Temperature Preference and Respiration of Acaridid Mites

STORED-PRODUCT

Temperature Preference and Respiration of Acaridid Mites J. HUBERT,1,2 S. PEKA´R,3 M. NESVORNA´,1

AND

V. SˇUSTR4

J. Econ. Entomol. 103(6): 2249Ð2257 (2010); DOI: 10.1603/EC10237

ABSTRACT The thermal preferences in a grain mass and respiration at various temperatures in mites (Acari: Acarididae) of medical and economical importance [Acarus siro (L. 1758), Dermatophagoides farinae Hughes 1961, Lepidoglyphus destructor (Schrank 1871), and Tyrophagus putrescentiae (Schrank 1781)] were studied under laboratory conditions. Based on the distribution of mites in wheat, Triticum aestivum L., grain along a thermal gradient from 10 to 40⬚C, L. destructor, D. farinae, and A. siro were classiÞed as eurythermic and T. putrescentiae as stenothermic. The lowest preferred temperature was found for D. farinae (28⬚C), followed by A. siro (28.5⬚C), L. destructor (29.5⬚C), and T. putrescentiae (31.5⬚C). The relationship between the respiration rate and the temperature was similar for all four mite species. The highest respiration was found in the range from 31 to 33⬚C. This is ⬇2⬚C higher than the preferred temperature of these species. The lower temperature threshold of respiration ranged from 1 to 5⬚C and the upper threshold ranged from 45 to 48⬚C. Acclimatization of A. siro to temperature regimes of 5, 15, and 35⬚C resulted in thermal preferences between 9 and 12⬚C, 9 and 20⬚C, and 28 and 35⬚C, respectively. The respiration rate of acclimatized specimens increased with the temperature, reaching a maximum at 29.0⬚C for mites acclimatized at 5 and 15⬚C and a maximum at 33.7⬚C for those acclimatized at 30⬚C. KEY WORDS mites, temperature, acclimation, respiration, grain

Because synanthropic mites are poikilothermic, their metabolic activity, including development, is strongly inßuenced by ambient temperature (Fields 1992). Through its effects on development and metabolism, the environmental temperature inßuences risks associated with pests, such as allergen production (vanBronswijk and Sinha 1971, Wharton 1976, Spieksma 1990, Arlian 2002), quality changes of stored food (Thind and Clarke 2001), and transmission of microorganisms (Franzolin et al. 1999, Hubert et al. 2004). Recently, we simulated the population dynamic in a grain store to estimate the risk of contamination by mites when exposed to natural temperatures during the storage period (Peka´r and Hubert 2008). In central Europe, the monthly mean temperature of stored grain generally decreased from 18⬚C in September through 10⬚C in November to 3⬚C during December to March and then increased to 8 Ð12⬚C in April and May (Aspaly et al. 2007). Thus, our model indicated that the risky period for the grain storage in terms of pest population increase is limited to ⬍3.5 mo, which represents only ⬇40% of the typical storage season in central Europe (Aspaly et al. 2007).

1 Department of Stored Product Pest and Food Safety, Crop Research Institute, Drnovska´ 507, Praha 6 Ruzyneˇ CZ 161 06. 2 Corresponding author, e-mail: [email protected]. 3 Department of Botany and Zoology, Faculty of Sciences, Masaryk University, Kotla´rˇ ska´ 2, 611 37 Brno, Czech Republic. 4 Biology Centre AS CR, Institute of Soil Biology, Na Sa ´dka´ch 7, Cˇ eske´ Budeˇ jovice, CZ 370 05.

This estimation did not take into account heterogeneity of temperature in the grain mass, the migration ability, and thermal acclimation of mites. The temperature in the grain mass is inßuenced by the ambient temperature, grain mass, type of stores, and position within the mass (Athanassiou et al. 2001). In addition, local temperature is inßuenced by hot spot formations (Sinha 1961, Sinha and Wallace 1966). The hot spots are induced by the interaction of microorganisms and arthropods and occur when the grain seems to spontaneously heat to temperatures as high as 60⬚C (Cook and Armitage 2003). Because previous research was conducted largely on short-term studies of mites reared usually at optimal conditions, it is not known whether and how mites respond to the prevailing low temperature in the stored grain. Very little is known about thermal preferences of synanthropic mites. Dermatophagoides specimens have been observed to migrate out of the top of a mattress when it is overheated, and the distribution of mites in this situation showed a temperature-dependent response (de-Boer 1996). It is expected that mites can migrate within the grain to spots with optimal physical conditions (e.g., temperature and humidity) or can potentially adapt to suboptimal temperatures. During the thermal acclimation, mites adapt to ambient temperatures (Davis and Boczek 1988). Sinha (1964) found that a population of A. siro reared at 6⬚C survived for longer at ⫺18⬚C than specimens reared at 21⬚C. These results indicate that acclimation inßu-

