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FOREST PRODUCTIVITY: LESSONS
TO BE LEARNED
Richard G. Cline
Nelson S. Loftus
ABSTRACT
This paper is a discussion of our research progress in
increasing forest productivity relative to that in cropland
agriculture. Key differences seem to be due to the intense
cooperation among various agronomic specialties, their
ability to measure product yields over short periods of
time, and the availability of data sets containing very
specific crop / species, soil, climate, and fertility information. The lessons to be learned from field-crop production
research include the value of ecological concepts, a focus on
basic processes and controlling factors, the value of observation, the need to be active rather than reactive, and the
advantages of working together.
INTRODUCTION
Forest productivity seems at times to be looked upon
as a special, and somehow unrelated, aspect of agriculture. This view seems a bit narrow. Forestry, after all,
is based on essentially the same biological processes as
the rest of agriculture. This being true, what can we do
to take advantage of the relationships?
First, let us assume agricultural production (including
forestry) is based primarily on our ability to retrieve a
plant or plant-derived product from our environment.
What we use it for after that is a related but secondary
question. We could use it to feed ourselves, to feed animals that we subsequently eat, to produce fiber that we
use, or to produce a recreational environment to be enjoyed. All of these things have value. We harvest them
all in one form or another.
For the sake of argument and comparison let us look
at plant products that can be produced on the land and
sold after harvest. Let us compare productivity, and our
understanding of it, in cropland agriculture with that in
forestry. We have a long history of production in both.
Our ability to achieve production improvements, however,
has been much more impressive in our croplands than in
forestry. Why?
The first general thought that comes to mind is historic.
We have a rich history of intense cooperation among the
various agronomic specialties in cropland agriculture.
This has produced some truly impressive synergisms,
particularly among the fields of crop science, soil science,
Paper presented at the Symposium on Management and Productivity
of Western-Montane Forest Soils, Boise, ID, April 10-12, 1990.
Richard G. Cline and Nelson S. Loftus are Soil Scientists, Forest Environment Research Staff and Timber Management Research Staff, respectively, Forest Service, U.S. Department of Agriculture, Washington, DC.
and genetics. The yield of wheat, for example, has more
than quadrupled in the past 50 years. This cooperation
is one of the main reasons for our rapid increase in crop
production during the last half century. This kind of
cooperation has often been nearly absent from the field of
forestry. Why? Are the growth processes somehow different in forests than in field crops? That does not seem very
reasonable. All plants operate pretty much the same way
within certain limits. The same basic principles should
apply if one allows for species and culture differences.
COMPARING MEASUREMENT
Maybe we can shed some light on this problem by comparing production measurement in these two areas of
agriculture. Table 1 attempts to compare the process of
production measurement in croplands with that of forests.
While the comparison is not absolutely a true one for all
cases, it seems correct in a general sense. The table suggests many more similarities than differences. This
seems logical. The differences, while apparently few,
are glaring, at least in practice.
Table 1- A comparison of productivity measurement in cropland
and forest agriculture
Measurement
considerations
Cropland
Forestland
Measure
Harvested product
(grain)
Harvested product
(fiber)
When measured
Yearly
Over the rotation
What measured
Mass (weight)
Volume (when
sold)
Mass (weight)
Volume (when
sold)
Measurement
method
Scales
(grain elevator)
Scales
Volume measurement
Volume estimates
Measurement
context
Species, often
variety specific
Often not species
specific
Location specific
(known soil, fertility
levels)
Not location, soil, or
fertility-level
specific
Cost vs. return
usually well known
Cost VS. return
often difficult to
determine because of rotation
length
The harvested product seems like an obvious choice
for a first view, and should provide a good basis for evaluation, providing good measures of the harvested product
can be obtained. Similarities are much more obvious than
differences here. The period of measurement is a bit more
of a problem. Field crops are usually harvested during
the same growing season they are sown, and reasonably
reliable measurements can be obtained at that time. Forest products, trees for this example, are harvested over
a rotation that can be 80 to 100+ years. At other times,
field measurements and estimates with varying degrees
of reliabili ty are used. Harvests can range from partial
cuts through thinnings, where residual volumes are estimated, to clearcuts where all trees are removed and merchantable or total volumes are estimated. This is an important difference even though the units of measure
might be quite similar-for example, tons of grain and
tons of green wood. Another major difference is the measurement context. It seems the context of measurements
in forestry is usually much less specific, making it more
difficult to obtain useful information.
