1. Use of survival data for planted woody stems to refine a vegetation monitoring protocol for restoration sites Thomas R. Wentworth, Michael T. Lee, Mac Haupt, M. Forbes Boyle, Robert K. Peet 17 November 2010

2. Optimized for field efficiency and repeatability. Resources include manuals, datasheets, and a data entry and reporting tool. Scalable to meet future requirements. Complies with US-FGDC National Vegetation Classification Standard. CVS-EEP Sampling Protocol

3. Current Monitoring Requirements Current Requirements Height or Type ddh (mm units) height (cm units) DBH (cm units) < 137 cm tall mm precisioncm precisionno ≥ 137 cm and < 250 cm tallmm precisioncm precision ≥ 250 cm and < 400 cm tallno10 cm precisioncm precision ≥ 400 cm tallno50 cm precisioncm precision Live stakenocm precision if ≥ 137 cm tall, cm precision

9. Utility of the Collected Data? Stakeholder feedback: What is gained from measurements collected using the CVS-EEP Protocol? Variables measured are mandated by EEP, not CVS. EEP initially required multiple types of measurements because it was unclear which ones would be most useful in assessing stem success. Available data from EEP Monitoring Firms will now allow CVS to assess the utility of each field measurement (e.g., ddh, height, DBH). Which plant attributes should continue to be measured in the field? Particular concerns were raised about ddh measurement.

10. Current Status of CVS-EEP Inventory Monitoring conducted for 5 years (2006-2010) Number of yearsNumber of projectsProject-years 5420 4 80 31648 22652 117 Totals:83217

11. Current Status of CVS-EEP Inventory LevelStems monitoredPlot-years Level 1Planted725 Level 2Planted, Natural1259 Level 3Planted, Natural4 Total1988 785 unique plots monitored 2006-2010 Range is 3-28 plots/project/year (median = 8)

12. Overview of Woody Stem Database As of October 2010, we have 30,544 individual records for planted woody stems. – 166 taxa, 127 species (18 oaks, 6 maples, etc.) Median is 141 stems/project-year: – height data: 121 stems/project-year – ddh data: 98 stems/project-year – DBH data: 38 stems/project-year – three largest tallies for a project in a given year are 800, 617, and 460 planted stems.

13. Modeling Rationale Goal: take a stem and characterize its likelihood of surviving to the next year, – then compare model prediction with reality among predictive variables available, which are essential and which are extraneous (particular focus on utility of ddh)? independent variables allow model evaluation with and without ddh-related variables benefits of such a modeling effort: – evaluating restoration plans, planting lists (including species, source, size, etc.) – being better able to identify projects on good or bad trajectories

14. Modeling Approach General approach was logistic regression using GLM, using survival to next year as dependent variable (1=survived, 0=died). Independent variables incorporated into models: ddh (ln transformed), RGR of ddh height (ln transformed), RGR of height year since planting (1-6) vigor (1-4) – 1 = not expected to survive – 4 = excellent source, for example: – ball and burlap (B) – potted (P) – bare root (R) – tubling (T)

15. Subsetting Database only planted woody stems only those with ddh and height minimum 3 years data (two years for RGR, third year to determine survival from year two) no pseudoreplication (random selection of one three-year sequence) withhold 25% of observations for validation (also random, for further work) 2120 stems, of which 429 (20.2%) died in year three

16. Raw Data

23. Discussion Models tested thus far are in the “fair” range, based on AUC criterion (0.69-0.79). Height-only (AUC=0.69) and ddh-only (AUC=0.71) models perform similarly. Combining height and ddh does not much improve model performance (AUC=0.71). Complex (“everything”) model shows enhanced performance (AUC=0.79) over simple models. Removing ddh from complex model results in little change in model performance (AUC=0.78). Categorical-variables-only model performs reasonably well (AUC=0.76).

24. Conclusions Given our perspective (predicting stem survival to next year), height and ddh are comparable in utility. Little benefit to including both variables. Omitting ddh from complex model has relatively little impact. In these models, it appears that ddh contributes little to prediction of stem survival, as long as we retain height measurement. However...

25. Possible revision of measurements for planted woody stems Current Requirements Height or Type ddh (mm units) height (cm units) DBH (cm units) < 137 cm tall mm precisioncm precisionno ≥ 137 cm and < 250 cm tallmm precisioncm precision ≥ 250 cm and < 400 cm tallno10 cm precisioncm precision ≥ 400 cm tallno50 cm precisioncm precision Live stakenocm precision if ≥ 137 cm tall, cm precision Possible Revised Requirements Height or Type height (cm units) DBH (cm units) < 137 cm tallcm precisionno ≥ 137 cm and < 250 cm tallcm precision ≥ 250 cmvaried precisioncm precision

26. Other Considerations We should exercise caution in discarding variable for which we have such a solid existing data base. ddh may yet prove to have benefits: – diameter (combined with height) allows for volume computation (d 2 h) – are there particular subsets of stems where ddh is a critical predictor of success (further work)? What is the cost in our cost:benefit analysis for this particular variable?

27. Thank You! http://cvs.bio.unc.edu/