...

Shaw JD - Benefits of a strategic national forest inventory to science

by user

on
Category:

forestry

3

views

Report

Comments

Transcript

Shaw JD - Benefits of a strategic national forest inventory to science
©
Commentary
i Forest – Biogeosciences and Forestry
Benefits of a strategic national forest
inventory to science and society: the USDA
Forest Service Forest Inventory and Analysis
program
Shaw JD
Forest Inventory and Analysis, previously known as Forest Survey, is one of the
oldest research and development programs in the USDA Forest Service. Statis­
tically-based inventory efforts that started in Scandinavian countries in the
1920s raised interest in developing a similar program in the U.S. The U.S.
Congress established the research branch of the U.S. Forest Service in 1928,
shortly after Dr. Yrjö Ilvessalo, leader of the first Finnish national forest inven­
tory, met with President Calvin Coolidge. Congress charged the Forest Service
to find “facts as may be necessary in the determination of ways and means to
balance the timber budget of the United States”. As a result, Forest Survey
maintained a timber focus for much its history. As society’s interest in forests
changed over time, so did information needs. Conflicts over resource alloca­
tion and use could not be resolved without up-to-date knowledge of forest sta­
tus and trends. In response to society’s needs, the Forest Inventory and Analy­
sis program has evolved from Forest Survey to address diverse topics such as
forest health, carbon storage, wildlife habitat, air pollution, and invasive
plants, while continuing its mandate to monitor the Nation’s timber supply.
The Forest Inventory and Analysis program collects data on all land ownerships
on an annual basis. The data are used to develop reports on a regular basis; re­
ports and raw data are available to the public at no cost. The data are also
used by scientists in a growing number of applications. A short history of the
Forest Survey is presented with several examples of current research based on
Forest Inventory and Analysis data.
Keywords: forest inventory, FIA, silviculture, disturbance, United States
Introduction
wide variety of forces that change them,
make national strategic forest inventory a
high research priority. This paper describes
the history of the Forest Inventory and Anal­
ysis program, the products it produces, and
the consumers of its products. Some of the
research and reporting examples are specific
to the Interior West FIA (IW-FIA) program,
but similar examples can be found in all the
regional FIA units.
History of the U.S. Forest Survey
Prior to the 20th century, North American
forest resources were treated primarily in an
extractive manner with little regard to regen­
eration or sustained yield. Forests were es­
sentially mined as the wave of European set­
tlement proceeded from east to west. In the
late 19th century, as concerns about the di­
minishing forest resource increased and sci­
entific forestry began to establish a foothold,
interest in assessing the status and trends of
the resource began to emerge. Early invento­
ries - for example, Hough’s Report Upon
Forestry (1878 to 1882) - were primarily
subjective and only provided a generalized
picture of forest conditions. In 1905, the For­
est Service was established under the U.S.
Department of Agriculture and was directed
to maintain healthy and productive forest
land in the U.S. Gifford Pinchot, the first di­
rector of the agency, emphasized scientific
forestry based on his forestry education in
Europe. In the early 1920s, Scandinavian
countries started to implement statisticallybased inventories, and in 1928 Dr. Yrjö Il­
vessalo of the Finnish national forest inven­
The Forest Inventory and Analysis (FIA)
program, previously known as Forest Sur­
vey, is one of the oldest research and devel­
opment programs in the USDA Forest Ser­
vice. The program is considered the nation’s
"forest census", because it includes all forest
types and land ownerships in the United
States. The forests are diverse both in terms
of their type - ranging from boreal spruce
forests in Alaska to subtropical hardwoods in
Florida - and their use - including intensively
managed, industry-owned forests in the Pa­
cific Northwest and unmanaged public
wilderness in the Rocky Mountains (Fig. 1).
The importance of these forests, and the
USDA Forest Service, Rocky Mountain
Research Station - 507 25th Street, Ogden,
Utah (USA)
*Email: ([email protected]).
Citation: Shaw JD, 2008. Benefits of a
