Journal of Thermal Biology 70 (2017) 27–36
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Temperature-dependent models of development and survival of an insect pest of African tropical highlands, the coffee antestia bug Antestiopsis thunbergii (Hemiptera: Pentatomidae)
MARK
Abdelmutalab G.A. Azraga,b, Lucy K. Murungic, Henri E.Z. Tonnangd, Dickson Mwendaa, ⁎ Régis Babina,e,f, a
International Centre of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya Department of Crop Protection, Faculty of Agricultural Sciences, University of Gezira, P.O. Box 20, Wad Medani, Sudan Department of Horticulture, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Nairobi, Kenya d International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, P.O. Box 1041, Nairobi, Kenya e CIRAD, UPR Bioagresseurs, P.O. Box 30677-00100, Nairobi, Kenya f Bioagresseurs, Univ Montpellier, CIRAD, Montpellier, France b c
A R T I C L E I N F O
A B S T R A C T
Keywords: Antestiopsis orbitalis Coffea arabica Life cycle modelling Life table parameters Thermal biology
The antestia bug Antestiopsis thunbergii (Hemiptera: Pentatomidae) is a major pest of Arabica coffee in African tropical highlands. It feeds on coffee plant vegetative parts and berries leading to a direct reduction in coffee yield and quality. This study aimed to determine A. thunbergii thermal requirements, and to obtain new information on the pest demography as influenced by temperature. Temperature-dependent models were developed using the Insect Life Cycle Modelling software (ILCYM) through a complete life table study at seven constant temperatures in the range 18–32 °C. Non-linear functions were fitted to A. thunbergii development, mortality, fecundity and senescence. Model parameters and demographic variables obtained from the models were given for each temperature and development stage. Life table parameters were estimated for nine constant temperatures, from 18 °C to 26 °C, using stochastic simulations. The minimum temperature threshold (Tmin) and the thermal constant (k) for the development from egg to adult were estimated from a linear function at 12.1 °C and 666.67° days, respectively. The maximum temperature threshold (Tmax) was estimated at 33.9 °C from a Logan model. The optimum temperature for immature stages’ survival was estimated to be between 22.4 and 24.7 °C. The maximum fecundity was 147.7 eggs female−1 at 21.2 °C. Simulated A. thunbergii life table parameters were affected by temperature, and the maximum value of intrinsic rate of increase (rm) was 0.029 at 22 °C and 23 °C. In general, the life cycle data, models and demographic parameters we obtained were in line with previous reports for antestia bugs or other stink bug species. The relationships between the pest thermal requirements and ecological preferences in highland coffee were discussed. Our results will contribute to risk prediction under climate change for this important coffee pest.
1. Introduction
bacterium, Pantoea coffeiphila (Enterobacteriaceae), which produces chemical compounds responsible for the distinctive ‘potato taste’ in brewed coffee (Gueule et al., 2015). The ‘potato taste’ defect compromises trust among international buyers of the specialty coffee of African Great Lakes, reducing its competitiveness in foreign markets (Bouyjou et al., 1999; Jackels et al., 2014). Antestiopsis thunbergii (Gmelin) (= A. orbitalis (Westwood)) is the most damaging species to coffee in Eastern and Southern Africa (Greathead, 1966). It thrives in highland coffee plantations (1000–2100 m asl) with a preference for highest elevations, whereas closely related species such as A. facetoides Greathead and A. intricata
Antestia bugs (or variegated coffee bugs), Antestiopsis spp. (Hemiptera: Pentatomidae), are major pests of Arabica coffee, Coffea arabica L. in tropical Africa (Greathead, 1966). Antestia nymphs and adults feed on coffee flower buds, shoots, leaves and green berries leading to direct yield reduction of up to ≈ 45% (Le Pelley, 1968; McNutt, 1979). Feeding lesions on berries are infection gates for Eremothecium fungi (Saccharomycetaceae), which invade the berries leading to bean rotting (Ribeyre and Avelino, 2012). In addition, antestia feeding on berries could contribute to berry infection by a ⁎
Corresponding author at: International Centre of Insect Physiology and Ecology, P.O. Box 30772-00100, Nairobi, Kenya. E-mail address:
[email protected] (R. Babin).
http://dx.doi.org/10.1016/j.jtherbio.2017.10.009 Received 11 June 2017; Received in revised form 14 October 2017; Accepted 22 October 2017 Available online 23 October 2017 0306-4565/ © 2017 Elsevier Ltd. All rights reserved.
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containers with coffee green berries and leaves as diet for transportation to icipe laboratory. Insects were then transferred into aerated Plexiglas cages (20 × 20 × 20 cm) and maintained at 25 ± 0.5 °C with RH of 70–85% and photoperiod 12:12 h L: D. A diet of fresh coffee leaves and green berries was provided every 2–3 days.
