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Keywords:

  • Conservation monitoring;
  • Diacritinae;
  • Diplazontinae;
  • edge effects;
  • Ichneumonidae;
  • Malaise trap;
  • parasitoid wasp;
  • Pimplinae;
  • Poemeniinae

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Abstract. 

  • 1
    Parasitoid wasps are species-rich and likely to be sensitive indicators of environmental change. Malaise traps are widely used for sampling certain taxa of parasitic Hymenoptera, but little is known about how they should best be used to monitor the community at an individual site.
  • 2
    To investigate the effects of sample duration, trap location and replication on the parasitoid assemblage, we sampled four ichneumonid subfamilies (Hymenoptera: Ichneumonidae) intensively using Malaise traps in two farm woods in the Vale of York, UK.
  • 3
    Species accumulation curves showed that even with 16 Malaise traps per wood, the community is incompletely sampled. Despite this, we caught up to 28% of all UK species in a single wood, implying that local parasitoid diversity may be very high.
  • 4
    Abundance and species richness of parasitoids differed significantly between sample periods (fortnights) and between traps, but did not differ overall between core and edge locations.
  • 5
    Parasitoid community composition differed between core and edge traps, but differences were much stronger in one wood than the other. One subfamily, the Poemeniinae, was found predominantly in edge locations. Catch differences became greater with increasing distance between traps.
  • 6
    The previous year, two traps in each of the same woods caught only half as many species, but species abundance was positively correlated between years.
  • 7
    Our results suggest that a small number of traps can contain useful information about the parasitoid community but is likely to seriously underestimate total species richness. To achieve extensive species coverage, sampling should continue over several weeks, with widely separated traps sampling both core and edge locations. Our focal taxa should prove excellent for monitoring the effects of environmental change on biodiversity.

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

It is widely acknowledged in conservation that, although we wish to conserve as many species as possible, we have no knowledge about the majority of them (May, 1988; Gaston, 1991). Difficulties are therefore faced in effectively identifying sites to serve as biodiversity reservoirs as well as targeting taxa that are most at risk (New, 1998; Hughes et al., 2000; Samways, 2005). One group that is highly under-represented in conservation planning is the parasitoid Hymenoptera (Hochberg, 2000; Shaw & Hochberg, 2001). In this study, we investigate how best to monitor parasitoid Hymenoptera assemblages, and hence to incorporate parasitoids into conservation planning.

Parasitoids (mainly wasps) develop to maturity by feeding on or in the bodies of other arthropods, eventually killing them (Godfray, 1994; Quicke, 1997). It is widely acknowledged that the parasitoid Hymemoptera comprises a large fraction of global species richness (LaSalle & Gauld, 1993; Grissell, 2000), as well as 25% of the UK insect fauna (Shaw & Hochberg, 2001); performs essential ecosystem services in the regulation of other insect populations (Hassell, 2000); is a valuable resource for use in biological control (Jervis, 2005); possess biologies likely to make them at risk from population decline and extinction (Hochberg, 2000; Shaw & Hochberg, 2001); and should serve as a sensitive indicator of environmental threats. However, almost no conservation or monitoring work specifically involves parasitic Hymenoptera outside an agricultural context, despite increasing accessibility of the group, thanks to recent introductory texts and taxonomic literature (see Shaw & Hochberg, 2001). Although the slim existing data suggest more dramatic declines than is generally estimated for insects (Therion, 1981; Shaw & Hochberg, 2001; Shaw, 2006b), only two parasitoid Hymenoptera species have been red listed at a global scale (Groombridge, 1993), and none in the UK (Shaw, 1987). This compares to the extensive contemporary list of 860 species of aculeate Hymenoptera (mainly comprising the nest-building bees, wasps and ants) red listed in European countries (Day, 1991).

One alternative to species-level conservation is conservation of habitats, but absence of knowledge of the habitat preferences of parasitoid Hymenoptera species precludes their inclusion in assessment procedures (e.g. Webb & Lott, 2006, see Fraser et al., 2007), such that conservation measures can only hope to benefit the group incidentally. Three important short-term goals in the conservation of parasitoid Hymenoptera therefore are (i) basic inventorying of the distribution of species, (ii) to understand better the relationship between habitat characteristics and parasitoid abundance and diversity (see Shaw, 2006a; Fraser et al., 2007), and (iii) to develop monitoring programmes that will allow us to assess better the conservation status of this group. All three goals depend on an understanding of efficient and informative field sampling procedures.