strategic national forest inventory to science
and society: the USDA Forest Service Forest
Inventory and Analysis program. iForest 1:
81-85 [online: Feb 28, 2008] URL:
http://www.sisef.it/iforest/
© SISEF http://www.sisef.it/iforest/
Fig. 1 - Examples of forest diversity from around the United States. (A) White spruce (Picea
glauca) woodland in Alaska. (B) Gum-cypress-cottonwood in South Carolina. (C) Intensive­
ly-managed Douglas-fir (Pseudotsuga menziesii) in the Oregon Cascades. (D) Oak-hickory
forests in Pennsylvania.
81
iForest (2008) 1: 81-85
Shaw JD - iForest 1: 81-85
ventory system using a standardized plot de­
sign (see below). Funding for the program
has increased dramatically since 1998. Fol­
lowing passage of the 1998 Farm Bill, FIA
program managers were asked to provide an
estimate of the cost to implement the annual
inventory in every state. While the required
amount has not yet been appropriated, the
gap between program needs and actual fund­
ing as decreased over the years. It should be
noted that approximately 15% of the FIA
budget is used for quality control of methods
and data.
How it is done
Fig. 2 - Regional Forest and Inventory and Analysis units and approximate forested area in­
cluded in each.
tory met with U.S. President Calvin
Coolidge. Later that year, the U.S. Congress
passed the McSweeney-McNary Act, estab­
lishing the research branch of USDA Forest
Service, including the Forest Survey (Van
Hooser et al. 1993). The law specifically in­
structed the Forest Service:
“... to make and keep current a compre­
hensive survey of the present and prospec­
tive requirements for timber and other forest
products in the United States, and of timber
supplies, including a determination of the
present and potential productivity of forest
land therein, and of such other facts as may
be necessary in the determination of ways
and means to balance the timber budget of
the United States”.
In 1929, Forest Survey planning began in
Oregon and by 1932 the inventory of the
western Cascades was complete. In the same
year, inventories were started in Idaho, the
Great Lakes States, and some southern
states. During World War II there was a tem­
porary halt to the survey. The last 3 states Arizona, New Mexico, and Nevada - were
completed in 1962, marking the end of the
first inventory cycle in the coterminous 48
states. In the 1960s and 1970s, funding for
the program increased; almost all states were
visited again, and some twice during the pe­
riod. The average re-visitation cycle between
the first and second inventory was then 1315 years. In the 1980s the Survey was active
in all states except Utah and Ohio. National­
ly, the re-visitation interval averaged about
12 years, but some of the southeastern states
were re-inventoried as frequently as 5 or 6year intervals (Van Hooser et al. 1993).
In the late 1980s and early 1990s the pro­
gram adopted a fixed periodic inventory sys­
iForest (2008) 1: 81-85
tem, with a 10-year cycle in most western
states and a 5-year cycle in most southern
and eastern states. However, some states, for
a variety of reasons, were not re-inventoried
on schedule and some states were not revisit­
ed for 15-20 years. By the early 1990s, some
users of FIA data recognized that aging peri­
odic inventories - even those done at 5-year
intervals - did not meet their needs. Rapid
changes, such as hurricanes and insect out­
breaks, prematurely outdated periodic inven­
tory data. As a result, the U.S. Congress in­
cluded language in the 1998 Farm Bill re­
quiring the FIA program to convert to a con­
tinuous annual inventory system and produce
state-level results on a regular schedule.
Today, the FIA program operates 4 region­
al programs (Fig. 2) and conducts inventory
on over 3 million forested hectares in the
United States and U.S. Territories. Nearly all
states have been converted to the annual in­
FIA inventories are conducted using a dou­
ble sampling design, with plots arranged on
a systematic grid. It is sometimes referred to
as a 3-phase design, although this is not a
precise description of the statistical design.
The third “phase”, described below, actually
consists of additional variables that are mea­
sured on a subset of plots. The term “phase”
is commonly used to refer to plot type and
will also be used here. Phase 1 (P1) plots are
based on remotely sensed data and are used
for stratification. In the past, Phase 1 consist­
ed of airphoto points located on a 1-kilome­
ter grid, but the availability of satellite im­
agery now allows for continuous (wall-towall) stratification. Phase 1 points are used
