Alliance level mapping problem comparison to ecological system mapping

1. Ecological system level classification: a relevant and realistic goal for intermediate scale land cover classification? Alliance level mapping problem comparison to ecological system mapping Criteria for ecological system labels Rule based classification methodology Results: evaluation of mapping unit legend and comparisons to possible alliance level mapping

2. Structure of the NVC

3. WHAT LEVEL OF VEGETATION COMMUNITY CLASSIFICATION IS THE APPROPRIATE OBJECTIVE FOR REMOTELY SENSED INTERMEDIATE SCALE MAPPING UNITS? • ALLIANCE CLASSIFICATION GROUPS PLANT ASSOCIATIONS SHARING PHYSIOGNOMY, SITE HYDROLOGY, AND DOMINANT OVERSTORY SPECIES • ECOLOGICAL SYSTEM CLASSIFICATION GROUPS PLANT COMMUNITIES THAT CO-OCCUR IN AN ECOLOGICLALLY DEFINED LANDSCAPE CONTEXT • ALLIANCE CLASSIFICATION IS A NARROWLY DEFINED FLORISTIC UNIT • ECOLOGICAL SYSTEM CLASSIFICATION MAY BETTER REFLECT COMPLEX COMMUNITY RELATIONSHIPS AT INTERMEDIATE SCALE RESOLUTION • ALLIANCE LEVEL CLASSIFICATION IS THEORITICALLY INCLUSIVE (OF ALL COMMUNITIES), BUT “PRACTICALLY” INCOMPLETE, THEREFORE ALLIANCE LABELS CAN ONLY BE APPLIED TO A SUBSET OF REAL WORLD SITE DATA • MANY ALLIANCE LEVEL COMMUNITIES ARE TOO SMALL TO ACHIEVE SPATIAL REGISTRY ON ETM IMAGERY • ECOLOGICAL SYSTEM CLASSIFCATION CAN BE APPLIED TO PROBLEMATIC SITE DATA WITHIN A CONTEXT OF LANDFORM AND POTENTIAL VEGETATION • ECOLOGICAL SYSTEM CLASSIFICATION IS A WORK IN PROGRESS BUT IS BASED ON GENERALLY UNDERSTOOD CONCEPTS BROAD COMMUNITES, SUCCESSIONAL RELATIONSHIPS, AND HABITAT VALUES

4. Mapping Formations: Issues 1. Distinguishing vegetation of mixed physiognomyoccurring within areas smaller map unit (e.g. Shrubland and Grassland in mosaic; Forest vs. Woodland) • 2. Mixed leaf type (broadleaf evergreen vs. deciduous, etc.) • 3. Hydrologic Modifiers (seasonally flooded, temporarily flooded, etc.) Semi-Permanently Flooded Cold-Deciduous Forest

5. Mapping Alliances: Issues 1. Carry-over of issues for Physiognomic and Hydrologic modifiers from Formation scale • 2. Floristic distinctions within Formations can be most difficult with herbaceous vegetation, some shrublands, some forests, even w/small MMUs (2-5 ha) Festuca campestris Herbaceous Alliance

6. Ecological Systems Groups of plant communities and sparsely vegetated habitats unified by similar ecological processes (e.g. fire, riverine flooding), substrates, (e.g., shallow soils, serpentine geology), and/or environmental gradients (e.g. local climate, hydrology in coastal zones). An ecological system will typically manifest itself in a landscape as a spatial aggregation at an intermediate scale (10 ha – 100,000 ha), persisting for 100 or more years. Great Lakes Dune and Swale Complex

7. “Nationally Consistent – Locally Relevant” NatureServe Ecological Systems ~ NVCS Class/Subclass NVCS Formation NVCS Alliance NVCS Association ~10 units ~300 units ~700 units ~1,800 units ~5,000 units MRLC 2000 Proposal Gap Analysis Program National Park Mapping USFWS Proposal (Natural/Semi-natural types)

8. Ecological Systems: Classification Development Associations in Bailey’s Division 330 Wetland Upland Associations Associations Forests Sparse Alluvial Depressional Herbaceous & Shrublands Vegetation Associations Associations Vegetation Woodlands Refinements based on environmental factors & gradients, physiognomy (some combining when seems Refinements based on environmental factors & gradients, appropriate), spp . composition, & refined location. physiognomy, spp . composition and refined location. E.g. Great Plains E.g. Great Plains Great Plains Great Plains Great Plains Great Plains Riparian Forests/Woodlands Emergent Wetlands P. ponderosa Mixedgrass Sagebrush Cliffs, Buttes Prairie Forest/ Wdlds Shrublands & Badlands ) Component NVCS Associations

9. Bioclimatic Divisions

10. Southern Rocky Mountains example Spatial Pattern Rocky Mountain Division Elevation Zone Upland/Wetland Ecological Systems (~90) (#) = NVC Alliances

11. “THE NUMBERS” • ABOUT 500 RECOGNIZED ALLIANCES (SW REGION)* • EXTENSIVE FIELD WORK WOULD PROBABLY DOUBLE RECOGNIZED ALLIANCES (in Utah)** • ABOUT 100 ECOLOGICAL SYSTEMS (SW REGION)* *Pat Comer **Gerald Manis

12. 63 different “established” alliances in mapping zone, classify 82% of representative, homogenous training site data, only 12 with 10+ samples out of 483 sites 24 different new “provisional” labels, many representing semi-natural conditions Most “target” alliance level cover types were not adequately sampled to provide a CART analysis of mappability Problem: how to attribute all data to meaningful and mappable alliance label? Conclusion: Reasonable classification labels may not equal reasonable mapping units Ecological system names were applied to 100% of sites based on indicator species, landform, physiognomy, hydrology, ground cover data, and other relevant ancillary site data System grouping was targeted to 22 “mappable” natural cover types Ecological systems relate well to landscape level habitat types Ecological systems can be “grouped up” if necessary to achieve acceptable accuracy What does the San Rafael Swell Mappping Zone field site data tell us about alliance versus ecological system analysis?

