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Evolution of pest resistance to pesticides is an urgent global problem with resistance recorded in at least 954 species of pests, including 546 arthropods, 218 weeds, and 190 plant pathogens. To facilitate understanding and management of resistance, we provide definitions of 50 key terms related to resistance. We confirm the broad, long-standing definition of resistance, which is a genetically based decrease in susceptibility to a pesticide, and the definition of "field-evolved resistance," which is a genetically based decrease in susceptibility to a pesticide in a population caused by exposure to the pesticide in the field. The impact of field-evolved resistance on pest control can vary from none to severe. We define "practical resistance" as field-evolved resistance that reduces pesticide efficacy and has practical consequences for pest control. Recognizing that resistance is not "all or none" and that intermediate levels of resistance can have a continuum of effects on pest control, we describe five categories of field-evolved resistance and use them to classify 13 cases of field-evolved resistance to five Bacillus thuringiensis (Bt) toxins in transgenic corn and cotton based on monitoring data from five continents for nine major pest species. We urge researchers to publish and analyze their resistance monitoring data in conjunction with data on management practices to accelerate progress in determining which actions will be most useful in response to specific data on the magnitude, distribution, and impact of resistance.
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FORUM
Defining Terms for Proactive Management of Resistance to Bt Crops
and Pesticides
BRUCE E. TABASHNIK,
1,2
DAVID MOTA-SANCHEZ,
3
MARK E. WHALON,
3
ROBERT M. HOLLINGWORTH,
3
AND YVES CARRIE
`RE
1
J. Econ. Entomol. 107(2): 496Ð507 (2014); DOI: http://dx.doi.org/10.1603/EC13458
ABSTRACT Evolution of pest resistance to pesticides is an urgent global problem with resistance
recorded in at least 954 species of pests, including 546 arthropods, 218 weeds, and 190 plant pathogens.
To facilitate understanding and management of resistance, we provide deÞnitions of 50 key terms
related to resistance. We conÞrm the broad, long-standing deÞnition of resistance, which is a
genetically based decrease in susceptibility to a pesticide, and the deÞnition of Þeld-evolved resis-
tance,which is a genetically based decrease in susceptibility to a pesticide in a population caused by
exposure to the pesticide in the Þeld. The impact of Þeld-evolved resistance on pest control can vary
from none to severe. We deÞne practical resistanceas Þeld-evolved resistance that reduces pesticide
efÞcacy and has practical consequences for pest control. Recognizing that resistance is not all or none
and that intermediate levels of resistance can have a continuum of effects on pest control, we describe
Þve categories of Þeld-evolved resistance and use them to classify 13 cases of Þeld-evolved resistance
to Þve Bacillus thuringiensis (Bt) toxins in transgenic corn and cotton based on monitoring data from
Þve continents for nine major pest species. We urge researchers to publish and analyze their resistance
monitoring data in conjunction with data on management practices to accelerate progress in deter-
mining which actions will be most useful in response to speciÞc data on the magnitude, distribution,
and impact of resistance.
KEY WORDS evolution, Þeld-evolved resistance, genetically engineered crop, Bacillus thuringiensis
Evolution of pest resistance to pesticides is an increas-
ingly urgent problem that threatens human health and
agriculture worldwide (Brent and Holloman 2007,
Enayati and Hemingway 2010, Powles and Yu 2010,
Heckel 2012, Wolstenholme and Kaplan 2012, Coetzee
and Koekemoer 2013, Shalaby 2013, Sierotzki and Scal-
liet 2013), with resistance recorded in at least 546
species of arthropod pests (Fig. 1), 218 species of
weeds, and 190 species of plant pathogens (Fungicide
Resistance Action Committee 2013, Heap 2013, Wha-
lon et al. 2013). Well-deÞned terms for detecting,
analyzing, and categorizing resistance are needed to
tackle this daunting challenge. However, the lack of
a modern glossary for resistance was recently
brought to our attention by an initiative of the U.S.
Environmental Protection Agency (EPA) seeking
input on deÞnitions of terms about resistance (Wha-
lon 2013).
Here, we provide a list of 50 key resistance terms
and deÞnitions aimed to facilitate understanding and
management of resistance (Tables 4). This article
emphasizes resistance to toxins from Bacillus thuringien-
sis (Bt) produced by transgenic plants, but our goal is to
deÞne the terms broadly so they can be applied to re-
sistance to any pesticide. Although we consulted many
references (Wilson and Bossert 1971, Hartl 1981, Li et al.
2007, Gassmann et al. 2009, and others cited below), the
deÞnitions here are not necessarily identical to those in
the references. Whereas some deÞnitions provided here
might be accepted readily, others may be contro-
versial. In controversial cases, the deÞnitions pro-
posed here can provide a point of reference for
discussions, reÞnements, and revisions. In particu-
lar, we review the deÞnitions of resistance,”“Þeld-
evolved resistance,and related terms to dispel con-
fusion about these terms. We also illustrate various
categories of Þeld-evolved resistance using data ob-
tained from monitoring pest resistance to Bt crops.
Resistance
We deÞne resistance as a genetically based de-
crease in susceptibility to a pesticide(Table 1). The
roots of this deÞnition are in the book produced by the
National Research Council of the National Academy
of Sciences of the United States, in which Brent (1986)
deÞnes resistance as any heritable decrease in sen-
sitivity to a chemical within a pest population.Brent
(1986) speciÞes that resistance can be slight, marked,
or completeand homogenous, patchy, or rare.In
the same book, Dekker (1986) emphasizes that resis-
1
Department of Entomology, University of Arizona, Tucson, AZ
85721.
2
Corresponding author, e-mail: brucet@cals.arizona.edu.
3
Department of Entomology, Michigan State University, E. Lan-
sing, MI 48824.
0022-0493/14/0496Ð0507$04.00/0 2014 Entomological Society of America
tance is a heritable decrease in sensitivity, citing an
expert panel of the Food and Agriculture Organization
of the United Nations (FAO 1979). The bookÕs glos-
sary gives a similar deÞnition: the inherited ability in
a strain of a pest to tolerate doses of toxicant that
would prove lethal to a majority of individuals in a
normal population,and adds: Laboratory documen-
tation of resistance, however, does not necessarily
indicate a current or impending loss of economic ef-
Þcacy in the Þeld.
The deÞnition stated here captures the essence of
the three deÞnitions from the National Research
Council (1986), which all emphasize any heritable
changes that reduce susceptibility of pests relative
to conspeciÞcs and do not include economic impact
as a criterion for resistance. The deÞnition offered
here includes resistance in organisms that are not
pests (Tabashnik and Johnson 1999, Pedra et al.
2004) and thus is broader than the earlier deÞni-
tions. With this general deÞnition of resistance as
the base, we deÞne three more speciÞc terms about
resistance: Þeld-evolved resistance, laboratory-se-
lected resistance, and practical resistance (Table 1;
Fig. 2).
Fig. 1. A century of arthropod resistance to pesticides. A) Number of arthropod pest species with resistance to one or
more pesticides. B) Records of arthropod pest resistance to pesticides. Each record consists of a published report of resistance
in one pest species to one pesticide in a particular geographic region during a particular time period (Mota-Sanchez et al.
2008). Less than 4% of the records reßect laboratory-selected resistance. Unlike some previous summaries, this Þgure excludes
resistance recorded in 40 species of nonpest arthropods, such as natural enemies and pollinators. As of 16 October 2013, totals
were 546 arthropod pest species with resistance and 11,254 resistance records. From 2000 to 2010, the number of resistance
records increased by 61% (from 6,617 to 10,661), while the number of species with resistance increased by only 4.6% (from
522 to 546) because resistance to at least one pesticide was already recorded in nearly all major arthropod pest species by
2000. The data were obtained from Whalon et al. (2013).
Table 1. General terms: pesticides and resistance
EfÞcacy: the extent to which a pesticide controls a pest population
Evolution of resistance: the process by which a genetically based decrease in susceptibility to a pesticide occurs in a population
Field-evolved resistance (Þeld-selected resistance): genetically based decrease in susceptibility to a pesticide in a population caused by
exposure to the pesticide in the Þeld
Incipient resistance: Þeld-evolved resistance in which a statistically signiÞcant, genetically based decrease in susceptibility has occurred,
but the percentage of resistant individuals is 1%
Laboratory-selected resistance: genetically based decrease in susceptibility to a pesticide in a population caused by exposure of the
population to the pesticide in the laboratory
Mode of action: how a pesticide works
Pesticide: a synthetic or natural substance that kills or harms pests (e.g., insecticides such as permethrin and Bt toxins; as well as
fungicides, herbicides, miticides, and nematicides)
Practical resistance (Þeld resistance): Þeld-evolved resistance that reduces pesticide efÞcacy and has practical consequences for pest
control
Resistance: genetically based decrease in susceptibility to a pesticide
Resistant individual: an individual with a genetically based decrease in susceptibility to a pesticide relative to other individuals of the
same species
Susceptibility (sensitivity): the tendency to be killed or harmed by a pesticide
Tolerance: We discourage use of this term because it has several deÞnitions, which fosters confusion. If the term is used, we recommend
using and citing the deÞnition of Finney (1971): the highest concentration of a particular pesticide that an individual can withstand
without being killed. We urge the use of inherent susceptibilityto signify the baseline susceptibility to a pesticide of a species before
it is exposed to the pesticide. We favor low level of resistanceor small decrease in susceptibilityto indicate a low level of resistance
Toxin: a poison produced by an organism (e.g., Bt toxin)
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 497
Field-Evolved Resistance, Laboratory-Selected
Resistance, and Practical Resistance
Field-evolved (or Þeld-selected) resistance is de-
Þned here as a genetically based decrease in suscep-
tibility of a population to a pesticide caused by expo-
sure to the pesticide in the Þeld. Because this
deÞnition uses the term pesticide,it is more general
than the deÞnition of Tabashnik et al. (2009) that
focuses on Bt crops and uses toxin,which speciÞes
a poison produced by an organism (e.g., a Bt toxin).
One can document Þeld-evolved resistance directly
by showing decreases in susceptibility through time
for a population, or indirectly by showing that a pop-
ulation with a history of relatively high exposure to a
pesticide is less susceptible than conspeciÞc popula-
tions that have had less exposure (Tabashnik 1994).
