Introduction
Soil biodiversity encompasses a complex network of interactions among
functionally and trophically diverse organisms, playing a vital role in
supporting ecosystem functions and services such as carbon
sequestration, organic matter decomposition, and enhancing plant
performance and resistance to pests and stress (Bardgett & van der
Putten 2014; Delgado-Baquerizo et al. 2020). Over the past
decades, our understanding of the spatial distribution of soil taxa has
improved, particularly for specific groups like bacteria (Fierer &
Jackson 2006; Delgado-Baquerizo et al. 2018) and fungi (Tedersooet al. 2014; Davison et al. 2015). However, our current
knowledge primarily relies on a few specific taxa, while the broader
ecological processes shaping the whole soil communities and their
organisation into interaction networks remain poorly understood. This
knowledge gap stem from challenges associated with capturing the
intricate spatial heterogeneity inherent to the soil environment (Ettema
& Wardle 2002), and the methodological complexities of sampling and
analysing the vast diversity of the soil biota (Geisen et al.2019). These limitations have hindered the application of existing
theoretical frameworks on soil biota (Thakur et al. 2020).
Advancing research in this direction promises to unravel the ecological
processes that structure soil biodiversity and to predict the impacts of
global change on terrestrial ecosystems (Soliveres et al. 2016;
Eisenhauer et al. 2021).
Gaining insights into the organization of soil communities necessitates
studying spatial, environmental, and biotic drivers and this poses
challenges (Decaëns 2010; Münkemüller et al. 2020; Eisenhaueret al. 2022). First, capturing the full complexity of soil
systems requires accounting for their inherent spatial heterogeneity
from landscape to local scales (Ettema & Wardle 2002; Thakur et
al. 2020). At the landscape scale, dominant habitat types, such as
grasslands or forests, are crucial for soil taxonomic and functional
composition (Fiore-Donno et al. 2020; Arribas et al. 2021;
Sepp et al. 2021). Consequently, the heterogeneity between
habitats within a landscape can give rise to mosaic patterns of soil
communities. Moreover, the spatial connectivity of habitats and the
varying dispersal capacities of soil organisms can influence the local
composition and structure of soil communities (Arribas et al.2021). But even at the local scale of a few meters, variable abiotic
conditions, including microclimate and soil physico-chemical properties,
along with stochastic processes, can lead to pronounced differences in
soil communities (Ramirez et al. 2014; O’Brien et al.2016; Zinger et al. 2019). The structure of the vegetation within
an habitat or its taxonomy or functional composition can also affect the
abundance and diversity of different soil taxa or trophic groups
(Noguerales et al. 2021; Calderón‐Sanou et al. 2022;
Ganault et al. 2022). Effectively disentangling the effects of
spatial, environmental and biotic processes necessitates a sampling
design that encompasses multiple spatial scales, ranging from the
heterogeneity between habitats to small-scale soil variations.
Second, comprehensive sampling and cross-taxa analysis are required to
capture the high diversity in soils. Recent advancements in monitoring
techniques, such as environmental DNA metabarcoding (eDNA)(Taberletet al. 2012), offer cost-effective means to obtain extensive data
on soil biota at large spatial extent (Taberlet et al. 2018;
Geisen et al. 2019). To more concisely present the different taxa
they can be classified into trophic groups that share similar resources
or prey (Eltonian niche; Elton 1927), e.g., fungivorous nematodes or
photoautotrophic bacteria (Louca et al. 2016; Potapov et
al. 2022). To better comprehend the complex interactions, we can
construct food webs that consider multiple trophic groups (nodes) and
their linkages across trophic levels (links) (Thompson et al.2012; Gravel et al. 2019). However, constructing food webs from
large eDNA datasets is not without challenges. It entails handling and
classifying thousands of sequences into trophic groups, and subsequently
linking these groups based on known interactions. Obstacles include the
resolution limitations of DNA markers for species-level assignment, the
incompleteness of sequence reference databases, inconsistent terminology
in trophic ecology across soil taxa (Hedde et al. 2022), and the
sparse trophic information available for soil organisms in literature
and repositories (but see Potapov et al. 2022). Nevertheless, the
application of artificial intelligence tools now offers the potential
for automating classification tasks (Compson et al. 2018; Le
Guillarme & Thuiller 2023).
Third, if we are to understand soil biodiversity, not as a group of
independent taxa, but rather as food webs, we need the appropriate
methods and frameworks to investigate how ecological processes act on
soil trophic groups and their interactions. The mono-trophic community
assembly framework (Keddy 1992; Thuiller et al. 2013) can be
extended to food webs using the metaweb concept (Dunne 2006). At the
regional scale, the metaweb represents the potential food web
encompassing all species (or trophic groups) from the regional pool and
their potential interactions (Fig.1c). At the local scale, realised
local food webs emerge as subsets of the metaweb due to ecological
filtering of species (Bauer et al. 2022). This filtering process
can be influenced by spatial filters like landscape barriers, limiting
dispersal (Peay et al. 2010), abiotic factors filtering out
species lacking physiological adaptations (Maaß et al. 2015;
Glassman et al. 2017), and biotic interactions such as
mutualisms, herbivory and predation (Vályi et al. 2016). By using
the metaweb concept, we can evaluate the effects of ecological filters
not only on the taxonomic composition of the local community but also on
its network structure (i.e., composition of interactions). Important
biotic interactions in the soil are via plant-soil feedbacks, where the
taxonomic or functional composition of plant communities influences soil
food webs and vice-versa (Kardol & De Long 2018; Kardol et al.2018). Moreover, trophic interactions within the food web can elucidate
its local structure and composition (Thakur & Geisen 2019). We
anticipate that interactions between taxa or groups within the food web
should result in co-variation across environmental and spatial
gradients. For instance, environments characterized by decomposer
communities dominated by bacteria (rather than fungi) should promote the
dominance of bacteria consumers and related higher-level consumers
within the food web (Moore & de Ruiter 1991), see e.g. Martinez-Almoynaet al. 2022. Null models can be used to test the significance of
such co-variation in the assembly of ecological communities (Carusoet al. 2022).
Here, we analysed the spatial variation in soil food web structure,
encompassing trophic group and interaction composition. We used data
from all over the French Alps including lowland forests and
high-altitude grassland ecosystems. To represent their spatial
heterogeneity, we employed a stratified and nested sampling design,
consisting of 24 elevational gradients with multiple plots at varying
altitudes (Fig. 1a). We measured soil biodiversity in 418 soil samples,
using environmental DNA (eDNA). Using an ontology-based data integration
pipeline, combining multiple databases with existing knowledge on the
trophic habits of soil organisms (Le Guillarme et al. 2023; Le
Guillarme & Thuiller 2023), we constructed a metaweb comprising 55 soil
trophic groups with 383 potential trophic interactions (Fig.1b).
Finally, we applied the metaweb framework to characterise the importance
of ecological filters on soil food webs (Fig.1c), using a combination of
network diversity indices based on Hill numbers (Ohlmann et al.2019) and associated null models. We quantified local variations in soil
food web structure both between and within habitats, addressing three
specific questions: (Q1) Do different habitats differ in soil food
webs?, (Q2) Do trophic interactions contribute to variations in group
abundances between habitats?, and, (Q3) How do abiotic conditions,
spatial factors, and plant communities shape soil food webs within
habitats?