Predictability of stream insect distributions is dependent on niche position, but not on biological traits or taxonomic relatedness of species

Abstract

Species distributions can be analysed under two perspectives: the niche‐based approach, which focuses on species–environment relationships; and the dispersal‐based approach, which focuses on metapopulation dynamics. The degree to which each of these two components affect species distributions may depend on habitat fragmentation, species traits and phylogenetic constraints. We analysed the distributions of 36 stream insect species across 60 stream sites in three drainage basins at high latitudes in Finland. We used binomial generalised linear models (GLMs) in which the predictor variables were environmental factors (E models), within‐basin spatial variables as defined by Moran's eigenvector maps (M models), among‐basin variability (B models), or a combination of the three (E + M + B models) sets of variables. Based on a comparative analysis, model performance was evaluated across all the species using Gaussian GLMs whereby the deviance accounted for by binomial GLMs was fitted on selected explanatory variables: niche position, niche breadth, site occupancy, biological traits and taxonomic relatedness. For each type of model, a reduced Gaussian GLM was eventually obtained after variable selection (Bayesian information criterion). We found that niche position was the only variable selected in all reduced models, implying that marginal species were better predicted than non‐marginal species. The influence of niche position was strongest in models based on environmental variables (E models) or a combination of all types of variables (E + M + B models), and weakest in spatial autocorrelation models (M models). This suggests that species–environment relationships prevail over dispersal processes in determining stream insect distributions at a regional scale. Our findings have clear implications for biodiversity conservation strategies, and they also emphasise the benefits of considering both the niche‐based and dispersal‐based approaches in species distribution modelling studies.

Using traits to explain interspecific variation in diatom occupancy and abundance across lakes and streams

“…Species’ pH preferences were variably associated with occupancy in lakes and streams, but in general, different environmental preferences of species were not clearly related to their occupancy and abundance. This finding is partly contradictory to earlier studies showing that species’ ‘true’ niche parameters can greatly affect interspecific variation in occupancy and/or abundance of freshwater organisms (Heino & de Mendoza, ; Heino & Tolonen, ; Rocha et al., ; Tales et al., ; Verberk et al., ; Vilmi et al., ). The difference between these earlier investigations and our current study is that we used existing literature knowledge on species’ pH and trophic preferences, while ‘true’ niche parameters are calculated based on actually measured environmental variables.…”

“…Species' pH preferences were variably associated with occupancy in lakes and streams, but in general, different environmental preferences of species were not clearly related to their occupancy and abundance. This finding is partly contradictory to earlier studies showing that species' 'true' niche parameters can greatly affect interspecific variation in occupancy and/or abundance of freshwater organisms (Heino & de Mendoza, 2016;Heino & Tolonen, 2018;Rocha et al, 2018;Tales et al, 2004;Verberk et al, 2010;Vilmi et al, 2019 Also, it is important to understand that reaching optimum environmental conditions is constrained by regional obstacles and processes, such as historical factors and dispersal limitation (e.g. Soininen, 2007).…”

Highly variable species distribution models in a subarctic stream metacommunity: Patterns, mechanisms and implications

“…In our case, shading was selected as a significant variable in binomial models for some predators (Isoperla difformis and P. conspersa) and shredders (Leuctra spp. 500 km latitudinal gradient), previous findings indicate a stronger relevance of environmental factors, compared to spatial restrictions, on single-species distributions (Heino & de Mendoza, 2016). Groups other than shredders perhaps benefit indirectly from the increase in potential resources that the variable "shading" represents for shredders, for example, through the enhancement of nutrient recycling by shredding coarse plant litter (Covich, Palmer, & Crowl, 1999;Wallace & Webster, 1996).…”

“…Such a sampling method has been shown to be effective in northern streams, allowing to detect patterns in community structure (Heino, Ilmonen, & Paasivirta, 2014) and distributions of single species (Heino & de Mendoza, 2016). 50 m 2 ) based on visual inspections of variation in depth, flow, moss cover and particle size.…”

“…Finally, for biodiversity conservation, it is essential to focus on maintaining habitat heterogeneity because it appears to determine metacommunity organisation (K€ arn€ a et al, 2015) and species distributions (Heino & de Mendoza, 2016) in streams at high latitudes.…”