# Toward a common set of functional traits for soil protists

Simone Giachello, Isabel Cantera, Alexis Carteron, Silvio Marta, Cristina

Cipriano, Alessia Guerrieri, Aurélie Bonin, Wilfried Thuiller, Gentile

Francesco Ficetola

► To cite this version:

Simone Giachello, Isabel Cantera, Alexis Carteron, Silvio Marta, Cristina Cipriano, et al. Toward a common set of functional traits for soil protists. Soil Biology and Biochemistry, 2023, 187, pp.109207. 10.1016/j.soilbio.2023.109207. hal-04378523

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Toward a common set of functional traits for soil protists

Simone Giachello<sup>a,b,*</sup>, Isabel Cantera<sup>a</sup>, Alexis Carteron<sup>a,c</sup>, Silvio Marta<sup>a,d</sup>, Cristina Cipriano<sup>e,f</sup>, Alessia Guerrieri<sup>a,g</sup>, Aurélie Bonin<sup>a,g</sup>, Wilfried Thuiller<sup>h</sup>, Gentile Francesco Ficetola<sup>a,h</sup>

ARTICLE INFO

Keywords:

Soil protists

Functional diversity

Traits

Glacier forelands

DNA metabarcoding

A B S T R A C T

Protists are major actors of soil communities and play key roles in shaping food webs, community assembly, and ecosystem processes, yet their functional diversity is understudied. High-throughput sequencing data have revealed their ubiquity and diversity, but lack of standardized traits has hampered the integration of functional information, limiting our understanding of soil ecosystems. Here, we propose a functional framework for soil protists, identify a set of common traits to characterize their functional diversity, and apply the framework on a broad-scale, real-world dataset. We reviewed studies on soil protists to identify the traits used in the literature, and define a framework based on 10 key traits that satisfy two criteria: availability of information, and applicability to most taxa. The framework was tested on a dataset of environmental DNA metabarcoding data from 1123 soil samples collected in 48 glacier forelands worldwide. Traits were assigned to the 570 Molecular Operational Taxonomic Units (MOTUs) detected in our dataset, leading to the production of a global trait-based dataset from glacier forelands. We estimated the functional space of protist communities and evaluated if the selected traits were effective in describing protist diversity. The functional space of protist communities showed that the MOTUs are clustered in three regions, mainly reflecting different nutritional and habitat preferences. The proposed framework is appropriate for multiple applications, including estimation of functional diversity and food web analyses, and provides a basis for ecological studies on soil protists, enabling the functional characterization of this essential but often neglected component of soil biodiversity.

# 1. Introduction

Soil ecosystems harbor more than half of the species of our planet (Anthony et al., 2023). Such impressive biodiversity provides essential services for life on Earth (Bardgett and Van Der Putten, 2014; Delgado-Baquerizo et al., 2020). Each biotic component of the belowground world interacts with the surrounding environment and other soil organisms, deeply influencing key ecosystem functions such as organic matter decomposition, soil structure, as well as aboveground productivity (Decaëns, 2010; Orgiazzi et al., 2016; Crowther et al., 2019). Nonetheless, due to its hidden nature and complexity, the soil biota has historically been understudied and only in the last decades we have

begun to uncover its essential role (Bardgett and Van Der Putten, 2014; Geisen et al., 2019; Guerra et al., 2020). Advances in molecular techniques have enabled ecologists to investigate the communities of micro-organisms that inhabit soil ecosystems, significantly increasing our knowledge of soil communities and the dynamics and processes regulating them (Geisen et al., 2019; Burki et al., 2021). Significant progress has been made for soil micro-organisms but, whereas for bacteria, fungi, and even archaea the number of studies has greatly increased in recent years, studies on protists have lagged behind (Fig. 1; Geisen et al., 2017; Guerra et al., 2020).

Protists have been defined as “a grab bag including anything
eukaryote that is not an animal, land plant, or dikaryon fungus” (Burki

<footnote><sup>a</sup> Department of Environmental Science and Policy, Università degli Studi di Milano, Via Celoria 10, Milano, Italy</footnote>

<footnote><sup>b</sup> University School for Advanced Studies IUSS Pavia. Piazza della Vittoria 15, Pavia, Italy</footnote>

<footnote><sup>c</sup> University of Toulouse, Ecole d'Ingénieurs de PURPAN, UMR INRAE-INPT DYNAFOR, Toulouse, France</footnote>

<footnote><sup>d</sup> Institute of Geosciences and Earth Resources, CNR, Via Moruzzi 1, 56124, Pisa, Italy</footnote>

<footnote><sup>e</sup> Impacts on Agriculture, Forests and Ecosystem Services (IAFES) Division, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viterbo, Italy</footnote>

<footnote><sup>f</sup> National Biodiversity Future Center (NBFC), Palermo, Italy</footnote>

<footnote><sup>g</sup> Argaly, Bâtiment CleanSpace, 354 Voie Magellan, 73800, Sainte-Hélène-du-Lac, France</footnote>

<footnote><sup>h</sup> University Grenoble Alpes, University Savoie Mont Blanc, CNRS, LECA, F-38000, Grenoble, France</footnote>

<footnote>* Corresponding author. Department of Environmental Science and Policy, Università degli Studi di Milano, Via Celoria 10, Milano, Italy.
E-mail address: simone.giachello@unimi.it (S. Giachello).</footnote>
<figure><img src="image_2.png" /></figure>

Toward a common set of functional traits for soil protists

Simone Giachello<sup>a,b,*</sup>, Isabel Cantera<sup>a</sup>, Alexis Carteron<sup>a,c</sup>, Silvio Marta<sup>a,d</sup>, Cristina Cipriano<sup>e,f</sup>, Alessia Guerrieri<sup>a,g</sup>, Aurélie Bonin<sup>a,g</sup>, Wilfried Thuiller<sup>h</sup>, Gentile Francesco Ficetola<sup>a,h</sup>

ARTICLE INFO

Keywords:

Soil protists

Functional diversity

Traits

Glacier forelands

DNA metabarcoding

A B S T R A C T

Protists are major actors of soil communities and play key roles in shaping food webs, community assembly, and ecosystem processes, yet their functional diversity is understudied. High-throughput sequencing data have revealed their ubiquity and diversity, but lack of standardized traits has hampered the integration of functional information, limiting our understanding of soil ecosystems. Here, we propose a functional framework for soil protists, identify a set of common traits to characterize their functional diversity, and apply the framework on a broad-scale, real-world dataset. We reviewed studies on soil protists to identify the traits used in the literature, and define a framework based on 10 key traits that satisfy two criteria: availability of information, and applicability to most taxa. The framework was tested on a dataset of environmental DNA metabarcoding data from 1123 soil samples collected in 48 glacier forelands worldwide. Traits were assigned to the 570 Molecular Operational Taxonomic Units (MOTUs) detected in our dataset, leading to the production of a global trait-based dataset from glacier forelands. We estimated the functional space of protist communities and evaluated if the selected traits were effective in describing protist diversity. The functional space of protist communities showed that the MOTUs are clustered in three regions, mainly reflecting different nutritional and habitat preferences. The proposed framework is appropriate for multiple applications, including estimation of functional diversity and food web analyses, and provides a basis for ecological studies on soil protists, enabling the functional characterization of this essential but often neglected component of soil biodiversity.

1. Introduction

Soil ecosystems harbor more than half of the species of our planet (Anthony et al., 2023). Such impressive biodiversity provides essential services for life on Earth (Bardgett and Van Der Putten, 2014; Delgado-Baquerizo et al., 2020). Each biotic component of the belowground world interacts with the surrounding environment and other soil organisms, deeply influencing key ecosystem functions such as organic matter decomposition, soil structure, as well as aboveground productivity (Decaëns, 2010; Orgiazzi et al., 2016; Crowther et al., 2019). Nonetheless, due to its hidden nature and complexity, the soil biota has historically been understudied and only in the last decades we have

begun to uncover its essential role (Bardgett and Van Der Putten, 2014; Geisen et al., 2019; Guerra et al., 2020). Advances in molecular techniques have enabled ecologists to investigate the communities of micro-organisms that inhabit soil ecosystems, significantly increasing our knowledge of soil communities and the dynamics and processes regulating them (Geisen et al., 2019; Burki et al., 2021). Significant progress has been made for soil micro-organisms but, whereas for bacteria, fungi, and even archaea the number of studies has greatly increased in recent years, studies on protists have lagged behind (Fig. 1; Geisen et al., 2017; Guerra et al., 2020).

Protists have been defined as “a grab bag including anything
eukaryote that is not an animal, land plant, or dikaryon fungus” (Burki

<footnote><sup>a</sup> Department of Environmental Science and Policy, Università degli Studi di Milano, Via Celoria 10, Milano, Italy</footnote>

<footnote><sup>b</sup> University School for Advanced Studies IUSS Pavia. Piazza della Vittoria 15, Pavia, Italy</footnote>

<footnote><sup>c</sup> University of Toulouse, Ecole d'Ingénieurs de PURPAN, UMR INRAE-INPT DYNAFOR, Toulouse, France</footnote>

<footnote><sup>d</sup> Institute of Geosciences and Earth Resources, CNR, Via Moruzzi 1, 56124, Pisa, Italy</footnote>

<footnote><sup>e</sup> Impacts on Agriculture, Forests and Ecosystem Services (IAFES) Division, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viterbo, Italy</footnote>

<footnote><sup>f</sup> National Biodiversity Future Center (NBFC), Palermo, Italy</footnote>

<footnote><sup>g</sup> Argaly, Bâtiment CleanSpace, 354 Voie Magellan, 73800, Sainte-Hélène-du-Lac, France</footnote>

<footnote><sup>h</sup> University Grenoble Alpes, University Savoie Mont Blanc, CNRS, LECA, F-38000, Grenoble, France</footnote>

<footnote>* Corresponding author. Department of Environmental Science and Policy, Università degli Studi di Milano, Via Celoria 10, Milano, Italy.
E-mail address: simone.giachello@unimi.it (S. Giachello).</footnote>
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** a) Number of studies on soil microorganisms (bacteria, fungi, archaea and protists); b) number of functional studies for each taxon; c) proportion of functional studies over the total number of studies for protists. See Supplementary Methods 1 for details on the literature search.</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** a) Number of studies on soil microorganisms (bacteria, fungi, archaea and protists); b) number of functional studies for each taxon; c) proportion of functional studies over the total number of studies for protists. See Supplementary Methods 1 for details on the literature search.</figcaption></figure>
et al., 2021), and include an unparalleled diversity of eukaryotes estimated in millions of species belonging to highly diverse lineages (Orgiazzi et al., 2016; Adl et al., 2019; Burki et al., 2021). Soil protists embrace organisms spanning five orders of magnitude in size, ranging from solitary cells measuring a few micrometers, to species of Amoebozoa forming colonies of several centimeters (Geisen et al., 2017). These organisms are an essential component of soil communities, providing an irreplaceable contribution to all soil functions (Bonkowski et al., 2019; Geisen et al., 2020; Oliverio et al., 2020). Despite their small size, protists are so abundant that their global biomass is estimated as 4 Gt, i.e., twice the biomass of all animals on Earth (Bar-On et al., 2018). Protists exhibit a large diversity of feeding modalities influencing different levels of the ecological food web. Phagotrophic protists regulate microbial populations through active predation, releasing nutrients back into the environment and thus strongly influencing plant growth (Clarholm, 1981; Coûteaux and Darbyshire, 1998; Bonkowski, 2004). Phototrophic protists contribute directly to primary production through carbon fixation (Schmidt et al., 2016). Parasitic protists can control populations of much larger organisms such as plants and animals (Mahé et al., 2017), while saprotrophic protists are fundamental for organic matter degradation (Savory et al., 2015). Nevertheless, our understanding of the role played by protists within soil ecosystems is far from exhaustive (Geisen et al., 2017, 2020).

The traits of organisms are known to be closely linked to ecosystem functioning (Loreau et al., 2001; Cardinale et al., 2012; Naeem et al., 2012). Thus, refined information on their functional diversity is required to deepen our understanding of the relationships between soil protists and ecosystem functions, but also their role in biogeochemical cycles, and how abiotic and biotic drivers shape communities in space and time (Cardinale et al., 2012; Naeem et al., 2012; Briones, 2014; Geisen et al., 2023). Functional diversity represents the variety of morphological, ecological, behavioral, and physiological traits exhibited by different species (Hooper et al., 2005; Cadotte et al., 2011). Despite preliminary efforts to define a functional classification for soil protists and identify functional groups (Coûteaux et al., 1998), functional studies on soil protists remain scarce (Fig. 1). This can be related to the complexity of the study of protists ecology (Geisen et al., 2023), but also to the lack of a conceptual framework and comprehensive databases covering key functional traits (Dumack et al., 2020). So far, publicly available datasets are mostly restricted to a few major taxa such as Cercozoa and Endomyxa (Fiore-Donno et al., 2019; Dumack et al., 2020), phytoplankton (Laplace-Treyture et al., 2021), or a subset of Ciliophora and amoeboid protists (Gulin et al., 2022). Furthermore, the few datasets covering phylogenetically diverse taxa are generally limited to a single functional trait, usually the trophic level (Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021). Nonetheless, a wealth of functional information on protists is available but spread across various sources of the existing literature, including taxonomic articles, functional datasets, and monographs/atlases spanning different taxonomic levels, from phylum (Bahls et al., 2018; Lynn et al., 2018), to family level (Berger, 1999, 2007, 2011; Foissner and Xu, 2007). Still, the absence of standard guidelines or established key functional traits hampers the extraction of information from existing literature.

The aim of this study is to propose a framework for developing a comprehensive database on the functional traits of soil protists that is designed to i) facilitate the retrieval of functional information, ii) accommodate most of soil protist diversity, iii) be exploitable in ecological studies and iv) use consistent terminology. To achieve this, we followed a standardized approach developed for soil fauna (Hedde et al., 2022) and reviewed the literature to define a common set of readily accessible traits to characterize the functional diversity of soil protists, akin to the framework proposed for terrestrial invertebrates (Moretti et al., 2017). To illustrate the efficacy of the proposed framework, we applied it to a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists obtained from the environmental DNA metabarcoding of 1123 soil samples covering a broad range of

environmental conditions and geographic regions.