to determine expansion factors for strata
(e.g., forest nonforest) at geographic scales
smaller than states (e.g., counties or sample
zones). Therefore, forest area represented by
a Phase 2 plot is determined according to
stratification of Phase 1 plots and not strictly
by their grid spacing.
Phase 2 (P2) plots, also known as standard
FIA plots, are located at 5-kilometer inter­
vals, equal to an intensity of approximately 1
field plot per 2388 hectares. The P2 plot de­
sign consists of 4 subplots of 0.017 ha each,
with centers 36,6 m apart (Fig. 3A). Plots are
mapped when more than one forest or nonforest condition occurs (Fig. 3B). Up to 120
variables are recorded at the plot, subplot,
Fig. 3 - FIA plot design (A) and example of mapping several conditions on one plot (B).
FWD = fine woody debris and CWD = coarse woody debris. Woody debris diameter ranges
are listed with the portion of the transect on which the classes are recorded.
82
© SISEF http://www.sisef.it/iforest/
Benefits of a strategic national forest inventory to science and society
Wyckoff et al. 1983). If these products do
not meet the user’s needs, raw data are avail­
able as database tables in comma-delimited
format, organized by state and inventory
year. Under the annual inventory system,
data are usually available to the public with­
in 6 months of the time that the last plots
have been measured in a state.
In response to user demand in recent years,
the FIA program has devoted significant re­
sources to the development of map products
and mapping techniques. These products are
produced by combining FIA data with a
wide variety of GIS data (usually at 250m to
1km resolution), using multivariate analysis
methods.
Examples of Scientific
Applications Using FIA Data
Fig. 5 - Progression of pinyon mortality (% of basal area) 2000-2004, based on FIA annual
inventory data from 4 western states (from Shaw et al. 2005); AZ = Arizona, CO = Col­
orado, NV = Nevada, UT = Utah, All = entire 4-state area.
condition, or tree level. Under the annual in­
ventory system, a fraction of the plots on the
P2 grid (10% in the west and 15% in the
east) are measured each year. Plots belong­
ing to an annual panel are distributed across
each state so as to be free of geographical
bias.
Phase 3 (P3) plots, also known as Forest
Health Monitoring plots, are a subset of P2
plots, with 1 field plot per approximately 38
850 ha (16x the area represented by a P2
plot). On P3 plots, several “health indica­
tors” are measured woody material, soils,
lichens, crown conditions, and ozone as well
as all P2 variables. P3 plots were remeasured
on a 5-year cycle, but recently have been
synchronized to the local P2 cycle.
data using the Forest Inventory Mapmaker
web interface (http://www.ncrs2.fs.fed.us/­
4801/FIADB/index.htm). Data may be sum­
marized at the state and county level, by
user-defined latitude-longitude boundaries,
or within a circle of user-defined center and
radius. Output may be obtained in the form
of a standard table set, user-defined tables,
maps, or dump files ready for input in the
Forest Vegetation Simulator (Johnson 1997,
FIA scientists have long used FIA data as a
research data set, and have implemented
many studies designed to improve inventory
and monitoring techniques. In addition, FIA
scientists frequently collaborate with scien­
tists at universities and other government
agencies on a variety of studies. Over 1425
citations related to the FIA program were
published from 1976 to 2001, including over
50 master’s theses and 100 doctoral disserta­
tions (Rudis 2003). The range of topics in­
cludes air pollution, biomass and dead wood,
esthetics, nonforest influences, owner atti­
tudes, rangeland values, recreation opportu­
nities, water quality, vegetative habitat typ­
ing, and wildlife habitat. The number and
scope of papers has increased steadily over
the past 30 years (Rudis 2003).
Use of FIA Data by Science and
Society
FIA data are used by many sectors of soci­
ety, each of which prefers data or analyses in
different formats. The distinction in the title
of this paper between science and society the
former of which is obviously a subset of the
latter is based on both data needs and the ex­
tent to which in each group has historically
used FIA data. Basic FIA products, such as
State or National Forest inventory reports are
used by a wide variety of clients for informa­
tion and planning purposes. FIA also pro­
duces special reports on topics such as forest
health or timber products output. In addition