(Ghesquière and Carayon) are usually found at lower elevation (Abebe, 1987; Greathead, 1966). In medium-elevation coffee (1300–1500 m asl), A. thunbergii is more common in shaded plantations compared to those grown under full-sun (Mugo et al., 2013). In addition, A. thunbergii is usually more abundant in bushy coffee trees in plantations, where it is easier to find shelter during the hottest hours of the day (Foucart and Brion, 1959; Kirkpatrick, 1937). These specific traits of the pest's ecology suggest a preference for habitats with cool environment. A recent study conducted by our team on A. thunbergii thermal biology gave life table parameters for three temperatures and revealed that the intrinsic rate of increase (rm) was more than double at 20 °C when compared to 25 °C and negative at 30 °C (Ahmed et al., 2016). In this previous study, we also reported some basic information on A. thunbergii life cycle, including immature stages’ development duration, adult longevity, survival, oviposition periods, fecundity and sex ratio. The present study builds from this work for the rearing method or the selection of temperature range for example, but goes beyond by developing temperature-based models and producing thermal requirements from life table data at seven constant temperatures. Insect standard thermal requirements, such as optimum development temperature, minimum and maximum temperature thresholds and thermal constant k (number of degree-days needed for development) are usually estimated through linear regression models (Nielsen et al., 2008; Wagner et al., 1991), combined with non-linear models at extreme temperatures (Quinn, 2017; Sharpe and DeMichele, 1977; Stinner et al., 1974). Other temperature-based models are widely used to describe the temperature dependence of different demographic variables like survival and fecundity (Hilbert and Logan, 1983; Wagner et al., 1991; Worner, 1992). Insect thermal requirements enabled the development of phenology models that are powerful tools for estimating insect life history events, predicting distribution over time and space, and making decision in insect pest management (Khadioli et al., 2014; Nietschke et al., 2007). Temperature-based models have been used to calculate synthetic life table parameters for insect population development, such as intrinsic rate of increase rm (Jaramillo et al., 2009). Recently, they have been used to predict insect pest distribution and abundance under different climate warming scenarios (Fand et al., 2014a, 2014b). These findings strengthen the role these models play in sustainable pest management in the context of climate variability. In the present work, we conducted a complete life table study at seven constant temperatures (18–32 °C) in order to develop temperature-based development models and provide A. thunbergii thermal requirements. In a second step, models were used to assess demographic variables such as development time, mortality and fecundity, as influenced by temperature. Finally, we assessed life table parameters at nine different temperatures (18–26 °C), using stochastic simulations.
2.2. Experimental design for development, mortality and fecundity monitoring The effect of temperature on A. thunbergii development, mortality and fecundity was studied as a complete life table at seven constant temperatures in laboratory incubators (SANYO MIR-553 and MIR-554, Sanyo Electrical Ltd., Tokyo, Japan). Experiments started in August 2014, i.e. one month after insect field collection. In the laboratory colony, A. thunbergii adult female usually laid eggs in batches of 12 attached to coffee berries or leaves provided as diet, or directly on the cage sides (Ahmed et al., 2016). Freshly laid eggs (≤ 24 h-old) of first laboratory generation were carefully collected from theses batches using a flexible forceps and individually introduced in small plastic containers (3.5 cm depth × 3.9 cm in diameter) lined with a paper towel. The containers were aerated by cutting part of the lid and then covering the opening with a fine muslin cloth (0.1 µm). A total of 210, 163, 126, 128, 92, 196 and 250 eggs were monitored daily at constant temperatures of 18, 20, 23, 25, 28, 30 and 32 °C ( ± 0.5 °C), respectively, with RH 80 ± 5% and photoperiod 12:12 h L:D. After emergence, nymphs were fed on fresh coffee green berries and leaves (Ahmed et al., 2016). Berries and leaves were changed every 2–3 days. Individuals were reared from egg to the adult stage in the same conditions and monitored daily to record the development time and mortality. After adult emergence, females were kept in the same containers and paired with males reared at the same temperature. Males and females were maintained together for frequent mating. In case a male died before the female, it was replaced by another male of similar age from the same temperature, or from the main colony if there was no available male from the same temperature. Adult survival and female oviposition were recorded daily. 2.3. Model development 2.3.1. Modelling software Life table data collected at seven constant temperatures were computed to develop temperature-dependent models for different demographic variables of A. thunbergii, using the Insect Life Cycle Modelling software (ILCYM, version 3.0) (Tonnang et al., 2013). This free and user-friendly software aims to assist researchers to develop models for studying insect population ecology. For this purpose, the software includes a model builder that helps users to fit non-linear functions as descriptors of relationships between temperature and development variables. ILCYM was developed with two open source computer programs, Java and R version 2.15.1 (R Development R Core Team, 2012), connected using R-serve, a spatial computer package. In ILCYM, statistical calculation, parameter estimation, data simulation and model graphics are generated using R.
