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Updating Illinois Stream Biological Characterizations and Assessments using Species Distribution Modeling
Schartel, Tyler; Cao, Yong; Hinz, Leon C. Jr.; Metzke, Brian
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https://hdl.handle.net/2142/128018
Description
- Title
- Updating Illinois Stream Biological Characterizations and Assessments using Species Distribution Modeling
- Author(s)
- Schartel, Tyler
- Cao, Yong
- Hinz, Leon C. Jr.
- Metzke, Brian
- Issue Date
- 2025-03-26
- Keyword(s)
- Illinois Department of Natural Resources
- Species distribution models
- Fish
- Freshwater mussels
- Mayflies
- Stoneflies
- Caddisflies
- Biodiversity
- Habitat
- Aquatic insects
- Environmental Management
- Stewardship
- Private Stakeholders
- Conservation
- Streams
- Decision-making
- Watch List species
- Species of Greatest Conservation Need
- Biogeographical ignorance
- Biological Stream Characterization
- Biologically Significant Streams
- Assessment
- Date of Ingest
- 2025-04-30T15:07:53-05:00
- Geographic Coverage
- Illinois
- Abstract
- This project updated the Biological Stream Characterization (BSC) and Biologically Significant Streams (BSS) assessments to facilitate their continued use by the Illinois Department of Natural Resources (IDNR) and state partners in characterizing biological conditions and assemblages in Illinois’ running waters. Both assessments were revised by developing biological references based on species distribution models (SDMs) for fishes, freshwater mussels, and EPT (Ephemeroptera [mayflies], Plecoptera [stoneflies], and Trichoptera [caddisflies]) in stream reaches throughout the State of Illinois. Stream reaches were graded independently for each of these taxonomic groups, and all groups collectively, based on the degree of correspondence between observed conditions or biodiversity and reference biological expectations. Updated BSC grades focus on the within-reach ncorrespondence between expected and observed habitat suitability for fish, mussel, and aquatic insect assemblages (i.e., integrity). Updated BSS grades identify those stream reaches with observed conditions having more intact and diverse assemblages relative to expected conditions. Updated grades for both assessments were applied to Illinois streams statewide to improve IDNR ability to deliver intuitive information about ecological integrity, management, and aquatic biodiversity to the Illinois public, as well as form stewardship collaborations between state agencies and private stakeholders. Species of Greatest Conservation Need (SGCN) and Watch List species were prioritized in project efforts. Project SDM outputs and updated BSC/BSS grades will facilitate conservation and management efforts for these species. In addition, uncertainty in project habitat suitability predictions was characterized relative to the data available to generate them (i.e., biogeographical ignorance; BI). For each species modeled, BI was estimated relative to predicted habitat suitability, the quality of the species’ occurrence records (i.e., the completeness, taxonomic quality, and temporal decay), and the spatio-environmental distance between the stream reaches used as geospatial context. This increased understanding of model uncertainty will further inform conservation and management decision-making, especially for Illinois SGCN and/or Watch-List species, by identifying state streams in need of additional or more intensive survey efforts.
- Publisher
- Illinois Natural History Survey
- Series/Report Name or Number
- Technical Report INHS 2025 (08)
- T-133 Final Summary Report
- Type of Resource
- text
- Genre of Resource
- technical report
- Language
- eng
- Sponsor(s)/Grant Number(s)
- State Wildlife Grants
- Copyright and License Information
- This document is a product of the Illinois Natural History Survey, and has been made available by the Illinois Natural History Survey and the University Library, University of Illinois at Urbana-Champaign. It is intended solely for noncommercial research and educational use, and proper attribution is required.
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Technical Reports - Illinois Natural History Survey PRIMARY
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