Preprint Article Version 1 This version is not peer-reviewed

Understanding Landscape Influences on Aquatic Fauna across the Central and Southern Appalachians

Version 1 : Received: 24 September 2018 / Approved: 26 September 2018 / Online: 26 September 2018 (05:23:02 CEST)

How to cite: Hanks, R.D.; Leonard, P.B.; Baldwin, R.F. Understanding Landscape Influences on Aquatic Fauna across the Central and Southern Appalachians. Preprints 2018, 2018090499 (doi: 10.20944/preprints201809.0499.v1). Hanks, R.D.; Leonard, P.B.; Baldwin, R.F. Understanding Landscape Influences on Aquatic Fauna across the Central and Southern Appalachians. Preprints 2018, 2018090499 (doi: 10.20944/preprints201809.0499.v1).

Abstract

Understanding influences of multiple stressors across the landscape on aquatic biota is important for conservation, as it allows for an understanding of spatial patterns and informs stakeholders of significant conservation value.  Data exists for land use/landcover (LULC) and other physicochemical components of the landscape throughout the Appalachian region yet biological data is sparse.  This dearth of biological data relative to LULC and physicochemical data creates difficulties in making informed management and conservation decisions across large landscapes.  At the HUC12 watershed scale we sought to create a single score for both abiotic and biotic values throughout the central and southern Appalachian region.  We used boosted regression trees (BRT) to model biological responses (fish and aquatic macroinvertebrate variables) to abiotic variables.  Variance explained by BRT models ranged from 62-94%.  We categorized both predictor and response variables into themes and targets respectively to better understand large scale patterns on the landscape that influence biological condition of streams.  We combined predicted values for a suite of response variables from BRT models to create a single watershed score for aquatic macroinvertebrates and fish.  Regional models were developed for fish but we were unable to develop regional models for aquatic macroinvertebrates due to the low number of sample sites.  There was strong correlation between regional and global watershed scores for fish models but not between fish and aquatic macroinvertebrate models.  Use of such multimetric scores can inform managers, NGOs, and private land owners regarding land use practices; thereby contributing to largescale landscape scale conservation efforts.

Subject Areas

aquatics; modeling; boosted regression trees; appalachians

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.