</td><td>EXP_W</td><td>tree injuries and exposed wood</td><td>12.8</td></tr><tr><td>Form</td><td>CR_DW</td><td>crown deadwood</td><td>23.2</td></tr><tr><td>Form</td><td>EXCR</td><td>Excrescences</td><td>6.4</td></tr><tr><td>Form</td><td>FUNG</td><td>Fungi</td><td>5.7</td></tr><tr><td>Form</td><td>EPI</td><td>Epiphytes</td><td>26.2</td></tr><tr><td>Form</td><td>EXU</td><td>Exudates</td><td>1.4</td></tr><tr><td>Group</td><td>WPBC</td><td>woodpecker breeding cavities</td><td>0.5</td></tr><tr><td>Group</td><td>RH</td><td>rot-holes</td><td>3.2</td></tr><tr><td>Group</td><td>IGAL</td><td>insect galleries and bore holes</td><td>0.9</td></tr><tr><td>Group</td><td>CON</td><td>Concavities</td><td>4.8</td></tr><tr><td>Group</td><td>EXSW</td><td>exposed sapwood</td><td>10.0</td></tr><tr><td>Group</td><td>EXSHW</td><td>exposed sapwood and heartwood</td><td>3.6</td></tr><tr><td>Group</td><td>CRDW</td><td>crown deadwood</td><td>23.2</td></tr><tr><td>Group</td><td>TWT</td><td> twig tangles</td><td>1.1</td></tr><tr><td>Group</td><td>BUCA</td><td>burrs and cankers</td><td>5.4</td></tr><tr><td>Group</td><td>PFUN</td><td>perennial fungi</td><td>5.3</td></tr><tr><td>Group</td><td>EPHFU</td><td>ephemeral fungi and slime moulds</td><td>0.4</td></tr><tr><td>Group</td><td>EPI</td><td>epiphytic and parasitic crypto- and phanerogams</td><td>23.6</td></tr><tr><td>Group</td><td>NEST</td><td>Nests</td><td>2.2</td></tr><tr><td>Group</td><td>MSOIL</td><td>Microsoils</td><td>1.6</td></tr><tr><td>Group</td><td>EXU</td><td>Exudates</td><td>1.4</td></tr></tbody></table>

epixylic structures (abbreviated as “epiphytes”, mostly lichens), crown deadwood (mostly dead branches) and tree injuries and exposed wood (mostly bark loss; see Table S1 in the Supplementary material). Several TreM groups were rare (<2% of bearing trees), including woodpecker breeding cavities, insect galleries and bore holes, twig tangles, ephemeral fungi and slime moulds, microsoils and fresh exudates. Of the 47 TreM types described by Larrieu et al. (2018), we were able to detect 37 different ones. Almost two thirds of all the trees (64.7%) bore at least one TreM, birch (77%) more often than either pine (58%) or aspen (56%). Only a few trees (15.9%) bore two or more different types of TreMs (three types 4.2%, four to six types 1.3%).

## Key factors for TreM occurrence

At the TreM form level, the best full models explained, on average, 17.7% of the variance in TreM occurrence, ranging from 3.9% for exudates to 50.4% for epiphytes (Table 2). At the TreM group level, the best full models explained, on average, 11.3% of the variance in TreM occurrence, ranging from 1.1% for ephemeral fungi and slime moulds to 58.5% for epiphytic and parasitic crypto- and phanerogams (Table 2). In 72% of models, transect context was the feature that explained the highest proportion of variance in TreM occurrence.