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Fig. 1. Schema of the thermal gradient. (A) Longitudinal section of the aluminum block (12) with temperature bridge. 1, temperature bride; 2 and 3, sensors PT 100 of the cooled and heated part, respectively; 4, Peltier⬘s modules; 5, digital temperature sensor; 6, heating; 7, ventilator; and 8, cooler. (B) Cross section of gradient: 9, polyurethane rigid foam-isolation; 10, chamber for experiments; 11, stainless steel plate; 12, aluminum block; 13, padding; 14, acrylate cover plate for chamber; and 15, the cover of the gradient.

ences mite metabolism and increases the potential for damage of stored grain (cf. Aspaly et al. 2007). During long unfavorable periods, from late autumn to early spring, mites could acclimate to low temperature and not only survive but also reproduce. Here, we investigated how experimental temperature inßuences mite distribution and migration in the grain (i.e., thermal preference), how temperature affects the metabolism of mites (estimated from respiration activity), and how these characteristics change when mites are acclimated to different temperatures. We compared mite respiration rates and thermal preferences in four pest species of mites of medical and economic importance: Acarus siro (L. 1758) (Acaridae), Dermatophagoides farinae Hughes 1961 (Pyroglyphidae), Lepidoglyphus destructor (Schrank 1871) (Glycyphagidae), and Tyrophagus putrescentiae (Schrank 1781) (Acaridae). Thermal preferences were observed using an artiÞcial temperature gradient, whereas the rate of metabolism was measured indirectly by recording CO2 production. Once the thermal preferences and metabolic response to the change of temperature were determined, we focused on the effect of temperature acclimation on the preference and metabolic activity of A. siro. Materials and Methods Mites. Four species of stored-product and house dust mites of medical and economic importance (Hughes 1976) were selected for this study: A. siro, T. putrescentiae, D. farinae; and L. destructor. The individuals used originated from laboratory stock cultures kept in the Crop Research Institute in Prague, Czech Republic. The mites were mass-reared on a wheat, Triticum aestivum L., and Þsh food-derived diet under controlled conditions (Erban and Hubert 2008). Mites

were collected using a camelÕs-hair brush from the surface of rearing chambers. Mites were not sexed, and the mixtures of all mobile stadia were used in all experiments. Thermal Acclimation of A. siro. Part of the A. siro culture that was kept at 25 ⫾ 0.5⬚C was divided into four separate chambers placed into thermostats with controlled temperatures 5 ⫾ 0.5; 15 ⫾ 0.5, and 30 ⫾ 0.5⬚C for 1 mo. The mites maintained at 25⬚C were used as a control. Temperature Gradient Funnel. The temperature gradient funnel (Fig. 1) consisted of an 80- by 800-mm chamber submerged (10 mm) into an aluminum block (1,200 by 250 by 300 mm). The bottom of the chamber was a stainless steel plate (thickness, 5 mm). The chamber was covered by an acrylate lid (10 by 900 mm) that was packed using rubber and silicon petroleum jelly. The temperature gradient was provided by Peltier Modules (catalog no. M-TEC1-24120, GM Elektronik, Prague, Czech Republic) cooling one side of the gradient and heating the opposite side. Both sides were controlled by TRIAC switches that checked the temperature. The funnel provided a gradient from 6 to 40⬚C. The chamber was divided into 10 sectors (80 by 80 mm), and every sector was controlled by a digital temperature sensor (catalog no. F-KV-VM145, GM Elektronik). Setup of Temperature Gradient Funnel. Before experiments, the wheat grain (mixture of cultivars) was cleaned (according to Krizkova-Kudlikova et al. 2007) and remoistened to 15% moisture content (m.c.) by using an Agricomputer MK2 (⫺0.4% accuracy; Opting servis, s.r.o., Ostrava, Czech Republic). The grain (400 g) was placed into a plastic container, and mites were added onto the surface of the grain. The sample was preincubated at 25⬚C for 2 h. During this time, the mites migrated into the grain. The grain was homog-

