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Greenop, A., Woodcock, B. A., Wilby, A., Cook, S. M. and Pywell, R. F. 2018. Functional diversity positively affects prey suppression by invertebrate predators: a meta-analysis. Ecology. 99 (8), pp. 1771-1782.
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Functional diversity positively affects prey suppression by invertebrate predators: a meta-analysis
Journal: Ecology ManuscriptFor ID ECY17-0800.R2 Review Only Wiley - Manuscript type: Articles
Date Submitted by the Author: 23-Feb-2018
Complete List of Authors: Greenop, Arran; Centre for Ecology and Hydrology, ; Lancaster Environment Centre, Woodcock, Ben; CEH Wilby, Andrew; Lancaster University Cook, Sam; Rothamsted Research Pywell, Richard; Centre for Ecology and Hydrology, UK
Predation < Species Interactions < Community Ecology < Substantive Area, Biological Control < Species Interactions < Community Ecology < Substantive Area: Substantive Area, Agroecosystems < Ecosystems < Substantive Area, Phylogenetics < Systematics < Population Ecology < Substantive Area, Species Interactions < Community Ecology < Substantive Area
Organism:
Habitat:
Geographic Area:
Functional diversity, Phylogenetic diversity, Predator-prey interactions, Traits, Conservation biological control, Natural enemies, Biodiversity and Additional Keywords: ecosystem functioning, Agricultural ecosystems, Ecosystem services, Species richness
The use of pesticides within agricultural ecosystems has led to wide concern regarding negative effects on the environment. One possible alternative is the use of predators of pest species that naturally occur within agricultural ecosystems. However, the mechanistic basis for how species can be manipulated in order to maximise pest control remains unclear. We carried out a meta-analysis of 51 studies that manipulated predator species richness in reference to suppression of herbivore prey to Abstract: determine which components of predator diversity affect pest control. Overall, functional diversity (FD) based on predator’s habitat domain, diet breadth and hunting strategy was ranked as the most important variable. Our analysis showed that increases in FD in polycultures led to greater prey suppression compared to both the mean of the component predator species, and the most effective predator species, in monocultures. Further analysis of individual traits indicated these effects are likely to be driven by Page 1 of 94 Ecology
broad niche differentiation and greater resource exploitation in functionally diverse predator communities. A decoupled measure of phylogenetic diversity, whereby the overlap in variation with FD was removed, was not found to be an important driver of prey suppression. Our results suggest that increasing FD in predatory invertebrates will help maximise pest control ecosystem services in agricultural ecosystems, with the potential to increase suppression above that of the most effective predator species.
For Review Only Ecology Page 2 of 94
1 Running head: Functional diversity drives prey suppression
2 Functional diversity positively affects prey suppression by invertebrate predators: a
3 meta-analysis
4 Arran Greenop. 1,2, Ben A Woodcock1, Andy Wilby 2, Samantha M Cook 3 & Richard F
5 Pywell 1.
6 1 NERC Centre for Ecology & Hydrology, Maclean Building, Crowmarsh Gifford,
7 Wallingford, Oxfordshire OX10 8BB, UK. Tel. +44(0)1491692415 8 2 Lancaster EnvironmentFor Centre, LibraryReview Avenue, Lancaster Only University, Lancaster LA1 4YQ 9 3 Biointeractions and Crop Protection Department, Rothamsted Research, Harpenden, Herts,
10 AL5 2JQ, UK.
11
12 Contact Author: Arran Greenop, e-mail:[email protected], 07538808379
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25
1 Page 3 of 94 Ecology
26 Abstract
27 The use of pesticides within agricultural ecosystems has led to wide concern regarding
28 negative effects on the environment. One possible alternative is the use of predators of pest
29 species that naturally occur within agricultural ecosystems. However, the mechanistic basis
30 for how species can be manipulated in order to maximise pest control remains unclear. We
31 carried out a meta-analysis of 51 studies that manipulated predator species richness in
32 reference to suppression of herbivore prey to determine which components of predator 33 diversity affect pest control.For Overall, Review functional diversity Only (FD) based on predator’s habitat 34 domain, diet breadth and hunting strategy was ranked as the most important variable. Our
35 analysis showed that increases in FD in polycultures led to greater prey suppression
36 compared to both the mean of the component predator species, and the most effective
37 predator species, in monocultures. Further analysis of individual traits indicated these effects
38 are likely to be driven by broad niche differentiation and greater resource exploitation in
39 functionally diverse predator communities. A decoupled measure of phylogenetic diversity,
40 whereby the overlap in variation with FD was removed, was not found to be an important
41 driver of prey suppression. Our results suggest that increasing FD in predatory invertebrates
42 will help maximise pest control ecosystem services in agricultural ecosystems, with the
43 potential to increase suppression above that of the most effective predator species.
44
45
46 Key words: Functional diversity, Phylogenetic diversity, Predator-prey interactions, Traits,
47 Conservation biological control, Natural enemies, Biodiversity and ecosystem functioning,
48 Agricultural ecosystems, Ecosystem services, Species richness
49
50
2 Ecology Page 4 of 94
51 Introduction
52 The predicted growth of global populations will lead to an ever-increasing demand for
53 agricultural systems to deliver greater food production (25% - 75% increase in food by 2050;
54 Hunter et al, 2017). Whilst this goal may be achieved through conventional forms of
55 agricultural intensification, there are likely limitations to the extent to which chemical
56 insecticides can be relied upon without facing a myriad of risks. These range from the
57 likelihood of pesticide resistance in pest species (Nauen & Denholm 2005; Bass et al. 2014), 58 the revocation of active Foringredients Review (NFU, 2014), damaging Only effects on non-target organisms 59 (Easton & Goulson 2013; Hallmann et al. 2014; Woodcock et al. 2016, 2017), as well as diffuse
60 pollution impacting on human and environmental health in general (Wilson & Tisdell 2001;
61 Horrigan et al. 2002). An increased reliance on conservation biological control, where
62 predators or parasitoids (here, referred to collectively as predators) of pest species are
63 encouraged within agricultural ecosystems has the potential to address some of these issues
64 (Begg et al. 2017). Fundamental to integrating conservation biological control into agricultural
65 practices is understanding which components of invertebrate biodiversity need to be managed
66 to maximise pest suppression.
