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OCR for page 5944
Proc. Natl. Acad. Sci. USA
Vol. 96, pp. 5944-5951, May 1999
Colloquium Paper
This paper was presented at the National Academy of Sciences colloquium "Plants and Population: Is There Time?"
held December 5-6, 1998, at the Arnold and Mabel Beckman Center in Irvine, CA.
Ecological approaches and the development of "truly integrated
pest management
MATTHEW B. THOMAS*
~ ..
Leverhulme Unit for Population Biology and Biological Control, Natural Environment Research Council Centre for Population Biology and CABI Bioscience,
Silwood Park, Ascot, Berks., SL5 7PY, United Kingdom
ABSTRACT Recent predictions of growth in human pop-
ulations and food supply suggest that there will be a need to
substantially increase food production in the near future. One
possible approach to meeting this demand, at least in part, is
the control of pests and diseases, which currently cause a
30-40% loss in available crop production. In recent years,
strategies for controlling pests and diseases have tended to
focus on short-term, single-technology interventions, partic-
ularly chemical pesticides. This model frequently applies even
where so-called integrated pest management strategies are
used because in reality, these often are dominated by single
technologies (e.g., biocontrol, host plant resistance, or bio-
pesticides) that are used as replacements for chemicals. Very
little attention is given to the interaction or compatibility of
the different technologies used. Unfortunately, evidence sug-
gests that such approaches rarely yield satisfactory results
and are unlikely to provide sustainable pest control solutions
for the future. Drawing on two case histories, this paper
demonstrates that by increasing our basic understanding of
how individual pest control technologies act and interact, new
opportunities for improving pest control can be revealed. This
approach stresses the need to break away from the existing
single-technology, pesticide-dominated paradigm and to
adopt a more ecological approach built around a fundamental
understanding of population biology at the local farm level
and the true integration of renewable technologies such as
host plant resistance and natural biological control, which are
available to even the most resource-poor farmers.
The continuing growth of the human population will, for the
foreseeable future, require that we find new ways to increase
food production. Reducing losses caused by pests and diseases
is one possible approach. Current estimates put global losses
caused by pests (insects, nematodes, diseases, and weeds) at
US$ 300 billion annually (1), which equals around 30-40% of
potential global food, fiber, and feed production (1) with
substantially higher proportions in particular developing coun-
tries. Moreover, these estimates generally concern losses to
crop production only. If losses caused by postharvest pests and
diseases are added, then figures approaching 60-70% may be
more typical for the developing world (2~.
Over the past 50 years, application of chemical pesticides has
come to be the dominant form of pest control in developed,
and increasingly in developing, countries (1~. Future ap-
proaches to reducing the damage caused by pests are, however,
likely to be very different from those that predominate today.
Indeed, while pests have been a chronic problem in agriculture
since its beginning, many of the serious pest problems in the
developing world today are the direct consequence of actions
taken to improve crop production (3~. These pest problems
associated with agricultural intensification particularly apply
PNAS is available online at www.pnas.org.
to insects. In recent decades, the dependence on chemical
insecticides has led in some crop systems to a high frequency
of insecticide resistance now recorded in more than 500
insect species worldwide (4~- pest resurgence, acute and
chronic health problems, environmental pollution, and uneco-
nomic crop production. All of these problems are particularly
severe in developing countries, where pesticide use is poorly
regulated and farmers often lack appropriate information or
training. For many of these farmers, pesticide use is becoming
a rising and unreliable component of the cost of crop produc-
tion.
In this environment, the concept of integrated pest man-
agement (IPM) is becoming more and more popular among
farmers, researchers, and policy makers. In IPM, a range of
methods are used for pest control. IPM seeks to minimize
reliance on pesticides by emphasizing the contribution of other
control methods, including biological control, host-plant re-
sistance breeding, and cultural techniques. Further, because
IPM places less emphasis on expensive pesticides and more on
renewable technologies available to the resource-poor farmer,
such as biological control and host plant resistance, it is more
possible for these farmers to share the benefits of this ap-
proach.
All of this sounds very encouraging and suggests a clear role
for IPM in crop production in the future. In practice, however,
IPM means many different things to many different people (5),
and the way it is actually conducted in the majority of crop
systems today still places emphasis on single technologies such
as the use of pesticides, biocontrol, or host plant resistance and
rarely considers the interactions among them (6~. The conse-
quence of this single technology focus and the search for
"magic bullets" is that pest control is often only partly effective
and, because of problems such as environmental damage and
development of resistance, the strategies themselves are rarely
sustainable. Furthermore, the implementation of these tech-
nologies traditionally has followed a top-down approach, which
is contrary to the concepts of user-orientation and empower-
ment that now are considered central to the development of
sustainable IPM (5~.
The aim of this paper is to highlight how the adoption of a
more ecological approach, in which the actions and interac-
tions of the component technologies are fully understood
within the context of the local agroecosystem, could lead to the
development of more effective and sustainable "truly integrat-
ed" pest management. To illustrate this argument I review
some recent ecological work from two different areas of pest
management. The first concerns the population dynamic basis
for integrating host plant resistance breeding and biological
control. The second is the application of ecology to microbial
Abbreviation: IPM, integrated pest management.
*To whom reprint requests should be addressed. e-mail: m.thomas@
cabi.org.