Malaise traps (Townes, 1972; New, 1998; Sutherland, 2006) are a widely used sampling method for many parasitic Hymenoptera that can result in numerically large catches (e.g. Sääksjärvi et al., 2004, 2006; Wells & Decker, 2006; Fraser et al., 2007), and are widely used in inventorying programmes (e.g. Gauld, 1991). They are a form of flight interception trap that can be left for long periods unattended in the field and therefore are both time and cost effective. They are likely to be the method of choice in many sampling or monitoring schemes, although this will vary depending on the taxa targeted (e.g. see Noyes, 1982, 1989a). However, because of their relative bulk and cost, Malaise traps are commonly used singly or with low replication within a site (e.g. Owen & Owen, 1974; Fraser et al., 2007), and little is known about how effectively small numbers of traps sample the community of species present at a single site, or how long they should be left to do so (see Noyes, 1989a; Wells & Decker, 2006). Furthermore, little is known of how the abundance of parasitoid Hymenoptera may change within a habitat patch (see Noyes, 1989b), and thus how to optimise trap locations to sample the community as a whole; in fact most collecting or surveying handbooks merely refer to the effectiveness of siting traps in ‘obvious’ insect flight corridors (e.g. Betts, 1986; New, 1998). With these issues in mind, we sampled four ichneumonid subfamilies intensively using Malaise traps in two farm woods in the Vale of York, UK. We wished to observe how the abundance, richness and community composition of parasitoids varied over time, and with spatial location, as well as how effectively different numbers of traps sampled the community present.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Sampling parasitoids

Four closely related subfamilies of the Ichneumonidae were chosen for study: Diplazontinae, Pimplinae, Diacritinae and Poemeniinae. These subfamilies have useable species level keys (Beirne, 1941; Fitton et al., 1988), are known to be abundant in many habitats, and have a wide range of hosts. All species in these four subfamilies are winged parasitoids. They have also been used as biodiversity indicators in diverse geographical locations (see Therion, 1979; Gaston & Gauld, 1993; Sääksjärvi et al., 2004; Fraser et al., 2007).

The Diplazontinae is a relatively small subfamily with 55 British species in 12 genera (Broad, 2005). All species are thought to be endoparasitoids of aphidophagous Syrphidae (Diptera) with host records available for approximately 50% of species.

The subfamily Pimplinae exhibits a wider range of biologies and hosts than any other subfamily of the Ichneumonidae (Fitton et al., 1988; Shaw, 2006b). It is also probably the most extensively studied subfamily, largely due to the fact that many species are parasitoids of economically important pests. In the British Isles, there are 103 species in 30 genera (Broad, 2005). The subfamily is currently divided into three monophyletic tribes – the Delomeristini, Ephialtini and Pimplini – which demonstrate distinct ecologies (Gauld et al., 2002; Broad, 2005). In the British Isles, the Delomeristini consists of nine species in two genera. Host information for this tribe is poor but some species in the genus Delomerista appear to parasitise cocoons of sawflies or other ichneumonids, while those in the genus Perithous appear to be associated most frequently with aculeate Hymenoptera (Fitton et al., 1988). The Ephialtini consists of 75 species in 24 genera. Host groups for this tribe are varied and are found across the orders Coleoptera, Hymenoptera, Diptera and Arachnida. The majority of species are ectoparasitoids of holometabolous insect larvae, pre-pupae or pupae (Fitton et al., 1988). The Pimplini consists of 20 species in three genera. All are chiefly idiobiont endoparasitoids of the pupae of Lepidoptera (Fitton et al., 1988). Idiobiont parasitoids permanently paralyse or kill the host before the parasitoid egg hatches. The host is consumed in the location and state in which it was attacked (Askew & Shaw, 1986).