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Fig. 2. Schema of respirometric device. 1, compressed calibration gas (CO2); 2, compressed gas (N2/O2; 80/20%); 3, container for calibration gas; 4, container for experimental gas; 5, three-way stopcock; 6, air pump; 7, washing chamber; 8, bridge through washing chamber; 9, respiration manifold; 10, gas dryer; 11, bridge trough gas dryer; 12, ßow meter; 13, IRGA-CO2 sensor; and 14, washing chamber with silicon oil.

enously spread over a chamber of the gradient apparatus. The gradient was separated into the 10 sectors (80 by 80 mm) from the right to the left side of the chamber. The temperature intervals corresponding to 10 individual sectors were as follows (rightÐleft sensor): 1) 7.2 ⫺10.6⬚C, 2) 10.6 Ð13.8⬚C, 3) 13.8 Ð17.4⬚C, 4) 17.4 Ð21.2⬚C, 5) 21.2Ð24.8⬚C, 6) 24.8 Ð27.7⬚C, 7) 27.7Ð 31.1⬚C, 8) 31.1Ð34.1⬚C, 9) 34.1Ð38.5⬚C, and 10) 38.5Ð 42.6⬚C. The mean temperatures of each sector were used for the sector marking. The mites and grain were incubated in the funnel for 24 h. After this period, the temperature on the sensors was recorded. The grain together with the mites was collected from each sector separately using an acrylic scoop and a camelÕs-hair brush. The mites were extracted from the grain samples by shaking onto a 2-mm mesh in a sieve shaker AS 200 digit (Retsch, DeHaan, Germany) and counted under a Stemi 2000C dissection microscope (Carl Zeiss, Jena, Germany). Six replicates per experimental group (species or acclimation temperature) were done. The total numbers of mites (N) in separate replicates were as follows: A. siro (1,183; 821; 1,003; 1,001; 725; and 957); D. farinae (1,357; 1,107; 856; 1,330; 1,149; and 1,991); L. destructor (3,615; 2,693; 1,233; 297; 636; and 813); T. putrescentiae (312; 887; 1,617; 1,556; 572; and 1,239). For acclimated A. siro groups, the numbers in each temperature group were as follows: 5⬚C (911, 555, 534, 627, 462, and 740); 15⬚C (889; 1,062; 1,199; 1,097; 975; and 833); and 30⬚C (324, 595, 865, 583, 200, and 811). Moisture was controlled (Agricomputer MK2) in the sectors, and the differences were lower than 1% m.c., which is 2 times higher than the accuracy of moisture measurement. Therefore, we suggest that the moisture content of the grain was basically constant

during incubation on the gradient funnel. Grain is not a natural habitat for D. farinae, which mainly inhabits house dust. We compared its distribution in zeoliteBiokatÕs Sepiolote (Gimborn, Barco di Bibbiano, Italy) and barley, Hordeum vulgare L., in preliminary experiments (J.H., unpublished). We did not Þnd any differences in their distribution between zeolite and grain. Respiration Apparatus. A modiÞcation of an open system infrared gas analyzer IRGA and respiration apparatus (catalog no. RP1LP, Qubit Systems, Kingston, ON, Canada) was used to study mite respiration (Fig. 2). The apparatus consisted of bottles with compressed gas: calibration gas (500 ppm CO2 in N2; Linde-Technoplyn s.r.o., Praha, Czech Republic) and compressed synthetic air (N2 80% and 20% O2; catalog no. GA231, Linde-Technoplyn s.r.o.). For apparatus calibration or experiments, the gas (Qubit Systems) containers were Þlled from the bottles. The containers were closed by a 3-way stopcock (catalog no. S7521, Sigma-Aldrich, St. Louis, MO). The gas was pumped by a gas pump (Qubit Systems) from the containers into the washing chamber (catalog no. 632 442 285 110, Vitrum, Praha, Czech Republic) and then continued to the respiration manifold. The respiration manifold consisted of six connected 3-way stopcocks (catalog no. S7521, Sigma-Aldrich), and the posterior and anterior part of the manifold was connected to the gas ßow in the apparatus. Six 1-ml syringes (catalog no. 9166017V, B. Braun, Melsungen, Germany) were added into the manifold. Gas from the manifold was dried in a DMTM-060-24-Series Gas Dryer 3 with DM-AR dryers (Perma Pure, Toms River NY). A ßowmeter (catalog no. 112-02-A, Aalborg, Orangeburg, NY) regulated the gas ßow to the IRGA. There was a permanent ßow of dried and synthetic gas in the ap-