67
68 A number of meta-analyses (Bianchi et al. 2006; Letourneau et al. 2009; Griffin et al. 2013)
69 have demonstrated that higher predator richness can increase prey suppression (reduction in
70 herbivores by predators), however, species richness provides little elucidation as to the
71 underlying mechanisms driving this trend. An important characteristic of multi-predator
72 systems is the presence of significant variation in the response of prey suppression to increasing
73 predator species richness; a consequence of the range of complex interactions between
74 predators, and predators and prey (Ives et al. 2004; Casula et al. 2006; Schmitz 2007). For
75 example, intraguild interactions can be positive (functional facilitation), whereby predators
3 Page 5 of 94 Ecology
76 facilitate the capture of prey by other predator species (Losey & Denno 1998). Niche
77 complementarity is another interaction that can lead to overyielding of prey suppression by
78 diverse assemblages, where individual predators may feed on different life stages of a prey
79 species (Wilby et al. 2005). However, negative interactions also occur between predators
80 reducing prey suppression in diverse assemblages. One of the most commonly encountered of
81 these is intraguild predation, whereby a top predator consumes not only the prey but also the
82 intermediate predators (Rosenheim et al. 2004a; Finke & Denno 2005). Interference 83 competition can also occurFor whereby Review one predator species Only reduces prey capture by the other due 84 to negative behavioural interactions (Lang 2003). Given the complexity of these interactions,
85 the net effect of predator species diversity is often difficult to predict.
86
87 Defining morphological or behavioral characteristics of individual species that potentially
88 impact on prey suppression, often referred to as functional effect traits, provides an opportunity
89 to elucidate the mechanistic link between predator biodiversity and the delivery of this
90 ecosystem service (Wood et al. 2015). For example, Schmitz (2007) suggested that traits
91 related to habitat domain (the spatial location of where the natural enemy feeds, e.g. ground or
92 upper canopy of vegetation) and hunting method (how they catch prey, e.g. sit & wait) were
93 important in understanding how predator interactions affected prey suppression. Similarly,
94 size differences between predators and prey can also influence intraguild interactions and play
95 an important role in predicting consumption rates (Rosenheim et al. 2004b; Brose et al. 2008;
96 Ball et al. 2015). While these assumptions have been supported in part by several studies
97 (Woodcock & Heard 2011; Miller et al. 2014; Northfield et al. 2014; Michalko & Pekár 2016)
98 the direct implications of functional diversity (FD) between species on their capacity to deliver
99 pest control remains poorly understood.
100
4 Ecology Page 6 of 94
101 An understanding of how predator diversity and traits influence pest suppression has been
102 identified by several reviews as being crucial to the implementation of sustainable pest
103 management in agricultural ecosystems (Bianchi et al. 2010; Wood et al. 2015; Jonsson et al.
104 2017; Perović et al. 2017). This information is a required step in bridging the gap between
105 experimental small-scale mesocosm (cage) studies and generalizable rules that can be used by
106 practitioners in field-scale management strategies, and a detailed meta-analysis directly
107 addressing this question has yet to be undertaken (Woodcock et al. 2013). 108 For Review Only 109 Here we address this knowledge gap by undertaking a meta-analysis to identify how
110 dissimilarity in key functional effects traits of invertebrate predators can influence interactions
111 between predators and their prey to affect pest suppression. The meta-analysis was undertaken
112 using 51 studies (214 data points) comprising a total of 73 predator species attacking 35 species
113 of arthropod prey. We assess how both FD based on an a priori selection of traits, and
114 phylogenetic diversity (PD) based on evolutionary history are linked to prey suppression
115 (Cadotte et al. 2013). We use the meta-analysis to test the general prediction that increased
116 predator species richness leads to greater prey suppression (prediction 1) (e.g. Letourneau et
117 al. 2009; Griffin et al. 2013; Katano et al. 2015). We also test the following predictions related
118 to explaining diversity effects; increased FD of key effects traits explains patterns in prey
119 suppression in polycultures due to increased niche complementarity between predator species
120 (prediction 2); PD has a smaller effect on prey suppression than FD as it accounts for broad
121 differences in evolutionary history, compared to FD which is based on an a priori selection of
122 traits (prediction 3); and finally related to body size differences between predators, and
123 predators and prey we predict that, increased body size ratio between predators and prey will
124 positively affect prey suppression, whilst greater size differences between predators will
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125 negatively affect prey suppression due to increased intraguild predation (prediction 4) (Lucas,
126 Coderre & Brodeur 1998; Rosenheim et al. 2004b; Brose 2010; Ball et al. 2015).
127
128 Materials and Methods
129 Study selection and data
130 We carried out a systematic literature search of studies testing the impact of factorial
131 combinations of increasing predator or parasitoid species richness on prey suppression. These 132 experiments were all undertakenFor Reviewin mesocosms, representing Only an experimental arena within 133 which population changes of the prey species could be monitored. Literature searches were
134 carried out between November 2016 – January 2017 using ISI Web of Science (search terms
135 included in Appendix S1 in Supporting Information) and reference lists published in the
136 following studies: Sih et al. 1998; Straub et al. 2008; Letourneau et al. 2009; Griffin et al.
137 2013; Katano et al. 2015. In addition, unpublished sources (Asiry, 2011; Fennel, 2013) of
138 literature were included and additional studies identified by E Roubinet (pers comm).
139
140 Studies were selected based on their fulfilment of the following criteria: 1) the study system
141 was of terrestrial arthropods, 2) predator species richness was manipulated in reference to the
142 suppression of arthropod prey species, 3) the study considered two or more predator species,
143 4) all predators of prey were included in monoculture (species A or species B) and polyculture
144 (species A+B) treatments, 5) the study contained a quantifiable measure of prey suppression,
145 6) the study included mean, standard deviations and the number of replicates for each
146 treatment. Typically, individual published studies were composed of multiple experiments
147 where factors other than predator species richness were manipulated. These factors included
148 prey species richness, habitat complexity, temperature/environmental conditions, predator life
149 stage, predator density as well as methodological factors such as the use of additive and
6 Ecology Page 8 of 94
150 substitutive experimental designs; of which factors could potentially impact the nature of multi-
151 predator trophic interactions and the observed outcome on prey suppression (Finke & Denno
152 2002; Wilby & Orwin 2013; Ajvad et al. 2014; Drieu & Rusch 2017). These experiments were
153 therefore treated as separate data points. For studies investigating responses of multiple instars
154 of the same predator species, only the life stages that provided the maximum and minimum
155 prey suppression were included. This was done to avoid potential pseudo-replication due to
156 strong functional similarity between successive larval instars while providing an indication of 157 the full range of potentialFor emergent Review impacts on prey Only suppression by that species (Cisneros & 158 Rosenheim 1997).
