1. Northern Oregon Demonstration Project
Realities of Conducting Natural Resource Surveys Interagency Cooperation in Natural Resource Surveys ____________________________________________________________
Introduction
Northern Oregon Demonstration Project
Annualized Interagency Inventory & Monitoring Initiative (AIIMI)
Other Interagency Efforts
Further Considerations

2. Introductory Comments
Several U.S. Federal agencies conduct national-scale periodic surveys to monitor status & trends of natural resources
Most are conducted by U.S. Department of Agriculture (USDA) or Department of Interior (DOI)
The setting: Current vs. Mid-1990’s vs. Earlier
Will focus mostly on FIA & NRI
Quick overview of programs
Historical endeavors
Ft. Collins project (early 1980’s); Lund (1986); Leech (1998)
“Realities of conducting natural resource surveys”

3. Northern Oregon Demonstration Project – Overview
Inter-agency demonstration project conducted in mid- 1990’s to examine feasibility of combining/integrating Federal environmental surveys
Focused on 6-county area of Oregon that contains diversity of land cover & use, and ownerships
Scientists from 6 agencies were responsible for funding, design, implementation, management, analysis [USFS, NRCS, NASS, USGS/NBS, BLM, EPA]

5. Northern Oregon Demonstration Project – Introduction
Support from Under Secretary’s office, Federal Geographic Data Committee (FGDC), and White House (CEQ) – but “hands off” approach
The project goal was to study broad topic of integrating natural resource surveys – but specific focus was on NRI, FIA, FHM, and NFS survey procedures
Goebel, Schreuder, House, Geissler, Olsen, and Williams (1998); House et al (1998)
Many issues and concerns were identified, but project focused on 7 objectives

6. Northern Oregon Demonstration Project – Objectives
Ascertain if sampling frames give proper coverage
Determine “best” frame; investigate statistical & operational difficulties of constructing joint data base
Explain discrepancies in forest & range (area) estimates

7. Northern Oregon Demonstration Project – Objectives
Investigate collecting common information on common samples with joint FIA/NRI data collection teams
Explore data collection methodology for vegetation & soil attributes in integrated survey context
Determine whether sampling for animal abundance can be included in survey design
Analyze measurement errors associated with collection of different variables [most important for new protocols]

8. Northern Oregon Demonstration Project – Data Collection Design & Methods
Data collection portion conducted in 3 phases
Included selection of important existing measurements from NRI, FIA, FHM, and NFS Region 6 surveys
Also included several experimental variables associated with soil quality, range and forest health, wildlife habitat, and animal relative abundance

9. Data Collection – Phase I
Carried out in office by experienced USFS, BLM, and NRCS personnel
Used aerial photos, GIS data layers, hard-copy ancillary materials
Sample consisted of 613 sample points: 337 FIA/NFS sites and 276 from NRI
samples selected independently from two complete frames, so
used straight-forward multiple-frame estimation procedures
Data elements: several cover & use, classifications, evidence of disturbance, soils, site characteristics ownership category, geographic delineations (e.g., HU)

10. Data Collection – Phase II
Carried out by joint 2- and 3-person field crews
USFS personnel were FIA inventory specialists
NRCS: soil scientists, soil conservationists, & range
conservationists [with some NRI experience]
Sample consisted of 91 sample points selected from the 613 Phase I sample sites [unable to sample 13 sites]
Data elements: site characteristics; veg. structure; ground cover; herbaceous veg. species freq.; shrub canopy cover; shrub density; tree tallies; woody debris; soil characteristics
Soil samples collected & analyzed at soil laboratory
All variables collected for each sample but various protocols used to obtain different measurements

11. Plot design
was similar to FIA/FHM
design

12. Data Collection – Phase III
Carried out by specialized 3-person USGS field crew [National Biological Survey staff]
Sample consisted of 14 Phase II sample sites occurring on particular portions of 3 national forests
Various protocols used to observe diurnal breeding birds, amphibians, ground insects, and flying insects
Each site visited 3 times within 5-week period