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paratus created by a throttle-valve at a rate of 0.1 liter of gas per 60 s. The IRGA was protected by an Acrodisk Minispike syringe PTEE Þlter (catalog no. Z260398, Sigma-Aldrich). The analyzer was based on a Gascaerd II infrared card (Edinburgh Sensors, Scotland, United Kingdom). The output of the analyzers was connected to a two-way 50-ml washing chamber where the gas was passed through silicon oil to prevent back ßow of gas into the IRGA. The IRGA was connected to a computer using a LabPro Interface (catalog no. C410, Qubit Systems). IRGA-CO2 mediated concentrations were loaded into the connected computer using Logger Pro software (Vernier Software & Technology, Beaverton, OR). Calibration of Respiration Apparatus. The sensor was calibrated using CO2 and synthetic air every time it was used. For calibration, the washing chamber and gas dryer were overcome by bridges. The peak of CO2 was never higher than 500 ppm, enabling the use of a sensor range of 0 Ð500 ppm. Respiration Setup. Before the experiments, a group of mites was weighed on a Mettler AE 240 microbalance (Mettler-Toledo, Columbus, OH), with the accuracy of 10 ␮g. The fresh weight of one sample was usually between 1.5 and 1.8 mg. The mites were transferred into the syringe in the respiration manifold. The aperture of the syringe was Þlled with a piece of Þlter paper to prevent movement of mites into the apparatus. Four syringes with mite samples and two controls without the mites were used for measurement. All manifolds were preincubated for 2 h in the ES-500 thermostat (Trigon-Plus, Cˇ estlice, Czech Republic) at the appropriate temperature (5, 10, 15, 20, 25, 30, 35, 40, and 45 ⫾ 0.1⬚C). After preincubation, the manifold was connected to the apparatus, and the air in the syringe was replaced by moistened synthetic gas. This process took ⬍10 min. The volume of the gas was 0.6 ml, from which the volume 0.5 ml was applied. Then, the manifold was replaced into the thermostat and incubated for 2 h. After incubation, the respiration manifold was connected to the respiration apparatus, and CO2 content was measured immediately. For this measurement, the ßow of synthetic air was used without moistening, and the moisture chamber was overcome by bridge. At 300-s intervals, the 0.5 ml of the gas from the incubated syringe in the manifold was injected into the apparatus. Logger Pro software recorded the concentration of CO2 for 240 s. The concentration was checked 180 times per s, and 16,201 concentration observations were collected. We found that 240 s was sufÞcient time to record the whole peak of injected CO2, and after this period, the CO2 concentration in the apparatus was near zero level. We observed the CO2 from the control syringes without any mites in the same way. The total volume of CO2 in the 0.5 ml of injected air was calculated by comparing the total sums of the IRGAÐCO2 signals (integrals of the concentration through time) minus the average of sums of signals from the control syringes. The CO2 produced by mites during two hours of incubation was recalculated to ppm of CO2 per g of fresh weight of mites for 1 h.

