Interactive effects of pests increase seed yield

Vesna Gagic, Laura G.A. Riggi, Barbara Ekbom, Gerard Malsher, Adrien A.

Rusch, Riccardo Bommarco

► To cite this version:

Vesna Gagic, Laura G.A. Riggi, Barbara Ekbom, Gerard Malsher, Adrien A. Rusch, et al. In-
teractive effects of pests increase seed yield. Ecology and Evolution, 2016, 6 (7), pp.2149-2157.
10.1002/ece3.2003 . hal-02633128

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# Interactive effects of pests increase seed yield

Vesna Gagic<fnref n="1" />, Laura GA Riggi<fnref n="1" />, Barbara Ekbom<fnref n="1" />, Gerard Malsher<fnref n="1" />, Adrien Rusch<fnref n="2" /> & Riccardo Bommarco<fnref n="1" />

**Keywords**

Herbivore, oilseed rape, plant compensation, plant damage, pollen beetle, weevils.

**Correspondence**

Vesna Gagic, CSIRO, GPO Box 2583, Brisbane, QLD 4001, Australia.
Tel: +61 73833 5923;
Fax: +61 7 3833 5505;
E-mail: vesna.gagic@csiro.au

**Funding Information**

Funding was provided by the Swedish research council FORMAS.

Received: 20 September 2015; Revised: 18 January 2016; Accepted: 23 January 2016

Ecology and Evolution 2016; 6(7): 2149-2157

doi: 10.1002/ece3.2003

**Abstract**

Loss in seed yield and therefore decrease in plant fitness due to simultaneous attacks by multiple herbivores is not necessarily additive, as demonstrated in evolutionary studies on wild plants. However, it is not clear how this transfers to crop plants that grow in very different conditions compared to wild plants. Nevertheless, loss in crop seed yield caused by any single pest is most often studied in isolation although crop plants are attacked by many pests that can cause substantial yield losses. This is especially important for crops able to compensate and even overcompensate for the damage. We investigated the interactive impacts on crop yield of four insect pests attacking different plant parts at different times during the cropping season. In 15 oilseed rape fields in Sweden, we estimated the damage caused by seed and stem weevils, pollen beetles, and pod midges. Pest pressure varied drastically among fields with very low correlation among pests, allowing us to explore interactive impacts on yield from attacks by multiple species. The plant damage caused by each pest species individually had, as expected, either no, or a negative impact on seed yield and the strongest negative effect was caused by pollen beetles. However, seed yield increased when plant damage caused by both seed and stem weevils was high, presumably due to the joint plant compensatory reaction to insect attack leading to overcompensation. Hence, attacks by several pests can change the impact on yield of individual pest species. Economic thresholds based on single species, on which pest management decisions currently rely, may therefore result in economically suboptimal choices being made and unnecessary excessive use of insecticides.

**Introduction**

Crop plants are attacked by many pests that affect plant survival, growth, and reproduction and as a result influence crop yield (Oerke 2006). Herbivory by an insect typically reduces plant performance (Bigger and Marvier 1998; Kolb et al. 2007). However, a plant is often attacked by several insect species and their combined attacks might nonadditively, that is, interactively, affect biomass and seed yield. The magnitude and frequency as well as the net effect of such interactive outcomes on crop plants are not well understood.

Both nonadditive and additive negative effects of multiple herbivorous insects on plant fitness have been reported. Nonadditive effects are generally negative and either greater (more negative) or lower (less negative) than expected when either of the insect species feeds alone (Strauss 1991; Karban and Strauss 1993; Wise and

Sacchi 1996; Hufbauer and Root 2002; Barber et al. 2012). This often occurs if one herbivore facilitates or negatively affects another herbivore species (Stephens et al. 2013). In a meta-analyses, Stephens et al. (2013) found that in one-quarter of cases the effect of plant enemies on plant performance was nonindependent and mostly led to a smaller reduction in plant performance than that predicted when each enemy feeds alone. Additive effects of insect attacks on wild plant fitness are also typically negative (Maron 1998; Puliafico et al. 2008; Irwin and Brody 2011; Stephens et al. 2013). However, the majority of these studies are evolutionary and have been conducted on wild plants contrasting pairwise with diffuse plant-herbivore coevolution, while current agroecological research is almost exclusively focused on individual pests. Little is known about interactive effects of insect pests on crop plant fitness and thereby on crop seed yield, although crops differ from wild plants in sev-

