Data from: On the shape and origins of the freshwater species-area relationship - Passy, Sophia; Mruzek, Joseph; Budnick, William; Leboucher, Thibault; Jamoneau, Aurélien; Chase, Jonathan; Soininen, Janne; Sokol, Eric; Tison-Rosebery, Juliette; Vilmi, Annika; Wang, Jianjun; Larson, Chad (Dryad, 2022)
The species-area relationship (SAR) has over a 150-year-long history in
ecology, but how its shape and origins vary across scales and organisms is
still not fully understood. This is the first subcontinental freshwater
study to examine both properties of the SAR in a spatially explicit way
across major organismal groups (diatoms, insects, and fish), differing in
body size and dispersal capacity. First, to describe the SAR shape, we
evaluated the fit of three commonly used models, logarithmic, power, and
Michaelis-Menten. Second, we proposed a hierarchical framework to explain
the variability in the SAR shape, captured by the parameters of the SAR
model. According to this framework, scale and species group were the top
predictors of the SAR shape, climatic factors (heterogeneity and median
conditions) represented the second predictor level, and metacommunity
properties (intraspecific spatial aggregation, γ-diversity, and species
abundance distribution), the third predictor level. We calculated the SAR
as a sample-based rarefaction curve using 60 streams within landscape
windows (scales) in the US, ranging from 160,000 to 6,760,000 km2. First,
we found that all models provided good fits (R2 ≥ 0.93), but the frequency
of the best-fitting model was strongly dependent on organism, scale, and
metacommunity properties. Michaelis-Menten model was most common in fish,
at the largest scales, and at the highest levels of intraspecific spatial
aggregation. The power model was most frequent in diatoms and insects, at
smaller scales, and in metacommunities with the lowest evenness. The
logarithmic model was best fitting exclusively at the smallest scales and
in species-poor metacommunities, primarily fish. Second, we tested our
framework with the parameters of the most broadly used SAR model, the
log-log form of the power model using a structural equation model. This
model supported our framework and revealed that the SAR slope was best
predicted by scale- and organism-dependent metacommunity properties,
particularly spatial aggregation, while the intercept responded most
strongly to species group and γ-diversity. Future research should
investigate from the perspective of our framework how shifts in
metacommunity properties due to climate change would alter the SAR.
Diatom, insect, and fish data were collected during the warmer months
(May-September) between 1993 and 2019 from streams
in all major watersheds in the US by the National Water-Quality
Assessment (NAWQA) Program of the US Geological Survey and
the National Rivers and Streams Assessment (NRSA) of the US
Environmental Protection Agency. Diatoms and insects were sampled from a
predefined area of substrate in 2,278 and 2,270 distinct localities,
respectively. Fish were collected by electrofishing and seines from 2296
distinct localities. Diatoms and fish were identified to species, and
insects, to genus. Taxonomic data include counts of taxa in a total count
of 400 individuals per site for diatoms and 100 individuals per site for
insects and fish. Bioclimatic data for each locality were retrieved from
the WorldClim database.
Microsoft Excel, R
Keywords: Biodiversity; Climate; Diatoms; environmental heterogeneity; Fish; Insects; intraspecific spatial aggregation; metacommunity; scale; Skewness; species abundance distribution; stream; FOS: Biological sciences