DOI: 10.5061/dryad.2fqz612qw
title: Species and environmental datasets from Sierra Nevada, CA (USA) streams in lake-stream networks

description: A major goal of community ecology is understanding the processes
 responsible for generating biodiversity patterns along spatial and
 environmental gradients. In stream ecosystems, system specific conceptual
 frameworks have dominated research describing biodiversity change along
 longitudinal gradients of river networks. However, support for these
 conceptual frameworks has been mixed, mainly applicable to specific stream
 ecosystems and biomes, and these frameworks have placed less emphasis on
 general mechanisms driving biodiversity patterns. Rethinking biodiversity
 patterns and processes in stream ecosystems with a focus on the
 overarching mechanisms common across ecosystems will provide a more
 holistic understanding of why biodiversity patterns vary along river
 networks. In this study, we apply the Theory of Ecological Communities
 (TEC) conceptual framework to stream ecosystems to focus explicitly on the
 core ecological processes structuring communities: dispersal, speciation,
 niche selection, and ecological drift. Using a unique case study from high
 elevation networks of connected lakes and streams, we sampled stream
 invertebrate communities in the Sierra Nevada, CA to test established
 stream ecology frameworks and compared them to the TEC framework. Local
 diversity increased and β-diversity decreased moving downstream from the
 headwaters, consistent with the river continuum concept and the small but
 mighty framework of mountain stream biodiversity. Local diversity was also
 structured by distance below upstream lakes, where diversity increased
 with distance below upstream lakes, in support of the serial discontinuity
 concept. Despite some support for the biodiversity patterns predicted from
 the stream ecology frameworks, no single framework was fully supported,
 suggesting “context dependence”. By framing our results under the TEC, we
 found species diversity was structured by niche selection, where local
 diversity was highest in environmentally favorable sites. Local diversity
 was also highest in sites with small community sizes, countering predicted
 effects of ecological drift. Moreover, higher β-diversity in the
 headwaters was influenced by dispersal and niche selection, where
 environmentally harsh and spatially isolated sites exhibit higher
 community variation. Taken together our results suggest that combining
 system specific ecological frameworks with the TEC provides a powerful
 approach for inferring the mechanisms driving biodiversity patterns and
 provides a path toward generalization of biodiversity research across
 ecosystems.
description: <strong>Study Area</strong> The
 study area was located in the Sierra Nevada Mountains of eastern
 California (USA) and encompasses portions of Inyo National Forest and
 Sequoia-Kings Canyon National Park. Over the ice-free seasons
 (June-September), we sampled five distinct lake-stream networks, where
 each network was within a spatially distinct catchment and were treated as
 independent replicate systems (Fig. 3). The Kern (n=24) and Bubbs (n=26)
 networks were sampled in 2011, the Evolution (n=21) and Cascades (n=11)
 networks in 2018, and Rock Creek (n=36) in 2019. For each lake-stream
 network, streams were sampled throughout the network along a spatial
 gradient from headwaters downstream as well as along a spatial gradient
 downstream from lakes. Because the spatial distances of the river networks
 and the distance separating lakes naturally vary among networks as well as
 backcountry sampling constraints, the number of sites sampled along the
 distance from headwaters gradient varied (n=11 to n=36) and the downstream
 lake gradient varied (n=1 to n=9). This field system and the data
 collected naturally provide spatial gradients relevant to test stream
 ecology theories. In addition, this data is ideal for testing TEC
 processes because of the naturally varying gradients of community size,
 connectivity, and environmental heterogeneity present in our sampling
 design. <strong>Field
 Methods</strong> At each sampling location, we
 established transects in riffle sections of streams. At five equally
 spaced points along transects we measured stream depth and current
 velocity at mid-depth using a portable flow meter (Marsh-McBirney Flow
 Mate 2000). We then calculated stream discharge as the sum of the product
 of average depth x current velocity x width/5 over all transect points
 (Gordon et al. 2010; Herbst et al. 2018). A calibrated YSI multiparameter
 device was placed above transects to measure temperature, dissolved
 oxygen, conductivity, and pH. Benthic chlorophyll data was collected by
 scrubbing the entire surface area of three randomly selected cobble sized
 rocks (64-255 mm) of benthic algae (periphyton) with a toothbrush for 60
 seconds (Herbst and Cooper 2010). Chlorophyll measurements were taken
 using a handheld fluorometer (Turner Designs Aquafluor), which measures
 raw fluorescence units. Florescent measurements were calibrated to
 chlorophyll concentration using a known concentration of Rhodamine. We
 standardized chlorophyll measurements by accounting for both the surface
 area of rocks and volume of water used to remove algae.
 Eight to twelve macroinvertebrate samples at each site were
 collected using a D-frame kick net (250 mm mesh, 30cm opening, 0.09m2
 sample area) in riffle habitats, depending on the density of
 macroinvertebrate samples collected. We took samples by placing the net on
 the streambed, then turning and brushing all substrate by hand in the
 sampling area (30cm x 30cm) immediately above the net, with dislodged
 invertebrates being carried by currents into the net. All
 macroinvertebrate samples were preserved in 75% ethanol within 48 hours of
 sampling. Samples were sorted, identified, and counted in the laboratory.
 Taxa were identified to the finest taxonomic level possible, usually to
 genus or species for insects (excluding Chironomidae) and order or class
 for non-insects (Merritt, Cummins, and Berg 2019). The replicate samples
 taken at each site were pooled together and divided by the number of
 replicates and the area sampled to determine the density of invertebrate
 communities. <strong>Spatial
 Data</strong> Stream distance measurements were
 taken using the R package “riverdist”, which utilizes data from the USGS
 National Hydrological Dataset Flowline in order to determine pairwise
 distances from sampling sites along the river network (Tyers 2020). We
 determined distance below upstream lakes, with the closest upstream lake
 location being the outlet of the lake determined by the USGS Watershed
 Boundary Dataset. For sites where multiple upstream lakes were draining
 into streams, we defined the upstream lake as the closest upstream lake to
 sites that was also along the mainstem of the flowline. We determined
 distance from headwaters as the streamwise distance from sites to the
 uppermost portion (headwaters) of the mainstem of streams, where the
 headwaters of streams was determined by the endpoint (beginning) of the
 flowline in the USGS NHD Flowline Dataset (U.S. Geological Survey 2016).
 In cases where multiple headwater stream reaches corresponded to
 downstream sites, we defined the headwaters as the particular reach that
 accounted for the most discharge which was determined using USGS Flowline
 Dataset. Upstream lake area and perimeter measurements were determined
 using the USGS Watershed Boundary Dataset. Land-cover proportions were
 computed using the 2016 USGS National Land Cover Database (Jin et al.
 2019).