Diptera: Drosophilidae - BioOne

20 downloads 0 Views 231KB Size Report
Apr 30, 2014 - Drosophila suzukii (Diptera: Drosophilidae) on Cherry and Blueberry ... compare the 2011 and 2012 crop seasons in an important cherry ...
PHYSIOLOGICAL ECOLOGY

Temperature-Related Development and Population Parameters for Drosophila suzukii (Diptera: Drosophilidae) on Cherry and Blueberry SAMANTHA TOCHEN,1 DANIEL T. DALTON,1 NIK WIMAN,1 CHRISTOPHER HAMM,2 PETER W. SHEARER,3 AND VAUGHN M. WALTON1,4

Environ. Entomol. 43(2): 501Ð510 (2014); DOI: http://dx.doi.org/10.1603/EN13200

ABSTRACT Temperature-related studies were conducted on Drosophila suzukii Matsumura (Diptera: Drosophilidae: Drosophilini). From 10 Ð28⬚C, temperature had a signiÞcant impact on blueberries, Vaccinium corymbosum L. (Ericales: Ericaceae), and cherries, Prunus avium (L.) L. 1755 (Rosales: Rosaceae), important commercial hosts of D. suzukii. Temperature had a signiÞcant inßuence on D. suzukii developmental period, survival, and fecundity, with decreasing developmental periods as temperatures increased to 28⬚C. At 30⬚C, the highest temperature tested, development periods increased, indicating that above this temperature the developmental extremes for the species were approached. D. suzukii reared on blueberries had lower fecundity than reared on cherries at all temperatures where reproduction occurred. The highest net reproductive rate (Ro) and intrinsic rate of population increase (rm) were recorded on cherries at 22⬚C and was 195.1 and 0.22, respectively. Estimations using linear and nonlinear Þt for the minimum, optimal, and maximum temperatures where development can take place were respectively, 7.2, 28.1, and 42.1⬚C. The rm values were minimal, optimal, and maximal at 13.4, 21.0, and 29.3⬚C, respectively. Our laboratory cultures of D. suzukii displayed high rates of infection for Wolbachia spp. (Rickettsiales: Rickettsiaceae), and this infection may have impacted fecundity found in this study. A temperature-dependent matrix population estimation model using fecundity and survival data were run to determine whether these data could predict D. suzukii pressure based on environmental conditions. The model was applied to compare the 2011 and 2012 crop seasons in an important cherry production region. Population estimates using the model explained different risk levels during the key cherry harvest period between these seasons. KEY WORDS fecundity, mortality, longevity, population matrix

Drosophila suzukii Matsumura (Diptera: Drosophilidae) is an economic pest of small and stone fruit species and is now established in many production areas of these crops in North America, Asia, and Europe (Kanzawa 1939, Kawase et al. 2007, Goodhue et al. 2011, Lee et al. 2011, Walsh et al. 2011, Cini et al. 2012). Two key economically important fruit produced in Oregon include blueberries, Vaccinium corymbosum L. (Ericales: Ericaceae), and cherries, Prunus avium (L.) L. 1755 (Rosales: Rosaceae). Female D. suzukii oviposit in ripening fruits using a serrated ovipositor (Lee et al. 2011, Walsh et al. 2011), as opposed to other drosophilids such as D. melanogaster, which oviposit in overripe or previously damaged fruit. Developing larvae subsequently consume the fruit ßesh, making infested fruit unmarketable for 1 Department of Horticulture, Oregon State University, Corvallis, OR 97331-7304. 2 Department of Evolution and Ecology, University of California, Davis 3347 Storer Hall, One Shields Ave., Davis, CA 95616. 3 Oregon State University, Mid-Columbia Agricultural Research and Extension Center, 3005 Experiment Station Dr., Hood River, OR 97031. 4 Corresponding author, e-mail: [email protected].

fresh consumption. Larval feeding degrades fruit quality, which may further lead to fruit rejection at processing facilities. It is estimated that D. suzukii damage may lead to US$500 million in annual losses in western United States production areas, assuming 30% damage levels (Goodhue et al. 2011). Mitsui et al. (2006, 2007) described high fecundity of D. suzukii on wild Japanese fruits that are closely related to American cultivated berry species, but no clear developmental or reproductive parameters were given in those studies. In North American commercial production areas of small and stone fruit, pesticide applications have been the primary control tactic against D. suzukii (Beers et al. 2011, Bruck et al. 2011). The most effective sprays include pyrethroids, carbamates, and spinosyns targeting ovipositing adult females. Current spray programs are timed to prevent oviposition in ripening susceptible crops (Beers et al. 2011, Bruck et al. 2011). Traps baited with apple cider vinegar or a combination of sugarÐwater and yeast are used to monitor for D. suzukii (Cha et al. 2012, Landolt et al. 2012, Lee et al. 2012) but cannot be used as the only warning tool against D. suzukii attack.

0046-225X/14/0501Ð0510$04.00/0 䉷 2014 Entomological Society of America

502

ENVIRONMENTAL ENTOMOLOGY

Current control methods can be improved by gaining knowledge of the basic mechanisms of D. suzukii population increase (Price 1997). The inßuence of long-term insect survival includes favorable temperatures during the overwintering period (Dalton et al. 2011) and the availability of essential food resources. Such factors may drive early season D. suzukii population increase and resultant elevated pest pressure (Kanzawa 1939; Mitsui et al. 2006, 2007). Infections from pathogens such as Wolbachia spp. (Rickettsiales: Rickettsiaceae) are known to impact fecundity and longevity of drosophilids (Turelli and Hoffmann 1991, 1995; Weeks et al. 2007), resulting in signiÞcant differences in population increase under Þeld conditions. Rapid microbial infection of D. suzukii also seems possible although the effects of Wolbachia spp. on North American populations of D. suzukii have not been systematically investigated. Studies describing the underlying mechanisms for population increase (Carey 1993, 2001) and the effect of temperature on D. suzukii development was originally investigated but was conducted under ßuctuating ambient (Kanzawa 1939) and outdoor temperatures (Kimura 2004). The status of Wolbachia spp. infection was not recorded in the Kanzawa (1939) and Kimura (2004) studies. The genetic origin of American D. suzukii pest populations also remains unknown, and possible fecundity effects of Wolbachia spp. infection are only now coming under examination and are research areas that demand attention. Blueberry and cherry are crops of signiÞcant economic value in Oregon and are attacked by this pest (Goodhue et al. 2011, Lee et al. 2011, Walsh et al. 2011). Baseline data are provided on the infection rate of Wolbachia spp. on the Þeld-collected colony of D. suzukii used in this study. The goals of this study were to estimate the net reproductive rate (Ro) and intrinsic rate of population increase (rm) of a laboratory colony of D. suzukii reared across a range of constant temperatures and on these two commercially valuable commercially valuable crops. These survival and fecundity data were also used to develop a temperaturerelated population model, which can be used by growers as an early risk model for D. suzukii pressure. Materials and Methods Collection, Pathogen Analysis, and Rearing. Initial stock cultures of D. suzukii adults and pupae were provided to Oregon State University (OSU) in 2009 by the U.S. Department of AgricultureÕs-Agricultural Research Service (USDA-ARS) Horticultural Crops Research Laboratory (HCRL), Corvallis, OR, and routinely augmented by Þeld-collected D. suzukii that were obtained from weekly Þeld collections made in the Willamette Valley from 2010 to 2012. Analysis of Wolbachia spp. infection was conducted on both laboratory and Þeld-collected samples of D. suzukii using the methods described by Nice et al. (2009). Shortly, we conducted two PCR reactions for each D. suzukii specimen. One PCR reaction ampliÞed 28S rDNA and acted as a positive control; the second reaction am-

