Redbay ambrosia beetle, Xyleborus glabratus Eichhoff (Coleoptera: Curculionidae: Scolytinae), is a nonnative pest that transmits the pathogenic fungus Raffaelea lauricola T.C. Harr., Fraedrich & Aghayeva (Ophiostomatales: Ophiostomataceae), which causes laurel wilt disease in trees of the family Lauraceae. Laurel wilt is present in the commercial avocado (Persea americana Mill.; Laurales: Lauraceae) growing areas of Florida and poses a potential threat to the avocado industries of California and Mexico. The life cycle of X. glabratus was studied in avocado logs at 16, 20, 24, 28, and 32 °C. Xyleborus glabratus successfully completed its life cycle at 24, 28, and 32 °C, with the greatest oviposition and development rate at 28 °C. Development of the egg and pupal stages was studied at 12, 16, 18, 20, 24, 28, 32, and 36 °C. One linear and 7 nonlinear developmental models were used to estimate the temperature-dependent development of both stages. The linear model estimated the lower threshold temperatures for egg and pupal development to be 13.8 °C and 11.1 °C, respectively, and the degree-days (DD) for egg and pupal development to be 55.1 DD and 68.2 DD, respectively. The Brier-2, Ratkowsky, Logan, and polynomial models gave the best estimates for the temperature-dependent development of the egg stages, whereas the Brier-1, Logan, and polynomial models gave the best estimates of temperature-dependent development of the pupal stages. Our results suggested that the optimal temperature for development of X. glabratus was around 28 °C, and that temperature will play an important role in the spread and successful establishment of X. glabratus.
The exotic redbay ambrosia beetle, Xyleborus glabratus Eichhoff (Coleoptera: Curculionidae: Scolytinae) has become a serious pest of trees of the family Lauraceae in the United States. The beetle is native to Southeast Asia and was introduced accidentally in the southeastern United States around 2002 (Haack 2003; Rabaglia et al. 2008; Peña et al. 2012). The redbay ambrosia beetle transmits the fungus Raffaelea lauricola T.C. Harr., Fraedrich & Aghayeva (Ophiostomatales: Ophiostomataceae), (Fraedrich et al. 2008; Hanula et al. 2008) that causes laurel wilt, a lethal vascular disease. Since the introduction of the beetle, the laurel wilt pathogen has been detected in the following Lauraceae species: redbay (Persea borbonia [L.] Spreng.), avocado (Persea americana Mill.), swampbay (Persea palustris [Raf.] Sarg.), silkbay (Persea humilis Nash), sassafras (Sassafras albidum [Nutt.] Nees), northern spicebush (Lindera benzoin [L.] Blume), pondspice (Litsea aestivalis [L.] Fernald), pondberry (Lindera melissifolia [Walter] Blume), and camphor tree (Cinnamomum camphora [L.] J. Presl). It sometimes causes mortality of 90% of infested trees (Fraedrich et al. 2008; Mayfield et al. 2008; Smith et al. 2009a, b; Hughes et al. 2013). Experimental inoculations with R. lauricola indicate that California bay laurel (Umbellularia californica [Hook & Arn.] Nutt.) and Gulf licaria (Licaria triandra [Sw.] Kosterm.) also are susceptible (Fraedrich 2008; Ploetz & Konkol 2013). Identical rates of development of X. glabratus were observed in avocado, redbay, and swampbay logs held at 25 ± 2 °C, with teneral adult stages encountered approximately 1 mo after gallery initiation (Brar et al. 2013). The emissions of α-cubebene, α-copaene, α-humulene, and calamenene from host trees were correlated with attraction of adult beetles to the host trees (Kendra et al. 2011, 2014). Laurel wilt currently is present in commercial avocado groves in southern Florida (FDOACS 2012) and has been the subject of recent reviews (Kendra et al. 2013; Ploetz et al. 2013).