159
160 Quantification of herbivore suppression effect sizes
161 Where possible, we extracted data on the impact of predator diversity on prey suppression
162 directly from published studies, either from presented data or using WebPlotDigitizer 3.11
163 (Rohatgi, 2017) to extract information from graphs. Where the required information was not
164 available, the raw data was requested directly from the corresponding author. A total of 51
165 studies constituting 214 data points were included in analyses (see Appendix S2 for literature
166 included). As prey suppression was measured in several different ways, we used the
167 standardised mean difference corrected for small sample sizes as our test statistic (Hedges
168 1981; Hedges & Olkin 1985). We also calculated the corresponding sampling variance for
169 each experiment (Hedges 1981; Hedges & Olkin 1985). Following Cardinale et al., 2006 and
170 Griffin, Byrnes & Cardinale, 2013, we calculated two test statistics for each experimental data
171 point. The first is SMDmean, which is the standardised mean difference between the mean (푥̅)
172 effect of the predator polyculture (p) on prey suppression compared to the mean effect of the
173 component predator species in monocultures (m) calculated as:
푥̅̅푝̅ − 푥̅̅푚̅̅ 174 푆푀퐷 = 퐽, 푠
7 Page 9 of 94 Ecology
175 where s is the pooled standard deviation calculated as: 176
2 2 (푛푝 − 1)푆퐷푝 + (푛푚 − 1)푆퐷푚 177 푠 = √ 푛푝 + 푛푚 − 2 178
179 and J a correction factor applied for small sample sizes:
3 180 퐽 = 4(푛푝 + 푛푚) − 1
181 The variance (v) for each experiment was calculated as:
2 푛푝 + 푛푚 푆푀퐷 182 For푉 =Review + Only 푛푝푛푚 2 (푛푝 + 푛푚)
183 The second metric, SMDmax, is the standardised mean difference between the mean effect of
184 the polyculture on prey suppression compared to the most effective predator species in a
185 monoculture (mx), where mx replaces m in the above equations. Where the measure of prey
186 suppression was negative (e.g. aphid population size decreased due to greater predation) then
187 the sign of the mean was reflected (multiplied by minus 1) so that the measure could be more
188 intuitively interpreted as a positive effect of increased prey suppression in polycultures (Griffin
189 et al. 2013). All effect sizes and sampling variances were calculated in RStudio using the
190 metafor package (Viechtbauer, 2010; R Core Team, 2016).
191
192 Species richness
193 Variables were included for predator species richness and prey species richness, as a meta-
194 analysis by Katano et al. (2015) demonstrated variation in herbivore suppression between
195 different richness levels. Both variables were included as categorical due to a strong skew
196 towards lower richness levels (prey richness = 1 (n = 177) and prey richness >1 (n = 37);
197 predator richness = 2 (n = 152) and predator richness > 2 (n = 62)).
198
8 Ecology Page 10 of 94
199 Effects traits describing functional diversity
200 For each of the predator species we collected information on ‘effects traits’ which represent
201 physical or behavioral characteristics that would have a direct impact on prey suppression. Due
202 to the taxonomic breadth of predator species we included effects traits based on: hunting
203 strategy, defined as the method used by the predator species to capture prey; habitat domain,
204 defined as the part of the experimental area where the predator predominantly hunts; and diet
205 breadth, describing whether the predators were generalists or specialists. The trait categories, 206 definitions and species withinFor these Review groups are shown Only in Appendix S3; Table 1 and 2. Where 207 possible trait classifications were obtained directly from the study included in the meta-
208 analysis. Where this was not possible information on species ecology was determined from a
209 search of primary and grey literature, as well as the use of expert opinion. These traits were
210 selected as previous research suggests they play an important role in predator-predator
211 interactions and the resultant effect on herbivore suppression (Losey & Denno 1998; Schmitz
212 2007; Straub et al. 2008; Woodcock & Heard 2011; Ball et al. 2015). A Gower dissimilarity
213 matrix (Gower 1971) was calculated using these effects traits. The square root of the Gower
214 dissimilarity matrix was then subjected to principle coordinate analysis and used to calculate
215 mean pairwise dissimilarity between the predator species within each experiment as an index
216 of functional diversity (FD) (see functional and phylogenetic diversity measures for a
217 description). Functional dissimilarity pairwise matrices were calculated using the decouple
218 function supplied in de Bello et al. 2017.
219
220 Phylogentic diversity
221 Whilst the functional effects traits were selected due to their direct importance in predicting
222 prey suppression based on previous research, these do not describe the full functional identity
223 of individual species. This functional identity would be defined by both response traits as well
9 Page 11 of 94 Ecology
224 as potentially undefined effects traits linked to pest control delivery. These between species
225 differences in combined functional characteristics can be explained by phylogenetic history,
226 with the assumption that a common evolutionary origin will explain a large component of the
227 functional similarity in traits that characterise predator species (Cadotte et al. 2013). We used
228 the Linnaean taxonomic classification (phylum, class, order, family, genus) for the predator
229 species to construct a surrogate phylogenetic tree in the ape package in RStudio (Paradis,
230 Claude and Strimmer, 2004). From this tree, a matrix of phylogenetic dissimilarity was 231 calculated from the squareFor root branchReview lengths between Only the tips of the tree for each species. 232 The overlap in variation between the functional dissimilarity and phylogenetic dissimilarity
233 between each species was then decoupled using the decouple function described in de Bello et
234 al, (2017). This was carried out to ensure that the two measures for each species were
235 explaining unique components of predator diversity. This was then used to derive a decoupled
236 phylogenetic dissimilarity matrix between predator species. The functional diversity metric
237 incorporates diversity linked to both individual traits and an inherent component resulting from
238 phylogenetic links between species (referred to as FDist in de Bello et al., 2017). As such this
239 is typical of other existing functional diversity metrics (for example Rao’s quadratic entropy
240 (de Bello et al., 2017)). However, the decoupled phylogenetic diversity metric represents the
241 residual phylogenetic variation not accounted for through the functional traits (referred to as
242 dcPDist in de Bello et al., 2017). This decoupled measure of phylogenetic diversity was
243 included as it allowed us to identify if other unmeasured traits captured by phylogenetic
244 diversity were important in prey suppression.
245
246 Functional and phylogenetic diversity measures
10 Ecology Page 12 of 94
247 From each functional and phylogenetic dissimilarity matrix, we calculated the mean pairwise
248 dissimilarity between species in each experiment using the melodic function supplied in de
249 Bello et al., (2016);
250
푁 1 251 Mean pairwise dissimilarity = 푁 ∑ 푝푖푝푗푑푖푗, ∑ 푝푖푝푗 푖>푗 푖>푗
252 253 where N is the number ofFor species Reviewin a community, dij Only is the dissimilarity between each pair of 254 different species i and j, respectively, pi and pj are the relative abundances of species i and j,
255 respectively, divided by the total of all species abundances in a community. We used an
256 unweighted index based on presence/absence (where pi = 1/N) as predator numbers were equal
257 in the majority of experiments included in the meta-analysis. Mean pairwise dissimilarity was
258 selected for all the phylogenetic and functional diversity measures (see Table 1) as it has been
259 found to be relatively insensitive to species richness where richness levels are low (de Bello et
260 al. 2016).