2. Materials and methods 2.1. Collection and maintenance of insects Insects used for this study were collected from a laboratory colony maintained at International Centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya. The colony was initiated with around 100 individuals collected in July 2014 in smallholder Arabica coffee farms, located on the south-eastern slope of Mount Kilimanjaro, near Moshi, Tanzania (area between 3.350°S, 37.462°E and 3.300°S, 37.455°E, with elevation of 1100–1600 m asl). In this area, the mean annual temperature ranges between 18.8 and 21.4 °C and the mean annual rainfall ranges between 1000 and 1300 mm, according to elevation (Mwalusepo et al., 2016). Land cover in this area is dominated by agroforestry systems known as Chagga home gardens, which include small coffee farms associated with shade trees such as avocado, banana and other food crops (Hemp, 2006). The insects collected from these coffee farms were identified as A. thunbergii (Greathead, 1966; Rider, 1998). The collected adult males and females were kept in plastic
2.3.2. Immature stage development time and adult longevity For each constant temperature and development stage, accumulated development/longevity time frequencies were plotted against lntransformed development/longevity times. Then, common binary distribution models for insect development time were fitted to values from experiments (observed data). The best-fitted model was selected through a GLM analysis, based on Akaike's information criterion (AIC) and the coefficient of determination R2. The best fitted models were the logit model for development time of all immature stages, for the total development time from egg to adult and for adult male longevity. The complementary log-log model (CLL) was the best fitted model for adult female longevity. The mathematical expression of the logit and CLL 28
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distribution functions are given by Tonnang et al. (2013):
where f (T ) is the fecundity at temperature T , and b1, b2 and b3 are model parameters. The senescence is defined as a decline in fitness traits due to ageing, but in practice, senescence is usually assessed through simple demographic variables such as longevity and fecundity (Boggs, 2009). ILCYM uses adult senescence rather than mortality to differentiate it from immature stage mortality that occurs instead of reaching the next development stage (Tonnang et al., 2013). In our study, the adult senescence rate was calculated as the inverse of the median longevity obtained from logit and CLL distributions for males and females, respectively (senescence rate = 1/median longevity) and was plotted against temperature. The exponential simple function below was selected as the best model for the senescence rate of both males and females:
Logit distribution: f (x ) = 1/(1 + exp( − (ai + b ln x )))
CLL distribution: f (x ) = 1 − exp ( − exp(ai + b ln x )), where f (x ) is the probability to complete development at time x , ln x is the natural logarithm of the observed development time (in days), ai is the intercept corresponding to temperature i and b is the common slope of the regression model. Immature stage development time and adult male and female longevity were then estimated for each constant temperature using the model distribution median at 95% confidence interval. 2.3.3. Immature stage development rate Development rate was calculated as the inverse median development time (development rate = 1/median development time) (Régnière, 1984), for each immature stage and for the total development from egg to adult, and plotted against temperature. A linear function was fitted to the data to determine the relationship between development rate and temperature (Tonnang et al., 2013). The data points for extreme temperatures (nonlinear points) were excluded. The below equation was used:
s (T ) = b1 exp (b2 T ), where s (T ) is the adult senescence rate and b1 and b2 are model parameters. 2.3.6. Simulation of life table parameters The models established for A. thunbergii demographic variables were compiled and used to compute the life table parameters. Using stochastic simulation tool (Curry et al., 1978) in ILCYM, the life table parameters, i.e. the gross reproductive rate (GRR), which is the average number of daughter nymphs produced by a living female throughout her entire reproductive period, the net reproductive rate (Ro), which additionally takes mother mortality into account, the intrinsic rate of increase (rm), which summarized from all the demographic variables the ability of a population to grow under specific environmental conditions, the mean generation time (T), and the population doubling time (Dt) were estimated. The simulations started with 100 individuals at egg stage and were conducted for nine constant temperatures, from 18 °C to 26 °C with 1 °C interval, and five replicates for each temperature. This sought to establish how the change in temperature by 1 °C can affect A. thunbergii population growth, and to determine the temperature limits of A. thunbergii population growth. The simulated life table parameters were subjected to an analysis of variance (ANOVA) in R (version 3.3.0) (R Development R Core Team, 2016).
r (T ) = a + bT , where r (T ) is the development rate at temperature T , a is the y-intercept of the regression line, b is the slope of the regression line. The lower development temperature threshold (Tmin ) was estimated using: Tmin = −a/ b while the thermal constant k (in degree days) was estimated using k = 1/b . Linear functions cannot correctly capture the development rate at extreme temperatures. Based on R2 and AIC selection criteria, the Logan model (Logan et al., 1976) was selected for all immature development stages. The following equation of the Logan model was used:
r (T ) = Υ ⎧exp(ρT ) − exp(ρTmax − ⎨ ⎩
(Tmax − T ) ⎫ ) , ⎬ v ⎭
where r (T ) is the development rate at temperature T , Υ is a measurable development rate at an arbitrary base temperature above developmental threshold, ρ is a composite Q10 value for enzyme-catalyzed biochemical reactions, Tmax is the maximum lethal temperature and v is the width of the decline phase in development rate above the optimum temperature (Logan et al., 1976). The maximum lethal temperature (Tmax ) and the temperature for the shortest development time were estimated from the Logan models for each immature stage and the total development from egg to adult.
3. Results 3.1. Development time models and estimated values Distribution of A. thunbergii development time was well described by the logit model (Table 1) for all immature stages (R2 = 0.94–0.99, AIC = 153.29–881.39). For adult females, development time distribution fitted well to a CLL model (R2 = 0.87, AIC = 1567.59), whereas for adult males, distribution fitted to a logit model (R2 = 0.88, AIC = 1841.69) (Table 1). Estimated immature stage development time constantly decreased with an increase in temperature, except for the 5th instar, where development time decreased between 18 °C and 25 °C and then increased again at 28 °C and 30 °C (Table 2). At 18 °C, 20 °C and 23 °C, immature stage developmental time was the longest for the 2nd instar when compared to other instars, with 40.63, 24.02 and 15.72 days, respectively. At 32 °C, there was no development beyond the 2nd instar. The longest developmental time from egg to adult was at 18 °C, with 126.31 days while the shortest was at 30 °C, with 53.39 days. Adult longevity was the longest at 20 °C, with 76.98 and 79.21 days for females and males, respectively, and dropped to 35.99 days and 20.99 days at 25 °C, for females and males, respectively.