13. Measurement Repeatability Study (Data Collection)
Each Phase II sample site was visited by 2 different crews
Subplots 1 & 2 sampled by both crews; only one crew sampled subplots 3 & 4
Plot data collected independently by the 2 crews
Visits by the 2 crews made at same time
Operational efficiency
Limited accessibility to private property
Ensured that measurements made at same locations

14. Some of the Lessons Learned
Agencies can work together; have complementary skills
Uniform land classification is achievable
Many basic inventory needs can be met with the same protocols
Sensitivity of access to private lands
Efficiencies of doing things only once is achievable
Plant identification to species level = large workload
Must have mobile GPS units and CASI (Computer Assisted Survey Instrument) – more than just a data recorder
Developed an “Integrated Inventory Vision”

15. Forest and rangeland estimates (in ha
Forest and rangeland estimates (in ha.) using USFS and NRCS definitions
Forest Land Rangeland
Crown USFS NRCS USFS NRCS
Land Class Cover % Estimate Estimate Estimate Estimate
Timberland , ,517
, ,972
Oak
Woodland , ,036
, ,358
Unclassified
Woodland
, ,361
Juniper
Woodland , ,403
, ,912
Chaparral , ,036
Desert Shrub , ,548
Grass/Herbaceous , ,820
Total (Phase I) , , , ,272
45% % % %
Total – Regression , , , ,913
Estimator % % % %

16. Repeatability of Selected Measurements
Correlation Measurement error as
(r) % of plot variance
Average # of plant
species per plot %
Average DBH %
Total basal area %
Number of species %
Number of trees %
% of total shrubs as seedlings %
% of total shrubs as mature %
Total count, shrubs %

17. Interagency Inventory & Monitoring Initiative (AIIMI)
Follow-up to Northern Oregon Demonstration Project
Study area = Minnesota; initiated in 1999
Further explored feasibility and limitations of integration (of FIA and NRI)
Featured assimilation & use of data rather than new data collection
Further examined differences in focus & design of inventories when combining data in a common framework
Collaborators: Minnesota DNR; USFS; NRCS
Also USGS EROS Data Center for one project
NRCS Statistician co-located with FIA in St. Paul
Czaplewski et al (2002); Rack et al (2002)

18. AIIMI - Products GIS Test Data Base
GIS test-bed provided a statewide integrated coverage of FIA, FHM, NRI, and variety of other (ancillary) spatial data
Huge task; quite valuable
Ancillary data included: STATSGO soils data; Census data; Digital Elevation Model (DEM) data; Digital Raster Graphics (DRG) data; supplemental digital aerial photography; Landsat TM imagery; Digital Ortho Photo quads; wetlands and ecological zone mapping
Intranet Application for Retrieving and Viewing Plot-level Imagery and GIS Data
Navigational capabilities enable data collection and QA specialists to view plot locations in a landscape context

19. (Nelson et. al. 2004)

20. Description
This shaded polygon map shows the amount of forest land converted to developed land between 1982 and 1997 within each 8-digit hydrologic unit. The acres converted are presented in five categories based on the following divisions: 20,000 or more acres, 5,000 to 20,000 acres, 2,000 ro 5,000 acres, and less than 2,000 acres. A total of 10.3 million acres were converted. Developed land includes urban and built-up areas and rural transportation land. Metropolitan Statistical Areas are indicated by black squares. Areas with 95% or more Federal area are shaded gray.
Cautions for this Product: This map does not show the total amount of forest land or developed land. Data are not collected on Federal land. Data are not available for Alaska or the Pacific Basin. Data for Puerto Rico and the U.S. Virgin Islands are shown by 6-digit hydrologic unit.
Center point of Central City for each MSA with a population of 100,000 or more.