Vol. 43, no. 2

pliÞed wsp (Wolbachia surface protein). PCR products were visualized on a 1% agarose electrophoresis gel. Positive infection was concluded only if both PCRs ampliÞed a product of the appropriate length, which we assumed was the target marker. Negative infection status was concluded if 28S was positive but wsp was negative. Reactions that produced no ampliÞed products were not scored. The infection frequency and 95% conÞdence interval (CI) were calculated following the method of Clopper et al. (1934) in statistical program R v 3.0 (R Development Core Team 2013). The OSU stock colony for these studies was maintained in the laboratory at 22 ⫾ 2⬚C, 65% relative humidity (RH), and a photoperiod of 16:8 (L:D) h. Each rearing cage contained a plastic container modiÞed to hold a sponge and water. An insect diet medium was added to the cage as an artiÞcial food source (Dalton et al. 2011) and provided a site for oviposition. Rearing containers for experimental units were constructed as previously described (Dalton et al. 2011). Containers consisted of 163-ml plastic soufße´ cups (Solo, Urbana, IL) equipped with a moistened Þlter paper strip (Whatman International, Ltd/, Maidstone, United Kingdom) and a cotton square (U.S. Cotton, LLC, Rio Rancho, NM) for texture and to act as a water source for the insects. Adult mated female ßies were secured in cups with tight-Þtting lids that were pierced to provide gas exchange between the cups and the temperature cabinets. Fresh unsprayed sweet cherries, P. avium (ÕRainierÕ and ÔBingÕ), and blueberries, V. corymbosum (ÕDukeÕ, ÔBluecropÕ, and ÔJerseyÕ), were regularly sourced from the OSU Mid-Columbia Research and Extension Center (MCAREC) in Hood River, OR, as well as the OSU Lewis-Brown and Botany Plant Pathology research farms in Corvallis, OR. Equivalent numbers of fruit were collected with stems intact and stored in cold rooms at 4⬚C until they were exposed to D. suzukii. Individual fruit were closely examined under a stereomicroscope to ensure that they were free of any eggs or larvae before being exposed to ßies. Fruit was exposed to D. suzukii females for 30 min at 22 ⫾ 2ⴗC, 65% RH, and was subsequently removed, examined under the stereomicroscope, and grouped by the number of eggs present. A single infested fruit containing no more than Þve eggs was subsequently placed into rearing containers and placed into the temperature cabinets within 1 h of initial egg laying. For both fruit types, each temperature treatment was replicated three times, and each replicate consisted of 20 containers each containing one fruit. The total oviposited D. suzukii eggs for the three replicates were 100. Rearing units containing infested fruit were placed in temperature-controlled growth chambers (model E-30BHO; Percival ScientiÞc, Perry, IA) at 10, 14, 18, 20, 24, 28, and 30⬚C and 60 Ð70% RH under a photoperiod of 16:8 (L:D) h. Each container was observed every 48 h (three lowest temperatures) or 24 h (four highest temperatures) until pupae became apparent on fruit or adult females were found. Attempts to track

April 2014

TOCHEN ET AL.: D. suzukii TEMPERATURE-RELATED DEVELOPMENT

individual larvae were made, but owing to the propensity of larvae to stay within fruit until the Þnal instar, these developmental data are not presented. Data are presented as time (d) taken from egg to pupal stage, pupal stage to adult, and adult to mortality. To allow controlled mating, females were removed on emergence and placed individually along with one male in separate cups containing uninfested fruit. Missing or dead male ßies were replaced throughout the oviposition period to mortality to allow continued mating and ensure optimal reproduction of D. suzukii females. Missing or dead females were excluded from data analysis. Fruit in each container was replaced every 24 h and examined to determine daily oviposition activity and survival period for each female D. suzukii. Data from these observations were plotted over time to display survival and oviposition trends for each of the fruit types and treatment temperatures. Statistical Analysis. Influence of Temperature on Survival and Developmental Period and Fecundity. Impact of temperature on duration of each life stage was analyzed using ANOVA with fruit, gender, and temperature as independent factors. Differences of the means were separated using TukeyÕs HSD. Nonparametric KruskalÐWallis ANOVA rank-sum tests were used to compare adult female survival for each temperature and fruit type. Analyses were conducted using Statistica (StafSoft 7.1, Tulsa, OK). Life Table Parameters and Threshold Determination. The mean generation times (T) of D. suzukii on cherries and blueberries were estimated using the equation, T ⫽ ⌺ lxmxx/Ro (Price 1997), where x ⫽ age in days, lx ⫽ the proportion of females surviving on day x, mx ⫽ the mean number of eggs produced on day x, and Ro is the net reproductive rate. The mean survival and fecundity values for each temperature were then used to estimate the intrinsic rate of population increase (rm) at each temperature. These values were determined by using the equation, rm ⫽ loge Ro/T (Price 1997), where Ro is the net reproductive rate and T is the mean generation time. Net reproductive rate was obtained using the equation, Ro ⫽ ⌺ lxmx, and rate of development was estimated by using linear and nonlinear regression. Linear and nonlinear regression was performed on the data of both fruit types by using the reciprocal of development time in days (1/T) on temperature. The lower developmental threshold was subsequently determined by solving the regression equation for 1/T ⫽ 0. A nonlinear model adapted from Briere et al. (1999) for temperature-dependent development was used to estimate upper and optimal thresholds. The expression of the user-speciÞed regression model isÑr(T) ⫽ nT(T ⫺ Tb)(TL ⫺ T)exp(1/ m), where r(T) is the rate of development at temperature T; TL is the upper temperature developmental threshold; Tb is the lower temperature developmental threshold; and n and m are empirical constants. The thermal constant (k) in degree-days (DD) from oviposition to adult was estimated by using k ⫽ 1/b, which represents the slope of the estimated relationship between temperature and the rate of development (Campbell et al. 1974, Liu and Meng 1999).

