| Literature DB >> 35447809 |
Freerk Molleman1, Urszula Walczak1, Iwona Melosik2, Edward Baraniak1, Łukasz Piosik3, Andreas Prinzing4.
Abstract
Communities of herbivorous insects on individual host trees may be driven by processes ranging from ongoing development via recent microevolution to ancient phylogeny, but the relative importance of these processes and whether they operate via trophic interactions or herbivore movement remains unknown. We determined the leaf phenology, trunk diameter, genotype, and neighbourhood of sessile oak trees (Quercus petraea), and sampled their caterpillar communities. We found that leaf development across a time period of days related to free-living caterpillars, which disappeared with leaf age. Tree growth across decades is related to increased parasitism rate and diversity of herbivores. The microevolution of oak trees across millennia is related to the abundance of leaf-mining casebearers, which is higher on more homozygous oaks. However, oak genome size was not important for any guild. In contrast to most previous studies, the phylogenetic distance of oaks from their neighbours measured in millions of years was associated with higher abundances of entire caterpillar guilds. Furthermore, on trees surrounded by only distantly related tree species, parasitism tended to be lower. Lower parasitism, in turn, was associated with higher abundances of codominant caterpillar species. Neighbourhoods and traits of trees were also related to community composition and diversity, but not to the average wingspans or specialization of species, consistent with the assembly of herbivore communities being driven by leaf traits and parasitism pressure on trees rather than by insect movement among trees. However, movement in rarer species may be responsible for concentration effects in more phylogenetically distant neighbourhoods. Overall, we suggest that the assembly of insects on a tree is mostly driven by trophic interactions controlled by a mosaic of processes playing out over very different time scales. Comparisons with the literature further suggest that, for oak trees, the consequences of growing amongst distantly related tree species may depend on factors such as geographic region and tree age.Entities:
Keywords: budburst phenology; concentration effect; dispersal limitation; functional traits; genome size; leaf miner; phylogenetic isolation; population genetics; shelter building
Year: 2022 PMID: 35447809 PMCID: PMC9029432 DOI: 10.3390/insects13040367
Source DB: PubMed Journal: Insects ISSN: 2075-4450 Impact factor: 3.139
Figure 1Mechanisms through which processes at different time scales could affect caterpillar communities on individual trees as explained in the Introduction. The importance of particular mechanisms could vary between guilds. Note that both red and green arrows will affect the abundance and diversity of insects. Green arrows (i.e. leaf quality and parasitism) will in addition favour particular species and thereby affect community composition. Red arrows (movement) will either not affect community composition if dispersal is entirely random across taxa, or increase the proportion of good dispersers. The blue arrow depicts interaction terms between phylogenetic distance of the neighbourhood and tree traits.
Summary of results for caterpillar abundances, parasitism rate, Simpson diversity, and functional traits. The models used data from 25 trees, except for Simpson diversity and insect traits, where two trees were excluded due to a lack of reared adults, and for Mantel tests, one tree was excluded due to a lack of genetic data. The number of models for which each predictor was selected out of the ten best-fitting models is given for each dependent variable. The direction of the effect is indicated with a plus or minus sign if it is consistent among models and not part of an interaction term. Predictors that were included in the top model are surrounded by black lines, with. p < 0.1, * p < 0.05, ** p < 0.01, and *** p < 0.001. The delta range denotes the difference in AICc between the top model and the tenth best-fitting model (Supplementary File S2). p-values from Mantel tests between genetic divergence and similarity in caterpillar abundance are given to the right, where ‘Raw’ is based on the raw abundance data, and ‘Residuals’ on the residuals of top models. n = the total number of caterpillars or moths, Cluster = locality, Day = sampling day, BB = date of 50% budburst, DBH = trunk diameter at breast height, Par = parasitism rate, Fcyt = genome size (2C nuclear DNA content (pg)), IH = stand-ardized individual heterozygosity based on the mean observed heterozygosity, PI = phylogenetic isolation (ma), sdPI = phylogenetic heterogeneity of the neighbourhood expressed as the standard deviation of phylogenetic isolation, P. = proportion, Spec. = specialists.
