|
Items in cart [0] |
Questions? Call 888-624-8373 |
HARDBACK + PDF HARDBACK PDF BOOK PDF CHAPTERS Free Resources |
||||||||||||||||
|
||||||||||||||||
|
|
|||||||||||||||
| ||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 64
4
Indicators for
National Ecological Assessments
' n the preceding chapters, we have discussed the desirable characteris-
tics of indicators, the sources of data that underlie them, the models
~ that support them, and the criteria by which good indicators can be
identified. Based on those discussions and the conceptual model we used,
the committee recommends national indicators for three major categories
of ecological information. These categories encompass the nation's most
important ecological issues. By computing them and paying attention to
them, the nation should be aware of the status of its ecosystems, be alerted
to changes that may require management interventions and policy
changes, and have a basis for ensuring that future generations will have
access to ecosystem goods and service as rich as those enjoyed today. In
some cases, noted for each indicator, some experience will need to be
gained on details of the indicator's behavior, but all the indicators are
based on soundly established scientific experience and principles. The
proposed indicators are in general applicable to both managed (e.g., agri-
cultural) and unmanaged ecosystems; the indicators of nutrient-use effi-
ciency and overall nutrient balance are specific to agricultural ecosystems.
· Information about the extent and status of the land use and cover
types that together make up the nation's ecosystems. Information about
the extent of the nation's land use and cover types informs us about the
extent of ecosystem types in the nation, and it is needed to calculate
several other indicators. The information and technology to calculate
land cover is currently available. Land use in some ways is more informa-
64
OCR for page 65
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
65
live because it provides additional information on the status of areas and
hence their ability to provide goods and services. Also, information on
how land is used is predictive of future land cover and hence predicts the
ability to provide goods and services. However, a land use indicator
requires much synthesis of existing information and some new informa-
tion, and thus will take longer to develop than a land cover indicator.
Meanwhile, land cover can serve as a valuable indicator.
· Information about the nation's ecological capital. This informa-
tion measures the nation's natural capital, or raw materials, both abiotic
and biotic. Abiotic raw materials essential for ecosystem functioning
include soil (also partly biotic) and its nutrients. Biotic raw material
includes the number of species still present in the country relative to their
number at the time of European contact, their distribution over today's
natural and human-modified environments, and the number of species
present today that are exotics, those species introduced, deliberately or
inadvertently, that have become established or naturalized.
Indicators of biological capital are important for several reasons.
Knowing what portion of our biological capital is native provides a sensi-
tive measure of humans' environmental impacts, as described below.
Assessing the status of the nation's biological capital is important for
ethical and aesthetic reasons. Also, biological diversity is an indicator of
the capacity of ecosystems to function effectively. An important but
controversial theory holds that because species differ, species-rich eco-
systems are more likely than species-poor ecosystems to contain some
species that can thrive during an environmental perturbation (Mooney et
al. 1996~. As a result, species-rich systems should be buffered against
disturbances and continue to perform better in fluctuating environments
than species-poor systems. Empirical studies are still few, but they pro-
vide some support for the hypothesis (Tilman 1996, Tilman and Downing
1994, Naeem et al. 1994~. Further investigations will clarify relationships
between biological diversity and ecosystem processes. Meanwhile, it is
prudent to monitor the status of the nation's biological resources.
· Information about the functioning (performance) of the nation's
ecosystems and how it is changing. This information includes measures
of productivity and other ecosystem processes. Changes in the produc-
tivity of ecosystems are generally accompanied by changes in their ability
to provide goods and services. Usually, declines in productivity are
undesirable, but in freshwater ecosystems, increases in productivity asso-
ciated with eutrophication can be undesirable.
For each of these major categories of information we recommend
indicators (Table 4.1) that are described in detail below. Although the
categories apply to all ecosystems, they differ in many details for marine,
OCR for page 66
66
ECOLOGICAL INDICATORS FOR THE NATION
TABLE 4.1 National Indicators of Ecological Condition
Category of Recommended Reasons for
EcologicalInformation Indicators Choosing Indicator
Extent and Status of
the Nation's
Ecosystems
Ecological Capital
Biotic Raw Materials
Land Cover and
Land Use*
Total Species Diversity
Native Species Diversity
Needed for calculation of most
other indicators. Inform us
about the overall extent of
different ecosystem types.
Measures nation's biological
resources (what is present
relative to what is expected).
Measures the amount of
biological diversity that is
native.
Ecological Capital Nutrient Runoff Estimator of total losses of
Abiotic Raw Materials nutrients. Nutrient runoff has
major effects on receiving
waters.
Soil Organic Matter* Best single indicator of soil
condition, related to erosion.
Ecological Functioning
(Performance)
Productivity, including
Carbon Storage, Net
Primary Production
(NPP), and Production
Capacity
Lake Trophic Status
Stream Oxygen
Soil Organic Matter*
Nutrient-Use Efficiency
and Nutrient Balance
Land Use*
Direct measures of the amount of
carbon sequestered or retained
in an ecosystem (NEP), energy
and carbon brought into an
ecosystem (NPP), and energy-
capturing capacity of ecosystems
(chlorophyll).
Direct measure of ability of lakes
to provide goods and services.
Captures the balance between
instream primary production
and respiration.
Single most important indicator
of soil quality and productivity.
Inefficient use of nutrients is
costly in terms of economics and
damage to ecosystems to which
nutrients are discharged.
Provides information about
ecosystem functioning.
*Indicators in more than one category.
OCR for page 67
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
67
freshwater, and terrestrial ecosystems. Because marine ecosystems were
not specifically covered by the committee's charge, we focus on terrestrial
and freshwater ecosystems and the interface between them-wetlands.
More research is needed for the full implementation of these indicators.
We offer some suggestions for the order in which some components might
best be initiated.
Although the national-level indicators we propose are highly aggre-
gated, most of them require detailed input data. If these data are archived
in a disaggregated form, the indicators can be computed in a variety of
ways to provide a rich array of indicators of great local and regional
value. Chapter 5 describes how that can be done and describes additional
regional and local indicators.