261
262 Body size
263 Body size has been shown to influence predator-predator interactions where large body sized
264 generalist predators may consume smaller predators as well as prey (Lucas, Coderre & Brodeur
265 1998; Rosenheim et al. 2004b). Additionally, body size ratios between predators and prey have
266 been shown to affect consumption rates (Lucas et al. 1998; Rosenheim et al. 2004b; Brose
267 2010; Ball et al. 2015). We defined a mean body size (body length in mm) for each predator
268 species (Appendix S3). Where different life stages of single predator species were used in
269 experiments, this was accounted for with life-stage specific mean body size. We also included
270 a mean body size for each of the prey species. From these measures of body size, we calculated
11 Page 13 of 94 Ecology
271 the mean size difference in predator body sizes, and the ratio between the smallest predator and
272 prey body size (Table 1). We did not include the individual sizes of smallest and largest
273 predators as covariates as these were both highly inter-correlated with either predator-predator
274 size differences or predator-prey body size ratios (see Appendix S4: Table 1). Similarly, a high
275 level of collinearity was also found between the prey and the largest predator body size ratio
276 (ratiolarge), and prey and the smallest predator size ratio (ratiosmall) variables. The highest ranked
277 model sets including ratiosmall had lower AICc scores than the highest ranked ratiolarge models; 278 therefore only ratiosmall wasFor included Review in final analysis Only (Appendix S4: Table 2-5). 279
280 Experimental factor moderator variables
281 In addition to factors associated with predator and prey species richness and traits, a number
282 of experimental factors were also included in analysis that have previously been shown to
283 influence prey suppression. These included: experimental arena volume (cm3; log transformed
284 to improve linearity), duration of study following predator addition (hours) and study setting
285 (field, or greenhouse/lab). Additionally, a factor was included to test between study designs
286 (additive or substitutive) as this has been shown to lead to different conclusions about prey
287 suppression depending on the design used (Schmitz 2007; Byrnes and Stachowicz, 2009).
288 Additive studies increase the number of predators in the polyculture based on the sum of the
289 component predators in monocultures, whereas substitutive designs maintain the same number
290 of predators in polycultures and monocultures.
291
292 Statistical analysis
293 Intercept only random effects models were used for both SMDmean and SMDmax to determine
294 whether there was an overall effect of greater prey suppression in polycultures. Models
295 included study identity as a random factor to account for the fact that multiple points came
12 Ecology Page 14 of 94
296 from single studies. The restricted maximum likelihood was used (REML) to estimate between
297 study variance. The meta-analysis was unweighted as weighting by inverse variance has been
298 shown to result in bias against small sample sizes (Hedges & Olkin 1985; Letourneau et al.
299 2009). All meta-analyses were undertaken using the rma.mv function in the package metafor
300 (Viechtbauer, 2010; RStudio, 2015). Wald-type 95% confidence intervals are given.
301 Assessments of publication bias in response to an underrepresentation of non-significant results
302 were undertaken using funnel plots (Koricheva, Gurevitch and Mengersen, 2013). Some 303 evidence of publication biasFor was foundReview whereby studies Only with lower precision were more likely 304 to detect negative effects for SMDmax (See Appendix S5). However, as this result was not
305 detected for SMDmean, this is likely caused by the calculation of the SMDmax metric (see Schmid
306 et al. 2008).
307
308 We used a meta-regression with a maximal model including FD, PD, ratiosmall, predator size
309 difference, prey size, prey richness and predator richness to quantify how emergent effects on
310 prey suppression were effected by aspects of invertebrate community structure (Table 1). The
311 response variables were the two metrics SMDmean and SMDmax. An information theoretic
312 approach was used to identify the best set of candidate models from the full model and we then
313 used multi-model averaging to obtain parameter estimates (Burnham & Anderson 2004).
314 Maximum-likelihood was used to allow model comparison with a study subject identifier
315 included as a random effect. All possible model combinations of the variables included in the
316 full model were run. Models that had ΔAICc values of <2 were then used to rank variable
317 importance and obtain model averaged parameter estimates based on AICc relative importance
318 weights (Burnham & Anderson 2004). Variables were transformed where required to improve
319 linearity (Table 1). All model averaging was carried out in the glmulti package in RStudio
320 (Calcagno and Mazancourt, 2010).
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321
322 Whilst the FD metric allowed for comparisons to be made to phylogenetic diversity, the
323 inclusion of a number of different traits meant it was difficult to discern which aspects of FD
324 were driving any potential trends. To account for this, we analysed differentiation within each
325 trait using mixed models comparing all possible model combinations based on AICc values.
326 Full models started with diet breadth, hunting strategy and habitat domain included as fixed
327 effects with the study subject identifier as a random effect. Models that had ΔAICc of <2 were 328 then ranked to obtain model-averagedFor Review parameter estimates Only based on AICc relative importance 329 weights (Burnham & Anderson 2004). Models were also run including just FD, so that a
330 comparison of AICc values of the individual traits with the composite metric of functional
331 diversity could be made.
332 333 We also individually tested whether the experimental moderator variables had a significant
334 effect on the two SMD metrics using mixed effects models, again using REML with a study
335 subject identifier included as a random factor. We did not include experimental variables in
336 model averaging as the focus of this analysis was to identify the importance of factors related
337 to predator and prey community structure on prey suppression, not experimental design.
338 Variables were tested individually as information was absent from several studies for some of
339 the experimental explanatory variables.
340
341 Results
342 General effects across studies
343 Overall trends showed greater prey suppression in predator polycultures compared to the mean
344 effect of the component species in a monoculture (SMDmean), as the average effect size for
345 SMDmean was significantly greater than zero (SMDmean = 0.444; 95% CI [0.265, 0.623]; Z =
346 4.858, p = <0.001). However, SMDmax (suppression of herbivores in the polyculture compared
14 Ecology Page 16 of 94
347 to the most effective predator) was not found to differ significantly from zero with a mean
348 effect size of -0.109 (95% CI [-0.308, 0.090], Z = -1.078, p = 0.281). This shows that increased
349 predator richness in polycultures did not result in significantly greater levels of prey
350 suppression than the most effective predator in a monoculture.
351
352 Predator and prey variables
353 SMDmean 354 Functional diversity wasFor ranked asReview the most important Only variable based on relative model 355 weights of the 2AICc subset, and was the only parameter included in the top ranked model
356 (Table 2: Figure 1) (See Appendix S6 for 2AICc subset). Functional diversity (parameter
357 estimate = 0.448, 95% CI [0.065, 0.831]) had a positive effect on SMDmean. Ratiosmall
358 (parameter estimate = -0.080, 95% CI [-0.344, 0.184]) was ranked as the second most
359 important variable, however had confidence intervals that overlapped zero, as did the
360 variables prey richness, predator richness, size difference, prey size and decoupled
361 phylogenetic diversity (Table 2; Figure 1).
362
363 Where the individual traits were analysed separately, diet breadth was the only variable
364 included in the top ranked model (See Appendix S7; Table 1). Differentiation within diet
365 breadth (parameter estimate = 0.371, 95% CI [0.096, 0.646]) was found to have a positive
366 effect on SMDmean. Hunting strategy was also included in the 2AICc subset, however had 95%
367 confidence intervals that overlapped zero (hunting parameter estimate = 0.023, 95% CI [-
368 0.098, 0.144]). The FD only model showed a positive effect of FD (parameter estimate =
369 0.453, 95% CI [0.072, 0.831]). When compared to the diet breadth only model, the FD
370 model had a higher AICc value (Diet breadth only model AICc = 443.960; Functional
371 diversity model AICc = 445.671). Suggesting that the beneficial effects of FD on SMDmean in
15 Page 17 of 94 Ecology
372 the main predator and prey model may have largely been driven by differentiation in diet
373 breadth.