We use the term Þeldin the broad sense to mean
any environment in which the pesticide is used to
control a pest, such as Þelds of crops, greenhouses
(Janmaat and Myers 2003), or inside organisms that
host parasites (Wolstenholme and Kaplan 2012).
Whereas Þeld-evolved resistance results from expo-
sure to a pesticide in the Þeld, laboratory-selected
resistance results from exposure to a pesticide in the
laboratory (Table 1; Fig. 2). This distinction is impor-
tant because control of pests in the Þeld can be re-
duced by Þeld-evolved resistance, but not by resis-
tance that is conÞned to the laboratory. Further, the
genetic basis, mechanism, and magnitude of resistance
are not necessarily the same in laboratory-selected
and Þeld-evolved resistance (Zhang et al. 2012).
We deÞne practical resistanceas Þeld-evolved
resistance that reduces the efÞcacy of a pesticide and
has practical consequences for pest control (Table 1;
Fig. 2). The efÞcacy of a pesticide can be evaluated as
the percentage reduction in pest density caused by the
pesticide, which is calculated as the density of the pest
in an untreated control minus its density after expo-
sure to the pesticide, divided by its density in the
untreated control (Tabashnik et al. 2000, Burkness et
al. 2001). This yields 0% efÞcacy when the pest density
is the same in the pesticide treatment and the un-
treated control, and 100% efÞcacy when the pesticide
reduces the pest density to zero. Using analogous
calculations, one could also evaluate pesticide efÞcacy
as the percentage reduction in pest damage caused by
a pesticide.
The decrease in efÞcacy associated with resistance
can be calculated as the efÞcacy of a pesticide against
a susceptible population minus the efÞcacy of the
Table 2. Genetic, evolutionary, and ecological terms relevant to resistance
Additive resistance: in reference to a single resistance gene, inheritance in which the phenotype for heterozygotes is intermediate
between the phenotypes of susceptible and resistant homozygotes; or in reference to two or more resistance genes, inheritance in
which the effect of resistance genes on the phenotype is additive across the genes
Allele: any one particular form of the several forms of a gene
Dominant resistance: inheritance of resistance in which the phenotype is resistant for individuals with either one or two resistance alleles
at a genetic locus that determines susceptibility
Evolution: changes in allele frequency in a population
Fitness: the ability to survive and produce offspring relative to other individuals of the same species
Fitness cost: a trade-off in which alleles conferring resistance to a pesticide reduce Þtness in environments lacking the pesticide
Genotype: the genetic makeup of an organism
Incomplete resistance: resistance in which Þtness is lower for resistant individuals exposed to a pesticide relative to resistant individuals
not exposed to the pesticide
Monogenic resistance: resistance conferred primarily or entirely by a single gene
Polygenic resistance: resistance conferred by two or more genes
Phenotype: an observable trait or set of traits of an organism
Population: a group of individuals of the same species that live in a particular geographic area
Quantitative trait loci: genes that contribute to a quantitative trait, such as polygenic resistance
Recessive resistance: inheritance of resistance in which individuals have a resistant phenotype only if they have two resistance alleles at a
genetic locus that determines susceptibility
Resurgence: rapid increase in numbers of a pest population that was previously suppressed by a pesticide, natural enemy, or other factors
Table 3. Mechanisms and modes of resistance to one or more pesticides
Behavioral resistance: resistance conferred by changes in behavior that reduce exposure to a pesticide
Cross-resistance: resistance to a pesticide caused by exposure of a population to a different pesticide
Mechanism of resistance: a genetically based change in a particular phenotypic trait that decreases susceptibility to a pesticide, such as a
change in physiology, morphology, or behavior
Metabolic resistance: resistance conferred by enhanced enzymatic transformation of a pesticide to make it less toxic
Multiple resistance: resistance to more than one pesticide in a single organism; can be caused by cross-resistance, by independent
evolution of resistance to two or more pesticides used sequentially or simultaneously, or by a combination of cross-resistance and
independent evolution of resistance
Reduced penetration: resistance conferred by reduced entry of a pesticide into an organism
Sequential resistance: evolution of resistance at different times to different pesticides in the same population
Sequestration: resistance conferred by increases in the extent to which a pesticide that enters an organism is kept away from target sites,
yet remains inside the organism (Pittendrigh et al. 2008, Yu et al. 2010)
Target site: the part of an organism a pesticide interacts with to kill or harm the organism; it can be a speciÞc molecule or portion of a
molecule
Target site resistance (target site insensitivity): resistance conferred by changes in the target site that reduce the toxicity of the
pesticide (e.g., changes in pesticide binding sites that reduce binding of the pesticide)
498 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 107, no. 2
pesticide against a resistant population. Within the
category of practical resistance, the loss in efÞcacy
caused by resistance can vary from a statistically sig-
niÞcant but minor decrease (e.g., 10% decrease in
efÞcacy) to a complete failure of the product to con-
trol the pest (0% efÞcacy). Although the meaning is
similar for the terms practical resistanceand Þeld
resistance(Brent 1986), we prefer practical resis-
tancebecause it emphasizes resistance that has prac-
tical consequences for pest control and avoids the
inevitable confusion between the terms Þeld resis-
tanceand Þeld-evolved resistance(e.g., Van den
Berg et al. 2013).
A Web of Science search (conducted on 10 January
2014) for the topic Þeld-evolved resistanceidenti-
Þed 66 publications, including 45 published from 2010
to 2013. Because this search identiÞed only papers in
which Þeld-evolved resistanceappears in the title,
abstract, or key words, it underestimates the use of this
term. For example, the term Þeld-evolvedand either
resistanceor resistantoccurs in at least 18 addi-
tional publications, including seven highly cited arti-
cles about insecticide or herbicide resistance: Roush
and McKenzie (1987); Holt et al. (1993); Roush
(1994); Tabashnik et al. (2002, 2008a); Bates et al.
(2005); and Powles and Yu (2010). According to the
Web of Science, the 84 publications mentioned above
were authored by 200 academic, government, and
industry scientists from 20 countries and have been
cited 2,500 times.
Despite the widespread and growing use of the term
Þeld-evolved resistance,some industry scientists
prefer deÞnitions of resistance that include failure of
the product (reviewed by Whalon et al. 2008, Tabash-
nik et al. 2013). However, we agree with Brent and
Holloman (2007), who concluded: attempts to re-
strict in this way the meaning of such a broadly used
term as ÔresistanceÕ are bound to fail and to create
more confusion.For example, the Insecticide Resis-
tance Action Committee (IRAC), composed of mem-
bers from more than a dozen major agrochemical and
biotechnology companies, deÞnes resistance as a her-
itable change in the sensitivity of a pest population
that is reßected in the repeated failure of a product to
achieve the expected level of control when used ac-
cording to the label recommendation for that pest
species(IRAC 2013). The Þrst part of the IRAC
deÞnition, a heritable change in the sensitivity of a
pest population,is similar to the deÞnition of resis-
tance provided here (Table 1). The rest of the IRAC
deÞnition sets additional criteria that are problematic
for objectively identifying resistance and for proactive
detection and responses to resistance (Whalon et al.
2008, Tabashnik et al. 2013). By the time a product has
failed repeatedly, it is too late to respond most effec-
tively to resistance. The expected level of controlis
not speciÞed, which allows for variation in interpre-
tation. Moreover, this deÞnition excludes resistance in
any species that are not on the label.
Compared with the IRAC deÞnition of resistance,
the deÞnition of Þeld-evolved resistanceprovided
here has several advantages. It explicitly recognizes
Fig. 2. Field-evolved resistance, laboratory-selected re-
sistance, and practical resistance. Resistance, deÞned as a
genetically based decrease in susceptibility, can evolve in the
laboratory or Þeld. Practical resistance is Þeld-evolved resis-
tance that reduces pesticide efÞcacy and has practical con-
sequences for pest control. See text and Table 1 for details.
Table 4. Resistance monitoring and management
Bioassay: a test in which a group of live organisms is exposed to a pesticide to evaluate their susceptibility
Concentration: amount of pesticide per unit of another substance (e.g., micrograms of pesticide per milliliter of a suspension, milligrams
of pesticide per gram diet, or nanograms of pesticide per square centimeter of a plant surface)
Diagnostic concentration (or dose): concentration (or dose) of pesticide in a particular bioassay that kills all or nearly all susceptible
individuals but few or no resistant individuals
Dose: amount of pesticide eaten by or administered to an organism, such as milligrams eaten per gram of the organism or grams of
pesticide injected into an organism
EC
50
(median effective concentration): concentration of pesticide that causes a speciÞc response (such as failure to emerge as an
adult) in 50% of the individuals in a population
IC
50
(median inhibitory concentration): concentration of a pesticide that inhibits an essential process such as growth or feeding in 50%
of the individuals in a population
LC
50
(median lethal concentration): concentration of a pesticide that kills 50% of the individuals in a population
LD
50
(median lethal dose): dose of a pesticide that kills 50% of the individuals in a population
Refuge: a place where organisms are not exposed to a pesticide or a time during which organisms are not exposed to a pesticide
Resistance management: tactics implemented to delay evolution of resistance in pest populations
Resistance monitoring: systematic testing of organisms with bioassays, biochemical tests (e.g., enzyme assays), or molecular tests (e.g.,
DNA screening) to assess the frequency, magnitude, and spatial pattern of resistance
Resistance ratio: an index of the magnitude of resistance often calculated as the LC
50
for a resistant population divided by the LC
50
for a
susceptible population; it can also be calculated analogously for other parameters that specify the amount of pesticide that causes a
response in a speciÞed percentage of a population such as LC
95
,LD
50
,LD
95
,IC
50
,orIC
95
(but a ratio is usually not useful if it is based
on the percentage mortality or percentage inhibition at a single pesticide concentration)
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 499
that resistance results from evolution that occurs in
the Þeld, enables objective identiÞcation of resistance,
includes nontarget pests and beneÞcial species, and
most importantly, it facilitates proactive detection and
management of resistance (Tabashnik et al. 2013).
Brent (1986), Brent and Holloman (2007), and Wha-
lon et al. (2008) provide additional discussion of the
history of various deÞnitions of resistance as well as
their advantages and disadvantages.
Categories of Field-Evolved Resistance to Bt Crops
The impact of Þeld-evolved resistance on pest con-
trol can vary from none to severe, depending on many
factors such as the frequency and magnitude of resis-
tance, the pestÕs population density, the geographic
distribution of resistant populations, and the availabil-
ity of alternative controls (Tabashnik et al. 2009,
2013). Recognizing this spectrum, Tabashnik et al.