The subfamilies Poemeniinae and Diacritinae were previously grouped within the Pimplinae (Fitton et al., 1988) and were included in this study for that reason although they are now recognised as distinct subfamilies (Wahl & Gauld, 1998; Gauld et al., 2002). The Poemeniinae contain six species in Britain (Broad 2005). Members of the Poemeniinae develop as idiobiont ectoparasitoids and at least some of these species are most often collected in association with dead and standing timber (Fitton et al., 1988). Diacritinae is one of the few subfamilies for which the larvae are completely unknown (Wahl & Gauld, 1998). In Europe, only one species is known, Diacritus aciculatus (Fitton et al., 1988).

The Malaise traps (Marris House nets, Bournemouth, UK) were all black in colour, 1.8 m high at the collection head end, tapering to 1 m high at the opposite end, and were 1.8 m in length. Thirty Malaise traps were divided between two woodlands, to give maximal within-site replication while retaining some across-site replication. Within woods, traps were then divided into edge and core locations (Fig. 1). Edge traps were placed in a line 10–20 m from the southern edge (Fig. 1), 20–40 m apart. This allowed a measure of within-site variance for trap catch while controlling for distance from the woodland edge and aspect, and also allows comparison with sampling in the same woods in 2003 (Fraser et al., 2007). Previously used procedures for trap siting within these parameters were followed (see Fraser et al., 2007). Eight traps were placed on the periphery at one wood (Copmanthorpe, see below) but only six were placed on the periphery of the other wood (New Covert, see below) because of the shorter length of its southern edge.

image

Figure 1. Malaise trap placement within woods. Either six or eight traps were placed in the edge trapping area. Eight traps were placed in the core trapping area. The drawing is not to scale.

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Core traps were placed in a circle (radius 40–50 m) around the centre of the woodland (Fig. 1). This design allowed a measure of within-site variance of trap catch in the core habitat, while controlling for distance from the woodland centre. This design also means that traps remain 20–40 m apart.

Traps were open for the last 2 weeks of July and first 2 weeks of August 2004, for consistency with Fraser et al. (2007), with trap bottles being changed every 2 weeks.

Sampling vegetation

A 20-m quadrat around each trap was used for a vegetation survey using the same methods as in Fraser et al. (2007). This gave, for each trap, data on broadleaf/coniferous content, tree/shrub species richness, ground vegetation species richness, plant architectural diversity, plant height diversity, ground and canopy cover.

Study sites

To investigate patterns of parasitoid distribution in both the periphery and core of woodland habitats, selected sites had to have a central area of over 140 m × 140 m, and preferably larger, to allow space for a core circle of traps (Fig. 1). Copmanthorpe Wood and New Covert, in the Vale of York, were selected. These two woods were included in a more extensive study in 2003 in which 15 woods were sampled using two traps per wood (see Fraser et al., 2007).

Copmanthorpe Wood (OS grid ref. SE 562 450) is a 6-ha, mixed broadleaved woodland, dominated by Betula pendula (silver birch), Acer pseudoplantanus (sycamore) and Quercus robur (pedunculate oak). New Covert (OS grid ref. SE 732 442) is a 3.3-ha, even-aged, mixed broadleaved woodland. It comprises mainly B. pendula, Salix caprea (goat willow), Q. robur, A. pseudoplantanus, Alnus glutinosa (common alder), Fraxinus excelsior (ash), Populus tremula (aspen) and Sorbus aucuparia (rowan).

Data analysis

Species accumulation curves were generated for the data set combined and for the subfamilies Diplazontinae and Pimplinae at each site. The curves indicate the extent to which the woodland fauna is sampled, and how many species each extra trap is likely to add. Curves were generated by running 14 (New Covert) or 16 (Copmanthorpe Wood) sequences of accumulations, one with each of the traps at the start, and then adding one trap at random until all were used. In addition, to help illustrate the utility of trap replication, we compared the catch in 2004 using 14–16 traps per wood, with that of the 2003 catch from the same woods that used just two (edge) traps.

To explore temporal and spatial variation in parasitoid abundance and richness, nested analysis of variance (anova) was carried out on the data for individual traps. Factors in the analysis were sample period (fortnight), trap, wood, position (core or edge). In the initial model, traps were nested within the position*wood interaction to account for variation between traps within the same wood and relative position. This is a repeated measure design; hence, sample period (fortnight) was included in the analysis to account for the problem of pseudo-replication by repeat visits to the same trap sites. Non-significant factors and interaction terms were sequentially removed from the original model to leave only those explaining a significant proportion of variance. If trap position was non-significant in the model, this was subsequently removed from the nesting. All abundance data were log10(x+ 1) transformed to reduce right skew.

