Technoscience and the modernization of freshwater fisheries assessment and management

Inland fisheries assessment and management are challenging given the inherent com- plexity of working in diverse habitats (e.g., rivers, lakes, wetlands) that are dynamic on organisms that are often cryptic and where fishers are often highly mobile. Yet, technoscience is offering new tools that have the potential to reimagine how inland fisheries are assessed and managed. So-called ‘‘technoscience’’ refers to instances in which science and technology unfurl together, offering novel ways of spurring and achieving meaningful change. This paper considers the role of technoscience and its potential for modernizing the assessment and management of inland fisheries. It first explores technoscience and its potential benefits, followed by presentation of a series of synopses that explore the application (both successes and challenges) of new tech- nologies such as environmental DNA (eDNA), genomics, electronic tags, drones, phone apps, iEcology, and artificial intelligence to assessment and management. The paper also considers the challenges and barriers that exist in adopting new technologies. The paper concludes with a provocative assessment of the potential of technoscience to reform and modernize inland fisheries assessment and management. Although these tools are increasingly being embraced, there is a lack of platforms for aggregating these data streams and providing managers with actionable information in a timely manner. The ideas presented here should serve as a catalyst for beginning to work collectively and collaboratively towards fisheries assessment and management systems that harness the power of technology and serve to modernize inland fisheries management. Such transformation is urgently needed given the dynamic nature of environmental change, the evolving threat matrix facing inland waters, and the complex behavior of fishers. Quite simply, a dynamic world demands dynamic fisheries management; technoscience has made that within reach.publishedVersio

Identifying non-independent anthropogenic risks using a behavioral individual-based model

Anthropogenic disturbances contribute to an animal\u27s perception of and responses to the predation risk of its environment. Because an animal rarely encounters threatening stimuli in isolation, multiple disturbances can act in non-independent ways to shape an animal\u27s landscape of fear, making it challenging to isolate their effects for effective and targeted management. We present extensions to an existing behavioral agent-based model (ABM) to use as an inverse modeling approach to test, in a scenario-sensitivity analysis, whether threatened Alberta boreal caribou (Rangifer tarandus caribou) differentially respond to industrial features (linear features, forest cutblocks, wellsites) and their attributes: presence, density, harvest age, and wellsite activity status. The spatially explicit ABM encapsulates predation risk, heterogeneous resource distribution, and species-specific energetic requirements, and successfully recreates the general behavioral mechanisms driving habitat selection. To create various industry-driven, predation-risk landscape scenarios for the sensitivity analysis, we allowed caribou agents to differentially perceive and respond to industrial features and their attributes. To identify which industry had the greatest relative influence on caribou habitat use and spatial distribution, simulated caribou movement patterns from each of the scenarios were compared with those of actual caribou from the study area, using a pattern-oriented, multi-response optimization approach. Results revealed caribou have incorporated forestry- and oil and gas features into their landscape of fear that distinctly affect their spatial and energetic responses. The presence of roads, pipelines and seismic lines, and, to a minor extent, high-density cutblocks and active wellsites, all contributed to explaining caribou behavioral responses. Our findings also indicated that both industries produced interaction effects, jointly impacting caribou spatial and energetic patterns, as no one feature could adequately explain anti-predator movement responses. We demonstrate that behavior-based ABMs can be applied to understanding, assessing, and isolating non-consumptive anthropogenic impacts, in support of wildlife management