Multiple mode of action (MOA) frameworks have been developed in aquatic ecotoxicology, mainly based on fish toxicity. These frameworks provide information on a key determinant of chemical toxicity, but the MOA categories and level of specificity remain unique to each of the classification schemes. The present study aimed to develop a consensus MOA assignment within EnviroTox, a curated in vivo aquatic toxicity database, based on the following MOA classification schemes: Verhaar (modified) framework, Assessment Tool for Evaluating Risk, Toxicity Estimation Software Tool, and OASIS. The MOA classifications from each scheme were first collapsed into one of 3 categories: non–specifically acting (i.e., narcosis), specifically acting, or nonclassifiable. Consensus rules were developed based on the degree of concordance among the 4 individual MOA classifications to attribute a consensus MOA to each chemical. A confidence rank was also assigned to the consensus MOA classification based on the degree of consensus. Overall, 40% of the chemicals were classified as narcotics, 17% as specifically acting, and 43% as unclassified. Sixty percent of chemicals had a medium to high consensus MOA assignment. When compared to empirical acute toxicity data, the general trend of specifically acting chemicals being more toxic is clearly observed for both fish and invertebrates but not for algae. EnviroTox is the first approach to establishing a high‐level consensus across 4 computationally and structurally distinct MOA classification schemes. This consensus MOA classification provides both a transparent understanding of the variation between MOA classification schemes and an added certainty of the MOA assignment. In terms of regulatory relevance, a reliable understanding of MOA can provide information that can be useful for the prioritization (ranking) and risk assessment of chemicals. Environ Toxicol Chem 2019;38:2294–2304. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Wireless sensor networks (WSNs) are increasingly becoming a critical tool for growers and researchers. We describe how the technology has advanced, starting with a commercially available WSN node and pushing the technology to make the data more meaningful, actionable and to add advanced irrigation control functionality. User features such as spatial views, custom charts, real-time data access, remote access, irrigation control, alerts, and plant models help create an advanced WSN system that is user centric. Growers and researchers were involved in the design process by directly communicating with the design engineers, and continuously using and testing new features, resulting in a user-centric design and experience. The results of this research are being rolled into a new line of commercial products and is continuously evolving based on user feedback and interaction.

This paper establishes a distributed data fusion method for ad hoc networks, enabling each device or agent to operate autonomously and collaboratively. In such a network, no infrastructure exists for centralized processing, and a lack offixed network membership creates ambiguous data fusion and reasoning architectures, communications patterns, and communications timing. The resulting data fusion method is shown to be consistent with other methods, including known architectures with closed-form solutions. The paper also applies the method to a short analysis of distributed data fusion with non-deterministic communications duty cycle where existing methods are impractical.

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