374
375 SMDmax
376 Functional diversity, predator richness and ratiosmall were all included in the top ranked model
377 for SMDmax (Appendix S6). Functional diversity (parameter estimate = 0.461, 95% CI [0.049,
378 0.873]) was again found to have a positive effect, whereas both predator richness of >2 species 379 (parameter estimate = -0.276,For 95% Review CI [-0.541, -0.011]) Only and ratiosmall (parameter estimate = - 380 0.282, 95% CI [-0.754, 0.190]) had a negative effect on SMDmax (although the 95% CI for
381 ratiosmall overlapped zero). Variables also included in the top ranked models were prey size and
382 size difference between predators, however, these were only included in models in combination
383 with functional diversity and had confidence intervals that overlapped zero (Table 2; Figure 2).
384 Decoupled phylogenetic diversity was included in one model in the 2AICc subset, however it
385 too had confidence intervals that overlapped zero (Table 2; Figure 2).
386
387 Where the traits were analysed separately, a null model was included in the 2AICc subset
388 (Appendix S7; Table 4). This indicated that none of the individual traits explained a greater
389 amount of the variation than a model without any factors included. In comparison to the trait
390 model, the FD model showed a clear positive effect of FD (parameter estimate = 0.458, 95%
391 CI [0.049, 0.867]) on SMDmax, and had a lower AICc by a value of <2 compared to the null
392 model (Appendix S7). This indicates that the positive effect of FD on SMDmax is likely
393 dependent on a composite measure of diversity including all three traits.
394
395 Experimental factors
16 Ecology Page 18 of 94
396 Of the experimental variables tested, study design (additive or substitutive) was found to have
397 a significant effect on SMDmax metric (Table 3). Compared to additive designs, substitutive
398 designs were found to have a significantly lower mean effect size (whilst the mean for additive
399 designs was positive, the 95% CI still overlapped zero) (Table 3; Figure 3). As this is indicative
400 of a potential density effect, where positive diversity effects in polycultures could be a product
401 of predator densities, we re-analysed the predator and prey variables for SMDmax only including
402 studies that accounted for density. This had no qualitative effect on our results (See Appendix 403 S8). None of the other experimentalFor Review variables included Only had a significant effect on SMDmean or 404 SMDmax, suggesting that the results were not artefacts of differences in spatio-temporal scale
405 or the study setting (Table 3).
406
407 Discussion
408 When compared to the pest suppression achieved by individual predator species, combining
409 predators in polycultures increased the top-down control of herbivores. This is consistent with
410 our first prediction that increased predator species richness leads to greater prey suppression.
411 However, this was only the case when considering the average level of prey suppression across
412 all predators (SMDmean), with polyculture effects not exceeding those of the most effective
413 predator (SMDmax). Interestingly, increased species richness above that of simple two predator
414 systems was shown to have a negative effect when polycultures were compared to the most
415 effective predator species. This result is likely an artefact of bias in the calculation of SMDmax
416 metric (Schmid et al. 2008; Griffin, Byrnes & Cardinale 2013). Where predator assemblages
417 are species rich they are increasingly likely to include species that affect the extreme ranges of
418 prey suppression. Therefore, whilst sampling effects increase the likelihood that diverse
419 polycultures will include a highly effective predator, when polycultures are compared to the
420 most effective predator in a monoculture, they may be as probable to perform badly due to an
17 Page 19 of 94 Ecology
421 increased likelihood of poorly performing predatory species also being present (Schmid et al.
422 2008). In an agricultural context, this would suggest that management should be targeted
423 towards the most effective predator species rather than increasing overall richness (Straub &
424 Snyder 2006; Straub et al. 2008).
425
426 Although where we considered moderator variables, the results of our meta-regression
427 supported our second prediction that greater FD positively affects prey suppression. Further 428 analysis, where we comparedFor theReview polyculture to Only the mean of the component species in 429 monocultures, revealed that this was most likely to be driven by differences in diet breadth.
430 Several studies suggest that intraguild predation by generalists on specialist predators can lead
431 to herbivore communities being released from predation (e.g. Hodge, 1999; Rosenheim,
432 Wilhoit and Armer, 1993; Snyder and Ives, 2001). However, our analysis would suggest that
433 the combination of both generalist and specialist predators in polyculture treatments can lead
434 to greater prey suppression than the mean of the component species. A number of mechanisms
435 are proposed for this; firstly, complementary predation may occur between a generalist
436 predator and specialist parasitoids where the predator prefers feeding on alternate or
437 unparasitised prey, thus minimising intraguild predation on the parasitoid (Cardinale et al.,
438 2003; Snyder et al., 2004). Secondly, it is possible that spatial resource partitioning commonly
439 occurs between generalist and specialist predators feeding on different parts of the plant
440 (Northfield et al., 2010; Gable et al., 2012). Consequently, our metric of diet breadth may have
441 captured more subtle separation in predator feeding locations between specialist and generalists
442 that were not captured by broader distinction within the habitat domain category. Thirdly,
443 through sampling effects alone, a polyculture containing both specialist and generalist
444 predators may lead to greater prey suppression when compared to the mean of the component
445 species, due to inclusion of the most effective predator. Thus, in our analysis, this may have
18 Ecology Page 20 of 94
446 led to polycultures with increased diversity in the diet breadth category causing greater prey
447 depletion than the mean of the component predator species. Where this occurs positive
448 sampling effects cannot be ruled out. This mechanism is supported by empirical evidence from
449 Straub and Snyder (2006), who found that the inclusion of an aphid specialist within
450 polycultures led to significantly greater aphid depletion than communities without the
451 specialist present. Finally, communities made up of both generalist and specialist predators
452 may provide more stable herbivore control than monocultures of either type of predator alone 453 due to the insurance hypothesisFor (Snyder Review et al., 2006) .Only 454
455 When we compared polycultures to the most effective predator, none of the single traits (diet
456 breadth, habitat domain and hunting strategy) had a clear effect on prey suppression. Instead,
457 only the composite measure of the functional diversity FD had a positive effect. Functional
458 diversity based on these traits is likely to reflect broad niche partitioning between predators
459 leading to fewer antagonistic interactions, and greater exploitation of available resources (Ives
460 et al. 2004; Finke & Snyder 2008; Northfield et al. 2010; Gontijo et al. 2015; Northfield,
461 Barton and Schmitz., 2017). Previous meta analyses by Cardinale et al. (2006) and Griffin,
462 Byrnes & Cardinale (2013) found that increased predator species richness provided greater
463 prey suppression than the mean of the component species, but not to a greater extent than the
464 most effective predator. The results of our main meta-analysis are consistent with these studies,
465 however, we have built on this previous research to suggest conditions under which predator
466 polycultures can provide greater prey suppression than the most effective predator, as a result
467 of functional diversity effects mediated through aggregate effects traits. Griffin, Byrnes &
468 Cardinale (2013) used taxonomic distinctness (similar to our measure of phylogenetic
469 diversity) as a proxy for functional diversity and found it had a positive effect on prey
470 suppression in polycultures when compared to the mean of the component species, but not
19 Page 21 of 94 Ecology
471 when compared to the most effective predator. In our analysis, when phylogeny was decoupled
472 from aspects of FD it was found to have no clear effect on prey suppression, supporting our
473 third prediction that PD has a smaller effect on prey suppression than FD. One of the reasons
474 that phylogeny was not identified as an important driver of prey suppression may be because
475 only a few effect traits impact on prey suppression in the context of mesocosm studies, all of
476 which were accounted for through the used metric of FD. Phylogenetic diversity is often used
477 as surrogate to represent all functional differences between species, however the variation 478 explained by the key effectsFor traits canReview be concealed by Only irrelevant traits also encompassed within 479 the metric, which are a result of divergent evolutionary histories. This has led to contradicting
480 results from other studies. For example, a study by Rusch et al. (2015) found that functional
481 traits selected a priori, based on their link to prey suppression, better predicted aphid pest
482 control compared to a taxonomic approach. Whereas a study by Bell et al. (2008) selected
483 broad ranging functional traits that were incorporated into a single metric and had little effect
484 in predicting the predation rates of a range of invertebrate predators compared to using
485 taxonomy. Therefore, careful consideration of appropriate functional traits would appear
486 imperative to discerning biodiversity and ecosystem functioning relationships where multiple
487 traits are incorporated into a single metric. Furthermore, the relative usefulness of phylogenetic
488 diversity/taxonomic approaches in predicting ecosystem services are also limited by the fact
489 that they do not allow a direct link between traits and a function to be ascertained. This does
490 not preclude the importance of phylogeny between species being of general importance,
491 however in the case of prey suppression where appropriate traits were identified PD did not
492 have a clear effect.