503

The lower and upper thresholds for intrinsic rate of population increase (rm) were estimated by Þtting the nonlinear model to the rm values obtained from blueberries and cherries. Fitting of nonlinear models were conducted using Statistica (StafSoft 7.1). Population Modeling. To determine the inßuence of environment on D. suzukii populations, we plotted temperature-related fecundity and survival data over temperature to each of 10 life periods of ßies aged from 1 to 50 d. Fecundity and survival data were subjected to linear and polynomial regression for all temperature treatments and for each of the age-groups. Age-groups included the egg or larval or pupal stages occurring from days 1Ð9, and larval or pupal or adult stages from days 10 Ð15, 16 Ð25, 26 Ð35, 36 Ð 45, and 46 Ð50. Regression models were selected according to maximization of coefÞcient of determination treatment. Regressions were then applied in a conditional Leslie matrix (Carey 1993, 2001) to provide a numerical tool to estimate population growth of D. suzukii populations based on mean daily temperature. The temperaturedependent regression functions for survival probability (sx) and fecundity (fx) for each age class were included in the matrix model to account for current temperature from a vector describing mean daily temperature in the 50 by 50 matrix using software from the open source statistical environment R (R Development Core Team 2013). Mean daily temperature data for Hood River, OR, were used for the 2011 and 2012 growing seasons in Hood River (U.S. Department of InteriorÑBureau of Reclamation [http://www.usbr. gov/pn/agrimet/agrimetmap/crvoda.html]). Matrices for each day and temperature were calculated and then stored as 2,500 row vectors in a matrix where columns represent days. For population calculations, columns were then expanded back to 50 by 50 matrices and multiplied by the population vector. These population data were then compared with phenological information provided by the current D. suzukii DD model (Coop 2012). Population matrices were initiated on 20 May of each year based on the observation that positive rm values were found for ⬎50% of the time examined at weekly intervals as estimated from the current study. The population matrices were initiated by arbitrarily placing 100 ßies into the matrix for the oldest age-group of ßies (x ⫽ 46- to 50-d-old females) because these age classes best represent ßies that could survive winters in Hood River (Dalton et al. 2011). Mean daily temperature data for Hood River were converted to DD values for cherries, at 4⬚C base temperature (Baskerville and Emin 1969, Eisensmith et al. 1982) to determine thermal effects between seasons.

Results Analysis of Wolbachia spp. incidence on D. suzukii collections from Oregon Þeld locations showed ⬇20% infection. In total, 28 ßies were screened for Wolbachia from the Tochen colony, of which 19 were infected (68% infection, 95% CI: 50 Ð 85%). In total, 30

504

ENVIRONMENTAL ENTOMOLOGY

Table 1.

Vol. 43, no. 2

D. suzukii mean developmental periods (day ⴞ SEM) at seven constant temperatures on ‘Rainier’ and ‘Bing’ cherries

Life stage Females Egg to pupa Pupa to adult Egg to adult Adult to mortality Males Egg to pupa Pupa to adult Egg to adult Adult to mortality

Temperature (⬚C) 10

14

18

22

26

28

30

n⫽3 47 ⫾ 4a 32.4 ⫾ 2.3a 79.3 ⫾ 4.1a 35 ⫾ 12.5aA n⫽7 43.1 ⫾ 2.5a 35.1 ⫾ 2.9a 78.3 ⫾ 3.1a 31.0 ⫾ 4.3aA

n ⫽ 38 14.7 ⫾ 0.3b 14.1 ⫾ 0.2b 28.8 ⫾ 0.3b 27.3 ⫾ 3.9bA n ⫽ 28 14.4 ⫾ 0.4b 14.3 ⫾ 0.3b 28.7 ⫾ 0.5b 20.76 ⫾ 3.2aA

n ⫽ 27 10.8 ⫾ 0.2c 7.6 ⫾ 0.2c 18.2 ⫾ 0.3c 18.2 ⫾ 2.9c n ⫽ 22 10.8 ⫾ 0.3c 8.1 ⫾ 0.6c 18.9 ⫾ 0.3c 16.8 ⫾ 3.2b

n ⫽ 37 8.0 ⫾ 0.2d 6.0 ⫾ 0.2d 14 ⫾ 0.1d 10.5 ⫾ 4.2d n ⫽ 31 8.5 ⫾ 0.2d 5.5 ⫾ 0.2d 14.0 ⫾ 0.2d 13.2 ⫾ 7.7a

n ⫽ 48 6.8 ⫾ 0.2f 4.0 ⫾ 0.1e 10.8 ⫾ 0.1e 12.8 ⫾ 4.9d n ⫽ 23 6.9 ⫾ 0.2e 4.2 ⫾ 0.1e 11.1 ⫾ 0.2e 12.8 ⫾ 8.2b

n ⫽ 19 6.2 ⫾ 0.2f 3.7 ⫾ 0.2e 9.9 ⫾ 0.3e 10.7 ⫾ 3.5d n ⫽ 20 6.1 ⫾ 0.2f 4.0 ⫾ 0.1e 10.0 ⫾ 0.1f 10.1 ⫾ 6.8b

n⫽2 7.5 ⫾ 0.5e 4.5 ⫾ 0.5de 12.0 ⫾ 1.0e 2.0 ⫾ 0e Ð Ð Ð Ð

Emerging individuals to adulthood for each sex are indicated on the according line. Means within a row followed by different lowercase letters are signiÞcantly different and means within a column followed by different uppercase letters are signiÞcantly different. Means were separated using TukeyÕs HSD (P ⬍ 0.05).

