Assessment of Long-Term Trends in Fish Distributions at Multiple Scales Decreases Uncertainty Associated with Historical Datasets.

Abstract:

:Monitoring long-term changes in aquatic biodiversity requires the effective use of historical data that were collected with different methods and varying levels of effort. Aggregating data into different spatial scales can control for such differences and provide a robust framework for monitoring distribution trends. We used a quantitative, multi-scale assessment to evaluate the potential drivers of distribution change for 60 fish species at three spatial scales, using 503 unique sampling events conducted between 1931 and 2019 in a stream biodiversity hotspot (French Creek, Pennsylvania, U.S.A). Trends delineated at multiple scales demonstrated that only one cyprinid species consistently declined through time. In contrast, several species, particularly centrarchids (bass and sunfish), appeared to increase with time. However, evidence for species' increases varied among the different spatial scales, and our observations suggest that differences in effort and detection across time periods may contribute to patterns of species increases. There was agreement among scales that agricultural land use, non-native brown trout (Salmo trutta), and anthropogenic barriers did not explain patterns in biodiversity change from the distribution trends in this study. The lack of species declines is likely due to the limited levels of historical impacts in the watershed compared with other locations in the region that experienced more acute pollution bottlenecks. Species increases were most prevalent for sportfish and baitfish species, suggesting that distribution increases were human mediated. Similar multi-scale assessments should provide more robust insight into patterns of biodiversity loss and distribution changes by maximizing the use of historical data.

journal_name

Environ Manage

journal_title

Environmental management

authors

Kirk MA,Wissinger SA

doi

10.1007/s00267-020-01298-1

subject

Has Abstract

pub_date

2020-07-01 00:00:00

pages

136-148

issue

1

eissn

0364-152X

issn

1432-1009

pii

10.1007/s00267-020-01298-1

journal_volume

66

pub_type

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