21. AIIMI - Products (cont.)
Comparison of FIA and NRI Estimates
Investigated land cover/use classification and area estimates to discover types and reasons for similarities and differences in estimates
Mapping Changes in Land Cover/Use
Based upon both FIA & NRI plot data
Geospatial representation of change
Provides insight and perspectives not available through commonly reported summary statistics

22. AIIMI - Products (cont.)
Image-based detection of land cover change
Used integrated set of FIA and NRI data for 10-county area as training data for classification
Landsat classification utilizing NRI and FIA plot data
Conducted in cooperation with USGS Data Center
To determine if FIA and NRI data would help in development of National Land Cover Data (NLCD) mapping

23. AIIMI - Discussion; Findings
GIS Data
It takes considerable work to “align” geospatial data
Mostly manual work rather than automatic
Differing standards, scales, etc
Cover and Use Data
Classification systems vary between programs
NRI and FIA oriented toward use; satellite data – cover
For plots giving heterogeneous signatures – difficult to correlate satellite and survey plot data

24. AIIMI - Discussion; Findings (cont.)
Maps – Geospatial Displays of Data
Very useful in supplementing area statistics [for example, where are the losses of forest land to urban development]
Requires spatial and temporal consistency
Annual Inventories
Both FIA and NRI migrated to Annual Inventory system during the period that AIIMI was being conducted
Both surveys being “annual” should help collaborative efforts
But both programs were too pre-occupied with implementation (including funding issues) to seriously investigate integration

25. AIIMI - Suggestions Use GIS to develop common “Universe of Interest”
NRI & FIA should have same Total Surface Area & Census Water
Develop common “cover” classification system
Would allow USDA to have “common reporting system”
But also – FIA and NRI need to keep their current/historical systems [needed for Agency programs & have huge investment]
Soils Data
Add NRCS soils data base information to FIA, geospatially [would have characteristics and interpretations for each sample site]
FIA would then supply plot information to NRCS to enrich the soils data bases [productivity; biomass]

26. AIIMI - Suggestions Further linkage of FIA and NRI data
Statistical
geospatial
Survey Integration
Czaplewski et al (2002)]
Limited budgets; Accountability; OMB
Do NOT start from scratch
Utilize strengths of each system
NRI: land use change; soil; cost/ plot; site condition (general)
FIA: volume; veg. composition change; site condition (specific)

27. .
FIA/NRI Integration – should take advantage of each program’s strengths & not start from scratch

28. Other Inter-Agency Efforts
Status and Trends of Wetlands
Assessment of Rangelands
North American Carbon Project
Agricultural Statistics
Resource Inventory & Monitoring, Focus Area Work Group (FAWG), NASA/USDA
National Land Cover Characterization, NLCD 2001

29. Status & Trends of Wetlands
National estimates produced through 2 separate natural
resource surveys [both with legislative mandates]
Status & Trends – USFWS, Dept. of Interior
NRI – NRCS, USDA
Considerable pressure during the 1990’s to develop a single report by year [Clean Water Act]
Currently not possible to produce statistically reliable results by combining USFWS and NRI data [Dahl (2000)]
Accomplishments
Joint press conference Jan. 2001, Secretaries of Interior & Agriculture
Statistics on trend (Quantities & types of loss) are “consistent” due to field work by USFWS & NRCS, and subsequent report modifications

30. Assessment of Rangelands
National Research Council (1994)
Called for development & utilization of new methods to classify, inventory, and monitor rangeland
Placed emphasis on rangeland healths
Cooperative work during 1995 – 2002 to develop field protocols that attempt to address Council’s call
NRCS, ARS, BLM, & USGS have been most active, with limited participation by USFS
What about “Criteria & Indicators for Sustainable Rangeland” [Sustainable Rangeland Roundtable]?
Protocols meant to help detect long-term changes in conditions & to monitor short-term impacts

31. Development of Rangeland Protocols
Limited trial studies started in 1996 in 2 regions
BLM conducted field test in Colorado, 1997 & 1998
Limited field test conducted on private lands in 7 states in 1999
Collected valuable cost/time data
Current protocols include combination of quantitative and qualitative measurements
NRCS utilizing these as part of NRI for 2003 – 2005
NRCS expects that a subset of these will be “permanent”
Research activities (with ARS) – reduce replications; incorporate remote sensing; make 100%quantitative