Stepwise backwards regression analysis was used to investigate relationships between measured vegetation variables and parasitoid abundance, richness and Simpson's index for each trap. Simpson's index is recommended as a good estimate of diversity for relatively small sample sizes (Magurran, 2004). The form of the Simpson's index used here is that which is appropriate for a finite community. The index is heavily weighted towards the most abundant species in the sample while being less sensitive to species richness. The index is expressed here as the reciprocal (1/D) and the value of the measure will rise as the assemblage becomes more even. As well as using data for the four subfamilies, data for the pimpline tribes Pimplini and Ephialtini were analysed separately, because previous results (Fraser et al., 2007) had shown a distinct difference between these tribes and their relationship to the vegetation.

Similarity indices were used to investigate the similarity of assemblages between traps within the two woodlands. The Jaccard index, Sørenson index, Sørenson quantitative and Morisita-Horn indices were calculated. These widely used measures were chosen to test the sensitivity of results to the properties of the index in question. All indices equal 1 in cases of complete similarity and 0 if the sites have no species in common (Magurran, 1988). The first two are simple but take no account of relative abundance of species. The Morista-Horn index does, and is often considered the most satisfying measure by researchers, but is highly sensitive to the abundance of the most abundant species (Magurran, 1988). The Sørenson quantitative is semi-metric but is not affected by shared missing species. Trap pairs were categorised as either both edge, both core, or 1 core versus 1 edge. anova was used to test whether these categories affected the similarity indices, thus indicating whether core or edge location affected the assemblage composition.

A Mantel test was used to ask whether samples from more distant traps were more dissimilar. A matrix of pairwise distances between traps was generated. This was the predictor matrix. A second matrix of pairwise dissimilarity scores was generated using the Jaccard index and the Morisita-Horn index and this formed the dependant matrix. Because the elements of the matrices are not independent, Mantel's test of significance is evaluated via permutation procedures. Here, 10 000 permutations were run (Sokal & Rohlf, 1995).

Detrended correspondence analysis (DCA) was carried out to determine whether assemblages in the periphery and core of the habitat were distinct in terms of parasitoid composition. The sample values for the first two axes of the DCA were correlated with habitat variables in an attempt to interpret the causes of species associations. Analyses were carried out in spss version 11.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

Traps caught 1323 individuals of 55 species in the two woodlands: 730 individuals in 46 species were captured at Copmanthorpe Wood; 593 individuals in 40 species were captured at New Covert.

Effect of trap replication

The species accumulation curves show no sign of reaching an asymptote (Fig. 2). For the pimplines and diplazontines, the continual rise of the curve after five to six traps is driven by the addition of singletons (species only trapped once in a woodland). To investigate the effectiveness of the low trap replication, the species accumulation data were examined to determine what proportion of the species caught in 2004 would have been caught if just two traps had been used (Table 1). Two traps consistently caught 30–50% of the total species in 2004. Similar values of species richness are found for two traps in 2003 and two traps in 2004 (Table 1). The log10(x+ 1) abundance of species caught by two traps per wood in 2003 was positively correlated with the log10(x+ 1) abundance of species caught by 14 or 16 traps in 2004 (Copmanthorpe Wood, Pearson's r= 0.706, n= 47, P < 0.001; New Covert, Pearson's r= 0.674, n= 43, P < 0.001).

image

Figure 2. Species accumulation curves for (a) Copmanthorpe wood, and (b) New Covert for all taxa combined (inline image), the Diplazontinae (inline image), and the Pimplinae (inline image), with 95% confidence intervals.

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Table 1.  Number of species caught by Malaise traps per wood
TrapsCopmanthorpe WoodNew Covert
AllDiplazontinaePimplinaeAllDiplazontinaePimplinae
  • Total for the 4 weeks of trapping at these sites in 2003.

  • Value as generated for species accumulation curve 2004.