(2013) described and applied criteria for four cate-
gories of Þeld-evolved resistance to classify 24 cases
involving Bt crops, with each case representing re-
sponses to one Bt toxin of one pest species in one
country. These criteria explicitly acknowledge that
Þeld-evolved resistance is not all or none,which
facilitates objective classiÞcation of monitoring data
and may help to appropriately gauge management
actions depending on the severity of resistance
(Tabashnik et al. 2013).
We can readily identify the two opposite ends of the
spectrum of susceptibility and resistance: no decrease
in susceptibility and resistance that causes complete
failure of a product to control a pest. However, char-
acterizing the various levels of resistance between
these two extremes is challenging. Moreover, with
intermediate levels of resistance, the impact on pest
control of any given level of resistance varies from
situation to situation. Although the particular criteria
of Tabashnik et al. (2013) may not be optimal for other
sets of resistance monitoring data, the concept of spec-
ifying objective criteria to describe the level of Þeld-
evolved resistance is widely applicable. To illustrate
this concept, we review and extend the four categories
of Þeld-evolved resistance described by Tabashnik et
al. (2013), all of which entail statistically signiÞcant,
genetically based decreases in susceptibility in Þeld
populations: 1) incipient resistance, 1% resistant in-
dividuals; 2) early warning of resistance, 6% resis-
tant individuals; 3) 50% resistant individuals and
reduced efÞcacy expected, but not reported; and 4)
50% resistant individuals and reduced efÞcacy re-
ported. Only cases in the last category meet the cri-
teria for practical resistance. To provide a compre-
hensive classiÞcation, we add a Þfth category here:
6Ð50% resistant individuals, which was not seen in
any of the 24 cases of resistance monitoring data for Bt
crops reviewed by Tabashnik et al. (2013).
In each case, the percentage of resistant individuals
was estimated from survival at a diagnostic concen-
trationof the relevant Bt toxin that kills all or nearly
all susceptible individuals (Tabashnik et al. 2013).
Large increases in the concentration of pesticide kill-
ing 50% (LC
50
) of insects tested also indicate that
50% of the individuals in a population are resistant.
The resistance ratio, typically calculated as the LC
50
for a resistant population divided by the LC
50
for a
susceptible population (Table 3), reßects the magni-
tude of resistance. A resistance ratio 10 has been
used as a standard for categorizing cases of resistance
(Mota-Sanchez et al. 2002). When some populations
are highly resistant, LC
50
values and survival at a
diagnostic concentration tend to be correlated
(Tabashnik et al. 1993). In the early stages of resis-
tance evolution, however, detection of resistance is
more sensitive with diagnostic concentration tests
than evaluations of LC
50
(Roush and Miller 1986). F
1
and F
2
screens can be especially useful for detecting
rare recessive resistance alleles (Gould et al. 1997,
Andow and Alstad 1998).
Of the 24 cases based on resistance monitoring data
from eight countries for responses to six Bt toxins by
13 major pest species (12 lepidopterans and 1 cole-
opteran), 11 cases showed no statistically signiÞcant
decrease in susceptibility after 2Ð15 yr (median 7
yr) of exposure to Bt crops (Tabashnik et al. 2013).
Below we review the other 13 cases (Table 5), which
all meet the criteria for Þeld-evolved resistance, but
only Þve cases meet the criteria for practical resis-
tance.
Downes et al. (2010) used the term incipient re-
sistanceto describe a statistically signiÞcant increase
in the frequency of alleles conferring resistance to Bt
toxin Cry2Ab in Helicoverpa punctigera (Wallengren)
from Australia. All three cases of incipient resistance
are from Australia, where a rigorous, proactive mon-
itoring program has enabled early detection of resis-
tance to Bt toxins in H. punctigera and Helicoverpa
armigera (Hu¨bner) (Downes et al. 2010; Downes and
Mahon 2012a,b; Table 5). Based on results from the
2008Ð2009 Þeld season, Downes et al. (2010) found
that the frequency of alleles conferring resistance to
Cry2Ab was eight times higher in areas where Bt
cotton producing this toxin was grown compared with
noncropping areas. They also detected an 11-fold in-
crease from 2004Ð2005 to 2008Ð2009 in the frequency
of resistance to Cry2Ab in populations exposed to this
toxin. However, they estimated that the maximum
percentage of resistant individuals was 0.2%, which is
too low to reduce the efÞcacy of Bt cotton. Moreover,
the frequency of resistance to Cry2Ab did not increase
from 2008Ð2009 to 2010Ð2011 (Downes and Mahon
2012a). These results show that the statistically sig-
niÞcant yet small increases in resistance allele fre-
quency characteristic of incipient resistance do not
necessarily indicate that further increases in resis-
tance are imminent.
Zhang et al. (2011) used the phrase early warning
of resistance to describe a statistically signiÞcant in-
crease in the percentage of individuals with resistance
to Bt toxin Cry1Ac in H. armigera from northern
China. Their 2010 survey showed that survival at a
diagnostic concentration of Cry1Ac was signiÞcantly
higher for 13 Þeld populations from northern China
where exposure to Bt cotton was extensive, relative to
500 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 107, no. 2
two Þeld populations from northwestern China where
exposure to Bt cotton was limited. For the populations
from northern China surveyed in 2010, the mean sur-
vival at the diagnostic concentration was 1.3% (range:
0Ð2.6%) compared with 0% for the populations from
northwestern China and a susceptible laboratory
strain (Zhang et al. 2011). Results of screening in 2009
and 2011 also support the conclusion that exposure to
Bt cotton increased the frequency of H. armigera re-
sistance to Cry1Ac in northern China, with up to 5.4%
resistant individuals in a population (Zhang et al. 2012,
Jin et al. 2013).
In total, four cases of early warningof resistance
show a statistically signiÞcant increase in resistance,
with the percentage of resistant individuals between
1 and 6% (Table 5). The other three cases are Þeld-
evolved resistance to Cry1Ac in Bt cotton by Pectino-
phora gossypiella (Saunders) in China (Wan et al.
2012), and resistance to Cry1Ab in Bt corn by Ostrinia
furnacalis (Guene´e) in the Philippines and Diatraea
saccharalis (F.) in the southern United States (Huang
et al. 2012).
As with incipient resistance, the four cases of early
warningof resistance entail a frequency of resistance
that is too low to substantially reduce the efÞcacy of
Bt crops. However, Þeld-evolved resistance with 1%
resistant individuals detected warrants consideration
of enhanced actions to manage resistance, such as
increases in monitoring, refuge requirements, and al-
ternative methods of control. It will be instructive to
see what actions, if any, are taken in these four cases
and how this affects the trajectory of resistance.
In the Þve most severe cases of Þeld-evolved resis-
tance to Bt crops, one or more pest populations had
50% resistant individuals and reduced efÞcacy of the
Bt crop was reported (Table 5). These Þve cases entail
practical resistance to Bt corn in three pests: Busseola
fusca (Fuller), Diabrotica virgifera virgifera LeConte,
and Spodoptera frugiperda (J.E. Smith); and practical
resistance to Bt cotton in two pests: Helicoverpa zea
(Boddie) and P. gossypiella.
In the U.S. territory of Puerto Rico, S. frugiperda
(fall armyworm) evolved resistance to Bt corn pro-
ducing Cry1F in 3 yr, which is the fastest documented
case of Þeld-evolved resistance to a Bt crop with re-
duced efÞcacy reported (Storer et al. 2010, 2012). This
is also the Þrst case of resistance leading to withdrawal
of a Bt crop from the marketplace. In 2011, 4 yr after
Dow Agro-Sciences and Pioneer Hi-Bred Interna-
tional voluntarily stopped selling Cry1F corn in Puerto
Rico, high levels of resistance persisted in the Þeld
(Storer et al. 2012).
Practical resistance to Bt corn producing Cry1Ab
occurred in B. fusca (maize stem borer) in South
Africa in 8 yr (Van Rensburg 2007, Tabashnik et al.
2009, Van den Berg et al. 2013), with striking parallels
Table 5. Field-evolved resistance to Bt crops in nine pest species classified into categories ranging in severity from incipient resistance
to practical resistance
a
Pest
a
Crop Toxin Country Practical
resistance
Incipient resistance (1% resistant individuals)
H. armigera
b
Cotton Cry1Ac Australia No
H. armigera
b
Cotton Cry2Ab Australia No
H. punctigera
c
Cotton Cry2Ab Australia No
Early warning (1Ð6% resistant individuals)
D. saccharalis
d
Corn Cry1Ab United States No
H. armigera
e
Cotton Cry1Ac China No
O. furnacalis
f
Corn Cry1Ab Philippines No
P. gossypiella
g
Cotton Cry1Ac China No
50% resistant individuals and reduced efÞcacy
expected
H. zea
h
Cotton Cry2Ab United States ?
i
Practical resistance (50% resistant individuals and
reduced efÞcacy reported)
B. fusca
j
Corn Cry1Ab South Africa Yes
D. v. virgifera
k
Corn Cry3Bb United States Yes
H. zea
l
Cotton Cry1Ac United States Yes
P. gossypiella
m
Cotton Cry1Ac India Yes
S. frugiperda
n
Corn Cry1F United States Yes
a
Adapted from Tabashnik et al. 2013; no cases occurred with 6% to 50% resistant individuals.
b
Downes and Mahon 2012b, Tabashnik et al. 2013.
c
Downes et al. 2010, Downes and Mahon 2012a.
d
Huang et al. 2012.
e
Zhang et al. 2011, 2012; Jin et al. 2013.
f
Alcantara et al. 2011.
g
Wan et al. 2012.
h
Ali and Luttrell 2007; Tabashnik et al. 2009, 2013.
i
Practical resistance is expected, but has not been reported.
j
Van Rensburg 2007, Kruger et al. 2011, Van den Berg et al. 2013.
k
Gassmann et al. 2011, 2012.
l
Luttrell et al. 2004; Ali et al. 2006; Tabashnik et al. 2008a,b.
m
Monsanto 2010, Dhurua and Gujar 2011.
n
Storer et al. 2010, 2012.
