How we count counts: Examining influences on detection during shoreline surveys of marine debris.

Shoreline surveys are a common approach for documenting loads of marine macrodebris (≥ 2.5 cm). When surveys are conducted repeatedly over time and space, patterns in source, abundance, geographic distribution, and composition can be detected.

Walking the talk: The responsibility of the scientific community for mitigating conference-generated waste.

An estimated 19-23 million metric tons of global plastic waste reportedly entered aquatic environments in 2016 with mounting evidence that plastic marine debris causes ecological effects across all levels of biological organization in aquatic systems. Scientific conferences generate opportunities for waste through food and beverage services, giveaways, marketing and registration materials, poster and trade exhibits, attendee travel, lodging services, and local transportation. Zero waste measures instituted at the Sixth International Marine Debris Conference resulted in the avoidance of 76,300 single-use items.

The multiple stressor ecological risk assessment for the mercury-contaminated South River and upper Shenandoah River using the Bayesian network-relative risk model.

We have conducted a regional scale risk assessment using the Bayesian Network Relative Risk Model (BN-RRM) to calculate the ecological risks to the South River and upper Shenandoah River study area. Four biological endpoints (smallmouth bass, white sucker, Belted Kingfisher, and Carolina Wren) and 4 abiotic endpoints (Fishing River Use, Swimming River Use, Boating River Use, and Water Quality Standards) were included in this risk assessment, based on stakeholder input. Although mercury (Hg) contamination was the original impetus for the site being remediated, other chemical and physical stressors were evaluated.

Evaluating nonindigenous species management in a Bayesian networks derived relative risk framework for Padilla Bay, WA, USA.

Many coastal regions are encountering issues with the spread of nonindigenous species (NIS). In this study, we conducted a regional risk assessment using a Bayesian network relative risk model (BN-RRM) to analyze multiple vectors of NIS introductions to Padilla Bay, Washington, a National Estuarine Research Reserve. We had 3 objectives in this study.