Two traps 20032311 922 613
Two traps 200420 81017 511
All traps 2004471924401323
Percentage of total species caught in two traps 200442.542.141.742.532.547.8

Temporal and spatial variation in parasitoid richness and abundance

Significant temporal variation in abundance and richness was found in all taxa except in the Poemeniinae (Table 2). In some cases, this temporal variation differed significantly between woods. The spatial variation in parasitoid richness and abundance was taxon specific (Table 2). Traps differed significantly in the abundance and richness of all taxa combined. Diplazontine abundance also differed significantly between traps. Traps located within the same relative position (periphery or core) and the same wood differed significantly in pimpline abundance but not in any of the other subfamilies. Only in the Poemeniinae did traps in the periphery differ significantly from those in the core for parasitoid richness and abundance (Table 2), with 10 (Copmanthorpe Wood) and 16 (New Covert) individuals in edge traps, but only 5 (Copmanthorpe Wood) and 0 (New Covert) in core traps.

Table 2.  Results of nested anova. The r2 values are given for factors that explain significant variation in parasitoid abundance and richness
FactorsLog10(Abundance + 1)Richness
AllDiplazontinaePimplinaePoemeniinaeDiacritinaeAllDiplazontinaePimplinaePoemeniinae
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05Nested anova: initial model – wood, week, position, trap (position*wood), position*wood, position*week, wood*week.

  • Fixed factors: position, wood.

  • Random factors: week, trap.

Wood*week0.184*** 0.149***  0.241***0.377***0.255** 
Trap (wood)0.628**0.526*   0.512*   
Position   0.216**    0.191**
Week 0.238***  0.235*    
Trap (position*wood)  0.666***      
Position*week  0.030*      

Effects of vegetation at the trap

At Copmanthorpe Wood (Table 3), the only model that significantly predicted abundance was for the Ephialtini. In analysis of species richness, significant models were found for the Pimplinae, Ephialtini and Poemeniinae. For diversity (Simpson's index), significant models were found for all taxa combined, Pimplinae, Pimplini and Ephialtini. The best overall predictor of parasitoid catch at Copmanthorpe Wood was plant height diversity (Table 3), although the effect of this was taxon specific.

Table 3.  Results of stepwise, backward regression for Copmanthorpe Wood. Only those vegetation variables for which significant results were obtained are illustrated. The values of the standardised coefficient (β) are given with the significance of the variables in the final model.
Response variableTaxaHabitat variables
Plant height diversityGround species richnessBroadleaf contentTree/shrub species richnessCanopy coverTree/shrub density
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05

Log10 (Abundance + 1)AllNSNSNSNSNSNS
DiplazontinaeNSNSNSNSNSNS
PimplinaeNSNSNSNSNSNS
PimpliniNSNSNSNSNSNS
Ephialtini0.674**–0.773**NSNS–0.551*NS
PoemeniinaeNSNSNSNSNSNS
DiacritinaeNSNSNSNSNSNS
RichnessAllNSNSNSNSNSNS
DiplazontinaeNSNSNSNSNSNS
PimplinaeNSNS0.512*NSNSNS
PimpliniNSNSNSNSNSNS
Ephialtini0.677**–0.731**NSNS–0.549*NS
Poemeniinae–0.794**NSNSNSNS–0.686*
Simpson's indexAllNSNS–0.540*NSNSNS
DiplazontinaeNSNSNSNSNSNS
PimplinaeNSNS–0.708**–0.616**NSNS
PimpliniNSNSNSNSNS0.507*
Ephialtini0.530*−0.535*NS–0.409*NSNS

As at Copmanthorpe Wood, very few significant correlations were found between trap vegetation data and parasitoid data at New Covert (Table 4). In the regression analysis (Table 3) of abundance, significant models were found for the Pimplini, Poemeniinae and Diacritinae. For richness, the only significant model was for the Poemeniinae. For diversity, significant models were found for Diplazontinae and Pimplinae. The best overall predictor of parasitoid catch at New Covert was tree/shrub density, which was always positively related to abundance, richness or diversity (Table 4).