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 501
to S. frugiperda resistance to Cry1F corn. In both cases,
proactive resistance monitoring was not conducted
and observations of reduced efÞcacy in the Þeld pre-
ceded documentation of resistance with bioassays
(Kruger et al. 2009, 2011, 2012; Storer et al. 2010, 2012;
Van den Berg et al. 2013). In South Africa, however,
Cry1Ab corn was not withdrawn from sales, with 1.8
million hectares planted in 2012 (James 2012). This
yielded widespread resistance and hundreds of re-
ports of product failure during the 2010Ð2011 and
2011Ð2012 seasons (Kruger et al. 2009, Van den Berg
et al. 2013). Monsanto, the company that developed
the predominant type of Cry1Ab corn grown in South
Africa, compensated growers for their insecticide
sprays on this Bt corn (Kruger et al. 2009). Large scale
planting of two-toxin Bt corn producing Cry1A.105
(similar to Cry1Ab; Tabashnik et al. 2009) and Cry2Ab
began during the 2012Ð2013 season in South Africa
(Van den Berg et al. 2013).
Field and laboratory data show that control prob-
lems in the Þeld during 2009 and 2010 were associated
with resistance to Cry3Bb in Bt corn in some Iowa
populations of D. v. virgifera (western corn rootworm;
Gassmann et al. 2011, 2012; Gassmann 2012). In prob-
lemÞelds, which had severe damage to Cry3Bb corn
caused by rootworms, Cry3Bb corn had been planted
for 3 to 7 yr (Gassmann et al. 2011, 2012). A 2011 Þeld
study of two of the problem Þelds identiÞed in 2009
found that D. v. virgifera emergence did not differ
signiÞcantly between Cry3Bb corn and non-Bt corn
(Gassmann 2012).
In a letter to the EPA, 22 public sector corn ento-
mologists stated that greater than expected damage
to Cry3Bb1 corn was Þrst seen widely during 2009, and
problem areas had been reported in Illinois, Iowa,
Minnesota, Nebraska, and South Dakota by 2011 (Por-
ter et al. 2012). They concluded that all available
evidence converges in implicating Þeld-evolved re-
sistance to Cry3Bb1 as the most likely cause of Ôgreater
than expected damageÕ in rootworm problem Þelds.
This urgent problem has been addressed in several
recent publications (Tabashnik and Gould 2012, Cul-
len et al. 2013, Devos et al. 2013, DiFonzo et al. 2013,
Gray 2013) and by a ScientiÞc Advisory Panel con-
vened in December 2013 by the EPA (2013b). In
addition, Monsanto (2013) has sponsored a new com-
petitive grant program that includes research on man-
aging corn rootworm resistance to Bt corn.
Both cases of practical resistance to Cry1Ac in Bt
cotton (P. gossypiella in India and H. zea in the United
States; Table 5) have been controversial, stimulating
discussion about bioassay data based on insects de-
rived from Bt crops (Tabashnik and Carrie`re 2010,
Tabashnik et al. 2013). Sampling insects from Bt crops
is essential for resistance monitoring (Tabashnik et al.
2008a,b; 2009; 2013) and has been important in doc-
umenting all three cases of practical resistance to Bt
corn (Van Rensburg 2007; Storer et al. 2010, 2012;
Gassmann et al. 2011, 2012; Kruger et al. 2011;
Gassmann 2012; Van den Berg et al. 2013). The pri-
mary goal of resistance monitoring is to detect resis-
tance soon enough to enable proactive management;
failure to sample insects from Bt crops can delay de-
tection of resistance (Tabashnik et al. 2009, 2013).
Although survival on a Bt crop alone does not consti-
tute evidence of resistance, bioassays of progeny de-
rived from such survivors can determine if the survi-
vors were resistant. For example, bioassays showed
that B. fusca and S. frugiperda surviving on Bt corn
were resistant (Van Rensburg 2007, Storer et al. 2010),
but Helicoverpa surviving on Bt cotton in Australia
during 2006 and D. v. virgifera surviving on Bt corn in
Missouri during 2005 and 2006 were not (Hibbard et
al. 2010, Downes and Mahon 2012a). Documentation
of Þeld-evolved resistance also requires evidence that
the frequency of resistance alleles has increased in
response to selection. Data provide strong evidence of
Þeld-evolved resistance if they show that the fre-
quency of resistance alleles is higher in insects derived
from Bt crops (or from any population with a history
of exposure to Bt crops) relative to insects from con-
speciÞc susceptible populations.
Resistance of P. gossypiella (pink bollworm) to Bt
cotton producing Cry1Ac was Þrst detected with lab-
oratory bioassays of the offspring of insects collected
from non-Bt cotton Þelds in 2008 in the state of Gujarat
in western India (Dhurua and Gujar 2011). India ranks
second in cotton production, behind only China, and
Gujarat accounted for one-third of IndiaÕs cotton pro-
duction in 2009Ð2010, which is equivalent to about
half of the annual cotton production in the United
States during 2009 and 2010 (FAO 2011, Desh Gujarat
2013). Monsanto (2010), the company that developed
Cry1Ac cotton, reported in a press release that its
monitoring of the 2009 cotton crop conÞrmedP.
gossypiella resistance to Cry1Ac in four districts of
Gujarat. This widespread resistance documented with
laboratory bioassays was associated with unusually
high abundance of both larvae on Cry1Ac cotton
(Monsanto 2010) and moths caught in pheromone
traps (IndiaÕs Genetic Engineering Approval Commit-
tee [GEAC] 2010).
As far as we know, the details of MonsantoÕs meth-
ods and results remain unpublished. Nonetheless, a
presentation at a scientiÞc meeting by Monsanto sci-
entists (Dennehy et al. 2010) indicated that most of
their bioassay data from populations sampled in 2009
were obtained from insects derived from Bt cotton. A
recent summary of this work coauthored by Monsanto
scientists (Sumerford et al. 2013) concluded that, in
laboratory bioassays of P. gossypiella populations sam-
pled in 2009, median survival was 70% at a diagnostic
concentration of Cry1Ac (500 times higher than the
LC
50
of susceptible populations). Sumerford et al.
(2013) added, During 2010, resistance also was de-
tected in populations collected from non-Bt cotton.
Bagla (2010) reported in the journal Sciencethat
Dr. Keshav Raj Kranthi, Director of IndiaÕs Central
Institute for Cotton Research, questioned MonsantoÕs
methods and its conclusion of Þeld-evolved resistance
to Bt cotton in P. gossypiella. According to IndiaÕs
GEAC (2010), Kranthi indicated that because Mon-
santoÕs bioassay data were derived from larvae col-
lected from Bt cotton instead of conventional cotton,
502 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 107, no. 2
their inferences about resistance were not correct. As
explained above, however, testing insects derived
from Bt crops is an essential component of resistance
monitoring. Consistent with this principle, Bagla
(2010) reported that Monsanto asserted that its meth-
ods (which include testing of insects from Bt cotton)
are standard practice.Furthermore, resistance in
insects derived from non-Bt cotton was reported sub-
sequently by Dhurua and Gujar (2011) and Sumerford
et al. (2013).
Meanwhile, since 2008, farmers in India have almost
completely switched from cotton producing only one
Bt toxin (Cry1Ac) to cotton that makes two Bt toxins
(Cry1Ac and Cry2Ab; Choudhary and Gaur 2010,
Monsanto 2010). The main advantage of this two-toxin
cotton against P. gossypiella is that Cry2Ab kills larvae
resistant to Cry1Ac (Tabashnik et al. 2002, Dhurua and
Gujar 2011).
As with P. gossypiella in India, documentation of
practical resistance of H. zea to Cry1Ac in the United
States includes evidence of resistance in samples from
Bt crops and other sources. Eight strains of H. zea
derived during 2003Ð2006 from Þeld sources other
than Bt crops had resistance ratios 100 (median
630), including two strains with resistance ratios
1,000 (Ali et al. 2006, Luttrell and Ali 2007, Tabashnik
et al. 2008b). In this case, the initial evidence of Þeld-
evolved resistance in the southeastern United States
came in 2002, 6 yr after commercialization of Bt cotton
in that region (Luttrell et al. 2004, Ali et al. 2006). The
extensive evidence conÞrming this case of practical
resistance includes 50% survival at a diagnostic con-
centration of Cry1Ac for four strains derived from the
Þeld in 2003 (Ali et al. 2006) and a signiÞcant associ-
ation between larval survival on Bt cotton leaves and
decreased susceptibility to Cry1Ac in bioassays
(Tabashnik et al. 2008b). Similar to the evidence from
India, the documentation of H. zea resistance includes
unacceptable levels of boll damagein problem Þelds
(Luttrell et al. 2004) as well as decreased susceptibility
to Cry1Ac in laboratory bioassays (Ali et al. 2006,
Luttrell and Ali 2007, Tabashnik et al. 2008b).
Despite the results summarized above, some scien-
tists have challenged the conclusion of practical re-
sistance to Bt cotton in H. zea (Moar et al. 2008,
Luttrell and Jackson 2012, Sumerford et al. 2013). One
of their principal arguments is that the documentation
relies on bioassays of insects collected from Bt crops
(Moar et al. 2008, Sumerford et al. 2013). However,
testing insects derived from Bt crops is essential for
resistance monitoring and H. zea resistance to Cry1Ac
was detected in samples from sources other than Bt
crops. In particular, Sumerford et al. (2013) stated that
the data for H. zea demonstrate strikingly elevated
LC
50
values, mostly from populations collected from
non-Bt crops.
In the United States from 2003 to 2011, Cry1Ac
cotton was progressively replaced by transgenic cot-
ton making two Bt toxins, predominantly Cry1Ac and
Cry2Ab (Bre´vault et al. 2013). Field-evolved resis-
tance of H. zea resistance to Cry2Ab in the southeast-
ern United States is categorized as 50% resistant
individuals detected, with reduced efÞcacy of the Bt
crop expected. Like both cases of Þeld-evolved resis-
tance to Bt cotton producing Cry1Ac, this case has
been controversial.
The data documenting resistance to Cry2Ab in-
clude a signiÞcant increase in the proportion of pop-
ulations screened that had an LC
50
value greater than
the diagnostic concentration of toxin (150
g Cry2Ab
per milliliter of diet), which indicates 50% survival
at the diagnostic concentration (Ali and Lutrell 2007,
Tabashnik et al. 2009). Based on this criterion, the
percentage of H. zea populations tested that were
resistant to Cry2Ab rose from 0% in 2002 to 50% in
2005, only 2 yr after commercialization of Bt cotton
producing Cry2Ab and Cry1Ac (Ali and Lutrell 2007,
Tabashnik et al. 2009). Three populations sampled
from non-Bt plants in Arkansas in 2005 had such low
mortality in bioassays that LC
50
values could not be
calculated, but were estimated to be 400
g Cry2Ab
per milliliter of diet (Ali and Luttrell 2007).
