Abstract In storage facilities one can find grain either in stored grain mass or ingrain residues in the store corners or machinery. Although it is claimed that grainresidues are serious pest reservoirs since they harbor numbers of stored productarthropods and are connected via continuous emigration with grain mass, the doc-umentation for this is not convincing. Therefore in 78 selected grain stores, wesimultaneously sampled the grain mass and residues in order to compare concurrentmite communities in these two different habitats. We found 30 species in about614 000 individuals in residues and 23 species in about 20 000 individuals in grainmass. Canonical correspondence analysis (CCA) of transformed abundance datashowed differences in the communities of mites in grain mass and residues: (i)species associated to grain residues (e.g. Tyrophagus longior, Tydeus interruptus,Acarus farris and Cheyletus eruditus) and (ii) species associated to both grain massand grain residues (e.g. Tarsonemus granarius, Acarus siro, Tyrophagus putrescen-tiae, Lepidoglyphus destructor and Cheyletus malaccensis). Although the residuesamples had more mites and higher species diversity than the stored grain mass, nocorrelation in mite abundance and species numbers between samples from grainresidues and grain mass was found, thereby indicating low connectivity of these twohabitats.

J. Hubert (&) Æ Z. Kucerova Æ V. StejskalResearch Institute of Crop Production, Drnovska 507, Praha 6,Ruzyne CZ-16106, Czech Republice-mail: hubert@vurv.cz

Z. Mu}nzbergovaInstitute of Botany, Academy of Sciences of the Czech Republic,CZ-252 43 Pruhonice, Czech Republic

Z. Mu}nzbergovaDepartment of Botany, Faculty of Science, Charles University,Benatska 2, CZ-12801 Praha 2, Czech Republic

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Exp Appl Acarol (2006) 39:149–158DOI 10.1007/s10493-006-0026-y

Comparison of communities of stored product mitesin grain mass and grain residues in the Czech Republic

Jan Hubert Æ Zuzana Mu}nzbergova ÆZuzana Kucerova Æ Vaclav Stejskal

Received: 29 July 2005 / Accepted: 24 March 2006 /Published online: 19 May 2006� Springer Science+Business Media B.V. 2006

Keywords Storage Æ Grain Æ Infestation Æ Grain residues Æ Canonicalcorrespondence analysis Æ Mite communities

Introduction

The infestation of grain by stored product mites may result in grain damage by mitesfeeding on grain germ, contamination of the stored grain by allergens of mite origin(Hage-Hamsten and Johansson 1998) and by transfer of mycotoxin-producing fungi(Hubert et al. 2003). Effective control of pest mite populations requires a deepunderstanding of all components of the stored grain system. Grain can be found in‘‘wanted’’ and ‘‘unwanted’’ forms in all types of storage facilities. Obviously, thewanted form represents stored grain masses in silos, flat stores, bags or containers.Unwanted, but hardly avoidable, are the various forms of grain residues and debris:(i) residues in the corners of store buildings that are formed by improper cleaningand sweeping, (ii) residues that are formed by spilled grain in and around stores, (iii)grain remnants present in improperly cleaned or designed handling equipment andother storage machinery (aeration systems), (iv) residues remaining in empty binsand flat stores, and (v) grain residues in neglected sacks outside or inside flat stores.From the ecological point of view, ‘‘grain mass’’ and ‘‘grain residues’’ representdifferent habitats since they differ in physical structure, humidity and temperature.

Grain mass consists of intact grains and a very small proportion of broken kernelsand dust. It is regularly inspected for humidity, temperature and presence of pests. Ifneeded, grain mass is treated by fumigants or ventilated to decrease temperature andmoisture to prevent infestation by arthropods and spoilage by microorganisms.Alternatively, residues are formed by a mixture of intact and broken grains and ahigh proportion of dust and small pieces of straw. The residues are usually in contactwith the ground, therefore they have a higher moisture content than stored grain,with improved condition for the growth of mites (Sinha 1979). In addition residuesare not usually monitored for pest presence, treated by fumigants or ventilatedthereby enabling pest and fungi infestations to develop.