## Redundancy and complementarity of tree-species for TreM supply

At the TreM form level, we found several characteristic TreMs-tree species associations (Table 3). Epiphytes were associated with birch; crown deadwood was characteristic both of Scots pine and aspen; fungi were associated with aspen, and excrescences with both birch and Scots pine. In addition, we highlighted an effect of geographical zone on the list of characteristic TreMs (results in Supplementary material:
<figure><img src="image_17.png" /><figcaption>**Table 2.** Proportion of variance explained by the full and simplified models for predicting the occurrence of tree-related microhabitats (TreM) in Fennoscandian boreal forests. For each form and group of TreMs, the full model includes tree diameter at breast height (dbh), transect context and tree species. Transect context integrates local environmental conditions, and local biotic features. To evaluate the proportion of variance in TreM occurrence explained by each feature, simplified models were built excluding each of these features in turn. The feature that explained the highest proportion of variance for each TreM group is shown in bold.</figcaption></figure>

<table><thead><tr><th rowspan="2">TreM level</th><th rowspan="2">TreM</th><th rowspan="2">TreM_full_name</th><th colspan="4">Variance explained (%)</th></tr><tr><th>Full model</th><th>Without dbh</th><th>Without transect context</th><th>Without tree-species</th></tr></thead><tbody><tr><td>Form</td><td>CAV</td><td>cavities</td><td>0.071</td><td>0.049</td><td><strong>0.010</strong></td><td>0.045</td></tr><tr><td>Form</td><td>EXP_W</td><td>exposed wood</td><td>0.043</td><td>0.043</td><td><strong>0.013</strong></td><td>0.051</td></tr><tr><td>Form</td><td>CR_DW</td><td>crown deadwood</td><td>0.174</td><td>0.159</td><td><strong>0.136</strong></td><td><strong>0.137</strong></td></tr><tr><td>Form</td><td>EXCR</td><td>excrescences</td><td>0.142</td><td>0.107</td><td>0.101</td><td><strong>0.092</strong></td></tr><tr><td>Form</td><td>FUNG</td><td>Fungi</td><td>0.267</td><td>0.218</td><td><strong>0.108</strong></td><td>0.248</td></tr><tr><td>Form</td><td>EPI</td><td>epiphytes</td><td>0.504</td><td>0.501</td><td><strong>0.385</strong></td><td>0.466</td></tr><tr><td>Form</td><td>EXU</td><td>exudates</td><td>0.039</td><td>0.022</td><td><strong>0.002</strong></td><td>0.021</td></tr><tr><td>Group</td><td>WPBC</td><td>woodpecker breeding cavities</td><td>0.022</td><td>0.012</td><td><strong>0.004</strong></td><td>0.011</td></tr><tr><td>Group</td><td>RH</td><td>rot-holes</td><td>0.083</td><td>0.050</td><td>0.047</td><td><strong>0.038</strong></td></tr><tr><td>Group</td><td>IGAL</td><td>insect galleries and bore holes</td><td>0.032</td><td>0.031</td><td><strong>0.005</strong></td><td>0.026</td></tr><tr><td>Group</td><td>CON</td><td>concavities</td><td>0.050</td><td>0.046</td><td><strong>0.008</strong></td><td>0.044</td></tr><tr><td>Group</td><td>EXSW</td><td>exposed sapwood</td><td>0.062</td><td>0.054</td><td><strong>0.011</strong></td><td>0.070</td></tr><tr><td>Group</td><td>EXSHW</td><td>exposed sapwood and heartwood</td><td>0.088</td><td>0.082</td><td><strong>0.060</strong></td><td>0.080</td></tr><tr><td>Group</td><td>CRDW</td><td>crown deadwood</td><td>0.173</td><td>0.159</td><td><strong>0.136</strong></td><td><strong>0.136</strong></td></tr><tr><td>Group</td><td>TWT</td><td>tree tangles</td><td>0.028</td><td>0.024</td><td><strong>0.002</strong></td><td>0.028</td></tr><tr><td>Group</td><td>BUCA</td><td>burrs and cankers</td><td>0.164</td><td>0.113</td><td><strong>0.087</strong></td><td>0.120</td></tr><tr><td>Group</td><td>PFUN</td><td>perennial fungi</td><td>0.299</td><td>0.238</td><td><strong>0.161</strong></td><td>0.273</td></tr><tr><td>Group</td><td>EPHFU</td><td>ephemeral fungi and slime moulds</td><td>0.011</td><td>0.008</td><td>0.009</td><td><strong>0.004</strong></td></tr><tr><td>Group</td><td>EPI</td><td>epiphytic and parasitic crypto - and phanerogams</td><td>0.585</td><td>0.573</td><td><strong>0.429</strong></td><td>0.548</td></tr><tr><td>Group</td><td>NEST</td><td>Nests</td><td>0.046</td><td>0.037</td><td><strong>0.033</strong></td><td>0.046</td></tr><tr><td>Group</td><td>MSOIL</td><td>microsoils</td><td>0.037</td><td>0.031</td><td><strong>0.013</strong></td><td>0.026</td></tr><tr><td>Group</td><td>EXU</td><td>exudates</td><td>0.022</td><td>0.021</td><td><strong>0.003</strong></td><td>0.022</td></tr></tbody></table>

