Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Richard H Walker; Matthew J Ashton; Matthew J Cashman; Rosemary M Fanelli; Kevin P Krause; Gregory B Noe; Kelly O Maloney

doi:10.1016/j.scitotenv.2021.147985

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Sci Total Environ. 2021 Oct 1:789:147985. doi: 10.1016/j.scitotenv.2021.147985. Epub 2021 May 24.

Authors

Richard H Walker¹, Matthew J Ashton², Matthew J Cashman³, Rosemary M Fanelli⁴, Kevin P Krause⁵, Gregory B Noe⁶, Kelly O Maloney⁵

Affiliations

¹ U.S. Geological Survey, Eastern Ecological Science Center at the Leetown Research Laboratory, Kearneysville, WV, USA. Electronic address: rhwalker@usgs.gov.
² Maryland Department of Natural Resources, Monitoring and Non-Tidal Assessment Division, Annapolis, MD, USA.
³ U.S. Geological Survey, Maryland-Delaware-District of Columbia Water Science Center, Baltimore, MD, USA.
⁴ U.S. Geological Survey, South Atlantic Water Science Center, Raleigh, NC, USA.
⁵ U.S. Geological Survey, Eastern Ecological Science Center at the Leetown Research Laboratory, Kearneysville, WV, USA.
⁶ U.S. Geological Survey, Florence Bascom Geoscience Center, Reston, VA, USA.

PMID: 34323823
DOI: 10.1016/j.scitotenv.2021.147985

Abstract

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape (e.g., elevation, longitude, latitude, geology) and land use (i.e., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality (e.g., total nitrogen and conductivity) and habitat (e.g., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species (e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Keywords: Benthic macroinvertebrates; Fishes; Maryland; Streams; Structural equation modeling; Total effects.

Published by Elsevier B.V.