Table 4.  Results of stepwise, backward regression for New Covert. Only those vegetation variables for which significant results were obtained are illustrated. The values of the standardised coefficient (β) are given with the significance of the variables in the final model.
Response variableTaxaHabitat variables
Tree/shrub densityTree/shrub species richnessGround species richnessGround coverCanopy cover
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05

Log10 (Abundance + 1)AllNSNSNSNSNS
DiplazontinaeNSNSNSNSNS
PimplinaeNSNSNSNSNS
Pimplini1.470**–1.180*1.217**–0.674*–0.717*
EphialtiniNSNSNSNSNS
Poemeniinae0.761**NSNSNSNS
DiacritinaeNS0.570*NSNSNS
RichnessAllNSNSNSNSNS
DiplazontinaeNSNSNSNSNS
PimplinaeNSNSNSNSNS
PimpliniNSNSNSNSNS
EphialtiniNSNSNSNSNS
Poemeniinae0.768**NSNSNSNS
Simpson's indexAllNSNSNSNSNS
Diplazontinae1.127**–0.751*NSNSNS
PimplinaeNSNS–0.576*NSNS
PimpliniNSNSNSNSNS
EphialtiniNSNSNSNSNS

Effects of trap position on assemblage composition

The location of a trap significantly affected parasitoid composition in all taxa at Copmanthorpe Wood (Table 5). Post-hoc tests revealed that all taxa were more similar in peripheral trap pairs than core traps pairs when using Sørenson's abundance index and the Morisita-Horn index. However, for the other indices, this trend was only significant for the pimplines. Trap location had no significant effect on assemblage similarity at New Covert (Table 5).

Table 5.  Results of one-way anova on similarity indices calculated for each combination of traps in a woodland. Pairs categorised as peripheral & peripheral, core & core, and peripheral & core.
IndicesCopmanthorpe Wood (F2,117)New Covert (F2, 88)
AllDiplazontinaePimplinaeAllDiplazontinaePimplinae
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05

Jaccard's8.000**8.851***3.958*0.3071.4360.608
Sørenson's8.270***9.492***4.336*0.2631.5540.673
Sørenson's abundance7.163**31.271***10.061***1.0450.2140.147
Morisita-Horn14.792***68.618***23.409***0.5940.5000.443

A Mantel test was used to test for association between the similarity between trap pairs and the distance between traps (Table 6). Traps at Copmanthorpe Wood were more dissimilar with increasing distance than at New Covert. At Copmanthorpe Wood, using the Jaccard index significant associations were found for all taxa combined and for the Diplazontinae but not the Pimplinae. Using the Morisita-Horn index, significant results were found for all taxa combined, the Diplazontinae and Pimplinae. At New Covert, the only significant results were for all taxa combined and the Jaccard index, and the Diplazontinae and Morisita-Horn index.

Table 6.  Results of Mantel test with r values illustrated. Similarity indices used in test as 1-S to give dissimilarity scores. Positive r values indicate increasing dissimilarity of trap fauna with distance.
IndicesCopmanthorpe WoodNew Covert
AllDiplazontinaePimplinaeAllDiplazontinaePimplinae
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05

Jaccard's0.312*0.362**0.1480.253*0.1320.140
Morisita-Horn0.542***0.463***0.507***0.1370.233*0.102

DCA was carried out on all taxa combined and for the Diplazontinae and Pimplinae at each site separately. For all taxa combined, there was a significant difference between axis one scores for peripheral and core traps at both Copmanthorpe Wood (t-test: t14 = –5.514, P < 0.001) and New Covert (t12 = –3.188, P < 0.001). For the Diplazontinae, there was a significant difference between axis one scores for peripheral and core traps at Copmanthorpe Wood (t13= 6.239, P < 0.001) but not New Covert. For Copmanthorpe Wood, peripheral trap 7 was removed from the analysis as no Diplazontinae were caught in this trap. For New Covert, peripheral trap 6 was removed as it only contained a single species not found anywhere else, which skewed the DCA plot. For the Pimplinae, there was a significant difference between the axis one scores for peripheral and core traps at Copmanthorpe Wood (t14 = −4.781, P < 0.001) but not New Covert.

Measured habitat variables were correlated against the first two DCA axes. Only axis one showed any significant correlations (Table 7). At Copmanthorpe Wood, for all taxa combined and for the Pimplinae, traps with a high score for axis one, core traps, have high ground cover, high tree/shrub species richness and high tree/shrub density. Tree/shrub density and ground cover were the vegetation variables most strongly associated with core traps in a vegetation principal components analysis (PCA) at Copmanthorpe Wood (Fraser, 2005). Traps with a low score on axis one for all taxa combined and the Pimplinae, peripheral traps, have a high broadleaf content and plant height diversity. These vegetation variables were the variables most associated with peripheral traps in a vegetation PCA for Copmanthorpe Wood (Fraser, 2005). For the Diplazontinae at Copmanthorpe Wood, traps with a high axis one score, peripheral traps, have high plant architectural diversity. Traps with a low axis one score, core traps, have high ground cover and tree/shrub species richness. At New Covert, the only significant correlation was for the Pimplinae with a high score on axis one being correlated with high tree/shrub species richness.

