Paul C. Van Deusen

The Southern Annual Forest Inventory System

The Southern Annual Forest Inventory System (SAFIS) is in various stages of implementation in 7 of the 13 southern states serviced by the Southern Research Station. The SAFIS design is an interpenetrating design where the n units (1/6 acre plots) are divided into k = 5 panels, each panel containing m = n/k units. Panel 1 plots are measured in year 1, panel 2 in year 2, etc., such that all plots have been visited by the end of year 5. The panel cycle is repeated into perpetuity. Each panel, in effect, is a 5-year periodic survey with complete overlap of sample units. Numerous estimation schemes are possible, and we explore five possible options. The five options are (1) use existing periodic inventory programs to produce 5-year survey estimates by adjusting all five panels to a common year, (2) analyze each annual panel independently, (3) produce 5-year estimates by combining the five panel estimates by varying the weight given to each panel, (4) base inventory estimates on mixed estimation where actual and predicted values are combined, and (5) use imputation techniques such that unmeasured plots are filled in with imputed plots. A two-phase method for forest area estimation that uses the known map marginals from a thematic map is presented as an alternative to photo interpretation-based estimates.

Synchronic large-scale disturbances and red spruce growth decline

Tree-ring data from the USDA Forest Service Forest Inventory & Analysis and other independent sources were used to study coincidence of changes in growth and large-scale disturbances. Numerous studies report that mean radial growth of red spruce (Picearubens Sarg.) declined synchronously throughout its range in the early 1960s. We use red spruce tree-ring data from most of the major studies to show that the synchronicity of red spruce growth decline is likely the outcome of the large-scale disturbances that occurred throughout the northeastern red spruce ecosystem in the late 1930s to early 1950s. Large-scale disturbances are either not detectable or not present in the same time interval in the southern Appalachians. This appears to correspond to an absence of a 1960s radial growth reduction in this region.

Detecting and Predicting Climatic Variation from Old-Growth Baldcypress

Tree-ring data can extend back in time for thousands of years allowing researchers to reconstruct certain environmental factors that have left an imprint or signal in the tree-ring record. Typically, these factors include reconstructions of annual precipitation or temperature for months or seasons to which a particular tree species is sensitive. Over the last several decades, scientists have used tree-ring records in novel ways to investigate the timing and extent of such natural phenomena as volcanoes (Baillie and Munro, 1988), earthquakes (Sheppard and Jacoby, 1987), El Nino/southern oscillation (Stahle and Cleaveland, 1993), fire (Swetnam 1993), carbon dioxide (CO2) (Graybill and Idso, 1993), and synchronous landscape-level disturbances (Reams and Van Deusen, 1993) by recognizing the possibility that various signals may be recorded in the growth record of trees, depending on microsite characteristics, geographic location, and disturbance history (Fritts 1976).

A robust weighted EM algorithm for use-availability data

Wildlife sampling for habitat selection often combines a random background sample with a random sample of used sites, because the background sample could contain too few used sites to be informative for rare species. This approach is referred to as use-availability sampling. Two variants are considered where there is: (1) a random background sample including used and unused sites augmented with a sample of used sites, and (2) a sample of used sites augmented with a contaminated background sample, i.e. use is not recorded. A weighted estimator first proposed by Manski and Lerman (Econometrica 45(8):1977–1988, 1977) forms the basis for our suggested approach. The weighted estimator has been shown to perform better than the usual unweighted approach with uncontaminated data and mis-specified logit models (Xie and Manski in Sociol Methods Res 17(3):283–302, 1989). A weighted EM algorithm is developed for use with contaminated background data. We show that the weighted estimator continues to perform well with contaminated data and maintains its robustness to model mis-specification. The weighted estimator has not been previously used for use-availability sampling due to reliance on the assumption that only the intercept is biased, which is valid for a correct logit model. We show that adjusting the intercept may not eliminate the bias with an incorrect logit model. In this case, the weighted estimator is a relatively simple and effective alternative.