5944
OCR for page 5945
Colloquium Paper: Thomas
control and the practical development of biopesticides. The
linking theme between these studies is the use of ecological
principles to improve prediction and interpretation of the
action of individual technologies and through this, identifying
new opportunities for IPM.
Integrating Biological Control and Host Plant Resistance
for Control of Insect Pests
Current Status. As alluded to above, although both biolog-
ical control and host plant resistance are thought of today as
key components of IPM, their development in recent years has
taken little account of their potential for integration in the
control of particular insect pests. This situation is unfortunate
given that for many key pest species, neither plant resistance
or biological control has provided us with a satisfactory,
sustainable control solution (6~.
In a recent review, Waage and I (6) showed that the action
of natural enemies can substantially modify the effectiveness
and the durability of host plant resistance. It was found that
partial resistance and partially effective biocontrol can be
combined to give additive or synergistic reductions in pest
density. Although neither strategy acting in isolation may be
completely successful, opportunities exist for improving con-
trol through their combined, integrated use. However, the
study also revealed that plant resistance and biocontrol can
interact negatively with, under some conditions, plant resis-
tance causing complete disruption of natural enemy activity.
The exact nature of the interaction depends on the specific
relationship between natural enemy and herbivore and the
mode of action of the host plant resistance and its effects on
herbivore life history. What this means in practice is that to
fully explore these tritrophic (plant-herbivore-natural enemy)
interactions and substantiate the effects and compatibility of
host plant resistance and biocontrol, a fundamental under-
standing of population dynamics is required. This argument is
illustrated below by using a simple population model. Here the
focus is on the biological insights gained from the model so the
model itself is described only verbally. Those readers inter-
ested in further details of the model and its derivations are
referred to ref. 6. In addition, it should be noted that the model
describes a basic scenario with an idealized crop, pest, and
generalist natural enemies and does not itself attempt to
encompass all the features of crop-pest-enemy interactions
(such as local spatial dynamics and intergenerational dynam-
ics), which may influence the ultimate outcome of the tritro-
phic interaction. Instead it provides a limiting case for a subset
of possible interactions and importantly examines and inter-
prets their effects in a population dynamic context.
Population Dynamics of Plant Resistance-Biocontrol In-
teractions. The model explores how the population dynamic
effects of the first (i.e., plant resistance traits) and third (i.e.,
natural enemies) trophic levels combine to determine pest
population growth rate. The model system is an idealized
annual crop attacked by a pest that builds up over the season.
Population growth rate (r) of the pest is determined by the
development time, the fecundity, and the mortality rate (of the
juveniles and adults). It is assumed that plant resistance can
affect any of these life history parameters independently. It
also is assumed the pest is attacked by a series of natural
enemies that are present or move into the crop but that do not
reproduce in the crop (or that reproduction has no effect on
natural enemy numbers in the current season). In this case the
population dynamics of the natural enemy during the season
need not be considered. Any effects of interactions in previous
generations on pest and natural enemy numbers in the present
generation are ignored. This assumption is justified when
annual crops are rotated, or when pests and natural enemies
disperse widely so that densities in any one place are not or are
little affected by densities in the previous generation. Pests of
Proc. Natl. Acad. Sci. USA 96 (1999J 5945
annual crops that are attacked by birds, by natural enemies
such as many spiders or beetles that may reproduce in the crop,
but whose progeny would not that season consume pests, or by
parasitoids whose progeny would not become adult until the
next season, all would be described by this scenario.
The model pest is an insect with a general life history similar
to that of a sucking homopteran pest such as an aphid. The
insect takes 2 weeks to develop from egg to adult and then lives
for an additional 2 weeks. Juvenile mortality is responsible for
the deaths of a little more than 60% of immatures. Throughout
its adult life, the female produces 20 female eggs a day. A
population with this natural history will grow at a rate r = 1.60
per week. This parameter set is used as a basis for exploring the
consequences of the different plant resistance-biocontrol in-
teractions. The natural enemies are assumed to act as an
additional mortality factor influencing either juvenile or adult
mortality. As stated above, the plant resistance potentially can
influence pest fecundity, juvenile or adult mortality, or devel-
opment time. The aim is to identify the change in the rate of
pest increase (r) that results from increased resistance, and
how such changes are influenced by the presence of natural
enemies. To do this, a means of comparing the effect of plant
resistance acting on different components of the pest's life
history is required. Here, the proportional sensitivity of the
intrinsic rate of increase is used. This measure is of the change
in r that results from a small percentage change in the value of
a parameter. Its exact meaning becomes clearer in Figs. 1 and
2, which examine the proportional sensitivity of r to changes in
the life history parameters (basically the relative impact or
value of plant resistance) in the presence of natural enemies
acting on either adult or juveniles stages of the pest, respec-
tively.
The first point to notice in both figures is that in the absence
of any natural enemies, the relative effect of a proportional
change in the different life history parameters (i.e., the base-
line proportional sensitivity at the intercept of they axis) varies
considerably. With the basic parameter set, by far the greatest
reduction in pest growth rate is achieved by increasing the pest
development time; a decrease in fecundity or an increase in
juvenile mortality have the same influence while an increase
in adult mortality is the least effective way to reduce the pest
growth rate. The generality of this conclusion is examined
2.0
.> 1.5
._
._
a)
In
`~5 1.0
o
.=
o
Q
° 0.5
cc
0.0
development
tic_
adult
Juvenlle
fecundity mortality
\
0 1 2
1
3 4 5
Rate of natural enemy mortality on adults
FIG. 1. Proportional sensitivities of pest population growth rate for
different pest life history parameters combined with natural enemy
mortality acting on the adult pests. Positive slopes indicate synergy
between host plant resistance acting on a particular life history
parameter and the natural enemy activity. Negative slopes indicate
subadditive interactions. Further details of the model and assumptions
are given in the text and in ref. 6. Reproduced with permission from
ref. 6.