In addition, data from Þeld populations in Arkansas
show that mortality caused by a diagnostic concen-
tration of Cry2Ab decreased substantially in 2010 com-
pared with the previous 4 yr (Jackson et al. 2011). This
evidence of Þeld-evolved resistance to Cry2Ab coin-
cided with higher abundance of H. zea in the Þeld and
increased insecticide sprays targeting H. zea on Bt
cotton in 2010 (Jackson et al. 2011). In the United
States from 1999 to 2011, the percentage of Bt cotton
producing two toxins increased from 0 to 90%, while
the sprays against H. zea on Bt cotton tripled (Williams
2012, Tabashnik et al. 2013). Although factors other
than resistance could contribute to increased sprays
against H. zea on Bt cotton, the data refute the alter-
native hypothesis offered by Luttrell and Jackson
(2012) that the increased abundance of this pest in the
midsouthern United States was associated with in-
creased planting of corn (Tabashnik et al. 2013).
Overall, the data summarized above include some
degree of Þeld-evolved resistance to Bt crops in nine
target pests, ranging from incipient resistance to prac-
tical resistance. Although Sumerford et al. (2013) ex-
pressed concern that claims of Þeld-evolved resistance
could trigger unnecessary resistance remediation,
we are not aware of any examples indicating this has
occurred in the 18 yr since Bt crops were commer-
cialized. Conversely, the Þve cases of practical resis-
tance to Bt crops (Table 5) are associated with failure
to comply with refuge requirements or inadequate
refuge requirements (Storer et al. 2010, 2012; Kruger
et al. 2012; Tabashnik et al. 2013; Van den Berg et al.
2013). Despite three cases of practical resistance to Bt
crops in the United States (Table 5), the observed
association between limited planting of refuges and
rapid evolution of resistance, and recommendations
from public sector scientists to maintain or increase
refuge requirements (EPA 2002, Knight 2003, Al-
yokhin 2011, Tabashnik and Gould 2012), the EPA has
greatly reduced refuge requirements for Bt crops
since 2007. Currently in the United States, refuges of
non-Bt corn can be as little as 5% of the total area
planted to corn (EPA 2011a,b; 2013a). Refuges of
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 503
non-Bt cotton are not required for Bt cotton in most
of the nation, primarily because of the presence of
non-Bt host plants other than cotton that are consid-
ered naturalrefuges (EPA 2007).
Conclusion
We hope that the deÞnitions provided here will
facilitate improved understanding and management of
resistance. Results from extensive resistance monitor-
ing conducted for Bt crops demonstrate that increases
in the frequency of resistance in pest populations can
be detected before reduced efÞcacy of Bt crops occurs
in the Þeld. Although the term practical resistanceis
useful because it recognizes resistance that has prac-
tical consequences, the broader term Þeld-evolved
resistanceis essential for proactive detection and
management of resistance. In the absence of consen-
sus, explicitly stating the deÞnition used in a particular
case and citing a relevant reference can avoid confu-
sion.
To expedite progress, we urge scientists in the pub-
lic and private sectors to publish and analyze their
resistance monitoring data in conjunction with rele-
vant information on management practices, including
the history of pest exposure to the pesticide. System-
atic analyses of such data can yield insights about the
relationship between management practices and re-
sistance evolution (Hutchison et al. 2010; Tabashnik et
al. 2010, 2013; Carrie`re et al. 2012). In general, the
sooner steps are taken to delay resistance, the more
likely they are to succeed. Finally, rather than debat-
ing deÞnitions of resistance, we encourage discussion
and analysis on a case-by-case basis engaging resis-
tance experts, agricultural economists, stakeholders,
industry scientists, and regulators to determine the
management actions that will be most useful in re-
sponse to speciÞc data on the magnitude, distribution,
and impact of resistance.
Acknowledgments
We thank Mark Sisterson and two anonymous reviewers
for comments on the manuscript; and Gene Reagan, James
Ottea, and Patricia Pietrantonio for their contributions to
earlier drafts of deÞnitions of resistance terms in response to
the EPA initiative. Funding was provided by U.S. Department
of Agriculture Biotechnology Risk Assessment Grant Award
2011-33522-30729.
References Cited
Alcantara, E., A. Estrada, V. Alpuerto, and G. Head. 2011.
Monitoring Cry1Ab susceptibility in Asian corn borer
(Lepidoptera: Crambidae) on Bt corn in the Philippines.
Crop Prot. 30: 554Ð559.
Ali, M. I., and R. G. Luttrell. 2007. Susceptibility of boll-
worm and tobacco budworm (Noctuidae) to Cry2Ab2
insecticidal protein. J. Econ. Entomol. 100: 921Ð931.
Ali, M. I., R. G. Luttrell, and S. Y. Young, III. 2006. Suscep-
tibility of Helicoverpa zea and Heliothis virescens (Lepi-
doptera: Noctuidae) populations to Cry1Ac insecticidal
protein. J. Econ. Entomol. 99: 164Ð175.
Alyokhin, A. 2011. Scant evidence supports EPAÕs pyra-
mided Bt corn refuge size of 5%. Nat. Biotechnol. 529:
577Ð578.
Andow, D. A., and D. N. Alstad. 1998. F2 screen for rare
resistance alleles. J. Econ. Entomol. 91: 572Ð578.
Bagla, P. 2010. Hardy cotton-munching pests are latest blow
to GM crops. Science 327: 1439.
Bates, S. L, J.-Z. Zhao, R. T. Roush, and A. M. Shelton. 2005.
Insect resistance management in GM crops: past, present
and future. Nat. Biotechnol. 23: 57Ð62.
Brent, K. J. 1986. Detection and monitoring of resistant
forms: an overview, pp. 298Ð312. In National Research
Council (ed.), Pesticide resistance: strategies and tactics
for management. National Academy Press, Washington,
DC.
Brent, K. J., and D. W. Holloman. 2007. Fungicide resis-
tance in crop pathogens: how can it be managed? FRAC
Monograph 1 2nd ed., Fungicide Resistance Action Com-
mittee, CropLife International, Brussels, Belgium.
(http://www.frac.info/publication/anhang/FRAC_
Mono1_2007_100dpi.pdf)
Bre´vault, T., S. Heuberger, M. Zhang, C. Ellers-Kirk, X. Ni,
L. Masson, X. Li, B. E. Tabashnik, and Y. Carrie`re. 2013.
Potential shortfall of pyramided Bt cotton for resistance
management. Proc. Natl. Acad. Sci. U.S.A. 110: 5806 Ð5811.
Burkness, E. C., W. D. Hutchison, P. C. Bolin, D. W. Bartels,
D. F. Warnock, and D. W. Davis. 2001. Field efÞcacy of
sweet corn hybrids expressing a Bacillus thuringiensis
toxin for management of Ostrinia nubilalis (Lepidoptera:
Crambidae) and Helicoverpa zea (Lepidoptera: Noctu-
idae). J. Econ. Entomol. 94: 197Ð203.
Carrie`re, Y., C. Ellers-Kirk, K. Harthfield, G. Larocque, B.
Degain, P. Dutilleul, T. J. Dennehy, S. E. Marsh, D. W.
Crowder, X. Li, et al. 2012. Large-scale, spatially explicit
test of the refuge strategy for delaying insecticide resis-
tance. Proc. Natl. Acad. Sci. U.S.A. 109: 775Ð780.
Choudhary, B., and K. Gaur. 2010. Bt cotton in India: a
country proÞle. International Service for the Acquisition
of Agri-biotech Applications, Ithaca, NY. (http://
www.isaaa.org/resources/publications/biotech_crop_
proÞles/bt_cotton_in_india-a_country_proÞle/download/
Bt_Cotton_in_India-A_Country_ProÞle.pdf)
Coetzee, M., and L. L. Koekemoer. 2013. Molecular system-
atics and insecticide resistance in the major African ma-
laria vector Anopheles funestus. Annu. Rev. Entomol. 58:
393Ð412.
Cullen, E. M., M. E. Gray, A. J. Gassmann, and B. E. Hibbard.
2013. Resistance to Bt corn by western corn rootworm
(Coleoptera: Chrysomelidae) in the U.S. corn belt. J. Int.
Pest Manag. 4: D1ÐD6. doi: http://dx.doi.org/10.1603/
IPM13012
Dekker, J. 1986. Preventing and managing fungicide resis-
tance, pp. 298Ð312. In National Research Council (ed.),
Pesticide resistance: strategies and tactics for manage-
ment. National Academy Press, Washington, DC.
Dennehy, T. J., G. P. Head, W. Moar, J. Greenplate, K. S.
Mohan, K. C. Ravi, P. J. Suresh, and S. Parimi. 2010.
Status of PBW resistance to Bollgard cotton in India.
Presentation at the Entomological Society of America
58th Annual Meeting, San Diego, CA. (http://esa.
confex.com/esa/2010/webprogram/Paper49973.html)
Desh Gujarat. 2013. State wise Þgures of cotton production
in India in last four years, even with lower production
Gujarat continues to top. 22 March 2013. (http://
deshgujarat.com/2013/03/22/state-wise-Þgures-of-
cotton-production-in-india-in-last-four-years-even-
with-lower-production-gujarat-continues-to-top/)
504 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 107, no. 2
Devos, Y., L. N. Meihls, J. Kiss, and B. E. Hibbard. 2013.
Resistance evolution to the Þrst generation of genetically
modiÞed Diabrotica-active Bt-maize events by western
corn rootworm: management and monitoring consider-
ations. Transgenic Res. 22: 269Ð299.
Dhurua, S., and G. T. Gujar. 2011. Field-evolved resistance
to Bt toxin Cry1Ac in the pink bollworm, Pectinophora
gossypiella (Saunders) (Lepidoptera: Gelechiidae), from
India. Pest Manag. Sci. 67: 898Ð903.