A summary of this comparison of cropland and forest
agriculture makes three points:
Obviously the returns for developing this kind of
knowledge and understanding for our intensively managed croplands are much greater than they are for our
forestlands. It is logical, then, to expect more effort in
those areas where returns are greater. This is likely to
continue in spite of increasing public attention on and
demands for resource returns from forested wildland
environments. We will need better data and firmer understanding of these environments to form the inferential
foundations for future management decisions as these
demands increase.
WHAT CAN WE DO?
It seems we have a challenge before us. We must overcome a limited, by comparison, availability of research
data, probably research funding, expertise, and the continuity of that expertise in the future. We must be more
efficient-use the data we have more efficiently and creatively and develop a more integrated understanding of
our resource base. There are a number of specific things
we can do. They are not new. They have been suggested
before, but we probably have not made adequate use of
them. Maybe, fuddy duddies that we are, we have trouble
forcing ourselves out of the rut in which we happen to find
ourselves. Here is a short list of some things to try, or try
again:
-We in forest science seem not to have brought the full
range of our scientific weapons to bear on the productivity
problem as has happened in cropland agriculture. We
tend not to work together. The reasons are not important.
We need to do it. The potential progress and benefits can
be significant if the results in other areas of agriculture
are any indication.
- Use ecological concepts to establish reference points
and a basis for data extrapolation and interpretation.
We have tried this before, often with considerable success.
Habitat type classifications and their growing utility are
but one example. There are a variety of other possibilities. We also need to recognize, however, that classifications are all artificial constructs. They are tremendously
valuable as a communication tool and as a method of
extrapolating inference through inductive reasoning.
The fact remains, however, that being artificial constructs
of our momentary and ever-changing concepts, they need
to be constantly challenged, tested, and revised. Their
value is that they are capable of helping us organize our
thoughts about complex landscape-based ecosystems,
isolate the properties of those systems most useful to us,
and facilitate our efforts to overcome our lack of adequate
empirical data.
-Our inability to measure our product reliably at short
intervals hampers progress. This seems like a major
problem. The long rotation length of forest crops makes
it much more difficult to accumulate the largely empirical
relational data sets critical to developing working mechanistic hypotheses. These hypotheses and the research
that they generate provide the specific understanding
needed to take advantage of the array of scientific synergisms seen in field-crop production.
-Our lack of data sets containing sufficient species and
growth environment (soil, climate, fertility) specificity is
another problem. The problem seems different, but its
effects are essentially the same as those related to long
rotations. We do not have the empirical data so necessary
to developing our concepts of mechanistic and process
reI ation shi ps.
-We need to focus on the basic processes and factors
controlling productivity. This is actually a corollary of the
previous point because the ecological concepts, if correctly
conceived, will be related to those basic factors and processes. Our ability to correctly identify these things will
be considerably enhanced by forming the alliances, previously mentioned, that have been so successful in cropland
agriculture. Having increased our productive capacity
for food, why should we ignore the potential for doing the
same for forested environments, whether we are producing fiber, wildlife, or scenery?
Research to determine productivity or response to
treatment has historically depended on field-plot-based
experiments. Results of this work have been used to infer
the effects of management inputs on outputs given a defined set of resource properties. Our history in the more
extensively managed forest environments has been less
successful than that in croplands and more dependent
on axiomatic information. Our efforts have been hindered
by the difficulty of adequately controlling experiments in
a highly variable wildland environment. This is not to
suggest that we have no good research results or that
there is no empirical data base to work from. We do have
data, and good research has been done.
- We need to relearn the value of observation. There
is a strong tendency in the scientific literature to discount
anything that does not have a number or a statistical procedure attached to it. Research should never be undertaken without adequate statistical preparation, but
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regression, for example, does not prove cause and effect.
Some of the most useful literature we have seen has been
among the older articles where conclusions were more
dependent on observation and where the logic connecting
observation and conclusions seems better developed than
is routine with our more sophisticated statistical procedures. Statistics are not a substitute for understanding
what is observed of nature.
properties we have been discussing. I would agree that
the taxonomy has extrapolative value. It is also an excellent vehicle for communicating commonly understood
ideas. It is, as are all classifications, a substantially artificial system reflective of the thoughts of its framers at
the time it was constructed. You might be aware that we
are continuing to change it as we learn more about soils.