OCR for page 5946
5946 Colloquium Paper: Thomas
2.0
.-~ 1.5
._
._
In
In
<~ 1.0
o
o
n
° 0.5
0.0 _
0 1
fecundity juvenile
~ if mortality
_
development
time
i/
adult
mortality
_~
5
Rate of natural enemy mortality on juveniles
FIG. 2. Proportional sensitivities of pest population growth rate for
different pest life history parameters combined with natural enemy
mortality acting on the juvenile pest stages. Other details are as in Fig.
1 and the text. Reproduced with permission from ref. 6.
analytically in ref. 6. The results of this analysis reveal that the
population dynamic effects of plant resistance depend not only
on which specific life history parameters the resistance influ-
ences but also on the general life history of the pest. Thus, in
slowly growing populations, increasing development time or
increasing juvenile mortality have roughly similar effects on
reducing r. As population growth rate increases, however, the
value of increasing development time markedly increases. The
relative advantages of manipulating adult mortality increases
as fecundity declines, as the product of juvenile mortality and
development time gets larger, and as the population growth
rate increases. Finally, the relative value of decreasing fecun-
dity depends on the parameter values for juvenile mortality
and development time. In sum, not all components of resis-
tance have equivalent effects on pest suppression; the effects
of individual mechanisms depend on the life history of the pest.
Considering now the combined effects of plant breeding and
biocontrol, Fig. 1 shows the proportional sensitivities of in-
trinsic growth rate with respect to the four pest life history
parameters plotted as a function of the natural enemy mor-
tality experienced by the adult pest (i.e., biocontrol acts only
on the adult stages). In this figure (and Fig. 2), a decrease in
proportional sensitivity (a negative slope) as natural enemy
mortality increases indicates a subadditive interaction because
the interaction of the two effects is less than the sum and the
relative impact of changing the parameter will have fallen.
Conversely, an increase in proportional sensitivity (a positive
slope) as mortality by natural enemies increases indicates
superadditivity or synergy such that the interaction of the two
effects is greater than the sum of their individual actions. It can
be seen in Fig. 1 that fecundity and juvenile mortality show a
superadditive effect, the other two parameters a subadditive
effect. However, the slope of the lines are rather shallow
indicating that, at least for our particular pest life history, the
effects of resistance and natural enemy mortality on adult pests
are at least roughly additive.
Moving on to natural enemy mortality acting on the juvenile
pest, it can be seen that the effect on r of a change in fecundity
or juvenile mortality is subadditive over a range of different
levels of juvenile mortality because of natural enemies (Fig. 2),
which is the reverse of the effect shown in Fig. 1. With respect
to the interaction between development rate and natural
enemy mortality on juveniles it can be seen that for rates of
natural enemy mortality of between O and 1 the proportional
sensitivity of growth to development time is approximately
Proc. Natl. Acad. Sci. USA 96 (1999J
constant (in fact it is slightly superadditive in the range O to O.S)
but is subadditive beyond. This effect may seem counterintui-
tive in the light of some studies that propose that slowing
development time should increase the chances of being killed
by a natural enemy (7, 8~. However, although increasing the
developmental period may well increase mortality by natural
enemies to a certain extent, the main value is in fact to slow
down the compounded growth rate of the pest population. If
the natural enemy already has reduced the pest's growth rate
to a low level, the proportional benefit of an increase in
development may be relatively small. Finally, natural enemy
mortality affecting juveniles and adult mortality combine
superadditively to reduce pest growth rate, which again is the
reverse of Fig. 1. Even if severe juvenile mortality through
natural enemies has reduced immature survival to very low
levels, a further reduction in pest numbers can be achieved by
an increase in adult mortality.
Again, the generality of these and the previous conclusions
has been investigated analytically (6~. This analysis reveals that
within the constraints of the model and its assumptions, the
interaction between natural enemy mortality of adult pests and
resistance effects on fecundity or juvenile mortality always will
be superadditive, whereas that with adult mortality always will
be subadditive. When natural enemies act on the juvenile pest
stages, the outcome of these equivalent interactions is re-
versed. The interaction of plant quality affecting development
time and either adult or juvenile natural enemy mortality can
be both superadditive or subadditive depending on specific
conditions.
Implications for IPM. The models presented here provide a
theoretical framework for quantifying the population dynamic
aspects of certain plant resistance-biological control interac-
tions. The results show that the effectiveness of individual
mechanisms in suppressing pest population growth rate de-
pends critically on pest life history. They also show that
biological control and host plant resistance can be compatible
and can combine additively or synergistically to improve pest
control. However, even with the simplest representation of
biological control (i.e., natural enemies providing an addi-
tional density independent mortality) subadditive and complex
interactions are also possible. What is important to note in this
context is that current resistance screening and evaluation
procedures do not examine the direct or indirect effects of
resistance on the third trophic level (6) and hence do not
account for the action of natural enemies or how this action
may vary across time and space. This means that positive
interactions between plant resistance and biological control
are not identified and that potentially useful partially resistant
varieties that, in combination with natural enemies, could
provide satisfactory control, frequently are rejected. It also
means that the effects of infochemicals or direct physical
interactions between the host plant and the natural enemy are
ignored. Worse, without examining the third trophic level it is
possible that wide-scale deployment of resistant varieties that
actively interfere with natural enemies could occur. This
practice could not only reduce the benefits gained from
resistance breeding but also could have long-term conse-
quences for the persistence of certain key natural enemy
species.