THE EXTENT AND STATUS OF THE NATION'S ECOSYSTEMS
To estimate the capacity of U.S. ecosystems to continue to provide the
goods and services that society depends on, one needs to know the status
of the different types of natural and human-modified ecosystems and
how much of each major type of ecosystem remains in the country. Infor-
mation is also needed on what the committee calls the matrix that the
ecosystems are in, i.e., the physical aspects of the land. Thus the indica-
tors in this category include land cover and land use; nutrient runoff to
coastal waters (a measure of loss of an element of the matrix); and soil
quality as measured by soil organic matter.
Land Cover and Land Use
Land cover refers to the ecological status and physical structure of the
vegetation on the land surface (e.g., forests, grasslands, wetlands, crop-
lands) (Meyer and Turner 1994~. However, land cover depends in part
on land use, the way the land is used by people (e.g., a forest managed for
timber, a forest used to conserve biological diversity, industrial areas,
areas of human settlements) (Meyer and Turner 1994~. Because changes
in land use often (but not always) affect land cover, land use is itself an
indicator of land cover. In general, land cover can be detected and moni-
tored from remotely sensed imagery, but detection and classification of
land use usually requires on-the-ground measurements. Often, especially
in industrialized countries, information about land use can be obtained
from maps and other data sources at local and regional scales, but such
compilation is more labor-intensive and expensive than getting informa-
tion on land cover.
Data on current land cover and trends in those values are essential for
the derivation and use of most indicators the committee recommends.
OCR for page 68
68
ECOLOGICAL INDICATORS FOR THE NATION
Therefore, we present the land cover indicator first and recommend that
top priority be given to developing this indicator as rapidly as possible. A
reliable land use indicator, although more difficult to develop, is also of
great importance. The mathematical tools needed to assess land cover
patterns and how they change are detailed in Appendix B.
To assess this component of human impacts on the land, the commit-
tee recommends a land cover indicator to track the amount of land in each
of an array of land cover types, such as croplands, forestlands, wetlands,
and nature reserves.
A large fraction of the Earth's land surface is devoted to agriculture,
and so agroecosystems ecological systems that are intensively managed
for the production of food or fiber are essential components of any land
cover and land use indicators. Agricultural systems are managed for high
production, and typically are characterized by intensive nutrient and
pesticide inputs, fast growth/harvest cycles, and low plant and animal
diversity (Odum 1984, Matson et al. 1997~. Negative effects that may
accompany these patterns include increases in soil erosion, groundwater
contamination, eutrophication of lakes and rivers, and increased resis-
tance of pest and plant pathogens to the chemicals used to kill them
(Matson et al. 1997~. Nevertheless, intensively managed agroecosystems
usually contain parcels of unmanaged or lightly managed areas, such as
woodlots, fencerows, or riparian areas that can act both as refuges for
beneficial predators of insect pests (Letourneau 1997) and as reserves for
insect pests, weed seeds, plant pathogens, and alternate hosts of fungal
pathogens of crops, such as cedar apple rust or crown rust of oats
(Schumann 1991~.
Because high-value farmland is being lost to commercial, industrial,
and residential land uses (USDA 1997), the amount of agroecosystems is a
component of the land cover indicator.
Both land cover and land use indicators are extremely important.
Although this section focuses on land cover, because data are more readily
available at present, much of it is relevant to land use, which should also
soon become a usable indicator.
The land cover indicator can be applied to all environments, includ-
ing those in which the "land" is submerged. Therefore, the land cover
indicator recommended by the committee, includes rivers, wetlands, and
riparian zones as well as dry land. The land cover indicator records the
percentage of land in each of a variety of land cover categories. Every
time land cover is computed, the proportional representations should be
compared with those that existed at the previous recording time. To
provide a useful indication of the status of the nation's lands, many cat-
egories of land cover types must be recognized and the input data entered
and stored separately for each one. Because the proportion of land in
OCR for page 69
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
69
each land cover category changes relatively slowly, land cover needs to
be reported only once every five years, but its values need to be computed
annually as inputs to other indicators.
Supporting Models and Data Requirements. The conceptual model for
land cover is simple. Land cover measures the proportion of the land-
scape (and waterscape) occupied by each member of a set of land cover
types that must, by definition, add up to the total area of the nation. The
major decisions concern the number of land cover categories to recognize,
how to account for their spatial configurations, and how to accommodate
changes in the number and kinds of categories that are recognized.
Change in the Proportional representation of various land cover cate~o-
ries is the variable of interest. Visually representing proportional changes
for a large number of land cover categories is difficult, but pie or star
diagrams may serve that purpose.
More sophisticated analyses of changes in land cover categories are
also possible through the use of Markovian models (Appendix B). Those
models assemble the transition probabilities between categories into
matrices. From the matrices the steady-state distribution of categories
and the rate of approach to the steady state can be calculated. As a result,
one can obtain an indication of what the landscape will eventually look
like under selected policies, and how long it will take to reach that state.
Data Needs. Current capabilities of satellite imagery are sufficient for
identifying a large number of categories of land cover. Very complex
classification schemes are possible by combining imagery from several
sensors with scenes from different seasons. As pointed out in Chapter 2,
such techniques depend either on the Advanced Very High Resolution
Radiometer (AVHRR), because of its more frequent sampling, or on a
combination of the coarse spatial resolution of AVHRR and the finer reso-
lution of Landsat Thermatic Mapper (TM). The forthcoming map by the
U.S. Geological Survey (USGS) with a 100 meter resolution, based on
Landsat TM data, also may serve as the basis for establishing categories.
The condition of the nation's flowing waters is clearly an important
element of the land cover indicator. An aggregated measure of flow
patterns of the nation's rivers would be useful, but the complexities of
river-flow dynamics make such a measure computable and understand-
able only at the level of river basins. For the land cover indicator, a
simpler measure percent free-flowing (as explained below) captures
enough of the pattern to serve as a useful surrogate.
