Delaware’s Parcel-Based Biodiversity

Model

Department of Natural Resources and Environmental Control, and Department of

Agriculture Partnership

Proposed developments since

August 1999

as mapped by Rob Line.

DNREC - DE Dept. of Agriculture Partnership

A two-pronged approach has been taken:1. Short-term immediate biodiversity model using

the best available existing data to identify biodiversity “hot spots”; and

2. Long-term BioLegacy project that depicts habitats and species at a fine scale.

Short-term Biodiversity Model

DE DDA offered to create a tax parcel-based model on “biodiversity value” and to use the model in their funding programs

Project builds on DDA’s experience using a computer model (“LESA” = Land Evaluation and Site Assessment) for agricultural preservation that includes:

•Parcel-based evaluation•Ranking system

Contributors in Biodiversity Model ProjectBiodiversity Conservation Partnership

Science Team SubcommitteeDE Department of Agriculture

DE Dept. of Natural Resources & Environmental ControlU.S. Fish &Wildlife

The Nature Conservancy

• Mark Davis, Planner, DE Dept. of AgricultureMark Davis, Planner, DE Dept. of Agriculture• Karen Bennett, Program Manager, DE Natural Heritage ProgramKaren Bennett, Program Manager, DE Natural Heritage Program• Rob Line, Title, DE Parks & Recreation DivisionRob Line, Title, DE Parks & Recreation Division• Mark Biddle, Title, Water Assessment BranchMark Biddle, Title, Water Assessment Branch• Ellen Roca, The Nature Conservancy of DEEllen Roca, The Nature Conservancy of DE• Greg Breese, USF&WGreg Breese, USF&W• Sherri Evans-Stanton, Biodiversity Coordinator, DNRECSherri Evans-Stanton, Biodiversity Coordinator, DNREC• Robert Zimmerman, Office of the Secretary, DNRECRobert Zimmerman, Office of the Secretary, DNREC• Bennett and Williams, ConsultantBennett and Williams, Consultant• Thompson Mapping Systems, Inc.Thompson Mapping Systems, Inc.

Biodiversity Modeling Tool includes the following components:

1. Selecting relevant data layers;2. Assigning scores and weights for each data layer based on how

well each represents the presence of biodiversity;3. Combining data layers to create “biodiversity layer”; 4. Testing the data to make sure it meets expectations;5. Producing maps;6. Developing comprehensive strategies to target state and federal

funds to protect biodiversity;7. Serving as underlying data layer in supporting the Green

Infrastructure Subcommittee of the Livable Delaware Advisory Council; and

8. Leading effort to revise the State Strategies Maps.

Data Sets Considered in Biodiversity Model

• Delaware Natural Heritage Program (DHP)• 1997 Forest Cover Greater than 25 Acres• Riparian Forests• Statewide Wetland Mapping Project (SWAMP)• Shorebird Conservation Migration• Schuster’s Horseshoe Crab Spawning Areas Analysis

• Eco Regional System (TNC)• GAP Modeling

– Vegetative Mapping– Protected Areas– Species Models (Likely Existence)

• Corridor Mapping Project• Source Water Assessment• Stream Habitat Assessment• Protected Areas

Criteria for Including Data Set in Biodiversity Model

• Data must include Statewide coverage and be representative of habitat or species locations and must also be:

Reliable Accurate Complete GIS-ready

• Data layers derived from other existing data were not used to avoid “double counting”.

• Each data layer was individually evaluated for inclusion in the model and pros and cons were discussed.

• After data layers were selected, each layer was divided into 3-4 components and each component was assigned a score. The data layer were then assigned weighted values based on biodiversity indication significance.

• Values were transformed into an overlay map depicting normalized values that fit into a color legend scaled to represent the levels of predicted biodiversity present.

• The overlay map was then combined with the parcel data through intersection to yield a parcel-based biodiversity map which predicts which parcels have higher biodiversity significance.

Rare Species (DNHP) LayerSource: Delaware Natural Heritage Program

1. Buffered each record of rare species (i.e., its lat/long) by 50 m to create circular polygon for each record. Did not take taxonomy / ecology into consideration, thus buffered points not clipped to habitat (e.g., forest edge, stream width/length), area needs not considered..

2. Combined (union) overlapping polygons and calculated “total point value” for each polygon based on characteristics for each record of a rare species contained within the polygon. For each lat/long record, incorporated the following:

- Global rank:If species is Globally Rare (G1 to G3), earned 100 points.

- State rank: If species is NOT Globally Rare but is State Rare (S1), earned 10 points.If species is NOT Globally Rare, but is State Uncommon (S2), earned 5 points.

- Density class (Based on cluster analysis, three classes including 1) Thiessen area, 2) Distance to nearest 10 rare species, 3) Number of rare species within a buffer distance of 100, 500, 1000, 3000):

If class 1, then high density, multiply points by 3.If class 2, then medium density, multiply points by 2.If class 3, then low density, multiply points by 1.

3. Total Point Value for each polygon = ([# Globally Rare x 100 x density class]) + [# State Rare x 10 x density class] + [# State Uncommon x 5 x density class])

Total Point Values for each Rare Species Polygon ranged from 5 to 1,260.