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Data Analysis. The response of mite density to the temperature gradient was studied using Generalized Additive Models (GAM) because the response was strongly nonlinear, and a good Þt could not be obtained by using any temperature-dependent model. The response was the number of specimens. Therefore, binomial family and logit link were used (Wood 2006). The linear predictor was an analysis of covariance (ANCOVA) model with the species or the acclimatization temperature as a factor and the gradient temperature as a covariate. The covariate was modeled using thin-plate regression splines. The basis dimension of the spline was set at default (⫽10) for initial models and eight for updated models to ßatten the prediction. Because the counts were taken serially along the gradient, a correlation was expected. Inclusion of an exponential correlation did not markedly increase the Þt of model, so the correlation structure was excluded. Two temperature-dependent models Þtted using nonlinear regression were used to describe the relationship between respiration and temperature. For data that showed almost symmetric responses around the optimal temperature (Topt), deÞned here as a temperature where the maximum respiration rate occurred, we adapted the model of Kontodimas et al. (2004), which provided a better Þt (assessed by Akaike information criterion [AIC]) than other models, namely, linear, Janisch, Logan-10, Taylor, Lactin and Briere 1 (Kontodimas et al. 2004, Walgama and Zalucki 2006). The Taylor model (Roy et al. 2002) provided a better Þt than the Kontodimas model, but this model does not include parameters of interest, namely, the lower (Tmin) and upper (Tmax) temperature thresholds. Here, Tmin and Tmax are temperatures where the respiration rate is zero. The Kontodimas model was adapted as follows: y ⫽ a(T ⫺ Tmin)2(Tmax ⫺ T), where y is respiration rate; T is experimental temperature; and a, Tmin, and Tmax are estimated parameters. The optimum temperature (Topt) was found numerically by solving dy/dT ⫽ 0. The formula was 0 ⫽ 2a(Tmax ⫺ Topt)(Topt ⫺ Tmin) ⫺ a(Topt ⫺ Tmin)2 and Topt was found as a root. The model adapted from Briere et al. (1999), y ⫽ aT(T ⫺ Tmin)√Tmax ⫺ T, provided best Þt to the A. siro acclimatization data. In this model, Tmin and Tmax have the same meaning as in the Kontodimas model. All analyses were performed within the R environment (R Development Core Team 2009). Results Thermal Preference of Mites. The distribution of the density of four mite species along the temperature gradient differed signiÞcantly among the study species (Table 1). The four mite species acclimatized at 25⬚C were found to prefer different temperature ranges. The thresholds of the ranges were estimated from the obtained models as temperature value (rounded to 0.5⬚C) where the relative frequency (proportion of the total density) of mites exceeded the initial relative density, i.e., 10%. The narrowest range was found for

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Table 1. Mean ⴞ SE relative frequency of density of four mite species for each of 10 temperature sectors along the gradient represented by mean temperature

Table 2. Mean ⴞ SE percentage of A. siro specimens acclimatized at three temperatures for each of 10 temperature sectors represented by mean temperature

Temp (⬚C)

A. siro

8.9 12.2 15.6 19.3 23.0 26.3 29.4 32.6 36.3 40.6

6.0 ⫾ 0.02 9.9 ⫾ 0.38 14.0 ⫾ 0.45 12.2 ⫾ 0.42 12.3 ⫾ 0.03 15.7 ⫾ 0.03 17.5 ⫾ 0.03 5.8 ⫾ 0.02 5.2 ⫾ 0.02 1.5 ⫾ 0.01

D. farinae 8.3 ⫾ 0.02 9.9 ⫾ 0.32 4.6 ⫾ 0.22 12.7 ⫾ 0.35 8.8 ⫾ 0.02 14.2 ⫾ 0.02 15.0 ⫾ 0.02 14.8 ⫾ 0.02 10.2 ⫾ 0.02 1.4 ⫾ 0.01

Acclimatization temp (⬚C)

L. destructor

T. putrescentiae

Temp (⬚C)

5

15

30

7.5 ⫾ 0.02 10.3 ⫾ 0.32 8.4 ⫾ 0.29 8.5 ⫾ 0.29 12.5 ⫾ 0.02 12.4 ⫾ 0.02 23.5 ⫾ 0.03 12.5 ⫾ 0.02 3.1 ⫾ 0.01 1.4 ⫾ 0.01

6.1 ⫾ 0.02 4.8 ⫾ 0.27 5.6 ⫾ 0.29 5.7 ⫾ 0.02 5.6 ⫾ 0.02 3.6 ⫾ 0.02 23.7 ⫾ 0.03 37.1 ⫾ 0.04 5.7 ⫾ 0.02 2.1 ⫾ 0.01

8.9 12.2 15.6 19.3 23.0 26.3 29.4 32.6 36.3 40.6

39.4 ⫾ 0.05 10.3 ⫾ 0.03 9.3 ⫾ 0.03 5.3 ⫾ 0.02 8.3 ⫾ 0.03 5.2 ⫾ 0.02 9.1 ⫾ 0.03 8.7 ⫾ 0.03 2.9 ⫾ 0.02 1.6 ⫾ 0.01

6.8 ⫾ 0.02 9.0 ⫾ 0.02 8.7 ⫾ 0.02 10.2 ⫾ 0.02 8.8 ⫾ 0.02 10.1 ⫾ 0.02 21.1 ⫾ 0.03 13.7 ⫾ 0.02 9.8 ⫾ 0.02 1.8 ⫾ 0.01

5.4 ⫾ 0.02 10.7 ⫾ 0.03 8.6 ⫾ 0.03 5.8 ⫾ 0.03 10.3 ⫾ 0.03 7.8 ⫾ 0.03 19.6 ⫾ 0.04 22.3 ⫾ 0.04 6.5 ⫾ 0.03 3.1 ⫾ 0.02

Data are given as percentages.