Dams, regardless of their purposes, change discharge patterns, in-
hibit movement of fishes, and impound sediments and their contained
organic carbon, nutrients, and contaminants (Poff et al. 1997~. Water is
OCR for page 70
70
ECOLOGICAL INDICATORS FOR THE NATION
retained in reservoirs to alter the pattern of peak flows and rates of flow
during storms. The timing of water release determines the timing and
magnitude of seasonal runoff maxima, which often differ from those in
free-flowing streams in the region. Therefore, for this reason it will be
desirable for the land cover indicator to include a measure of percent free-
flowing, or the length of free-flowing parts of streams and rivers divided
by their total length. The percentage can be computed for each river basin
and then aggregated into a single nationwide value.
Percent free-flowing can change in response to policy and manage-
ment decisions. Benke (1990) estimated that of the 5,200,000 km of streams
in the contiguous 48 states, only 42 streams flowed unimpeded for more
than 200 km. This is much less than 1 percent of the length of the nation's
rivers. Of these 42 rivers, only six, all of which are in the southeastern
United States, flow to the sea. Damming of rivers may continue, at least
for hydropower generation, with the greatest number of undeveloped
sites in the Pacific, mountain, and northeastern states. On the other hand,
sentiment is increasing for removing some dams. Data on the length of
large rivers impounded behind dams can be obtained using satellite mea-
surements, but information on dams on small rivers can be gathered only
by field surveys. However, because the number of dams built or destroyed
over a short period is a very small percentage of all dams, the percentage
free-flowing would change extremely slowly. Updating the data base
would be relatively simple once it had been compiled.
As mentioned previously, the U.S. Department of Agriculture's
National Resources Inventory (NRI) provides a comprehensive assess-
ment of the state and performance of natural and agricultural ecosystems
on 800,000 sites on private lands every five years. The NRI is a compre-
hensive sampling of land cover, land use, soil erosion, prime farmland,
wetlands, and other characteristics on nonfederal lands in the United
States. These data show that although soil erosion and agricultural wet-
lands loss have decreased, 6 million acres of prime farmland were con-
verted to nonagricultural uses between 1982 and 1992. NRI data can form
part of a system to confirm ground truth of land use categories identified
by satellite imagery.
The U.S. Geological Survey (USGS), through its Biological Resources
Division, and in collaboration with other federal agencies, is creating a
vegetation map for the United States at 1:100,000 scale from Landsat TM
data. The USGS is also more than halfway through a major effort to map
existing land cover for the United States, at approximately 100 m resolu-
tion, also using Landsat TM data. Several national- and continental-scale
data sets acquired by federal agencies over the past few years to pro-
mote land cover studies for the United States, the humid tropics, and
North American boreal forests are now available to the scientific com-
OCR for page 71
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
71
munity for analysis. At a global scale, the first complete 1 km resolution
global land-cover product was released by the International Geosphere
Biosphere Program (IGBP) in Summer 1997.
A land use indicator will need to distinguish among forms of a gen-
eral category of land use depending on the criteria by which they are
managed. For example, forest lands should be segregated into categories
such as primary forest, unmanaged second-growth forest, forest man-
aged primarily for timber production (referred to here as timberland),
recently burned forest, forest managed for biodiversity preservation (e.g.,
forests in Safe Harbor agreements), and forest reserves, as well as into
categories such as deciduous forest, boreal forest, and Pacific coast rain-
forest. Such categories can be aggregated into fewer categories as needed,
but to identify forests in which the human impact is being reduced, is not
changing, or is increasing, the disaggregated input data will be needed.
As an example, we discuss wetlands in some detail. Categories of
aquatic habitats include wetlands, fresh and saline lakes, reservoirs, rivers,
and bays. Most difficult to identify and monitor are wetlands water-
logged landscapes that are inhabited by distinctive biotas (NRC 1995b).
Wetlands cover 26 percent more area in the coterminous United States
than all other categories of aquatic habitat combined (Frayer 1991~. Their
biotic communities respond chiefly to the influence of hydrology, driven
by topography and climate, but also to nutrient supply related to geology
and soils. In many locations, because of anaerobic conditions, wetlands
accumulate substantial deposits of organic detritus. Wetlands are called
peatlands when accumulations of partly decomposed organic matter
reach a depth of 30 cm. Many diverse oxidation/reduction reactions
mediate elemental fluxes between the atmosphere and wetlands (Mitsch
and Gosselink 1993~. Wetlands are of major significance for the cycles of
carbon, nitrogen, and sulfur, and peatlands are a reservoir of at least 400
billion tons of carbon worldwide (Woodwell et al.1995~. Significant losses
of carbon from that reservoir are projected if the global climate warms
(Gorham 1991, 1995a). Therefore, monitoring the extent and status of
various categories of wetlands is extremely important.
Many physical, chemical, and biological criteria have been used to
categorize and monitor wetlands (Adamus and Brandt 1990, NRC 1995b),
and a land use indicator will need to recognize a substantial number of
wetland types. As in the case of terrestrial land use types, specific catego-
ries of wetlands should be separated according to the criteria by which
they are managed. A particularly important category is wetlands created
as part of mitigation settlements under Section 404 of the Clean Water Act
(Kusler and Kentula 1989), because created wetlands seldom fully replace
naturally functioning wetlands (Erwin 1991, Gorham 1995b, NRC 1995b,
Race and Fonseca 1996~. It is also important to recognize as a separate
OCR for page 72
72
ECOLOGICAL INDICATORS FOR THE NATION
category wetlands restored after years of tile drainage and crop produc-
tion under the government's Wetlands Reserve Program, which since
1990 has been administered by the Natural Resource Conservation Service
(formerly the Soil Conservation Service) under the Food and Security Act
of 1985.
Wetland types can be distinguished using data from the National
Wetland Inventory (NWI) carried out by the U.S. Fish and Wildlife Service
since the mid-1970s, mostly by means of 1:60,000 color-infrared photogra-
phy. By late 1991, 70 percent of the coterminous states and 22 percent of
Alaska had been mapped (NRC 1995b), the basic mapping units being the
set of wetland categories devised by Cowardin et al. (1979~. The NWI has
prepared a report on wetland status as of the mid-1980s, and on the trend
of losses since the mid-1970s (Dahl and Johnson 1991), based on a repre-
sentative sample of U.S. wetlands. Future reports are planned at 10 year
intervals. Other NWI products include reports to accompany each
1:100,000 scale wetland map, reports on state wetlands, and a wetland-
plant database (Mitsch and Gosselink 1993~. NWI maps are being digi-
tized for a computerized geographic information system that will facilitate
both analysis and display of the data. In only ten states, however, was the
process near completion in 1994 (NRC 1995b).