4. Scores assigned to polygons:Rare Species Polygons with Total Point Value of 200 to 420 assigned a ranked score of 9. (More than one G1-G3, multiple S1 and S2).Rare Species Polygons with Total Point Value of 90 to 190 assigned a rank score of 7. (At least one G1-G3, multiple S1 and S2).Rare Species Polygons with Total Point Value of 25 to 85 assigned a rank score of 5. (One-two S1 and one - several S2 or several S2).Rare Species Polygons with Total Point Value of 5 to 20 assigned a rank score of 3. (Mostly S2, a few S1).

Forest Cover Greater than 25 AcresSource: Delaware Division of Parks & Recreation, DNREC

1992 infrared and 1997 black and white aerial photos

• Data type: Habitat • Mapping was done at a scale of 1:3,000 in ArcView• Data is currently ranked by the following:

– Overall Size – Interior Forest Size – Connectivity to other habitats likely to support some of the same species

(range from isolated from other habitats (score=0) to directly connected to other large tracts (score=4).

– Element Occurrences, Rare Species and Habitats (evaluated after parcels have been ranked for size and connectivity starting with top ranking parcels).

– Management Potential: Habitat Quality• Three components in score:

High (scored as 9) Medium (scored as 6) Low (scored as 3)

Riparian ForestsSource: Division of Parks & Recreation, DNREC

1997 Data

• Data Type: Habitat

• Data consists of 1600 polygons (hectare and acreage) of actual strips of forested corridors along waters (streams, lakes, Delmarva bays, ditches).

• Data does not include buffers and does not overlap with data covered under forests greater than 25 acres.

• Two components:

– High (scored 6) (Riparian forests where The Nature Conservancy’s diversity index indicated high quality streams)

– Medium/low (scored 3)

Statewide Wetlands Mapping Project (SWAMP)Source: Water Assessment Branch, DNREC

1992 data using aerial color infrared photography (1:12,000 scale)

• Data Type: Habitat

• Photo interpretation experts determined location of wetlands using aerials and other background information (e.g., NWI, soils)

• Wetland “polygons” are labeled (using the Cowardin, et al. classification system) to describe wetland class, water regime, dominant vegetation type and other formative or impacting factors.

• State of Delaware modifier added in some cases for special community types.

• Data includes types of hydrology and types of vegetation.

• High function/high value reflected by assigned scores: Marine (low – score of 3) Estuarine, riverine and lacustrine (ponds, lakes) (medium – score of 3) Palustrine (high – score of 9)

Shorebird Spring Migratory Concentration AreasSource: Delaware Coastal Programs, DNREC

Delaware Bay Only, Pre-2002

Red Knot Points Ruddy Turnstone PointsExtremely High 200 Extremely High 80High 100 High 25Moderate 50 Moderate 10Occasional 25Rare 10

1. Systematic counts of birds using bayshore made from boat, data used to characterize level of shorebird use for at least two species: Red Knot and Ruddy Turnstone.

2. Lengths of bay-front beach delineated as polygons and ranked according to level of use.

3. Total Point Value calculated for each polygon according to points assigned by level of use within species:

4. Total Point Values calculated for each polygon ranged from 20-280.5. Scores assigned to polygons:

• Rare Species Polygons with Total Point Value of 200 to 420 assigned a ranked score of 9. (Extremely high use).• Rare Species Polygons with Total Point Value of 90 to 190 assigned a rank score of 7. (High use.).• Rare Species Polygons with Total Point Value of 25 to 85 assigned a rank score of 5. (Moderate use.).• Rare Species Polygons with Total Point Value of 5 to 20 assigned a rank score of 3. (Rare to moderate use).

Horseshoe Crab Spawning AreasSource: Delaware Bay Estuary Project, U.S. Fish and Wildlife Service

(Data from 1978-1996; Metadata available)

1. Identified spawning beaches using information from multiple sources (Schuster, Day, and Swann), including ground surveys.

2. USFWS buffered use areas by 1 km to create polygons, and subdivided into High and Moderate use areas.

3. Scores assigned to polygons:

High use areas = 6 Moderate use areas = 3

Data Layer Component Score Weight

Rare Species (DNHP) Very High 9 9High 7 9Medium 5 9Low 3 9

Shorebird Spring Migratory Areas Very High 9 8 (Bay only) High 7 8

Medium 5 8Low 3 8

Forest Cover* High 9 7Medium 6 7Low 3 7

Wetlands High 9 6Medium 6 6Low 3 6

Riparian Forests** High 9 3Med/Low 5 3

Horseshoe Crab Spawning Areas High 6 2Medium 3 2

Biodiversity Model

Biodiversity Model Overlay

Creation of Parcel-Based Model

• Intersect Parcel Polygons with Biodiversity Overlay Polygons;

• Calculate the % of each overlay polygon within each parcel polygon, then multiply by the score of the overlay polygon;

• Sum the results of each to yield the parcel polygon score.

Parcel-Based Biodiversity Model