Raymond Sheffield
                        Supervisory Research Forester
                    Southeastern Forest Experiment Station
                                P.O. Box 2680
                             Asheville, NC 28802

ABSTRACT:  A network of 3,500 permanent ground plots was utilized to assess
damage from a major hurricane that struck the Southeastern United States in
1989.  Hurricane Hugo inflicted varying degrees of forest damage across an
area of 4.4 million hectares.  This paper summarizes data collection and
analytical procedures used to assess forest damage across this area.  Results
that are easily provided from remeasurement of permanent plots are
highlighted.  Advantages and disadvantages of ground-based permanent plot
assessment systems are highlighted.

                                 INTRODUCTION

   Hurricane Hugo struck the Southeastern United States in September 1989 with
winds of 217 kilometers per hour, or 60 meters per second (Powell, Dodge and
Black, 1991).  Hugo extensively damaged forest stands in North Carolina and
South Carolina.  It significantly altered forest conditions and inventory
volumes and rendered many short- and long-term forestry resource programs
obsolete.  Forestry agencies in the two States conducted aerial and ground
reconnaissance surveys to determine the extent of the damage.  Their
observations and subjective estimates were adequate for planning initial
responses, but they needed more quantitative measures for long-term planning.

   The South Carolina Forestry Commission asked the Forest Inventory and
Analysis (FIA) Research Work Unit at the Southeastern Forest Experiment
Station to conduct a special inventory of forests in that State's affected
area.  This damage assessment was later expanded to include a large portion of
North Carolina (  Figure 1  ).  The area of timberland in the study region totaled
4.4 million hectares.  Utilizing a previously established network of permanent
ground plots throughout this region, FIA designed damage inventory procedures
to:  (1) quantify the extent of damage and describe associated stand
conditions, (2) determine the volume of hurricane-related mortality and damage
to live trees, and (3) provide an estimate of current inventory volume.

                                   METHODS

   FIA is a research sctivity of the USDA Forest Service.  Its mission is to
comprehensively inventory the status and trends of the country's diverse
forest ecosystems, their use, and their health (U.S. Department of
Agriculture, Forest Service, 1992).  Six regional FIA units maintain a network
of permanent samples on forest land across the United States.  More than 3,500
of these permanent plots were in North and South Carolina counties damaged by
Hurricane Hugo.  Prior to the hurricane, these ground plots had been visited
and measured last in 1984 in North Carolina and 1986 in South Carolina.

Field Procedures

   Data collection procedures are briefly summarized in this paper; details
are available in a report by Sheffield and Thompson (1992).  Two-person crews
visited each sampling location in 1990, 5 to 9 months after Hurricane Hugo
struck.  Each tree above a minimum diameter at 1.4 meters above the ground was
relocated.  The minimum diameter used was 7.6 centimeters for trees in natural
stands and 2.5 centimeters for trees in planted stands.  Each tree was
assigned one of the following six tree histories:

                   <> tree alive without hurricane damage
                   <> tree alive with hurricane damage
                   <> tree dead (hurricane related)
                   <> tree dead (other causes)
                   <> tree cut, associated with hurricane salvage efforts
                   <> tree cut, associated with normal harvest operations

   For all live trees with hurricane damage, specific classes of damage were
noted.  Damage classes were:

                   <> leaning or bending (degrees from vertical)
                   <> root system damage
                   <> damage to tree bole
                   <> loss of tree crown

Any combination of these could be assigned to a tree; multiple damages, such
as severe lean and exposed root system, were common.

Analytical Procedures

   Standard protocols for the analysis of data from a damage inventory are not
available.  One must adjust methods to account for the magnitude of loss and
the specific goals that have been specified.  After Hugo, we wanted to
quantitatively estimate damage to individual trees and to stands of trees.
Little published data were available in the literature to assist in this
process, so various approaches to solving these problems were used.

   In a ground-based damage inventory, the types of damage to individual trees
must be categorized.  Damage may be so minor that the tree's value, growth,
and probability of survival are not affected.  Conversely, damage may be so
severe that the tree's value has been destroyed, its growth potential reduced
to a fraction of normal, or its survival chances severely reduced.  Guidelines
for assigning meaningful categories of damage were not found in the
literature, so we developed our own classification framework.  Our design
permits decisions about individual trees to be made on the basis of value,
likely contribution, and development in the future.  Detailed criteria for
assignment of softwood and hardwood trees into four damage categories were
developed and modified based on review by more than a dozen individuals.
Sheffield and Thompson (1992) describe the process and the criteria.  Here I
present the damage/risk classes used and a brief description of levels of tree
damage in each class.

   Class 1.  High-risk tree with a probability of dying in the near future.
             damage and value loss are severe enough that this tree should
             not be retained in the stand.

   Class 2.  Moderate-risk tree with elevated risk of mortality.  Damage and
             value loss are substantial enough to make the retention of this
             tree in the stand questionable.  Retention depends upon
             management objectives, stand and rotation age, and product
             objectives.

   Class 3.  Low-risk tree with a high probability of survival.  Damage
             elevates the risk of mortality slightly, but reduced growth and
             value degrade are minimal.  This tree should be retained in the
             stand under most management scenarios.