ßies were screened from the Miller colony, of which 21 were infects (70% infection, 95% CI: 53Ð 86%). Influence of Temperature on Survival Periods. D. suzukii developed and eclosed at all temperatures in infested fruit within experimental containers. Subsequent survival of adults occurred at all temperatures except at 30⬚C for males on cherries (Table 1) and 30⬚C for females on blueberries (Table 2). Survival periods were shortest at the extreme temperatures of 10 and 30⬚C in blueberries (10% and 1% survival, respectively). In cherries, survival from egg to adulthood was 10% at 10⬚C and 2% for 30⬚C, respectively. The lowest percent mortality occurred at 26⬚C with 10% in blueberries and 29% mortality in cherries. In blueberries, similar proportions of males developed to adulthood at 10 Ð14⬚C. Numerically more females developed to adulthood at 18 Ð22⬚C, and more males developed to adulthood at 26 Ð30⬚C. In cherries, relatively more females developed to adulthood at 14, 18, 22, 26, and 30⬚C and relatively more males developed to adulthood at 10 and 28⬚C. Fruit (F ⫽ 3.2; df ⫽ 4, 607; P ⫽ 0.011) had an impact on survival periods from adult to mortality. Survival periods were shorter in blueberries compared with cherries at 10 and 14⬚C (Tables 1 and 2; Fig. 1A and B). No survival periods were statistically different when compared by gender, Table 2. blueberries

except for the period from adulthood to mortality at 10 and 14⬚C. At these temperatures, male longevity was shorter than that of females (F ⫽ 2.79; df ⫽ 4, 607; P ⫽ 0.025). Life span for adult females ranged from 2 to 35 d. In general, temperature increase resulted in a decrease in survival period (Tables 1 and 2; Fig. 1A and B). The shortest survival period (2 d) for adult ßies was recorded at 30⬚C in cherry. Median rank-sum tests comparing survival rates of reproducing females on cherries (median ⫽ 51 d) were signiÞcantly higher than those on blueberries (median ⫽ 47 d, ␹2 ⫽ 3.61; df ⫽ 1, 4; P ⫽ 0.05; Fig. 1). Rank-sum tests for adult female survival displayed signiÞcant differences for cherries (H ⫽ 76.97; df ⫽ 4, 124; P ⫽ 0.0001; Fig. 1A). Multiple comparisons of P values for days survived showed that adult females exposed to 14, 18, and 22⬚C displayed similar longevity, and longevity comparing 26 and 28⬚C was statistically similar. The higher two temperatures resulted in a shorter adult life span compared with the lower three temperatures. Survival periods in cherry were significantly different depending on temperature (␹2 ⫽ 12.91; df ⫽ 1, 4; P ⫽ 0.03), and median adult female survival times for 14, 18, 22, 26, and 28⬚C were 40.7, 44.2, 14.9, 6.4, and 5 d, respectively.

D. suzukii mean developmental rates (day ⴞ SEM) at seven constant temperatures on ‘Duke’, ‘Bluecrop’, and ‘Jersey’

Life stage Females Egg to pupa Pupa to adult Egg to adult Adult to mortality Males Egg to pupa Pupa to adult Egg to adult Adult to mortality

Temperature (⬚C) 10

14

18

22

26

28

30

n⫽5 43.6 ⫾ 2.3a 33.8 ⫾ 1.1a 77.4 ⫾ 2.4a 24.4 ⫾ 4.3aB n⫽5 45 ⫾ 2.9a 42.4 ⫾ 10.4a 78.4 ⫾ 2.8a 22.2 ⫾ 4.7aB

n ⫽ 26 16.2 ⫾ 0.4b 12.7 ⫾ 0.5b 28.3 ⫾ 0.4b 16.6 ⫾ 2.1bB n ⫽ 16 14 ⫾ 0.5b 14.1 ⫾ 1.4b 27.3 ⫾ 0.8b 11.5 ⫾ 1.2bB

n ⫽ 22 11.7 ⫾ 0.3c 8.5 ⫾ 0.2c 20.1 ⫾ 0.3c 17 ⫾ 2.1c n ⫽ 16 11.1 ⫾ 0.2c 8.4 ⫾ 0.1c 19.5 ⫾ 0.2c 14.2 ⫾ 2.9c

n ⫽ 41 8.2 ⫾ 0.2d 6.0 ⫾ 0.2d 14 ⫾ 0.2d 11.7 ⫾ 0.4d n ⫽ 39 8.1 ⫾ 0.2d 6.2 ⫾ 0.3d 14.1 ⫾ 0.2d 11.9 ⫾ 2d

n ⫽ 48 6.6 ⫾ 0.1e 4.6 ⫾ 0.1e 10.9 ⫾ 0.1e 12.1 ⫾ 0.7d n ⫽ 42 6.8 ⫾ 0.2e 4.6 ⫾ 0.3e 11.1 ⫾ 0.1e 12.1 ⫾ 1.9e

n ⫽ 19 5.9 ⫾ 0.3f 4.2 ⫾ 0.3e 10.1 ⫾ 0.3e 12 ⫾ 0.5d n ⫽ 20 6.0 ⫾ 0.2f 4.1 ⫾ 0.1f 10.1 ⫾ 0.1 g 13.2 ⫾ 0.8e

Ð Ð Ð n⫽1 6.0 ⫾ 0.2f 4.0 ⫾ 0.2f 10.0 ⫾ 0.2f 10.2f

Emerging individuals to adulthood for each sex are indicated on the according line. Means within a row followed by different lowercase letters are signiÞcantly different and means within a column followed by different uppercase letters are signiÞcantly different. Means were separated using TukeyÕs HSD (P ⬍ 0.05).

TOCHEN ET AL.: D. suzukii TEMPERATURE-RELATED DEVELOPMENT

April 2014

Fig. 1. Proportion of adult female D. suzukii survival at Þve constant temperatures on cherry (A) and blueberry (B).

Rank-sum tests for adult female survival curves displayed signiÞcant differences in blueberries (H ⫽ 50.24; df ⫽ 4, 83; P ⫽ 0.0001; Fig. 1B). Multiple comparison of P values for days survived showed that adult females exposed to 14 and 18⬚C displayed similar longevity, and comparison between 22, 26, and 28⬚C treatments produced statistically similar longevity. The three higher temperatures resulted in shorter adult life span compared with the two lower temperatures. Survival periods in blueberry were signiÞcantly different based on temperature (␹2 ⫽ 32.96; df ⫽ 1, 4; P ⫽ 0.0001). Median adult female survival times on blueTable 3. Fruit Cherry Blueberry