Table S4). We also found an effect of the dbh on the list of characteristic TreM forms: “excrescences” were significantly associated with the largest (dbh > 40 cm) birch trees (0.49***; IndVal and *p*-value < 0.001).

As for TreM forms, we found several characteristic TreMs-tree species associations at the TreM group level (Table 4). While most of the results confirmed the TreMs-tree species associations found at the TreM form level, we also found some additional ones. Exposed sapwood was characteristic of Scots pine and aspen; concavities for birch and Scots pine, and rot-holes for both soft wood species, i.e. birch and aspen. By merging location and tree species, we also found an effect of geographical zone on the list of characteristic TreM groups (results in Supplementary material: Table S5). We also highlighted an effect of the dbh on the list of characteristic TreM groups: “burrs and cankers” were significantly associated with the largest (dbh > 40 cm) birch trees (0.49***), and “concavities” with the smallest (dbh < 20 cm) Scots pines (0.412***).

## Comparison between the Fennoscandian and Canadian contexts

The best full models explained, on average, 10.8% of the variance in TreM form occurrence and 10.7% in TreM

group occurrence for the Fennoscandian dataset, while they explained 17.9% of the variance in TreM form occurrence and 16.7% in TreM group occurrence for the Canadian dataset (Table 5). At the form level, values ranged from 4.3% (tree injuries and exposed wood) to 17.4% (crown deadwood) and 13.1% (tree injuries and exposed wood) to 22.8% (crown deadwood) for Fennoscandian and Canadian datasets, respectively. At the group level, values ranged from 6.2% (tree injuries and exposed sapwood) to 17.3% (crown deadwood) and 11.10% (exposed sapwood) to 25.5% (exposed sapwood and heartwood) for Fennoscandian and Canadian datasets, respectively. Transect context was the feature that explained the highest proportion of variance in TreM occurrence both in

<table><caption>**Table 4.** Characteristic TreM groups, determined by the IndVal approach. Only TreMs significant at both permutation tests and with an indicator value higher than 25% were selected.</caption><thead><tr><th>TreM groups</th><th>Betula spp.</th><th>Populus tremula</th><th>Betula spp. + Pinus sylvestris</th><th>Pinus sylvestris + Populus tremula</th><th>Betula spp. + Populus tremula</th></tr></thead><tbody><tr><td>rot-holes</td><td></td><td></td><td></td><td></td><td>0.247***</td></tr><tr><td>concavities</td><td></td><td></td><td>0.283**</td><td></td><td></td></tr><tr><td>exposed sapwood</td><td></td><td></td><td></td><td>0.429***</td><td></td></tr><tr><td>exposed sapwood and heartwood</td><td></td><td></td><td></td><td></td><td>0.251**</td></tr><tr><td>crown deadwood</td><td></td><td></td><td></td><td>0.756***</td><td></td></tr><tr><td>burrs and cankers</td><td></td><td></td><td>0.292**</td><td></td><td></td></tr><tr><td>perennial fungi</td><td></td><td></td><td></td><td>0.572***</td><td></td></tr><tr><td>epiphytic and parasitic crypto - and phanerogams</td><td></td><td></td><td>0.838***</td><td></td><td></td></tr></tbody></table>