Proportion 0.2 0.4 0.6

10 15 20 25 30 35 40 Temperature [°C]

Temperature [°C]

0.6

C

0.4

Proportion

0.4

0.0

0.2

Proportion

0.0

0.2

Temperature [°C]

10 15 20 25 30 35 40

0.2

D

Temperature [°C]

B

0.0

0.0

C

10 15 20 25 30 35 40

A

Proportion 0.2 0.4 0.6

0.4 0.0

10 15 20 25 30 35 40

0.4

10 15 20 25 30 35 40 Temperature [°C]

0.0

Proportion

B

0.2

Proportion

0.2

0.4

A

0.0

Proportion

T. putrescentiae (29 Ð35⬚C). All other species had a range at least 2 times wider, speciÞcally, L. destructor (21Ð33⬚C), D. farinae (19 Ð36⬚C), and A. siro (13Ð 31⬚C). The relative frequency of A. siro showed two peaks below 20% ⬇7⬚C wide (GAM, ␹28.94 ⫽ 34.7, P ⬍ 0.0001) (Fig. 3A), whereas the relative frequency of the other three species had only one peak along the gradient. SpeciÞcally, in D. farinae the peak was below 20% and 14⬚C wide (GAM, ␹28.98 ⫽ 36.5, P ⬍ 0.0001) (Fig. 3B); in L. destructor, the peak was higher than 20% and ⬇7⬚C wide (GAM, ␹28.93 ⫽ 67.1, P ⬍ 0.0001) (Fig. 3C) and in T. putrescentiae, the peak was up to 40% and 7⬚C wide (GAM, ␹28.96 ⫽ 162.1, P ⬍ 0.0001) (Fig. 3D). The lowest threshold of the range was found for D. farinae (28⬚C), followed by A. siro (28.5⬚C), L. destructor (29.5⬚C), and T. putrescentiae (31.5⬚C).

Effect of Acclimatization Temperature on A. siro. Acclimatization of A. siro at three different temperatures resulted in signiÞcantly different distributions of density along the temperature gradient (Table 2). Acclimatization at 5⬚C resulted in a single peak reaching up to 60% between 9 and 12⬚C (GAM, ␹28.91 ⫽ 75.1, P ⬍ 0.0001) (Fig. 4A). Acclimatization at 15⬚C resulted in a peak up to 30% between 9 and 20⬚C (GAM, ␹28.95 ⫽ 53.5, P ⬍ 0.0001) (Fig. 4B), and acclimatization at 30⬚C resulted in a peak higher than 20% between 27 and 35⬚C (GAM, ␹28.91 ⫽ 30.1, P ⫽ 0.0004) (Fig. 4C). In all cases, the acclimatization temperature fell within the range of the preferred temperature range. Respiration Rate Along the Thermal Gradient. The relationship between the respiration rate and the temperature was similar for the four mite species (Fig. 5). Overall, the respiration rate increased almost linearly with the temperature up to ⬇30 C and then decreased

10 15 20 25 30 35 40 Temperature [°C]

Fig. 3. Proportion of mite individuals of four mite species acclimatized at 25⬚C along the temperature gradient. The Þtted lines (solid) represent spline smoother. (A) A. siro. (B) D. farinae. (C) L. destructor. (D) T. putrescentiae. Dotted lines represent initial relative frequency (i.e., 10%) across the entire gradient. Points below the dotted line indicate a sample composed of individuals that avoided a certain temperature, and points above the line indicate a sample composed of individuals that preferred a certain temperature.

10 15 20 25 30 35 40 Temperature [°C]

Fig. 4. Proportion of A. siro individuals acclimatized at three different temperatures along the temperature gradient. The Þtted lines (solid) represent spline smoother. (A) 5⬚C. (B) 15⬚C. (C) 30⬚C. Dotted horizontal lines represent initial relative frequency (10%). Points below the dotted line indicate a sample composed of individuals that avoided a certain temperature, and points above the line indicate a sample composed of individuals that preferred a certain temperature.

