1. VEGETATION MAPPING AND WILDLIFE MANAGEMENT SEEKING REPEATABLE MEASUREMENT NATIONAL MILITARY FISH & WILDLIFE ASSOCIATION Wednesday, March 12, 2014 Jonathan Dunn AECOM

2. Vegetation Mapping and Wildlife Habitat Outline of Presentation 1.How is a fine-scale vegetation map useful to the Wildlife Manager? 2.How are fine-scale vegetation maps typically produced? 3.How do methods for fine-scale and broad-scale mapping differ? 4.How can these methods be used for monitoring habitats and detecting change?

3. Vegetation Mapping and Wildlife Habitat Concepts An accurate and sufficiently attributed vegetation map is a fundamentally useful base analysis layer for wildlife management Minimum attribution should include finest level of vegetation classification possible (Group < Alliance < Association) and additional compositional and structural characteristics (cover density, heterogeneity, height, etc) But “sufficient” attribution should also consider the habitat requirements and ecologies of the management species

4. Vegetation Mapping and Wildlife Habitat Locating Survey Areas and Quantifying Effort

6. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer

7. NVCS Hierarchy Hierarchy Level Criteria Upper:Physiognomy plays a predominant role. L1 – Formation Classroad combinations of general dominant growth forms that are adapted to basic temperature (energy budget), moisture, and substrate/aquatic conditions. L2 - Formation Subclass Combinations of general dominant and diagnostic growth forms that reflect global macroclimatic factors driven primarily by latitude and continental position, or that reflect overriding substrate/aquatic conditions. L3 – FormationCombinations of dominant and diagnostic growth forms that reflect global macroclimatic factors as modified by altitude, seasonality of precipitation, substrates, and hydrologic conditions. Middle:Floristics and physiognomy play predominant roles L4 – DivisionCombinations of dominant and diagnostic growth forms and a broad set of diagnostic plant species that reflect biogeographic differences in composition and continental differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes. L5 – MacrogroupCombinations of moderate sets of diagnostic plant species and diagnostic growth forms, that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes. L6 – GroupCombinations of relatively narrow sets of diagnostic plant species (including dominants and co-dominants), broadly similar composition, and diagnostic growth forms that reflect regional mesoclimate, geology, substrates, hydrology and disturbance regimes. Lower:Floristics plays a predominant role L7 – AllianceDiagnostic species, including some from the dominant growth form or layer, and moderately similar composition that reflect regional to subregional climate, substrates, hydrology, moisture/nutrient factors, and disturbance regimes. L8 – AssociationDiagnostic species, usually from multiple growth forms or layers, and more narrowly similar composition that reflect topo-edaphic climate, substrates, hydrology, and disturbance regimes.

8. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats include: annual grassland and coastal sage scrub with sparse shrub cover, commonly in association with Eriogonum fasciculatum, Artemisia californica, and Erodium cicutarium Typical habitat includes sparsely vegetated areas (perennial cover less than 30%) with loose, friable, well-drained soil (generally at least 0.5 m deep) and flat or gently rolling terrain. (USFWS, 1997) Stephens' kangaroo rat (Dipodomys stephensi)

9. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats include: annual grassland and coastal sage scrub with sparse shrub cover, commonly in association with Eriogonum fasciculatum, Artemisia californica, and Erodium cicutarium Typical habitat includes sparsely vegetated areas (perennial cover less than 30%) with loose, friable, well-drained soil (generally at least 0.5 m deep) and flat or gently rolling terrain. (USFWS, 1997) Vegetation map NVCS Alliance Association Vegetation map Percent Cover By Stratum Soils NRCS Soil Series Topography USGS DEM Others Stephens' kangaroo rat (Dipodomys stephensi)

10. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats include: annual grassland and coastal sage scrub with sparse shrub cover, commonly in association with Eriogonum fasciculatum, Artemisia californica, and Erodium cicutarium Typical habitat includes sparsely vegetated areas (perennial cover less than 30%) with loose, friable, well-drained soil (generally at least 0.5 m deep) and flat or gently rolling terrain. (USFWS, 1997) Vegetation map NVCS Alliance Association Vegetation map Percent Cover By Stratum Soils NRCS Soil Series Topography USGS DEM Others Stephens' kangaroo rat (Dipodomys stephensi)

11. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats include: annual grassland and coastal sage scrub with sparse shrub cover, commonly in association with Eriogonum fasciculatum, Artemisia californica, and Erodium cicutarium Typical habitat includes sparsely vegetated areas (perennial cover less than 30%) with loose, friable, well-drained soil (generally at least 0.5 m deep) and flat or gently rolling terrain. (USFWS, 1997) Vegetation map NVCS Alliance Association Vegetation map Percent Cover By Stratum Soils NRCS Soil Series Topography USGS DEM Others Stephens' kangaroo rat (Dipodomys stephensi)

12. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats include: annual grassland and coastal sage scrub with sparse shrub cover, commonly in association with Eriogonum fasciculatum, Artemisia californica, and Erodium cicutarium Typical habitat includes sparsely vegetated areas (perennial cover less than 30%) with loose, friable, well-drained soil (generally at least 0.5 m deep) and flat or gently rolling terrain. (USFWS, 1997) Vegetation map NVCS Alliance Association Vegetation map Percent Cover By Stratum Soils NRCS Soil Series Topography USGS DEM Others Stephens' kangaroo rat (Dipodomys stephensi)

13. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer Habitats : Prefers vegetation dominated by Eriogonum fasciculatum and Artemisia californica Disfavors vegetation dominated by Salvia mellifera, and Malosma laurina Typical habitat structure is open with shrub cover range of 25 – 40% Disfavors vegetation greater than 2 meters Vegetation map NVCS Alliance Association Vegetation map Density of Cover By Stratum Vegetation map Vegetation Height By Stratum California gnatcather (Polioptila californica)

14. Wildlife Habitat Model Vegetation Map Forms the Base Analysis Layer

16. Habitats : Prefers vegetation dominated by Eriogonum fasciculatum and Artemisia californica Disfavors vegetation dominated by Salvia mellifera, and Malosma laurina Nests almost exclusively in Opuntia littoralis, O. oricola, and Cylindropuntia prolifera Vegetation map NVCS Alliance Association Coastal cactus wren (Campylorhynchus brunneicapillus)

17. Creating a Fine-Scale Vegetation Map Methodology Prepare (or adopt) a Vegetation Classification – Collect quantitative environmental data in the form of Rapid Assessments (or Relevés) – Conduct statistical analysis of dataset to form basis for classifications (ordination) – Define the qualitative and quantitative descriptions (membership rules) Define mapping rules – How to spatially apply themes Field map to begin delineating stands of vegetation Complete work through heads up digitization in lab Conduct accuracy assessment of final map

18. Creating a Fine-Scale Vegetation Map Methodology – Calibration

19. Creating a Fine-Scale Vegetation Map Methodology – Data Collection

20. Creating a Fine-Scale Vegetation Map Methodology – Data Analysis

21. Creating a Fine-Scale Vegetation Map Methodology – Quantitative Descriptions

22. Creating a Fine-Scale Vegetation Map Methodology – Field Mapping

23. Creating a Fine-Scale Vegetation Map Methodology – Office Mapping

24. Creating a Fine-Scale Vegetation Map Methodology – Data Management

25. Creating a Fine-Scale Vegetation Map Methodology – Accuracy Assessment

26. Vegetation Mapping Fine-scale >< Broad-scale Typically performed by botanists and vegetation ecologists (The Natural Sciences Department) Typically performed by geographers (The Physical Sciences Department) Typically hand-drawn over high resolution 3 or 4 band imagery Typically computer generated from low resolution >4 band imagery Almost exclusively vector based Almost exclusively raster based Even with rules, its subtleties can be fairly subjective Even with algorithms, its subtleties can be difficult to interpret Difficult to sequentially compare (see above) Easy to sequentially compare (see above)

27. Change Detection Mapping Subtleties of Interpretation

28. Change Detection Mapping

29. Change Detection Mapping Image Classification

30. Change Detection Mapping Hybrid Approach

31. Change Detection Mapping Advances in Remote Sensing and Classification Intellectual Advances Sub-pixel analysis Object-based image analysis Technological Advances Increased resolution Improving cost curve Increase sampling frequency Collection of multiple phenologies

32. Change Detection Mapping Advances in Remote Sensing and Classification

34. Jonathan DunnAECOMSan Diego, California