## 2. Methods

### 2.1. Functional traits review

To review and identify the functional traits generally used in soil protists studies, we performed a literature search in Web of Science (October 21st, 2022) with the following string: TS=(soil* AND protist* AND function* AND trait*) OR TS=(soil* AND protozo* AND function* AND trait*) OR TS=(terrestrial AND protist* AND function* AND trait*) OR TS=(terrestrial AND protozo* AND function* AND trait*). We focused on research articles without imposing temporal constraints, i.e. we covered the period 1944–2022. The abstract of each resulting article was read, and non-relevant studies were discarded (e.g., studies analyzing functional traits of other groups, or studies just mentioning protists). To avoid missing relevant literature not available from the Web of Science, we also inspected the references cited by each of the retained studies to identify additional pertinent works. From the retained literature, we extracted information on article type, year of publication, research topic, location and geographical scale, sampling method, sampling environment, taxa considered, the functional traits and functional categories used, and the source of the functional data (Table S1).

The functional traits found through the review were classified into six broad types (Moretti et al., 2017; Dumack et al., 2020): nutrition, morphology, life-history, physiology, behavior, and habitat. From those traits, we selected for our functional framework the ones that satisfied two main criteria: a) information availability, b) broad applicability. Information availability was evaluated considering the possibility to retrieve functional information in the literature (e.g., availability of trait datasets), while the applicability to a broad range of soil protists was assessed by checking if the traits can be used to characterize multiple protist lineages (Table S2). These two criteria of selection are meant to identify a limited number of traits that are useable to characterize soil protists diversity. In some cases, protists exhibit different characters/behaviors depending on features such as the life stage or the environmental conditions (Archibald et al., 2017; Adl et al., 2019), complicating trait assignment. Such organisms (e.g., a parasite with a free-living flagellate stage for dispersal) can be characterized by all the functional categories it can exhibit (e.g., free-living and endoparasite) using fuzzy-coded dummy variables (de Bello et al., 2021), even though researchers can decide to use the predominant one (e.g., endoparasite), depending on the specific aim of the study.

### 2.2. Application: functional traits of protists from glacier forelands

To illustrate the application of the selected functional traits, we used a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists detected using environmental DNA metabarcoding from 1123 soil samples collected along 48 glacier forelands around the world (Fig. S1). The 48 glacier forelands range from 48°S to 79°N and encompass five continents. Each glacier foreland represents a sequence of dated sites starting from 1 to a maximum of 483 years after glacier retreat (Marta et al., 2021) with a general habitat shift from bare ground to fully vegetated ecosystems (Cantera et al., 2023). MOTUs were derived from the amplification of the eukaryotic marker Euka02 (Guardiola et al., 2015; Taberlet et al., 2018) which amplifies a ~123 bp fragment of the V7 region of the 18S rDNA gene. For details on sample collection, DNA extraction, amplification, sequencing and bioinformatic analyses, see Supplementary Methods 2. After clustering similar sequences (97% threshold; Bonin et al., 2023), a total of 2008 MOTUs belonging to different kingdoms in the Eukaryota domain were detected (Fig. 2). Taxonomy was defined through the NCBI Taxonomy database (Schoch et al., 2020).

We then applied our framework to functionally characterize protist
et al., 2021), and include an unparalleled diversity of eukaryotes estimated in millions of species belonging to highly diverse lineages (Orgiazzi et al., 2016; Adl et al., 2019; Burki et al., 2021). Soil protists embrace organisms spanning five orders of magnitude in size, ranging from solitary cells measuring a few micrometers, to species of Amoebozoa forming colonies of several centimeters (Geisen et al., 2017). These organisms are an essential component of soil communities, providing an irreplaceable contribution to all soil functions (Bonkowski et al., 2019; Geisen et al., 2020; Oliverio et al., 2020). Despite their small size, protists are so abundant that their global biomass is estimated as 4 Gt, i.e., twice the biomass of all animals on Earth (Bar-On et al., 2018). Protists exhibit a large diversity of feeding modalities influencing different levels of the ecological food web. Phagotrophic protists regulate microbial populations through active predation, releasing nutrients back into the environment and thus strongly influencing plant growth (Clarholm, 1981; Coûteaux and Darbyshire, 1998; Bonkowski, 2004). Phototrophic protists contribute directly to primary production through carbon fixation (Schmidt et al., 2016). Parasitic protists can control populations of much larger organisms such as plants and animals (Mahé et al., 2017), while saprotrophic protists are fundamental for organic matter degradation (Savory et al., 2015). Nevertheless, our understanding of the role played by protists within soil ecosystems is far from exhaustive (Geisen et al., 2017, 2020).

The traits of organisms are known to be closely linked to ecosystem functioning (Loreau et al., 2001; Cardinale et al., 2012; Naeem et al., 2012). Thus, refined information on their functional diversity is required to deepen our understanding of the relationships between soil protists and ecosystem functions, but also their role in biogeochemical cycles, and how abiotic and biotic drivers shape communities in space and time (Cardinale et al., 2012; Naeem et al., 2012; Briones, 2014; Geisen et al., 2023). Functional diversity represents the variety of morphological, ecological, behavioral, and physiological traits exhibited by different species (Hooper et al., 2005; Cadotte et al., 2011). Despite preliminary efforts to define a functional classification for soil protists and identify functional groups (Coûteaux et al., 1998), functional studies on soil protists remain scarce (Fig. 1). This can be related to the complexity of the study of protists ecology (Geisen et al., 2023), but also to the lack of a conceptual framework and comprehensive databases covering key functional traits (Dumack et al., 2020). So far, publicly available datasets are mostly restricted to a few major taxa such as Cercozoa and Endomyxa (Fiore-Donno et al., 2019; Dumack et al., 2020), phytoplankton (Laplace-Treyture et al., 2021), or a subset of Ciliophora and amoeboid protists (Gulin et al., 2022). Furthermore, the few datasets covering phylogenetically diverse taxa are generally limited to a single functional trait, usually the trophic level (Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021). Nonetheless, a wealth of functional information on protists is available but spread across various sources of the existing literature, including taxonomic articles, functional datasets, and monographs/atlases spanning different taxonomic levels, from phylum (Bahls et al., 2018; Lynn et al., 2018), to family level (Berger, 1999, 2007, 2011; Foissner and Xu, 2007). Still, the absence of standard guidelines or established key functional traits hampers the extraction of information from existing literature.

The aim of this study is to propose a framework for developing a comprehensive database on the functional traits of soil protists that is designed to i) facilitate the retrieval of functional information, ii) accommodate most of soil protist diversity, iii) be exploitable in ecological studies and iv) use consistent terminology. To achieve this, we followed a standardized approach developed for soil fauna (Hedde et al., 2022) and reviewed the literature to define a common set of readily accessible traits to characterize the functional diversity of soil protists, akin to the framework proposed for terrestrial invertebrates (Moretti et al., 2017). To illustrate the efficacy of the proposed framework, we applied it to a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists obtained from the environmental DNA metabarcoding of 1123 soil samples covering a broad range of

environmental conditions and geographic regions.

## 2. Methods

### 2.1. Functional traits review

To review and identify the functional traits generally used in soil protists studies, we performed a literature search in Web of Science (October 21st, 2022) with the following string: TS=(soil* AND protist* AND function* AND trait*) OR TS=(soil* AND protozo* AND function* AND trait*) OR TS=(terrestrial AND protist* AND function* AND trait*) OR TS=(terrestrial AND protozo* AND function* AND trait*). We focused on research articles without imposing temporal constraints, i.e. we covered the period 1944–2022. The abstract of each resulting article was read, and non-relevant studies were discarded (e.g., studies analyzing functional traits of other groups, or studies just mentioning protists). To avoid missing relevant literature not available from the Web of Science, we also inspected the references cited by each of the retained studies to identify additional pertinent works. From the retained literature, we extracted information on article type, year of publication, research topic, location and geographical scale, sampling method, sampling environment, taxa considered, the functional traits and functional categories used, and the source of the functional data (Table S1).

The functional traits found through the review were classified into six broad types (Moretti et al., 2017; Dumack et al., 2020): nutrition, morphology, life-history, physiology, behavior, and habitat. From those traits, we selected for our functional framework the ones that satisfied two main criteria: a) information availability, b) broad applicability. Information availability was evaluated considering the possibility to retrieve functional information in the literature (e.g., availability of trait datasets), while the applicability to a broad range of soil protists was assessed by checking if the traits can be used to characterize multiple protist lineages (Table S2). These two criteria of selection are meant to identify a limited number of traits that are useable to characterize soil protists diversity. In some cases, protists exhibit different characters/behaviors depending on features such as the life stage or the environmental conditions (Archibald et al., 2017; Adl et al., 2019), complicating trait assignment. Such organisms (e.g., a parasite with a free-living flagellate stage for dispersal) can be characterized by all the functional categories it can exhibit (e.g., free-living and endoparasite) using fuzzy-coded dummy variables (de Bello et al., 2021), even though researchers can decide to use the predominant one (e.g., endoparasite), depending on the specific aim of the study.

### 2.2. Application: functional traits of protists from glacier forelands

To illustrate the application of the selected functional traits, we used a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists detected using environmental DNA metabarcoding from 1123 soil samples collected along 48 glacier forelands around the world (Fig. S1). The 48 glacier forelands range from 48°S to 79°N and encompass five continents. Each glacier foreland represents a sequence of dated sites starting from 1 to a maximum of 483 years after glacier retreat (Marta et al., 2021) with a general habitat shift from bare ground to fully vegetated ecosystems (Cantera et al., 2023). MOTUs were derived from the amplification of the eukaryotic marker Euka02 (Guardiola et al., 2015; Taberlet et al., 2018) which amplifies a ~123 bp fragment of the V7 region of the 18S rDNA gene. For details on sample collection, DNA extraction, amplification, sequencing and bioinformatic analyses, see Supplementary Methods 2. After clustering similar sequences (97% threshold; Bonin et al., 2023), a total of 2008 MOTUs belonging to different kingdoms in the Eukaryota domain were detected (Fig. 2). Taxonomy was defined through the NCBI Taxonomy database (Schoch et al., 2020).

We then applied our framework to functionally characterize protist
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Taxonomic composition of MOTUs detected with the general Eukaryota marker Euka02 (Guardiola et al., 2015) of all soil samples collected for the dataset; numbers indicate the number of MOTUs within each taxonomic group. a) All MOTUs identified at least at the kingdom level divided in the four kingdoms Protista, Fungi, Metazoa and Plantae. b) Taxonomic breakdown of MOTUs belonging to the kingdom Protista.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Taxonomic composition of MOTUs detected with the general Eukaryota marker Euka02 (Guardiola et al., 2015) of all soil samples collected for the dataset; numbers indicate the number of MOTUs within each taxonomic group. a) All MOTUs identified at least at the kingdom level divided in the four kingdoms Protista, Fungi, Metazoa and Plantae. b) Taxonomic breakdown of MOTUs belonging to the kingdom Protista.</figcaption></figure>
communities in proglacial soils. To assign functional traits, we searched for information on nutrition, morphology, behavior, life-history, and habitat preferences for MOTUs belonging to 27 phyla/clades and to six supergroups (i.e., Alveolata, Amoebozoa, Archaeplastida, Opisthokonta, Rhizaria, Stramenopiles; Fig. 2). In so doing, we conducted an extensive literature search for each taxon included in the dataset using references obtained through our review, plus additional specific searches in Google, Google Scholar and Web of Science. We gathered information from a total of 197 references (176 scientific articles including 17 datasets, 15 books/guides/atlas, and six websites; Table S1). The taxonomic level of identification of MOTUs varied, with some MOTUs identified at fine taxonomic resolution (e.g., Vorticella sphaeroidalis or Euglypha rotunda), and others identified at coarser resolution (e.g., Cercozoa or Bacillariophyta). Therefore, the assignment of functional traits depended on the taxonomic level of identification of each MOTU. MOTUs that could not be characterized by a unique functional category due to the lack of taxonomic resolution (e.g., MOTU identified as Cercomonadidae), were described using two or more functional categories separated by “or” (e.g., for Cercomonadidae, feeding mode: bacterivore_or_omnivore).

To visualize how the traits proposed in our framework describe the community of protists from the proglacial soil dataset, we estimated the functional space through a principal coordinates analysis (PCoA) using the R package “ape” (Paradis and Schliep, 2019). To build the functional space, we merged MOTUs with the same taxonomic identification, and excluded MOTUs with a taxonomic assignment coarser than family. The remaining MOTUs were characterized by every trait defined in our framework. Categorical traits were coded as dummy variables (de Bello et al., 2021).

Length was log-transformed and scaled between 0 and 1. Dissimilarities among MOTUs were estimated using the Gower distance weighted through the “gawdis” R function to uniform the contribution of different traits (de Bello et al., 2021). Finally, we tested the correlation between the first two PCoA axes and functional traits through the function envfit() from the R package “vegan” (Oksanen et al., 2022). Data manipulation and statistical analyses were done using the R platform v.4.2.2.

## 3. Results

### 3.1. Review of functional traits

The Web of Science search resulted in 51 scientific articles, but only 22 actually focused on protists. Inspection of articles and of references therein yielded 10 additional references focusing on functional traits of soil protists. Of the 32 studies, one presents a functional database (Dumack et al., 2020), while the remaining ones are primary research. All retained studies were published between 2015 and 2022, with an increase in publication rate during the last three years (77% of studies published between 2020 and 2022). Studies encompassed different approaches, such as tests of relationships between functional traits and environmental factors (21 studies), network analyses (eight), identification of community assembly processes (four), microcosm experiments (four), and one comparative analysis. Most studies were carried out in Europe (15 studies), followed by Asia (five), South America (two), and Oceania (two); four studies sampled multiple continents. Six studies

<caption>**Table 1**</caption>

Overview of the set of the 10 key traits included in the framework with a short description of each trait, the categories composing them, and taxa for which they have been used.