   Healthy.  No obvious hurricane damage.  A tree with hidden or internal
             damage would be classed as healthy.

   The assessment of stand conditons depends on the condition of individual
trees remaining in the stand.  Thus, the decision to regenerate or salvage
requires sound judgments about individual trees and about the level of
residual stocking needed for an acceptable stand.  One must also determine
which categories of damage are acceptable for inclusion in minimum residual
stocking.  In the analysis of damage from Hurricane Hugo, I used the three
broad categories of damage to trees in different ways to estimate lower- and
upper-bound values for timberland area by condition class and treatment
opportunity.  For example, in South Carolina the estimate of timberland area
needing regeneration because of Hurricane Hugo ranged from 328,000 to 623,000
hectares depending on which live tree damages were used to discount existing
stocking in the stand (Sheffield and Thompson, 1992).

                    RESULTS AVAILABLE FROM PERMANENT PLOTS

   Damage inventories utilizing permanent plot remeasurement can provide a
wealth of information to the resource manager or analyst.  The classifications
and resource items than can be displayed depend in part on the classifications
that have been made prior to the damage event.  Forest type and age, for
example, are sometimes difficult to assess after severe damage or salvage has
occurred.  The following is a brief summary of the kinds of results that were
available in the Hurricane Hugo damage assessment.

   (1) AREAL EXTENT OF DAMAGE.  Timberland area damaged can be estimated and
displayed for political or administrative units, ownership categories, forest
types, or any other stand classification available from the existing
inventory.  Information about the impact on the age structure of the forest is
often needed to evaluate timber supply impacts.   Figure 2 shows how the age
structure of natural pine stands in South Carolina was affected by Hugo.  Maps
showing the geographic extent and distribution of forest damage are also
easily produced ( Figure 3 ).  If the coordinates of each permanent sampling
point are known, a geographic information system can overlay information about
stand damage severity with other layers.  In  Figure
3, State and county
boundaries and the path of the hurricane's eye are shown along with damage.
Inventory results such as this map are similar to products developed from
satellite imagery.  Ground-based inventories, however, can provide more
quantitative estimates of timber volumes associated with conditions on the
ground.

   (2) INVENTORY UPDATES.  The remeasurement of all merchantable-size trees
facilitates accurate estimates of current inventory volume, change since the
previous sample measurement, and volume loss due to the damaging event.
 Figure 4 summarizes volume change for softwood species in South Carolina.
In this example, softwood volume totaled 136 million cubic meters in 1986 and
had dropped to 107 million cubic meters in 1990.  Mortality and timber salvage
due to hurricane damage accounted for 29 million cubic meters.  Inventory
updates such as this can be summarized by ownership class, stand condition,
political or geographic unit, species, or tree size.

   (3) DAMAGE SEVERITY IN LIVE TREES.  Estimates of the prevalence of damages
to the current inventory of live trees are needed to predict future mortality.
If substantial numbers of live trees are classed as severely damaged (class
1), mortality is likely to remain high for a long time ( Figure 5 ).  In this
example, 68 percent of the hardwood volume in South Carolina was classed as
healthy and 32 percent damaged.  About 37 percent of the damaged trees were
classed as severely damaged (class 1).  If these trees die, an additional
reduction in inventory volume of around 12 percent can be anticipated.

   (4) ESTIMATES OF TREATMENT OPPORTUNITIES.  For long- and short-term
planning, estimates of stand treatment needs for regional areas are essential
after catastrophic events such as hurricanes.  The classifications described
earlier help in estimation of the forest areas needing regeneration, salvage,
and other treatments.

       PERMANENT PLOT DAMAGE ASSESSMENT -- ADVANTAGES AND DISADVANTAGES

Advantages

   A network of permanent ground samples offers five obvious advantages over
other methods such as remote sensing for forest damage assessment:

   (1) Forest conditions that existed before the catastrophic event are known.

   (2) Quantitative estimates of volume loss and damage are direct outputs
       from the system, and can be provided for critical subsets of the
       overall resource.

   (3) Up-to-date estimates of inventory volumes are provided.

   (4) Ground-based inventories set the stage for subsequent remeasurements
       to estimate recovery.

   (5) Ground-based inventories provide precise values needed to validate the
       rough estimates that can be made with remote sensing data.

Disadvantages

   (1) Depending on the inventory objectives, ground-based activity can be
       more costly than other inventory methods.

   (2) Results may take longer to produce because field visits are so time
       consuming.

   (3) A satisfactory network of permanent plots for producing reliable
       results may not exist.

   (4) Large numbers of samples may be needed.


                               LITERATURE CITED

Powell, Mark D., Peter P. Dodge and Michael L. Black.  1991.  The landfall of
   Hurricane Hugo in the Carolinas:  surface wind distribution.  Weather and
   Forecasting 6:379-399.

Sheffield, Raymond M. and Michael T. Thompson.  1992.  Hurricane Hugo:
   effects on South Carolina's forest resource.  Res. Pap. SE-284, Asheville,
   NC:  U.S. Department of Agriculture, Forest Service, Southeastern Forest
   Experiment Station.  51 p.

United States Department of Agriculture, Forest Service.  1992.  Forest
   Service resource inventories:  an overview.  Washington, DC.  39 p.