Reliability. Calculating changes in the proportions of land cover in the
United States with fully replicable techniques will require integrating
remotely sensed information with data from statistically based, in situ
sampling programs. A growing number of examples exist in which such
information has been collected on regional scales, especially using remote
sensing. Of particular interest to the scientific community are studies of
tropical deforestation (Skole and Tucker 1993; Laporte et al. 1995; lanetos
et al. 1997 [GOFC]), in which changes in proportions of land cover types
have been calculated and full transition-probability matrices have been
derived.
Temporal and Spatial Variability. The land cover indicator itself does
not retain the spatial information in the underlying data. However, if the
underlying data are archived with all their spatial information intact, then
more complex, spatially explicit measures of land cover changes can be
computed (Appendix B). These measures are likely to be of substantial
regional and local interest.
Many natural processes cause changes in land cover, but typically
they result in relatively small annual changes. Appreciable changes typi-
cally occur only over decades. However, some anthropogenic changes,
such as clearing forests for rangeland or farmland, and large fires, happen
OCR for page 73
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
73
quickly. Therefore, land cover needs to be computed annually but it need
not be formally reported more often than once every five years.
Statistical Properties. The statistical properties of land cover are clearly
a function of the reliability of identification of land cover types from
remote sensing and of the statistics of the in-situ sampling program.
Because the use of remote sensing to quantify land cover change is an
active area of research and application within the scientific community
and operational agencies, the statistical properties of land cover should be
clarified in the near future.
The classification of land cover types in the land cover indicator must
be sufficiently comprehensive for all the additional indicators that are
derived from it. Classification issues can be addressed in two ways. One
would be to determine the number of classes required by the most
demanding indicator and use that classification in all input data. This
method would force the unification of classification schemes for all indi-
cators. The other would be to have a more flexible, hierarchical classifica-
tion scheme that would allow the unfolding of additional classes of land
cover from a smaller number of aggregated classes from the same under-
lying data. The latter approach has been used by the IGBP (IGBP 1992b;
Defries and Townshend 1994; Townshend et al. 1994) in its global 1 km
land cover product. A flexible, hierarchical classification system would
best serve the needs of a variety of environmental indicators.
The rate of land cover change determines the most appropriate sam-
pling intervals, but there are also practical limitations on sampling fre-
quencies. For example, analyses of satellite data are constrained by both
the technical features of the satellite itself and by the ability of investiga-
tors to handle and interpret the very large volume of data. In addition,
the return time for sampling NRI plots or CFI plots is largely determined
by the availability of field crews. However, the mean resampling time for
CFI plots is approximately 10 years, which compares favorably with theo-
retically determined appropriate sampling frequencies for forest produc-
tivity (Appendix A).
Scientists who use remote sensing have addressed issues of sampling
intervals at some length (Skole et al. 1997; IGBP 1992b; Justice and
Townshend 1988~. As a rule of thumb, they have suggested that five-year
intervals of complete remote-sensing surveys at national, continental, and
global scales are generally adequate. Complete surveys could be inter-
spersed with annual stratified samples to detect rapid changes without
overwhelming the capacities of investigators and systems to perform the
analyses.
Necessary Skills. The collection of remotely sensed data obviously
OCR for page 74
74
ECOLOGICAL INDICATORS FOR THE NATION
demands a high degree of familiarity and experience with the instru-
ments and data-handling capabilities. However, technological barriers to
handling remotely sensed data are shrinking as computer technology
improves and costs decline. The greatest barriers to developing and using
the land cover indicator are probably conceptual: developing the detailed
techniques for classifying, combining, and interpreting changes in land
cover categories by means of which remote-sensing and in situ data are
evaluated.
Data Quality Control, Archiving, and Access. The input data for land
cover should be archived at the most highly resolved and disaggregated
levels, and the techniques used to generate land cover classes need to be
described clearly and documented. Only in this way will the land cover
indicator be replicable and real changes detectable. Sources of error in
both measurements and classifications should also be clearly defined and
documented. Comparing maps derived at different times, although fea-
sible, is not a good method of documenting changes in land cover because
it confounds measurement errors, interpretation errors, and cartographic
errors in ways that would be extremely difficult to quantify. It is more
straightforward and desirable to detect change in the underlying data
themselves, use those differences for quantitative analyses, and then
derive maps for presentation purposes.
Robustness. Although tremendous strides have been made in recent
years, the use of remotely sensed information for ecological analyses is
still in its infancy. For many years, the technical challenges of simply
handling and processing the data were so large that they inhibited the use
of the systems by all but the most sophisticated laboratories. Rapid
improvements in cost and performance of computer hardware and soft-
ware are removing many of these technical impediments, but other issues
remain. The most important ones include the care, maintenance, and
accessibility of data archives, and the intercalibration of the remote-
sensing instruments themselves.
The land cover indicator is likely to be robust to reasonable sources of
interference, especially if the original data are archived carefully. How-
ever, the time series of measurements can be compromised by technologi-
cal changes unless sufficient care is taken to ensure that new instruments
are cross-calibrated, and that the calibration of instruments is maintained
and monitored carefully over their lifetimes. Achieving calibration precise
enough for these quantitative scientific measurements is difficult, but it
can be achieved, as the Landsat data record shows. For data sets that last
longer than the lifetime of any one instrument, successive instruments
must be flown and cross-calibrated for a period of overlap. In this way,
OCR for page 105
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
105
the past five decades, increased demand, trends in dietary preferences,
and the development of new technologies have led to greatly expanded
use of chemical fertilizers, pesticides, and water for irrigation and live-
stock production. Research to find ways to reduce the deleterious effects
of these practices on surface and groundwater quality and on soils is
leading to policies to protect soil and water while sustaining the profit-
able production of agricultural goods, but considerable improvements
can still be made (NRC 1993~.