Proceedings of the third annual forest inventory and analysis symposium; 2001 October 17-19; Traverse City, Michigan

Documents contributions to forest inventory in the areas of sampling, remote sensing, modeling, information management, and analysis with emphasis on implementation of the annual inventory system of the Forest Inventory and Analysis program of the USDA Forest Service.

Proceedings of the first annual forest inventory and analysis symposium; 1999 November 2-3, San Antonio, TX.

Documents progress in developing the techniques required for full implementation of the national Forest Inventory and Analysis programs new annual forest inventory system.

Proceedings of the seventh annual forest inventory and analysis symposium

The ArcViewTM Geographic Information System (GIS) is probably the GIS that is most widely used by federal and state natural resource management agencies, industries, and non-profit institutions. As such, there is a great deal of expertise and comfort with this package within the FIA user community. The North Central Research Station and Michigan Technological University have recently cooperated in the release of ArcView GIS projects for each of the eleven North Central states. These projects facilitate analyses of current volume, net growth, mortality, and removals for any geographic region within a state, whether determined from ancillary polygon data (such as soil or watershed boundaries) or defined on-screen by the user. Current efforts are focused on developing a single project that will allow similar analyses that are not limited by state boundaries within the eleven-state North Central region. 1 Paper presented at the Second Annual Forest Inventory and Analysis (FIA) Symposium, Salt Lake City, UT, October 17–18, 2000. 2 Professor and Assistant Research Scientist, School of Forestry and Wood Products, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931; Forester, USDA Forest Service, North Central Research Station, 1992 Folwell Ave., St. Paul, MN 55108; and Professor, School of Forestry and Wood Products, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, respectively.

Proceedings of the fourth annual Forest Inventory and Analysis symposium

Abstract. —We provide here a short description of theorigin, current work, and future outlook of the FiberSupply Assessment program at the D.B. WarnellSchool of Forest Resources, University of Georgia,whose work includes various analyses of FIA data.Since 1997, the program has intended to assist theimplementation of the new Southern Annual ForestInventory System through related data analyses.Currently its projects include basic problems in theoryof equations and parameter estimation and variousanalyses of ground inventories and remote sensingand GIS data. We describe some of these projects andassociated software, hardware, and information dis-semination problems and solutions. The Fiber Supply Assessment program (FSA) at the Daniel B.Warnell School of Forest Resources was initiated by DeanArnett Mace, Jr. in 1997. The establishment of this programcoincided with the beginning of the implementation of theSouthern Annual Forest Inventory Analysis System (SAFIS)and was intended to provide the school’s input into solving thevarious problems of timely and accurate fiber supply assess-ment in Georgia. Parties interested in creation of this program includedmembers of the forest product industry, and others. Theirexpectations were directed toward finding new relationshipsand revealing information in the new annual measurement dataproduced by SAFIS. The new design of the continuous annualinventory was attracting many questions about statistical accu-racy, the possibility of monitoring growth, and differencesbetween current and former periodic estimates. Notwithstanding the above, in the beginning the FSAcould not focus on the annual data analysis due to the unavail-ability of such data. Furthermore, there was also little pragmat-ic value in work on new estimators because it seemed ratherfutile to begin changing the barely conceived statistical design,which was so new that it was not even quite implemented yet.Thus, at the outset the FSA focused initially on theoreticalstudies of inventory projection equations. Subsequent effortsconcentrated on building collaborative studies with other pro-grams and exploring funding opportunities related to the gener-al mandate of the program. Presently the program iscollaborating with forest biometrics, the quantitative forestmanagement and wood quality programs, the center for forestbusiness, forest finance, forest economics, and a number of for-est product industry partners.

Proceedings of the fifth annual forest inventory and analysis symposium

— The Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture Forest Service has made significant progress implementing the annualized inventory in 46 States in 2004. Major increases in program performance included the availability of plot data and the plots’ corresponding approximate coordinates. A mill site study and biomass models were used to compare actual versus approximate coordinates. The protocols used to protect the privacy of private forest landowners did not meaningfully alter the results. A new strategic plan for FIA will be developed for 2007–12. Through meetings with partners and customers, FIA will evaluate opportunities to broaden the information collected and analyses of this data.