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B

0

500 1000

500 1000

50

Respiration [mg/h]

500 1000 0

10

20

30

40

10

20

30

40

50

Temperature [°C]

C

0

0

D 500 1000

10 20 30 40 Temperature [°C]

0

0

Respiration [mg/h]

Respiration [mg/h]

A

0

Respiration [mg/h]

2254

50

0

Temperature [°C]

10

20

30

40

50

Temperature [°C]

Fig. 5. Relationship between the respiration rate and temperature for four mite species. The Þtted lines represent the model of Kontodimas et al. (2004). (A) A. siro. (B) D. farinae. (C) L. destructor. (D) T. putrescentiae.

to zero. The rate of increase (a) was similar for all four species (P ⬎ 0.05; t-tests), but it was signiÞcantly lower in T. putrescientiae than in D. farinae (P ⫽ 0.0009; t-test) (Table 3). The lower temperature threshold, Tmin, was similar for all species (P ⬎ 0.05; t-tests). The upper temperature threshold, Tmax, was similar for all four species (P ⬎ 0.05; t-tests), but it was signiÞcantly lower in A. siro than in T. putrescientiae (P ⫽ 0.0003; t-test). The temperature at which the speciÞc respiration rate was maximal, Topt, was very similar for all four species (Table 3). Respiration Rate of Acclimatized A. siro. Mites acclimatized at three different temperatures showed different relationships between respiration and temperature (Fig. 6). Their respiration increased with the temperature reaching a (modeled) maximum at 29.0⬚C for populations acclimatized at 5 and 15⬚C and at 33.7⬚C for the populations acclimatized at 30⬚C (Table 4). Furthermore, there was a positive relationship between the acclimatization temperature and the maximum respiration rate. At 5⬚C, the maximum measured rate was 1,042 mg h⫺1 (SE ⫽ 59.5); at 5⬚C it was 1,502 mg h⫺1 (SE ⫽ 78.1); and at 15⬚C it was 1,895.6 mg h⫺1 (SE ⫽ 116.3). Discussion The data show that four synanthropic mites are thermophilous. When acclimated at 25⬚C, they moved Table 3.

Fig. 6. Relationship between the respiration rate of A. siro and temperature for three acclimatization temperatures (A5⬚C, A15⬚C, A30⬚C). Points are means; whiskers are SE. For each acclimatization temperature, the nonlinear model of Briere et al. (1999) is displayed.

to the temperature zone that allows accelerated metabolism and that is optimal for their development (Barker 1967; Solomon 1969; Cunnington 1984, 1985; Emekci and Toros 1989; Arlian and Dippold 1996; Sa´nchez-Ramos and Castan˜ era 2001). This suggests that there is a migration inside the grain mass, which may affect the spatial distribution and aggregation pattern (Zˇ dÕa´ rkova´ et al. 1983, Athanassiou et al. 2005). It is, however, not known how far the mites can migrate. Mites have been observed to remain and prefer locations with high grain moisture (Athanassiou et al. 2001). In this study, we further demonstrated that temperature has an important effect on mite migration and distribution. In warmer zones or hot spots, their pest potential should be higher than that estimated using only the mean temperature of the surface layer (Aspaly et al. 2007, Peka´ r and Hubert 2008). Here, we observed the thermal preferences of mites only for a single period, after 24 h. We chose this period because in preliminary experiments, we found that grain moisture changes differently at different temperature sectors after periods longer than 24 h. Then, the moisture is not constant along the gradient and the preference to a certain sector could not be attributed solely to the temperature. At present, we are not able to foresee whether a longer experimental period would inßuence thermal preferences of mites.

Estimated parameters and their SEs from the Kontodimas et al. (2004) model for four species

Parameter

A. siro

a Tmin Tmax Topt

0.064 (0.009)AB 2.338 (1.528) 45.069 (0.494)A 30.83

D. farinae 0.092 (0.012)A 5.229 (1.191) 47.668 (0.539)AB 33.52

L. destructor

T. putrescentiae

0.066 (0.012)AB 2.926 (1.665) 46.306 (0.649)AB 31.85

0.046 (0.007)B 0.804 (1.436) 48.109 (0.686)B 32.34

Parameter values signiÞcantly different at ␣ ⫽ 0.05 (t-test) are marked with different uppercase letters.