Nutrient cycles differ dramatically between agricultural ecosystems
and the natural ecosystems they replaced. The most significant recent
change involves massive movements of nutrients across landscapes. For
example, fertilizers are transported to crop-producing areas in the spring,
grain is transported to animal-producing areas in the fall, and animal
manures become wastes or excess fertilizer because the rate of production
exceeds local needs and the cost of transport make redistribution eco-
nomically infeasible (Magdoff et al. 1997~.
More land, fertilizer, pesticides, and irrigation water are needed to
support animal production, and the environmental impacts are greater
than if dietary choices demanded less animal protein. The importance of
animal protein in human diets, which is consumer-driven, is an important
factor in agriculture's impacts on the biosphere. Nations, such as the
United States, with extensive concentrated animal production facilities
generate large amounts of excess nutrients because nutrient use in animal
production is much less efficient than in producing crops (van der Ploeg
et al. 1997~.
The NRC (1993) analyzed agricultural practices and impacts to iden-
tify opportunities that held the most promise for "improving the environ-
mental performance of farming systems while maintaining profitability."
The broad recommendations of that report were the following:
1. Conserve and enhance soil quality as a fundamental first step to
environmental improvement.
systems.
2. Increase nutrient, pesticide, and irrigation efficiencies in farming
3. Increase the resistance of farming systems to erosion and runoff.
4. Make greater use of field and landscape buffer zones.
Following this framework, the committee evaluated and recommends
national-level indicators of nutrient-use efficiency and balance.
The high productivity of most modern agriculture depends on added
nutrients. In most agroecosystems, more nutrients are added to the sys-
tem than are extracted from it in harvested products; and the imbalance is
OCR for page 106
106
ECOLOGICAL INDICATORS FOR THE NATION
far greater for animal production than for crop production. These excess
nutrients find their way into the soil, the atmosphere, and water.
We define the proportion of added nutrients removed in products as
nutrient-use efficiency. Because the efficiency with which nutrients espe-
cially N and P are used in the production of crops and animal products
is of great economic and environmental significance, it is important to
monitor changes in inputs and outputs from agricultural lands. Losses of
agricultural chemicals account for a major share of nonpoint-source N
and P pollution of ground and surface waters (NRC 1993~. Because point-
source control of N and P inputs to surface and groundwaters has been
easier to achieve, nonpoint sources account for an increasing share of the
total inputs (Sharpley and Meyer 1994~. The increasing demand for agri-
cultural products will generate powerful pressures for increased agricul-
tural chemical use.
N export from agroecosystems is known to adversely affect drinking-
water supplies. Nitrate (NO3) in drinking water can be acutely toxic, and
it can cause methemoglobinemia in infants (Spaulding and Exner 1993~.
The maximum contaminant level has been set at 10 mg NO3-N LO for
drinking water. Regions of irrigated agriculture such as the wheat belt
and California's Central Valley have the highest incidence of elevated
NO3 levels, but many other such areas are scattered about the United
States (Spaulding and Exner 1993, Kolpin 1997, Lichtenberg and Shapiro
1997~. N also contributes to eutrophication of aquatic and estuarine
systems (Spaulding and Exner 1993~.
Local, regional, and national annual N budgets for cropland and agri-
cultural watersheds indicate that more N is added to croplands (manure
N plus fertilizer N plus N fixed by legumes) than is removed in crops.
The amount of N not transferred to crops varies widely as a function of
site conditions and management practices. Site conditions that control N
transformations vary among regions, along topographic gradients, and
with different cropping practices. Also gaseous losses from and additions
to the soil are difficult to measure; and cropping practices other than
fertilization can release stored soil N at substantial rates (Keeney and
DeLuca 1993, David et al. 1997~. Therefore it is difficult to rigorously
determine the fate of excess fertilizer and manure N. and difficult to relate
the excesses directly to elevated ground- and surface-water N levels
(Keeney and DeLuca 1993, David et al. 1997, Kolpin 1997~.
Gaseous losses of N (as N2O and NH3) have other influences. N2O is
a significant greenhouse gas. NH3, volatilized from fertilizers and animal
manure, is eventually deposited as NH4. After being taken up by plants,
atmospherically deposited NH4 acidifies the soil and, in some regions
(e.g., the montane watersheds of the northeastern United States), contrib-
OCR for page 107
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
107
utes substantially to the N and H+ loads that must be assimilated by
sensitive landscapes (Iohnson and Lindberg 1992, Vitousek et al. 1997~.
Soil phosphorus lost from agricultural systems to watersheds acceler-
ates eutrophication of lakes and streams. Productivity and algal blooms
in lakes and streams are promoted by elevated inputs of dissolved
inorganic P. and by labile P ("algal-available P") bound to sediments or in
labile organic combinations. In general, P is less mobile than N. because it
adheres strongly to soil constituents. P applied in excess of crop uptake is
retained to a considerable extent in nonsandy mineral soils. Quantita-
tively important leaching losses of P through the soil to ground and sur-
face waters are limited to areas of sandy soils, organic soils, and cases of
extreme P loading. Surface runoff and tile-drain effluent from fertilized
cropland, pastures, and animal-feeding operations and the accompany-
ing suspended sediment are thus the most important vectors for P deliv-
ery to surface waters. The importance of each source varies according to
region, soil conditions, and management practices.
As concern about environmental impacts of agricultural nutrient
losses has grown over the past decade, so has research on how to manage
agricultural nutrient use to minimize loss, while maintaining productivity
and profitability. Because nutrient loss from agricultural systems is a site-
specific problem (NRC 1993, Harris et al. 1995), site- and practice-specific
mitigation measures are required. Many efforts are under way to gain the
understanding necessary to balance environmental and productivity
needs (see reviews by NRC 1993, Harris et al. 1995, Daniel et al. 1998,
Sharpley et al. 1996~.
