Data from: On the shape and origins of the freshwater species-area relationship
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https://datadryad.org/dataset/doi:10.5061/dryad.4tmpg4fdq
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资源简介:
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.
提供机构:
Dryad
创建时间:
2022-10-19



