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FIA-SRS Phase 3 Vegetation Structure and Diversity Pilot Study Year 2

FIA-SRS Phase 3 Vegetation Structure and Diversity Pilot Study Year 2. Sonja Oswalt Research Associate University of Tennessee Forestry, Wildlife & Fisheries Dept. Outline. What is VEG? Recap of 2002 South Carolina Pilot Study Tennessee 2003 Pilot Study—Why it Worked

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FIA-SRS Phase 3 Vegetation Structure and Diversity Pilot Study Year 2

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  1. FIA-SRS Phase 3Vegetation Structure and Diversity Pilot StudyYear 2 Sonja Oswalt Research Associate University of Tennessee Forestry, Wildlife & Fisheries Dept.

  2. Outline • What is VEG? • Recap of 2002 South Carolina Pilot Study • Tennessee 2003 Pilot Study—Why it Worked • South Carolina VEG Data Analysis—A Glimpse of What’s to Come

  3. What is VEG? • A measurement of the composition and spatial arrangement of all vascular plants on plot • Includes all trees, shrubs, herbs, grasses, ferns, and fern allies (horsetails and club mosses) Examine which forest types are more prone to invasion by non-native species Assess which reporting areas are most diverse Complete sample tree diversity on plot (regeneration) allows better prediction of successional trends

  4. South Carolina 2002 RecapField Methods: • Four subplots per plot • Subplot = 24’ radius circle • Three 1-m2 quadrats in each SP • Quadrats: Ground cover to 1% • Quadrats: Species cover to 1% • Subplot: List all species, cover to 1% • Subplot: Note layer of greatest cover for all species • Subplot: Total cover (of all species combined) to 1% for each layer class (1-4)

  5. South Carolina 2002 RecapLogistics • Botanist traveled with forestry crew doing P2 and other P3 variables • Forestry crew marked subplots for veg. work • Botanist collected veg. data without help from foresters • Crew left plot when foresters were done, regardless of Veg. Indicator completion (Subplots that were started were finished) • Crew traveled from Lexington/Newberry daily and returned home every night

  6. South Carolina 2002 RecapCompletion Results • Collected data on 31 out of 33 plots in 27 counties in SC • Completed 71 out of 124 subplots (57%) • Subplots completed (# plots): 4 (4) 3 (6) 2 (16) 1 (5) Average: 2.3 subplots per plot

  7. South Carolina 2002Why Didn’t It Work? • More travel than plot time • No overnight stays • Ave. 3.3 hrs on plot/day, 4.4 hrs travel/day • One plot: 65 min. in field, 7 hours driving (1 SP completed) • Botanist did not adhere to time limits for species search • Excessive keying/coding on plot

  8. Tennessee 2003—How Did it Differ? • Slightly Different Methodology • Ability to work 10-hour days • Overnight stays in working counties • Cooperative crew members • Strict adherence to time limits • Collecting more, keying less… • Data collection on paper—entry into Tally later • Coding either en route from plot or in hotel

  9. 2003 Methodology • Four subplots per plot • Subplot = 24’ radius circle • Three 1-m2 quadrats in each SP • Quadrats: Ground cover to 1%--ELIMINATED • Quadrats: Species cover to 1%--ELIMINATED List presence/absence of species only • Subplot: List all species, cover to 1% • Subplot: Note layer of greatest cover for all species CHANGED: Record % cover of each species in 3 Ht classes: 0-6 ft, 6-16 ft, 16+ ft • Subplot: Total cover (of all species combined) to 1% for each layer class (1-4)

  10. Tennessee 2003 Completion Results • Collected data on 15 plots in 15 counties • 60 Subplots Total, 4 non-forested: 56 Total Forested Subplots • ALL BUT ONE PLOT COMPLETED --Why the one? The botanist got lost…

  11. Why Did Tennessee Work? • Fewer, Longer days are Key, and the ability to “trade-off” hours between days (i.e., work 12 hours one day and 8 the next) • Elimination of time-consuming, redundant data collection • Strict Adherence to Time Limits • Total Hours spent Traveling: 76 • Total Hours spent on Plot: 47 • Total Hours spent Pressing Plants: 3 • Total Hours spent Identifying: In process • Total Hours spent Entering data: In process

  12. Per-Day Breakdown • 5 Hours Traveling per day • 3-4 Hours on plot per day • 20 minutes pressing plants • ~ 20 minutes to prepare unknowns • ~ 30 minutes to code data • ~ 45 minutes to enter data Preparing & Sending Unknowns / Entering Data completed in hotel during evening Total Time Needed Per Day: ~ 10 Hours

  13. 2003 Time (Preliminary) Logistics remain the largest problem. However, 4 10-hour days and shorter methods help to counteract.

  14. Where Are We Headed With The Data? South Carolina Invasive Species Report: An Example of Uses for VEG P3 Data

  15. Data Analysis • Data from South Carolina P-2 Exotic Species Variable • Data from South Carolina P-3 VEG collection • Analyzed by Eco-region and Physiographic Section • Two Levels: Plot and Subplot • SAS software, NCSS software, Arcview • Summary statistics, differences in relative diversity, occurrence of non-native invasives

  16. Results (P-2 and P-3) • Phase-2 • 505 forested plots in 46 counties in 2002-2003 • 41% contained at least one alien species • 15% contained at least two • 3 % contained at least 3 • <1% contained 4 or more • Phase-3 • 102 plant families represented • 6% of all identified species are alien • However: Alien species occurred in 80% of measured plots • In contrast: 73% of native species occurred in LESS THAN 10% of all plots and 48% occurred in only ONE measured plot

  17. Mean Number of Species/Subplot by Ecological Region (Significantly Different at α = 0.10)

  18. Alien Species Detection • P-2: Japanese honeysuckle (Lonicera japonica) was most common (Frequency = 31.88%) • However, P-2 can ONLY detect up to 4 per plot, and only those “On the List” (total of 16) • P-3: Japanese honeysuckle was most common (Frequency = 45.16%), which corresponds to the P-2 data • P-3 can detect as many non-native potentially invasive species as are present (total of 27), making it a more sensitive method for detection

  19. Effects of Disturbance Logistic regression indicated that distance of a plot from agricultural land was significant in explaining the presence of exotic species on a plot (p < 0.001)

  20. Proportion of plots containing exotic species in each major ecological region Atlantic Coastal Plain 23%

  21. South Carolina 2002/2003 Data Conclusions • Non-native Species constitute a substantial threat to forest health in South Carolina • Phase-3 data indicate that although non-natives comprise a small % of vascular plants, those few species are alarmingly widespread • As the more detailed P-3 data continues to be collected, examination of edge-related disturbances may give insight into the impacts of types and patterns of disturbance on the establishment and reproduction of vascular plant species

  22. Conclusion • With increased efficiency in protocol and fewer but longer days in a week, the P-3 VEG collection is possible in the south • P-3 VEG can provide additional information regarding the spread of non-native species, the impacts of disturbance on vascular plant composition, and differences in regional diversity

  23. Acknowledgements • University of Tennessee, Department of Forestry, Wildlife, & Fisheries, Dr. George Hopper-Department Head • USDA Forest Service Southern Research Station FIA, John Kelly-Acting Project Leader • South Carolina State Forestry Commission • Tennessee Division of Forestry • Sharon King, Jeff Turner, Beth Schulz, Cindy Aulbach, Byron Rominger, John Mullins, Anita Rose, TDF Crew Members

  24. Questions?

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