<table><thead><tr><th>Type</th><th>Trait</th><th>Description</th><th>Categories</th><th>Taxa</th><th>References</th></tr></thead><tbody><tr><td rowspan="2">Nutrition</td><td>Trophic level</td><td>Position of an organism in a food web</td><td>consumer; parasite; autotroph</td><td>community</td><td>Voss et al., 2019; Nguyen et al., 2020, 2021; Oliverio et al., 2020; Seppey et al., 2020; Chen et al., 2021; Mazel et al., 2022; Singer et al., 2021</td></tr><tr><td>Feeding mode</td><td>Group of organisms exploiting analogous food resources</td><td>bacterivore; omnivore; eukaryovore; animal parasite; plant parasite; other parasite; saprotroph; histophagous</td><td>Cercozoa; Endomyxa</td><td>Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020; Roshan et al., 2021</td></tr><tr><td rowspan="4">Morphology</td><td>Body size (length/width/ volume)</td><td>Multiple measures giving an indication of the dimension of an organism</td><td>Continuous traits</td><td>community</td><td>Xiong et al., 2018; Schulz et al., 2019; Santos et al., 2020; Ritter et al., 2021; Zhang et al., 2021</td></tr><tr><td>Shell</td><td>Protective structure usually composed by proteins and self-secreted minerals</td><td>naked; silica; organic</td><td>testate amoebae</td><td>Fournier et al., 2015, 2016; Song et al., 2018</td></tr><tr><td>Locomotion structures</td><td>Appendages involved in locomotion</td><td>flagella; pseudopodia; pseudopodia and flagella; cilia; none</td><td>Chlorophyta Ciliophora community Cercozoa; Endomyxa;</td><td>Fang et al. (2021) Krztoń and Kosiba, 2020 Luan et al., 2020; Aslani et al., 2022 Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020</td></tr><tr><td>Lifestyle</td><td>Living modality of an organism</td><td>free-living; sessile; endoparasite</td><td>amoeboid Cercozoa; Endomyxa amoeboid Cercozoa; Endomyxa Ciliophora; amoeboid community Ciliophora; amoeboid</td><td>Gulin et al. (2022) Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020 Gulin et al. (2022) Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020 Gulin et al. (2022) Voss et al. (2019) Gulin et al. (2022)</td></tr><tr><td rowspan="2">Life history</td><td>Life form</td><td>Level of organization of an organism</td><td>solitary; colonial; multicellular</td><td>amoeboid</td><td>No studies</td></tr><tr><td>Resting cyst</td><td>Dormant life stage with thick shell</td><td>presence/absence</td><td>NA</td><td>No studies</td></tr><tr><td rowspan="2">Habitat</td><td>Sporulation</td><td>Spores for reproduction and dispersal</td><td>presence/absence</td><td>NA</td><td>No studies</td></tr><tr><td>Habitat preferences</td><td>Environments where the species has been sampled</td><td>terrestrial; freshwater; ubiquitous; marine</td><td>Cercozoa; Endomyxa Chlorophyta Ciliophora; amoeboid</td><td>Dumack et al. (2020) Fang et al. (2021) Gulin et al. (2022)</td></tr></tbody></table>
communities in proglacial soils. To assign functional traits, we searched for information on nutrition, morphology, behavior, life-history, and habitat preferences for MOTUs belonging to 27 phyla/clades and to six supergroups (i.e., Alveolata, Amoebozoa, Archaeplastida, Opisthokonta, Rhizaria, Stramenopiles; Fig. 2). In so doing, we conducted an extensive literature search for each taxon included in the dataset using references obtained through our review, plus additional specific searches in Google, Google Scholar and Web of Science. We gathered information from a total of 197 references (176 scientific articles including 17 datasets, 15 books/guides/atlas, and six websites; Table S1). The taxonomic level of identification of MOTUs varied, with some MOTUs identified at fine taxonomic resolution (e.g., Vorticella sphaeroidalis or Euglypha rotunda), and others identified at coarser resolution (e.g., Cercozoa or Bacillariophyta). Therefore, the assignment of functional traits depended on the taxonomic level of identification of each MOTU. MOTUs that could not be characterized by a unique functional category due to the lack of taxonomic resolution (e.g., MOTU identified as Cercomonadidae), were described using two or more functional categories separated by “or” (e.g., for Cercomonadidae, feeding mode: bacterivore_or_omnivore).

To visualize how the traits proposed in our framework describe the community of protists from the proglacial soil dataset, we estimated the functional space through a principal coordinates analysis (PCoA) using the R package “ape” (Paradis and Schliep, 2019). To build the functional space, we merged MOTUs with the same taxonomic identification, and excluded MOTUs with a taxonomic assignment coarser than family. The remaining MOTUs were characterized by every trait defined in our framework. Categorical traits were coded as dummy variables (de Bello

et al., 2021). Length was log-transformed and scaled between 0 and 1. Dissimilarities among MOTUs were estimated using the Gower distance weighted through the “gawdis” R function to uniform the contribution of different traits (de Bello et al., 2021). Finally, we tested the correlation between the first two PCoA axes and functional traits through the function envfit() from the R package “vegan” (Oksanen et al., 2022). Data manipulation and statistical analyses were done using the R platform v.4.2.2.

### 3. Results

#### 3.1. Review of functional traits

The Web of Science search resulted in 51 scientific articles, but only 22 actually focused on protists. Inspection of articles and of references therein yielded 10 additional references focusing on functional traits of soil protists. Of the 32 studies, one presents a functional database (Dumack et al., 2020), while the remaining ones are primary research. All retained studies were published between 2015 and 2022, with an increase in publication rate during the last three years (77% of studies published between 2020 and 2022). Studies encompassed different approaches, such as tests of relationships between functional traits and environmental factors (21 studies), network analyses (eight), identification of community assembly processes (four), microcosm experiments (four), and one comparative analysis. Most studies were carried out in Europe (15 studies), followed by Asia (five), South America (two), and Oceania (two); four studies sampled multiple continents. Six studies

<caption>**Table 1**</caption>

Overview of the set of the 10 key traits included in the framework with a short description of each trait, the categories composing them, and taxa for which they have been used.

<table><thead><tr><th>Type</th><th>Trait</th><th>Description</th><th>Categories</th><th>Taxa</th><th>References</th></tr></thead><tbody><tr><td rowspan="3">Nutrition</td><td>Trophic level</td><td>Position of an organism in a food web</td><td>consumer; parasite; autotroph</td><td>community</td><td>Voss et al., 2019; Nguyen et al., 2020, 2021; Oliverio et al., 2020; Seppey et al., 2020; Chen et al., 2021; Mazel et al., 2022; Singer et al., 2021</td></tr><tr><td>Feeding mode</td><td>Group of organisms exploiting analogous food resources</td><td>bacterivore; omnivore; eukaryovore; animal parasite; plant parasite; other parasite; saprotroph; histophagous</td><td>Cercozoa; Endomyxa</td><td>Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020; Roshan et al., 2021</td></tr><tr><td></td><td></td><td></td><td>community</td><td>Xiong et al., 2018; Schulz et al., 2019; Santos et al., 2020; Ritter et al., 2021; Zhang et al., 2021</td></tr><tr><td rowspan="4">Morphology</td><td>Body size (length/width/ volume)</td><td>Multiple measures giving an indication of the dimension of an organism</td><td>Continuous traits</td><td>testate amoebae</td><td>Fournier et al., 2015, 2016; Song et al., 2018</td></tr><tr><td>Shell</td><td>Protective structure usually composed by proteins and self-secreted minerals</td><td>naked; silica; organic</td><td>Chlorophyta Ciliophora community Cercozoa; Endomyxa;</td><td>Fang et al. (2021) Krztoń and Kosiba, 2020 Luan et al., 2020; Aslani et al., 2022 Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020</td></tr><tr><td>Locomotion structures</td><td>Appendages involved in locomotion</td><td>flagella; pseudopodia; pseudopodia and flagella; cilia; none</td><td>amoeboid Cercozoa; Endomyxa amoeboid Cercozoa; Endomyxa Ciliophora; amoeboid community Ciliophora; amoeboid</td><td>Gulin et al. (2022) Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020 Gulin et al. (2022) Fiore-Donno et al., 2019, 2020, 2022; Dumack et al., 2020 Gulin et al. (2022) Voss et al. (2019) Gulin et al. (2022)</td></tr><tr><td>Lifestyle</td><td>Living modality of an organism</td><td>free-living; sessile; endoparasite</td><td>amoeboid community Ciliophora; amoeboid</td><td>Voss et al. (2019) Gulin et al. (2022)</td></tr><tr><td rowspan="2">Life history</td><td>Life form</td><td>Level of organization of an organism</td><td>solitary; colonial; multicellular</td><td>NA</td><td>No studies</td></tr><tr><td>Resting cyst</td><td>Dormant life stage with thick shell</td><td>presence/absence</td><td>NA</td><td>No studies</td></tr><tr><td rowspan="2">Habitat</td><td>Sporulation</td><td>Spores for reproduction and dispersal</td><td>presence/absence</td><td>NA</td><td>No studies</td></tr><tr><td>Habitat preferences</td><td>Environments where the species has been sampled</td><td>terrestrial; freshwater; ubiquitous; marine</td><td>Cercozoa; Endomyxa Chlorophyta Ciliophora; amoeboid</td><td>Dumack et al. (2020) Fang et al. (2021) Gulin et al. (2022)</td></tr></tbody></table>
identified protists based on their morphological features, 21 used mo-
lecular approaches, and one combined both approaches. Regarding the
targeted taxa, 17 articles considered the protist community as a whole,
six focused on Cercozoa, five on testate amoebae, three on Ciliophora,
two on Oomycota and one on Chlorophyta. Most studies considered
nutrition traits (24 studies) and morphology (15 studies), whereas
behavioral and physiological traits were included in only seven and two
studies, respectively (Table 1). Our review identified 28 distinct traits
for the functional characterization of soil protists (Table S2), distributed
into five broad types: nutrition (six traits), morphology (11 traits),
physiology (two traits), behavior (five traits), and habitat (four traits).

Through the application of the selection criteria (data availability and applicability), we identified a set of functional traits enabling us to describe most of protist diversity with the data available in the literature (Table S2). Below, we describe the eight functional traits obtained from the selection, including two additional life-history traits (i.e., sporulation and resting cyst) that were not considered in the selected articles, but could be relevant to describe the variation in life history and persistence under specific environmental conditions (Geisen et al., 2018). For each trait, we report the definition, ecological relevance, functional categories (for qualitative traits), availability in the literature, and critical aspects. Given the presence of inconsistent terminology for the same traits, we selected the most commonly used terms in the available literature (summarized in Table 1).

3.1.1. Nutrition

Nutrition describes dietary habits, synthesizing the consumer-resource interaction. Information on nutrition is essential to analyze predator-prey dynamics, build food webs, and test relationships with environmental drivers (Briones, 2014; Bonkowski et al., 2019; Potapov et al., 2022). Considering the high diversity of nutrition modalities within protists, we considered two functional traits with different levels of precision. First, the “trophic level” (Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021) represents general information that allows for the discrimination of three broad trophic categories (consumer, parasite, and autotroph). Subsequently, the “feeding mode” allows for a more detailed identification of dietary habits (Fiore-Donno et al., 2019; Dumack et al., 2020; Zhang et al., 2021).

3.1.1.1. Trophic level

3.1.1.1.1. **Definition.** The trophic level indicates the position of an organism in a trophic web, based on feeding relationships and energy transfer. Trophic modalities can be characterized by a first broad discrimination between heterotrophs and autotrophs (Voss et al., 2019), but heterotrophic protists can be further distinguished in phagotrophs (i. e., consumers) and parasites (Bonkowski et al., 2019).

3.1.1.1.2. *Ecological relevance.* The trophic level has been often used to characterize community assembly of soil protists (Singer et al., 2021), verify relationships with environmental factors (Seppey et al., 2020) or detect community changes along elevational gradients (Mazel et al., 2022).

3.1.1.1.3. Functional categories. Three main trophic categories are generally considered (Oliverio et al., 2020; Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021):

a) Consumer: heterotrophic protists feeding through phagocytosis.

b) Parasite: heterotrophic protists living at the expense of another organism.

c) Autotroph: a non-heterotrophic protist, typically a phototrophic or- ganism that produces energy through photosynthesis.

3.1.1.1.4. Availability in the literature. A comprehensive dataset reporting trophic levels of all protist taxa can be found in Singer et al. (2021), whereas Laplace-Treyture et al. (2021) published a detailed functional dataset for phytoplankton.

3.1.1.1.5. *Critical aspects.* Due to its coarse characterization, the

trophic level is not appropriate for detailed analyses of the trophic
composition of communities, or to infer specific biotic interactions.
Furthermore, several taxa can have two trophic levels (e.g., both con-
sumer and autotroph) or are able to switch between different trophic
levels (Singer et al., 2021).

3.1.1.2. Feeding mode

3.1.1.2.1. **Definition.** The feeding mode identifies a group of organisms exploiting analogous food resources (Bonkowski et al., 2019).

3.1.1.2.2. **Ecological relevance.** Grouping protists in a few well-defined feeding modes is pivotal to understand community assembly (Roshan et al., 2021), test relations among feeding groups and environmental factors (Fiore-Donno et al., 2019, 2020, 2022), infer biotic interactions (e.g., predator-prey), and reconstruct food webs (Briones, 2014; Geisen and Bonkowski, 2018; Potapov, 2022). The assignment of a specific feeding mode is also essential to study key soil nutrient dynamics such as the microbial loop (Bonkowski and Clarholm, 2012) or alternative pathways for nutrient cycling (Seppey et al., 2017; Geisen et al., 2020).

3.1.1.2.3. Functional categories. We use the functional categories reported by Dumack et al. (2020) to discriminate among seven feeding modes, adding the categories “histrophagous” and “saprotroph” (Lynn, 2008; Adl et al., 2019).

a) Bacterivore: phagotroph feeding exclusively on prokaryotes.

b) Eukaryvore: phagotroph feeding exclusively on eukaryotes (algae, fungi, other protists, and small metazoans).

c) Omnivore: phagotroph feeding on both prokaryotes and eukaryotes.

d) Animal parasite: protist living at the expense of a metazoan host.

e) Plant parasite: protist living at the expense of a plant host.

f) Other parasites: protists living at the expense of neither a metazoan
nor a plant (typically another protist).

g) Histrophagous: protist feeding on tissues of unhealthy bodies of metazoans.

h) Saprotroph: protist feeding on decaying organic matter.

i) Autotroph.

