Complex-to-predict generational shift between nested and clustered organization of individual prey networks in digger wasps

Abstract

Although diet has traditionally been considered to be a property of the species or populations as a whole, there is nowadays extensive knowledge that individual specialization is widespread among animal populations. Nevertheless, the factors determining the shape of interactions within food webs remain largely undiscovered, especially in predatory insects. We used an aggregation of the digger wasp Bembix merceti to 1) analyse patterns of individual prey use across three flying seasons in a network-based context; and 2) test the effect of four potential factors that might explain network topologies (wasp mass, nest spatial distribution, simultaneous nest-provisioning, prey availability). Inter-individual diet variation was found in all three years, under different predator-prey network topologies: Individuals arranged in dietary clusters and displayed a checkerboard pattern in 2009, but showed nestedness in 2008 and 2010. Network topologies were not fully explained by the tested factors. Larger females consumed a higher proportion of the total number of prey species captured by the population as a whole, in such a way that nested patterns may arise from mass-dependent prey spectrum width. Conversely, individuals with similar body mass didn't form clusters. Nested patterns seemed to be associated with a greater availability of the main prey species (a proxy for reduced intra-specific competition). Thus, according with theory, clusters seemed to appear when competition increased. On the other hand, the nests of the individuals belonging to a given cluster were not more closely located, and neither did individuals within a cluster provision their nests simultaneously. Thus, a female-female copying behaviour during foraging was unlikely. In conclusion, wasp populations can maintain a considerable individual variation across years under different food web organizations. The tested factors only partially accounted for the shift in network properties, and new analyses should be carried out to elucidate how diet network topologies arise in wasp populations.

Figure 1. Schematic representation of alternative ways in which specialized individuals can subdivide the population diet niche.

The upper curve represents the population diet niche, and the smaller curves represent individual niches. (A) Individuals have different niches, one within each other in a nested pattern. (B) Individuals are so highly specialized that neither nestedness nor clustering is possible (overdispersion). (C) Individuals group in different clusters. Modified from Araújo et al. .

Figure 2. Graphic representation of the females' dietary distribution, performed with Pajek.

(A) For the experimental female population of 2009. Three clusters (superimposed ellipses) appear, on the basis of similar or dissimilar captures among the individuals. (B) For a hypothetical population of the same sample size in which individuals arrange randomly.

Figure 3. Pairs of prey species never co-occurring together, or co-occurring at least once.

Black cells: pairs of prey species that never co-occurred; white cells: pairs of prey species that co-occurred at least once within the pool of a given female wasp. SpSc =  Sphaerophoria scripta; Odo =  Odontomyia sp.; SysG =  Systoechus gradatus; AmVa =  Amictus variegatus; UsAe =  Usia aenea; HeVe =  Hemipenthes velutinus; StLu =  Stomorhina lunata; Pel =  Peleteria sp.; ViHo =  Villa hottentotta; Mi(II) =  Miltogramminae sp. 2; UTa(I) =  Tachinidae sp. 1; Mi(I) =  Miltogramminae sp. 1; ChAr =  Chrysotoxum arcuatum; UTa(II) =  Tachinidae sp. 2; BoCr =  Bombylisoma croaticum; EupC =  Eupeodes corollae.