Metacommunity structure analysis reveals nested patterns in deconstructed macroinvertebrates assemblages

Abstract

1. Understanding processes driving patterns of species distribution and diversity is one of the main objectives of community ecology. 2. The aim of our study was to evaluate the spatial variation in assemblage composition of stream-dwelling macroinvertebrates and identify which factors (e.g. water quality, land cover) are the most important drivers. 3. We applied the elements of the metacommunity structure approach on a dataset of 38 communities from the Futaleufú basin in northwestern Patagonia. To better understand assemblage variation, we deconstructed our macroinvertebrate dataset into different taxonomic and trait groups. We then identified the most influential factors driving community composition using random forests. 4. We found that half of our datasets (i.e. macroinvertebrate groups) exhibited a nested structure with clumped species loss, while the other half showed a quasi-nested pattern with either clumped or stochastic species loss. 5. Overall, water quality was the most important driver of community variation, although climate, geography, and land cover were more or less relevant in particular cases. We found differences in the relative importance of the selected explanatory variables among datasets. This would suggest that different components of the macroinvertebrate community respond differently to environmental factors. 6. Our findings could be of value for conservation planning, as they suggest that preserving the most species-rich streams would, to some extent, guarantee the conservation of the entire species pool.

Spatio‐temporal variation of macroinvertebrate metacommunity organization in a monsoon‐climate region

“…This may blur the observed metacommunity patterns. Therefore, dividing entire metacommunities into more homogeneous deconstructed trait groups and, respectively, examining their typologies and underlying drivers may have the potential to provide clues to differences among different seasons (Fernandes et al, 2014; Tonkin et al, 2016; Williams‐Subiza et al, 2020). Finally, the dominant macroinvertebrate taxa in this drainage basin are characterized by small body size, short life span, fast development and high dispersal capability (Li et al, 2019), which may thus display relatively high resistance and resilience to natural and anthropogenic disturbances (Kuzmanovic et al, 2017; Lytle & Poff, 2004).…”

“…A growing number of recent studies in rivers have evaluated metacommunity structures and assembly mechanisms in different habitats (Heino, Soininen, et al, 2015; Tonkin et al, 2016), network positions (López‐Delgado et al, 2019; Tonkin et al, 2015), catchments (Alves‐Martins et al, 2019; Tonkin, Shah, et al, 2017), ecoregions (Brasil et al, 2017; Murray‐Stoker & Murray‐Stoker, 2020), as well as among multiple biological groups (He et al, 2020; Williams‐Subiza et al, 2020). Generally, these studies found that environmental filtering frequently has greater importance than spatial effects on community structure, and a metacommunity thus usually displays a gradient‐driven typology (e.g.…”

“…spring, summer, autumn and winter) from five tributaries of the Hanjiang River, an important drainage basin in the East Asian subtropical monsoon zone. Macroinvertebrates are regarded as suitable model organisms for metacommunity research, since they are highly diverse, sensitive to environmental variation, have a variety of phylogenetic origins, and exhibit a range of biological traits (Williams-Subiza et al, 2020). By using both descriptive (i.e.…”

Nestedness theory suggests wetland fragments with large areas and macrophyte diversity benefit waterbirds

“…The system is perfectly nested if all species in the small island are also found in the adjacent larger island; however, this perfectly nested pattern rarely occurs in nature (Wright et al., 1998 ). Nestedness, to some extent, is one of the most frequently occurring patterns for biotas in the island landscape (Wang et al., 2013 ; Wright et al., 1998 ), including birds (Fernández‐Juricic and Jokimäki, 2001 ; Murgui, 2010 ; Wang et al., 2013 ), fish (Fernández‐Juricic and Jokimäki, 2001 ), insects (Fernández‐Juricic, 2002 ; Fernández‐Juricic and Jokimäki, 2001 ; Xu et al., 2017 ), plants (Platt and Lill, 2006 ), mammals (Chen et al., 2019 ), reptiles (Wang et al., 2010 ), and macroinvertebrates (Florencio et al., 2011 ; Williams‐Subiza et al., 2020 ).…”