2.3.4. Immature stage mortality rate Mortality rate was calculated for each A. thunbergii immature stage at each constant temperature. Based on AIC and R2, a second order exponential polynomial function was fitted to describe the effect of temperature on mortality for all immature life stages. The following equation was used (Tonnang et al., 2013):
m (T ) = exp(b1 + b2 T + b3 T 2), where m (T ) is the mortality rate, b1, b2 and b3 are model parameters and T is the rearing temperature. Optimum temperature for survival (= temperature for lowest mortality) was estimated from the models for each immature stage. 2.3.5. Temperature-dependent fecundity and adult senescence The mean fecundity was calculated for each temperature as the mean total oviposition per female. A second order exponential polynomial function was fitted to describe the effect of temperature on fecundity using the expression:
f (T ) = exp(b1 + b2 T + b3
3.2. Immature stage development rate Temperature effect on development rate was well described by combinations of linear regressions and Logan models for all immature stages and from egg to adult (Fig. 1 and Table 3). For linear regressions,
T 2), 29
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Table 1 Parameters (y-intercept a, common slope b) and goodness of fit estimators (R2 and AIC) of models fitted to cumulated frequency distributions of Antestiopsis thunbergii immature stage development time and adult longevity distributions at 7 constant temperatures. Numbers in brackets are standard errors (SE). Model parameters
Intercept (a) at:
Immature stages
Adults
T (°C)
Egg
1st instar
2nd instar
3rd instar
4th instar
5th instar
Male
Female
18 20 23 25 28 30 32
−72.92 (2.89) −63.81 (2.52) −52.45 (2.12) −45.50 (1.83) −36.00 (1.39) −38.15 (1.62) −31.80 (1.33) 30.38 (1.29) 0.99 153.29
−43.75 (1.41) −38.93 (1.26) −32.19 (1.05) −28.45 (0.94) −23.84 (0.84) −19.77 (0.68) −20.59 (0.68) 18.89 (0.61) 0.99 200.74
−36.13 (0.67) −31.01 (0.57) −26.87 (0.50) −23.26 (0.44) −22.30 (0.43) −20.93 (0.40) −20.90 (0.39) 9.75 (0.18) 0.97 727.42
−30.34 (0.67) −25.15 (0.57) −23.04 (0.53) −21.58 (0.49) −22.10 (0.50) −21.03 (0.48) – 9.39 (0.21) 0.94 881.39
−29.77 (0.65) −25.76 (0.57) −24.09 (0.54) −23.37 (0.52) −22.49 (0.52) −22.37 (0.49) – 9.75 (0.21) 0.96 703.92
−23.67 (0.45) −23.03 (0.43) −21.38 (0.41) −21.06 (0.40) −21.89 (0.42) −22.86 (0.42) – 8.00 (0.15) 0.96 861.35
−8.77 (0.18) −9.72 (0.19) −9.43 (0.18) −8.08 (0.16) −8.23 (0.16) −7.42 (0.15) – 2.15 (0.04) 0.88 1841.69
−9.79 (0.23) −10.71 (0.23) −9.61 (0.21) −7.46 (0.17) −8.85 (0.21) −7.47 (0.17) – 2.45 (0.05) 0.87 1567.59
Slope (b) R2 AIC
R2 was high (0.92–0.99) for all immature stages. Fitting to Logan models was good for all immature stages (R2 = 0.88–0.99, AIC between −48.53 and −27.18). The thermal constant (k) increased with age, with 46.7 DD for egg stage, 129.8 DD for 2nd instar, and 322.6 DD for 5th instar. For the total development from egg to adult, k was 666.6 DD. The lower development temperature threshold (Tmin) decreased similarly, whereas the maximum lethal temperature (Tmax) was less variable. Tmin and Tmax for development from egg to adult were estimated at 12.1 °C and 33.9 °C, respectively. The temperature for shortest development time was estimated from the Logan model curve peaks at 32.0, 31.0, 31.5, 29.0, 30.0 and 26.7 °C for egg, 1st, 2nd, 3rd, 4th and 5th instars, respectively (Fig. 1).
