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

Elevation-associated pathways mediate aquatic biodiversity at multi-trophic levels along a plateau inland river

Aquatic biodiversity plays a significant role in maintaining the ecological balance and the overall health of riverine ecosystems. Elevation is an important factor influencing biodiversity patterns. However, it is still unclear through which pathway elevation influences riverine biodiversity at different trophic levels. In this study, the elevation-associated pathways affecting aquatic biodiversity at different trophic levels were explored using structural equation modeling (SEM) and taking the Bayin River, China as the case. The results showed that the elevational patterns were different among aquatic organisms at different trophic levels. For macroinvertebrates and bacteria, the pattern was hump-shaped; while for phytoplankton and zooplankton, it was U-shaped. Building upon these observed elevational patterns, our investigation delved into the direct and indirect pathways through which elevation influences aquatic biodiversity. We found that elevation exerts an impact on aquatic biodiversity via indirect pathways. For all aquatic organisms investigated, the major pathway through which elevation influences biodiversity is mediated by water temperature and water quality. For aquatic organisms at higher trophic levels, like macroinvertebrates and zooplankton, the crucial pathway is also mediated by the landscape. The results of this study contributed to understanding the effects of elevation on aquatic organisms at different trophic levels and provided an important basis for the assessment of riverine biodiversity at large scales.

Causal inference approaches reveal both positive and negative unintended effects of agricultural and urban management practices on instream biological condition

Agricultural and urban management practices (MPs) are primarily designed and implemented to reduce nutrient and sediment concentrations in streams. However, there is growing interest in determining if MPs produce any unintended positive effects, or co-benefits, to instream biological and habitat conditions. Identifying co-benefits is challenging though because of confounding variables (i.e., those that affect both where MPs are applied and stream biota), which can be accounted for in novel causal inference approaches. Here, we used two causal inference approaches, propensity score matching (PSM) and Bayesian network learning (BNL), to identify potential MP co-benefits in the Chesapeake Bay watershed portion of Maryland, USA. Specifically, we examined how MPs may modify instream conditions that impact fish and macroinvertebrate indices of biotic integrity (IBI) and functional and taxonomic endpoints. We found evidence of positive unintended effects of MPs for both benthic macroinvertebrates and fish indicated by higher IBI scores and specific endpoints like the number of scraper macroinvertebrate taxa and lithophilic spawning fish taxa in a subset of regions. However, our results also suggest MPs have negative unintended effects, especially on sensitive benthic macroinvertebrate taxa and key instream habitat and water quality metrics like specific conductivity. Overall, our results suggest MPs offer co-benefits in some regions and catchments with largely degraded conditions but can have negative unintended effects in some regions, especially in catchments with good biological conditions. We suggest the number and types of MPs drove these mixed results and highlight carefully designed MP implementation that incorporates instream biological data at the catchment scale could facilitate co-benefits to instream biological conditions. Our study underscores the need for more research on identifying effects of individual MP types on instream biological and habitat conditions.

Identifying Key Stressors Driving Biological Impairment in Freshwater Streams in the Chesapeake Bay Watershed, USA

Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.