505

berry for 14, 18, 22, 26, and 28⬚C were 34.3, 28.3, 13.8, 3.4, and 2 d, respectively. Influence of Temperature on Developmental Periods. Most statistical comparisons were nonsigniÞcant at similar developmental stages in both fruit at 26 and 28⬚C. In cherries and blueberries, developmental periods of all life stages were signiÞcantly affected by temperature (F ⫽ 6.35; df ⫽ 20, 1934; P ⬍ 0.0001; Tables 1 and 2). The numerically largest differences were recorded between 10 and 14⬚C. Statistical differences were found in virtually all cases for developmental times required by each of the recorded life stages from 10 to 26⬚C. However, no statistical difference was observed in the duration of the developing stages of surviving ßies from the 30⬚C treatments compared with survivors at the 26 and 28⬚C treatments. The longest development period from egg to adult occurred at 10⬚C (79.4 ⫾ 4.1 d) in cherry and the shortest (11.0 ⫾ 0.2 d) in blueberry at 30⬚C (Tables 1 and 2). Immature ßies spent the largest proportion of time in the feeding (larval) stage compared with all other developmental stages at all temperatures except for 26 and 28⬚C in both fruits. Influence of Temperature on Fecundity. No eggs were laid at 10 or 30⬚C. Statistical comparison of D. suzukii fecundity showed that signiÞcantly more eggs were laid in cherries compared with blueberries at all temperatures (F ⫽ 6.1; df ⫽ 5, 170; P ⬍ 0.0001; Table 3). Within cherries, the highest numbers of eggs were laid at 18⬚C, followed in order by 22, 26, 14, and 28⬚C. In blueberries, differences were less pronounced with statistically similarly numbers of eggs laid at 22 and 18⬚C. Lower numbers of eggs were laid at 26⬚C followed by 28 and 14⬚C. The lowest fecundity was recorded at 14⬚C in blueberry. The oviposition period was longest (⬇38 d) at 14⬚C on cherry (Fig. 2). Oviposition on cherries at 14⬚C started at 29 d postemergence and continued to 64 d postemergence in one case. Preoviposition periods decreased as temperatures increased in both fruit treatments. At all temperatures, age-speciÞc fecundity assumed a normal curve shape typical of insects (Carey 1993). The maximum fecundity of 141 eggs per female was recorded at 18⬚C on cherry. Life Table Parameters and Threshold Determination. Because both cherries and blueberries produced ßies with similar developmental times from egg to adult, data of both fruit types were combined to determine lower threshold, upper threshold, and optimal developmental temperatures (Table 4). The function obtained by linear regression using 10, 14, 18, and 22⬚C

Temperatures where D. suzukii fecundity (eggs per adult female life stage ⴞ SEM) was measured on cherry and blueberry Temperature (⬚C) 14

18

22

26

28

18.6 ⫾ 2.1cA 6.6 ⫾ 2.1eB

141 ⫾ 20.3aA 17 ⫾ 2.1cB

62 ⫾ 15.2bA 19.8 ⫾ 7.9cB

20.3 ⫾ 2.1cA 12.1 ⫾ 4.9dB

12 ⫾ 0.5dA 7.3 ⫾ 0.8eB

Means within a row followed by different lowercase letters are different and means within a column followed by different uppercase letters are signiÞcantly different. Means were separated using TukeyÕs HSD (P ⬍ 0.05).

506

ENVIRONMENTAL ENTOMOLOGY

Vol. 43, no. 2

Fig. 3. Optimum temperature for development and minimum and maximum developmental thresholds for D. suzukii as a function of temperature.

Fig. 2. Mean daily D. suzukii egg production at Þve temperatures on cherry (A) and blueberry (B).

was y ⫽ 0.0048x ⫺ 0.0344 (R2 ⫽ 0.997; F ⫽ 4289; df ⫽ 1, 8; P ⫽ 0.0001), with an estimated lower developmental threshold of 7.2⬚C (Fig. 3). The thermal constant, k ⫽ 208.33 DD, was obtained using the minimum threshold temperature from linear regression. The upper developmental threshold temperature (42.1⬚C) and optimal temperature for development (28.1⬚C) were obtained using the nonlinear model. The nonlinear equation is y ⫽ (0.156e⫺6) ⫻ (x ⫺ (6.513))((42.0577) ⫺ x)exp(1/0.235) (R2 ⫽ 0.98; F ⫽ 26.12; df ⫽ 1, 9; P ⫽ 0.00028). We estimate that there will be 7.1 generations per season using 20-yr daily means for the publicly availTable 4.

able weather collected from Corvallis, OR (USDIÑBureau of Reclamation). The developmental times spent in each life stage from cherries and blueberries showed similarities (Tables 1 and 2). Generation time (T) for D. suzukii ranged from 12 to 43.9 d and decreased with an increase in temperature. The net reproductive rate (Ro) and intrinsic rate of population increase (rm) for both fruit increased as temperature increased to peak at 22⬚C, and then decreased at 28⬚C (Table 4). The rate of increase was above zero in all cases, indicating positive population growth over this range of temperatures. The numerically highest population developmental parameters were found from D. suzukii on cherries at 22⬚C, Ro ⫽ 195.1 eggs per female, rm ⫽ 0.22, and generation time of 24.2 d. The corresponding parameters on blueberries were lower. The lowest Ro and rm for D. suzukii were recorded at 28⬚C on blueberries with estimated values Ro ⫽ 0.6 and rm ⫽ 0.01. For cherries, the lower (13.4⬚C) and upper (29.33⬚C) threshold for rm and optimal temperature (21⬚C) were obtained using nonlinear estimation. The nonlinear equation is y ⫽ (0.0000161) ⫻ (x ⫺ (13.4))((29.33) ⫺ x)exp(1/0.33) (R2 ⫽ 0.81; F ⫽ 13.04; df ⫽ 1, 9; P ⫽ 0.024). Population Modeling. The functions Þtted to survival and fecundity provided good Þt to the analyzed

Parameters of temperatures where population increase for D. suzukii was measured on cherry and blueberry Developmental and reproductive parameters Ro

Temperature (⬚C) 14 18 22 26 28

T

rm

Cherry

Blueberry

Cherry

Blueberry

Cherry

Blueberry

8.1 140.8 195.1 13.4 2.1

7.0 33 79.1 17.2 0.6

43.9 39 24.2 12.5 12.7

39 28.3 25.1 13.9 12

0.05 0.13 0.22 0.21 0.02

0.05 0.12 0.17 0.2 0.01

Ro, the net reproductive rate; T, mean generation time in days; rm, intrinsic rate of population increase.