Optimum temperature for fecundity estimated from the model was 21.2 °C, with a total oviposition of 147.7 eggs female−1. Estimated fecundity dropped to 48.9 eggs female−1 at 18 °C and 33.6 eggs female−1 at 25 °C. At 30 °C, estimated fecundity was close to 0 (Fig. 3). The impact of temperature on A. thunbergii adult senescence was described by simple exponential functions, but with relatively low R2 values (for males: R2 = 0.54 and AIC = −32.97, and for female: R2 = 0.71 and AIC = −41.88) (Fig. 4 and Table 5). The effect of temperature on adult senescence was significant for females (p = 0.03), but not for males (p = 0.09) (Table 5). 3.5. Life table parameters A. thunbergii life table parameters were significantly affected by temperature (p < 0.0001) (Table 6). rm was maximal at 22 and 23 °C, with 0.029 and negative at 18 °C. GRR was maximal at 21 °C, with 100.7 daughters female−1. Ro was maximal at 22 °C with 20.2 daughters female−1 generation−1, compared to 18.3 and 16.5 at 21 °C and 23 °C, respectively. T decreased significantly with increasing temperature, with 172.2 and 81.0 days at 18 °C and 26 °C, respectively. Dt was minimal at 22 °C, with 24.05 days, and maximal at 19 °C, with 63.41 days.
3.3. Immature stage mortality rate Temperature significantly affected survival of A. thunbergii immature stages (p ≤ 0.05) (Table 4). For all stages, the best fitted model was a second-order polynomial function (R2 = 0.75–0.99 and AIC between −27.20 and −5.61) (Fig. 2 and Table 4). The 2nd instar showed the highest mortality rate for all temperatures with 93.9%, 68.5%, 27.3%, 27.5%, 59.1%, 63.2% and 90.1% at 18, 20, 23, 25, 28, 30 and 32 °C, respectively (Fig. 2). Temperatures for lowest mortality estimated from the models were 22.4, 24.7, 24.7 23.7, 24.3 and 24.3 °C for egg, 1st, 2nd, 3rd, 4th and 5th instars, respectively. At these temperatures, estimated mortality rates were 10%, 5%, 43.2%, 11.8%, 0.7% and 5.0% for the egg, 1st, 2nd, 3rd, 4th and 5th instar, respectively (Fig. 2).
4. Discussion 4.1. Modelling impact of temperature on demographic variables Temperature is considered the most important environmental factor that affects insect development, reproduction, mortality and behavior (Frizzi et al., 2017; Hance et al., 2007; Inward et al., 2012; Joshi, 1996). Our study showed that temperature influenced A. thunbergii demographic variables and is therefore in agreement with this statement. Linear functions fitted well to the effect of temperature on the development rate for all A. thunbergii immature stages, especially for temperature between 18 and 25 °C. For higher temperatures, the Logan
3.4. Female fecundity and adult senescence Temperature impact on A. thunbergii fecundity was well described by a second order polynomial function (Fig. 3 and Table 5). Model fitting was good for fecundity with R2 value of 0.96 and AIC of 51.60. Temperature significantly affected A. thunbergii fecundity (p < 0.05).
Table 2 Estimated immature stage development time and adult longevity (in days) obtained from logit and complementary log-log distributions models (distribution median) for Antestiopsis thunbergii reared at 7 constant temperatures. Numbers in brackets are standard errors (SE). Temp. (°C)
18 20 23 25 28 30 32
Immature stage development time (days)
Adult longevity (days)
Egg
1st instar
2nd instar
3rd instar
4th instar
5th instar
Egg to adult
Female
Male
11.03 (0.07) 8.17 (0.06) 5.62 (0.04) 4.47 (0.03) 3.27 (0.02) 3.51 (0.01) 2.85 (0.04)
10.13 (0.09) 7.85 (0.08) 5.49 (0.06) 4.51 (0.05) 3.53 (0.04) 2.85 (0.05) 2.97 (0.05)
40.63 (0.66) 24.02 (0.37) 15.72 (0.25) 10.86 (0.18) 9.84 (0.17) 8.55 (0.14) 8.52 (0.16)
25.24 (0.62) 14.52 (0.23) 11.61 (0.20) 9.94 (0.18) 10.50 (0.22) 9.37 (0.20) –
21.16 (0.18) 14.02 (0.23) 11.82 (0.21) 10.98 (0.19) 10.04 (0.17) 9.91 (0.17) –
19.26 17.78 14.47 13.90 15.43 17.41 –
126.31 (0.35) 86.12 (0.65) 64.93 (0.40) 56.53 (0.36) 54.10 (0.34) 53.39 (0.34) –
49.58 76.98 67.25 35.99 38.56 26.53 –
54.49 79.21 50.45 20.99 37.04 21.06 –
30
(0.24) (0.38) (0.28) (0.31) (0.33) (0.29)
(0.81) (3.28) (2.75) (1.95) (1.66) (0.93)
(0.01) (3.25) (2.91) (1.66) (1.44) (1.63)
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Fig. 1. Temperature-dependent developmental rate of Antestiopsis thunbergii. A) egg; B) 1st instar; C) 2nd instar; D) 3rd instar; E) 4th instar; F) 5th instar. Observed values are the points, with bars representing standard deviation of the mean. Fitted models are the straight line for linear regression and solid curved line for the Logan model. Dashed lines above and below represent the upper and lower 95% confidence bands.