Overall, a central conclusion of this study is that population
dynamics provides a common language for plant breeders and
biocontrol practitioners with the power to reveal how the
different technologies, acting perhaps on different stages and
different aspects of pest population growth, may interact in
determining the trajectory of pest populations and hence
damage to crops. Presently, most information on the relation-
ship of biological control and host plant resistance is conjec-
tural, speculative, or based only on limited observation (9~.
Population dynamic thinking, aided by simple models, has the
potential to help us to generate the right questions and design
OCR for page 5947
Colloquium Paper: Thomas
the right experiments for better understanding the interactions
of host plant resistance and biological control.
Ecology of Host-Pathogen Interactions and Microbial Pest
Control
In response to the problems of intensification and chemical
pesticide use touched on in the Introduction, there is today a
growing interest in the potential of pathogens for use in
biological control, particularly as biorational pesticides (1O,
11~. However, in spite of much evidence suggesting a role for
parasites in the regulation of host abundance, our understand-
ing of the impact of infectious diseases and the role they play
in the population dynamics of their hosts remains poor (11, 12~.
An important applied consequence of this limited understand-
ing is that efforts to use diseases for pest control often meet
with failure. This certainly holds for the use of biopesticides,
which generally are characterized by their poor and erratic
performance under field conditions (13~. Consequently, bio-
pesticides and microbial agents are viewed by industry and
crop protection specialists with considerable skepticism, which
is reflected in the marketplace with biopesticides representing
<1% of the global market for agrochemical crop protection
(13~. Moreover, the way microbial organisms are used as
biopesticides tends to emphasize aspects of their biology that
mimic conventional chemical pesticides (i.e., simply using the
capacity of pathogens to kill the target host) and overlooks
many other biological attributes that may have important
population dynamic implications (5, 10, 11~. This paradigm
holds for the development of bioinsecticides and bioherbicides.
If microbial control agents and biopesticides are to attain
anything like their full potential, moving beyond the status of
novelty products suitable only for limited niche markets and
playing a major role in sustainable crop protection in the
future, a far greater and more detailed understanding of
host-parasite biology and disease dynamics is required.
This argument is further illustrated by some recent ecolog-
ical studies conducted as part of an ongoing biocontrol pro-
gram developing a biopesticide, based on a fungal ento-
mopathogen, for control of locusts and grasshoppers in Africa.
The program, LUBILOSA, has made considerable progress in
the development of an effective and reliable biopesticide, and
many successful field tests have been conducted against a range
50
40
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In
~5
o
._
-
Q 20
o
Q
U)
o
I
30
10
o
Proc. Natl. Acad. Sci. USA 96 (1999> 5947
of locust and grasshopper hosts under a variety of ecological
conditions (see ref. 14 for a recent review of the program). The
pathogen itself acts like a chemical pesticide through direct
contact and on the whole, the development, testing, and
registration of the biopesticide have tended to follow what
could be considered a traditional chemical pesticide model.
However, a number of ecological studies have shown that the
pathogen has a range of additional biological characteristics
quite unlike a chemical, which contribute to its overall per-
formance and which need to be considered in its evaluation
and ultimate use.
The Importance of Horizontal Transmission. Studies after
spray applications have identified that under certain condi-
tions hosts infected by the biopesticide can go on to produce
new spores and infect further hosts through horizontal trans-
mission (11, 15, 164. The dynamics of this process are governed
by the factors that regulate natural host-pathogen interactions
because infections result from natural pathogen delivery
mechanisms. These include a number of biotic factors relating
to the specific life history and behavioral traits of the host and
the pathogen, as well as a range of abiotic factors that have a
fundamental influence on the physical and biochemical pro-
cesses involved in the host-pathogen interaction (refs. 11, 15,
and 16; S. Blanford and M.B.T., unpublished work). These
processes have very few chemical analogues and consequently,
quantifying the impact of horizontal transmission in the field
is not straightforward and certainly not amenable to standard
protocols adopted from short-term chemical pesticide evalu-
ation studies. In the LUBILOSA program, therefore, evalua-
tion of the horizontal transmission has been aided by the
development of some simple population models, built around
empirical data describing the different biological processes
governing pathogen cycling. Full details of these models can be
found in refs. 11, 15, and 16. In brief, the models, combined
with field observations, have demonstrated that contact with
spores from infected cadavers can provide an important source
of infection by both prolonging the effects and increasing the
impact of single spray applications. This is illustrated in Figs.
3 and 4, which show model simulations of grasshopper popu-
lations under two control scenarios.
In Fig. 3 it is assumed that the biopesticide acts just through
direct contact and residual pickup of spores, with no horizontal
transmission. Spraying is restricted to once a season after egg
Plllllllllllllllllill ~llllllllllllllllllll
o
1500 3000 4500
Time (days)
ATI
FIG. 3. Output of a simple host-pathogen model showing predicted change in grasshopper population density through time after applications
of a biopesticide. In this example, the biopesticide acts like a chemical through direct contact and residual pickup of spores only, with no horizontal
transmission. The system is seasonal, with a season duration of 90 days and one grasshopper generation per season (each peak, therefore, represents
the grasshopper density at the start of a new generation). Spraying occurs just once per season and only if the host density exceeds the spray action
threshold (ATL) of 10 m-2. Each spray event is indicated with an arrow. FU11 details of the model and its assumptions are given in ref. 11.
