Large-scale variation in density of an aquatic ecosystem indicator species

Chris Sutherland*, Angela K. Fuller, J. Andrew Royle, Matthew P. Hare, Sean Madden

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Monitoring indicator species is a pragmatic approach to natural resource assessments, especially when the link between the indicator species and ecosystem state is well justified. However, conducting ecosystem assessments over representative spatial scales that are insensitive to local heterogeneity is challenging. We examine the link between polychlorinated biphenyl (PCB) contamination and population density of an aquatic habitat specialist over a large spatial scale using non-invasive genetic spatial capture-recapture. Using American mink (Neovison vison), a predatory mammal and an indicator of aquatic ecosystems, we compared estimates of density in two major river systems, one with extremely high levels of PCB contamination (Hudson River), and a hydrologically independent river with lower PCB levels (Mohawk River). Our work supports the hypothesis that mink densities are substantially (1.64-1.67 times) lower in the contaminated river system. We demonstrate the value of coupling the indicator species concept with well-conceived and spatially representative monitoring protocols. PCBs have demonstrable detrimental effects on aquatic ecosystems, including mink, and these effects are likely to be profound and long-lasting, manifesting as population-level impacts. Through integrating non-invasive data collection, genetic analysis, and spatial capture-recapture methods, we present a monitoring framework for generating robust density estimates across large spatial scales.

Original languageEnglish
Article number8958
Number of pages10
JournalScientific Reports
Volume8
DOIs
Publication statusPublished - 12 Jun 2018

Fingerprint

Dive into the research topics of 'Large-scale variation in density of an aquatic ecosystem indicator species'. Together they form a unique fingerprint.

Cite this