| Number of Linear Models out of Top 10 with: | Mantel Tests | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Main Effect: | Interactions with PI | Range | ||||||||||||||||||
| Dependent Variable | n | Cluster | Day | BB | DBH | Par | IH | Fcyt | PI | sdPI | Day | BB | Diam | Par | IH | Fcyt | sdPI | Delta | Raw | Residuals |
|
| 612 | 1 | 3− | 0 | 1− | 4 | 0 | 1+ | 10+ ** | 1− | 0 | 0 | 0 | 2− | 0 | 0 | 0 | 2.8 | 0.400 | 0.541 |
|
| 214 | 3 | 2− | 0 | 0 | 9− | 8− | 0 | 10 * | 1− | 0 | 0 | 0 | 8− | 5+ | 0 | 0 | 3.3 | 0.153 | 0.094 |
|
| 48 | 0 | 1− | 3− | 1− | 10− *** | 3− | 1− | 4 | 0 | 0 | 0 | 0 | 0 | 2+ | 0 | 0 | 2.7 | 0.212 | 0.230 |
|
| 37 | 10 | 1− | 5+ | 1− | 7− *** | 2− | 2− | 1+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.3 | 0.044 * | 0.152 |
|
| 261 | 1 | 2− | 1+ | 2+ | 1− | 1+ | 1+ | 10+ ** | 1− | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.9 | 0.436 | 0.614 |
|
| 35 | 0 | 1+ | 3+ | 1− | 5− | 0 | 0 | 3+ | 1+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.7 | 0.130 | 0.191 |
|
| 136 | 1 | 8− | 1− | 1+ | 1− | 2+ | 1+ | 9+ * | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3.1 | 0.469 | 0.462 |
| Geometrids | 57 | 3 | 3− | 1− | 4− | 4− * | 0 | 0 | 0 | 8+ * | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1.7 | 0.278 | 0.379 |
|
| 126 | 2 | 1+ | 2− | 6+ | 1+ | 1− | 2− | 9+ * | 0 | 0 | 0 | 0 | 0 | 1+ | 2.6 | 0.342 | 0.182 | ||
|
| 214 | 9 | 2+ | 1+ | 8 ** | 2+ | 9− * | 2− | 9 *** | 4− | 2− | 0 | 8− *** | 0 | 1+ | 2+ | 0 | 3.3 | 0.38 | 0.767 |
| Wingspan | 214 | 5 | 3− | 1+ | 1− | 1− | 1+ | 0 | 1+ | 1+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.4 | 0.377 | 0.411 |
| P. Specialists | 214 | 1 | 1− | 1− | 1− | 4− | 2+ | 1− | 0 | 1+ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.1 | 0.196 | 0.271 |
| P. Particular Spec. | 214 | 4 | 2− | 0 | 2− | 1− | 1− | 2− | 1− | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2.4 | 0.619 | 0.529 |
Figure 2Relationships between caterpillar abundance and tree characteristics per guild weighted by leaf mass. The characteristics of focal trees are ordered by the time scale at which each process plays out. Data derived from larger samples are depicted with larger circles. Relationships that were significant in OLS regressions are indicated with (*) p < 0.1, * p < 0.05, ** p < 0.01 and grey bands depict standard error. Spearman correlation coefficients are given in Supplementary File S2, Table S2.1, and results of multiple regression analyses are summarized in Table 1.
Figure 3Relationships between the abundance of the three most common caterpillar species and overall parasitism on a tree., with (a) Colephora flavipennella OLS regression: R2 = 49%, p < 0.001, (b) Colephora lutipennella R2 = 16%, p = 0.051, (c) Carcina quercana R2 = 11%, p = 0.103. In multiple regression analyses, the abundance of both Coleophora species was significantly predicted by parasitism, and for C. quercana, parasitism was selected into the top model but was marginally significant (Table 1, Supplementary File S2). Since a given species may have been absent while parasitism rates were calculated for other species, there are points of zero abundance in these graphs.
Figure 4Relationships between caterpillar parasitism rate and trunk diameter, and phylogenetic heterogeneity of the neighbourhood (standard deviation of phylogenetic isolation). PI = phylogenetic isolation, n = sample size. In multiple regression analyses, trunk diameter and phylogenetic heterogeneity of the neighbourhood were included in the top model with trunk diameter being significant and phylogenetic heterogeneity marginally significant (Table 1, Supplementary File S2).
Figure 5Simpson diversity of caterpillar communities based on larvae reared to adults and casebearer cases from small (DBH < 50 cm) and large (>50 cm) individual trees, illustrating the model with the lowest AICc value (Table 1). OLS Regression lines illustrate the interactive effects of phylogenetic isolation and tree size and use the number of identified moths (n moths) as weight. Both when using a large-small dichotomy and when using all continuous predictors, there is a significant interaction between diameter and phylogenetic isolation (Table 1). The additional effect of heterozygosity (IH, Table 1) is only significant if the interaction between DBH and phylogenetic isolation is accounted for. This probably reflects that for larger trees, points above the regression line tend to have lower heterozygosity than those below it. Note that the range of phylogenetic isolation is narrower for larger trees.
Results of PERMANOVA analysis of caterpillar communities on individual oak trees. SS = sum of squares, MS = mean squares, Day = sampling day, BB= date of 50% budburst, DBH = trunk diameter at breast height, Par = proportion of caterpillars parasitized, IH = standardized individual heterozygosity based on the mean observed heterozygosity, Fcyt = 2C nuclear DNA content (pg)), PI = phylogenetic isolation (ma), sdPI = phylogenetic heterogeneity (standard deviation of phylogenetic isolation). * p < 0.05, ** p < 0.01.
| Day | BB | Diam | Par | IH | Fcyt | PI | sdPI | Residuals | Total | |
|---|---|---|---|---|---|---|---|---|---|---|
| Df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 16 | 24 |
| SS | 0.51 | 0.027 | 0.13 | 0.217 | 0.352 | 0.098 | 0.276 | 0.26 | 1.461 | 3.33 |
| MS | 0.51 | 0.027 | 0.129 | 0.217 | 0.352 | 0.098 | 0.276 | 0.26 | 0.091 | 1 |
| Pseudo-F | 5.584 | 0.292 | 1.418 | 2.374 | 3.856 | 1.073 | 3.026 | 2.844 | 0.439 | |
| R2 | 0.15 | 0.01 | 0.04 | 0.07 | 0.11 | 0.03 | 0.08 | 0.08 | ||
|
| 0.006 ** | 0.886 | 0.210 | 0.077 | 0.017 * | 0.35 | 0.039 * | 0.047 * |