<table><caption>**Table 3.** Characteristic TreM forms for different tree species, determined by the IndVal approach (IndVal + *p*-value). Only TreMs significant at both permutation tests and with an indicator value higher than 25% were selected.</caption><thead><tr><th>TreM forms</th><th>Betula spp.</th><th>Populus tremula</th><th>Betula spp. + Pinus sylvestris</th><th>Pinus sylvestris + Populus tremula</th></tr></thead><tbody><tr><td>Crown deadwood</td><td></td><td></td><td></td><td>0.755***</td></tr><tr><td>Excrescences</td><td></td><td></td><td>0.324***</td><td></td></tr><tr><td>Fungi</td><td></td><td>0.561***</td><td></td><td></td></tr><tr><td>Epiphytes</td><td>0.816***</td><td></td><td></td><td></td></tr></tbody></table>

<footnote>***: *p*-value < 0.001.</footnote>

<footnote>**: *p*-value < 0.001; **: *p*-value < 0.01</footnote>
<figure><img src="image_18.png" /><figcaption>**Table 5.** Proportion of variance explained by the full and simplified models for predicting the occurrence of tree-related microhabitats (TreMs). When indicated « _F » values refer to Fennoscandian context while « _C » to the Canadian one. Comparisons between the two datasets were possible for only two TreM forms and three TreM groups. For each form and group of TreMs, the full model includes tree diameter at breast height (dbh), plot/transect context and tree species. Plot/transect context integrates local environmental conditions, and local biotic features. To evaluate the proportion of variance in TreM occurrence explained by each feature, simplified models were built that excluded each one of these features in turn. The feature that explained the highest proportion of variance for each TreM group is indicated in bold.</figcaption></figure>

<table><thead><tr><th>TreM_level</th><th>TreM_full_name</th><th>Full model_F</th><th>Full model_C</th><th>Without dbh_F</th><th>Without dbh_C</th><th>Without transect context_F</th><th>Without plot context_C</th><th>Without tree-species_F</th><th>Without tree-species_C</th></tr></thead><tbody><tr><td>Form</td><td>tree injuries and exposed wood</td><td>0.043</td><td>0.228</td><td>0.043</td><td>0.179</td><td><strong>0.013</strong></td><td><strong>0.095</strong></td><td>0.051</td><td>0.164</td></tr><tr><td>Form</td><td>crown deadwood</td><td>0.174</td><td>0.131</td><td>0.159</td><td><strong>0.048</strong></td><td><strong>0.136</strong></td><td>0.049</td><td>0.137</td><td>0.09</td></tr><tr><td>Group</td><td>exposed sapwood</td><td>0.062</td><td>0.111</td><td>0.054</td><td>0.055</td><td><strong>0.011</strong></td><td><strong>0.042</strong></td><td>0.070</td><td>0.086</td></tr><tr><td>Group</td><td>exposed sapwood and heartwood</td><td>0.088</td><td>0.255</td><td>0.082</td><td>0.195</td><td><strong>0.060</strong></td><td><strong>0.054</strong></td><td>0.080</td><td>0.180</td></tr><tr><td>Group</td><td>crown deadwood</td><td>0.173</td><td>0.136</td><td>0.159</td><td>0.051</td><td><strong>0.136</strong></td><td><strong>0.047</strong></td><td><strong>0.136</strong></td><td>0.083</td></tr></tbody></table>

Fennoscandia (100% of models) and in Canada (80% of models). Tree dbh explained the highest proportion of variance for crown deadwood (TreM form level) in Canada, while tree species explained the highest proportion of variance for crown deadwood (TreM group level) in Fennoscandia.