493
494 Previous literature suggests that hunting mode and habitat domain play important roles in
495 emergent impacts on prey suppression. However, in the current meta-analysis neither trait was
20 Ecology Page 22 of 94
496 identified to be individually important. The absence of detected effects of these traits within
497 this meta-analysis may be due to limitations in the data set. For example, biases in the source
498 data meant that ‘sit and wait’ and ‘mobile-active’ predators occurring within the same habitat
499 made up a small proportion (18%) of the studies included in the analysis. This would limit the
500 capacity of the analysis to differentiate between effects of these hunting modes. A further issue
501 may relate to the resolution with which broad habitat categorisations capture fine scale
502 differences in predator’s habitat use in diverse systems (as considered here). It is possible that 503 while the application of huntingFor domain Review and habitat domainOnly to predict overyielding is effective, 504 its definition within these categories needs to be defined on a community by community basis.
505 Independent of these issues linked to limitations in the data, our results still suggest that broad
506 niche differentiation through FD leads to overyielding. It is highly likely that this is at least in
507 part a function of complementarity between predators within combinations of habitat domain,
508 hunting mode and/or the diet preferences. This study ultimately provides evidence for the
509 importance of predator functional diversity as a prerequisite for effective pest control across
510 compositionally different predator-prey systems. However, pulling apart the exact nature of
511 the mechanisms that underpin this will be dependent on new methodological approaches to
512 classification of factors like hunting strategy and habitat domain that allow for making high
513 resolution comparisons between fundamentally different predator-prey systems. Northfield,
514 Barton and Schmitz, (2017) present a spatially explicit theory to describe predator interactions
515 across landscapes that is not dependent on temporal or spatial scale. They suggest that where
516 there is complete overlap in spatial resource utilisation between predators, antagonistic
517 interactions are likely to decrease the capacity of predators to suppress herbivore prey. Our
518 results, whilst not from a spatially explicit standpoint, also broadly suggest that separate
519 resource utilisation by predators will promote positive intraguild interactions across diverse
520 systems.
21 Page 23 of 94 Ecology
521
522 In contradiction to our fourth prediction, we found an increase in the body size ratio between
523 the smallest predator and prey species had a negative impact on prey suppression in
524 polycultures, although there was large variation within this result. This is surprising as
525 consumption rates and handling times are predicted to be larger and smaller, respectively,
526 where the size difference between a predator and its prey is large (Petchey et al. 2008; Ball et
527 al. 2015). A possible explanation is that as animals with larger body sizes tend to consume prey 528 with a wider range of bodyFor sizes Review(Cohen et al. 1993), Only top generalist predators may consume 529 smaller predators as well as prey where the difference in energy gain between prey items is
530 large (Heithaus, 2001; Lima, 2002). However, it could have been expected that the size
531 difference variable between predators would have had a greater effect in our analysis. Size
532 differences between predators may become more important where predators occupy the same
533 habitat and show little specialisation in diet breadth. For example, Rusch et al., (2015) found
534 that size differences weakened pest suppression in predatory ground beetles, which not only
535 occur in the same habitat domain but are also generalist predators.
536
537 Our meta-analysis highlights the importance of trait identification when discerning the
538 relationships between biodiversity and ecosystem functioning, i.e. true effects traits like diet
539 breadth, hunting strategy and habitat domain as used in this study that have been shown in
540 quantitative research to play a direct role in the provision of an ecosystem service (Losey &
541 Denno 1998; Schmitz 2007; Straub et al. 2008; Woodcock & Heard 2011; Ball et al. 2015).
542 Understanding how species will respond to environmental perturbation through key response
543 traits and how this will in turn affect functioning through fluctuations in effects traits is
544 important in ascertaining the stability of ecosystem services in a changing environment
545 (Jonsson et al., 2017; Oliver et al. 2015; Perović et al. 2017). Theoretically, where FD is
22 Ecology Page 24 of 94
546 concomitant with redundancy amongst predators and there is little correlation between
547 response and effects traits, this should provide greater stability of pest control ecosystem
548 services (Oliver et al. 2015). This is because systems are more resilient to the loss of individual
549 predators as long as their functions are maintained within the ecosystem (Oliver et al. 2015).
550 However, whilst redundancy should theoretically lead to greater ecosystem service stability,
551 this does not always occur. For example, functional redundancy between parasitoids species
552 was not found to improve the temporal stability of parasitism rates, with food web connectivity 553 appearing more importantFor in stability Review (Peralta et al., Only 2014). Consequently, more research is 554 needed to determine the role of FD and functional redundancy in ecosystem service stability.
555
556 Of the experimental variables, only study design (additive vs substitutive) had a significant
557 effect on prey suppression. Prey suppression in polycultures compared to monocultures was
558 lower in substitutive than additive designs. The predominant reason for this could be that higher
559 predator density in additive experimental polycultures may increase prey suppression where
560 predation rates are density dependant and intraspecific interactions between heterospecific
561 predators are neutral or positive (Griffen 2006). Importantly, this also highlights the possibility
562 that increasing predator density within agro-ecosystems has beneficial effects on pest
563 suppression.