3.1.1.2.4. Availability in literature. The feeding mode is one of the most widely used functional traits for soil protists. It can be found in available functional datasets (Adl et al., 2019; Dumack et al., 2020; Calderón-Sanou et al., 2022; Gulin et al., 2022), and can be deducted from monographies or original description articles reporting the food sources exploited by a species or higher taxonomic groups. A synopsis of feeding habits of protists is also found in a recent review on feeding habits of soil consumers (Potapov et al., 2022).

3.1.1.2.5. *Critical aspects.* Although a good amount of data is available concerning feeding preference of soil protists, for many taxa uncertainty remains regarding their actual food sources and further analyses are needed. For instance, recent studies have discovered that several taxa traditionally defined as strictly bacterivorous actually are omnivores (Dumack et al., 2020). Finally, some species can drastically switch their food sources during their life cycle. For instance, *Chlorella* green algae are usually phototrophs, but under specific environmental conditions they can parasitize animals (Jagielski et al., 2019).

3.1.2. Morphology

Morphology includes all traits describing the size and shape of an
organism and its structural features. Morphological traits can be quan-
titative such as body size, or qualitative such as the presence of a shell,
its composition, and the type of structures used for locomotion. Size
information is useful to understand functional roles in the community,
the potentially exploited microhabitat, and to infer prey-predator in-
teractions (Potapov, 2022). Regarding qualitative traits, major groups
such as Ciliophora, Cercozoa, or Amoebozoa have been traditionally
described using the terms “ciliates”, “flagellate”, “amoeba”, or “amoe-
boflagellate”, often coupled with information regarding the presence
identified protists based on their morphological features, 21 used mo-
lecular approaches, and one combined both approaches. Regarding the
targeted taxa, 17 articles considered the protist community as a whole,
six focused on Cercozoa, five on testate amoebae, three on Ciliophora,
two on Oomycota and one on Chlorophyta. Most studies considered
nutrition traits (24 studies) and morphology (15 studies), whereas
behavioral and physiological traits were included in only seven and two
studies, respectively (Table 1). Our review identified 28 distinct traits
for the functional characterization of soil protists (Table S2), distributed
into five broad types: nutrition (six traits), morphology (11 traits),
physiology (two traits), behavior (five traits), and habitat (four traits).

Through the application of the selection criteria (data availability and applicability), we identified a set of functional traits enabling us to describe most of protist diversity with the data available in the literature (Table S2). Below, we describe the eight functional traits obtained from the selection, including two additional life-history traits (i.e., sporulation and resting cyst) that were not considered in the selected articles, but could be relevant to describe the variation in life history and persistence under specific environmental conditions (Geisen et al., 2018). For each trait, we report the definition, ecological relevance, functional categories (for qualitative traits), availability in the literature, and critical aspects. Given the presence of inconsistent terminology for the same traits, we selected the most commonly used terms in the available literature (summarized in Table 1).

3.1.1. Nutrition

Nutrition describes dietary habits, synthesizing the consumer-resource interaction. Information on nutrition is essential to analyze predator-prey dynamics, build food webs, and test relationships with environmental drivers (Briones, 2014; Bonkowski et al., 2019; Potapov et al., 2022). Considering the high diversity of nutrition modalities within protists, we considered two functional traits with different levels of precision. First, the “trophic level” (Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021) represents general information that allows for the discrimination of three broad trophic categories (consumer, parasite, and autotroph). Subsequently, the “feeding mode” allows for a more detailed identification of dietary habits (Fiore-Donno et al., 2019; Dumack et al., 2020; Zhang et al., 2021).

3.1.1.1. Trophic level

3.1.1.1.1. **Definition.** The trophic level indicates the position of an organism in a trophic web, based on feeding relationships and energy transfer. Trophic modalities can be characterized by a first broad discrimination between heterotrophs and autotrophs (Voss et al., 2019), but heterotrophic protists can be further distinguished in phagotrophs (i. e., consumers) and parasites (Bonkowski et al., 2019).

3.1.1.1.2. *Ecological relevance.* The trophic level has been often used to characterize community assembly of soil protists (Singer et al., 2021), verify relationships with environmental factors (Seppey et al., 2020) or detect community changes along elevational gradients (Mazel et al., 2022).

3.1.1.1.3. Functional categories. Three main trophic categories are generally considered (Oliverio et al., 2020; Seppey et al., 2020; Mazel et al., 2022; Singer et al., 2021):

a) Consumer: heterotrophic protists feeding through phagocytosis.

b) Parasite: heterotrophic protists living at the expense of another organism.

c) Autotroph: a non-heterotrophic protist, typically a phototrophic or- ganism that produces energy through photosynthesis.

3.1.1.1.4. Availability in the literature. A comprehensive dataset reporting trophic levels of all protist taxa can be found in Singer et al. (2021), whereas Laplace-Treyture et al. (2021) published a detailed functional dataset for phytoplankton.

3.1.1.1.5. *Critical aspects.* Due to its coarse characterization, the

trophic level is not appropriate for detailed analyses of the trophic
composition of communities, or to infer specific biotic interactions.
Furthermore, several taxa can have two trophic levels (e.g., both con-
sumer and autotroph) or are able to switch between different trophic
levels (Singer et al., 2021).

3.1.1.2. Feeding mode

3.1.1.2.1. **Definition.** The feeding mode identifies a group of organisms exploiting analogous food resources (Bonkowski et al., 2019).

3.1.1.2.2. **Ecological relevance.** Grouping protists in a few well-defined feeding modes is pivotal to understand community assembly (Roshan et al., 2021), test relations among feeding groups and environmental factors (Fiore-Donno et al., 2019, 2020, 2022), infer biotic interactions (e.g., predator-prey), and reconstruct food webs (Briones, 2014; Geisen and Bonkowski, 2018; Potapov, 2022). The assignment of a specific feeding mode is also essential to study key soil nutrient dynamics such as the microbial loop (Bonkowski and Clarholm, 2012) or alternative pathways for nutrient cycling (Seppey et al., 2017; Geisen et al., 2020).

3.1.1.2.3. Functional categories. We use the functional categories reported by Dumack et al. (2020) to discriminate among seven feeding modes, adding the categories “histrophagous” and “saprotroph” (Lynn, 2008; Adl et al., 2019).

a) Bacterivore: phagotroph feeding exclusively on prokaryotes.

b) Eukaryvore: phagotroph feeding exclusively on eukaryotes (algae, fungi, other protists, and small metazoans).

c) Omnivore: phagotroph feeding on both prokaryotes and eukaryotes.

d) Animal parasite: protist living at the expense of a metazoan host.

e) Plant parasite: protist living at the expense of a plant host.

f) Other parasites: protists living at the expense of neither a metazoan
nor a plant (typically another protist).

g) Histrophagous: protist feeding on tissues of unhealthy bodies of metazoans.

h) Saprotroph: protist feeding on decaying organic matter.

i) Autotroph.

3.1.1.2.4. Availability in literature. The feeding mode is one of the most widely used functional traits for soil protists. It can be found in available functional datasets (Adl et al., 2019; Dumack et al., 2020; Calderón-Sanou et al., 2022; Gulin et al., 2022), and can be deducted from monographies or original description articles reporting the food sources exploited by a species or higher taxonomic groups. A synopsis of feeding habits of protists is also found in a recent review on feeding habits of soil consumers (Potapov et al., 2022).

3.1.1.2.5. *Critical aspects.* Although a good amount of data is available concerning feeding preference of soil protists, for many taxa uncertainty remains regarding their actual food sources and further analyses are needed. For instance, recent studies have discovered that several taxa traditionally defined as strictly bacterivorous actually are omnivores (Dumack et al., 2020). Finally, some species can drastically switch their food sources during their life cycle. For instance, *Chlorella* green algae are usually phototrophs, but under specific environmental conditions they can parasitize animals (Jagielski et al., 2019).

3.1.2. Morphology

Morphology includes all traits describing the size and shape of an
organism and its structural features. Morphological traits can be quan-
titative such as body size, or qualitative such as the presence of a shell,
its composition, and the type of structures used for locomotion. Size
information is useful to understand functional roles in the community,
the potentially exploited microhabitat, and to infer prey-predator in-
teractions (Potapov, 2022). Regarding qualitative traits, major groups
such as Ciliophora, Cercozoa, or Amoebozoa have been traditionally
described using the terms “ciliates”, “flagellate”, “amoeba”, or “amoe-
boflagellate”, often coupled with information regarding the presence
3.1.2.5.2. **Functional categories.** a) Solitary: most of the life cycle is spent as solitary unicellular individuals.

b) Colonial: organism capable of organizing in colonies of multiple unicellular individuals.

c) Multicellular: organism composed of multiple cells.

**3.1.2.5.3. Availability in literature.** Information about life forms is often indicated in original description articles but datasets reporting this information are scarce (but see Laplace-Treyture et al., 2021 for phytoplankton; Gulin et al., 2022 for Ciliophora).

**3.1.2.5.4. Critical aspects.** Even though the definition of a solitary unicellular protist is generally unambiguous, some taxa can create large multinucleate structures (e.g., plasmodia of Myxomycetes; Archibald et al., 2017). Here we considered these taxa as "solitary" since they are neither colonial nor multicellular.

### 3.1.3. Life-history

Life-history type represents traits defining the ontogeny, life stages, and reproductive modalities of an organism. Protists show many types of life cycles, each one characterized by peculiar life stages. To limit the number of categories and ease interpretations, we defined two binary traits describing the presence/absence of ecologically relevant life stages, namely spores and resting cysts. Spores are related to reproduction and dispersal, while resistant stages enable organisms to survive in unsuitable conditions (Geisen et al., 2018).

#### 3.1.3.1. Resting cyst

**3.1.3.1.1. Definition.** The resting or resistant cyst is a life stage of many protists, in which the organism produces a thick shell around its body and enters a dormant phase.

**3.1.3.1.2. Ecological relevance.** Encystment can enable protists to survive unfavorable environmental conditions, such as drought or extreme temperatures, helping life in harsh environments (Geisen et al., 2017).

**3.1.3.1.3. Functional categories.** Present/Absent: ability to produce a resting cyst or not.

**3.1.3.1.4. Availability in literature.** For many soil protists, the resting cyst is a significant life stage, thus information on its presence is usually available in taxonomic articles when resting cysts were observed. Laplace-Treyture et al. (2021) gathered information on the presence of a resting cyst is for algae (but see Geisen et al., 2018 for other few examples).

**3.1.3.1.5. Critical aspects.** The presence of resting cysts can only be assessed through visual observation, thus defining with certainty whether a species is unable to produce resting cysts is challenging, as their absence could be caused by lack of observation. So far, the ability to produce resting cysts as a functional trait is seldom considered in ecological studies.

#### 3.1.3.2. Sporulation

**3.1.3.2.1. Definition.** Sporulation involves the production of spores by organisms and is typically related to reproduction and dispersal (Geisen et al., 2018). Soil protists often produce "sporocysts", i.e., spores covered by a protection layer, enabling survival under hostile conditions.

**3.1.3.2.2. Ecological relevance.** Sporulation can improve survival and dispersal potential (e.g. pioneer species; Geisen et al., 2018).

**3.1.3.2.3. Functional categories.** Present/Absent: ability to produce spores or not.

**3.1.3.2.4. Availability in literature.** The ability to produce spores is usually shared at the phylum (or higher) level, therefore handbooks (Archibald et al., 2017) and generic taxonomic articles (Adl et al., 2019) are helpful to find information on this trait.

**3.1.3.2.5. Critical aspects.** So far, sporulation is seldom considered in ecological studies and datasets (but see Geisen et al., 2018 for some examples).

### 3.1.4. Habitat

Although habitat preferences are not always considered in common sets of functional traits (Moretti et al., 2017; Brousseau et al., 2018), discriminating protists inhabiting marine, freshwater, or terrestrial environments provides key information on their adaptations. The definition of habitat for protists is different from that of plants and metazoans. Due to their small size, most freshwater protists can inhabit terrestrial environments with high moisture, where they live within thin water layers, thus many protists inhabit both terrestrial and freshwater environments (Burki et al., 2021). Nonetheless, some species show stronger specialization to specific habitats. Furthermore, metabarcoding data from freshwater ecosystems revealed the presence of taxa traditionally assumed to be specialists of marine habitats (Simon et al., 2015), hence the presence of these protists in soil communities cannot be excluded.

#### 3.1.4.1. Habitat preferences

**3.1.4.1.1. Definition.** Type of environments in which the species have been sampled (Burki et al., 2021).

**3.1.4.1.2. Functional categories.** a) Terrestrial: found exclusively in terrestrial environments.

b) Freshwater: found exclusively in freshwater environments.

c) Marine: found exclusively in marine environments.

d) Ubiquitous: found in both terrestrial and aquatic environments.

**3.1.4.1.3. Availability in literature.** Information on the typical habitat is usually present in taxonomic articles and has been summarized in some datasets (Dumack et al., 2020; Gulin et al., 2022).

**3.1.4.1.4. Critical aspects.** Data on the type of exploited habitats typically refers to where a specific taxon has been historically found, thus information available in the literature is probably incomplete (Simon et al., 2015).

### 3.2. Application of the framework to soil protists from glacier forelands

The eDNA metabarcoding of 1123 soil samples yielded 570 MOTUs assigned to protists, encompassing six major supergroups (Alveolata, Amoebozoa, Archaeplastida, Opisthokonta, Stramenopiles, Rhizaria; Fig. 2). The most detected phyla were represented by Cercozoa (194 MOTUs, ~34%) and Ciliophora (191 MOTUs, ~34%) followed by Endomyxa, Bacillariophyta and Chrysophyta (each representing 4% of MOTUs). The taxonomic resolution of detected MOTUs was highly variable, ranging from species to phylum levels. Specifically, 297 MOTUs were identified at the genus level or better, 119 at the family level, 53 at the order level, 33 at the class level, and 68 at the phylum level. After consulting 197 scientific references, we were able to functionally characterize 99.7% of MOTUs identified at the genus level or better, 98.3% of MOTUs identified at the family level, and all MOTUs identified at coarser levels. Due to coarse taxonomic assignment, some MOTUs received an uncertain assignment at one or more categorical traits (trophic level: uncertainty for 1.6% of MOTUs; feeding mode: 27.4%; shell: 9.1%; locomotion structures: 19.1%; lifestyle: 8.2%; life form: 9.3%; resting cysts: 21.6%).