It is known that grain residues may harbor many species of insects (beetles andpsocids) and mites (Zd’arkova 1967; Pagliarini 1979; van Asselt et al. 1996; Reedet al. 2003). Kucerova et al. (2003) found that pest populations in grain residues inempty stores might increase manifold between consequent harvests. Thus, grainresidues are an ideal pest shelter and reproduction site. These pests are hidden in theundisturbed microhabitats of grain stores and usually overlooked for a long time. Itis concluded that infested grain residues are serious pest reservoirs since storedproduct arthropods may continually emigrate to infest sound grain mass. Althoughgenerally accepted, there is surprisingly little evidence for this claim, especially inmites (Sinha 1968). In addition, unlike the mite pest populations inside the grainmass, the population in grain residues had remained out of the focus of most studiesand we know little about communities, population dynamics and migration of storedproduct arthropods in grain residues.

Therefore in 78 selected grain stores, we simultaneously sampled the grain massand residues in order to compare mite communities in these two habitats. This studyis part of a long-term research program on fauna of the agricultural and food storesin the Czech Republic (e.g. Stejskal et al. 2003; Lukas et al. 2006).

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Methods

Sampled sites

Altogether 147 geographically isolated stores were inspected in the Czech Republic(Central Europe) during 1996–1998, but only in 78 mite infestations were found inboth grain residues and/or grain mass. Typical ranges of temperature (t) and mois-ture content (m.c.) of grain at 1 m grain depth in Czech stores are: September:t = 17–19�C, m.c. = 12.8–13.4%; October: t = 17–19�C, m.c. = 12.3–13.2%; Novem-ber: t = 9–17�C, m.c. = 12.8–13.5%; December: t = 5–13�C, m.c. = 12.4–13.5%;January: t = 3–10�C, m.c. =12.2–13.5%; February: t = 2–9�C, m.c. = 12.2–13.7%;March: t = 0–9�C, m.c. = 12.0–13.7%; April: t = )1 to +7�C, m.c. = 12.0–13.7%. Thevariability of these physical parameters is much higher at the grain surface duringwinter months (t = )5 to +12�C and m.c. = 11–16%) (Lukas et al. 2006).

In each store, four to five store units were sampled (one ‘‘store unit’’ = one bin orflat-store chamber with identical sort of grain). Each sample (2.5 kg grain) consistedof 5 sub-samples (0.5 kg grain) taken from 5 sampling points per store unit(Zd’arkova 1998a; Stejskal et al. 2003).

The grain residue samples were taken from the floor and handling machinery. Insome stores, we were not always able to sample enough grain residues to divide itinto five sub-samples due to low amounts of residue or due to poor access on cracksand crevices or because they were inside inaccessible machinery equipment etc. Insuch cases one sample (2.5 kg) was taken.

Treatment of samples and data

Each sample (2.5 kg) was gently mixed, and then a 200 g sub-sample was placed onthe Berlese-Tullgren funnel (exposure 24 h, temperature 40�C). Mites were sortedout, preserved and mounted on microscope slides for species determination. Miteswere preserved in Oudemans solution (70% ethanol (87 ml); acetic acid (8 ml),glycerol (5 ml)) (Zd’arkova 1967). Identification of mites was conducted accordingto Zachvatkin (1941), Robertson (1959), Samsinak (1962, 1966), Griffiths (1964),Johnston and Bruce (1965) and Hughes (1976). The abundance of a particularspecies was recalculated to 1 kg of the sample.

Data analysis

The data on species composition of mites in the stores were analyzed usingCanonical correspondence analysis (CCA, Jongman et al. 1987). The sample type(grain residues or grain mass) was used as independent variable and store codewas used as a covariate. We used a Monte Carlo permutation test to test forsignificant differences between the two types of samples (Leps and Smilauer2003). The two samples from the same store were treated as split-plots forming awhole-plot and were permuted within the whole plot (store). Whole plots werenot permuted. Two types of analysis were performed, either using the originalabundance data, or using the data log-transformed. The former analysis comparescomposition of the common species, the latter gives higher weight also to the rarespecies.