Another point concerning the soil taxonomy seems important. It is, on the whole, a general system designed
to reflect concepts of the whole population of soils as we
presently understand them. This seems to be its main
objective. We need that kind of an overall view to help us
define and communicate ideas in common. Mapping problems and their associated local interpretations require a
different objective, consequently a different classification
design. It is basic to the logic of classification systems
that, for optimum utility, the system design should
change when its objectives change.
I will provide two examples using taxonomy as a reference to make this point. The taxonomy uses 35 percent
rock fragments as the class break between skeletal and
nonskeletal families. Remember that this must be imposed downward on the series, taken as a taxonomic class.
The field criteria for map unit design in a survey with
which I am familiar placed the class break for map units
near 20 percent. This suggests that the practical interpretive criteria did not fit the taxonomic criteria very
well. The solution was to ignore the taxonomic criteria
for survey purposes and handle the two taxonomic classes
involved (20-35 percent and 35 to something over 55 percent) as similar soils.
Another instance of map unit design at variance with
taxonomic criteria relates to classes of Andepts (35 cm
of andic, volcanic ash, material at the surface) and andic
subgroups (18-35 cm of andic material). This material
has some unique and valuable water-retention characteristics. These soils on steep south aspects seemed to need
about 25 cm of this material to support certain types of
productive timber stands and provide assurance of stand
regeneration. The map unit design described Andepts
and andic subgroups with ash caps greater than 25 em
as similar soils in some map units and andic subgroups
with typic subgroups (less than 18 cm) as similar soils
in others. The same kinds of soils on steep north aspects
in the same survey were not separated at the same
boundary (25 em ash cap), because the water relations
were not the same.
The point of all this is that, with changing class separation objectives, class boundaries need to change. This
is just fine for local interpretive purposes. The more general, formal taxonomies provide us with our conceptual
and communication tools. They need the stability associated with consistently established class definitions. We
need to recognize the value each has in our scheme of
things and avoid making ourselves slaves to either. We
build map units and interpretations from the soil properties and associated biological and physical responses we
observe. We develop concepts and communicate using
consistently defined sets of properties that we understand
in common.
-We need to resist the temptation to allow crisis to
drive programs. Too often, we are driven by short-term
objectives. This tendency is not going to go away. We
will all succumb to the short-term imperative at times,
but we must make sure, through it all, that we maintain
(reestablish where necessary) the utility and value of
long-term data. This is particularly important when the
crop we grow is a long-term crop. If the long-term experiments of Rothamsted and other places are valuable for
short-rotation species, think how valuable they must be
for species with much longer rotations.
- We need to take a lesson from our colleagues in cropland agriculture. We need to take advantage of the combined experience of the variety of specialty areas wi thin
both forestry and agronomic sciences. We need to work
together more than we do now.
The discussion, to this point, has concentrated on commodity production by plants. Forests have much more to
offer. Recreation opportunity, esthetics, and high-quality
water are but three examples. The demand for these
resources, and their value, seems to be increasing. This
trend is expected to continue. We need to develop better
productivity relationships for these resources because we
are being asked to produce them. Our management systems need to provide reliable estimates of our ability to
produce a complex array of values.
Speakers answered questions after their presentations.
Following are the questions and answers on this topic:
Q. (referred by Glen Klock)-About 95 percent of the
talks in this "Forest Soils Conference" have not used any
reference to soil taxonomic units. Are we really using
soils as currently defined in a taxonomic system, or do
we get enough soil direction by characterizing such factors
as soil compaction, soil erosion, nitrogen and carbon contents, and mycorrhizal conditions? If generalizations are
used, how do we extrapolate data and communicate with
others? Are we really preaching to the converted?
A. (from Cline}-I will answer the last part of the question first because it is the easiest. Yes, we probably are
preaching to the converted, especially at a conference like
this attended mostly by resource professionals and most
of those probably soil scientists. It is unlikely to be otherwise in this situation. The value of the conference of
course, is not the preaching. It is the exchange of ideas
and the publication we can use to inform others.
Concerning the apparent lack of taxonomic class reference in papers presented, I would suggest that taxonomic
classes are only useful if their specific interpretive value
is known and well documented in relation to the soil
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