564
565 Conclusion
566 Our results suggest that maximising functional diversity in predatory invertebrates within
567 agricultural ecosystem will improve natural pest control. Relatively simple management
568 measures, such as the inclusion of tussock-forming grasses in buffer strips surrounding crop
569 fields, have been found to increase the FD of ground beetle assemblages on arable farmland
570 (Woodcock et al. 2010). However, it is currently difficult to advocate single management
23 Page 25 of 94 Ecology
571 options as other field margin types, such as grass leys, have conversely been found to increase
572 the functional similarity in spider communities (Rusch et al. 2014). It is therefore likely that
573 habitat complexity plays an important role with a diversity of non-crop habitats needed to
574 promote FD across a wide range of predators (Woodcock et al. 2010; Lavorel et al., 2013;
575 Rusch et al. 2016). However, it is difficult to ascertain the precision with which this can be
576 achieved in practice. Whilst mesocosms are useful for identifying basic species interactions
577 they represent a simplified environment. Real-world agricultural ecosystems are host to an 578 array of predator and pestFor species Review with complex life Onlycycles. Mesocosm studies fail to account 579 for fluctuations in predator numbers/assemblages both spatially and temporally. Therefore,
580 traits related to phenology and dispersal are likely to be relevant in field conditions and would
581 be important to consider in any management practices (Landis, Wratten and Gurr, 2000). The
582 results of our meta-analysis fall short of identifying a generalizable rule across all predator
583 interactions that lead to overyielding. However, the findings do highlight the need to quantify
584 how important context is, in terms of predator community assemblage and habitat, in
585 determining which trait combinations promote beneficial effects from functional diversity for
586 pest control ecosystem services. Future studies should aim to identify complimentary sets of
587 traits within different predator communities to determine whether certain trait combinations
588 consistently lead to overyielding, or whether the context dependency of differing predator
589 communities and habitat means that the importance of different trait combinations fluctuates
590 depending on the ecological setting. As we found no clear effects of individual traits, and only
591 our overall metric of FD affected overyielding, our results would suggest that the latter is more
592 likely. However, further research is required in realistic field based studies to determine this.
593
594 Acknowledgements
24 Ecology Page 26 of 94
595 We would like to thank all the authors who contributed primary data to the meta-analysis, and
596 Jonathan Storkey and Andreas Cecelja and two anonymous reviewers for additional comments
597 which helped improve the manuscript. We would also like to thank Eve Roubinet for help with
598 identifying studies and discussion around the subject. This study was supported by the Centre
599 for Ecology & Hydrology, Rothamstead Research and Lancaster University. The research was
600 also supported by the Natural Environment Research Council (NERC) and the Biotechnology
601 and Biological Sciences Research Council (BBSRC) under research programme 602 NE/N018125/1LTS-M For ASSIST Review – Achieving Only Sustainable Agricultural Systems 603 www.assist.ceh.ac.uk.
604
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833 834 Rosenheim, J.A., Glik, T.E., Goeriz, R.E. & Rämert, B. (2004a). Linking a predator’s 835 foraging behavior with its effects on herbivore population suppression. Ecology, 85, 3362– 836 3372. 837 838 Rosenheim, J.A., Limburg, D.D., Colfer, R.G., Fournier, V., Hsu, C.L., Leonardo, T.E., et al. 839 (2004b). Herbivore population suppression by an intermediate predator, Phytoseiulus 840 macropilis, is insensitive to the presence of an intraguild predator: an advantage of small 841 body size? Oecologia, 140, 577–585. 842 843 Rusch, A., Birkhofer, K., Bommarco, R., Smith, H.G. & Ekbom, B. (2014). Management 844 intensity at field and landscape levels affects the structure of generalist predator communities. 845 Oecologia, 175, 971–983. 846 847 Rusch, A., Chaplin-Kramer, R., Gardiner, M.M., Hawro, V., Holland, J., Landis, D., et al. 848 (2016). Agricultural landscape simplification reduces natural pest control: A quantitative 849 synthesis. Agriculture, Ecosystems & Environment, 221, 198–204. 850 851 Schmid, B., Hector, A., Saha, P. & Loreau, M. (2008). Biodiversity effects and transgressive 852 overyielding. Journal of Plant Ecology, 1, 95–102. 853 854 Schmitz, O.J. (2007). Predator diversity and trophic interactions. Ecology, 88, 2415–2426. 855 856 Sih, A., Englund, G. & Wooster, D. (1998). Emergent impacts of multiple predators on prey. 857 Trends in Ecology and Evolution, 13, 350–355. 858 859 Snyder, W.E. and Ives, A.R. (2001). Generalist predators disrupt biological control by a 860 specialist parasitoid. Ecology, 82, 705-716. 861
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862 Snyder, W.E., Ballard, S.N., Yang, S., Clevenger, G.M., Miller, T.D., Ahn, J.J., Hatten, T.D. 863 and Berryman, A.A. (2004). Complementary biocontrol of aphids by the ladybird beetle 864 Harmonia axyridis and the parasitoid Aphelinus asychis on greenhouse roses. Biological 865 Control, 30, 229-235 866 867 Snyder, W.E., Snyder, G.B., Finke, D.L. & Straub, C.S. (2006). Predator biodiversity 868 strengthens herbivore suppression. Ecology Letters, 9, 789–796.