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The differences in number of species, abundance and transformed abundancedata between grain mass and grain residues were compared using STATISTICA(version 5.1) and Wilcoxon’s paired tests (Sokal and Rohlf 1995).

Results

From a total of 78 inspected stores, 64 had mite infestations in both residues andgrain mass, 4 had infested grain mass but uninfested residues and 10 had infestedresidues but uninfested grain mass. Altogether about 635 000 mites were analyzed,comprising 33 species. There were about 30 species (ca. 614 000 individuals) inresidues, and only 23 species (ca. 20 000 individuals) in stored grain mass.

The number of species in the residue samples was significantly higher (Wilcoxon‘spaired test; Zðn¼78Þ ¼ 2:232; p = 0.027) than in the grain mass (Fig. 1). The sametrend was found for abundance (Wilcoxon‘s paired test; Zðn¼78Þ ¼ 6:738; p > 0.001)with the residues containing a higher proportion of samples with high abundancevalues in comparison to grain mass (Fig. 2).

There was no correlation between number of species and mite abundance insamples of grain mass and grain resides from the same store (Table 1). Also therewas no correlation between abundances of the majority of species sampled, exceptfor Cheyletus aversor and Tydeus interruptus.

There were no significant differences between grain and grain residues when weused the original mite abundance data in the analysis (Trace = 0.010, F-ratio = 0.793,p = 0.426). This indicates that the composition of the common species is the same inthe two types of samples. On the other hand, there were significant differences inspecies composition between the two environments when the abundance data werelog-transformed (Trace = 0.084, F-ratio = 4.499, p = 0.002). This indicates that thereare significant differences between the communities in the species that are rare.Sample type explained 2.4% of the total variation in the dataset in this case.

Number of species Tranformed abundance

0

1

2

3

4

5

grain grainresidues

0

1

2

3

4

5

grain grainresidues

S

log

(N+1

)

Fig. 1 Comparison of species numbers (S) and transformed abundance (N) in samples (1 kg) takenin grain mass and residues. The columns are medians and abscissa indicates interquartile range

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Based on this analysis, the first canonical axes divided species into those occurringmainly in grain residues and those occurring mainly in the grain (Table 1). The mainspecies associated with the residues were Chortoglyphus arcuatus, Eulaelabs stabu-laris, Cheyletus aversor, Haemogamasus pontiger, Tyrophagus longior, Tydeusinterruptus, Alliphis siculus, Cheyletus trouessarti, Tyrophagus perniciosus, Acarusfarris and Cheyletus eruditus. There were no species that would be associated mainlywith grain mass and there was a large group of species associated with both types ofenvironments (Tarsonemus granarius, Acarus siro, Androlaelaps casalis, Cheyletusmalaccensis, Tyrophagus putrescentiae, Lepidoglyphus destructor and Acaropsellinadocta) (see Table 1 and Fig. 2).

Discussion

This work offers new information on the occurrence of pest and beneficial mites intwo storage habitats, i.e. grain masses and grain residues. As expected, we foundmany more mite species (30 vs. 23) and individuals (614 000 vs. 20 000) in grainresidues than in grain mass. The results support the findings, that grain residuesappear to be attractive to stored grain pests not only before grain harvest, but alsoduring the whole storage season (Reed et al. 2003). We confirmed the differencebetween communities of mites occurring in grain mass and grain residues; the speciescompositions differed especially in predatory (Cheyletus spp., Blattisocius spp.) andrare pest mites (Table 1). The most surprising result of the study was the absence ofcorrelation in mite abundance and species numbers between samples of residues andgrain mass from the same store.