13. ECOLOGICAL SYSTEMS CLASSIFICATION: TESTING CONCEPTS San Rafael Swell Mapping Zone

14. San Rafael Mapping Zone Mapping zones based on ecoregion boundaries modified by topography, soils, and mapping economy

17. MAPPING ZONE PROBLEMS • VERY DIVERSE MAPPING ZONE WITH A LOT OF PATCHY VEGETATION COMMUNITIES • LARGE AREA OF LOW CANOPY COVER • TRAINING SITE DATA ACQUIRED FROM ROADS, MAPPING ZONE IS LARGELY ROADLESS • HALF THE ECOLOGICAL SYSTEMS ARE CONFINED TO 10 PERCENT OF THE TOTAL AREA (HENRY MTNS.)

18. MAPPING SOLUTIONS • ECOLOGICALLY STRUCTURED MODEL USING RULE BASED DATABASE QUERIES • COMBINE SOME ECOLOGICAL SYSTEMS • RELY ON LANDFORM MODEL TO REPRESENT CERTAIN MAPPING UNITS • SPARSE VEGETATION: WEIGH CLASSIFICATION MORE HEAVILY ON ENVIRONMENTAL SETTING RATHER THAN SPECTRAL DATA • MAY BE DESIRABLE TO SEARCH FOR ADDITIONAL DATA OR PHOTO INTERPRET DATA

19. COVER TYPE CLASSIFICATION METHODS • “TRAINING SITE” DATA COLLECTION • IMAGE LAYERS AND ANCILLARY LAYERS DATA PREP • SITES INTERSECTED THROUGH TM AND ANCILLARY DATA LAYERS • DATA ANALYSIS • RULE BASED CLASSIFICATION MODEL • LIFE ZONAL MODEL SEGMENTATION TO SIMPLIFY MODEL RULES • IMAGE AND DOQ INTERP WAS USED TO FIND OR VALIDATE MODEL RULES IN COVER TYPES WITH WEAK DATA • ITERATIVE PROCESS OF VISUALLY CHECKING THE MODEL OUTPUT & ADJUSTING RULES TO REDUCE ERRORS

21. Imagery Derived Data Layers(Spring, Summer & Fall 1999-2001) • NDVI, SAVI or Fractional Vegetation Index • Brightness (Tassel-cap) • Greenness (Tassel-cap) • Wetness (Tassel-cap) • Individual Bands (1-5 & 7) • ISODATA Clusters

22. CLIMATIC (ZONAL) STRATIFICATION • Climatic data (PRISM) for temperature and precipitation is, unfortunately, too coarse to work at GAP mapping scale. • Elevation data is detailed, accurate, but is not directly correlated. Still, better than climatic data as a model builder. • Soils criteria is climatically based so STATSGO should be great. Spatial resolution is not adequate for model building and state edge-match is climatically inconsistent. However, it could be used for sampling stratification. • Vegetation indices are image based, pixel scale, “fit” landscapes in ways that interpretive vectors do not, and have fewer problems. This option is the recommended option for high relief zones. May work well in other zones with a “zonal” distribution of soil fertility or precipitation. Combining NDVI thresholds with elevation thresholds solves most problems.

24. DEM Derived Data Layers • Aspect • Elevation • Slope • Topographic Relative Moisture Index (TRMI) (Parker 1982; Haplin 1999), (modified by Manis, 2001) • Landform (10 Class) (Manis 2001)

25. 10 CLASS LANDFORM MODEL

26. Landform Classification

28. Raw Terrain Corrected ETM Imagery for Spring, Summer, and Fall

29. General Substrate Gray shales Light colored (white to buff) sandstone and aeolian sands Red brown siltstone/sandstone and silty aeolian soils Vegetated Soils (substrate not visible)

30. MAPPING UNIT LEGEND

31. Slickrock Canyons and Tablelands Sparse Pinyon – Juniper System

32. Soft, mixed substrate, Escarpments Sparse Dwarf-shrubs and Grasses System

33. Plateau/Benchland Pinyon – Juniper Shrubland System

34. Plateau/Benchland Desert Dwarf-shrub Steppe System

35. Mormon Tea Shrubland System (alliance)

36. Matted Saltbush System

37. Desert Dry Wash and Greasewood Flats System

38. Blackbrush System (alliance)

39. Plateau/Benchland Sagebrush Steppe System

40. Mountain Sagebrush System

41. Rubbleland and Rock Outcrop

42. Ponderosa Pine – Pinyon -Douglas-fir System

43. Quaking Aspen – Mixed Conifer System

44. Alpine – Sub-Alpine Herbaceous System

45. COLLABORATORS • Gerald Manis, John Lowry, R. Douglas Ramsey (RS/GIS Laboratory, Utah State University, Logan UT) • Pat Comer, Keith Schultz (Natureserve, 2060 Broadway, Boulder, CO)