<footnote n="1">¹Department of Ecology, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden</footnote>

<footnote n="2">²INRA, ISVV, UMR1065 Santé et Agroécologie du Vignoble, F-33883 Villenave d'Ornon, France</footnote>
eral ways. Herbivores damage crops more than wild
plants, presumably due to genetic changes in plants and
herbivores following domestication (Morris et al. 2007).
Artificial selection for palatability for humans may make
crop plants more vulnerable to other herbivores, while
increased nitrogen input can make them more prone to
pest attack. On the other hand, plants coexist closely in
crop fields and their exposure to volatile organic com-
pounds from neighboring plants may ‘prime’ them to
respond more efficiently to herbivore attacks once they
themselves are attacked (Heil and Kost 2006). Addition-
ally, anthropogenic inputs of water and nutrients to the
crop can affect the ability of a plant to compensate for
damage by regrowth following herbivory (Levine and
Paige 2004; Wise and Abrahamson 2007). Given the
increasing evidence for nonadditive effects of multiple
herbivores on wild plants, it might be problematic to pre-
dict crop losses based on information on attacks of single
pest species. If interactive effects among insect pests are
common in crop fields, wrong pest management decisions
can be taken, as they are based on economic thresholds
that are almost entirely derived from studies of single, or
several closely related pest species expected to have similar
and additive effect.

Combined effects of multiple, distantly related insect
pests have mostly been investigated when there is facilita-
tion of one pest by another. For example, the economic
threshold for the seed weevil (Ceutorhynchus assimilis
Payk., Curculionidae, Coleoptera) in oilseed rape is lower
when the pod midge (Dasineura brassicae Winn.,
Cecidomyiidae, Diptera) is present. The midge uses the
seed weevil feeding punctures and larval exit holes to
infest the plant (Alford et al. 2003). Furthermore, Dangles
et al. (2009) found that herbivore insect diversity
increases potato yield loss, but the effect of insect density
and time of the attack was not tested. However, plants
with high levels of early herbivory can suffer less damage
by late herbivores due to changes in plant traits (Barber
et al. 2012). According to a recent meta-analysis, plant
performance should be independently reduced by natural
enemies sharing a host plant, except in cases where ene-
mies attack the same plant part concurrently (direct inter-
actions) or attack plant reproductive structures. In such
cases, multiple enemies should lead to a smaller reduction
in performance than that predicted from each enemy
alone (Stephens et al. 2013). Moreover, the net effect of
combined insect attack may vary depending on the dam-
age levels of each herbivore species (Lerin 1988; Pilson
1996) and depends on the plant's ability to compensate
for damages. Several instances of overcompensation for
pest-induced damages have been reported for pairwise
plant-insect interactions (Belsky 1986; Crawley 1987;
Owen 1980; Paige and Whitham 1987; Williams 2010),

but little is known about whether plants can overcompensate for damage caused by multiple herbivores.

Here, we used oilseed rape as a model system because
it is an important crop for proteins and oil and it has
high compensatory abilities for insect damage (Free and
Williams 1978, 1979; Williams and Free 1979). Neverthe-
less, yield losses of 70–80% have been recorded in oilseed
rape not treated with insecticides (Nilsson 1987; Hansen
2003). Together with the seed weevil and the pod midge,
the most common insect pests on winter oilseed rape in
northern Europe are the pollen beetle (Meligethes aeneus
F., Nitidulidae, Coleoptera) and the cabbage stem weevil
(C. pallidactylus Marsh., Curculionidae, Coleoptera).
These four species attack either different plant parts or
during different stages of the plant's development (Alford
et al. 2003). Pollen beetle infestation can result in blind
stalks that prevent pod development, while stem weevils
cause distortion of stem tissue and loss of plant vigor.
Pod midge and seed weevil infestations often result in
considerable seed loss due either to the direct effect of
larvae feeding on seeds, or due to the development of yel-
low pods that split open to release midge larvae, simulta-
neously dropping seeds. (Williams 2010). The magnitude
of the negative effects of these four pest species on crop
yield differs greatly, with pollen beetles being identified as
the major oilseed rape pests, while stem weevils rarely
cause economically significant losses (Alford et al. 2003).
Pest infestations can also trigger compensation in oilseed
rape. For example, bud abortion can lead to the produc-
tion of new racemes and buds, and seed loss can be com-
pensated by higher seed weight (Free and Williams 1978,
1979; Williams and Free 1979). Given the difference in
the magnitude of the negative pest effects on yield and in
the plant compensatory mechanisms, the net effect of
combined pest attack on seed yield is hard to predict.

