Tales from the underground: Soil heterogeneity and not only above‐ground plant interactions explain fine‐scale species patterns in a Mediterranean dwarf‐shrubland

Abstract

Questions:The current paradigm of plant community assembly relies on a set of processes operating at particular spatial scales. It is assumed that as the spatial scale becomes finer, environmental filtering loses its importance in favor of biotic interactions and neutral processes. Thus, at the very fine spatial scale represented by a rectangular plot of 72.25 m 2 in a Mediterranean semiarid dwarf-shrubland, we ask: (a) are the spatial distributions of individuals of the different species explained by neutral models; (b) are these distributions dependent on above-ground plant interactions with the dominant species in the community; and/or (c) are they responding to the spatial variation of different soil variables, in a kind of fine-scale environmental filtering? Location: Central Spain. Methods:To assess the correlates of fine-scale (i.e., from 0.05-2.00 m) spatial patterns of the species in the community, we fully mapped all perennial individuals inside the rectangular plot. For each species, we fitted one complete spatial randomness (CSR) model that does not assume spatial heterogeneity and three weighted-average inhomogeneous Poisson process (IPP) models using six soil covariates, distribution patterns of the four above-ground dominant plants in the community or both types of covariates. All models were evaluated and compared to select the best-fitting weighted-average model. Results:We recorded 7,988 individuals of 22 species. Patterns of all species were appropriately explained by IPP models. For most species the best-fitting weightedaverage model included both soil and dominant plants (i.e., 15) or only soil covariates (i.e., 6). The improvement provided by the best-fitting weighted-averaging model in comparison with the CSR model was consistently high (81%).

The role of root community attributes in predicting soil fungal and bacterial community patterns

“…In addition, because both microbial communities and environmental factors, including nonmeasured ones such as topography or soil moisture content, frequently have a predictable spatial structure (Ettema & Wardle, 2002), we also considered the role of explicit spatial covariates. For this purpose, we combined DNA metabarcoding techniques with spatially explicit sampling in a Mediterranean scrubland, considering the scale at which plant‐to‐plant interactions occur in this community (Chacón‐Labella et al ., 2016; Pescador et al ., 2020). Specifically, we addressed the following questions: (1) Which root community attributes (root richness, biomass, composition and β‐diversity) predict the patterns of microbial diversity?…”

Conditional love? Co‐occurrence patterns of drought‐sensitive species in European grasslands are consistent with the stress‐gradient hypothesis

“…A notable exception was graminoid Koeleria vallesiana , which had positive association shifts with 55% of drought‐sensitive species. This species was recently identified as a potential nurse species in dry grasslands (Pescador et al., 2020 ), highlighting that there is a large variability in habits and traits of potential nurse plants.…”

Every bit helps: The functional role of individuals in assembling any plant community, from the richest to monospecific ones

“…Although this trait-based approach was very efficient for describing community structure and dynamics at relatively coarse spatial scales (Diaz et al, 2004), and helped to solve the overlap between proposed mechanisms, it is imprecise at the finest scales where individuals interact (Lawton, 1999;Vellend, 2010). At these scales, neutral processes seem to be dominant (Hubbel, 2001;McGill, 2010), giving opportunity to stochastic events to rule out community structure (Chase, 2014, but see Pescador et al, 2020).…”