DiFonzo, C., T. Baute, R. Hammond, C. Krupke, A. Michel,
A. Schaafsma, E. Shields, J. Smith, and J. Tooker. 2013.
Consensus recommendation: managing western corn
rootworm resistance to Bt on the fringe. (http://www.
noticeandcomment.com/Consensus-recommendation-
Managing-Western-Corn-Rootworm-Resistance-to-Bt-
on-the-Fringe-fn-80225.aspx)
Downes, S., and R. Mahon. 2012a. Evolution, ecology and
management of resistance in Helicoverpa spp. to Bt cotton
in Australia. J. Invertebr. Pathol. 110: 281Ð286.
Downes, S., and R. Mahon. 2012b. Successes and challenges
of managing resistance in Helicoverpa armigera to Bt
cotton in Australia. GM Crops and Food 3: 228Ð234.
Downes, S., T. Parker, and R. Mahon. 2010. Incipient resis-
tance of Helicoverpa punctigera to the Cry2Ab Bt toxin in
Bollgard II cotton. PLoS ONE 5: e12567. doi: http://
dx.doi.org/10.1371/journal.pone.0012567
Enayati, A., and J. Hemingway. 2010. Malaria management:
past, present, and future. Annu. Rev. Entomol. 55: 569Ð
591.
[EPA] Environmental Protection Agency. 2002. Final
meeting minutes. FIFRA ScientiÞc Advisory Panel Meet-
ing Held August 27Ð29, 2002. Corn Rootworm Plant-In-
corporated Protectant Non-target Insect and Insect
Resistance Management Issues. (http://www.epa.gov/
scipoly/sap/meetings/2002/082702_mtg.htm#minutes)
[EPA] U. S. Environmental Protection Agency. 2007.
Pesticide News Story: EPA Approves Natural Refuge
for Insect Resistance Management in Bollgard II Cot-
ton. (http://www.epa.gov/oppfead1/cb/csb_page/
updates/2007/bollgard-cotton.htm)
[EPA] Environmental Protection Agency. 2011a. Biopesti-
cides Registration Action Document. MON 89034
TC1507 MON 88017 DAS-59122Ð7 (SmartStax)
B.t. Corn Seed Blend. (http://www.regulations.gov/
#!documentDetail;DEPA-HQ-OPP-2011Ð0362-0002)
[EPA] Environmental Protection Agency. 2011b. Notice of
Pesticide Registration 67979Ð17. Bt11 x DAS-59122Ð7 x
MIR604 x TCI507 Corn. (http://www.kellysolutions.
com/erenewals/documentsubmit/KellyData%5CGA%5
Cpesticide%5CMSDS%5C67979%5C67979 Ð17%5C67979 Ð7_
BT11_X__DAS_59122_7_X_MIR604_X_TC1507_CORN__
ALTERNATE_BRAND_NAME__AGRISURE_3122__8_
16_2011_11_10_07_AM.pdf)
[EPA] Environmental Protection Agency. 2013a. Current
& Previously Registered Section 3 PIP Registrations.
(http://www.epa.gov/pesticides/biopesticides/pips/pip_
list.htm)
[EPA] Environmental Protection Agency. 2013b. Decem-
ber 4Ð6, 2013: ScientiÞc Uncertainties Associated with
Corn Rootworm Resistance Monitoring for Bt corn Plant
Incorporated Protectants (PIPs). (http://www.epa.gov/
scipoly/sap/meetings/2013/120413meeting.html)
[FAO] Food and Agriculture Organization. 1979. Pest re-
sistance to pesticides and crop loss assessment. FAO Plant
Production and Protection Paper No. 6/2. FAO, Rome,
Italy.
[FAO] Food and Agriculture Organization. 2011.
FAOSTAT: Food and Agricultural commodities produc-
tion. (http://faostat.fao.org/site/339/default.aspx)
Finney, D. J. 1971. Probit analysis, 3rd ed. Cambridge Uni-
versity Press, London, United Kingdom.
Fungicide Resistance Action Committee. 2013. FRAC list of
plant pathogenic organisms resistant to disease control
agents. Revised January 2013. (http://www.frac.info/)
Gassmann, A. J. 2012. Field-evolved resistance to Bt maize
by western corn rootworm: predictions from the labora-
tory and effects in the Þeld. J. Invertebr. Pathol. 110:
287Ð293.
Gassmann, A. J., Y. Carrie`re, and B. E. Tabashnik. 2009.
Fitness costs of insect resistance to Bacillus thuringiensis.
Annu. Rev. Entomol. 54: 147Ð163.
Gassmann, A. J., J. L. Petzold-Maxwell, R. S. Keweshan, and
M. W. Dunbar. 2011. Field-evolved resistance to Bt
maize by western corn rootworm. PLoS ONE 6: e22629.
Gassmann, A. J., J. L. Petzold-Maxwell, R. S. Keweshan, and
M. W. Dunbar. 2012. Western corn rootworm and Bt
maize: challenges of pest resistance in the Þeld. GM Crops
Food 3: 1Ð10.
[GEAC] Genetic Engineering Approval Committee. 2010.
Decisions taken in the 100th Meeting of the Genetic
Engineering Approval Committee (GEAC) held on 12
May 2010. (www.envfor.nic.in/divisions/csurv/geac/de-
cision-may-100.pdf)
Gould, F., A. Anderson, A. Jones, D. Sumerford, D. G.
Heckel, J. Lopez, S. Micinski, R. Leonard, and M. Laster.
1997. Initial frequency of alleles for resistance to Bacillus
thuringiensis toxins in Þeld populations of Heliothis vire-
scens. Proc. Natl. Acad. Sci. U.S.A. 94: 3519Ð3523.
Gray, M. E. 2013. Soil insecticide use on Bt corn expected
to increase this spring across much of Illinois. Pest man-
agement and crop development bulletin, March 28, 2013,
University of Illinois, Champaign-Urbana, IL.
Hartl, D. L. 1981. A primer of population genetics. Sinauer,
Sunderland MA.
Heckel, D. G. 2012. Insecticide resistance after Silent
Spring. Science 337: 1612Ð1614.
Heap, I. 2013. International survey of herbicide resistant weeds.
(http://www.weedscience.org/summary/home.aspx)
Hibbard, B. E., T. L. Clark, M. R. Ellersieck, L. N. Meihls,
A. A. El Khishen, V. Kaster, H.-Y. Steiner, and R. Kurtz.
2010. Mortality of western corn rootworm larvae on
MIR604 transgenic maize roots: Þeld survivorship has no
signiÞcant impact on survivorship of F1 progeny on
MIR604. J. Econ. Entomol. 103: 2187Ð2196.
Holt, J. S., S. B. Powles, and J.A.M. Holtum. 1993. Mecha-
nisms and agronomic aspects of herbicide resistance.
Annu. Rev. Plant Physiol. Plant Mol. Biol. 44: 203Ð229.
Huang, F., M. N. Ghimire, B. R. Leonard, C. Davies, R. Levy,
and J. Baldwin. 2012. Extended monitoring of resistance
to Bacillus thuringiensis Cry1Ab maize in Diatraea sac-
charalis (Lepidoptera: Crambidae). GM Crops Food 3:
245Ð254.
Hutchison, W. D., E. C. Burkness, P. D. Mitchell, R. D. Moon,
T. W. Leslie, S. J. Fleischer, M. Abrahamson, K. L. Ham-
ilton, K. L. Steffey, M. E. Gray, et al. 2010. Areawide
suppression of European corn borer with Bt maize reaps
savings to non-Bt maize growers. Science 330: 222Ð225.
[IRAC] Insecticide Resistance Action Committee. 2013.
Resistance deÞnition. (http://www.irac-online.org/
about/resistance/)
Jackson, R. E., A. Catchot, J. Gore, and S. D. Stewart. 2011.
Increased survival of bollworms on Bollgard II cotton
compared to lab-based colony, pp. 893Ð 894. In S. Boyd, M.
Huffman, and B. Robertson (eds.), Proceedings, 2011
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 505
Beltwide Cotton Conferences, 4 Ð7 January 2011, Atlanta,
GA. National Cotton Council of America, Memphis, TN.
James, C. 2012. Global status of commercialized biotech/
GM Crops: 2012. ISAAA brief no. 44. International Service
for the Acquisition of Ag-biotech Applications, Ithaca, NY.
Janmaat, A. F., and J. H. Myers. 2003. Rapid evolution and
the cost of resistance to Bacillus thuringiensis in green-
house populations of cabbage loopers, Trichoplusia ni.
Proc. R. Soc. Lond. B 270: 2263Ð2270.
Jin, L., Y. Wei, L. Zhang, Y. Yang, B. E. Tabashnik, and Y. Wu.
2013. Dominant resistance to Bt cotton and minor cross-
resistance to Bt toxin Cry2Ab in cotton bollworm from
China. Evol. Appl. 6: 1222Ð1235. doi: http://dx.doi.org/
10.1111/eva. 12099
Knight, J. 2003. Agency Ôignoring its advisorsÕ over Bt maize.
Nature 422: 5.
Kruger, M., J.B.J. Van Rensburg, and J. Van den Berg. 2009.
Perspective on the development of stem borer resistance
to Bt maize and refuge compliance at the Vaalharts irri-
gation scheme in South Africa. Crop Prot. 28: 684Ð689.
Kruger, M., J.B.J. Van Rensburg, and J. Van Den Berg. 2011.
Resistance to Bt maize in Busseola fusca (Lepidoptera:
Noctuidae) from Vaalharts, South Africa. Environ. En-
tomol. 40: 477Ð483.
Kruger, M., J.B.J. Van Rensburg, and J. Van Den Berg. 2012.
Transgenic Bt maize: farmersÕ perceptions, refuge com-
pliance and reports of stem borer resistance in South
Africa. J. Appl. Entomol. 136: 38Ð50.
Li, X., M. A. Schuler, and M. R. Berenbaum. 2007. Molec-
ular mechanisms of metabolic resistance to synthetic and
natural xenobiotics. Annu. Rev. Entomol. 52: 231Ð253.
Luttrell, R. G., and M. I. Ali. 2007. Exploring selection for Bt
resistance in heliothines: results of laboratory and Þeld
studies, pp. 1073Ð1086. In D. A. Richter (ed.), Proceed-
ings, 2007 Beltwide Cotton Conferences, 9Ð12 January
2007, New Orleans, LA. National Cotton Council of
America, Memphis, TN.