April 2014 Table 5. Day Survival 1Ð9 10Ð15 16Ð25 26Ð35 36Ð45 46Ð50 Fecundity 1Ð9 10Ð15 16Ð25 26Ð35 36Ð45 46Ð50

TOCHEN ET AL.: D. suzukii TEMPERATURE-RELATED DEVELOPMENT

507

Functions describing survival and fecundity of D. suzukii for each of six age periods (d) on cherry R2

F-Value

P value

df

Y ⫽ ⫺0.0008x2 ⫹ 0.02x ⫹ 0.85 Y ⫽ ⫺0.004x2 ⫹ 0.11x ⫹ 0.25 Y ⫽ ⫺0.005x2 ⫹ 0.13x ⫹ 0.17 Y ⫽ ⫺0.004x2 ⫹ 0.08x ⫹ 0.6 Y ⫽ ⫺0.002x2 ⫹ 0.03x ⫹ 0.9 Y ⫽ ⫺0.002x2 ⫹ 0.009x ⫹ 1.2

0.72 0.91 0.84 0.88 0.87 0.89

2523 808 180 176 117 74

⬍0.01 ⬍0.01 ⬍0.01 ⬍0.01 ⬍0.01 ⬍0.01

3 3 3 3 3 3

0 Y ⫽ (0.002) ⫻ (x ⫺ (30.97)) ( (18.8) ⫺ x)exp (1/ (2.2)) 2 Y ⫽ ⫺0.15x ⫹ 6.1x ⫺ 54.8 Y ⫽ ⫺ 0.1 x2 ⫹ 3.6x ⫺ 28.1 Y ⫽ ⫺ 0.1 x2 ⫹ 4.4x ⫺ 31.4 Y ⫽ ⫺ 0.1 x2 ⫹ 3.9x ⫺ 27.6

Ð 0.54 0.63 0.57 0.70 0.76

Ð

Ð ⬍0.01 ⬍0.01 ⬍0.01 ⬍0.01 ⬍0.01

Ð 4 3 3 3 3

Function

data (Table 5). Cherry harvest during 2011 and 2012 occurred from 15 June to 30 July. The Þrst color change of early cultivars was as early as the Þrst week of June during both seasons (P. Shearer, personal communication). Reports of crop losses in this region owing to D. suzukii were made during 2012, whereas in 2011 no crop losses were reported by packing houses (P. Shearer, personal communication). First color change in 2011 was estimated at 953 DD and in 2012 the estimate was 1043 DD. The conclusion of harvest in 2011 was at 1605 DD, and harvest was over in 2012 at 2029 DD. Populations of D. suzukii were detected earlier in 2012 compared with 2011, and estimates of population size in Hood River were higher in 2012 during the cherry harvest period (Fig. 4). Comparing the two seasons, peak adult emergence of the Þrst-generation females was estimated to be 2 wk later in 2011 (19 June) than in 2012 (4 June). The current online model (Coop 2012) estimated that these Þrst-generation females would have emerged by 11 July in 2011 and 30 June in 2012. The model predicted a later timing of second-generation adults than was actually seen, as well. The Leslie matrix can provide population estimates in addition to timing of adult activity. The peak adult emergence population of the Þrst generation females was 15% of the total during 2011 compared with those estimated to emerge in

Fig. 4. Population estimates for D. suzukii during the peak harvest period of cherries in Hood River during 2011 and 2012 starting with a population of 100 ovipositing females.

6 20 15 22 14

2012. The peak adult emergence population estimates of the second-generation females were 56% of the estimated total number of adults emerging during 2012 for Hood River. The mean estimated percent of adult ßies at peak harvest during 2011 was estimated to be at 26% of the total compared with that of 2012. Discussion The data presented in this study provide a comprehensive set of survival, developmental, and reproductive parameters for a D. suzukii colony that continues to be maintained in Oregon. Age-related female survival and oviposition at each temperature provide an indication of which temperatures are most suitable for longevity and reproduction of D. suzukii. Both survival and reproductive potential are summarized by the rm values and indicate optimal population increase at 21⬚C using nonlinear estimation. The lower and upper estimated thresholds for population increase are realistic in comparison with tephritids (QuesadaMoraga et al. 2012) and initial data on D. suzukii (Kanzawa 1939, Kimura 2004). It is clear that Drosophila fecundity can vary signiÞcantly depending on Wolbachia spp. pathogen infection status (Weeks et al. 2007) and should be investigated further. The fact that no adult males were recorded at 30⬚C for both cherry and blueberry suggests that D. suzukii has low survival in the Þeld at these temperatures. In the current study, only three individuals (1.5%) survived to adulthood at this upper temperature. The relatively low survival rates and slow developmental rates recorded on both fruit at 10 and 30⬚C are an indication that these temperatures are close to the developmental extremes for D. suzukii. A recent study has shown high mortality for ßies subjected to even more severe cold temperatures (Dalton et al. 2011). Data lacking from this study are temperature-related survival rates of the individual developmental stages of eggs and larvae. The developmental period from egg to adult ranged from 28.8 d at 14⬚C to 10.8 d at 26⬚C. These Þndings are similar to earlier research that showed developmental periods from egg to adults at 37 d under ßuctuating cold temperatures (10 Ð14⬚C), and 11 d at ßuctuating mild temperatures (24 Ð26⬚C; Kanzawa 1939). The life

508

ENVIRONMENTAL ENTOMOLOGY

history traits identiÞed under constant temperatures in the current study are not possible to directly compare with the decades-old research conducted on D. suzukii at ßuctuating temperatures in Japan (Kanzawa 1939). In our study, developmental periods decreased in an approximately linear fashion from 14 to 26⬚C before increasing again at the hottest temperature of 30⬚C. Reproduction of D. suzukii was facilitated in cherries and blueberries at temperatures ranging from 14 to 28⬚C. The mean fecundity per female increased with increasing temperatures up to 22⬚C, and decreased at temperatures above this for both fruit types. Fecundity rates of the closely related Drosophila simulans over a 10-d period ranged from 350 to 500 eggs per female, depending on the strain of Wolbachia spp. infection present (Weeks et al. 2007). Fecundity of D. suzukii on cherries, as recorded by Kanzawa (1939), was 172 eggs per female. The highest mean oviposition recorded in this study was 141 eggs per female at 18⬚C over 45 d, a much lower value than found on D. simulans (Weeks et al. 2007). However, our fecundity data are relatively similar to that found by earlier research (Kanzawa 1939). Direct comparisons between studies cannot be made because of lacking environmental data from the earlier work. In addition, the Wolbachia spp. infection status of past study populations is unknown but may have impacted D. suzukii fecundity. The fecundity of D. suzukii on blueberries was signiÞcantly lower than that found in cherries, with the highest fecundity of 19.8 eggs per female recorded at 22⬚C. In a separate unpublished study (J. L., unpublished data), the fecundity rate of D. suzukii was higher at 148.4 ⫾ 19.1 eggs over a 4-wk period on Elliott blueberries and 160.5 ⫾ 46.8 eggs on artiÞcial rearing medium. This may be a possible indication that the cultivars used in our study were comparably less suitable than Elliott for oviposition and development. The fact that no reproduction was recorded at 10 and 30⬚C does not mean that reproduction cannot occur at these temperatures, but rather that these temperatures may approach the lower and upper extremes for development, irrespective of Wolbachia spp. infection status. Future work at extreme developmental boundaries may be useful to explain possible Þeld reproduction under these conditions. The high Wolbachia spp. infection rates of the laboratoryreared cultures may have negatively inßuenced the fecundity levels found in the current study owing to cytoplasmic incompatibility (Turelli and Hoffmann 1991, 1995). Hamm and Turelli (unpublished data) found signiÞcantly lower fecundity levels when comparing high rates of Wolbachia spp. infection with lower rates of infection from D. suzukii populations collected from California caneberry Þelds during the 2012 Þeld season. The impact of Wolbachia spp. infection on developmental parameters of D. suzukii did not fall in the scope of the current study but it is acknowledged that this organism has a signiÞcant impact on mortality. Additional detailed studies focused on the inßuence and incidence of Wolbachia spp.