OCR for page 5948
5948 Colloquium Paper: Thomas
50
40
.~
v)
a)
o
._
-
Q
o
Q
an
o
I
20
10
·C
Proc. Natl. Acad. Sci. USA 96 (1999J
1 1 1 1 1 1 1 1 1 1 1
· 1 1 l
............... 1 1
~ ~ x1,
· 1 ~1 1 1
:1~ ~ ~ ~ I
1500
Time (days)
3000
4500
ATE
FIG. 4. Predicted change in grasshopper population density through time after applications of a biopesticide when a horizontal transmission
component is added. Spray frequency has fallen to just once in every 4-5 generations, and peak population densities are uniform compared with
Fig. 3. Other details are as in Fig. 3 and ref. 11.
hatch, and then only if the host density exceeds the spray action
threshold of 10 hosts m-2. In combination, direct hit and
contact with the spray residue result in approximately 80%
mortality, causing the population to crash dramatically after
spraying. However, in spite of this impact, given the pest
reproductive rate (in this case a finite rate of increase = 5) the
biopesticide fails to provide any long-term control and host
densities recover to above the spray threshold nearly every
season. Thus, under these model assumptions (which are based
on real field data) the biopesticide acts just like a chemical
pesticide inducing a standard level of density-independent
mortality.
The addition of horizontal transmission (described in the
model again by empirically derived data) changes this picture
dramatically (Fig. 4~. The reason is that the biopesticide now
has a density-dependent, "numerical response" component to
its action. Although pickup of spores from the initial spray
application kills the majority of grasshoppers, horizontal trans-
mission from infected cadavers can still act to clear up those
remaining and reduce the host population to very low levels.
This process contributes to better overall control by restricting
population peaks and reducing spray frequencies.
This result is important whenever the choice of pathogen
strain or formulation involves a tradeoff between direct and
residual kill rates and the potential for secondary cycling. For
example, a tradeoff between virulence and pathogen repro-
duction (i.e., spore production) has been noted for a number
of fungal isolates (unpublished data). Similar relationships also
have been identified for certain viruses (18~. Although high
virulence may be a desirable trait (virulence is often the
principle criterion for isolate selection), selecting isolates on
the basis of this factor alone may have unforeseen conse-
quences for the population dynamics of the host-pathogen
interaction and overall pest control. Furthermore, these stud-
ies reveal that under realistic conditions when direct hit and
residual pickup have a high initial impact, the effect of
horizontal transmission, although important, is very subtle and
is not likely to be apparent until late in the season.
Behavioral Changes and Sublethal Effects. Beyond hori-
zontal transmission, other ecological studies have further
identified some intriguing problems in assessing and quanti-
fying the impact of the biopesticide. For example, studies have
revealed that infected hosts appear to be more vulnerable to
predation than healthy hosts before death (ref. 19 and unpub-
lished data). This phenomenon may have benefits in that speed
of kill after application may effectively be increased through
the pathogen's interaction with other mortality factors, al-
though the extent to which this mortality occurs will depend on
the nature and abundance of natural enemies at the site of
application. Moreover, given that the biopesticide is specific to
locusts and grasshoppers, these important natural enemies are
conserved, providing a "value added" component to the
biopesticide's activity, relative to broad-spectrum chemical
pesticide alternatives, which can remove this natural back
ground biocontrol (at least temporarily). However, heavy
predation also means that potential sources of inoculum for
horizontal transmission are lost. Interestingly, this loss is
balanced to some extent by the fact that infected cadavers are
avoided by scavengers and persist far longer in the field than
uninfected cadavers (unpublished data). Overall, the situation
is complex but it is becoming clear that studies of interactions
between infection and predation are relevant to understanding
both short-term patterns of disease incidence and longer-term
disease dynamics.
In addition, several studies indicate that the pest status of
infected insects is markedly reduced soon after application of
the pathogen because of a rapid reduction in feeding. This
result has been shown in laboratory and field settings for a
range of species and pathogen doses (19-22~. Thus it appears
that the overall impact of the biopesticide is determined by
more than just mortality rate (which can be slow under field
conditions; see below) and that even infections with very low
levels of pathogen still may have important consequences for
control.
Finally, studies have identified that the role of environmen-
tal temperature and host thermal biology are central for
interpreting patterns of mortality observed following spray
applications.
Many grasshoppers and locusts actively thermoregulate to
maintain their body temperatures around a preferred set point
during the day. This set point can be significantly different
from ambient and can be maintained for a number of hours
given the right environmental conditions. For example, studies
during large-scale field trials in west Africa revealed that the
preferred body temperature of the Senegalese grasshopper,
Oedaleus senegalens~s, (one of the most important grasshopper
pests in the Sahel) is 39°C (23~. This temperature is high
enough to cause significant decline in growth of the pathogen
inside infected insects. Moreover, this species was found to
adopt a "behavioral fever" response to infection whereby
OCR for page 5949
Colloquium Paper: Thomas
internal body temperatures were elevated higher still to a new
set point around 42°C. At this temperature all fungal growth
is completely inhibited. However, this new set point is only
achievable during the day. During the evening, night, and
morning when active thermoregulation is not possible, the
body temperature of these grasshoppers is close to ambient
(22-32°C), providing a window for pathogen growth. Thus, the
effect of the fever is to prolong the disease incubation period,
allowing insects to survive longer than expected in the field.