Changes in nutrient-use efficiency in agricultural systems and nutri-
ent losses from these systems have been driven by the increased availabil-
ity of chemical fertilizer since World War II; by the availability of trans-
portation for fertilizer, feed, and agricultural products; and by increases
in meat consumption, which has led to the growth of specialized animal-
production systems. The trend toward greater livestock production in
the Western world during the latter half of this century is a major con-
tributor to overall loss rates of nutrients used in agriculture, because the
nutrients in manure are much less efficiently incorporated into animal
products than into crops (e.g., van der Ploeg et al. 1997~. This situation is
magnified in small meat-producing countries such as the Netherlands,
where animal feeds grown on five to seven times the Dutch agricultural
land area are imported. This large import of nutrients is driving country-
wide nutrient enrichment as the manure is applied to Dutch agricultural
land and excess nutrients make their way into ground and surface waters
(Van der Molen et al. 1998~.
OCR for page 108
108
ECOLOGICAL INDICATORS FOR THE NATION
The Indicators. Nutrient leakage is an inherent property of current
agricultural activities (see review by Magdoff et al. 1997) and will remain
so for the foreseeable future. Because the demand for agricultural prod-
ucts will increase as the human population and economic activity increase,
the only way to reduce losses of nutrients to ground and surface waters
(and to the atmosphere in the case of gaseous N losses) is to develop and
implement site-specific and practice-specific management techniques that
improve the efficiency of nutrient use in crop-producing areas, and that
limit the leaching and runoff of nutrients from animal-producing opera-
tions. Considerable agricultural research is being conducted on this
matter; NRC (1993) covers useful management alternatives. If animal
products become less important in people's diets, overall agricultural
nutrient losses will decrease (van der Ploeg et al. 1997~. However, even if
substantial improvements in nutrient-use efficiency occur, overall losses
from agricultural lands will increase if demands for agricultural products
outpace improvements in nutrient-use efficiency. Accordingly, it is use-
ful to have indicators of both the overall efficiency of nutrient use in the
production of crops and animal products and the overall nutrient bal-
ance. Efficiency indicators are ratios or percentages that can increase or
decrease with time. Balance indicators record the excess of nutrients
applied to agricultural land over nutrients removed in harvested prod-
ucts. Indicators of nutrient-use efficiency and overall balance can be
created for use at virtually any scale from farm fields to countries.
Nutrient-Use Efficiency. N and P use-efficiency indicators are useful
for crops or industries, for counties, and for watersheds in which ground
or surface waters are perceived to be adversely affected. These indicators
can be used in testing trends in the effectiveness of management pro-
grams locally, regionally, nationally, or on a crop-specific basis. Aggre-
gated data at a national scale have been useful for detecting and under-
standing trends in N-use efficiency in Germany (van der Ploeg et al.1997~.
N and P budgets for cropland are often very hard to construct given the
difficulties in tracking nutrients applied in excess of crop uptake, and
especially in determining gaseous inputs and outputs of N. Different
authors have used different indicators to represent fertilizer-use efficiency,
and several assumptions are usually made in estimating N budgets for
croplands (e.g., lenkinson and Smith 1988, Black 1993, NRC 1993~. We
have adapted the approach and budget methods used by the NRC (1993)
and van der Ploeg et al. (1997) in constructing the following indicators to
monitor trends in agricultural nutrient-use efficiency at a national scale.
For cropland:
OCR for page 109
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
(1) Nitrogen-use efficiency Nc =
N removed in crop biomass (mass y-l)
chemical fertilizer N applied + animal manure N applied
+ N fixed by legumes (mass ye)
(2) Phosphorus-use efficiency Pc =
P removed in crop biomass (mass y-l)
chemical fertilizer P applied + animal manure P applied (mass ye)
109
Data inputs for N and P removed in crops are crop yields by type,
dry-matter percentages, and biomass N and P content. Fertilizer sales by
county (e.g., EPA 1990, Smith et al. 1997), county animal censuses (e.g.,
U.S. Bureau of Census 1987), and per-animal nutrient excretion rates (U.S.
Soil Conservation Service 1992) can be used as estimates of the terms in
the equations. Legume N fixation requires assumptions, but they are
straightforward and useful if they are uniformly applied (NRC 1993~.
Because the indicators are percentages, they take values ranging from O to
100 percent, higher values indicating greater efficiency.
Depending on availability of data, these indicators could be calcu-
lated annually and should be able to detect changes in nutrient-use effi-
ciency on a decadal scale. For example, in the former West Germany,
crop N-use efficiency, calculated as shown above (without N fixed by
legumes), decreased from about 100 percent in 1964 to a low of 72 percent
in 1984, then increased to about 81 percent in 1990 (van der Ploeg et al.
1997~. Using NRC (1993) data for 1987 (NRC's Table 6-3, medium N-
fixation scenario), N-use efficiency for U.S. cropland was 59 percent and
for P 31 percent. Because such large quantities of nutrients in excess of
those harvested are applied to U.S. agroecosystems, the potential for
improvements in nutrient-use efficiency is great (NRC 1993~.
Nutrient-use efficiency indicators should provide integrated mea-
sures of how well management strategies are working. Application of the
indicators at smaller scales would provide opportunities to target specific
geographic areas or crop-production systems. A rough but potentially
useful measure of the efficiency of N and P use in agriculture on a national
scale can be approximated by the equation
(3) Na =
N content of crops produced for human consumption
+ N content of animal products produced (mass N ye)
Chemical N fertilizer applied to cropland
+ N fixed by legumes (mass N ye)
OCR for page 110
110
(4) Pa =
ECOLOGICAL INDICATORS FOR THE NATION
P content of crops produced for human consumption
+ P content of animal products produced (mass p y-l)
Chemical P fertilizer applied to cropland (mass P ye)
These indicators could be applied to smaller scales such as states,
counties, or watersheds, but at these smaller scales the indicators would
need to be modified to account for imported (or exported) nutrients in
crops produced for animal feed. The large decrease in N-use efficiency
for agriculture as a whole (i.e., animal and crop production) from 1951 (77
percent) to 1980 (27.2 percent) in West Germany resulted from increasing
rates of applications of chemical fertilizers, the rise of livestock produc-
tion (a much less efficient user of nutrients than crop production), and an
attendant 10-fold increase in imported N in feed (van der Ploeg et al.
1997).