to hardcopy format, these reports are accessi­
ble to the public on the worldwide web at no
cost.
If a user needs more data and tables than
are presented in FIA reports, he or she can
produce customized tables or download raw
© SISEF http://www.sisef.it/iforest/
Fig. 4 - DCA plot of aspen structure and composition in the western United States. Labels
are at approximate DCA coordinates for geographic regions (from Shaw 2005).
83
iForest (2008) 1: 81-85
Shaw JD - iForest 1: 81-85
Fig. 6 - Forest damage typical of areas severely affected by hurricanes Katrina and Rita. Dominant species on this site was loblolly pine (Pi­
nus taeda).
Recent examples of silvicultural and eco­
logical research in the Interior West include
development of density management dia­
grams (Long & Shaw 2005), range-wide
analysis of aspen stand structure (Shaw
2005), and monitoring the effects of pro­
longed drought on pinyon-juniper woodlands
(Shaw et al. 2005). One important factor,
common to these and other FIA based stud­
ies, is that the data are drawn from an unbi­
ased, systematic sample of plots that are dis­
tributed throughout the range of the forest
types of interest.
The ponderosa pine density management
diagram (Long and Shaw 2005) was devel­
oped using 767 plots selected from over
8800 FIA plots on which ponderosa pine oc­
curred. Analysis plots were selected accord­
ing to strict composition and structural crite­
ria, and represented the entire range of pon­
derosa pine in the U.S. Maximal stand densi­
ty was found to be similar among regions,
but there were regional differences in "typi­
cal" stand structure and composition. As a
iForest (2008) 1: 81-85
result, it was shown that the diagram would
be applicable throughout the range of pon­
derosa pine in the U.S.
In the aspen study (Shaw 2005), 3371 plots
from 19 FIA surveys in 13 states in the west­
ern U.S. were found to have at least one as­
pen present. There were 70 associated tree
species, and 45 of those were sufficiently
common as to be included in the analysis.
Ordination of stands based on structure and
composition revealed broad regional patterns
(Fig. 4). These patterns may be used to de­
velop strategies for regional risk assessment,
because structural and compositional charac­
teristics offer insight into possible succes­
sional patterns and potential responses to
disturbance.
Assessment of drought effects in pinyonjuniper woodlands was possible because im­
plementation of the annual inventory system
was coincident with the beginning of the
drought in the American Southwest (Shaw et
al. 2005). Recent periodic inventories and
the first 2 years of annual inventory showed
84
that, in non-drought years, background mor­
tality of pinyon and juniper species was rela­
tively low. Mortality increased dramatically
over a 2-year period, before wetter weather
and crashing beetle populations caused mor­
tality rates to decrease. The availability of
annual inventory data made it possible to
track the progression of mortality in "real
time". The current estimate is that approxi­
mately 6% of the basal area of pinyon died
due to drought-related causes since 2000,
with Arizona suffering the greatest amount
of pinyon mortality (>13% of basal area) and
Nevada having the lowest pinyon mortality
(3% of basal area - Fig. 5). No estimate will
be available for New Mexico until annual in­
ventory is implemented, but mortality mod­
els, based on edaphic factors and stand struc­
tural characteristics of affected plots in other
states, should permit predictions of severity
and extent.
A common and important aspect of these
studies is that the results were obtained using
data available to the public in other words,
© SISEF http://www.sisef.it/iforest/
Benefits of a strategic national forest inventory to science and society
the results can be produced (or reproduced)
by anyone. Although verifiability is an im­
portant tenet of scientific inquiry, access to
researchers’ data can be difficult at times.
However, data collected under the FIA pro­
gram, which is publicly funded, are available
to all. This fact in itself constitutes an impor­
tant contribution to science and society. That
being said, there are also safeguards in place
to ensure confidentiality of data collected on
private lands and the integrity of permanent
plot locations. This (perhaps unique) combi­
nation of openness and security contribute to
users’ confidence in the integrity of the FIA
program.
Continuing Value of FIA
The discussion above of mortality in piny­
on-juniper woodlands alluded to the value of
