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.

Estrogenic activity response to best management practice implementation in agricultural watersheds in the Chesapeake Bay watershed.

Best management practices (BMPs) have been predominantly used throughout the Chesapeake Bay watershed (CBW) to reduce nutrients and sediments entering streams, rivers, and the bay. These practices have been successful in reducing loads entering the estuary and have shown the potential to reduce other contaminants (pesticides, hormonally active compounds, pathogens) in localized studies and modeled load estimates. However, further understanding of relationships between BMPs and non-nutrient contaminant reductions at regional scales using sampled data would be beneficial. Total estrogenic activity was measured in surface water samples collected over a decade (2008-2018) in 211 undeveloped NHDPlus V2.1 watersheds within the CBW. Bayesian hierarchical modeling between total estrogenic activity and landscape predictors including landcover, runoff, BMP intensity, and a BMP*agriculture intensity interaction term indicates a 96% posterior probability that BMP intensity on agricultural land is reducing total estrogenic activity. Additionally, watersheds with high agriculture and low BMPs had a 49% posterior probability of exceeding an effects-based threshold in aquatic organisms of 1 ng/L but only a 1% posterior probability of exceeding this threshold in high-agriculture, high-BMP watersheds.

Environmental and anthropogenic drivers of contaminants in agricultural watersheds with implications for land management.

If not managed properly, modern agricultural practices can alter surface and groundwater quality and drinking water resources resulting in potential negative effects on aquatic and terrestrial ecosystems. Exposure to agriculturally derived contaminant mixtures has the potential to alter habitat quality and negatively affect fish and other aquatic organisms. Implementation of conservation practices focused on improving water quality continues to increase particularly in agricultural landscapes throughout the United States. The goal of this study was to determine the consequences of land management actions on the primary drivers of contaminant mixtures in five agricultural watersheds in the Chesapeake Bay, the largest watershed of the Atlantic Seaboard in North America where fish health issues have been documented for two decades. Surface water was collected and analyzed for 301 organic contaminants to determine the benefits of implemented best management practices (BMPs) designed to reduce nutrients and sediment to streams in also reducing contaminants in surface waters. Of the contaminants measured, herbicides (atrazine, metolachlor), phytoestrogens (formononetin, genistein, equol), cholesterol and total estrogenicity (indicator of estrogenic response) were detected frequently enough to statistically compare to seasonal flow effects, landscape variables and BMP intensity. Contaminant concentrations were often positively correlated with seasonal stream flow, although the magnitude of this effect varied by contaminant across seasons and sites. Land-use and other less utilized landscape variables including biosolids, manure and pesticide application and percent phytoestrogen producing crops were inversely related with site-average contaminant concentrations. Increased BMP intensity was negatively related to contaminant concentrations indicating potential co-benefits of BMPs for contaminant reduction in the studied watersheds. The information gained from this study will help prioritize ecologically relevant contaminant mixtures for monitoring and contributes to understanding the benefits of BMPs on improving surface water quality to better manage living resources in agricultural landscapes inside and outside the Chesapeake Bay watershed.