Luttrell, R. G., and R. E. Jackson. 2012. Helicoverpa zea and
Bt cotton in the United States. GM Crops Food 3: 213Ð227.
Luttrell, R. G., I. Ali, K. C. Allen, S. Y. Young, III, A. Szalanski,
K. Williams, G. Lorenz, C. D. Parker, Jr., and C. Blanco.
2004. Resistance to Bt in Arkansas populations of cotton
bollworm, pp. 1373Ð1383. In D. A. Richter (ed.), Pro-
ceedings, 2004 Beltwide Cotton Conferences, 5Ð9 Janu-
ary 2004, San Antonio, TX. National Cotton Council of
America, Memphis, TN.
Moar, W., R. Roush, A. Shelton, J. Ferre´, S. MacIntosh, B. R.
Leonard, and C. Abel. 2008. Field-evolved resistance to
Bt toxins. Nat. Biotechnol. 26: 1072Ð1074.
Monsanto. 2010. Cotton in India. Updated 5 May 2010.
(http://www.monsanto.com/newsviews/Pages/india-
pink-bollworm.aspx)
Monsanto. 2013. Corn rootworm knowledge research pro-
gram. (http://www.monsanto.com/crwknowledge/Pages/
default.aspx)
Mota-Sanchez, D., S. P. Bills, and M. E. Whalon. 2002. Ar-
thropod resistance to pesticides: Status and overview, pp.
241Ð272. In: W. Wheeler and B. Gainesville (eds.), Pes-
ticides in agriculture and the environment. Marcel
Decker, New York, NY.
Mota-Sanchez, D., M. E. Whalon, R. M. Hollingworth, and Q.
Xue. 2008. Documentation of pesticide resistance in ar-
thropods, pp. 32Ð39. In M. E. Whalon, D. Mota-Sanchez,
and R. M. Hollingworth (eds.), Global pesticide resis-
tance in arthropods. CABI International, Wallingford,
United Kingdom.
National Research Council. 1986. Pesticide resistance: strat-
egies and tactics for management. National Academy
Press, Washington, DC. (http://www.nap.edu/catalog.
php?record_id619)
Pedra, J.H.F., L. M. McIntyre, M. E. Scharf, and B. R. Pit-
tendrigh. 2004. Genome-wide transcription proÞle of
Þeld- and laboratory-selected dichlorodiphenyltrichoro-
ethane (DDT)-resistant Drosophila. Proc. Natl. Acad. Sci.
U.S.A. 101: 7034Ð7039.
Pittendrigh, B. R., V. M Margam, L. Sun, and J. E. Huesing.
2008. Resistance in the post-genomics age, pp. 39Ð68. In
D. W. Onstad (ed.), Insect resistance management: bi-
ology, economics and prediction. Academic, London,
United Kingdom.
Porter, P., E. Cullen, T. Sappington, A. Schaafsma, S. Pueppke,
D. Andow, J. Bradshaw, L. Buschman, Y. Cardoza, C. Di-
Fonzo, et al. 2012. Comment submitted by Patrick Porter,
North Central Coordinating Committee NCCC46. (http://
www.regulations.gov/#!documentDetail;DEPA-HQ-
OPP-2011Ð0922-0013)
Powles, S. B., and Q. Yu. 2010. Evolution in action: plants
resistant to herbicides. Annu. Rev. Plant Biol. 61: 317Ð347.
Roush, R. T. 1994. Managing pests and their resistance to
Bacillus thuringiensis: Can transgenic crops be better than
sprays? Biocontrol Sci. Technol. 4: 501Ð516.
Roush, R. T., and J. A. McKenzie. 1987. Ecological genetics
of insecticide and acaricide resistance. Annu. Rev. Ento-
mol. 32: 361Ð380.
Roush, R. T., and G. L., Miller. 1986. Considerations for
design of insecticide resistance monitoring. J. Econ. En-
tomol. 79: 293Ð298.
Shalaby, H. A. 2013. Antihelmintics resistance; How to over-
come it? Iran. J. Parasitol. 8: 18Ð32.
Sierotzki, H., and G. Scalliet. 2013. A review of current
knowledge of resistance aspects for the next-generation
succinate dehydrogenase inhibitor fungicides. Phytopa-
thology 103: 880Ð887.
Storer, N. P., J. M. Babcock, M. Schlenz, T. Meade, G. D.
Thompson, J. W. Bing, and R. M. Huckaba. 2010. Dis-
covery and characterization of Þeld resistance to Bt
maize: Spodoptera frugiperda (Lepidoptera: Noctuidae)
in Puerto Rico. J. Econ. Entomol. 103: 1031Ð1038.
Storer, N. P., M. E. Kubiszak, J. E. King, G. D. Thompson, and
A. C. Santos. 2012. Status of resistance to Bt maize in
Spodoptera frugiperda: lessons from Puerto Rico. J. In-
vertebr. Pathol. 110: 294Ð300.
Sumerford, D. V., G. P. Head, A. Shelton, J. Greenplate, and
W. Moar. 2013. Field-evolved resistance: Assessing the
problem and moving forward. J. Econ. Entomol. 106:
1525Ð1534.
Tabashnik, B. E. 1994. Evolution of resistance to Bacillus
thuringiensis. Annu. Rev. Entomol. 39: 47Ð79.
Tabashnik, B. E., and Y. Carrie`re. 2010. Field-evolved re-
sistance to Bt cotton: Helicoverpa zea in the U.S. and pink
bollworm in India. Southwest. Entomol. 35: 417Ð424.
Tabashnik, B. E., and F. Gould. 2012. Delaying corn root-
worm resistance to Bt corn. J. Econ. Entomol. 105: 767Ð
776.
Tabashnik, B. E., and M. W. Johnson. 1999. Evolution of
pesticide resistance in natural enemies, pp. 673Ð689. In
T. W. Fisher and T. S. Bellows (eds.), Handbook of bi-
ological control: principles and applications, Academic,
San Diego, CA.
Tabashnik, B. E., N. Finson, C. F. Chilcutt, N. L. Cushing, and
M. W. Johnson. 1993. Increasing efÞciency of bioassays:
evaluation of resistance to Bacillus thuringiensis in dia-
mondback moth (Lepidoptera: Plutellidae). J. Econ. En-
tomol. 86: 635Ð644.
Tabashnik, B. E., A. L. Patin, T. J. Dennehy, Y. B. Liu, Y.
Carrie`re, M. A. Sims, and L. Antilla. 2000. Frequency of
506 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 107, no. 2
resistance to Bacillus thuringiensis in Þeld populations of
pink bollworm. Proc. Natl. Acad. Sci. U.S.A. 97: 12980Ð
12984.
Tabashnik, B. E., T. J. Dennehy, M. A. Sims, K. Larkin, G. P.
Head, W. J. Moar, and Y. Carrie`re. 2002. Control of
resistant pink bollworm by transgenic cotton with Bacil-
lus thuringiensis toxin Cry2Ab. Appl. Environ. Microbiol.
68: 3790Ð3794.
Tabashnik, B. E., A. J. Gassmann, D. W. Crowder, and Y.
Carrie`re. 2008a. Insect resistance to Bt crops: evidence
versus theory. Nat. Biotechnol. 26: 199Ð202.
Tabashnik, B. E., A. J. Gassmann, D. W. Crowder, and Y.
Carrie`re. 2008b. Field-evolved resistance to Bt toxins.
Nat. Biotechnol. 26: 1074Ð1076.
Tabashnik, B. E., J.B.J. Van Rensburg, and Y. Carrie`re. 2009.
Field-evolved insect resistance to Bt crops: deÞnition,
theory, and data. J. Econ. Entomol. 102: 2011Ð2025.
Tabashnik, B. E., M. S. Sisterson, P. C. Ellsworth, T. J. Den-
nehy, L. Antilla, L. Liesner, M. Whitlow, R. T. Staten, J. A.
Fabrick, G. C. Unnithan, et al. 2010. Suppressing resis-
tance to Bt cotton with sterile insect releases. Nat. Bio-
technol. 28: 1304Ð1307.
Tabashnik, B. E., T. Bre´vault, and Y. Carrie`re. 2013. Insect
resistance to Bt crops: lessons from the Þrst billion acres.
Nat. Biotechnol. 31: 510Ð521.
Van den Berg, J., A. Hilbeck, and T. Bøhn. 2013. Pest resis-
tance to Cry1Ab Bt maize: Þeld resistance, contributing
factors and lessons from South Africa. Crop Prot. 54:
154Ð160.
Van Rensburg, J.B.J. 2007. First report of Þeld resistance by
stem borer, Busseola fusca (Fuller) to Bt-transgenic
maize. S. Afr. J. Plant Soil 24: 147Ð151.
Wan, P., Y. Huang, H. Wu, M. Huang, S. Cong, B. E. Tabash-
nik, and K. Wu. 2012. Increased frequency of pink boll-
worm resistance to Bt toxin Cry1Ac in China. PLoS ONE
7: e29975.
Whalon, M. 2013. 2013 ESA-SME: Þrst quarter report on
USEPA liaison activities. (http://www.entsoc.org/PDF/
2013/2013EPA-Report2.pdf)
Whalon, M. E., D. Mota-Sanchez, and R. M. Hollingworth.
2008. Analysis of global pesticide resistance in arthropods,
pp. 5Ð31. In M. E. Whalon, D. Mota-Sanchez, and R. M.
Hollingworth (eds.), Global pesticide resistance in arthro-
pods. CABI International, Wallingford, United Kingdom.
Whalon, M. E., D. Mota-Sanchez, and R. M. Hollingworth.
2013. Arthropod Pesticide Resistance Database. (http://
www.pesticideresistance.com/index.php).
Williams, M. R. 2012. Cotton insect loss estimate. pp. 1001Ð
1012. In S. Boyd, M. Huffman, and B. Robertson (eds.),
Proceedings, 2012 Beltwide Cotton Conferences, 6
January 2012, Orlando, FL. National Cotton Council of
America, Memphis, TN.
Wilson, E. O., and W. H. Bossert. 1971. A primer of popu-
lation biology. Sinauer, Sunderland, MA.
Wolstenholme, A. J., and R. M. Kaplan. 2012. Resistance to
macrocyclic lactones. Curr. Pharm. Biotechnol. 13: 873Ð
887.
Yu, Q., S. Huang, and S. Powles. 2010. Direct measurement
of paraquat in leaf protoplasts indicates vacuolar paraquat
sequestration as a resistance mechanism in Lolium rigi-
dum. Pestic. Biochem. Physiol. 98: 104Ð109.