32. Current Rangeland Protocols
Ecological site information; soils; landscape
Line point transects for cover composition
Line intersect transects for basal & canopy cover
Cover density & height [wildlife habitat]
Disturbance indicators; conservation practices & treatment needs
Noxious weeds & invasive/alien plants
Soil stability test
Species composition by weight
Rangeland Health

33. North American Carbon Project
Need complete accounting for carbon
Involves many Agencies, Universities, etc.
Science-based approach
For both domestic and international reporting
Need to reconcile models [& calibrate & improve]
“Top down” approach [Atmospheric scientists]
“Bottom up” approach [Agricultural & forestry scientists]

34. Soil carbon in forested lands of the North Central region

35. Opportunity
As part of the North American Carbon Project, there appears to be a need to build a comprehensive FIA/NRI Data Base
Reconcile FIA & NRI data for use in C models & elsewhere
One “proposal” is to create geospatial (tesellated) data base with land use, land management, land use history, soils [maybe something equivalent to 10-km. grid ??]
Would include measures of “uncertainty”
Would need protection of confidentiality
Should also investigate incorporation of NASS crop maps, MODIS data, and ???

36. 2-mile cells
(4 sq.

37. Agricultural Statistics
NASS & NRCS currently cooperating on several survey activities
Reconciliation of NRI and Census of Agriculture acreage figures – showing how to properly align categories
Conservation Effects Assessment Project (NRI-CEAP), where NASS conducting 0n-farm interviews for NRI sample sites; Farm Services Agency (FSA) also cooperating
Investigating integration of Agricultural Resource Management Survey (ARMS) & NRI-CEAP, collaboratively with Economic Research Service (ERS)
NRI needs NRI-CEAP type data on an annual basis for many uses (including C modeling) – part of Continuous NRI concept introduced in 1998
NASS crop maps

38. Resource Inventory and Monitoring, Focus Area Work Group (FAWG)
One of 8 focus areas identified by NASA and USDA in May 2003 MOU
Objective is to identify projects for collaborative development to enable USDA operating units to incorporate NASA earth observations, modeling, and systems engineering capabilities
NRI and FIA serving as co-chair

39. National Land Cover Characterization (NLCD), 2001
Land cover data base being developed by region/zone
Cooperative mapping effort of Multi-Resolution Land Characteristics (MRLC) 2001 consortium
USGS EROS Data Center collaborating with EPA, USFS, NOAA, NASA, NPS, USFWS, BLM, NRCS (NASS?)
Utilizes Landsat TM data from 3 time periods, plus ancillary data from Digital Elevation Model (DEM)
Zone 41 (much of Minnesota) – developed as part of AIIMI
Produces “objective” data layers for each time period
Decision tree approach – rules developed to transform objective data into themes [cover; imperviousness; trees]

40. The Realities of Conducting Natural Resource Surveys – Lessons Learned
Who pays the bills? What pays the bills?
What is expected of your survey program?
When do we get “burned”?
How do we maintain “credibility” with Policy Makers, other scientists, the public? Perception is almost everything. Cooperating with an independent entity like Iowa State University is good business & good science!!
“Keeping NRI going” is a large challenge. Therefore, inter-agency is even greater challenge?

41. The Realities of Conducting Natural Resource Surveys – Lessons Learned
Who pays the bills? What pays the bills?
“MONITORING” – conducting a longitudinal survey properly for natural resources rather than for people issues [health; economics] – are the scientific and operational challenges fully realized
New (& great) technologies come along that affect your “favorite reporting indicator”, like soil erosion for NRI. What do you do?
Are you sampling farms or fields or forests or trees? What happens with departures and new arrivals into your universe of interest?

42. The Realities of Conducting Natural Resource Surveys – Lessons Learned
Who pays the bills? What pays the bills?
“MONITORING”
Indicators [condensing complicated science into useful factoids] – collect the “most basic factors” and not the “Indicator” itself
OMB/USDA Quality of Information standards
Realistic – must use Computer Assisted Survey Instruments & modern supporting systems
Make sure that you can deliver – No excuses!