The functional composition of protist communities from proglacial soils was dominated by consumers, mostly omnivores, and was further characterized by the abundance of solitary, free living, ciliates and flagellates, without a shell (Fig. S2a; Fig. S2b). Protists able to produce a resting cyst represented 40% of the total, whereas 15% of MOTUs were known to produce spores. The body length range covered four orders of magnitude, spanning from 2.5 µm (Siluania monomastiga) to the >6 cm of the multicellular golden alga Hydrurus foetidus (Fig. S2b).

The ordination of MOTUs in the functional space showed that communities of proglacial soils are not evenly distributed across the whole functional space (Fig. 3) but clustered in three regions, mostly reflecting the three broad trophic levels: consumers, parasites, and freshwater
3.1.2.5.2. **Functional categories.** a) Solitary: most of the life cycle is spent as solitary unicellular individuals.

b) Colonial: organism capable of organizing in colonies of multiple unicellular individuals.

c) Multicellular: organism composed of multiple cells.

**3.1.2.5.3. Availability in literature.** Information about life forms is often indicated in original description articles but datasets reporting this information are scarce (but see Laplace-Treyture et al., 2021 for phytoplankton; Gulin et al., 2022 for Ciliophora).

**3.1.2.5.4. Critical aspects.** Even though the definition of a solitary unicellular protist is generally unambiguous, some taxa can create large multinucleate structures (e.g., plasmodia of Myxomycetes; Archibald et al., 2017). Here we considered these taxa as "solitary" since they are neither colonial nor multicellular.

### 3.1.3. Life-history

Life-history type represents traits defining the ontogeny, life stages, and reproductive modalities of an organism. Protists show many types of life cycles, each one characterized by peculiar life stages. To limit the number of categories and ease interpretations, we defined two binary traits describing the presence/absence of ecologically relevant life stages, namely spores and resting cysts. Spores are related to reproduction and dispersal, while resistant stages enable organisms to survive in unsuitable conditions (Geisen et al., 2018).

#### 3.1.3.1. Resting cyst

**3.1.3.1.1. Definition.** The resting or resistant cyst is a life stage of many protists, in which the organism produces a thick shell around its body and enters a dormant phase.

**3.1.3.1.2. Ecological relevance.** Encystment can enable protists to survive unfavorable environmental conditions, such as drought or extreme temperatures, helping life in harsh environments (Geisen et al., 2017).

**3.1.3.1.3. Functional categories.** Present/Absent: ability to produce a resting cyst or not.

**3.1.3.1.4. Availability in literature.** For many soil protists, the resting cyst is a significant life stage, thus information on its presence is usually available in taxonomic articles when resting cysts were observed. Laplace-Treyture et al. (2021) gathered information on the presence of a resting cyst is for algae (but see Geisen et al., 2018 for other few examples).

**3.1.3.1.5. Critical aspects.** The presence of resting cysts can only be assessed through visual observation, thus defining with certainty whether a species is unable to produce resting cysts is challenging, as their absence could be caused by lack of observation. So far, the ability to produce resting cysts as a functional trait is seldom considered in ecological studies.

#### 3.1.3.2. Sporulation

**3.1.3.2.1. Definition.** Sporulation involves the production of spores by organisms and is typically related to reproduction and dispersal (Geisen et al., 2018). Soil protists often produce "sporocysts", i.e., spores covered by a protection layer, enabling survival under hostile conditions.

**3.1.3.2.2. Ecological relevance.** Sporulation can improve survival and dispersal potential (e.g. pioneer species; Geisen et al., 2018).

**3.1.3.2.3. Functional categories.** Present/Absent: ability to produce spores or not.

**3.1.3.2.4. Availability in literature.** The ability to produce spores is usually shared at the phylum (or higher) level, therefore handbooks (Archibald et al., 2017) and generic taxonomic articles (Adl et al., 2019) are helpful to find information on this trait.

**3.1.3.2.5. Critical aspects.** So far, sporulation is seldom considered in ecological studies and datasets (but see Geisen et al., 2018 for some examples).

### 3.1.4. Habitat

Although habitat preferences are not always considered in common sets of functional traits (Moretti et al., 2017; Brousseau et al., 2018), discriminating protists inhabiting marine, freshwater, or terrestrial environments provides key information on their adaptations. The definition of habitat for protists is different from that of plants and metazoans. Due to their small size, most freshwater protists can inhabit terrestrial environments with high moisture, where they live within thin water layers, thus many protists inhabit both terrestrial and freshwater environments (Burki et al., 2021). Nonetheless, some species show stronger specialization to specific habitats. Furthermore, metabarcoding data from freshwater ecosystems revealed the presence of taxa traditionally assumed to be specialists of marine habitats (Simon et al., 2015), hence the presence of these protists in soil communities cannot be excluded.

#### 3.1.4.1. Habitat preferences

**3.1.4.1.1. Definition.** Type of environments in which the species have been sampled (Burki et al., 2021).

**3.1.4.1.2. Functional categories.** a) Terrestrial: found exclusively in terrestrial environments.

b) Freshwater: found exclusively in freshwater environments.

c) Marine: found exclusively in marine environments.

d) Ubiquitous: found in both terrestrial and aquatic environments.

**3.1.4.1.3. Availability in literature.** Information on the typical habitat is usually present in taxonomic articles and has been summarized in some datasets (Dumack et al., 2020; Gulin et al., 2022).

**3.1.4.1.4. Critical aspects.** Data on the type of exploited habitats typically refers to where a specific taxon has been historically found, thus information available in the literature is probably incomplete (Simon et al., 2015).

### 3.2. Application of the framework to soil protists from glacier forelands

The eDNA metabarcoding of 1123 soil samples yielded 570 MOTUs assigned to protists, encompassing six major supergroups (Alveolata, Amoebozoa, Archaeplastida, Opisthokonta, Stramenopiles, Rhizaria; Fig. 2). The most detected phyla were represented by Cercozoa (194 MOTUs, ~34%) and Ciliophora (191 MOTUs, ~34%) followed by Endomyxa, Bacillariophyta and Chrysophyta (each representing 4% of MOTUs). The taxonomic resolution of detected MOTUs was highly variable, ranging from species to phylum levels. Specifically, 297 MOTUs were identified at the genus level or better, 119 at the family level, 53 at the order level, 33 at the class level, and 68 at the phylum level. After consulting 197 scientific references, we were able to functionally characterize 99.7% of MOTUs identified at the genus level or better, 98.3% of MOTUs identified at the family level, and all MOTUs identified at coarser levels. Due to coarse taxonomic assignment, some MOTUs received an uncertain assignment at one or more categorical traits (trophic level: uncertainty for 1.6% of MOTUs; feeding mode: 27.4%; shell: 9.1%; locomotion structures: 19.1%; lifestyle: 8.2%; life form: 9.3%; resting cysts: 21.6%).

The functional composition of protist communities from proglacial soils was dominated by consumers, mostly omnivores, and was further characterized by the abundance of solitary, free living, ciliates and flagellates, without a shell (Fig. S2a; Fig. S2b). Protists able to produce a resting cyst represented 40% of the total, whereas 15% of MOTUs were known to produce spores. The body length range covered four orders of magnitude, spanning from 2.5 µm (Siluania monomastiga) to the >6 cm of the multicellular golden alga Hydrurus foetidus (Fig. S2b).

The ordination of MOTUs in the functional space showed that communities of proglacial soils are not evenly distributed across the whole functional space (Fig. 3) but clustered in three regions, mostly reflecting the three broad trophic levels: consumers, parasites, and freshwater
<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Functional space of protist communities in proglacial soils. Black dots represent MOTUs; centroids of each category of the categorical traits are represented by larger dots colored by trait type; full dots are the categories significantly related to the first two PCoA axes (Table S3). The arrow indicates the direction and the strength of the correlation between body length and the first and second PCoA axes. Shaded areas represent the density of MOTUs computed with a two-dimensional Kernel density estimation.</figcaption></figure>

autotrophs. A further distinction was represented by habitat prefer- ences, with the typically terrestrial or ubiquitous MOTUs localized around the space characterized by negative values of the first PCoA axis, whereas freshwater MOTUs were positively related to the first PCoA axis. For all traits considered, most categories were significantly related to the first two PCoA axes (Table S3). The first axis of the functional space explained 40.7% of variation and mainly represented traits belonging to types habitat and behavior while the second axis (21.7% of variation) mostly represented morphological, nutritional and life history traits (Fig. 3). The majority of MOTUs were localized in the region of consumers (low values of the first PCoA axis), within which they were mainly discerned by morphological traits. Freshwater autotrophs were positively related to the first PCoA axis and associated with a sessile lifestyle. Parasites were negatively related to both the first and second PCoA axes. This region of the functional space showed a significant as- sociation with the endoparasitic lifestyle and the presence of sporulation.

# 4. Discussion

## 4.1. Knowledge gaps on functional traits of soil protists

The advancement of sequencing techniques is opening a door to the secretive belowground world and is boosting the study of its amazing biodiversity. Soil protists remain understudied compared to other key microorganisms, despite increasing interest in recent years (Fig. 1). This rise in interest was likely driven by the publication of seminal works that provided large amounts of functional information on protists (Adl et al., 2019; Dumack et al., 2020). Indeed, half of the studies that used func- tional data from the literature were based on these two aforementioned publications. As observed for most biodiversity research (Martin et al., 2012), there is a severe geographical bias with most studies carried out in Europe, while hyperdiverse tropical areas remain understudied.

Consequently, the availability of functional information is uneven with most data referring to European taxa (Fiore-Donno et al., 2019; Lap- lace-Treyture et al., 2021; Gulin et al., 2022), even though information remains incomplete also for taxa found in Europe (Geisen et al., 2018). So far, protists lack of a comprehensive trait repository similar to those available for other taxa (e.g., TRY for plants, FAPROTAX for bacteria, or FUNGuild/NEMAGuild for fungi and nematods; Kattge et al., 2011; Louca et al., 2016; Nguyen et al., 2016), limiting the potential of func- tional analyses and ecological interpretation (Geisen et al., 2018). In fact, most functional studies on soil protists have focused on one or a few traits, often limited to nutrition and morphology – the trait types for which most data are available. While a single-trait approach can reveal how specific features or behaviors are related to environmental factors (Oliverio et al., 2020; Fiore-Donno and Bonkowski, 2021; Singer et al., 2021) or ecological gradients (Mazel et al., 2022), the use of multiple traits is required to investigate the complexity of biotic communities and understand the role their inhabitants play in providing ecosystem functions (Lavorel et al., 2013; Krause et al., 2014; Potapov, 2022).

## 4.2. A common framework to describe the functional diversity of soil protists

To address the need for more accessible and standardized functional information, we proposed a framework consisting of a set of 10 key traits that summarize current knowledge on soil protist functional diversity (Table 1). The aim of this framework is to promote reproducibility and comparability across existing datasets and repositories, representing a first step toward the development of a common trait database for soil protists. Given that protists are an extremely heterogeneous group, it is debatable whether one comprehensive framework can effectively describe such diverse organisms or, alternatively, a specific functional characterization would be required for each clade/group (e.g., Cil- iophora, Cercozoa, testate amoebae). We argue that each approach has
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Functional space of protist communities in proglacial soils. Black dots represent MOTUs; centroids of each category of the categorical traits are represented by larger dots colored by trait type; full dots are the categories significantly related to the first two PCoA axes (Table S3). The arrow indicates the direction and the strength of the correlation between body length and the first and second PCoA axes. Shaded areas represent the density of MOTUs computed with a two-dimensional Kernel density estimation.</figcaption></figure>

autotrophs. A further distinction was represented by habitat prefer- ences, with the typically terrestrial or ubiquitous MOTUs localized around the space characterized by negative values of the first PCoA axis, whereas freshwater MOTUs were positively related to the first PCoA axis. For all traits considered, most categories were significantly related to the first two PCoA axes (Table S3). The first axis of the functional space explained 40.7% of variation and mainly represented traits belonging to types habitat and behavior while the second axis (21.7% of variation) mostly represented morphological, nutritional and life history traits (Fig. 3). The majority of MOTUs were localized in the region of consumers (low values of the first PCoA axis), within which they were mainly discerned by morphological traits. Freshwater autotrophs were positively related to the first PCoA axis and associated with a sessile lifestyle. Parasites were negatively related to both the first and second PCoA axes. This region of the functional space showed a significant as- sociation with the endoparasitic lifestyle and the presence of sporulation.

# 4. Discussion

## 4.1. Knowledge gaps on functional traits of soil protists

The advancement of sequencing techniques is opening a door to the secretive belowground world and is boosting the study of its amazing biodiversity. Soil protists remain understudied compared to other key microorganisms, despite increasing interest in recent years (Fig. 1). This rise in interest was likely driven by the publication of seminal works that provided large amounts of functional information on protists (Adl et al., 2019; Dumack et al., 2020). Indeed, half of the studies that used func- tional data from the literature were based on these two aforementioned publications. As observed for most biodiversity research (Martin et al., 2012), there is a severe geographical bias with most studies carried out in Europe, while hyperdiverse tropical areas remain understudied.

Consequently, the availability of functional information is uneven with most data referring to European taxa (Fiore-Donno et al., 2019; Lap- lace-Treyture et al., 2021; Gulin et al., 2022), even though information remains incomplete also for taxa found in Europe (Geisen et al., 2018). So far, protists lack of a comprehensive trait repository similar to those available for other taxa (e.g., TRY for plants, FAPROTAX for bacteria, or FUNGuild/NEMAGuild for fungi and nematods; Kattge et al., 2011; Louca et al., 2016; Nguyen et al., 2016), limiting the potential of func- tional analyses and ecological interpretation (Geisen et al., 2018). In fact, most functional studies on soil protists have focused on one or a few traits, often limited to nutrition and morphology – the trait types for which most data are available. While a single-trait approach can reveal how specific features or behaviors are related to environmental factors (Oliverio et al., 2020; Fiore-Donno and Bonkowski, 2021; Singer et al., 2021) or ecological gradients (Mazel et al., 2022), the use of multiple traits is required to investigate the complexity of biotic communities and understand the role their inhabitants play in providing ecosystem functions (Lavorel et al., 2013; Krause et al., 2014; Potapov, 2022).