## How many trees are enough to be observed in the field to assess TreM diversity?

At the TreM form level, 500 trees was the minimum sample size required to observe all the TreMs present in the field in the Fennoscandian context, whereas 1000 trees were the optimal sample size to correctly rank TreMs according to their frequencies, i.e. to indicate their true degrees of relative abundance. At the TreM group level, sampling 1000 trees was not enough to either detect or correctly classify the TreMs, in particular the rarer ones.

## Discussion

Applying the method of Larrieu et al. (2018) on 1515 trees in Fennoscandian boreal forests, using slightly modified size limits (Supplementary material: Table S3), we detected a total of 37 out of 47 TreM types, within all seven different forms and 15 groups. Undetected TreM types included small woodpecker breeding cavities, hollow branches and lightning scars, which are also rare in unmanaged temperate forests in general (Bütler et al. 2020). Cryptic TreMs like myxomycetes, and TreMs that are much more common in managed forests (such as dendrotelms; Larrieu et al. 2012) and those associated with temperate forests (e.g. ivy and lianas, and mistletoe) were also not detected.

The relatively large sample sizes required to observe the full set of TreMs and rank them according to their frequency may be due to the relative rarity of some TreM forms (Table 1), and the high variability of site conditions within the large geographical area, covering approximately 1200 km in latitude and 800 km in longitude, which may favour specific TreMs in specific sites. Indeed, we observed that transect context, including climatic, environmental and local biotic and abiotic features, is relevant to the occurrence of TreMs in boreal forests.

## Local context explains TreM occurrence in Fennoscandia

Transect context explained the highest proportion of variance in most of the models (Table 2). Site effects are known to have a strong influence on TreM profiles (Courbaud et al. 2022). Our Fennoscandian study area covered a large geographic range of about 1200 km in latitude and 800 km in longitude, including a variety of different forest types (considerous and deciduous dominated), climates and local site conditions (from dry to wet, from poor to fertile soils, etc.).

Our results are consistent with other large scale TreM studies covering multiple forest types and climatic regions. For example, in a study that pooled TreM data from several temperate and Mediterranean forests, TreM occurrence was also primarily explained by plot context (Larrieu et al. 2022). A large variation of TreMs between old-growth Scots pine stands along a geographical and human impact gradient was demonstrated in mid-boreal Fennoscandia (Lilja and Kuuluvainen 2005).

In our study, transect context is a “black box” that combines different local conditions (i.e. climatic, environmental and historical) with local biotic and abiotic features, all of which together have high explanatory power for predicting TreM occurrence. Natural forest dynamics, in response to varying disturbance histories across sites, are likely to influence the development of TreMs over time. On the one hand, natural disturbance sizes, frequencies and severities in European boreal forests are highly variable in space and time, leading to a wide variation in biological legacies (Aszalós et al. 2022; Martin et al. 2021a). On the other hand, natural disturbances are also known to be essential determinants of TreM-availability (Zemlerová et al. 2023). On a smaller scale, site-specific environmental features may play an important role in TreM formation (Larrieu et al. 2022). For example, unfavourable conditions for tree growth can induce specific TreMs (crown deadwood, rot-holes, exposed sapwood and heartwood), humid climate favours epiphytes on trees (Rameau et al. 1991), and thin and compact soils can lead to buttress formations (concavities; Ennos 1993) and crown deadwood (Bréda et al. 2004). Several of the above environmental factors may be relevant to our study. Firstly, humid climates on the Norwegian West coast, in alluvial areas or nearby lakes may explain the high abundance of
<figure><img src="image_19.png" /></figure>

epiphytic lichens (Gauslaa 2014). Second, thin soils on rocky sites on the Norwegian north coast might favour the formation of buttress-root concavities and dead branches. Thirdly, strong winds on the west and north coast of Fennoscandia and heavy snow loads on sites with cold continental climate in Finland could lead to stem or limb breakage. The presence of lignivorous fungi on trees can also be partly explained by the transect context, either because of exposed heartwood after a breakage event, or due to unfavourable conditions for tree growth in moorlands or nearby rivers on temporarily flooded soils (Ballesteros-Cánovas et al. 2015; Kozlowski and Pallardy 2002).