31
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Table 3 Model parameters of linear regressions and Logan functions for temperature effect on Antestiopsis thunbergii immature stage development rate (1/day), with linear regression models, a: yintercept, b: slope, k: thermal constant (DD), Tmin: lower development temperature threshold, and for Logan models, Υ , ρ and v: model parameters and Tmax: maximum lethal temperature. Life stage
Egg 1st instar 2nd instar 3rd instar 4th instar 5th instar Egg to adult
Linear regression model
Logan model
a
b
R2
k (DD)
Tmin (°C)
Tmax (°C)
Υ
ρ
v
R2
AIC
−0.3030 −0.2819 −0.1126 −0.1018 −0.0546 −0.0036 −0.0181
0.0214 0.0205 0.0077 0.0082 0.0060 0.0031 0.0015
0.99 0.98 0.97 0.96 0.92 0.97 0.99
46.73 48.78 129.87 121.95 166.67 322.58 666.67
14.15 13.75 14.62 12.47 9.10 1.16 12.07
38.06 32.92 35.60 34.35 35.10 33.59 33.91
0.016 0.018 0.003 0.012 0.014 0.021 0.001
0.164 0.100 0.197 0.160 0.141 0.121 0.164
5.445 0.578 4.648 5.637 6.167 7.185 5.228
0.96 0.99 0.97 0.88 0.95 0.94 0.97
−27.19 −43.31 −42.66 −31.16 −38.42 −48.53 −60.23
respectively. First instar development time also is similar in Le Pelley's study, with 10–13 days at 17–18 °C and 7–9 days at 19–20 °C. By contrast, development time of 2nd instar we obtained at 18 °C (40.6 days) was much longer than the one reported by Le Pelley (18–28 days). In our study, this remarkably long development time for 2nd instar, when compared to 1st and 3rd instars, especially at 18, 20, and 23 °C, suggests that temperature might not be the only factor affecting A. thunbergii nymphal development. A. thunbergii female usually lays eggs in batches of 12 eggs. After hatching, 1st instars stay in groups on egg chorions for a few days and feed very little, or not at all (Kirkpatrick, 1937). In contrast, the 2nd instars spread over their close environment in search for food and feed actively. This behavior of 1st instar is common in stink bugs and allows the vertical transmission through egg chorions of gut symbionts from the mother to offspring (Hosokawa et al., 2013). In the current study, for the purpose of life table analysis, eggs were collected from batches and maintained in containers individually. The manipulation of eggs might have affected the vertical transmission of gut symbionts to 1st instars. The presence of bacterial gut symbionts has been demonstrated in A. thunbergii (Matsuura et al., 2014), and a lack of these symbionts has shown a tendency to slow down the nymphal development and to increase mortality in other stink bugs (Prado et al., 2009; Kikuchi et al., 2016). This limitation in our rearing method should be considered carefully in further studies. It is to be noted that this long development time in 2nd instars was true for the lowest temperatures (18 and 20 °C) and tended to decrease with increasing temperature. This suggests that an increase in temperature leads to a quicker adaptation to food. Further studies are needed to better understand the role temperature plays in feeding of antestia bugs, especially in the relationships between the bug and its gut symbionts. For third, fourth and fifth instars our results are consistent with ranges given by Le Pelley (1968), as well as for the total development time from egg to adult, which falls into Le Pelley's ranges of 54–108 days and 74–116 days for temperature of 17–18 °C and 19–20 °C, respectively. In a study from Kirkpatrick (1937) in Tanzania, A. thunbergii adult lifespan ranged between 121 and 131 days for females and 98 and 106 days for males under fluctuating temperatures, which is longer that the
model gave good results and allowed the calculation of the maximum temperature threshold. The Logan model has been widely used for insects of different groups and geographical origins (Andreadis et al., 2013; Arbab and Mcneill, 2011; Grout and Stoltz, 2007; Quinn, 2017; Son et al., 2010). For example, the Logan model was used to predict the impact of temperature on the development rate of the coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Scolytinae) (Jaramillo et al., 2009). In our study, impact of temperature on A. thunbergii mortality and fecundity was well described by second-order polynomial functions. Similar models were used for two devastating moths, the potato tuberworm, Phthorimaea operculella Zeller (Lepidoptera: Gelechiidae) and the maize stem borer, Chilo partellus Swinhoe (Lepidoptera: Crambidae) (Khadioli et al., 2014; Sporleder et al., 2004). 4.2. Development time, adult lifespan and female fecundity Some reports on A. thunbergii demographic variables are available in the literature. Our team recently published basic data on development time, adult lifespan, survival and fecundity, in the same rearing conditions, but at 3 constant temperatures, 20, 25 and 30 °C (Ahmed et al., 2016). The values we obtained from the models in the current study are consistent with those of this previous study. For example, complete development, from egg to adult, was 89.6, 63.1 and 55.8 days, at 20, 25 and 30 °C in the previous study. The values we obtained from the models for the same temperatures were similar, with 86.1, 56.5 and 53.39 days. In addition, our previous study reported a mean fecundity of 132.7 eggs female−1 at 20 °C, which dropped at 27.9 eggs female−1 at 25 °C, and 4.5 eggs female−1 at 30 °C. From our models, fecundity was maximal at 21.3 °C, with 147.7 eggs females−1, dropped to 33.6 eggs female−1 at 25 °C and was close to 0 at 30 °C. These comparisons seem to validate the models we developed in the present study, which is not surprising since we used the same rearing method (Ahmed et al., 2016). Unfortunately, aside from this work, most studies on A. thunbergii described life cycle under room fluctuating temperatures, which makes comparison uneasy. Nevertheless, our results for egg development are in line with those of Le Pelley (1968), who reported an incubation period of 6 and 15 days, at mean temperature of 22.5 and 16.9 °C,
Table 4 Model parameters of polynomial function for temperature effect on Antestiopsis thunbergii immature stage mortality rate, with b1, b2 and b3: model parameters (SE in brackets), F: F-test statistic, d.f.: degree of freedom, p: probability value. Life stage
Egg 1st instar 2nd instar 3rd instar 4th instar 5th instar
Model parameters
Statistics
b1
b2
3.726 (0.003) 9.853 (0.002) 10.788 (0.001) 15.887 (0.001) 39.364 (0.002) 29.381 (0.002)
−0.538 −1.039 −0.940 −1.519 −3.644 −2.669
b3 (0.036) (0.019) (0.014) (0.008) (0.019) (0.025)
0.012 0.021 0.019 0.032 0.075 0.055
(0.001) (0.001) (0.001) (0.000) (0.001) (0.001)
32
F
d.f.