Since its introduction, the redbay ambrosia beetle has been reported in North Carolina, South Carolina, Georgia, Florida, Alabama, and Mississippi, USA, and its range has expanded more quickly than predicted by Koch & Smith (2008). Beetle population dynamics studies in South Carolina and Georgia, USA, have shown that adult beetles were active throughout the year, with greater flight activity in Sep compared with Jan and Feb (Hanula et al. 2008, 2011). In Alachua County, Florida, USA, strong activity of the beetles was recorded in Apr 2010, Oct 2010, and Mar 2011, whereas little activity was recorded in Nov 2010, Dec 2010, and Jan 2011 (Brar et al. 2012). This suggests that the beetles are more active in the summer months than in colder months in northern Florida. Variation in temperature, along with other climatic variables, might play an important role in the population dynamics of this species (Brar et al. 2012). Given the potential impact of the beetle-fungus complex on the avocado industry of Florida and California, USA, and its potential threat to other lauraceous plants throughout North, Central, and South America (Gramling et al. 2010; Peña et al. 2012), it is desirable to develop phenological and population dynamics models to help predict pest infestations, and to initiate control measures.
Climate limits the distribution of insect pests, with temperature being one of the abiotic factors that play a major role. Knowledge of insect development in relation to temperature is critical in order to understand insect population dynamics, but knowledge of temperature relations is also essential to create phenological predictive models. During the last few decades, various mathematical models have been used to model temperature-dependent development of insects. These models range from simple linear models (Campbell et al. 1974; Roy et al. 2002) that can predict the lower developmental threshold temperature within limited ranges of temperature, to nonlinear mathematical models (Logan et al. 1976; Taylor 1981; Ratkowsky et al. 1983; Lamb at al. 1984; Lactin et al. 1995; Briere et al.1999) that can describe temperature-dependent development over wider ranges of temperatures. Nonlinear models have been compared to find the model that reliably predicts development close to actually observed values based on commonly used criteria such as higher r2 (coefficient of determination) and lower RSS (residual sum of squares) and AIC Akaike information (Walgama & Zalucki 2007b; Aghdam et al. 2009; Sandhu et al. 2010, 2013). The objectives of this study were to 1) evaluate temperaturedependent development of the egg and pupal stages of X. glabratus, 2) develop a valid model based on various linear and nonlinear models, and 3) study the life cycle and temperature-dependent development of X. glabratus in avocado logs placed at different constant temperatures.
Materials and Methods
BEETLE SOURCE
Redbay and swampbay trees with high infestations of X. glabratus were scouted at 3 locations in Florida, USA, i.e., Austin Cary Memorial Forest (Alachua County), Ordway-Swisher Biological Station (Putnam County), and Hammock Dunes Club Golf Course, Palm Bay (Brevard County). Infested logs were collected, and a beetle colony was maintained at the University of Florida, Entomology and Nematology Department, Gainesville (Alachua County), Florida, USA, by methods previously reported (Brar et al. 2013).
REARING OF X. GLABRATUS FOR DEVELOPMENTAL STAGES
Avocado ‘Booth 7’ logs measuring 4.5 to 6.5 cm in diameter and 8 to 10 cm in length from healthy trees without beetle infestation were procured from the University of Florida, Tropical Research and Education Center, Homestead (Miami Dade County), Florida, USA. Logs were soaked in tap water for 48 h, removed, and individually placed in 946 mL clear plastic containers (American Plastics, Gainesville, Florida, USA). Each container was covered with Plankton netting (150 microns, BioQuip, Rancho Dominguez, California, USA). To keep the logs moist, approx. 100 mL of water were maintained in each container throughout the experiment. Twenty sclerotized female adult beetles were placed directly on the bark of each log and were allowed to bore. Logs were kept in an incubator (Precision® illuminated incubator, Precision Scientific Inc., Chicago, Illinois, USA) at 25 ± 2 °C in complete darkness. The number of logs infested on a given day was dependent on the number of adult females available. Infested logs were divided into 2 sets, one for collection of eggs and the other for collection of pupae. Based on data previously obtained regarding the life cycle of X. glabratus on avocado (Brar et al. 2013), the logs were split and galleries carefully opened with a hand pruner (Fiskars compound anvil hand pruner, Lowes, Gainesville, Florida, USA) on the 10th to 13th day after gallery initiation, and eggs were carefully extracted with sterilized needles. In like manner, the logs were split, galleries carefully opened on the 24th to 26th day after gallery initiation, and pupae were extracted.
DEVELOPMENT OF EGG AND PUPAL STAGES AT CONSTANT TEMPERATURES
The duration of development from egg to larval stage and from pupal to adult stage was studied at constant temperatures. Eggs extracted from avocado logs were placed in Petri dishes (50 × 9 mm, BD Falcon, Franklin Lakes, New Jersey, USA) lined with moist paper towel. Petri dishes were placed in Florida Reach-In incubators (Walker et al. 1993) held at constant temperatures of 12, 16, 20, 24, 28, 32, and 36 °C (± 0.1 °C) and kept under constant darkness. For each temperature, the numbers of larvae that hatched were recorded daily. Numbers of eggs used for each temperature study were dependent on the numbers available after splitting the logs. The number of eggs placed at each temperature ranged from 20 to 60. Pupae extracted from avocado logs were placed in Petri dishes following the same method used for eggs. Numbers of pupae placed at each temperature treatment ranged from 20 to 45. The number of days required for the development of egg to the 1st instar and from the pupal to the adult stage for all temperature treatments was recorded daily. Paper towels were kept moist to prevent desiccation of insects. The study was conducted between Mar and Jun 2012. Temperature-dependent development of the various larval instars was not studied due to lack of an adequate artificial medium on which to rear larvae.
LIFE CYCLE AND DEVELOPMENT OF X. GLABRATUS IN AVOCADO LOGS AT CONSTANT TEMPERATURES
The life cycle and development of X. glabratus in avocado logs were studied at 5 constant temperatures (16, 20, 24, 28, and 32 °C) during Sept 2011 to May 2012. Avocado ‘Booth 7’ logs of 4.5 to 6.5 cm diameter were cut from healthy trees without any beetle infestation from the University of Florida, Tropical Research and Education Center, Homestead (Miami Dade County), Florida, USA. The logs were cut to 8 to 10 cm length, soaked in tap water for 48 h, and then placed in a 946 mL clear plastic container (American Plastics, Gainesville, Florida, USA). Depending on the availability of beetles, 5 to 20 sclerotized adult female beetles were placed on each log and allowed to bore for 24 h at 25 ± 2 °C. Each container was covered with Plankton netting (150 microns, BioQuip, Rancho Dominguez, California, USA). After 24 h of infestation, infested logs were placed in Florida Reach-In incubators (Walker et al. 1993) held at 5 constant temperatures (16, 20, 24, 28, and 32 °C [± 0.1 °C]) under complete darkness. For each temperature treatment, 60 logs were infested and studied for 40 d. For each temperature treatment, every other day, 3 logs or 3 replicates were randomly removed from the incubators, and for each log, 5 active galleries (with signs of fresh frass) were marked with a permanent marker (Sharpie pen). The logs were split to expose the marked galleries, and galleries were further dissected to record the number of insects at each developmental stage. The whole study was repeated twice.
MATHEMATICAL MODELS AND STATISTICAL ANALYSES
The development rate of eggs and pupal stages was regressed against temperature in linear and nonlinear models. Seven nonlinear models (Table 1) used to describe temperature-dependent development of insects—such as Halyomorpha halys (Stal) (Hemiptera: Pentatomidae) (Nielsen et al. 2008), Cydia pomonella L. (Lepidoptera: Tortricidae) (Aghdam et al. 2009), Plutella xylostella L. (Lepidoptera: Plutellidae) (Golizadeh et al. 2007), and Elasmopalpus lignosellus (Zeller) (Lepidoptera: Pyralidae) (Sandhu et al. 2010, 2013)-were used to describe temperature-dependent development of the egg and pupal stages of X. glabratus. The estimated parameters were T0 (the temperature at, or below, which no measurable development was visible; also called lower development threshold) (Howell & Neven 2000; Sandhu et al. 2010), Tm (upper development threshold, temperature at, or above, which no visible development takes place) (Kontodimas et al. 2004; Sandhu et al. 2010), Topt (temperature at which highest rate of development takes place) (Briere & Pracros 1998; Sandhu et al. 2010), and K (thermal constant; the number of degree-days required by an immature stage to complete its development) (Campbell et al. 1974; Aghdam et al. 2009). The value of T0 can be estimated from a linear model and from 3 nonlinear models (Briere-1, Briere-2, and Ratkowsky and Taylor). Tm can be estimated by nonlinear models (Briere-1, Briere-2, Lactin, and Logan). Topt can be calculated with the Taylor, Briere-1, Briere-2, and Lactin and Logan models. In the Briere-1 and Briere-2 models, Topt can be calculated by Equation 1.
Table 1.
Mathematical equations of nonlinear developmental models tested to describe the relationship between temperature and development of egg and pupal stages of Xyleborus glabratus.
The m is the empirical constant with value 2 for the Briere model (Briere & Pracros 1998). In the Lactin and Logan models, Topt can be estimated as the parameter value for which the first derivative equals zero. In the Taylor model, Topt can directly be estimated from the model (Table 1). The value of K can be estimated by linear regression (Campbell et al. 1974). Criteria used to compare performance of nonlinear mathematical models were (1) coefficient of determination (r2), wherein the higher value indicates a better fit of the model, and (2) residual sum of squares (RSS), wherein the lower value indicates a better fit of the model (Aghdam et al. 2009). A third additional criterion, the Akaike information criterion (AIC) was used to compare nonlinear models. The model that has the lower AIC value has a better fit when comparing models. AIC was calculated by Equation 2.
where n is the sample size, p is the number of parameters, and SSE is the sum of the squared errors.
Data for different experiments were tested with Shapiro-Wilk normality tests (Shapiro & Wilk 1965) to ensure that the assumptions of homogeneity of variance and normality were met before the data were analyzed. To determine differences between the duration of development from egg to larval stage and from pupal to adult stage at different constant temperatures, we subjected the data to separate 1-way analysis of variance (ANOVA) and Tukey-Kramer tests, by Proc GLM in SAS (SAS 2003). Linear regression (SAS) was used to model the rate of development for each stage at 16, 20, 24, and 28 °C. The linear model y = a + bx (Campbell et al. 1974) was used to estimate the lower developmental threshold temperature (Tmin = -a / b), and thermal constant (K = 1 / b). Seven nonlinear models (Table 1) were used to model temperature-dependent development of the egg and pupal stages. The nonlinear models were fitted with the Marquardt algorithm (Marquardt 1963) in SAS software. The differences in time to occurrence of different development stages after initial infestation of avocado logs at different constant temperatures were analyzed by conducting ANOVA in SAS. Tukey—Kramer tests were conducted to ascertain differences in duration of developmental stages of the beetle in logs at constant temperatures using SAS.
Results
EGG DEVELOPMENT
Temperature had a significant effect on egg development (F = 192.3; df = 5, 188; P < 0.0001) (Table 2). No development was observed in eggs held at 12 °C. Successful progression from egg to the 1st instar occurred from 16 to 36 °C, with the fastest development rate observed at 28 °C (Table 2). Mean development time for eggs ranged from 21.1 ± 0.75 d at 16 °C to 10.9 ± 0.75 d at 36 °C (Table 2). A linear regression model of temperatures ranging from 16 to 28 °C with development rate yielded a lower temperature threshold of 13.8 °C, requiring 52.1 DD for beetles to develop from egg to the larval stage (Table 3).
Table 2.
Mean (± SE) number of days required for development of Xyleborus glabratus eggs and pupae at constant temperatures.
The model evaluation parameters, fitted coefficients, and evaluation criteria indices for 7 nonlinear models tested for temperature-dependent development of egg to larval stages are presented in Table 4. The estimated optimum temperature for development of egg to larval stage ranged between 32.3 °C (Briere-2 model) and 27.7 °C (Taylor model). In general, all the models gave a good fit with r2 values above 0.85, except for the modified Lactin model, where the r2 value was 0.53. The Briere-2, Ratkowsky, polynomial, and Logan models gave better fits than other models based on a greater r2 value and smaller RSS and AIC values. The Taylor model gave a good fit based on the greater r2 value and smaller RSS and AIC values, but its estimated lower development thresholds were less than the observed values. The Logan model provided estimates of Tmax (37.0 °C) and Topt (28.7 °C). The Ratkowsky and Briere-2 models provided estimates of T0 (14.4 °C) that were closer to the observed values.
PUPAL DEVELOPMENT
Temperature had a significant effect on the development of the pupal stage (F = 97.5; df = 4, 144; P < 0.0001) (Table 2). No pupal development was observed at 12 and 36 °C. Mean development times for pupae ranged from 6.4 ± 0.26 d at 32 °C to 12.9 ± 0.51 d at 16 °C (Table 2). Development times for the pupal stages decreased from 16 to 28 °C and then increased at 32 °C. In the temperature range from 16 to 28 °C, linear regression yielded a lower temperature threshold of 11.1 °C, with the pupal stage requiring 68.2 DD to develop to the adult stage (Table 3).
Table 3.
Linear regression parameters for in vitro development of eggs and pupae of Xyleborus glabratus over a range of constant temperatures (16–28 °C).
Table 4.
Nonlinear regression parameters, fitted coefficients, and evaluation indices of 7 nonlinear models tested for temperature-dependent development of eggs and pupae of Xyleborus glabratus.
All nonlinear models gave a good fit with r2 values above 0.87 with the exception of the modified Lactin model, which gave a poor fit with an r2 value of 0.34. All the evaluation parameters, fitted coefficients, and evaluation criteria indices are presented in Table 4. The optimal temperature of development of the pupal to adult stage ranged from 27.4 °C (Taylor model) to 33.4 °C (Briere-1 model). The Briere-1, Logan, and polynomial models gave better fits based on a greater r2 value and smaller RSS and AIC values. The Taylor model was a good fit based on a greater r2 value and lower RSS and AIC values, but its estimated lower development thresholds were less than the observed values. The Logan model provided the best estimates of Tmax (33.7 °C) and Topt (28.7 °C).
LIFE CYCLE AND DEVELOPMENT OF X. GLABRATUS IN AVOCADO LOGS AT CONSTANT TEMPERATURES
Xyleborus glabratus successfully completed its life cycle in avocado logs held at temperatures of 24, 28, and 32 °C. There was no development observed at 16 °C. Temperature had a significant effect on the development of egg stage (F = 10.78; df = 3, 14; P = 0.0006), larval stage (F = 7.66; df = 3, 16; P = 0.0021), pupal stage (F = 12.76; df =3, 13; P = 0.0004), and teneral adults (F = 6.33; df = 2, 14; P = 0.01) in avocado logs placed at different constant temperatures ranging from 16 to 32 °C (Table 5). The mean number of days to first occurrence of each developmental stage in avocado logs held at various constant temperatures is presented in Table 5 and Figs. 1 to 4. The largest numbers of eggs, larvae, and teneral adults were encountered at 28 °C, followed by 24, 32, and 20 °C (Table 6). The largest numbers of pupae were observed at 24 °C followed by 28, 32, and 20 °C.
Discussion
The results from the current investigation suggest that duration of life cycle and development time of immature stages is strongly related to temperature. We exposed egg and pupal stages of X. glabratus to constant temperatures ranging from 12 to 36 °C. Egg and pupal development were similar, as reported for Xyleborus fornicatus Eichhoff (Gadd 1949; Walgama & Zalucki 2007a). For instance, X. fornicatus eggs and pupae did not develop at 15 °C; however, X. fornicatus eggs and pupae developed when held at 18 to 32 °C (Gadd 1947; Walgama & Zalucki 2007b). Likewise, eggs of Ips calligraphus (Germar) (Coleoptera: Curculionidae developed at 12.5 to 35.0 °C, and pupae developed at 12.5 to 37.0 °C, when exposed to constant temperatures ranging from 10 °C to 37.5 °C (Wagner et al. 1987, 1988). Identical trends of development were observed with Ips avulsus (Eichhoff) (Coleoptera: Curculionidae) egg and pupal stages, with development occurring from 15 to 35 °C when observed at 7 constant temperatures ranging between 10 and 35 °C (Wagner et al. 1988). Thus, X. glabratus egg and pupal development range temperatures were similar to those of other scolytine species.
Table 5.
Mean (± SE) number of days to first occurrence of each developmental stage of Xyleborus glabratus in avocado (Persea americana) logs held at constant temperatures. Results are based on the first observation of each developmental stage in avocado logs dissected at 2 d intervals.