Table 7.  Significant correlations between measured habitat variables and DCA axis one.
HabitatDCA 1
Copmanthorpe WoodNew Covert
AllDiplazontinaePimplinaeAllDiplazontinaePimplinae
  • ***

    P < 0.001,

  • **

    P < 0.01,

  • *

    P < 0.05

Ground cover0.766**–0.523*0.794***   
Tree/shrub species richness0.611*–0.581*0.655**  –0.538*
Broadleaf content–0.722** –0.786***   
Tree/shrub density0.660** 0.713**   
Plant height diversity–0.623* –0.574*   
Plant architectural diversity 0.588*    

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

The aim of this study was to provide recommendations on how best to sample parasitoid Hymenoptera using Malaise trapping. In addition to the longer-term goal of basic inventorying of species’ distributions, Malaise trapping is a potentially useful tool to achieve two short-term goals in parasitoid conservation: (i) to understand the relationship between habitat characteristics and parasitoid abundance and diversity, and (ii) to develop monitoring programmes to assess better the conservation status of this group. We wished to understand the consequences of different levels of trap replication within a site, as well as the effects of sample duration and location on our knowledge of the parasitoid assemblage.

Trap number and species richness

The fact that the species accumulation curves do not approach an asymptote at either site, nor for diplazontines or pimplines, suggests that short-term studies of Malaise trapping will fail to produce a complete species list of parasitoid Hymenoptera. Such findings have been replicated previously for parasitoids at a regional scale (e.g. Sääksjärvi et al., 2004; Fraser et al., 2007), but we find that it also applies at a local scale, even when up to 16 traps are used. Previous researchers have also showed that using alternative collecting methods, such as sweeping or yellow pans, can be an effective way of compiling a more complete species list for a site (Noyes, 1989a, Wells & Decker, 2006).

While Malaise trapping, using only a few traps at a single site over a short timescale, will provide an incomplete species list, our results suggest that the information provided can nonetheless be useful for long-term monitoring. Two traps in 2003 in the same woods, while only capturing about half as many species as the more intensive trapping in 2004, nonetheless did capture species in proportion to their abundance in 2004, suggesting that the most abundant species will generally be well sampled by less intensive trapping, and thus could be useful species to monitor in a long-term but less-intensive study. It is also likely that the ‘singleton’ species, which comprise the majority of the species collected here, will eventually be sampled in such a long-term study as long as the number of trap hours is large over the length of the entire study.

The status of such ‘singletons’ is open to debate. They could be species that are ‘resident’, in the sense that they find hosts or mates within the habitat (see Shaw, 2006a). Alternatively, they could be ‘tourist’ species, which are just moving between oviposition or mating sites and happen to be trapped. Malaise traps, in common with most other trapping methods, cannot distinguish between these two categories of individuals, and this has been one of the arguments in favour of direct rearing methods (e.g. Morris et al., 2004). However, direct rearing is not always practical, provides only a very narrow view of the fauna present, and cannot include species that use the habitat for important activities other than oviposition (see Shaw, 2006a). The fact that Malaise trap samples are often very different between nearby sites, especially in the rarer species, and that these differences are often linked to the local vegetation (Sääksjärvi et al., 2004, 2006; Shaw, 2006a; Fraser et al., 2007), suggests that many of these singletons are resident species in the above sense, but simply not abundant or not efficiently trapped, perhaps because of different flight activity.

A further outcome of our intensive sampling within individual sites was the extent to which individual woods can harbour a diversity of parasitoid species. In our 2003 sampling of 15 woods with two traps per wood, we trapped 60 species out of the 165 known in these taxa in the UK (36%), a relatively high proportion (Fraser et al., 2007), with a maximum richness of 31 species per wood. Here, we have shown that within-wood richness may reach comparable levels, with up to 46 species per wood (28% of UK species) sampled in 4 weeks, and almost certainly several others not recorded. Extrapolating this proportion across the 6000 species of UK parasitoid Hymenoptera (> 1680 species) suggests that they may comprise a very high proportion of local biodiversity, and therefore a rewarding group on which to monitor how environmental changes affect biodiversity at key sites and more widely.

