Aquatic Data & Decision Information Compilation Tool (ADDICT) SARP Science and Data Committee Meeting January 2012 Will Duncan (U.S. Fish and Wildlife.

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Presentation transcript:

Aquatic Data & Decision Information Compilation Tool (ADDICT) SARP Science and Data Committee Meeting January 2012 Will Duncan (U.S. Fish and Wildlife Service) Steve Hartley (U.S. Geological Survey, National Wetlands Research Center) Nicholas Enwright( Five Rivers Services, U.S. Geological Survey, National Wetlands Research Center)

Presentation Overview Project Timeline Early Guidance Viewer Conceptual Framework Inputs Document Library Named Sessions Demo Technical Advisory Group Deliverables Q/A

Project Timeline Winter 2011 Developed Prioritization Tool Subcommittee Developed white paper on Prioritization Tool Summer 2012 Named tool: Aquatic Data & Decision Information Compilation Tool (ADDICT) Developed a proposal for U.S. Geological Survey Science Support Partnership (SSP) funding. Fall 2012 Received partial funding for development of ADDICT Spring 2013 Begin first year of project development?

Prioritization Tool Development – Winter 2011 General survey results from the SARP Science and Data Committee: Prioritization should begin now, not waiting for completion of all SAHP assessments Should be informed by state priorities to a moderate or large degree, but should not be determined solely by the states. Should be applicable at fine and coarse spatial scales. Should consider separately restoration, enhancement, and preservation. Should be informed by the 8 SARP SAHP objectives. The New Prioritization Committee met on January 19, Other needs identified on conference calls and in SAHP included: Components of the tool must be geographically explicit. Tools should be dynamic, capable of integrating new information as it becomes available. Should consider the priorities of SARP’s potential partners. Would be good if it accounted for geographic variation in priorities. Would be more useful if it could depict the major regional priorities from other agencies and NGOs. We should explore ways of integrating biological information (sensu Priority Areas for Freshwater Conservation Action)

Viewer Examples of Base Layers: – Hydrologic Unit Code (HUC 8, 10, 12) – NHD+ – National Wetlands Inventory (NWI) – State and County Boundaries – Cities – Aerial imagery More complex data layers that are relevant to planning restoration and conservation activities for aquatic habitat will also be available for display: – Federal priorities – State priorities – Partners’ priorities – National Fish Habitat Action Plan (NFHAP) assessment data – Data driven assessments Built with ESRI ArcGIS Server Password protected

Conceptual Model

Priorities of Other Partnerships and Entities Rationale for inclusion : To capitalize on the power of partnerships (sharing financial and technical resources to work toward a common goal) Criteria for inclusion : Related to fish habitat Geographically explicit Scientifically defensible Logical (Note, we would need to evaluate whether these priorities meet the criteria above, and we would need to explain how they do to the user.) Atlantic Coast Fish Habitat Partnership Ohio River FHP Inland Coastal

State Priorities Coastal and Inland State Wildlife Action Plans Results of SARPS’s Prioritization Survey indicated that priorities should be informed to a medium-large degree by the states, but not completely by the states. For the coast and inland, state priorities will be determined using two methods. 1) State Wildlife Action Plans will be used to compile all state- identified high priority waters. Although SWAPs identify key issues and important priorities, uniform criteria were not used to identify these waters. Consequently, we will employ a second method. 2) Science and data leads for each state will be asked to supply information on existing statewide efforts and priorities. Description

Federal Priorities Inland Coastal Results of SARP’s Prioritization Survey indicated that priorities should be informed to a medium-large degree by the states, but not completely by the states. For the coast and inland, this module will enable federal agencies to provide their priority areas or datasets that help inform priority setting. An advantage of using federal analyses and priorities is that the results are uniformly developed and transcend state boundaries. For example, USEPA collaborates with states to use scientific information to identify priority watersheds for investing dollars to meet water quality goals. Description

Essential Fish Habitat (EFH) Habitat Areas of Particular Concern (HAPC)

Data Driven Assessments Priority Rivers Rationale for inclusion : Agencies and NGOs have used scientific expertise and data to identify waters in greatest need of protection and restoration. Criteria for inclusion : Regional in scope Geographically explicit Quantitative Accepted approaches within conservation community

Priority Rivers

NFHAP scores (and priorities?) The NFHAP assessment is one of the most robust national assessments ever initiated. It employs multiple datasets that are likely to be related to fish habitat, available at national and catchment scales, and are quantitative. Thus, they are likely to aid in priority setting for restoration, enhancement, and preservation separately- a need identified in the survey.

SARP Assessments SARP is completing assessments that are intended to inform successful completion of the SARP objectives in the Southeast Aquatic Habitat Plan. An advantage of this framework is that we can build this prioritization tool now (per the prioritization survey results), and as these assessments become available, they can be included. Because the assessments can be quantitative, they can fairly easily be integrated into separate prioritizations for restoration vs. enhancement vs. protection.

USGS has developed multiple models that quantitatively evaluate water chemistry. For example, the SPARROW model output for phosphorus and nitrogen loading of streams is particularly useful for impacts to streams, rivers, and probably estuaries. Datasets like these can be used to quantitatively separate areas for restoration vs. preservation. Data Driven Assessments

Model Output The raster layer will be available to the user for query and visual inspection from within the web mapping window. Data will be downloadable for use at the user’s desktop. Users will be allowed to create new sessions and/or return to previous sessions for duplication and editing.

Resource Library A web based “digital library” which can act as a clearinghouse for references to important documents and pertinent resources. – BMPs – Past project documentation – Funding availability – Other Pertinent literature Librarian Role – Populate and maintain content

DEMO

Technical Working Group NameAgencyRole Jon BeckerUS Environmental Protection Agency, Region 4 Water Quality Planning Branch, Monitoring and Information Analysis Section Water Quality information expert Craig Conzelmann U.S. Geological Survey National Wetlands Research Center Application Development Will DuncanU.S. Fish and Wildlife ServiceData analysis/ Aquatic ecology Steve HartleyU.S. Geological Survey National Wetlands Research Center Geospatial data management and analysis Scott RobinsonSoutheast Aquatic Resources PartnershipInteragency collaboration coordinator Mark ScottSouth Carolina Department of Natural ResourcesData analysis/ User interface/Aquatic Ecology Ryan SmithThe Nature ConservancyFish database development and management Mark SramekNational Oceanic and Atmospheric Administration Estuary and marine applications *We requested LCC Science Coordinator involvement in this committee. To date, John Tirpak (Gulf Coastal Prairie and Ozarks LCC), James Broska (Great Plains LCC), and Steve Traxler (Peninsular Florida LCC) have agreed to participate.

Restoration vs. Enhancement vs. Protection Example output from riparian assessment: Quantitative datasets lend themselves to approaches that can separate restoration options from preservation options. For example, there are multiple utilities for the riparian assessment, although none have been developed to date. One possibility is that all riparian in the analysis is quantitatively given a relevance score. The score is easily generated based on the expected relationship (or relevance) to the conservation objective (e.g. restoring cold water conditions for trout via riparian restoration). When the score is used with the “% disturbed riparian dataset,” it can be used as a guide to separate and weigh restoration vs. enhancement vs. protection strategies. Using the graph on the right, sites that are highly relevant and have low % disturbed riparian are prime candidates for conservation. Those that are highly relevant but have a little bit of disturbed riparian are high candidates for riparian restoration. The degree to which we want to pursue a restoration option is indicated by the number of plus signs. Bottom line: We need to develop better ways of using existing data to determine where our options are for protection vs. restoration. Here’s one option, of several: