DOI: 10.5061/dryad.3r2280gm5
title: An omnivore vigor hypothesis? Nutrient availability strengthens herbivore suppression by omnivores across 48 field sites

description: Nutrients regulate herbivore growth from the ‘bottom-up’ via improved
 plant vigor and food quality. Nitrogen also affects ‘top-down’ control of
 herbivores by moderating attraction of predators and the rates at which
 they consume herbivorous prey. Tri-trophic consequences of nitrogen
 availability are more challenging to predict among omnivorous natural
 enemies who feed on both plants and herbivores, limiting our ability to
 predict net outcomes of nutrient availability in food webs. In a two-year
 field survey of insects on zucchini host plants at 48 sites, I predicted
 that both herbivores and foliar-feeding omnivores would increase with
 nutrient availability, while predators would not. My results revealed
 positive relationships between omnivores and foliar nitrogen
 concentrations, while predators had neutral responses to foliar N.
 Surprisingly, herbivores declined with increasing foliar N across the
 field sites. Greenhouse experiments reinforced these patterns, as
 herbivore growth inversely correlated with soil N concentrations in
 communities that included foliar-feeding omnivores. Conversely, herbivore
 growth was uncorrelated with soil N on plants with generalist predators,
 nor on predator-free plants. These results suggest that omnivores mount
 strong and consistent responses to nitrogen in plant tissues in a variety
 of ecological contexts. In environments where omnivorous arthropods can
 thrive, their recruitment to nitrogen-rich plants may increase predation
 and thereby counterbalance and stabilize ‘bottom-up’ increases in
 herbivore performance supported by enhanced foliar nutrition.
description: <em>Field survey </em> To examine
 how natural populations of herbivores, omnivores and generalist predators
 respond to plant quality along a nutrient gradient, I performed
 observational field surveys. Between 2020 and 2021, my students and I
 sampled arthropods, soils and foliar tissues at 56 farm fields that varied
 in fertility management practices and formed a gradient of nutrient
 availability across Georgia, South Carolina, and North Carolina, USA
 (Appendix Fig. S1, Appendix Tables 1,2). The number of sites surveyed in
 2020 (18) were considerably fewer than those sampled in 2021 (38) due to
 restricted mobility during the Covid-19 pandemic. At
 each site, we randomly selected 10 unique zucchini plants along a transect
 spanning each field and visually surveyed arthropods on six haphazardly
 selected leaves (two new leaves, two middle-aged leaves, and two old
 leaves), stems, and in all open flowers. Herbivores and natural enemies
 were counted and identified on-site with the finest resolution possible.
 Most common taxa (noted above in the study system) were identified to
 species or genus, while some taxa are more challenging to identify
 on-site, and were identified at the family level, or order (spiders).
 Fewer than 1% of the arthropods we observed were impossible to confidently
 assign to functional trophic groups (decomposers, herbivores,
 foliar-feeding omnivores, generalist predators), and these were excluded
 from analyses.  We then collected 4.5 L soil at five
 locations along the transect from the 0–15cm profile, homogenized it in a
 bucket, collected a subsample for chemical/physical analyses, and saved
 the remaining soil for the greenhouse experiment (described below). We
 collected foliar tissue from five plants per field from the 3rd leaf below
 the apical meristem. Foliar tissue samples were collected at 48 of the 56
 sites visited; some farmers preferred that I not remove plant tissue. Soil
 and foliar tissue samples were sent to the Agricultural and Environmental
 Service Laboratory at the University of Georgia to determine percent total
 nitrogen concentrations (organic + inorganic N) with an Elementar Vario
 Max Total Combustion Analyzer (Langenselbold, Germany).
 <em>Greenhouse experiment</em> To
 determine how nitrogen availability influences suppression of herbivores
 by omnivores and generalist predators, I performed a greenhouse predation
 experiment. From a randomly selected subset of 25 farms, I planted
 zucchini seeds in three pots of soil collected per site (for a total of 75
 pots) on 27 September 2021. The three pots from each site were placed in a
 single cage, and the 25 cages were randomized on the greenhouse bench.
 After four weeks of growth, I introduced 25 mixed-age cotton melon aphids
 (<em>A. gossypii</em>) to the 3rd leaf from the apical
 meristem and enclosed each plant in an individual cage. To reduce error
 from differential growth rates in mixed-age colonies, I returned after 24
 and 48 h to subsidize or reduce colonies on plants so that all plants
 contained 25 aphids before data collection began. It is difficult to
 introduce aphid colonies at uniform stages of development, and some
 introduced colonies inevitably include more late-instar individuals than
 others, and will therefore reproduce more rapidly regardless of treatment.
