Using natural landscape and instream habitat to identify stream reference groups for bioassessment

The two K-means analyses resulted in six groups that represented both regional differences and reach-scale geomorphological differences. We determined that there were two regions, West and East that were primarily distinguished by mean annual precipitation. Tier II clustering identified Plains and Valley stream groups in both the East and West regions. These groups represented shallow, run-dominated, sand bed streams, and relatively deep, pool dominated, silty streams, respectively. The East region possessed two additional stream groups (<i>i.e</i>., Hills and Highlands groups), each with rocky substrate and riffle channel units that broke up the runs and pools in the stream. Of these, the Hills group was more prone to having pools than runs and had low nutrient concentrations compared to the Highlands group. We found that the six groups explained variability in habitat and water chemistry as well as the previous 13 ecoregion-based reference groups. Further, we confirmed that the groups were not the result of common anthropogenic influences on stream ecosystems. The six groups were subsequently organized into three stream archetypes, Plains (East and West), Valley (East and West) and Rocky (Hills and Highlands). We expect these six hierarchical stream groups and three archetypes to be useful in evaluating biotic communities in Oklahoma moving forward.

Authors

Institutions

Publication Details

Journal
PeerJ
Published
2025-10-21
DOI
https://doi.org/10.7717/peerj.20234
Primary Topic
Fish Ecology and Management Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using natural landscape and instream habitat to identify stream reference groups for bioassessment

Joseph J. Dyer, Joseph E. Flotemersch, Daniel Dvorett
PeerJ
Fish Ecology and Management Studies
article

Using natural landscape and instream habitat to identify stream reference groups for bioassessment

Joseph J. Dyer, Joseph E. Flotemersch, Daniel Dvorett
article en

Abstract

The two K-means analyses resulted in six groups that represented both regional differences and reach-scale geomorphological differences. We determined that there were two regions, West and East that were primarily distinguished by mean annual precipitation. Tier II clustering identified Plains and Valley stream groups in both the East and West regions. These groups represented shallow, run-dominated, sand bed streams, and relatively deep, pool dominated, silty streams, respectively. The East region possessed two additional stream groups (<i>i.e</i>., Hills and Highlands groups), each with rocky substrate and riffle channel units that broke up the runs and pools in the stream. Of these, the Hills group was more prone to having pools than runs and had low nutrient concentrations compared to the Highlands group. We found that the six groups explained variability in habitat and water chemistry as well as the previous 13 ecoregion-based reference groups. Further, we confirmed that the groups were not the result of common anthropogenic influences on stream ecosystems. The six groups were subsequently organized into three stream archetypes, Plains (East and West), Valley (East and West) and Rocky (Hills and Highlands). We expect these six hierarchical stream groups and three archetypes to be useful in evaluating biotic communities in Oklahoma moving forward.

PeerJVol. 13
Oklahoma City University (US), TutorGen (United States) (US)
Openalex Percentile: Top 70%
Fish Ecology and Management Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.