Vol. 43, no. 2

infection is needed. Our current study, however, does provide comparative reproductive data when looking at temperature and fruit type using a D. suzukii stock culture highly infected with Wolbachia spp. We believe that our D. suzukii population estimates provide a clearer picture of relative pest pressure when comparing less optimal to more optimal growing seasons. We assume that higher populations of D. suzukii translate to increased pest pressure owing to oviposition in susceptible fruit. Rejections of fruit owing to D. suzukii infestation were recorded during the more optimal D. suzukii 2012-growing season in Hood River, compared with no rejections during the less optimal season of 2011. In 2012, population levels at cherry harvest were approximately four times higher than 2011 levels at harvest. Our data suggest that D. suzukii has short generation times and high reproductive levels compared with other Dipteran pests found in fruit in the United States (Reissig et al. 1979, Teixeira and Polavarapu 2001, Quesada-Moraga 2012). The apple maggot, Rhagoletis pomonella (Walsh) (Diptera: Tephritidae) (Reissig et al. 1979), and blueberry maggot, Rhagoletis mendax (Curran) (Teixeira and Polavarapu 2001), both complete fewer generations per season than D. suzukii. It is more important to predict Þrst emergence in the case of these pests. For the Lepidopteran pests such as Cydia pomonella L. (Lepidoptera: Tortricidae), another severe fruit pest with relatively discrete generations, the same is true (Jones and Wiman 2012). The thermal constant for C. pomonella was estimated to range from 510 to 615 DD (Rock and Shaffer 1983, Aghdam et al. 2009), and the intrinsic rate of natural increase (rm) was 0.08 (Rock and Shaffer 1983). The thermal constant and rm values are 208 DD and 0.2, respectively, for D. suzukii, allowing more rapid population increase in comparison to these insects. We therefore believe that pest models using only DD have limited value for D. suzukii for three reasons. First, D. suzukii has relatively short generation times, and generations begin to overlap relatively early during the growing season. Second, D. suzukii has a high reproductive potential and population increase is more rapid at ideal temperatures. Third, ßuctuating temperatures dramatically impact both reproduction and survival for D. suzukii, and DD models do not estimate the impact of these ßuctuations on insect population levels and resultant population pressure. We believe that the population estimate model of D. suzukii described here can be useful to approximate population levels, to more clearly determine the number of injurious life stages and provide additional information that may aid in decision making. Future research efforts will be directed toward validating and improving this temperature-dependent matrix model for D. suzukii in a wider range of production regions. Our study is an attempt to understand the impact of temperature on D. suzukii developmental, survival, and reproductive parameters. Information from this work is intended to identify temperature factors favorable to D. suzukii but by no means provides a comprehensive picture of all factors inßuencing D. suzukii population levels. More detailed work is

April 2014

TOCHEN ET AL.: D. suzukii TEMPERATURE-RELATED DEVELOPMENT

needed on the mechanisms of winter survival, the impact of humidity on development and population increase parameters under controlled ßuctuating temperatures, and the effects of pathogen infection on fecundity, and the impact of temperature on the immature developmental stages of eggs and larvae. Acknowledgments Thanks to Anita Azarenko, Bernadine Strik, David Bryla, and Jay Pscheidt for providing fresh fruit needed for experimentation. Technical support, laboratory rearing, Þeld-collected insects, and data procurement was provided by Betsey Miller and Preston Brown. Funding for this research was provided from the U.S. Department of AgricultureÐNational Institute of Food and Agriculture (USDAÐNIFA) award #2010-51181-21167.

References Cited Aghdam, H. R., Y. Fathipour, G. Radjabi, and M. Rezapanah. 2009. Temperature-dependent development and temperature thresholds of codling moth (Lepidoptera: Tortricidae) in Iran. Environ. Entomol. 38: 885Ð895. Baskerville, G. L., and P. Emin. 1969. Rapid estimation of heat accumulation from maximum and minimum temperatures. Ecology 50: 514Ð517. Beers, E. H., R. A. Van Steenwyk, P. W. Shearer, W. W. Coates, and J. A. Grant. 2011. Developing Drosophila suzukii management programs for sweet cherry in the western United States. Pest Manag. Sci. 67: 1386Ð1395. Briere, J. F., P. Pracros, A. Y. Le Roux, and J. S. Pierre. 1999. A novel rate model of temperature-dependent development for arthropods. Environ. Entomol. 28: 22Ð29. Bruck, D. J., M. Bolda, L. Tanigoshi, J. Klick, J. Kleiber, J. DeFrancesco, B. Gerdeman, and H. Spitler. 2011. Laboratory and Þeld comparisons of insecticides to reduce infestation of Drosophila suzukii in berry crops. Pest Manag. Sci. 67: 1375Ð1385. Campbell, A., B. D. Frazer, N. Gilbert, A. P. Gutierrez, and M. Mackauer. 1974. Temperature requirements of some aphids and their parasites. J. Appl. Ecol. 11: 431Ð438. Carey, J. R. 1993. Reproduction, pp. 43Ð76. In J. R. Carey (ed.), Applied Demography for Biologists with Special Emphasis on Insects. Oxford University Press, New York, NY. Carey, J. R. 2001. Insect biodemography. Annu. Rev. Entomol. 46: 79 Ð110. Cha, D. H., T. Adams, H. Rogg, and P. J. Landolt. 2012. IdentiÞcation and Þeld evaluation of fermentation volatiles from wine and vinegar that mediate attraction of spotted wing drosophila, Drosophila suzukii. J. Chem. Ecol. 38: 1419 Ð1431. Cini, A., C. Ioriatti, and G. Anfora. 2012. A review of the invasion of Drosophila suzukii in Europe and a draft research agenda for integrated pest management. Bull. Insectol. 65: 149 Ð160. Clopper, C. J., and E. S. Pearson. 1934. The use of conÞdence or Þducial limits illustrated in the case of the binomial. Biometrika 26: 404 Ð 413. Coop, L. 2012. Online phenology and degree-day model for agricultural and decision-making in the US. Integrated Plant Protection Center, Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR. (http://uspest.org/risk/models_spp_swd). Dalton, D. T., V. M. Walton, P. W. Shearer, D. B. Walsh, J. Caprile, and R. Isaacs. 2011. Laboratory survival of Drosophila suzukii under simulated winter conditions of the