Trap position

If only a few Malaise traps can provide useful information about parasitoid assemblages, where should they be placed? In contrast to Fraser et al. (2007) and numerous other studies (see above references), which have addressed the vegetation differences between whole sites, this study showed relatively few associations between the vegetation local to a trap and the abundance and richness of parasitoids sampled. Furthermore, the relationships were site and taxon specific. Perhaps the lack of consistent relationships is not surprising given that all the species sampled are winged, and hence are probably relatively mobile (see Jones et al., 1996). On the other hand, our results did show that the parasitoids sampled differed more with increasing distance between traps, and, for certain taxa at least, between core and edge locations. This suggests that researchers wanting to compile a more complete species list for a site should space their traps widely apart and should site traps both close to the habitat edge and the habitat centre.

The occurrence of edge effects, in which communities change in composition close to the edge of habitat patches, have been widely reported in invertebrates, and have generally shown an increase in species richness near the edge (Buse & Good, 1993; Axmacher et al., 2004) or no effect on richness (Davies & Margules, 1998; Taboada et al., 2004). The only study on parasitoids, known to us, that addresses edge effects is that of Noyes (1989b), which showed that Parasitica diversity in Sulawesi forest was higher in the interior (see Ozanne et al., 1997, for a similar trend in forest canopy arthropods). Here, we have shown no edge effect with respect to overall species richness or abundance, but we have shown changes in community composition that are correlated with changes in vegetation structure. In addition, we have shown that one taxon appears to prefer edge locations to core locations. The widespread presence of edge effects that increase species richness is one motivation behind the common forestry practice of providing open rides and glades. The existing data suggest that this may not enhance the local diversity of parasitoids, although it is likely to benefit particular taxonomic groups. Because our edge traps were all a standard distance from the woodland edge (for comparison with the 2003 data and to decrease the data variance with our relatively low replication), it is possible that we have failed to capture edge effects that occur closer to the woodland boundary.

Sample duration

A further issue concerning the use of Malaise traps is the sampling duration and season. We based our collection dates on the balance between the increasing impracticality of sorting and identifying many samples, and the need to sample as much of the community as possible. Previous collections in 2003 showed that July and August were the peak months in terms of numbers of insects (Fraser et al., 2007). Our results here show, as previously, that different sample periods (weeks in 2003, fortnights in 2004) within our collection dates differed significantly in parasitoid abundance and richness. Two contributing factors are likely to be weather variation, which affects parasitoid behaviour such as flight activity (Weisser & Hassell, 1997), and seasonality, which determines when species are adults (Gaasch et al., 1998). The fact that both abundance and richness were affected suggests that short sample periods are likely to produce a biased view of parasitoid assemblages. This could be problematic if the study is not long term or if sampling is irregular. This problem could be even more exacerbated in the tropics where insect activity may be expected year round with different species displaying different seasonal peaks.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

In conclusion, our results suggest the following recommendations for sampling and monitoring the parasitoid Hymenoptera community within sites using Malaise traps: (i) that low trap replication can provide useful information on common species but is likely to considerably underestimate the total species present unless it is supported by high temporal replication; (ii) that short sample duration is likely to produce a biased picture of the community, and therefore the longer traps are open, the better; and (iii) that within a habitat, traps will sample more of the community present if they are widely spaced and cover both edge and core habitat. Our use of pimplines and diplazontines as focal taxa has proved informative both on a local (this paper) and regional scale (Fraser et al., 2007), and we believe that they would make excellent subjects for future conservation monitoring schemes.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References

We are grateful to M. Shaw (Pimplinae, Poemeniinae and Diacritinae), G. Rotheray (Diplazontinae) and E. Diller (Diplazontinae) for help with species identification, and H. Edwards and R. Shortridge for assistance with fieldwork. We thank the many landowners for permission to establish traps in their woodlands. This work was funded by a Natural Environment Research Council studentship to S.E.M. Fraser.

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  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgements
  9. References
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