Zhang, H., W. Yin, J. Zhao, L. Jin, Y. Yang, S. Wu, B. E.
Tabashnik, and Y. Wu. 2011. Early warning of cotton
bollworm resistance associated with intensive planting of
Bt cotton in China. PLoS ONE 6: e22874.
Zhang, H., T. Wen, J. Zhao, L. Jin, J. Yang, C. Liu, Y. Yang,
S. Wu, K. Wu, J. Cui, et al. 2012. Diverse genetic basis of
Þeld-evolved resistance to Bt cotton in cotton bollworm
from China. Proc. Natl. Acad. Sci. U.S.A. 109: 10275Ð
10280.
Received 17 October 2013; accepted 25 January 2014.
April 2014 TABASHNIK ET AL.: TERMS FOR PROACTIVE RESISTANCE MANAGEMENT 507
... O custo adaptativo é um fenômeno que ocorre quando alelos (formas alternativas de um determinado gene) conferem alto fitness (habilidade de um indivíduo com determinado genótipo sobreviver e reproduzir em relação a outro indivíduo da mesma espécie) em um ambiente específico, mas baixo fitness em um ambiente alternativo (GASSMANN et al, 2009;TABASHNIK et al, 2014). Um exemplo é o caso de insetos que carregam alelos de resistência a inseticidas, os quais no ambiente com aplicações do inseticida demonstram um fitness superior aos insetos que não carregam o alelo de resistência, no entanto, quando a utilização do inseticida é interrompida, o fitness dos insetos resistentes torna-se inferior ao fitness dos insetos suscetíveis (TABASHNIK et al, 2014). ...
... O custo adaptativo é um fenômeno que ocorre quando alelos (formas alternativas de um determinado gene) conferem alto fitness (habilidade de um indivíduo com determinado genótipo sobreviver e reproduzir em relação a outro indivíduo da mesma espécie) em um ambiente específico, mas baixo fitness em um ambiente alternativo (GASSMANN et al, 2009;TABASHNIK et al, 2014). Um exemplo é o caso de insetos que carregam alelos de resistência a inseticidas, os quais no ambiente com aplicações do inseticida demonstram um fitness superior aos insetos que não carregam o alelo de resistência, no entanto, quando a utilização do inseticida é interrompida, o fitness dos insetos resistentes torna-se inferior ao fitness dos insetos suscetíveis (TABASHNIK et al, 2014). ...
... These measures consisted of: (1) the confirmation of the unexpected damage on plants expressing Cry1Ab and the investigation of potential practical resistance (i.e. field-evolved resistance that reduces pesticide efficacy with practical consequences for pest control (Tabashnik et al., 2014)); and (2) the inclusion of the area of Girona in the annual resistance monitoring plan. ...
... Although this statement caused some debates [138], evidence of PRBT evolution gradually accumulated. Practically, resistance was observed in the insect species of B. Fusca, D.v. virgifera, H. zea, P. gossiypiella, and S. frugiperda against Cry1Ab, Cry3Bb, Cry1Ac, Cry1Ac, and Cry1Fa, respectively [141]. Fall army worm (S. frugiperda) has developed a maximum level of resistance against Cry1Ac, Cry2Ab, and Cry1Fa [142]. ...
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... Oat crop is one of the preferred hosts of this pest. Since this fodder crop is directly used as animal feed [7], chemical control of pest is not preferable and it is well known that some synthetic insecticides may deplete natural enemy population, cause contamination problems and most importantly, they are toxic to human and animals [8]. One of the alternatives for the management of FAW on fodder oats are the use of microbials which have some advantages over the use of chemical insecticides, as they are highly host specific and also induce low environmental contamination [9]. ...
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The fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), is a cosmopolitan pest that exploits more than 350 host plants, including economically important crops such as corn, cotton and rice. Control of S. frugiperda largely relies on transgenic crops producing insecticidal proteins from Bacillus thuringiensis (Bt) and spraying synthetic insecticides. Here, we established the susceptibility and diagnostic concentration for 2 Bt toxins and 5 newer insecticides in invasive populations of S. frugiperda from southeastern China. Concentrations causing 50% mortality (LC50) in ten field populations sampled in 2022 ranged from 2.13 to 19.29 and 22.43 to 71.12 ng/cm2 for Cry1Fa and Vip3Aa, and 0.83 to 5.30, 2.83 to 9.94, 0.04 to 0.23, 4.59 to 8.40, and 1.49 to 6.79 mg/liter for chlorantraniliprole, chlorfenapyr, emamectin benzoate, indoxacarb, and spinosad, respectively. Relative to the susceptible strain YJ-19, the largest resistance ratio in the field populations was 5.1, 1.6, 6.2, 3.9, 4.6, 2.2, and 3.6 for Cry1Fa, Vip3Aa, chlorantraniliprole, chlorfenapyr, emamectin benzoate, indoxacarb, and spinosad, respectively, indicating that the field populations were generally susceptible to these Bt toxins and insecticides. Based on the pooled response of the field populations, the diagnostic concentration for resistance monitoring, estimated as ca. twice the LC99, was 400 and 1,500 ng/cm2 for Cry1Fa and Vip3Aa, and 2, 40, 60, 60, and 100 mg/liter for emamectin benzoate, chlorantraniliprole, chlorfenapyr, spinosad, and indoxacarb, respectively. These results provide useful information for monitoring resistance to key Bt toxins and insecticides for the control of S. frugiperda in China.
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The risk of rapid pest adaptation to an insecticide is highly dependent on the initial frequency of resistance alleles in field populations. Because we have lacked empirical estimates of these frequencies, population–genetic models of resistance evolution have relied on a wide range of theoretical estimates. The recent commercialization of genetically engineered cotton that constitutively produces an insecticidal protein derived from the biocontrol agent, Bacillus thuringiensis (Bt) has raised concern that we lack data needed to quantify the risk of insect pests such as Heliothis virescens rapidly adapting to this ecologically valuable class of toxins. By individually mating over 2,000 male H. virescens moths collected in four states to females of a Bt toxin-resistant laboratory strain, and screening F 1 and F 2 offspring for tolerance of the toxic protein, we were able to directly estimate the field frequency of alleles for resistance as 1.5 10 3. This high initial frequency underscores the need for caution in deploying transgenic cotton to control insect pests. Our single-pair mating technique greatly increases the efficiency of detecting recessive resistance alleles. Because alleles that decrease target site sensitivity to Bt toxins and other insecticides are often recessive, this technique could be useful in estimating resistance allele frequencies in other insects exposed to trans-genic insecticidal crops or conventional insecticides.
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This book contains 6 chapters focusing on the following topics: analysis of global pesticide resistance in arthropods; documentation of pesticide resistance in arthropods; the biochemical and molecular genetic basis of resistance to pesticides in arthropods; assessing the risk of the evolution of resistance to pesticides using spatially complex simulation models; pesticide and transgenic plant resistance management in the field; and the politics of resistance management.
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Over the last decade, there has been an exponential growth in interest and investigation of the problem of how best to conserve populations of endangered species. As a result, there is now a very extensive and widely scattered literature on this subject. Among recent papers which cite a large number of references are those of Boyce (1992), Ellstrand and Elam (1993) and Nunney and Campbell (1993). Soulé’s (1987) book gives a valuable survey of the subject, in which the chapter by Lande and Barrowclough (1987) deals with the population genetics of the problem. Much of this literature is concerned with the conservation of species where ex situ conservation is not a realistic alternative. The demographic and population genetics theory on which discussion of this broader issue is based, however, is also relevant to the special case of those species where the conservation of material in gene banks is possible. The purpose of this chapter is to give a brief outline of the population genetics theory on which discussion of in situ conservation is based and to introduce some of the terms and concepts used in the literature. We also indicate the kinds of experimental investigation of populations which are necessary to produce better recommendations about minimum viable population size than are possible at present.
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This chapter reviews what is known about insect resistance in a select group of classic pesticide classes and then discusses some exciting new possibilities that ". Omics" may provide for the near future. The potential importance of understanding the molecular mechanism by which insects resist environmental challenges is also discussed. An "Achilles' heel trait" as a target molecule that, when inhibited (or negatively impacted), reduces the ability of an organism or a population of organisms to persist in a specific environmental condition or challenge has been defined. Examples are illustrated that insects use evolutionarily conserved resistance mechanisms common to all animals (e.g., some aspects of oxidative stress) as well as those that are particular to insects (e.g., the peritrophic membrane in the digestive system). Finally, we have illustrated how the ". Omics" revolution is just beginning to reveal more in-depth knowledge of the system-wide bases of these mechanisms (e.g., metabolic pesticide resistance). Perhaps not surprising, but none the less exciting, are emerging examples of the involvement of hitherto unidentified genes and mechanisms involved in resistance. These findings should allow us to identify novel and safe pesticides as well as better design resistance management strategies to ensure their long-term utility.
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Pesticide resistance has had a substantial impact on crop production and has been an important driver of change in modern agriculture, animal production and human health. Focusing specifically on arthropods, this book provides a comprehensive review of relevant issues in pesticide resistance. Detailed listings and references to all documented reports of resistance from around the world are included.
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Pesticide resistance is a genetically based, statistically significant increase in the ability of a population to tolerate one or more pesticides. Resistant pest populations can attract immediate attention when pesticide treatments fail to control them. Resistance in natural enemies, however, does not create problems and may go unnoticed. The differential preadaptation hypothesis states that resistance to pesticides evolves more readily in pests than it does in natural enemies due to differences in the responses to pesticides between pests and natural enemies that existed before the selection for pesticide resistance. The idea that natural enemies are intrinsically less tolerant to pesticides than pests is, in effect, a generalized version of the differential detoxification enzyme hypothesis. The concept is the same, but unlike the differential detoxification hypothesis, the mechanism causing the intrinsic difference is unspecified. The tests of this version of the preadaptation hypothesis must determine whether pests have higher intrinsic tolerance to pesticides than what the natural enemies have, and if so, then whether such intrinsic differences in tolerance cause natural enemies to evolve resistance more slowly than pests do. The idea that natural enemies are not generally less tolerant to pesticides than pests differs from widely held perceptions. Such perceptions may be based partly on observations that field applications of pesticides affect natural enemies more than they affect pests.