Nutrient Balance. The same data can be used to compute indicators of
overall nutrient balance. Changes in these indicators reflect the combined
effects of changes in nutrient-use efficiency and in the quantity of agricul-
tural products. Tables 4.3 and 4.4 show the mass-balance approach used
by the NRC (1993) for N and P applied to cropland. Such budgets require
several assumptions, but they are straightforward. For nitrogen, the indi-
cator would be N fertilizer applied plus recoverable N in animal waste
(manure) applied plus N fixed by legumes minus N removed in harvested
crops (assuming steady-state nutrient pools in crop residues). A similar
indicator could be used for P. as described for the nutrient-use efficiency
indicator. These national-level indicators would provide important input
for understanding changes in water quality and other aspects of nutrient
cycling. The units of the indicators are Mg/year for the area of interest.
Nutrient-balance indicators could also be used at local and regional
scales. States and counties conduct censuses of farm animals, and methods
are available for estimating per capita manure production by poultry and
livestock (NRC 1993). The indicator would not be affected by variations
in the distances between the animal production facilities and the crop-
lands that support them. The indicator would have smaller values in
areas of crop-only production and higher values where animal produc-
tion is concentrated. Such indicators would help states and counties
evaluate their agricultural practices in light of potential nutrient losses to
surface water and groundwater.
OCR for page 111
111
v)
o
o
v)
u
v)
o
v)
H
bC
o
5-
V)
V)
. - O
V) ~
~U
C ~
~ O
· -
5-
U
cr~
O .0
·bC t~
X
~ ._'
E~
U
O > ~
o
E~
CD
O CD
5-
o
E~
CD
O CD
5-
O ~
~ .N
50- ~
5 -
~0
~ .
O O O O O O O
O O O O O O O
O O O O O O O
ON ~ ~ ~ O ~ ON C~ ON ~ O
p ~ ~ ~o Lr) ~ Lr) 00 ~ ~1 ~1
~ Lr) ~ 00 ~ ~ ~
O O O O O O O
O O O O O O O
O O O O O O O
C~ CO O O 0 00 0
00 t3N 00 CO CO ~ ~)
Lr) ~ ~ O Lr) Lr)
~ Lr) ~i
O O O O
O O O O
O O O O
O
00 0
Lr) Lr)
O O O O O O O O O O
O O O O O O O O O O
C~1 0 00 0 0 0 0 0 0 00
~ ~ ~ ~ ' ~ ~ ~ ~ ~
O C~ CO 00 0 Lr) C~ ON 00 00
O ~ ~ C~ O O C~ Lr) oo
~ Ct) C~l~
O O O
O O O
O O O
O O O
O O O
O O O
O ~
~ ~ O
00 - `
O O O O O O
O O O O O O
O O O O O O
O ~ O ~ ~ 00
~ ~ ~) O 00 t3N
00 ~ ~ Lr)
O O O O
O O O O
O O O O
O O O O
00 t3N
~ ~ CO ~
O O O O O O
O O O O O O
C~l O 00 0 0 0 0 0 0 ~
~ ~ ~ ~ ' ~ ~ ~ ~ ~
O C~ CO 00 0 Lr) C~ ON 00 00
O ~ ~ C~ O O C~ Lr) oo
~ Ct) C~l~ ~ ~ ~ ~
o
o
o
o
~N
00
c~i
o
o
o
o
o
o
O
O
O
O
O
O
o
o
o
o
~N
00
O O O O O O O O O O O
O O O O O O O O O O O
O O O O O O O O O O O
~ Lr) CO ~ O C~ O C~ ~ ~ O
00 t3N ~ 00 Lr) Lr) C~l 00 Lr) ~ ~
`` Lr) O~ ~ ~ 00
~1
O O O
O O O
O O ~
00
O ~
O O O O
O O O O
O ~ O O
O ~ ~ ~
~ Lr) Lr) oo
O O O O O O O O O
O O O O O O O O O
O O O O O O O O O
~ ~h ~ oo o oo o o ~
Lr) ~ o oo ~ ~ ~ ~ Lr)
Lr) ~ ~ `` ~ Lr) ~ Lr)
,~
cn ~ ~
o ~ 'o ~ ~ ~ ~ .=
~ ~ ~ ~ o ~ o ~ o
o o
o o
o o
~ o
o o
o o
o o
ON O
00 ON
~N
co
cn
u ~
·_1
u ~
z
. .
o
v,
OCR for page 112
112
oo
V)
o
o
V)
u
V)
o
V)
H
V)
o
V)
o
o
V)
V)
o
o
.
V)
~U
5-
˘ ~
E~ ~
U
-
o
E~
O > ~
CD
O CD
5- ~
o
E~
CD
O CD
5-
O ~
5-
~0
~ .
O O O
O O O
O O O
~ Lr)
00 ~ ~
O O O
O O O
O ~ 00
Lr)
Lr)
O O O O
O O O O
0 ~1 0 0
C~
00 00 ~
O O O O
O O O O
O C~l O
~ Lr) ON ~
ON ~ ~ 00
Lr) ~
O O O O O O O O O O
O Ct) ~ O O O O O O Lr)
Lr) - `
ON ~ ~ C~ 0 00 ~ ~ 00
~ ~ ~ Lr) ~ ~
o o o o o o o o o o
o o o o o o o o o o
co Lr) oo o o ~ o ~ Lr
oo o ~ oo ~ ~ ~ c~ co ~
Lr) ~ ~ ~ Lr)
o o o o o o o o o o
o o o o o o o o o o
o o o o o o o o o o
ON Lr) O Lr) O ~ Lr) 00 ~h ~
co oo o ~ Lr) Lr) o ~ Lr) oo
~ ~ ~ Lr) ~) ~ ~ ~ ~ ~
o
o
o
o
o
c~i
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
o
Lr)
o o o o o o o o o o o
o ~ o o o o o o Lr) o
ON ~ O ~ 00 CO Lr) ~ O
ON CO ~ C~ O 00 ~ ~ 00 C~
co
~ c~
o o o o o o o o o o o
o o o o o o o o o o o
Lr) o ~ o ~ ~ ~ o
C~ C~ 00 Lr) C~ O ON CO ~ Lr)
Lr) Lr) Lr) Lr)
o o o o
o o o o
o o o o
Lr)
Lr
~ co
o o o
o o o
o o o
o o o
o o o
o o o
~ ~ o
oo ~ ~
~ ~ Lr)
co co
.= .= 'o
·=
.=
z
. .