## Tree species matters for TreM occurrence

The occurrence of TreMs is influenced by a combination of local environmental factors, disturbance dynamics, and specific tree species characteristics, including architecture, bark acidity and texture, presence of heartwood, and compartmentalization capacity (Larrieu et al. 2022). For instance, TreMs associated with wood decay, such as rot-holes and fungi, are more commonly found on fast-growing pioneer species like birch and aspen (Spînu et al. 2023; Cadieux et al. 2023), which typically have lower compartmentalization capacities (Lonsdale 2013). In contrast, trees with heartwood and resin, such as pine species, exhibit greater resistance to decay (Smith 2015). Consistent with these patterns, we observed that perennial fungi were a characteristic TreM on aspen, while rot-holes were typical of both aspen and birch (Table 4) but were rarely found on Scots pine.

Crown deadwood was observed on both Scots pine and aspen, with distinct characteristics for each species. In Scots pine, dead branches were typically large (diameter >10 cm), while in aspen, dead branches were generally smaller (>3 cm, and >10% of the crown was dead). These patterns align with the species' respective growth and mortality dynamics. Aspen, a light-demanding species, undergoes self-pruning to shed shaded, diseased, or infested branches that tax its resources (Nekrasova 1970). In contrast, old Scots pines usually die gradually after extended periods of slow growth. Their wood decomposes slowly, allowing them to persist for decades, or even centuries (Kuuluvainen et al. 2017).

In our study, epiphytic lichens (i.e. foliose and fruticose types) were strongly associated with birch, while they were uncommon on both Scots pine and aspen. The composition and abundance of epiphytic lichen communities are shaped by factors such as moisture, light availability, bark chemistry, and bark structure (Asplund et al. 2014), so differences between tree species are expected. Birch, for example, appears to support faster colonization of epiphytic macrolichens compared to Scots pine and aspen (Uliczka and Angelstam 1999), and it may also have the highest water retention capacity (Nordén, pers. comm.), both of which may explain our findings. Additionally, the low detection of lichens on aspen may be due to our inventory's size threshold (minimum 1 cm in depth), as most epiphytic lichen communities on aspen do not reach these dimensions (Nordén, pers. comm.).

Exposed sapwood, resulting from bark loss, was commonly observed on both Scots pine and aspen (Table 4). In aspen, we attributed bark loss to winter browsing by moose (Alces alces), as indicated by characteristic tooth marks. Moose browsing behaviour aims to balance nutritional intake, fiber, and energy (Felton et al. 2018), leading these large herbivores to strip bark from various tree species (Faber and Edenius 1997). While aspen is a preferred food source for moose (Bergqvist et al. 2018), Scots pine is the most important winter forage species in some regions (Lindmark et al. 2020).

Exposed sapwood and heartwood – resulting from stem breakages, limb breakages, and cracks – were significantly associated with birch in specific areas. This pattern may relate more to local site conditions than to the tree species itself. Factors such as heavy snow leading to breakage or winter frost in cold continental climates, like those in Pallas-Yllästunturi National Park, Finland, may favour cracking.

Furthermore, we identified a combined effect of tree species and tree diameter on the list of characteristic TreM groups. The presence of burrs and cankers was found to be significantly associated with the largest birch trees (dbh >40 cm), while concavities were observed to occur more frequently on the smallest Scots pines. Regarding cankers, the so-called "chaga," typically charcoal-black and sterile conks, was frequently observed on birch trees. These formations result from the fungus *Inonotus obliquus*, a primary parasite that decomposes living stems and is prevalent in birch stands across the circumboreal regions of the Northern Hemisphere (Szychowski et al. 2021; Miina et al. 2021; Lee et al. 2008). Concavities on the smallest Scots pines were predominantly observed on rocky sites, where tree growth is constrained, and trees develop thick roots for anchoring. In birches growing in alluvial forests with a bump-and-dip microtopography, concavities at the stem base were also common.