## 4.2. A common framework to describe the functional diversity of soil protists

To address the need for more accessible and standardized functional information, we proposed a framework consisting of a set of 10 key traits that summarize current knowledge on soil protist functional diversity (Table 1). The aim of this framework is to promote reproducibility and comparability across existing datasets and repositories, representing a first step toward the development of a common trait database for soil protists. Given that protists are an extremely heterogeneous group, it is debatable whether one comprehensive framework can effectively describe such diverse organisms or, alternatively, a specific functional characterization would be required for each clade/group (e.g., Cil- iophora, Cercozoa, testate amoebae). We argue that each approach has
its own purpose. On one hand, clade-specific traits are often used in
studies at fine taxonomic resolution, because they allow for a more
refined characterization that permits to functionally discriminate
similar species or even individuals within the same species. This
approach can be used to identify ecological processes (e.g., environ-
mental selection) structuring the composition of specific taxonomic
groups (Fiore-Donno et al., 2019), and can enable the detection of local
trait adaptation following habitat restoration (Gulin et al., 2022).
Clade-specific approaches are also used in palaeoecological studies to
reconstruct past environmental conditions (Fournier et al., 2015; Mar-
cisz et al., 2020). However, the clade-specific approach lacks the po-
tential to perform multi-taxa analyses and is not appropriate for datasets
with broad taxonomic scope (i.e., high-throughput sequencing data
based on generalist markers). In this case, a common set of key traits can
facilitate a multi-taxa approach which is essential to explain community
assembly (Calderón-Sanou et al., 2022), to reveal the functions and
services provided by soil ecosystems (Donald et al., 2021) and to
construct ecological networks such as belowground food webs (Potapov,
2022). A multi-taxa approach is frequent in metabarcoding studies (69%
of reviewed studies; Table S1), which often use generalist markers
providing an overall characterization of protist communities but often
show limited taxonomic resolution. A common framework is thus
pivotal to exploit the full potential of these datasets and will facilitate
relating detected organisms with ecosystem processes and functions (de
Bello et al., 2010; Brousseau et al., 2018). The generality and flexibility
of this approach can also encourage studies in less investigated areas of
the world, reducing the observed geographical bias.

Along with the multi-taxa approach, the common set of traits pro-
posed in our framework enables us to investigate the multifaceted
variation of traits in soil protist communities. This is particularly helpful
to identify patterns of co-variation in functional traits across taxa (i.e.,
trait syndromes; Raffard et al., 2017), favouring the discrimination be-
tween traits constrained by phylogeny and those related to local envi-
ronmental conditions and ecological trade-offs (Ellers et al., 2018). A set
of multiple traits can also be used to estimate the functional space of the
community, which can lead to the identification of broad evolutionary
or ecological trajectories represented by the main dimensions of varia-
tion in the trait space, such as what was done for size and leaf economics
spectrum for plants (Díaz et al., 2016), reproductive strategies for
mammals (Bielby et al., 2007) or the maturity index for nematodes
(Bongers, 1990). The combination of a multi-taxa and multi-trait
approach can also help estimating the relative position and links of an
organism in a food web, accounting for traits such as diet, dimensions, or
physical protection (Potapov, 2022). A multi-trait approach is particu-
larly important for soil protists, as this group encompasses highly
distinct evolutionary lineages. For instance, considering a single trait
such as “life-form”, which discriminates between solitary and colonial
protists, leads to grouping phylogenetically distant protists with
differing ecological functions. The integration of multiple traits like
feeding mode, morphology, lifestyle, and habitat preferences enables to
construct a functional space in which protist communities are well
discriminated into distinct clusters. These clusters may suggest that a
few traits can effectively summarize the functional diversity of protist
communities but could also reflect a strong phylogenetic signal of traits
(Goberna and Verdú, 2016).

The application of the framework to a metabarcoding dataset pro-
vided a practical example of how these traits can be suitable for high-
throughput sequencing data. Nonetheless, characterizing a MOTU
identified only to the genus or the family level requires specific adjust-
ments to apply functional information defined at the species level. Such
a process is different between trait types. Continuous traits, such as body
size, can be defined by averaging the values (e.g., mean length) from the
multiple species belonging to high-level MOTUs (e.g., genus or family),
whereas categorical traits can be transformed in fuzzy dummy variables
(de Bello et al., 2021) to account for the functional variability across
species composing the MOTU (i.e., species from the same taxonomic unit

exhibiting diverse ecological features). Due to the lack of a common trait
repository, trait assignment required an extensive literature search. The
search was particularly challenging for body size data, which are usually
only found in taxonomic articles where the species or genus is described
or revised. To facilitate data retrieval in future studies, we report the
main datasets available for different traits and taxonomic groups,
highlighting the ecological relevance and potential issues for each trait
(see Results section 3.1). Despite these challenges, the framework
allowed us to develop a functional dataset on proglacial soils, repre-
senting a starting point toward the creation of a common trait re-
pository. However, the use of a single generic eukaryotic marker limited
the ability to target specific taxonomic groups (e.g., Amoebozoa or
Heterolobosea; Geisen et al., 2023) and, therefore, the dataset presented
is not complete, as widespread soil protist taxa are missing.

5. Conclusion

Exhaustive understanding of soil biodiversity requires the develop-
ment of multi-taxa approaches to the analysis of protist traits. The
widespread adoption of high-throughput sequencing techniques has
boosted the study of soil communities and will greatly increase the
availability of information in the coming years. To complete the puzzle,
we now need to effectively couple the taxonomic data with functional
information, in order to obtain a more comprehensive view on the
processes structuring belowground ecosystems. The common set of key
traits proposed here can be applied to high-throughput sequencing data
and is based on traits for which information is available in the existing
literature, thus can help achieving these tasks. Nonetheless, further ef-
forts are needed to make functional information on a large number of
taxa promptly available, to measure functional data on taxa from the
whole globe, and to adapt raw functional information to the specific
features of high-throughput sequencing data. We encourage researchers
to build upon the proposed framework and functional dataset while
tailoring it to their specific research needs.

Data accessibility statement

Raw sequencing data is deposited in Zenodo (10.5281/zenodo.6620359). The functional dataset is available in figshare at the following Digital Object Identifier: 10.1016/j.soilbio.2023.109207.

Author contributions

SG, IC, AC and GFF conceived the ideas and designed methodology;
SG and CC performed the literature review; SM, AG, AB and GFF
collected and analyzed the environmental DNA metabarcoding data; SG,
IC and AC analyzed the data; SG led the writing of the manuscript. All
authors contributed critically to the drafts and gave final approval for
publication.

Declaration of competing interest

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.

Data availability

Raw sequencing data is deposited in Zenodo (10.5281/zenodo.6620359). The functional dataset is available in figshare at the following Digital Object Identifier: 10.1016/j.soilbio.2023.109207

Acknowledgements

This study was funded by the European Research Council under the
European Community Horizon 2020 Programme, Grant Agreement no.
its own purpose. On one hand, clade-specific traits are often used in
studies at fine taxonomic resolution, because they allow for a more
refined characterization that permits to functionally discriminate
similar species or even individuals within the same species. This
approach can be used to identify ecological processes (e.g., environ-
mental selection) structuring the composition of specific taxonomic
groups (Fiore-Donno et al., 2019), and can enable the detection of local
trait adaptation following habitat restoration (Gulin et al., 2022).
Clade-specific approaches are also used in palaeoecological studies to
reconstruct past environmental conditions (Fournier et al., 2015; Mar-
cisz et al., 2020). However, the clade-specific approach lacks the po-
tential to perform multi-taxa analyses and is not appropriate for datasets
with broad taxonomic scope (i.e., high-throughput sequencing data
based on generalist markers). In this case, a common set of key traits can
facilitate a multi-taxa approach which is essential to explain community
assembly (Calderón-Sanou et al., 2022), to reveal the functions and
services provided by soil ecosystems (Donald et al., 2021) and to
construct ecological networks such as belowground food webs (Potapov,
2022). A multi-taxa approach is frequent in metabarcoding studies (69%
of reviewed studies; Table S1), which often use generalist markers
providing an overall characterization of protist communities but often
show limited taxonomic resolution. A common framework is thus
pivotal to exploit the full potential of these datasets and will facilitate
relating detected organisms with ecosystem processes and functions (de
Bello et al., 2010; Brousseau et al., 2018). The generality and flexibility
of this approach can also encourage studies in less investigated areas of
the world, reducing the observed geographical bias.

Along with the multi-taxa approach, the common set of traits pro-
posed in our framework enables us to investigate the multifaceted
variation of traits in soil protist communities. This is particularly helpful
to identify patterns of co-variation in functional traits across taxa (i.e.,
trait syndromes; Raffard et al., 2017), favouring the discrimination be-
tween traits constrained by phylogeny and those related to local envi-
ronmental conditions and ecological trade-offs (Ellers et al., 2018). A set
of multiple traits can also be used to estimate the functional space of the
community, which can lead to the identification of broad evolutionary
or ecological trajectories represented by the main dimensions of varia-
tion in the trait space, such as what was done for size and leaf economics
spectrum for plants (Díaz et al., 2016), reproductive strategies for
mammals (Bielby et al., 2007) or the maturity index for nematodes
(Bongers, 1990). The combination of a multi-taxa and multi-trait
approach can also help estimating the relative position and links of an
organism in a food web, accounting for traits such as diet, dimensions, or
physical protection (Potapov, 2022). A multi-trait approach is particu-
larly important for soil protists, as this group encompasses highly
distinct evolutionary lineages. For instance, considering a single trait
such as “life-form”, which discriminates between solitary and colonial
protists, leads to grouping phylogenetically distant protists with
differing ecological functions. The integration of multiple traits like
feeding mode, morphology, lifestyle, and habitat preferences enables to
construct a functional space in which protist communities are well
discriminated into distinct clusters. These clusters may suggest that a
few traits can effectively summarize the functional diversity of protist
communities but could also reflect a strong phylogenetic signal of traits
(Goberna and Verdú, 2016).

The application of the framework to a metabarcoding dataset pro-
vided a practical example of how these traits can be suitable for high-
throughput sequencing data. Nonetheless, characterizing a MOTU
identified only to the genus or the family level requires specific adjust-
ments to apply functional information defined at the species level. Such
a process is different between trait types. Continuous traits, such as body
size, can be defined by averaging the values (e.g., mean length) from the
multiple species belonging to high-level MOTUs (e.g., genus or family),
whereas categorical traits can be transformed in fuzzy dummy variables
(de Bello et al., 2021) to account for the functional variability across
species composing the MOTU (i.e., species from the same taxonomic unit

exhibiting diverse ecological features). Due to the lack of a common trait
repository, trait assignment required an extensive literature search. The
search was particularly challenging for body size data, which are usually
only found in taxonomic articles where the species or genus is described
or revised. To facilitate data retrieval in future studies, we report the
main datasets available for different traits and taxonomic groups,
highlighting the ecological relevance and potential issues for each trait
(see Results section 3.1). Despite these challenges, the framework
allowed us to develop a functional dataset on proglacial soils, repre-
senting a starting point toward the creation of a common trait re-
pository. However, the use of a single generic eukaryotic marker limited
the ability to target specific taxonomic groups (e.g., Amoebozoa or
Heterolobosea; Geisen et al., 2023) and, therefore, the dataset presented
is not complete, as widespread soil protist taxa are missing.

5. Conclusion

Exhaustive understanding of soil biodiversity requires the develop-
ment of multi-taxa approaches to the analysis of protist traits. The
widespread adoption of high-throughput sequencing techniques has
boosted the study of soil communities and will greatly increase the
availability of information in the coming years. To complete the puzzle,
we now need to effectively couple the taxonomic data with functional
information, in order to obtain a more comprehensive view on the
processes structuring belowground ecosystems. The common set of key
traits proposed here can be applied to high-throughput sequencing data
and is based on traits for which information is available in the existing
literature, thus can help achieving these tasks. Nonetheless, further ef-
forts are needed to make functional information on a large number of
taxa promptly available, to measure functional data on taxa from the
whole globe, and to adapt raw functional information to the specific
features of high-throughput sequencing data. We encourage researchers
to build upon the proposed framework and functional dataset while
tailoring it to their specific research needs.

Data accessibility statement

Raw sequencing data is deposited in Zenodo (10.5281/zenodo.6620359). The functional dataset is available in figshare at the following Digital Object Identifier: 10.1016/j.soilbio.2023.109207.

Author contributions

SG, IC, AC and GFF conceived the ideas and designed methodology;
SG and CC performed the literature review; SM, AG, AB and GFF
collected and analyzed the environmental DNA metabarcoding data; SG,
IC and AC analyzed the data; SG led the writing of the manuscript. All
authors contributed critically to the drafts and gave final approval for
publication.

Declaration of competing interest

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.

Data availability

Raw sequencing data is deposited in Zenodo (10.5281/zenodo.6620359). The functional dataset is available in figshare at the following Digital Object Identifier: 10.1016/j.soilbio.2023.109207

Acknowledgements

This study was funded by the European Research Council under the
European Community Horizon 2020 Programme, Grant Agreement no.
772284 (IceCommunities). This research was also supported by Bio-
diversa+, the European Biodiversity Partnership under the 2021–2022
BiodivProtect call for research proposals, co-funded by the Euro-
pean Commission (Grant Agreement no. 101052342 'PrioriticeVan-
ishing habitats: conservation priorities for glacier-related biodiversity
threatened by climate change') and with the funding organizations MUR
and ANR. SG is funded by the Italian national inter-university PhD
course in Sustainable Development and Climate change.

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.soilbio.2023.109207.