We used fifteen oilseed rape fields to investigate how
plant damage caused by four insect pest species (brassica
pod midge, seed weevil, stem weevil, and pollen beetle) in
concert affect oilseed rape seed yield. We focused on the
interactive effects of plant damage caused by insects on
seed yield and tested the presence and direction of these
effects.

**Materials and Methods**

Study design

The study was carried out in 2013, in 15 conventionally
managed winter oilseed rape fields in the Swedish pro-
vince Västergötland. The land-use in the region is charac-
terized by arable land (19.42%), woodlands (20%) and
pastures/meadows (2.53%) (http://statistik.sjv.se/, data
from 2013), while the rest of the area is covered mainly
by built-up areas, lakes, and waterways. To ensure among-field differences in pest colonization and subsequent pest pressure, the fields were chosen along a gradient of agricultural intensity measured as percentage arable land in a circular landscape sector of 1.5 km diameter encompassing the field (Zaller et al. 2008a). Percentage arable land in the landscape sectors varied between 38% and 93.62%. Due to a wet autumn in 2012 and harsh winter conditions, the oilseed rape area in the landscape sectors had decreased on average by 25% in 2013 compared to 2012. This allowed us to conduct our study with unusually high pest pressures as the pests converged on the remaining fields. Insect pest abundances per plant exceeded the economic thresholds in many fields. Especially high were attacks by pollen beetles during the most susceptible green bud stage and by seed weevils (60% and 73% fields, respectively, exceeded the economic thresholds).

To avoid high multicollinearity in the data and ensure that the colonization of the fields by the four pests and the subsequent damage would not strongly covary, the landscape sectors were selected so that percentage oilseed rape, grassland and woodland area in the landscape sectors are not correlated. This is because the four investigated pest species respond differently to these landscape elements. Pollen beetle and stem weevil damages to oilseed rape have been shown to be negatively related to proportion oilseed rape and positively related to proportion woodlands at a 1.5 km landscape scale, although the response of pollen beetles was much stronger (Zaller et al. 2008a). Pod midge conversely does not seem to respond to either woodland or oilseed rape percentage at 1.5 km landscape scale (Zaller et al. 2008a). Grassland meanwhile can support high overwintering populations of pollen beetles, but also of the pests' natural enemies (Rusch et al. 2013). It can positively affect rates of parasitism in pollen beetles (Rusch et al. 2011) and activity-denisty and richness of generalist natural enemies (Purtauf et al. 2005). To verify our design we checked for multicollinearity in the data by studying the VIF (variance inflation factors) for all parameters included in the statistical models. There was no collinearity, as indicated by VIF-values lower than 1.5 in all cases (Zuur et al. 2009).

To ensure spatial, independence selected fields were at least 3 km apart. Within each field, we selected a 40 × 70 m unsprayed area located at the edge of the field. Observations were made along two transects parallel to the field edge, 3 and 30 m into the field. In each transect, we estimated insect damage and seed yield per plant, as well as plant density and weed cover per square meter at five sample points 10 m apart and a minimum of 10 m away from the sprayed area. The sampled field edge was next to a grassy strip (of minimum 2 m width) in all fields.

# Plant damage sampling

## Pollen beetles

Adult pollen beetles cause most damage to oilseed rape plants when they feed on pollen in the buds early in the season, affecting developing racemes and causing bud abortion (Alford et al. 2003). To assess pollen beetle damage, we calculated the percentage of podless stalks in relation to total number of pods on 10 randomly chosen plants per sampling point (100 plants in total per field) at GS (growth stages) 77–79 (70–100% pods having reached final size, cf. Lancashire et al. 1991). Since podless stalks can be caused by other factors, we correlated percent podless stalks with the mean pollen beetle density and found high correlation (Pearson's product-moment correlation = 0.35, *P* < 0.001). Pollen beetle density was estimated using data from visual counts of adults. Pollen beetle counts were conducted weekly on ten randomly chosen plants per sampling point, three times in total during the season from oilseed rape green bud stage until flowering.

## Stem weevils

Stem weevil larvae feed gregariously for 3–5 weeks and form extensive galleries in the oilseed rape stems that cause distortion of tissue and loss of plant vigor (Alford et al. 2003). To assess damage by stem weevil larvae, we dissected 10 randomly chosen plant stems per sampling point at GS 64-67 (oilseed rape flowering, Zaller et al. 2008b). We calculated the percentage of stem damage (including zeros) as the length of the damaged part (stem length exhibiting visible signs of weevil herbivory) divided by the total stem length. Additionally, we measured the diameter of the main stem of each sampled plant.

## Seed weevils

Seed weevil adults typically deposit one egg per pod in which the larva usually destroys an average of five seeds (Alford et al. 2003). To assess the level of seed weevil damage, 10 pods were randomly selected at each sampling point (GS 80-81, beginning of ripening) and the percentage of pods with emergence holes was used as a measure of seed weevil damage.

## Brassica pod midge

The brassica pod midge causes most damage to the plant when the larvae feed on the inner walls of the pods late in the season (Alford et al. 2003). To assess damage by brassica pod midge larvae (GS 77-79) we picked ten ran-
domly chosen plants per sampling point and estimated
the percentage of premature, yellow and split pods. (Zal-
ler et al. 2008b).

Seed yield

Three components of seed yield in oilseed rape were assessed: pod number per plant, seed number per pod, and seed weight. To measure total seed yield (total seed weight per plant) we calculated the number of healthy, fully developed pods per plant multiplied by the average number of seeds per pod and the average seed weight. Number of seeds per pod was counted on 20 pods randomly chosen from terminal raceme from five plants at each sampling plot. We measured seed weight per sampling point by selecting and weighing three subsamples of 100 seeds from randomly chosen pods. The farmers were interviewed and information about crop cultivar and management practices such as fertilization and yield was collected. To check how our estimation of seed yield (estimated per plant) correlated with the farmers' estimates of yield (per area), we multiplied our seed yield measurements with the estimates of plant numbers per square meter to get an area based measure (averaged per field). We found a high correlation (Pearson's product-moment correlation = 0.74, *P* = 0.01).

Statistical analyses

For the analyses of total seed yield (total seed weight per plant) and its individual components (1) number of healthy, fully developed pods; (2) average seed number per pod; (3) average seed weight, we used mixed effects models with edge effect (distance from edge: 3 m and 30 m) nested within fields as random factors. As predictors, we used percentage podless stalks (as a proxy for pollen beetle damage), percentage stem damage (as a proxy for stem weevil damage), percentage pods with seed weevil exit holes (as a proxy for seed weevil damage) and percentage yellow, split pods (as a proxy for pod midge damage) as well as their pairwise interactions.

We used multimodel inference (Burnham and Anderson
2002) to identify which of the predictors were the main
determinants of yield. This approach allows for compar-
isons among multiple models with different combinations
of predictors, and the identification of the most parsimo-
nious model according to the criterion used. To rank the
models, we used the second order Akaike information cri-
terion corrected for a small sample size (AICc, Hurvich
and Tsai 1989). For each model, we calculated the Akaike
weight (wi) and used the model averaging procedure of
selected models that had Δ wi <2. If only one model was
selected with this criterion, we did not use a model averag-

ing procedure and we presented the top ranked model. All
variables were standardized (to a mean of zero and a stan-
dard deviation of one) beforehand to reduce collinearity,
improve model convergence and to make effect sizes easier
to compare and interpret (Zuur et al. 2009; Schielzeth
2010). Due to the small sample size (n = 15), we restricted
the number of parameters in the alternative models to four
and the main effects were always in the model if interac-
tion was present. Because there already exists solid evi-
dence that pollen beetle damage is important for
determining yield (Williams and Free 1979; Zaller et al.
2008b), we included this variable in all models. Alternative
models contained two additional predictors with or with-
out interactions yielding 13 alternative models that entered
the analyses. The global model residuals were visually
inspected for normality of errors and heteroscedasticity.
Power or exponential variance function structure was used
to improve model residuals (Pinheiro and Bates 2000) in
the models for seed yield and mean seed weight. We used
spline correlogram and we found no spatial autocorrela-
tion in the model residuals. Additionally, in a preliminary
analyses we found no large effect of alternative variables:
weed cover, N fertilization, tiller density and cultivar on
seed yield (Fig. S1), so these variables were not included in
the main analysis. To make sure that the direction of
causality was the one we expected, we checked whether
stem weevils attack more vigorous plants, as previously
reported (Dechert and Ulber 2004). We found no strong
relationship between the stem weevil damage (cm) and the
height or diameter of the main stem (Fig. S2). All analyses
were done in R 3.1.0 (2014-04-10) using packages “nlme”
(Pinheiro et al. 2014), “ncf” (Bjornstad 2013), and
“MuMln” (Barton 2014).

Results

Seed yield

Plant damage and yield varied considerably among the 15
fields (Table 1). The highest ranked model for seed yield
contained the interaction between stem and seed weevil
damage in addition to the main effect of pollen beetle
damage, and was the only selected model with Δi < 2.
For this model, the AICc had a high model probability
(wi = 0.87) and it was 52.9 times more likely to be better
model than the second ranked model (wi = 0.02, see
Table S1. for the full model selection table). Pollen beetle
damage had a negative main impact on seed yield (model
estimate: -0.91 ± 0.09, P < 0.001, Fig. 1). Stem weevil
damage (model estimate: 0.04 ± 0.11, P = n.s, Fig. 2A)
and seed weevil damage (model estimate: 0.06 ± 0.08,
P = n.s) had no main effect on seed yield, but in their
interaction they increased yield (model estimate:
<table><caption>**Table 1.** The mean, standard error (SE), median, 1st and 3rd quartile values of damage measures for four insect pests and oilseed rape yield measures across 15 fields.</caption><thead><tr><th rowspan="2">Damage and yield measures</th><th rowspan="2">Mean ± SE</th><th rowspan="2">Median</th><th>1st</th><th>3rd</th></tr><tr><th>Quartile</th><th>Quartile</th></tr></thead><tbody><tr><td>Percentage pollen beetle damage</td><td>25.82 ± 2.28</td><td>23.40</td><td>17.95</td><td>31.18</td></tr><tr><td>Percentage seed weevil damage</td><td>12.60 ± 2.39</td><td>10.00</td><td>0.00</td><td>20.00</td></tr><tr><td>Percentage pod midge damage</td><td>5.42 ± 1.54</td><td>3.15</td><td>0.74</td><td>7.35</td></tr><tr><td>Percentage of stem damage</td><td>2.75 ± 0.66</td><td>1.50</td><td>0.08</td><td>4.06</td></tr><tr><td>Number of fully developed pods</td><td>30.81 ± 1.79</td><td>30.50</td><td>24.60</td><td>36.75</td></tr><tr><td>Thousand seed weight</td><td>5.70 ± 0.10</td><td>5.78</td><td>0.52</td><td>0.64</td></tr><tr><td>Seed number per pod</td><td>26.06 ± 0.88</td><td>25.95</td><td>22.80</td><td>29.49</td></tr><tr><td>Total seed yield</td><td>4.60 ± 0.13</td><td>4.52</td><td>3.62</td><td>5.73</td></tr></tbody></table>

<figure><img src="image_2.png" /><figcaption>**Figure 1.** Model predictions for the relationship between oilseed rape seed yield and pollen beetle damage.</figcaption></figure>

0.41 ± 0.09, *P* < 0.001, Fig. 2B and C). In particular, the model predicted high stem weevil damage to have a negative effect on yield in the absence of seed weevil damage (26% decrease in seed yield at maximum stem weevil damage), but the interaction turned increasingly positive with increasing levels of seed weevil damage (214% increase in yield at max seed and stem weevil damage). At no stem and seed weevil damage, the model predicted seed yield of 4.73 g/plant (similar to the model predictions of 4.55 g/plant at mean seed and stem weevil damage, See Table 1 for the mean, minimum and maximum values for seed and stem weevil damage).

## Individual seed yield components

Mean seed number per pod increased with seed weevil damage (model averaged coefficient, 1.09 ± 0.30, *P* < 0.001). Mean seed weight per plant was not influenced by any of the factors investigated. The best ranked model for the number of healthy and fully developed pods included the interaction between stem and seed weevil damage and the main effect of pollen beetle damage. It had a high model probability (wi = 0.757) and it was nine times more likely to be better model than the second ranked model (wi = 0.084). It was the only selected model with Δ*il* < 2. The number of healthy and fully developed pods decreased with increasing pollen beetle damage (model estimate: -5.6 ± 0.35, *P* < 0.001). Stem and seed weevil damage showed no strong main effects (model estimate: 0.29 ± 0.36, *P* = n.s and -0.40 ± 0.35, *P* = n.s, respectively), while in interaction they positively affected pod number (model estimate: 1.26 ± 0.32, *P* < 0.001). The direction of this effect was similar to the stem and seed weevil interactive effect on total seed yield.

## Discussion

By themselves, stem weevils are reported to cause little yield loss in winter oilseed rape in Northern Europe (Williams 2010), a finding confirmed in our study. Surprisingly, however, we found that although neither stem weevil nor seed weevil individually influenced seed yield, they jointly had a positive impact. When stem and seed weevils both attacked the plant, the seed yield increased more than two folds, mainly through increasing pod number. Our findings contradict predictions by Stephens et al. (2013) who argued that in cases when herbivores attack different plant parts or at different times (indirect interactions), plant performance should be independently reduced by each species. In our study, the effect on seed yield of the two herbivores (seed and stem weevils) that attack different plant parts at different times was neither additive nor negative. Furthermore, in the meta-analysis by Stephens et al. (2013), attacks on seeds, fruits and flowers were associated with antagonistic interactions among herbivores, but in our study we did not observe any interactions among damages caused by pollen beetles, seed weevils, and pod midges that feed on plant reproductive parts.

The underlying mechanisms for the interactive effects of combined insect attacks are argued to be either interference competition among herbivores or changes in plant nutritional quality, phenology or defenses (Stephens et al. 2013). Direct interference competition between the two pests is unlikely to have occurred in our study, because stem weevils (early herbivores) and seed weevils (late herbivores) attack different plant parts and at different times.
<figure><img src="image_3.png" /><figcaption>**Figure 2.** Damage to oilseed rape caused by seed and stem weevils. Model predictions for the interactive effects of stem damage at (A) no (0%), (B) mean (12.6%, full data) and (C) and high (60% < x > 20%, predicted regression line at 40% damage by seed weevil) levels of the seed weevil damage on seed yield. Thus, stem weevils have negative effect on seed yield when there is no damage caused by seed weevils, but when the damage by seed weevil increases the effect of stem weevils on seed yield changes from negative to positive.</figcaption></figure>

It is moreover unlikely that the observed interactive effect
is due to decreased damage by later herbivores when
plants suffer high early herbivory, because the stem and
seed weevil damages were not correlated in our study.
Instead, it is possible that early herbivore attacks ‘primed’
the plants to respond more efficiently to damage by late
herbivores (Heil and Kost 2006), presumably through
plant compensatory mechanisms. Oilseed rape plants can
compensate for high seed weevil densities by producing
more pods (Tatchell 1983), but we found this only when
densities of stem weevils were high. This compensatory
growth can also be due to pod damage caused by adult
weevils, rather than for seed loss to larvae. Compensatory
growth is a common response of oilseed rape to pest
injury, facilitated by redistribution of metabolites to
already existing organs, or by production of new organs.

Seed weevil larvae can consume 8–15% of the seeds in
a pod and reduce yield by 18% (Williams 2010). Interest-
ingly, seed weevils did not only positively affect pod num-
ber in interaction with stem weevils, but also had an
independent positive effect on seed number per pod.
Although this is somewhat counter-intuitive, a positive
relationship between plant fitness (fruit set, seed yield,
and seeds per fruit) and oviposition or seed predation by
predispersal seed predators (i.e. where predation occurs
before the seeds have been released from the parent plant)
has also been documented for other plant species (Brody

and Mitchell 1997; Brody and Morita 2000; Brody and
Irwin 2012). This relationship may result from two mech-
anisms. First, oviposition by seed predators can affect the
plant's reproduction. For example, Brody and Morita
(2000) showed that the predispersal seed predator of *Ipo-
mopsis aggregata* is able to induce a response in its host
plant to ensure fruit set. Seed predators such as seed wee-
vils can also locate fruits with a low probability of abor-
tion, possibly using fruit position and phenology as cues
(Östergård 2008). It is possible that the same plant trait,
such as large floral displays, attracts both seed predators
and pollinators (Brody and Mitchell 1997), thereby result-
ing in increased seed yield (Cariveau et al. 2004) even in
presence of seed predation. Hence, seed predation and
fruit set can be related to the same plant trait, rather than
directly affecting each other. Since seed weevils affected
both fruit set and seeds per fruit, all these mechanisms
are possible in our study.

