Elsa K Toskey

Mx. Elsa K Toskey

Fish Program, Washington Department of Fish and Wildlife, Olympia, Washington, USA
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orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 May 2024 in Water
Verified
Journal Article
Open access
PDF file
ETElsa K Toskey
Elsa K Toskey
SBStephen M. Bollens
Stephen M. Bollens
Gretchen Rollwagen-BollensGretchen Rollwagen-Bollens
Gretchen Rollwagen-Bollens
PKPeter Kiffney
Peter Kiffney
KMKyle Martens
Kyle Martens
BBBernard T. Bormann
Bernard T. Bormann
Benthic algae and autotrophic seston are important bases of stream food webs, and several different environmental factors may influence their biomass. We explored how benthic algae and autotrophic seston biomass (using chlorophyll-a as a proxy for algal biomass) were associated with stream temperature, channel width, canopy cover, stream cardinal orientation, benthic macroinvertebrate functional feeding group abundance, salmonid biomass, and water velocity in 16 small, fish-bearing streams in the temperate rainforest of the Olympic Peninsula in Washington State, USA, in the summer of 2020. We performed a mixed-effects regression analysis of extracted chlorophyll-a (chl-a) and then used model averaging to determine significant (α = 0.05) algal–environmental associations for benthic algae and autotrophic seston separately. We found that benthic algae chl-a concentration increased significantly with stream temperature (p = 0.0085) and decreased significantly with water velocity (p = 0.0053). For autotrophic seston, we found that chl-a concentration increased significantly with benthic macroinvertebrate predator abundance (p = 0.0007) and stream temperature (p = 0.0160). This study underscores the need to consider a broad range of environmental variables when making research and management decisions concerning stream ecology.

15 September 2026 in Ecology
Verified
Journal Article
Open access
PDF file
ETElsa K Toskey
Elsa K Toskey
TMToshio Matsuoka
Toshio Matsuoka
PKPeter Kiffney
Peter Kiffney
SNSean M. Naman
Sean M. Naman
MLMartin C. Liermann
Martin C. Liermann
RWRobert W. Wisseman
Robert W. Wisseman
Prey availability is among the most influential and highly variable determinants of fish growth and freshwater habitat carrying capacity, yet it remains understudied compared to physical habitat variables (Ouellet et al., 2025; Rosenfeld et al., 2014; Weber et al., 2017). We often lack a clear understanding of how much food is available to fishes, how it varies spatially and temporally, and how it influences responses to restoration (Ouellet et al., 2025; Rossi et al., 2024; Wipfli et al., 2010). Drift invertebrates—the primary food source for juvenile salmonids and other drift‐foraging fishes—play a pivotal role in these dynamics. To better understand the spatiotemporal variability of drift invertebrate abundance and biomass across the freshwater range of drift‐feeding salmonids in western North America, we compiled the DRift Invertebrates For salmonids in River Systems (DRIFteRS) dataset. The dataset encompasses 6125 samples of drift invertebrates, and, for a subset of drift samples, associated benthic invertebrate density data, collected from 1360 reaches on 459 unique rivers and streams spanning 55 river basins considered hydrologically independent (i.e., not nested within the same larger watershed) across British Columbia, Canada, and the U.S. states of Alaska, Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. Sample sites represent a diverse array of river and stream habitats (e.g., headwater, mainstem, side channel), in watersheds with diverse land uses (e.g., urban, wilderness, agricultural), and disturbance histories (e.g., fire, restoration). Collected between 1997 and 2024, the data span the full calendar year and capture daily and seasonal patterns in drift abundance and biomass densities. When paired with water quality and quantity data as well as remotely sensed environmental landscape data, such as land use/land cover, climate, and disturbance history, channel morphology, and riparian vegetation composition, the DRIFteRS dataset can aid in identifying key drivers of drift invertebrate densities and mean body size and support predictive modeling in unsampled locations and times. The dataset may also be used to analyze aquatic‐terrestrial resource flows, derive prey‐encounter rates and profitability (mean prey size), and inform broader investigations of sit‐and‐wait foraging ecology, especially when paired with data on drift‐foraging predators. For salmonid‐focused applications, the dataset can be integrated into habitat evaluation models, including bioenergetic (e.g., Naman et al., 2019) and life cycle models (e.g., Beechie et al., 2023), to improve estimates of habitat capacity and population dynamics for river‐ and stream‐rearing salmonids. Understanding prey availability dynamics is increasingly important, because rising water temperatures increase salmonid metabolic demands (Crozier et al., 2010). Flow regime transitions (i.e., snow or glacier dominated to rain dominated; Beechie et al., 2013), wildfire frequency and intensity (Hessburg et al., 2021), as well as plant community and phenology shifts (Cleland et al., 2007; Franklin et al., 2016) are all predicted to change with rising temperatures and are potential drivers of terrestrial and aquatic invertebrate prey quality and availability in lotic systems. These insights can ultimately inform restoration prioritization and design, helping managers consider food resource implications when evaluating restoration priorities and match habitat improvement to food supply. The data are released under the Creative Commons Attribution 4.0 International license and may be reused with attribution.

1 October 2024 in Aquatic Sciences
Verified
Journal Article
Closed access
PDF file
ETElsa K Toskey
Elsa K Toskey
SBStephen M. Bollens
Stephen M. Bollens
PKPeter Kiffney
Peter Kiffney
KMKyle D. Martens
Kyle D. Martens
Gretchen Rollwagen-BollensGretchen Rollwagen-Bollens
Gretchen Rollwagen-Bollens