 Including this brief acclimation period where individuals are culled from
 colonies with faster initial growth rates helps to even the age structure
 before assays begin, which reduces this random source of error (Blubaugh
 et al. 2018, Blubaugh et al. 2021). While colonies were establishing and
 acclimating, I monitored baseline colony growth across the plants for 5
 days before introducing predators. Once aphid colonies
 were established (after 5 days), I initiated three predation treatments on
 three separate benches, each containing 25 plants grown in the farm soils
 from the survey, completely randomized in cages 12 inches apart. In my
 first treatment, I introduced two omnivorous minute pirate bugs per cage
 (<em>O. insidiosus</em>, Evergreen Growers Supply, Portland,
 Oregon, USA); in the second treatment, one convergent ladybeetle (a
 generalist predator) was introduced (<em>Hippodamia
 convergens</em> Guérin-Méneville, Carolina Biological, USA). Natural
 enemies were introduced at natural densities similar to those most
 commonly observed in surveys (1.85 <em>Orius</em>/plant, and
 1.25 ladybeetles/plant), and they were replaced if found dead in cages
 during daily inspections. In the last treatment, aphids grew on 22 plants
 (three of the 25 plants failed to germinate) in predator-free cages. I
 arranged each of the predation assays together in separate blocks because
 aphid growth rates can be affected by alarm pheromones emitted by adjacent
 colonies when exposed to natural enemies (Vandermoten et al. 2012).
 Therefore, to minimize error related to alarm pheromones and prioritize
 quantifying fertility-mediated effects for each predator, I spatially
 separated each of the predation assays (Appendix Fig. S4). I placed each
 predator treatment on the same bench because space constraints required
 that the 25 cages be immediately next to each other, potentially within
 range of detection of alarm pheromones coming from nearby predator
 treatments. I counted aphids on all plants and terminated the experiment
 96 h after introducing the natural enemies (as in Desneux and O’Neill
 2008), as some of the aphid colonies had grown large enough that host
 plants were beginning to die. <em>Statistical
 analyses</em> All analyses were performed in R
 version 3.6.0. To examine how nitrogen availability influences top-down
 and bottom-up forces shaping herbivore pressure in the field, I ran path
 analyses using the ‘piecewiseSEM’ package in R (Lefcheck, 2016). My
 hypothetical model included all possible links between foliar N and counts
 of omnivores, generalist predators, and herbivores. Each of the component
 generalized linear models (predicting counts of omnivores, generalist
 predators, and herbivores, respectively) were modeled with a Poisson
 distribution and had normally distributed residuals. Since relatively few
 repeat visits to farms were made between 2020 and 2021, and because all
 farmers rotated their crops to different locations between years, I
 considered each visit to a unique field to be an independent replicate in
 the model and therefore included no random effects. I used nitrogen
 concentrations in foliar tissue as my predictor variable for host plant
 quality in the field survey (rather than soil nitrogen) because it is a
 more reliable indicator of plant quality during the brief visit.
 Fertilizer application timing, planting dates, and mineralization rates
 varied considerably across the farms we visited, leading to wide variation
 in available soil nitrogen that did not correlate with nitrogen available
 in plant tissue to herbivores and omnivores at the time of the visit. I
 evaluated the overall fit of my path model with d-separation tests on
 Fisher’s C statistic and AIC (Shipley, 2013). I gradually eliminated
 non-significant predictors in the series of path models until I minimized
 AIC, indicating the best-fit series of interactive models.
 In my greenhouse experiment, I performed simple linear
 regressions on aphid growth in each of my predator treatments with soil N
 concentration as the predictor variable. Unfortunately, technical problems
 with the analysis of the greenhouse plant tissue samples meant that I
 could not include foliar N in the model, as I did in the field surveys,
 and had to instead use less-reliable and more-widely varying estimates of
 nitrogen in the soil (Ransom et al. 2020). However, because planting dates
 and data collection were uniform across the samples in the controlled
 greenhouse experiment, soil N should reasonably predict nitrogen available
 to the herbivores we introduced. Percent soil N and dry plant biomass
 positively correlated (Appendix Fig. S2), indicating that plant growth
 (i.e. plant vigor) is indeed linked with soil nutrient
 availability. My response variable was the relative
 proportionate growth rate of aphid colonies 96 h after predators were
 introduced (i.e. I divided the difference in aphid counts after 96 h by
 the initial number of aphids in each cage when predators were introduced;
 Leather and Dixon 1984). Greenhouse space limitations required spatial
 segregation of my predator treatments and precluded explicit tests of
 interactions between soil N and predator feeding guilds (compromising
 independence between predator treatments), so I analyzed each of the three
 predator treatments separately. Normality assumptions and homogeneity of
 variance assumptions were checked by examining histograms and residual
 plots. I also analyzed aphid counts for all plants across the experiments
 together during the 5-day baseline period of colony establishment, prior
 to predator introduction, with Poisson regression. Percent soil N was a
 predictor variable, and aphid counts five days after aphid introduction as
 the response variable, with farm identification nested in block as a
 random effect.
description: Microsoft Excel, program R