continuous inventory under the annual sys­
tem. However, recent events in particular,
the devastating effects of hurricanes Katrina
and Rita on the southeastern U.S. (Fig. 6)
may further prove the value of the FIA pro­
gram. At the time of this presentation
(September 27, 2005), only 29 days after Ka­
trina made landfall, the FIA program has
produced a rapid assessment of the economic
and ecological damage caused by the hurri­
cane (Society of American Foresters 2005,
U.S. Department of Agriculture 2005):
• Over 2.000.000 ha of forest were affected
by Katrina
• The value of timber affected is greater than
$US 5.000.000.000
• If recoverable, damaged wood is sufficient
to produce 800.000 single family homes
and 20.000.000.000 kilos of paper products
• Most of the damage occurred within 95km
of the Gulf Coast
• Approximately 2/3 of the damage occurred
in Mississippi
• Detailed FIA assessment has already start­
ed, and the inventory will be updated annu­
© SISEF http://www.sisef.it/iforest/
ally as annual panels are completed
It should be noted that continuing assess­
ment of hurricane damage will not require a
change in FIA sampling protocol, although
grid intensification or other ad-hoc changes
may be made to answer specific questions.
The annual inventory system, conducted on a
routine basis, will permit not only assess­
ment of hurricane damage, but also the ef­
fects of salvage, insect outbreaks, and fire in
the affected areas, as well as monitoring re­
covery over time.
Conclusions
The USDA Forest Service Forest Inventory
and Analysis program serves a broad seg­
ment of society by keeping a comprehensive
inventory of the forests of the U.S., and pro­
ducing data, summaries, and analyses for a
variety of audiences. Use of FIA data has
been growing steadily over the past 3
decades, but use in scientific applications is
still lower than potential. However, the list
of research applications is growing as more
scientists become familiar with the program.
Open access to data, the integrity of the pro­
gram, and continuing service to society has
earned support that is important in a time of
tight budgets. Finally, the recent evolution of
the FIA program into a continuous annual in­
ventory system ensures that FIA data will
only become increasingly valuable with
time.
References
Hough FB (1878). Report upon forestry. Washing­
ton, D.C.: U.S. Government Printing Office.
Johnson RR (1997). A historical perspective of the
Forest Vegetation Simulator. In: Proceedings Forest Vegetation Simulator conference, Feb. 37, 1997 (Teck R, Moeur M and Adams J eds).
USDA For. Serv. Gen. Tech. Rep. INT-373. pp
3-4.
Long JN, Shaw JD (2005). A density management
85
diagram for even-aged ponderosa pine stands.
Western Journal of Applied Forestry 20: 205215.
Rudis VA (2003). Comprehensive regional re­
source assessments and multipurpose uses of for­
est inventory and analysis data, 1976 to 2001: a
review. Gen. Tech. Rep. SRS70. Asheville, NC:
U.S. Department of Agriculture, Forest Service,
Southern Research Station.
Shaw JD (2005). Aspen stand structure and com­
position in the western U.S.: implications for
management. Proceedings: Canadian Institute of
Forestry / Society of American Foresters Joint
2004 Annual General Meeting and Convention.
October 2-6, 2004. Edmonton, Alberta, Canada.
Bethesda, Maryland: Society of American
Foresters. [published on CD-ROM].
Shaw JD, Steed BE, De Blander LT (2005). Forest
Inventory and Analysis (FIA) annual inventory
answers the question: what is happening to piny­
on-juniper woodlands? Journal of Forestry 103:
280-285.
Society of American Foresters (2005). USDA sci­
entists estimate Katrina destroyed 19 billion
board feet of timber. The E-Forester, September
19, 2005 [distributed by email].
U.S. Department of Agriculture (2005). USDA
Forest Service reports significant damage by hur­
ricane Katrina to public and private timberland.
News Release No. 0376.05 (September 15,
2005). U.S. Department of Agriculture, Wash­
ington, D.C.
Van Hooser DD, Cost ND, Lund HG (1993). The
history of the Forest Survey program in the Unit­
ed States. In: Proceedings of the IUFRO Centen­
nial Meeting, August 31 - September 4, 1992,
Berlin, Germany (Preto G, Koch B eds). Japan
Society of Forest Planning Press, Tokyo Univer­
sity of Agriculture, pp. 19-27.
Wykoff WR, Crookston NL, Stage AR (1982).
User’s guide to the Stand Prognosis Model.
USDA For. Serv. Gen. Tech. Rep. INT-133.
USDA Forest Service, Intermountain Forest and
Range Experiment Station, Ogden, Utah.
iForest (2008) 1: 81-85
Fly UP