p
R2
AIC
6.16 21.13 12.52 447.09 523.11 47.22
2,4 2,4 2,4 2,4 2,4 2,4
0.050 0.007 0.019 < 0.001 < 0.001 0.001
0.75 0.91 0.86 0.99 0.99 0.95
−16.559 −24.372 −5.618 −27.201 −26.749 −11.069
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Fig. 2. Temperature-dependent mortality rate of Antestiopsis thunbergii fitted to second order polynomial functions: A) egg; B) 1st instar; C) 2nd instar; D) 3rd instar; E) 4th instar; F) 5th instar. The points are observed values and the solid curves are the selected models (polynomial functions) output. Dashed lines above and below represent the upper and lower 95% confidence bands of the model.
development from egg to adult gave a larger thermal window of 12.1–33.9 °C. We obtained the shortest development time from egg to adult for a temperature of 30 °C, but under this temperature, immature stage mortality was very high. Optimum temperature for immature stage survival was between 22.4 and 24.7 °C, depending on the development stage. This temperature range may be considered as optimum for the development of A. thunbergii from egg to adult. The Tmin we obtained for 5th instar was abnormally low and should be considered with caution, as well as the related thermal constant (k), which was twice higher than this of the previous instar. In fact, the impact of temperature on the 5th instar was not clear in our study, when compared with early immature stages. One explanation could be adaption
maximum lifespan we obtained at 20 °C. On the other hand, our estimation of maximum fecundity is in line with reports at room temperature from Kirkpatrick (1937), with a mean of 148 eggs female−1, and Le Pelley (1968), with a mean of 142 eggs female−1. 4.3. Thermal requirements In our study, A. thunbergii was able to complete life cycle at all tested constant temperatures except 32 °C. Temperature thresholds obtained from the models for each immature stage suggest that A. thunbergii may not be able to develop below 14.6 °C (Tmin for second instar) and above 32.9 °C (Tmax for first instar). However, model developed for the whole 33
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was estimated at 0.01 at 20 °C, 0.02 at 25 °C and −0.01 at 30 °C (Prado et al., 2009), while it was 0.07 at 25 °C for the invasive brown marmorated stink bug, Halyomorpha halys (Stål) (Nielsen et al., 2008). For the predatory stink bug Podisus nigrispinus (Dallas), rm was estimated at 0.039, 0.059 and 0.081, at 20, 23 and 25 °C, respectively (Medeiros et al., 2003). Different rearing conditions, especially diet, make it difficult to compare these results with ours. More interesting is the comparison with field A. thunbergii population assessments conducted in South Africa for the same species (referred to as A. orbitalis in the study) (van der Meulen and Schoeman, 1990). By studying conjointly A. thunbergii seasonal variations and weather conditions, the authors reported that the highest nymph abundance was observed for mean temperature between 19 and 24 °C. Authors also estimated that an annual temperature range of 9.8–28.4 °C was not lethal for the pest, and that field populations had about 4 generations per year in the study site. However, authors tempered these findings by suggesting that the availability of green berries on coffee, which were more frequent on trees in cold and rainy seasons, might play an important role in pest population dynamics (van der Meulen and Schoeman, 1990). Fig. 3. Temperature-dependent fecundity of Antestiopsis thunbergii (total oviposition per female). Black dots are observed data points at tested constant temperatures. Black curve is the fitted second-order polynomial function, with the upper and lower 95% confidence interval indicated with dashed lines.