Pollen beetles substantially reduced seed yield, which is in
accordance with a number of studies showing pollen beetles
to be the main oilseed rape pests in Europe (Williams 2010
and references therein). Pollen beetle damage can induce
the plant to compensate with newly produced racemes and
buds, higher seed weight and lower seed number per pod
(Alford et al. 2003), but this was not the case in our study.
Instead, the effect of pollen beetles on the seed yield was
negative, mainly because of the reduced number of healthy,
developed pods. This effect of pollen beetles on seed yield was independent of the damage caused by other insects, presumably due to the absence of plant compensatory growth as a response to pollen beetle attack in our study.

Pods infested by the pod midge split open or shatter prematurely and this can result in considerable yield loss (Alford et al. 2003; Zaller et al. 2008b). However, in our study pod midge damage had little effect on seed yield, or any of the yield components (number of seeds per pod, number of healthy pods, average seed weight), although pod damage reached 12%. In contrast, Zaller et al. (2008b) found negative pod midge effects on oilseed rape yield. The difference between our findings and theirs may be explained by the different yield measures. We estimated average seed weight per plant, while Zaller et al. measured seed weight per area (ha), a measure that depends on plant density. Pod midge damage was strongly negatively correlated with plant density in our study (data not shown, see also Valentin-Morison et al. 2007) and consequently to the area-based yield measure (seed yield multiplied by plant density per m²). Hence, the scale of the yield measure, that is per plant versus per unit area, might influence conclusions of the herbivore impact on yield, since plant density can affect both pest pressure and seed yield measure. Furthermore, if one pest facilitates a second, as has been commonly reported with seed weevil and pod midge, plant performance can be reduced by their combined attack. However, this was not the case in our study, possibly because the effect of pod midge on seed yield was low or because plant compensation for the damage masked the effect.

## Conclusions

To our knowledge, this is the first study in crop fields showing that pests from different feeding guilds can not only individually affect yield through increased plant damage, but can also interactively affect yield, possibly through plant compensatory mechanisms. Hence, the mechanism behind the effect of diverse insect pests on the provisioning ecosystem service, that is yield, is not necessarily complementarity (niche differentiation, i.e. additive effects of pests on yield). Complementarity is one of the common hypotheses explaining how species biodiversity affects ecosystem functioning, but it is almost exclusively tested on organisms providing ecosystem services, rather than disservices. Furthermore, our study shows that to produce satisfactory harvests with reduced inputs of pesticides, we need to take into account all potentially harmful species and the natural variations in the plant damages they cause. Considering the effect of only one pest species separately from other harmful species, may result in economically suboptimal choices being made.

Seed yield more than doubled when the level of attack by both seed and stem weevils were high. These results show that increasing our knowledge about multiple pest-plant interactions has a large potential for not only directly increasing yield, but also for reducing pesticide input and thereby the negative impacts of agricultural intensification on the environment. However, our study is observational and experiments need to be undertaken before recommendations on crop management can be given. Additionally, it should be noted that the joint effect of pests on yield is probably not fixed, but rather can shift depending on a number of biotic and environmental drivers (e.g. resource availability, competition among plants, plant genetic variation, the strength of pest attack, plant and insect phenology). To quantify the economic consequences of insect attacks, we need to better understand the ecological processes and mechanisms explaining the interactive insect effects on yield, and the scale (plant vs. field) at which they occur. Nevertheless, our results show a promising way that explores a new area of research in agroecology, connects to similar evolutionary studies and has a large potential to lead to a more sustainable agricultural management and increased production.

## Acknowledgments

We are grateful to Carol Högfeldt for technical assistance. We thank the numerous field assistants and farmers for their efforts and participation. Funding was provided by the Swedish research council FORMAS.

## Data Accessibility

Data available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.8g3j2

## Conflict of Interest

None declared.

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## Supporting Information

Additional Supporting Information may be found in the online version of this article:

**Figure S1.** Relationship between seed yield and a) weed cover, b) number of plants per square meter, c) oilseed rape variety and d) amount of nitrogen fertilizers applied in 15 oilseed rape fields.

**Figure S2.** Relationship between main stem damage and main stem height and diameter.

**Figure S3.** Relationship between stem and seed weevil damage.

**Table S1.** Model selection table (coefficients, *df*, log-likelihood, the value of the information criterion used (AICc), ΔAICc and ‘Akaike weight’) for seed yield. There are 13 alternative models including intercept only model. “NA” – parameter not tested in the model.