The differences in species composition and abundance of mites indicate that grainresidues constitute a specific type of environment within the stores. The resultsclearly show that these residues are more favorable for the mites than the grainmasses; this was confirmed by the absence of species that would be restricted only tothe grains. This is in agreement with previous studies (Solomon 1969; Cunnington1976; Thomas and Dicke 1971; Hubert et al. 2004) that demonstrated that thepresence of broken/crushed grains, grain dust and fungal mycelium/spores, that arefrequently found in grain residues, is essential for the survival and multiplication ofmany mite species.

0 20 40 60 80 100

10 000-100 000

5000-10000

1000-5000

1-1000

0

grain grain residues

abundant

% samples

Fig. 2 Distribution of mite abundances in samples of grain mass and residues. Abundance is numberof mites recalculated per 1 kg sample

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The most important pest mite species (e.g. species associated to both grain massand grain residues, Acarus siro, Tyrophagus putrescentiae and Lepidoglyphusdestructor) are adapted to low humidity and food conditions in grain mass, which isdry, fungus-free and with fewer broken kernels (Cunnington 1976; Sinha 1979), andthey can reproduce here as well as in grain residues. This fact is also supported bytheir wide distribution in stored grain and farming environments (e.g. Revsbech andAnderson 1987; Iversen et al. 1990; Solarz et al. 1997, Franz et al. 1997; Athanassiouet al. 2003; Georges-Gridelet et al. 2003).

Table 1 Comparison of mite species based on their response to grain and residues detected usingCCA analysis. Scores of single mite species (ax1) along 1st ordination axis from the CCA analysisindicate preferences for grain (negative values on 1st axis) or grain residues (positive values), boldax1-values indicate the importance of particular species (product of sum of its abundances in allsamples). The first canonical axis explained 2.4% of the total variation in the dataset

Species ax1 Grain-mass Grain residues

N F(%) iF N F (%) iF

Blattisocius tarsalis )1.02 – – – 236 3 18–22Spinibdella lignicola )0.53 2 1 17–23 163 5 14–16Tyrophagus miripes )0.53 – – – 4,200 3 18–22Chortoglyphus arcuatus )0.41 3 1 17–23 13,812 10 9–10Eulaelabs stabularis )0.40 – – – 1,139 6 13Proctolaelaps pygmaeus )0.37 3 1 17–23 130 3 18–22Leiodinychus krameri )0.37 – – – 298 3 18–22Cheyletus aversor )0.35 91 5 10–11 2,605 9 11Haemogamasus pontiger )0.34 26 5 10–11 1,388 10 9–10Tyrophagus longior )0.32 18 3 13–16 72,972 18 7Tydeus interruptus )0.28 7,415 29 5 44,633 53 2Alliphis siculus )0.28 113 1 17–23 437 4 17Acarus immobilis )0.27 – – – 7 1 23–30Glycyphagus privatus )0.26 – – – 325 1 23–30Cheyletus trouessarti )0.25 10 3 13–16 2,289 8 12Tyrophagus perniciosus )0.19 1,361 5 14–16Acarus farris )0.18 90 12 7 52,370 19 6Cheyletus eruditus )0.18 2,046 35 3 17,157 56 1Caloglyphus oudemansi )0.07 50 1 17–23 10,000 1 23–30Caloglyphus berlesei 0.00 – – – 6,000 1 23–30Lepidoglyphus michaeli 0.00 – – – 220 1 23–30Ctenoglyphus plumiger 0.00 – – – 50 1 23–30Tarsonemus granarius 0.04 1,647 19 6 28,409 33 5Acarus siro 0.09 4,561 50 2 279,048 46 3Androlaelaps casalis 0.15 34 8 9 272 5 14–16Cheyletus malaccensis 0.20 48 3 13–16 440 1 23–30Blattisocius keegani 0.24 38 3 13–16 91 1 23–30Tyrophagus putrescentiae 0.46 1,268 32 4 42,718 14 8Lepidoglyphus destructor 0.46 2,809 63 1 31,511 36 4Acaropsellina docta 0.68 43 9 8 60 3 18–22Tyrophagus neiswanderi 0.87 2 1 17–23 – – –Pyemotes herfsi 1.91 1 1 17–23 – – –Hypoaspis lubrica 2.18 22 4 12 – – –TOTAL 20,338 614,340Number of species 23 30

ax1—species score, N—total abundance, F—frequency (%) of occurrence of mite in samples,i—indexes