509

PaciÞc Northwest and seasonal Þeld trapping in Þve primary regions of small and stone fruit production in the United States. Pest Manag. Sci. 67: 1368 Ð1374. Eisensmith, S. P., A. L. Jones, E. D. Goodman, and J. A. Flore. 1982. Predicting leaf expansion of ÔMontmorencyÕ sour cherry from degree-day accumulations. J. Am. Soc. Hort. Sci. 107: 717Ð722. Goodhue, R. E., M. Bolda, D. Farnsworth, J. C. Williams, and F. G. Zalom. 2011. Spotted wing drosophila infestation of California strawberries and raspberries: economic analysis of potential revenue losses and control costs. Pest Manag. Sci. 67: 1396 Ð1402. Jones, V. P., and N. G. Wiman. 2012. Modeling the interaction of physiological time, seasonal weather patterns, and delayed mating on population dynamics of codling moth, Cydia pomonella (L.) (Lepidoptera: Tortricidae). Popul. Ecol. 54: 421Ð 429. Kanzawa, T. 1939. Studies on Drosophila suzukii Mats. Kofu, Yamanashi Agricultural Experiment Station 49 pp. (abstr.). Rev. Appl. Entomol. 29: 622. Kawase, S., K. Uchino, and K. Takahashi. 2007. Control of cherry drosophila, Drosophila suzukii, injurious to blueberry. Plant Prot. 61: 205Ð209. Kimura, M. T. 2004. Cold and heat tolerance of drosophilid ßies with reference to their latitudinal distributions. Oecologia 140: 442Ð 449. Landolt, P. J., T. Adams, and H. Rogg. 2012. Trapping spotted wing drosophila, Drosophila suzukii (Matsumura) (Diptera: Drosophilidae), with combinations of vinegar and wine, and acetic acid and ethanol. J. Appl. Entomol. 136: 148Ð154. Lee, J. C., H. J. Burrack, L. D. Barrantes, E. H. Beers, A. J. Dreves, K. A. Hamby, D. R. Haviland, R. Isaacs, T. A. Richardson, P. W. Shearer, et al. 2012. Evaluation of monitoring traps for Drosophila suzukii (Diptera: Drosophilidae) in North America. J. Econ. Entomol. 105: 1350Ð1357. Lee, J. C., D. J. Bruck, H. Curry, D. L. Edwards, D. Haviland, R. Van Steenwyk, and B. Yorgey. 2011. The susceptibility of small fruits and cherries to the spotted wing drosophila, D. suzukii.. Pest Manag. Sci. 67:1358 Ð 6137. Liu, S. S., and X. D. Meng. 1999. Modeling development time of Myzus persicae (Hemiptera: Aphididae) at constant and natural temperatures. Bull. Entomol. Res. 89: 53Ð63. Mitsui, H., K. H. Takahashi, and M. T. Kimura. 2006. Spatial distributions and clutch sizes of Drosophila spp. ovipositing on cherry fruits of different stages. Popul. Ecol. 48: 233Ð237. Mitsui, H., K. Van Achterberg, and G. Nordlander. 2007. Geographical distributions and host associations of larval parasitoids of frugivorous Drosophilidae in Japan. J. Nat. Hist. 41: 1731Ð1738. Nice, C. C., Z. Gompert, M. L. Forister, and F. A. Fordyce. 2009. An unseen foe in arthropod conservation efforts: the case of Wolbachia infections in the Karner blue butterßy. Biol. Conserv. 142: 3137Ð3146. Price, P. W. 1997. Insect ecology, pp. 169 Ð197, 3rd edn. Population Dynamics Wiley, New York, NY. Quesada-Moraga, E., P. Valverde-Garcı´a, and I. Garrido-Jurado. 2012. The effect of temperature and soil moisture on the development of the preimaginal Mediterranean fruit ßy (Diptera: Tephritidae). Environ. Entomol. 41: 966Ð970. Reissig, W. H., J. Barnard, R. W. Weires, E. H. Glass, and R. W. Dean. 1979. Prediction of apple maggot ßy emergence from thermal unit accumulation. Environ. Entomol. 8: 51Ð54. Rock, G. C., and P. L. Shaffer. 1983. Developmental rates of codling moth (Lepidoptera: Olethreutidae) reared on apple at four constant temperatures. Environ. Entomol. 12: 831Ð 834.

510

ENVIRONMENTAL ENTOMOLOGY

R Development Core Team. 2013. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (ISBN 3-900051-07-0). Teixeira, L.A.F., and S. Polavarapu. 2001. Postdiapause development and prediction of emergence of female blueberry maggot (Diptera: Tephritidae). Environ. Entomol. 30: 925Ð931. Turelli, M., and A. A. Hoffmann. 1991. Rapid spread of an inherited incompatibility factor in California Drosophila. Nature 353: 440 Ð 442. Turelli, M., and A. A. Hoffmann. 1995. Cytoplasmic incompatibility in Drosophila simulans: dynamics and parameter estimates from natural populations. Genetics 140: 1319Ð1338.

Vol. 43, no. 2

Walsh, D. B., M. P. Bolda, R. E. Goodhue, A. J. Dreves, J. Lee, D. J. Bruck, V. M. Walton, S. D. O’Neal, and F. G. Zalom. 2011. Drosophila suzukii (Diptera: Drosophilidae): invasive pest of ripening soft fruit expanding its geographic range and damage potential. J. Integr. Pest Manag. 2: G1ÐG7. Weeks, A. R., M. Turelli, W. R. Harcombe, K. T. Reynolds, and A. A. Hoffmann. 2007. From parasite to mutualist: rapid evolution of Wolbachia in natural populations of Drosophila. PLoS Biol. 5: e114. Received 11 July 2013; accepted 30 January 2014.