**References**

Adl, S., Girard, V., Breton, G., Lak, M., Maharning, A., Mills, A., Perrichot, V.,
Trionnaire, M., Vullo, R., Néraudeau, D., 2011. Reconstructing the soil food web of a
100 million-year-old forest: the case of the mid-Cretaceous fossils in the amber of
Charentes (SW France). Soil Biology and Biochemistry 43, 726–735. https://doi.org/
10.1016/j.soilbio.2010.12.003.

Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S., Berney, C.,
Brown, M.W., Burki, F., Cárdenas, P., Cepíčka, I., Chistyakova, L., del Campo, J.,
Dunthorn, M., Edvardsen, B., Eglit, Y., Guillou, L., Hampl, V., Heiss, A.A.,
Hoppenrath, M., James, T.Y., Karnkowska, A., Karpov, S., Kim, E., Kolisko, M.,
Kudryavtsev, A., Lahr, D.J.G., Lara, E., Le Gall, L., Lynn, D.H., Mann, D.G.,
Massana, R., Mitchell, E.A.D., Morrow, C., Park, J.S., Pawlowski, J.W., Powell, M.J.,
Richter, D.J., Rueckert, S., Shadwick, L., Shimano, S., Spiegel, F.W., Torruella, G.,
Youssef, N., Zlatogursky, V., Zhang, Q., 2019. Revisions to the classification,
nomenclature, and diversity of eukaryotes. The Journal of Eukaryotic Microbiology
66, 4–119. https://doi.org/10.1111/jeu.12691.

Anthony, M.A., Bender, S.F., van der Heijden, M.G.A., 2023. Enumerating soil
biodiversity. Proceedings of the National Academy of Sciences 120. https://doi.org/
10.1073/pnas.2304663120.

Archibald, J.M., Simpson, A.G.B., Slamovits, C.H., 2017. Handbook of the protists. In:
Handbook of the Protists, second ed. Springer. https://doi.org/10.1007/978-3-319-
32669-6.

Aslani, F., Geisen, S., Ning, D., Tedersoo, L., Bahram, M., 2022. Towards revealing the
global diversity and community assembly of soil eukaryotes. Ecology Letters 25,
65–76. https://doi.org/10.1111/ele.13904.

Bahls, L., Boynton, B., Johnston, B., 2018. Atlas of diatoms (Bacillariophyta) from diverse
habitats in remote regions of western Canada. PhytoKeys 186, 1–186. https://doi.
org/10.3897/phytokeys.105.23806.

Bardgett, R.D., Van Der Putten, W.H., 2014. Belowground biodiversity and ecosystem
functioning. Nature 515, 505–511. https://doi.org/10.1038/nature13855.

Bar-On, Y.M., Phillips, R., Milo, R., 2018. The biomass distribution on Earth. Proceedings
of the National Academy of Sciences of the United States of America 115,
6506–6511. https://doi.org/10.1073/pnas.1711842115.

Berger, H., 2011. Monograph of the Gonostomatidae and Kahliviidae (Ciliophora,
Hypotricha). Springer.

Berger, H., 2007. Monograph of the Urostyloidea (Ciliophora, Hypotricha). Springer.

Berger, H., 1999. Monograph of the Oxytrichidae (Ciliophora, Hypotrichia). Springer.

Bielby, J., Mace, G.M., Bininda-Emonds, O.R.P., Cardillo, M., Gittleman, J.L., Jones, K.E.,
Orde, C.M.D., Purvis, A., 2007. The fast-slow continuum in mammalian life history:
an empirical reevaluation. The American Naturalist 169, 748–757. https://doi.org/
10.1086/516847.

Bongers, T., 1990. The maturity index: an ecological measure of environmental
disturbance based on nematode species composition. Oecologia 83, 14–19. https://
doi.org/10.1007/BF00324627.

Bonin, A., Guerrieri, A., Ficetola, G.F., 2023. Optimal sequence similarity thresholds for
clustering of molecular operational taxonomic units in DNA metabarcoding studies.
Molecular Ecology Resources 23, 368–381. https://doi.org/10.1111/1755-
0998.13709.

Bonkowski, M., 2004. Protozoa and plant growth: the microbial loop in soil revisited.
New Phytologist 162, 617–631. https://doi.org/10.1111/j.1469-8137.2004.01066-
x.

Bonkowski, M., Clarholm, M., 2012. Stimulation of plant growth through interactions of
bacteria and protozoa: testing the auxiliary microbial loop hypothesis. Acta
Protozoologica 51, 237–247. https://doi.org/10.4467/16890027AP.12.019.0765.

Bonkowski, M., Dumack, K., Fiore-Donno, A.M., 2019. The protists in soil – a token of
untold eukaryotic diversity. In: Van Elsas, J.D., Trevors, J.T., Rosado, A.S.,
Nannipieri, P. (Eds.), Modern Soil Microbiology. CRC Press, Boca Raton, FL, USA,
pp. 125–140.

Briones, M.J.I., 2014. Soil fauna and soil functions: a jigsaw puzzle. Frontiers in
Environmental Science 2, 1–22. https://doi.org/10.3389/fenvs.2014.00007.

Brousseau, P.M., Gravel, D., Handa, I.T., 2018. On the development of a predictive
functional trait approach for studying terrestrial arthropods. Journal of Animal
Ecology 87, 1209–1220. https://doi.org/10.1111/1365-2656.12830.

Burki, F., Sandin, M.M., Jamy, M., 2021. Diversity and ecology of protists revealed by
metabarcoding. Current Biology 31, R1267–R1280. https://doi.org/10.1016/j.
cub.2021.07.066.

Cadotte, M.W., Carscadden, K., Mirothchick, N., 2011. Beyond species: functional
diversity and the maintenance of ecological processes and services. Journal of
Applied Ecology 48, 1079–1087. https://doi.org/10.1111/j.1365-2664.2011.02048.
x.

Calderón-Sanou, I., Zinger, L., Hedde, M., Martínez-Almoyna, C., Sallارد, A., Renaud, J.,
Gielly, L., Khedim, N., Lionnet, C., Ohlmann, M., Consortium, O., Münkemüller, T.,
Thuiller, W., 2022. Energy and physiological tolerance explain multi-trophic soil
diversity in temperate mountains. Diversity and Distributions 1–16. https://doi.org/
10.1111/ddi.13529.

Cantera, I., Carteron, A., Guerrieri, A., Marta, S., Bonin, A., Ambrosini, R., Anthelme, F.,
Azzoni, R., Almond, P., Alviz Gazitúa, P., Cauvy-fraunié, Ceballos Lievano, J.,
Chand, P., Chand Sarma, M., Clague, J., Alejo Cochachín Rapre, J., Compostella, L.,
Encarnación, R.C., Dangles, O., Eger, A., Erokhin, S., Franzetti, A., Gielly, L., Gili, F.,
Gobbi, M., Hagvar, S., Khedim, N., Peyre, G., Pittino, F., Rabatel, A., Urseitova, N.,
Yang, Y., Zaginaev, V., Zerboni, A., Zimmer, A., Taberlet, P., Diolaïuti, G.,
Poulenard, J., Thuiller, W., Caccianiga, M., Ficetola, F., 2023. The importance of
species addition versus replacement varies over succession in plant communities
after glacial retreat. PREPRINT (Version 1). Available at: Research Square https://
doi.org/10.21203/rs.3.rs-2482972/v1.

Cardinale, B.J., Duffy, J.E., Gonzalez, A., Hooper, D.U., Perrings, C., Venail, P.,
Narwani, A., MacE, G.M., Tilman, D., Wardle, D.A., Kinzig, A.P., Daily, G.C.,
Loreau, M., Grace, J.B., Larigauderie, A., Srivastava, D.S., Naemst, S., 2012.
Biodiversity loss and its impact on humanity. Nature 486, 59–67. https://doi.org/
10.1038/nature11148.

Cavalier-Smith, T., van der Heyden, S., 2007. Molecular phylogeny, scale evolution and
taxonomy of centrohelid heliozoa. Molecular Phylogenetics and Evolution 44,
1186–1203. https://doi.org/10.1016/j.mjyte.2007.04.019.

Chen, B., Xiong, W., Qi, J., Pan, H., Chen, S., Peng, Z., Gao, H., Zhang, L., Jiang, Y.,
Wei, G., Jiao, S., 2021. Trophic interrelationships drive the biogeography of
prostistan community in agricultural ecosystems. Soil Biology and Biochemistry 163.
doi.org/10.1016/j.soilbio.2021.108445.

Clarholm, M., 1981. Protozoan grazing of bacteria in soil-impact and importance.
Microbial Ecology 7, 343–350. https://doi.org/10.1007/BF02341429.

Coúteaux, M.-M., Darbyshire, J.F., 1998. Functional diversity amongst soil protozoa.
Applied Soil Ecology 10, 229–237. https://doi.org/10.1016/S0929-1393(98)00122-
x.

Coúteaux, M.-M., Raubuch, M., Berg, M., 1998. Response of protozoan and microbial
communities in various coniferous forest soils after transfer to forests with different
levels of atmospheric pollution. Biology and Fertility of Soils 27, 179–188. https://
doi.org/10.1007/s003740050418.

Crowther, T.W., van den Hoogen, J., Wan, J., Mayes, M.A., Keiser, A.D., Mo, L.,
Averill, C., Maynard, D.S., 2019. The global soil community and its influence on
biogeochemistry. Soil Ecology 365. https://doi.org/10.1126/science.aav0550.

de Bello, F., Botta-Dukát, Z., Leps, J., Fibich, P., 2021. Towards a more balanced
combination of multiple traits when computing functional differences between
species. Methods in Ecology and Evolution 12, 443–448. https://doi.org/10.1111/
2041-210X.13537.

de Bello, F., Lavorel, S., Díaz, S., Harrington, R., Cornelissen, J.H.C., Bardgett, R.D.,
Berg, M.P., Cipriotti, P., Feld, C.K., Hering, D., da Silva, P.M., Potts, S.G., Sandin, L.,
Sousa, J.P., Storkey, J., Wardle, D.A., Harrison, P.A., 2010. Towards an assessment
of multiple ecosystem processes and services via functional traits. Biodiversity &
Conservation 19, 2873–2893. https://doi.org/10.1007/s10531-010-9850-9.

Decaëns, T., 2010. Macroecological patterns in soil communities. Global Ecology and
Biogeography 19, 287–302. https://doi.org/10.1111/j.1466-8238.2009.00517.x.

Delgado-Baquerizo, M., Reich, P.B., Trivedi, C., Eldridge, D.J., Abades, S., Alfaro, F.D.,
Bastida, F.E., Berhe, A.A., Cutler, N.A., Gallardo, A., García-Velázquez, L., Hart, S.C.,
Hayes, P.E., He, J.Z., Hsein, Z.Y., Hu, H.W., Kirchmair, M., Neuhauser, S., Pérez, C.A.,
Reed, S.C., Santos, F., Sullivan, B.W., Trivedi, P., Wang, J.T., Weber-Grullon, L.,
Williams, M.A., Singh, B.K., 2020. Multiple elements of soil biodiversity drive
ecosystem functions across biomes. Nature Ecology and Evolution 4, 210–220.
https://doi.org/10.1038/s41559-019-1084-y.

Díaz, S., Kattge, J., Cornelissen, J.H.C., Wright, I.J., Lavorel, S., Dray, S., Reu, B.,
Kleyer, M., Wirth, C., Colin Prentice, I., Garnier, E., Bónisch, G., Westoby, M.,
Poorter, H., Reich, P.B., Moles, A.T., Dickie, J., Gillison, A.N., Zanne, A.E., Chave, J.,
Joseph Wright, S., Sheremetev Ev, S.N., Jactel, H., Baraloto, C., Cerabolini, B.,
Pierce, S., Shipley, B., Kirkup, D., Casanoves, F., Joswig, J.S., Günther, A.,
Falczuk, V., Rüger, N., Mahecha, M.D., Gorné, L.D., 2016. The global spectrum of
plant form and function. Nature 529, 167–171. https://doi.org/10.1038/
nature16489.

Donald, J., Murienne, J., Chave, J., Iribar, A., Louisanna, E., Manzi, S., Roy, M., Tao, S.,
Orivel, J., Schimann, H., Zinger, L., 2021. Multi-taxa environmental DNA inventories
reveal distinct taxonomic and functional diversity in urban tropical forest fragments.
Global Ecology and Conservation 29. https://doi.org/10.1016/j.gecco.2021.e01724,
0–2.

Dumack, K., Fiore-Donno, A.M., Bass, D., Bonkowski, M., 2020. Making sense of
environmental sequencing data: ecologically important functional traits of the
prostistan groups Cercozoa and Endomyxa (Rhizaria). Molecular Ecology Resources
20, 398–403. https://doi.org/10.1111/1755-0998.13112.

Ellers, J., Berg, M.P., Dias, A.T.C., Fontana, S., Ooms, A., Moretti, M., 2018. Diversity in
form and function: vertical distribution of soil fauna mediates multidimensional trait
variation. Journal of Animal Ecology 87, 933–944. https://doi.org/10.1111/1365-
2656.12838.

Fang, J., Chen, Y., Liu, G., Verbruggen, H., Zhu, H., 2021. Chloroplast genome traits
correlate with organismal complexity and ecological traits in chlorophyta. Frontiers
in Ecology and Evolution 9. https://doi.org/10.3389/fevo.2021.791166.
772284 (IceCommunities). This research was also supported by Bio-
diversa+, the European Biodiversity Partnership under the 2021–2022
BiodivProtect call for research proposals, co-funded by the Euro-
pean Commission (Grant Agreement no. 101052342 'PrioriticeVan-
ishing habitats: conservation priorities for glacier-related biodiversity
threatened by climate change') and with the funding organizations MUR
and ANR. SG is funded by the Italian national inter-university PhD
course in Sustainable Development and Climate change.

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.soilbio.2023.109207.

**References**

Adl, S., Girard, V., Breton, G., Lak, M., Maharning, A., Mills, A., Perrichot, V.,
Trionnaire, M., Vullo, R., Néraudeau, D., 2011. Reconstructing the soil food web of a
100 million-year-old forest: the case of the mid-Cretaceous fossils in the amber of
Charentes (SW France). Soil Biology and Biochemistry 43, 726–735. https://doi.org/
10.1016/j.soilbio.2010.12.003.

Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S., Berney, C.,
Brown, M.W., Burki, F., Cárdenas, P., Cepícka, I., Chistyakova, L., del Campo, J.,
Dunthorn, M., Edvardsen, B., Eglit, Y., Guillou, L., Hampl, V., Heiss, A.A.,
Hoppenrath, M., James, T.Y., Karnkowska, A., Karpov, S., Kim, E., Kolisko, M.,
Kudryavtsev, A., Lahr, D.J.G., Lara, E., Le Gall, L., Lynn, D.H., Mann, D.G.,
Massana, R., Mitchell, E.A.D., Morrow, C., Park, J.S., Pawlowski, J.W., Powell, M.J.,
Richter, D.J., Rueckert, S., Shadwick, L., Shimano, S., Spiegel, F.W., Torruella, G.,
Youssef, N., Zlatogursky, V., Zhang, Q., 2019. Revisions to the classification,
nomenclature, and diversity of eukaryotes. The Journal of Eukaryotic Microbiology
66, 4–119. https://doi.org/10.1111/jeu.12691.

Anthony, M.A., Bender, S.F., van der Heijden, M.G.A., 2023. Enumerating soil
biodiversity. Proceedings of the National Academy of Sciences 120. https://doi.org/
10.1073/pnas.2304663120.

Archibald, J.M., Simpson, A.G.B., Slamovits, C.H., 2017. Handbook of the protists. In:
Handbook of the Protists, second ed. Springer. https://doi.org/10.1007/978-3-319-
32669-6.

Aslani, F., Geisen, S., Ning, D., Tedersoo, L., Bahram, M., 2022. Towards revealing the
global diversity and community assembly of soil eukaryotes. Ecology Letters 25,
65–76. https://doi.org/10.1111/ele.13904.

Bahls, L., Boynton, B., Johnston, B., 2018. Atlas of diatoms (Bacillariophyta) from diverse
habitats in remote regions of western Canada. PhytoKeys 186, 1–186. https://doi.
org/10.3897/phytokeys.105.23806.

Bardgett, R.D., Van Der Putten, W.H., 2014. Belowground biodiversity and ecosystem
functioning. Nature 515, 505–511. https://doi.org/10.1038/nature13855.

Bar-On, Y.M., Phillips, R., Milo, R., 2018. The biomass distribution on Earth. Proceedings
of the National Academy of Sciences of the United States of America 115,
6506–6511. https://doi.org/10.1073/pnas.1711842115.

Berger, H., 2011. Monograph of the Gonostomatidae and Kahliviidae (Ciliophora,
Hypotricha). Springer.

Berger, H., 2007. Monograph of the Urostyloidea (Ciliophora, Hypotricha). Springer.

Berger, H., 1999. Monograph of the Oxytrichidae (Ciliophora, Hypotrichia). Springer.

Bielby, J., Mace, G.M., Bininda-Emonds, O.R.P., Cardillo, M., Gittleman, J.L., Jones, K.E.,
Orde, C.M.D., Purvis, A., 2007. The fast-slow continuum in mammalian life history:
an empirical reevaluation. The American Naturalist 169, 748–757. https://doi.org/
10.1086/516847.

Bongers, T., 1990. The maturity index: an ecological measure of environmental
disturbance based on nematode species composition. Oecologia 83, 14–19. https://
doi.org/10.1007/BF00324627.

Bonin, A., Guerrieri, A., Ficetola, G.F., 2023. Optimal sequence similarity thresholds for
clustering of molecular operational taxonomic units in DNA metabarcoding studies.
Molecular Ecology Resources 23, 368–381. https://doi.org/10.1111/1755-
0998.13709.

Bonkowski, M., 2004. Protozoa and plant growth: the microbial loop in soil revisited.
New Phytologist 162, 617–631. https://doi.org/10.1111/j.1469-8137.2004.01066.
x.

Bonkowski, M., Clarholm, M., 2012. Stimulation of plant growth through interactions of
bacteria and protozoa: testing the auxiliary microbial loop hypothesis. Acta
Protozoologica 51, 237–247. https://doi.org/10.4467/16890027AP.12.019.0765.

Bonkowski, M., Dumack, K., Fiore-Donno, A.M., 2019. The protists in soil – a token of
untold eukaryotic diversity. In: Van Elsas, J.D., Trevors, J.T., Rosado, A.S.,
Nannipierie, P. (Eds.), Modern Soil Microbiology. CRC Press, Boca Raton, FL, USA,
pp. 125–140.

Briones, M.J.I., 2014. Soil fauna and soil functions: a jigsaw puzzle. Frontiers in
Environmental Science 2, 1–22. https://doi.org/10.3389/fenvs.2014.00007.

Brousseau, P.M., Gravel, D., Handa, I., 2018. On the development of a predictive
functional trait approach for studying terrestrial arthropods. Journal of Animal
Ecology 87, 1209–1220. https://doi.org/10.1111/1365-2656.12830.

Burki, F., Sandin, M.M., Jamy, M., 2021. Diversity and ecology of protists revealed by
metabarcoding. Current Biology 31, R1267–R1280. https://doi.org/10.1016/j.
cub.2021.07.066.

Cadotte, M.W., Carscadden, K., Mirothchick, N., 2011. Beyond species: functional
diversity and the maintenance of ecological processes and services. Journal of
Applied Ecology 48, 1079–1087. https://doi.org/10.1111/j.1365-2664.2011.02048.
x.

Calderón-Sanou, I., Zinger, L., Hedde, M., Martínez-Almoyna, C., Sallارد, A., Renaud, J.,
Gielly, L., Khedim, N., Lionnet, C., Ohlmann, M., Consortium, O., Münkemüller, T.,
Thuiller, W., 2022. Energy and physiological tolerance explain multi-trophic soil
diversity in temperate mountains. Diversity and Distributions 1–16. https://doi.org/
10.1111/ddi.13529.

Cantera, I., Carteron, A., Guerrieri, A., Marta, S., Bonin, A., Ambrosini, R., Anthelme, F.,
Azzoni, R., Almond, P., Alviz Gazitúa, P., Cauvy-fraunié, Ceballos Lievano, J.,
Chand, P., Chand Sarma, M., Clague, J., Alejo Cochachín Rapre, J., Compostella, L.,
Encarnación, R.C., Dangles, O., Eger, A., Erokhin, S., Franzetti, A., Gielly, L., Gili, F.,
Gobbi, M., Hagvar, S., Khedim, N., Peyre, G., Pittino, F., Rabatel, A., Urseitova, N.,
Yang, Y., Zaginaev, V., Zerboni, A., Zimmer, A., Taberlet, P., Diolaïuti, G.,
Poulenard, J., Thuiller, W., Caccianiga, M., Ficetola, F., 2023. The importance of
species addition versus replacement varies over succession in plant communities
after glacial retreat. PREPRINT (Version 1). Available at: Research Square https://
doi.org/10.21203/rs.3.rs-2482972/v1.

Cardinale, B.J., Duffy, J.E., Gonzalez, A., Hooper, D.U., Perrings, C., Venail, P.,
Narwani, A., MacE, G.M., Tilman, D., Wardle, D.A., Kinzig, A.P., Daily, G.C.,
Loreau, M., Grace, J.B., Larigauderie, A., Srivastava, D.S., Naemst, S., 2012.
Biodiversity loss and its impact on humanity. Nature 486, 59–67. https://doi.org/
10.1038/nature11148.

Cavalier-Smith, T., van der Heyden, S., 2007. Molecular phylogeny, scale evolution and
taxonomy of centrohelid heliozoa. Molecular Phylogenetics and Evolution 44,
1186–1203. https://doi.org/10.1016/j.mjvep.2007.04.019.

Chen, B., Xiong, W., Qi, J., Pan, H., Chen, S., Peng, Z., Gao, H., Zhang, L., Jiang, Y.,
Wei, G., Jiao, S., 2021. Trophic interrelationships drive the biogeography of
prostisan community in agricultural ecosystems. Soil Biology and Biochemistry 163.
doi.org/10.1016/j.soilbio.2021.108445.

Clarholm, M., 1981. Protozoan grazing of bacteria in soil-impact and importance.
Microbial Ecology 7, 343–350. https://doi.org/10.1007/BF02341429.

Coúteaux, M.-M., Darbyshire, J.F., 1998. Functional diversity amongst soil protozoa.
Applied Soil Ecology 10, 229–237. https://doi.org/10.1016/S0929-1393(98)00122-
x.

Coúteaux, M.-M., Raubuch, M., Berg, M., 1998. Response of protozoan and microbial
communities in various coniferous forest soils after transfer to forests with different
levels of atmospheric pollution. Biology and Fertility of Soils 27, 179–188. https://
doi.org/10.1007/s003740050418.

Crowther, T.W., van den Hoogen, J., Wan, J., Mayes, M.A., Keiser, A.D., Mo, L.,
Averill, C., Maynard, D.S., 2019. The global soil community and its influence on
biogeochemistry. Soil Ecology 365. https://doi.org/10.1126/science.aav0550.

de Bello, F., Botta-Dukát, Z., Leps, J., Fibich, P., 2021. Towards a more balanced
combination of multiple traits when computing functional differences between
species. Methods in Ecology and Evolution 12, 443–448. https://doi.org/10.1111/
2041-210X.13537.

de Bello, F., Lavorel, S., Díaz, S., Harrington, R., Cornelissen, J.H.C., Bardgett, R.D.,
Berg, M.P., Cipriotti, P., Feld, C.K., Hering, D., da Silva, P.M., Potts, S.G., Sandin, L.,
Sousa, J.P., Storkey, J., Wardle, D.A., Harrison, P.A., 2010. Towards an assessment
of multiple ecosystem processes and services via functional traits. Biodiversity &
Conservation 19, 2873–2893. https://doi.org/10.1007/s10531-010-9850-9.

Decaëns, T., 2010. Macroecological patterns in soil communities. Global Ecology and
Biogeography 19, 287–302. https://doi.org/10.1111/j.1466-8238.2009.00517.x.

Delgado-Baquerizo, M., Reich, P.B., Trivedi, C., Eldridge, D.J., Abades, S., Alfaro, F.D.,
Bastida, F.E., Berhe, A.A., Cutler, N.A., Gallardo, A., García-Velázquez, L., Hart, S.C.,
Hayes, P.E., He, J.Z., Hsein, Z.Y., Hu, H.W., Kirchmair, M., Neuhäuser, S., Pérez, C.A.,
Reed, S.C., Santos, F., Sullivan, B.W., Trivedi, P., Wang, J.T., Weber-Grullon, L.,
Williams, M.A., Singh, B.K., 2020. Multiple elements of soil biodiversity drive
ecosystem functions across biomes. Nature Ecology and Evolution 4, 210–220.
https://doi.org/10.1038/s41559-019-1084-y.

Díaz, S., Kattge, J., Cornelissen, J.H.C., Wright, I.J., Lavorel, S., Dray, S., Reu, B.,
Kleyer, M., Wirth, C., Colin Prentice, I., Garnier, E., Bónisch, G., Westoby, M.,
Poorter, H., Reich, P.B., Moles, A.T., Dickie, J., Gillison, A.N., Zanne, A.E., Chave, J.,
Joseph Wright, S., Sheremetev Ev, S.N., Jactel, H., Baraloto, C., Cerabolini, B.,
Pierce, S., Shipley, B., Kirkup, D., Casanoves, F., Joswig, J.S., Günther, A.,
Falczuk, V., Rüger, N., Mahecha, M.D., Gorné, L.D., 2016. The global spectrum of
plant form and function. Nature 529, 167–171. https://doi.org/10.1038/
nature16489.

Donald, J., Murienne, J., Chave, J., Iribar, A., Louisanna, E., Manzi, S., Roy, M., Tao, S.,
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Potapov, A.M., 2022. Multifunctionality of belowground food webs: resource, size and spatial energy channels. Biological Reviews 97, 1691–1711. https://doi.org/10.1111/brv.12857.

Potapov, A.M., Beaulieu, F., Birkhofer, K., Bluhm, S.L., Degtyarev, M.I., Devetter, M., Goncharov, A.A., Gongalsky, K.B., Klarner, B., Korobushkin, D.I., Liebke, D.F., Maraun, M., Mc Donnell, R.J., Pollierer, M.M., Schaefer, I., Shrubovych, J., Semenyuk, I.I., Sendra, A., Tuma, J., Tümová, M., Vassilieva, A.B., Chen, T.W., Geisen, S., Schmidt, O., Tiunov, A.V., Scheu, S., 2022. Feeding habits and multifunctional classification of soil-associated consumers from protists to vertebrates. Biological Reviews 97, 1057–1117. https://doi.org/10.1111/ brv.12832.

Raffard, A., Lecerf, A., Coet, J., Buoro, M., Lassus, R., Cucherousset, J., 2017. The functional syndrome: linking individual trait variability to ecosystem functioning. Proceedings of the Royal Society B: Biological Sciences 284. https://doi.org/10.1098/rspb.2017.1893.

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Schoch, C.L., Ciufo, S., Domrachev, M., Hotton, C.L., Kannan, S., Khovanskaya, R., Leipe, D., McVeigh, R., O'Neill, K., Robbertse, B., Sharma, S., Soussov, V., Sullivan, J.P., Sun, L., Turner, S., Karsch-Mizrachi, I., 2020. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database 1–21. https://doi.org/10.1093/database/baa062, 2020.

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Seppey, C.V.W., Singer, D., Dumack, K., Fournier, B., Belbahri, L., Mitchell, E.A.D., Lara, E., 2017. Distribution patterns of soil microbial eukaryotes suggests widespread algalogy by phagotrophic protists as an alternative pathway for nutrient cycling. Soil Biology and Biochemistry 112, 68–76. https://doi.org/10.1016/j.soilbio.2017.05.002.

Seppey, C.V.W., Broennimann, O., Buri, A., Yashiro, E., Pinto-Figueroa, E., Singer, D., Blandenier, Q., Mitchell, E.A.D., Niculita-Hirzel, H., Guisan, A., Lara, E., 2020. Soil protist diversity in the Swiss western Alps is better predicted by topo-climatic than by edaphic variables. Journal of Biogeography 47, 866–878. https://doi.org/10.1111/jbi.13755.

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