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There are several species of high medical importance that are associated only withgrain residues namely Chortoglyphus arcuatus, Tyrophagus longior and Acarus farris(Luczynska et al. 1990; Muesken et al. 2000, 2003). This indicates that it is importantto regularly inspect and control the pests in grain residues, not only from an agri-cultural perspective but also for medical reasons as allergenic mites can causeallergies in storekeepers and farmers (Spiewak et al. 2001a, b; Muesken et al. 2002,2003; Szilman et al. 2004; Vidal et al. 2004). Clearly, accurate cleaning coupled withchemical treatment of mite infested grain residues may reduce the risk of allergensensitisation for farmers in a better way than high volume control of small miepopulations in total grain mass.

The multivariate analysis (CCA) indicates that the predatory mite Cheyletuseruditus is more common in grain residues, while the reverse is true for Cheyletusmalaccensis. Although both predators feed on pest mites and insect eggs (Hughes1976), only C. eruditus is used as a biological control agent (Cheyletin) (Zd’arkova1991, 1998b). The natural ability of C. malaccensis to penetrate into grain massindicates a new potential of this species for biological control of pest mites.

As stated above the most interesting finding of this study is that we found (almost)no correlation of mite abundance and species numbers between samples taken fromgrain residues and grain mass in the same store. Dramatically different abundancesof the same species on two sites within one storage facility indicate that mites in thetwo environments function as two independent communities growing at differentrates. In addition, the extent of population differences indicates that the connectivityof these sub-populations is lower than originally thought. This is in contradictionwith currently prevailing opinions since the grain residues are claimed the mainreservoirs from which pests migrate into sound grain mass or are the resourcefor re-infestation of grain after fumigation (Pagliarini 1979; Reed et al. 2003). Itcould be that mites easily infest the newly harvested grain when it is loaded directlyon the infested residues remaining on the bottom of empty stores from the previ-ous year. However, long distance active dispersal of mites from residues is lim-ited (Athanassiou et al. 2001), unlike relatively large storage beetles and moths(Kucerova et al. 2003), by their low walking capacity and sensitivity to dry air(Hughes 1976). Nevertheless, from time to time, insects or rodents may transfermites on their bodies over large distance (Houck and OConnor 1991).

The existence of two partly independent communities of mites within a singlestore indicates that performance of mites in the store is not driven only by simplelocal dynamics of the populations and by interactions between the species, but alsoby differential migration ability of the species in the two communities. Specifically,the whole system may be viewed as a metapopulation obeying source-sink dynamics(Gilpin and Hanski 1991) where the grain residues represent a source of potentialmigrants into the grain. Such systems have been described for many natural popu-lations (e.g. Wootton and Bell 1992; Donahue et al. 2003; Travis and Park 2004;Jonzen et al. 2005), and recently a similar pattern was indicated by studies ingreenhouses (e.g. Nachman 1991; Nachman and Zemek 2002a, b) or food industryenvironments and stored commodities (Stejskal 2002; Athanassiou et al. 2002). Thesystem described in this study may thus be treated as a new environment in whichsource sink dynamics may take place. It indicates that we need to gain informationon temporal dynamics of the system and use modelling approaches to fully under-stand the dynamics in these communities.

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Acknowledgements The authors are obligated to Dr. Eva Zd’arkova for the determination ofmites. This work was supported by a grant MZE-000-2700603. It is also partly supported by MSMT0021620828 and AV0Z6005908. Authors thank to Sarka Tuckova, Marta Nesvorna, Radek Aulickyand Pavel Horak for technical assistance and collecting the samples.

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