In our dataset, the most widespread TreM groups were epiphytic lichens (24% of trees), followed by crown deadwood, primarily in the form of dead branches (23% of trees), and exposed sapwood, mostly resulting from bark loss (10% of trees). Given the limited number of comprehensive TreM studies conducted in boreal forests, direct comparisons across different sites and species are challenging. Consistent with findings from an Estonian study (Korkjas et al. 2021b), the dominant TreM types associated with aspen in our data were crown deadwood and fungi. Additionally, we frequently observed exposed sapwood in association with aspen, while Korkjas et al. (2021b) reported a high prevalence of epiphytic lichens on aspen. In contrast, in our study, epiphytic lichens were almost exclusively found on birch.

Our observations indicate that birch, Scots pine, and aspen are complementary in their provision of TreMs. The influence of tree species on TreM assemblages has similarly been noted in prior studies in temperate forests (e.g. Larrieu and Cabanettes 2012; Przepiora and Ciach 2022; Asbeck et al. 2019), suggesting that mixed-species stands are likely to support a higher diversity of TreMs than monospecific stands. For instance, aspen is recognized as the primary cavity tree genus for woodpeckers in boreal forests, both in
<figure><img src="image_20.png" /></figure>

Fennoscandia (Pakkala et al. 2024) and Canada (Cadieux et al. 2023). Thus, incorporating broadleaved trees – particularly retaining larger aspen trees within conifer-dominated stands – is highly beneficial for primary and secondary cavity nesters. More broadly, as TreMs are defined as “particular and essential substrates or life sites for species or species communities during at least a part of their life cycle to develop, feed, shelter, or breed” (Larrieu et al. 2018), increased TreM diversity and complementary TreM assemblages in boreal forests are likely to enhance the diversity of TreM-dwelling species.

## Tree diameter is not a significant TreM driver in boreal forests

In both our Fennoscandian and Canadian study sites, tree diameter was not identified as a significant driver of TreM occurrence. Instead, TreM profiles were primarily influenced by local conditions at the plot scale, including factors such as disturbance history, microtopography, rocky soil, heavy snowfall, cold continental climate, and biotic factors, such as the presence of specific fungi or large herbivores.

This observation is in contrast with that made in the context of temperate forests, where tree diameter is frequently recognized as a key factor influencing TreM richness and abundance (Asbeck et al. 2019; Paillet et al. 2019; Przepiora and Ciach 2022; Acloque et al. 2023; Vuidot et al. 2011; Courbaud et al. 2022; Larrieu and Cabanettes 2012). Only large and very large trees are expected to host the full range of TreM groups (Larrieu et al. 2014). While trees in unmanaged temperate forests can reach substantial diameters (Hobi et al. 2015; Nilsson et al. 2002), trees in boreal forests, even when they reach advanced ages, do not attain similarly large sizes due to climatic limitations (Rouvinen and Kuuluvainen 2005). The tree diameter range in our datasets was 9–84 cm (Canada) and 11–88 cm (Fennoscandia), in contrast to a European database, where the range was 6–200 cm for trees in long-term unmanaged temperate forests (Larrieu and Courbaud 2024; cf. Supplementary material: Figure S1). It is therefore unsurprising that other factors exert a greater influence on the occurrence of TreM than tree diameter *per se*. An exception to this trend was observed in the Canadian dataset, where tree diameter emerged as a significant driver of rot-hole occurrence. Given that rot-holes take decades to develop (Stokland et al. 2012), larger, often older trees, are more likely to exhibit them than smaller trees (Ranius et al. 2009; Sebek et al. 2013). In European temperate forests, tree age is recognized as a key determinant of TreM richness and abundance. Certain TreM groups demonstrate a positive correlation with tree age, irrespective of tree diameter (Kozak et al. 2023). Although we did not determine tree age in our study, it can be inferred that old trees with smaller diameters are likely present in long unmanaged forests at high latitudes, as reported by Martin et al. (2020 and 2021b).