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HUBERT ET AL.: TEMPERATURE PREFERENCE AND RESPIRATION OF MITES

Table 4. Estimated parameters and their SEs from the Briere model for A. siro and each acclimatization temperature Parameter a Tmin Tmax

Acclimatization temp (⬚C) 5

15

30

0.363 (0.053) ⫺4.712 (3.599) 36.77 (0.448)A

0.444 (0.083) ⫺6.010 (4.699) 36.89 (0.529)A

0.441 (0.108) ⫺5.699 (5.125) 42.76 (2.409)B

Parameter values signiÞcantly different at ␣ ⫽ 0.01 (t-test) are marked with different uppercase letters.

But we expect that their preference should be rather similar even for longer periods. A single period for determination of thermal preferences in oribatid mites has been used by other researchers, too (Madge 1965, Wallwork 1965). The wide range of preferred temperatures by A. siro, D. farinae, and L. destructor indicates a eurythermic nature, whereas T. putrescentiae is clearly stenothermic and more thermophilous than the other studied species. This observation is supported by previous Þndings that both the developmental optima (Sa´nchez-Ramos and Castan˜ era 2005) and upper developmental threshold of T. putrescentiae (Aspaly et al. 2007) were higher than in other stored product mite species. Mite respiration showed an almost linear response to temperature up to 30⬚C. This Þnding is different from the temperature model of the intrinsic growth rate showing the temperature optimum at 25⬚C (Aspaly et al. 2007). The respiration optima of all species are only ⬇2⬚C higher than the temperature preferred in the artiÞcial temperature gradient and the optima for development. For respiration, the lower thresholds were lower, and the upper thresholds were higher than for development (Aspaly et al. 2007). Temperatures above 40⬚C were not preferred by any mite species, but the respiration rates at 40 and 45⬚C were still higher than zero. This means that the mites are able to survive for some time even in such unfavorable temperatures. Eaton and Kells (2009) suggested that T. putrescentiae has an ability to survive in unfavorable temperature or moisture conditions long enough to escape to more suitable microhabitats. Similar observations are reported for Dermatophagoides pteronyssinus Trouessart 1897, which is tolerant to ßuctuating temperatures (Pike et al. 2005). Cunnighton (1984) suggested that acclimation to cold is important for survival of mites in grain stores during winter. Such acclimation is expected due to changes in respiration. The respiration rate of A. siro increased with increasing acclimation temperature corresponding to the inverse compensation as described by Precht et al. (1973). The inverse compensation may prompt the thermal acceleration of metabolic activity during longer periods of increased temperature. In this study, A. siro acclimated to 30⬚C had signiÞcantly higher Tmax than those acclimated to 5 and 15⬚C. This Þnding indicates that the acclimation changed thermal resistance as was expected (cf. Sa´ nchez-Ramos and Castan˜ era 2001).

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Our results showed that cold acclimation shifted the thermal preferences of A. siro to lower temperatures, indicating that their thermal preference is plastic and depends on acclimatization temperatures. It remains to be investigated whether acclimatized mites are able to develop and reproduce at suboptimal temperatures at a comparable rate as at the optimal temperature. If development and reproduction takes place at low temperature then predictions of population dynamics by current models (Peka´r and Zˇ dÕa´rkova´ 2004, Aspaly et al. 2007) are markedly underestimated. It is also not known whether acclimation inßuences developmental temperature thresholds. We expect that thermal history can inßuence the prediction of the optimal temperatures for the development of mites and thus explain the variability between different observations. For example the optimal temperature for development of T. putrescentiae was 30⬚C (Sa´nchez-Ramos and Castan˜ era 2001) or ⬇32⬚C (Barker 1967, Cunnington 1969) and for population growth 25⬚C (Aspally et al. 2007). The study mites could be categorized either as eurythermic (A. siro, L. destructor, and D. farinae) or stenothermic (T. putrescentiae). The model species, A. siro, showed that thermal acclimation changes thermal preferences. The rate of respiration increased with acclimation temperature (inverse compensation), which is probably a strategy promoting strong population increase of thermophilous mites in favorable conditions (an r-strategy). In future studies, the effect of constant and ßuctuating temperatures on synanthropic mites should be considered.

Acknowledgments We thank Petr Loskot and Jan Svoboda for gradient construction and documentation and Rostislav Zemek and Vaclav Stejskal for comments on the manuscript. J.H. and M.N. obtained support from the Czech Ministry of Agriculture (0002700604). S.P. was supported by the grant MSM0021622416 provided by the Ministry of Education, Youth and Sports of the Czech Republic.

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