Standardized protocols for sensor-based chlorophyll monitoring are now available for use by staff around the system to implement high frequency chlorophyll monitoring at their reserves.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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This tool provides an overview of acoustic monitoring in aquatic ecosystems, including sources of sound, metrics for measurement, data collection and analysis, and applications for habitat assessment, stewardship, and education.
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This decision support tool, developed as part of a 2017 collaborative research project, allows users to select different combinations of tidal range, suspended sediment, ditch density, and sea-level rise variables and visualize predicted outcomes over different time frames.
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This curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.
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These guidance documents and videos provide field and lab protocols for preparing for, collecting and fitering water samples for use in eDNA analyses.
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These resources from a stakeholder visit to the Stariski Creek Meadows headwaters in July 2019 were developed as part of a project to improve groundwater management on the Kenai Peninsula, Alaska.
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This geodatabase of groundwater on the Kenai Peninsula, Alaska, can be used as a foundation for decision-making to determine the locations of aquifers and predict groundwater discharge to streams.
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This stakeholder engagement plan outlines an approach to strengthen stakeholder networks and advance blue carbon conversations in the Kenai Lowlands, Alaska.
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This focus group template is part of a training and facilitation toolkit, developed to help coastal leaders use the Alaska Fisheries Resilience Index to promote coastal resilience.
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A 2018 catalyst project developed tools for working with SET data including a series of computer codes - R scripts - for processing, quality checking, analyzing and visualizing these complex datasets. The statistical codes re available through GitHub and are explained in a Guide to the SETr Workflow.