## Limitations of our study

Our study represents a preliminary attempt to apply the TreM typology (Larrieu et al. 2018) in a boreal context. In

Fennoscandia, we focused on three tree species, i.e. birch, Scots pine and aspen, but did not include Norway spruce (*Picea abies*), one of the major constituents of the boreal forest. To facilitate comparisons with the Canadian boreal zone, we conducted our analysis at the tree genus level, although we acknowledge potential differences in TreM assemblages between the European birch species *Betula pendula* and *B. pubescens*, and the American paper birch (*Betula papyrifera*) (personal observations). Another limitation of our study is that we only sampled live trees, even though snags are known to be significant drivers of TreM formation (Larrieu and Cabanettes 2012; Paillet et al. 2019), meaning that TreM assemblages were only partially assessed. Although there were slight differences in TreM inventory size thresholds between our Fennoscandian (Supplementary material: Table S3) and Canadian datasets (Martin et al. 2021a, 2021c), we do not believe these differences undermine the robustness of our findings. For future studies on TreMs in boreal contexts, we recommend adopting the TreM typology specific to boreal and hemiboreal forests (Bütler et al. 2024) and standardizing both tree size inventory thresholds and sampling methodologies.

## Conclusion

This preliminary study, based on a limited number of trees, is to our knowledge one of the first to test the TreM typology proposed by Larrieu et al. (2018) in Fennoscandian boreal forests. Our observations suggest that TreM assemblages in boreal forests are strongly influenced by local plot contexts, including climate, disturbance history, environmental conditions, and both biotic and abiotic factors. Different tree species, namely Scots pine, birch, and aspen, host distinct and complementary TreM assemblages, supporting the value of mixed-species stands for biodiversity conservation in managed forests. Within homogeneous and smaller geographic areas, tree species appear to be a key driver of TreM assemblages, whereas plot context becomes the primary driver across larger geographic areas encompassing diverse forest types and climatic conditions. In contrast to temperate forests, tree diameter did not emerge as a major driver of TreM assemblages in boreal forests. Given the considerable variation in TreM assemblages within the boreal biome, a large sample size is essential to comprehensively assess TreM diversity. A sample of 1000 trees is adequate to evaluate the seven TreM forms, while a larger sample is necessary to capture all fifteen TreM groups.

## Acknowledgements

We would like to thank Michel Goulard, retired from INRAE UMR DYNAFOR, for the data analyses he performed for this paper. For the Canadian data set, we would like to thank Hubert Morin, Nicole J. Fenton, Patricia Raymond, and Yan Boucher for their financial, logistical, and scientific support in making these surveys possible. We would also like to thank all the students and technical staff who helped collect data in the field. For the Scandinavian data set, we are grateful to Björn Nordén of the Norwegian Institute for Nature Research (NINA) for
<figure><img src="image_21.png" /></figure>

his cooperation and advice, and to Elina Sauvain for her help with field data collection. Finally, we are grateful to the two anonymous reviewers for their insightful comments, which contributed to the improvement of the manuscript.

## Data availability statement

The data supporting this study's findings are available from the corresponding author upon request.

## Disclosure statement

No potential conflict of interest was reported by the author(s).

## Authors' contributions

Rita Bütler: Conceptualization, Methodology, Data collection, Resources, Writing (original draft and review & editing). Laurent Larrieu: Conceptualization, Methodology, Resources, Writing (original draft and review & editing). Maxence Martin: Resources, Writing (review & editing). This research has not received any specific grant from any public, commercial or not-for-profit funding body. It was supported by the research institutes with which the authors are affiliated.

## ORCID

Rita Bütler http://orcid.org/0000-0002-8865-8805

Laurent Larrieu http://orcid.org/0000-0002-9050-0281

Maxence Martin http://orcid.org/0000-0002-1384-0514

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