o
v,
OCR for page 113
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
RESEARCH NEEDS
113
Although the committee's recommended indicators are based on solid
theoretical justification and extensive data, the precision and interpreta-
tion of the indicators should be improved by additional research and
development. Moreover, future research may suggest new indicators
that may be better than existing indicators or may be usefully added to
the set of regularly reported indicators. More research is needed to iden-
tify organisms and biological processes that are especially sensitive to
stresses and perturbations and to determine more accurately the temporal
behavior of indicators. To address problems associated with spatial scale
in indicator performance, it is important to test new indicators carefully
in pilot programs before implementing them nationally (NRC 1995a). For
the recommended indicators that are new, especially the ones that mea-
sure land cover, land use, and species diversity, further work is needed
on how best to operationalize the indicators and to help identify future
research plans. This work, which should include one or more workshops,
should include academic scientists, practitioners, agency scientists, and
other interested parties.
Temporal Behavior of Ecological Indicators
Knowing temporal variations in indicator values is important for
interpreting monitored data. Because very few monitoring efforts exceed
a decade, and many for no more than a few years, other methods need to
be used to provide a record long enough to capture normal variations in
the proposed indicator values, as well as to investigate surprise variations.
The source of much of the variation in indicators may be found at the
interface between population and ecosystem processes. Population cycles
are well studied, but how population cycles affect temporal patterns of
species diversity, carbon storage and flow, and nutrient runoff is unknown.
Experimental and theoretical investigations into the relationship between
current population cycles and related ecosystem processes will provide
the mechanistic understanding needed to improve predictions and inter-
pret the causes of indicator behavior.
In addition, research is needed on applications of the mathematical
techniques of spectral analysis (Platt and Denman 1975) and wavelet
analysis (Wickerhauser 1994) to time series of model outputs and to
patterns in the paleorecord. Spectral analysis identifies the periods and
amplitudes of fluctuations in a time series of data. An example of how
this method can assist in the design of sampling systems is provided in
Appendix A. Wavelet analysis identifies periods in which there is a
sudden change in system behavior. These periods may correspond to
OCR for page 114
4
ECOLOGICAL INDICATORS FOR THE NATION
"surprises." These mathematical techniques have been developed for
analysis of digital signals and other relatively clean data sets free from
stochastic effects. Ecological data, in contrast, are often incomplete be-
cause of gaps in the record. In addition, in ecological research, stochastic
noise often obscures the detection of fluctuations of long periods or low
amplitudes, and the detection of sudden changes in the data spectrum.
Research is required on adapting these mathematical techniques to the
more problematic data sets typical of environmental monitoring and the
paleorecord.
Keystone Species
Species whose removal results in a large effect on some functional
property of an ecosystem called keystone species are good targets for
indicators. Research is needed to develop a predictive theory of keystone
species and to identify tolerant species. Traditionally, ecologists have
looked for and identified keystone species by their effects on the species
richness and composition of the community in which they live. Keystone
species also may have major effects on primary and secondary productiv-
ity and nutrient cycling. Unfortunately, although a number of keystone
species have been identified, no predictive theory of keystone species yet
exists.
Tolerant Species and Assessing the Regional Importance
of Local Sites
Evaluating places using only indicators that focus on each site sepa-
rately would not lead to decisions that would sustain the greatest amount
of species diversity. A hypothetical example suffices to explain why.
Suppose a company intends to build a factory but it does not care on
which of two equal-sized natural areas it builds. For purposes of preserv-
ing biological diversity, it might appear obvious that the site with the
fewest species is preferable for the factory.
The issue is more complicated than that because one needs to know if
the diversity on the richer site is sustainable (as has been taken into
account for measuring species densities), and also the extent to which the
site is redundant in the system of reserves that maintains S for the region
as a whole. If the richer site has virtually the same list of species as
another site and the species appear to be sustainable at the other site, the
value of the rich site is lower. Conversely, if the alternate site for the
factory, although relatively poor in diversity, harbors species found
nowhere else in the region, or nowhere else in the world, it has higher
biodiversity value than the richer site. The lessons of this simple example
OCR for page 115
INDICATORS FOR NATIONAL ECOLOGICAL ASSESSMENTS
115
can be used to suggest ways to evaluate the contribution of a site, Ri, to
regional diversity.
To achieve this, for example, separate Si into two components. The
species not found in sustainable condition elsewhere are Ri. The defini-
tion of "elsewhere" may vary depending on the objective of the group
doing the evaluation. In other words, elsewhere means "anywhere else in
the area whose diversity one is trying to protect." In this context, a species
whose range is so fragmented that its survival depends on a number of
sites should be counted as a full species in the Ri of each site that forms a
necessary part of its support range.
To use Ri one must be able to measure sustainability. Sustainability is
increased by avoiding overload in Di, but understanding sustainability
fully also requires knowledge of the population dynamics, meta-
population dynamics, and species interactions of the species contributing
to Ri. Because obtaining all this knowledge is difficult and laborious, it
cannot be done for all the species in a place. A reasonably accurate esti-
mate of Ri can probably be obtained by focusing investigations on a few,
charismatic taxa, such as birds, fishes, mammals, butterflies, wildflowers,
and trees, instead of a random scattering of species in many taxa. How-
ever, considerable research will be needed to generate the data necessary
for computing measures of sustainability.
As human uses take more of a region's area, many sites will shrink or
disappear. As a result, the list of species restricted to a critical few sites
and the average value of Ri will both climb. A place that lacks importance
today may become important in the future. Thus, Ri must be reassessed
periodically, probably once each decade. Ri is not an indicator but com-
puting its values is an important part of an overall assessment of the
performance of a system of reserves, so that biodiversity protection is
achieved most efficiently.
Representative terms from entire chapter:
species diversity