However, because, in field trials, insects are exposed to
relatively high doses of pathogen, total mortality appears not
to be affected. That said, additional follow-up studies in the
laboratory suggest that thermoregulation and behavioral fever
may enhance host resistance to lower, more natural doses of
pathogen and restrict disease spread. Indeed, studies on a
range of species infected with different pathogens suggest that
host thermal biology and environmental temperature (rather
than the widely assumed effects of environmental moisture
and humidity) may be key factors in understanding natural
disease dynamics and explaining seasonal variation in disease
prevalence in the field (S. Blanford and M.B.T., unpublished
work). This work has shown that key parameters such as
pathogenicity, the latent period of infection, and host recovery
rate all can vary dramatically across time and space because of
thermal biology of the host and changes in environmental
temperature. Such effects have not been thoroughly explored
in any previous investigations (neither practically in the de-
velopment of biopesticides or in the wealth of modeling studies
that guide established theory) but have major qualitative and
quantitative implications for disease dynamics in insects and
possibly ectotherms in general.
Implications for Microbial Control and IPM. Although the
work presented here derives from one specific biocontrol
program, there are a number of insights relevant to develop-
ment of insect pathogens as biocontrol agents in general. First,
because of the biological nature of the active ingredient, a
biopesticide may have a "numerical response" component to
its action. As stated above, this possibility rarely has been
considered in the development of biopesticides, with current
commercial development following a chemical pesticide model
and emphasizing the "functional response" components only
(11~. Clearly, however, such properties can be important and
could provide new opportunities for using pathogens in bio-
logical pest control and have significant consequences for the
economics of biopesticide use. This aspect is seen in the
combined model where although in absolute terms, secondary
cycling of the pathogen appears to have little impact, its effect
on reducing the frequency of spray applications is most
pronounced. This thinking also extends to sublethal effects
such as reduction in feeding and increased susceptibility to
natural enemies. All of these features combine to define the
impact, competitiveness and utility of a biopesticide product
and must be known.
Beyond this, the work on temperature and thermal biology
has major implications for use of microbial agents in insect pest
control and for managing disease dynamics in natural popu-
lations. For example, basic screening bioassays for selecting
pathogens for use in biological control usually are conducted
under constant laboratory conditions far removed from con-
ditions in the field (24~. However, given that virulence and host
recovery appear highly temperature sensitive, it is clear that
this approach can lead to erroneous conclusions and the
selection of inappropriate isolates. This conclusion is sup-
ported by a number of studies that report initial positive results
in the laboratory only to find performance in the field highly
variable with environmental factors, and in particular temper-
ature, appearing to play an important role (25, 26~. Under-
standing the effect of temperature and/or the role of host
thermal behavior on the host-pathogen interaction could make
a major contribution to improving this situation. This conclu
Proc. Natl. Acad. Sci. USA 96 (1999J 5949
sion extends to assessing the risks of biopesticides against
nontarget species and determining the ultimate fate of patho-
gens in the environment. Finally, natural epizootics frequently
are linked with periods of rainfall and high relative humidity
(27, 28~. However, such conditions are also likely to lower
ambient temperatures and increase cloud cover. Thus, in
addition to any direct effect on disease transmission, rain
episodes are likely to alter the relative susceptibility of hosts to
pathogens through effects on body temperature. For mobile
species such as locusts and grasshoppers, suboptimal temper-
atures also would reduce movement, possibly increasing op-
portunities for contact between hosts at a time when suscep-
tibility to disease is increased. Understanding such complex
interplay between humidity, temperature, and physiological
and behavioral changes in susceptibility could reveal exciting
new opportunities for using pathogens via strategies of con-
servation, augmentation, and classical introduction. Such ap-
proaches have virtually been ignored to date.
Conclusions
In this paper I have tried to demonstrate the value of adopting
a more rigorous ecological approach to understanding the
impact of pest control technologies. The need for this approach
derives from the fact that the single solution, "magic bullet"
approach has undermined our basic understanding of how
individual components actually work and has oriented IPM
toward quick fixes, often underpinned by commercial incen-
tives. Developing truly integrated pest management that ad-
dresses the problems of sustainable agriculture will require
that we break away from this model. The downside is that pest
control may be more complicated. At the very least, it will be
"knowledge intensive," requiring a greater input of appropri-
ate ecological research in the development stage and with
more emphasis placed on long-term solutions, even if the
practical outputs are inherently simple. That said, it must be
remembered that the complexity of nature also makes it
difficult to apply conventional area-wide prescriptions success-
fully across all systems. Equally, compensating for a lack of
understanding with excessive reliance on single technologies
and short-term solutions does not make sense; experience of
the last 30 years has shown the greater the apparent success in
achieving pest or disease control in the short term, the greater
the likelihood of a serious breakdown in the long run (29~.