4.5. Relationships between thermal requirements and ecological traits As already mentioned above, A. thunbergii displays ecological traits (preference for plantations at high elevation, for shaded plantations at low elevation and for bushy coffee trees), which may suggest a preference for cool environment. This may distinguish the pest from other tropical species of stink bugs. An important component of the thermal requirement that may allow comparison between species is the thermal window (Dixon et al., 2009), which is the difference between maximum and minimum temperature thresholds. By compiling thermal requirements of 66 insect species originated in different geographical areas, Dixon et al. (2009) showed that thermal window was affected by phylogenetic characteristics of the species but not by their ecological traits. However, the authors also showed that thermal window was globally narrower for tropical species when compared to species originated in subtropical and temperate areas. In the current study, we estimated a thermal window at 21.8 °C (12.1–33.9 °C) for A. thunbergii, which is wider by to 2 °C than the mean obtained by Dixon et al. (2009), with 19.8 °C. Reports of thermal requirements of other phytophagous pentatomids are scarce in literature, especially for tropical species, and totally inexistent for other antestia bugs. H. halys is native to temperate Asia and showed temperature thresholds of 14.2 and 35.8 °C, that correspond to a similar thermal window at 21.6 °C (Nielsen et al., 2008). The predatory stink bug Podisus maculiventris (Say) is distributed in North America and showed temperature thresholds of 12.7 and 35.2 °C, that results in a thermal window at 22.5 °C (Baek et al., 2014). Unfortunately, current knowledge on the thermobiology of the two closely related antestia species, A. intricata and A. facetoides, is not sufficient to allow comparison. These two species have similar life history traits and can even be found living together with A. thunbergii in coffee plantations. However, they prefer low elevation Arabica coffee plantations, which may suggest different thermal requirements. Further studies are therefore needed to better understand the relationships between temperature and ecology of antestia bugs.
to temperature during individual development or, more probably, the impact of other factors, like food, that may be amplified for 5th instar. These findings merit further studies to better understand the role that the food may play in A. thunbergii physiology. 4.4. Life table parameters Simulated fecundity-based parameters, i.e. gross reproductive rate and net reproductive rate were maximal for 21 °C and 22 °C, respectively. The simulated intrinsic rate of increase was maximal for 22 °C and 23 °C. Our results also showed that an A. thunbergii population maintained under constant temperature could not grow at temperature below 19 °C and above 25 °C. At 18 °C, the negative rm value was mainly due to very high mortality of nymphs, especially second instars. In contrast, at 26 °C, the null rm value was mainly due to a drop in fecundity as suggested by the low GRR, which was six times lower than that at 25 °C. In addition, for temperature range 19–25 °C, simulated generation time ranged between 141 and 83 days, which correspond to 2.6– 4.4 generations per year. For optimum temperature range (22–23 °C), A. thunbergii population had 3.6 generations per year. In the previous paper on A. thunbergii, our team reported rm values of 0.013, 0.006 and −0.027 at 20, 25 and 30 °C, respectively (Ahmed et al., 2016). Our simulated rm values were similar at 20 °C but higher at 25 °C, with 0.021. The drop in simulated rm values between 25 °C and 26 °C suggests that 25 °C is a threshold temperature, where small variation in temperature may induce significant change in rm. This may explain the difference between values from observations and simulations. Other studies on different stink bug species reported slightly different rm: for the southern green stink bug, Nezara viridula (L.), rm
Table 5 Model parameters of the second-order polynomial function for temperature effect on Antestiopsis thunbergii female fecundity (total oviposition per female) and the exponential simple function for temperature effect on adult senescence rates (1/day). b1, b2 and b3 are model parameters, with SE in brackets, F: F-test statistic, d.f.: degree of freedom, p: probability value. Demographic parameters
Fecundity Female senescence Male senescence
Model parameters
Statistics
b1
b2
b3
F
d.f.
p
R2
AIC
−42.387 (0.003) 0.004 (0.003) 0.004 (0.004)
4.461 (0.037) 0.077 (0.025) 0.084 (0.043)
−0.105 (0.002) – –
45.26 10.04 4.72
2,3 1,4 1,4
0.005 0.033 0.090
0.96 0.71 0.54
51.60 −41.89 −32.97
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Fig. 4. Temperature-dependent senescence rates (1/day) for adults of Antestiopsis thunbergii: A) females; B) males. Curves show fitted exponential simple functions with the upper and lower 95% confidence interval of the model indicated with dashed lines. Bars represent standard deviation of the mean.
Acknowledgements
Table 6 Simulated life table parameters of Antestiopsis thunbergii at different constant temperatures (initial egg number (n) = 100), with rm: intrinsic rate of increase, GRR: gross reproduction rate, Ro: net reproduction rate, T: mean generation time, Dt: doubling time, F: F-test statistic, d.f.: degree of freedom, p: probability value. Temperature (°C)
18 19 20 21 22 23 24 25 26 F d.f. p
The authors gratefully acknowledge the financial support provided by the CHIESA project (Climate Change Impacts on Ecosystem Services and Food Security in Eastern Africa) funded by the Ministry of Foreign Affairs of Finland. The authors thank the coffee team in the “Coffee Pest” laboratory at icipe for the support provided during this study.
Life table parameters rm
GRR
Ro
T (days)
Dt (days)
−0.005 0.009 0.016 0.025 0.029 0.029 0.024 0.021 0.000 73.08 8,33 < 0.0001
29.75 50.95 65.99 100.70 90.60 76.67 38.25 23.48 3.86 46.02 8,33 < 0.0001
0.50 4.94 8.16 18.29 20.21 16.54 8.59 5.83 1.02 38.38 8,33 < 0.0001
172.20 140.70 126.20 114.40 103.80 97.56 90.34 83.48 81.00 522.00 8,33 < 0.0001
– 63.41 42.64 27.54 24.05 24.19 29.56 34.84 – 13.24 6,27 < 0.0001
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