One of the objectives was to select the mathematical model that would best explain the temperature-dependent development of X. glabratus. We tested 1 linear and 7 nonlinear models on how well they describe the relationships between temperature and the development rates of eggs and pupae. Linear correlation of the development rates of X. glabratus eggs and pupae with temperatures between 16 and 28 °C resulted in estimated lower developmental threshold temperatures of 13.8 °C and 11.1 °C for eggs and pupae, respectively. In contrast, the estimated lower developmental threshold temperatures for egg and pupal stages were 15.7 °C and 14.3 °C, respectively, for X. fornicatus (Walgama & Zalucki 2007a) and 10.6 °C and 9.9 °C, respectively, for Ips typographus (L.) (Coleoptera: Curculionidae) (Wermelinger & Seifert 1998). The lower threshold temperatures estimated by the linear model for the temperature-dependent development of eggs were close to the observed values, but the estimates for the pupal stage were below the lowest temperature tested experimentally. This discrepancy might be due to nonlinear relationships between temperature and development rate near the threshold temperatures (Wagner et al. 1991).
In the present investigation, we evaluated the performance of 7 nonlinear models to describe the development of egg and pupal stages of X. glabratus. The Briere-2, Ratkowsky, polynomial, and Logan models gave good fits for the temperature-dependent development of eggs as indicated by greater r2 and smaller RSS and AIC values, but the Logan model gave estimates that were closest to the actual observations. For temperature-dependent development of the pupal stage, the Briere-1, Logan, and polynomial models each gave a good fit, with the Logan model giving estimates closest to the observed values. The Logan model proved to be the best model based on the evaluation criteria and its closeness of estimated values of parameters to the actual observed values. In contrast, the Lactin model gave the best fit for temperaturedependent development of X. fornicatus as compared with other mathematical models tested (Walgama & Zalucki 2007b), whereas the Lactin model proved least fit to describe the temperature-dependent development of the egg and pupal stages of X. glabratus. The Briere-1 model gave the best fit for the temperature-dependent development of E. lignosellus as indicated by a larger r2 value and smaller RSS and AIC values (Sandhu et al. 2010). Examples of best fit for development rates include the following: Logan model for Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae) (Coop et al. 1993), Briere-2 model for P. xylostella (Golizadeh et al. 2007), Lactin 2 model for Sesamia nonagrioides (Lefèbvre) (Lepidoptera: Noctuidae) (Fantinou et al. 2003), and Briere-1 and Briere-2 models for C. pomonella (Aghdam et al. 2009). The variability in the performance of different mathematical models to describe the temperature-dependent development of insects might be due to variability in thermal adaptations of different insect species (Sandhu et al. 2010), but the quality of the data set, especially data near the upper and lower developmental thresholds, also influences model fitting.
Fig. 1.
Mean ± SE number of eggs per 5 galleries per log observed every other day in the avocado logs at 4 constant temperatures.
Fig. 2.
Mean ± SE number of larvae per 5 galleries per log observed every other day in the avocado logs at 4 constant temperatures.
Fig. 3.
Mean ± SE number of pupae per 5 galleries per log encountered every other day in the avocado logs at 4 constant temperatures.
Fig. 4.
Mean ± SE number of teneral adults per 5 galleries per log encountered every other day in the avocado logs at 4 constant temperatures.
Future studies are warranted to study temperature-dependent development of larval stages of X. glabratus along with its symbionts at different constant temperatures. Moreover, avocado is not considered the preferred host for X. glabratus, and it is important to determine the development of X. glabratus on other host plants such as P. borbonia and P. pallustris that support denser beetle infestations than avocado. We hypothesize that redbay ambrosia beetle will have more generations per year at lower latitudes compared with higher latitudes. The warm conditions in the southeastern United States and availability of different host trees may be influencing the more rapid range expansion of the redbay ambrosia beetle than predicted by earlier models of Koch & Smith (2008).
Table 6.
Total number of Xyleborus glabratus of each developmental stage observed in dissected avocado (Persea americana) logs held at constant temperatures. Results are based on observations in logs dissected at 2 d intervals for 40 d after gallery initiation.
Acknowledgments
We gratefully acknowledge Stephen McLean (Entomology and Nematology Department, University of Florida) for help in maintaining the redbay ambrosia beetle colony. We also gratefully acknowledge the Hammock Dunes Club Golf Course, Palm Bay (Brevard County) for allowing us to cut infested redbay and swampbay wood. We gratefully acknowledge the assistance of James Colee (IFAS Statistics, University of Florida). This research was supported by a SCRI grant to Dr. R. C. Ploetz (University of Florida, TREC, Homestead, Florida).