Moreover, and perhaps most importantly, the upside of this
increased effort is that it could provide access to some of the
substantial amounts of yield currently lost to pests and dis-
eases. Stressing the theme of the symposium and the question
of time, an important dimension here is that this yield is
available now, if we can manage these biotic constraints. To
this end, many IPM tools are available now (e.g., partially
resistant germplasm, partially effective indigenous natural
enemies, and potentially effective but unreliable microbial
agents) and do not require further technological break-
throughs to be useful. The immediate challenge lies in the
genuine application of ecological research (i.e., truly dealing
with applied problems and not merely paying them lip service)
to understand how these components interact and identify
more effective and sustainable integrated strategies for their
use.
Putting these conclusions into a broader ecological context,
we need a greater understanding of how different components
in the agroecosystem function and how their "ecological
services" can be maintained, while moving toward the goals of
intensification. In essence, replacing chemicals and capital
with locally available biological resources and knowledge. This
problem is summarized visually in Fig. 5. Fig. 5 illustrates the
general negative relationship or tradeoff between functional
biodiversity, which provides biological services that contribute
to system resilience, and intensification, which tends to strip
OCR for page 5950
5950 Colloquium Paper: Thomas
~ -
v' a.)
.o
>
._ ~
O in
-
~ .O
0 0
. _ _
~ O
_%
~ w
11
\ B
1 ,
Intensification ('external services')
FIG. 5. Representation of the general negative relationship be-
tween functional biodiversity and the contribution of ecological ser-
vices to community stability, and agricultural intensification and its
associated reliance on external inputs. For model A the system is
managed in such a way that the ecological services are well maintained
as the system is intensified (at least over moderate levels of intensi-
fication). Model A contrasts with model B in which intensification
causes a sharp loss of functional diversity, resulting in a rapid increase
in external inputs.
away this diversity and replaces the biological services with
external inputs to provide insurance against collapse. More
Potential yield
(growth cletermining
factors)
(a)
(b)
(c)
Proc. Natl. Acad. Sci. USA 96 (1999J
over, from the figure it is clear that what is important is the
exact nature of this negative relationship; in the context of
sustainability and minimization of external inputs, intensifica-
tion model A is clearly better than model B. Overall, it is this
tradeoff, our understanding of it and our ability to manage it
that is fundamental to IPM, and one that places basic ecology
at the heart of sustainable crop production. Boldly stated, the
shortcomings of IPM over the last 30 years generally can be
ascribed to a lack of such ecological thinking. This situation is
unfortunate given that the types of manipulations and man-
agement practices necessary to maintain the functional com-
ponents of the ecosystem themselves may be inherently simple.
For example, studies in the Philippines have demonstrated that
intercropping maize and peanuts can create a sufficiently
complex and beneficial food web to keep maize stemborer in
check (30~. Similarly, the simple addition of narrow grass-
covered banks to cereal fields in the United Kingdom has been
shown to improve overwintering conditions for key predators
of aphids and facilitate effective colonization of the fields in
the spring (31~.
Finally, in any particular setting, the role of IPM needs to be
considered in the context of the overall production system. To
do this it is necessary to determine the role of different
constraints in the production chain and define where the
greatest gains per unit investment can be made. A conceptual
framework for this approach is presented in Fig. 6. Here,
factors influencing production in the field are grouped into
three categories (a fourth could be added to account for
postharvest losses). At the most basic level, productivity is
determined by yield potential, which is defined by character-
istics of the crop, temperature, and sunlight (17~. Yield po
Attainable yielcl
(growth limiting
factors)
· ~
Actual yield
(growth reducing
factors)
181 ~1
Relative constraint
Absolute constraint
r.
.,
13-
FIG. 6. Conceptual framework for defining constraints to crop production along the production chain and identifying where the greatest gains
per unit investment can be made. Shaded areas represent the amount of yield available at one point in the chain that can be passed onto the next.
(a) A system with 50~o loss to potential yield, 20% loss to attainable yield and 40% loss to actual yield. (b) The effect of relative constraints. (c)
The effect of an absolute constraint (in this case attainable yield). Further details are provided in the text.
OCR for page 5951
Colloquium Paper: Thomas
tential, therefore, describes the maximum possible yield under
optimum growing conditions for a given crop. At the next level,
attainable yield is determined by the real (and often more
limited) availability of factors such as nutrients, water, and
sunlight in the farmers' field (17~. Finally, actual yields ob-
tained tend to be lower again because of the action of
growth-reducing factors such as pests and diseases (17~. In a
perfect system, yield potential, attainable yield, and actual
yield all would be loom, with no losses along the production
chain. A more typical scenario, however, might look like Fig.
6a where yield potential is 50% of the maximum, attainable
yield is 80%, and actual yield is 60%. In this system it would
appear that the greatest restriction to yield, and hence the
priority for research input, lies with the growth defining factors
affecting yield potential. However, in addition to identifying
where in the production chain losses occur, it is necessary to
consider the nature of the constraints and whether they are
relative or absolute. With relative constraints, increases in
yield are passed along the production chain. This process is
demonstrated in Fig. 6b where improvements in yield potential
translate to relative increases in attainable yield and actual
yield, in spite of the percentage constraints at these points in
the chain remaining the same. However, if one of the con-
straints is absolute rather than relative, a bottleneck is created
that restricts the passage of yield gain along the chain. In Fig.
tic, where the constraint to attainable yield is assumed to be
absolute, none of the gain in yield potential ultimately is
attained. Under these circumstances, the research priority may
switch to examining why the constraint is absolute, or to
addressing factors below the absolute constraint where gains
can still be realized. What is important to appreciate here is
that the size, position, and nature (i.e., whether absolute or
relative) of the constraints in any system will be highly location
specific. Thus, a critical step in future efforts to increase
productivity will be to move away from generalist, area-wide
management prescriptions, toward local solutions developed in
response to questions generated at the local level. Unfortu-
nately, such an approach presents considerable challenges and
even conflicts with existing research incentives and institu-
tional structures (5~. This conclusion identifies that whatever
technological or methodological advances to improve produc-
tivity are identified, effective implementation will be possible
only with appropriate economic and political support.
1. Natural Resources Institute (1992) A Synopsis of Integrated Pest
Management in Developing Countries in the Tropics (Natural
Resources Institute, Chatham, U.K.~.
2. Kumar, R. (1984) Insect Pest Control with Special Reference to
African Agriculture (Edward Arnold, London).
3. Waage, J. K. (1993) in agriculture and Environmental Challenges:
Proceedings of the Thirteenth Agricultural Sector Symposium, eds.
Srivastava, J. P. & Alderman, H. (World Bank, Washington, DC),
pp. 119-134.
Proc. Natl. Acad. Sci. USA 96 (1999J 5951
4. Georghiou, G. P. (1990) in Managing Resistance toAgrochemicals,
eds. Green, M. B., LeBaron, H. M. & Moberg, W. K. (Am. Chem.
Soc., Washington, DC), pp. 18-41.
5. Waage, J. K. (1998) Entomologia Sinica 5, 257-271.
6. Thomas, M. B. & Waage, J. K. (1996) Integration of Biological
Control and Host Plant Resistance Breeding: A Scientific and
Literature Review (Technical Centre for Agricultural and Rural
Cooperation of the European Union, Wageningen, The Neth-
erlands).
7. Price, P. W., Bouton, C. E., Gross, P., McPheron, B. A., Thomp-
son, J. N. & Weis, A. J. (1980) Annul Rev. Ecol. Syst. 11, 41-65.
8. Price, P. W. (1986) in Interactions of Plant Resistance and
Parasitoids and Predators of Insects, eds. Boethel, D. J. & Eiken-
bary, R. D. (Wiley, Chichester, U.K.), pp. 11-30.
9. Herzog, D. C. & Funderburk, J. E. (1985) in Biological Control
in Agricultural IPM Systems, eds. Hoy, M. A. & Herzog, D. C.
(Academic, New York), pp. 67-88.
10. Lacey, L. A. & Goettel, M. S. (1995) Entomophaga 40, 3-27.
11. Thomas, M. B. & Wood, S. N. (1997) Br. Crop Protection Council
Symp. Proc. 68, 63-72.
12. Grenfell, B. T. & Dobson, A. P., eds. (1995) Ecology of Infectious
Diseases in Natural Populations (University Press, Cambridge).
13. Lisansky, S. (1997) Br. Crop Protection Council Symp. Proc. 68,
3-10.
14. Bateman, R. P. (1997) Outlook Agric. 26,13-18.
15. Thomas, M. B., Wood, S. N. & Lomer, C. J. (1995) Proc. R. Soc.
London Ser. B 259, 265-270.
16. Wood, S. N. & Thomas, M. B. (1996) Proc. R. Soc. London Ser.
B 263, 673-680.
17. Rabbinge, R. (1993) in Crop Protection and Sustainable Agricul-
ture, eds. Chadwick, D. J. & Marsh, J. (Wiley, Chichester, U.K.),
pp. 2-29.
18. Hails, R. S. (1997) Br. Crop Protection Council Symp. Proc. 68,
53-62.
19. Thomas, M. B., Blanford, S., Gbongboui, C. & Lomer, C. J.
(1998) Entomol. Exp. Appl. 87, 93-102.
20. Moore, D., Reed, M., Le Patourel, G., Abraham, Y. J. & Prior,
C. (1992) J. Invertebr. Pathol. 60, 304-307.
21. Seyoum, E., Moore, D. & Charnley, A. K. (1994) J. Appl.
Entomol. 118, 310-315.
22. Thomas, M. B., Blanford, S. & Lomer, C. J. (1997) Biocontr. Sci.
Technol. 7, 327-334.
23. Blanford, S., Thomas, M. B. & Langewald, J. (1998) Ecol.
Entomol. 23, 9-14.
24. Thomas, M. B. & Jenkins, N. E. (1997) Mycol. Res. 101 1469
1474. '
25. Samways, M. J. & Grech, N. M. (1986)Agric. Ecosyst. Environ. 15,
231-239.
26. Inglis, G. D., Johnson, D. L. & Goettel, M. S. (1996) Biol. Control
7, 131-139.
27. Hajek, A. E. & St. Leger, R. J. (1994) Annul Rev. Entomol. 39,
239-322.
28. Carruthers, R. I. Ramos, M. E., Larkin, T. S., Hostetter, D. L. &
Soper, R. S. (1997) Mem. Entomol. Soc. Can. 171, 329-353.
29. Conway, G. (1997) The Doubly Green Revolution: Food for All in
the 21st Century (Penguin, London).
30. Altieri, M. A. (1995) Agroecology: the Science of Sustainable
Agriculture (Intermediate Technology, London), 2nd Ed.
31. Thomas, M. B., Wratten, S. D. & Sotherton, N. W. (1991) J. Appl.
Ecol. 28, 906-917.
Representative terms from entire chapter:
natural enemies