869 870 Straub, C.S., Finke, D.L. & Snyder, W.E. (2008). Are the conservation of natural enemy 871 biodiversity and biological control compatible goals? Biological Control, 45, 225–237. 872 873 Straub, C.S. & Snyder, W.E. (2006). Species identity dominates the relationship between 874 predator biodiversity and herbivore suppression. Ecology, 87, 277–282. 875 876 Tylianakis, J.M. & Romo,For C.M. (2010).Review Natural enemy Only diversity and biological control: 877 Making sense of the context-dependency. Basic and Applied Ecology, 11, 657–668. 878 879 Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. J. Stat. 880 Softw., 36, 1-48. URL: http://www.jstatsoft.org/v36/i03/ 881 882 Wilby, A. & Orwin, K.H. (2013). Herbivore species richness, composition and community 883 structure mediate predator richness effects and top-down control of herbivore biomass. 884 Oecologia, 172, 1167–1177. 885 886 Wilby, A. & Thomas, M.B. (2002). Natural enemy diversity and pest control: patterns of pest 887 emergence with agricultural intensification. Ecology Letters, 5, 353–360. 888 889 Wilby, A., Villareal, S.C., Lan, L.P., Heong, K.L. & Thomas, M.B. (2005). Functional 890 benefits of predator species diversity depend on prey identity. Ecological Entomology, 30, 891 497–501. 892 893 Wilson, C. & Tisdell, C. (2001). Why farmers continue to use pesticides despite 894 environmental, health and sustainability costs. Ecological Economics, 39, 449–462. 895 896 Wood, S.A., Karp, D.S., DeClerck, F., Kremen, C., Naeem, S. & Palm, C.A. (2015). 897 Functional traits in agriculture: agrobiodiversity and ecosystem services. Trends in Ecology 898 Evolution, 30, 531–539. 899 900 Woodcock, B.A., Bullock, J.M., Shore, R.F., Heard, M.S., Pereira, M.G., Redhead, J., et al. 901 (2017). Country-specific effects of neonicotinoid pesticides on honey bees and wild bees. 902 Science, 356, 1393–1395. 903 904 Woodcock, B.A. & Heard, M.S. (2011). Disentangling the effects of predator hunting mode 905 and habitat domain on the top-down control of insect herbivores. Journal of Animal Ecology, 906 80, 495–503. 907
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908 Woodcock, B.A., Isaac, N.J.B., Bullock, J.M., Roy, D.B., Garthwaite, D.G., Crowe, A., et al. 909 (2016). Impacts of neonicotinoid use on long-term population changes in wild bees in 910 England. Nature Communications, 7, 12459. 911 912 Woodcock, B.A., Redhead, J., Vanbergen, A.J., Hulmes, L., Hulmes, S., Peyton, J., et al. 913 (2010). Impact of habitat type and landscape structure on biomass, species richness and 914 functional diversity of ground beetles. Agriculture, Ecosystems & Environment, 139, 181– 915 186. 916 917 Woodcock, B.A., Savage, J., Bullock, J.M., Nowakowski, M., Orr, R., Tallowin, J.R.B., et al. 918 (2013). Enhancing beetle and spider communities in agricultural grasslands: The roles of seed 919 addition and habitat management. Agriculture, Ecosystems & Environment, 167, 79–85. 920 921 For Review Only 922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
32 Ecology Page 34 of 94
943 Table 1. Species variables included in analysis. Variable Measure Description Functional diversity Continuous Mean pairwise functional dissimilarity (FD) between species in each experiment based on the traits included in Appendix S3 (excluding body size). Hunting strategy Continuous Mean pairwise dissimilarity between species in each experiment based on hunting (sit and wait, ambush and pursue or active). Habitat domain Continuous Mean pairwise dissimilarity between species in each experiment based on habitat (ground/base of plant, foliar or broad). Diet breadth ForContinuous Review OnlyMean pairwise dissimilarity between species in each experiment based on diet breadth (specialist or generalist). Phylogenetic Continuous Mean pairwise phylogenetic diversity (PD) dissimilarity between species based on Linnaean taxonomic classification decoupled from the functional traits. ratiolarge Continuous Body size ratio between the largest predator species and the prey species (largest predator body size/prey body size). Sqrt transformed. *Excluded from analysis. ratiosmall Continuous Body size ratio between the smallest predator species in the polyculture and the prey species (smallest predator body size/prey body size). Sqrt transformed. Size difference Continuous Mean pairwise difference in body size (length in mm) between predator species in each experiment. Prey size (mm) Continuous Body length of the prey. Where multiple prey were included in a treatment the mean of their body sizes was used. Log transformed. Predator species Factor (2 or >2) Two level factor categorising richness polyculture treatments on whether they contained two predators or more than two predators (max predator species richness = 4). Prey species richness Factor (1 or >1) Two level factor categorising whether one or more than one prey species was present in the study (max prey species richness = 4). 944
33 Page 35 of 94 Ecology
945 Table 2. Multimodel average parameter estimates for SMDmean (predator polyculture
946 compared to the mean of the component predator species in monocultures) and SMDmax
947 (predator polyculture compared to the most effective predator species in a monoculture). Prey
948 richness and predator richness estimate is the difference between the reference level (predator
949 richness = 2 species; prey richness = 1). Parameters in bold indicate that the variable was
950 included in the highest ranked model.
Metric Parameter Estimate Importance 95% CI lower 95% CI upper bound bound SMDmean For Review Only Prey richness >1 0.007 0.062 -0.033 0.047 Predator richness >2 0.011 0.120 -0.044 0.066 Prey size -0.011 0.133 -0.062 0.04 Phylogenetic 0.099 0.233 -0.284 0.482 diversity Size difference -0.008 0.320 -0.035 0.019 ratiosmall -0.080 0.336 -0.344 0.184 Functional diversity 0.448 1.000 0.065 0.831
SMDmax Phylogenetic 0.038 0.122 -0.147 0.223 diversity Prey size -0.032 0.211 -0.149 0.085 Size difference -0.005 0.245 -0.026 0.016 ratiosmall -0.282 0.747 -0.754 0.190 Predator richness >2 -0.276 1.000 -0.541 -0.011 Functional diversity 0.461 1.000 0.049 0.873 951
952
953
954
955
956
957
958
959
960
34 Ecology Page 36 of 94
961 Table 3. Tests for experimental moderator variables. Parameter estimates are shown for
962 continuous variables. Categorical variable estimate is the reference level then the difference
963 between the other levels of the factor. QM statistic is the omnibus test for the factors and
964 Wald z-tests show differences between levels. SMDmean is predator polyculture compared to
965 the mean of the component predator species in monocultures. SMDmax is the predator
966 polyculture compared to the most effective predator species in a monoculture.
Metric Factor n Estimate 95% CI 95% CI QM df P-value lower upper For Reviewbound Only bound SMDmean Log cage 186 0.049 -0.018 0.116 2.084 1 0.149 volume (cm3) Duration of 209 -0.0002 -0.001 0.0002 0.892 1 0.345 study (hours) Design 3.188 1 0.074 Additive 99 0.569 0.341 0.797 (reference) Substitutive 115 -0.277 -0.581 0.027 0.074
Study setting 0.191 1 0.662 Field (reference) 89 0.487 0.222 0.752 Lab/Greenhouse 125 -0.072 -0.393 0.250 0.662 SMDmax Log cage 186 0.037 -0.036 0.109 0.988 1 0.320 volume (cm3) Duration of 209 -0.0002 -0.001 0.0003 0.707 0.401 study (hours) Design 9.351 1 0.002 Additive 99 0.122 -0.136 0.379 (reference) Substitutive 115 -0.519 -0.852 -0.186 0.002 Study setting 0.003 1 0.955 Field (reference) 89 -0.104 -0.392 0.185 Lab/Greenhouse 125 -0.010 -0.353 0.333 0.955 967
968
969
970
971
972
35 Page 37 of 94 Ecology
973 Figure 1. Multimodel average parameter estimates for SMDmean (predator polyculture
974 compared to the mean of the component predator species in monocultures); lines indicate
975 ±95% confidence intervals. Predator richness and prey richness are factors and show the
976 difference between the reference level (reference level for predator richness = 2 species and
977 prey richness = 1 species).
978
979 Figure 2. Multimodel average parameter estimates for SMDmax (predator polyculture 980 compared to the most effectiveFor predator Review species in a Onlymonoculture); lines indicate ±95% 981 confidence intervals. Predator richness is the difference between the reference level (predator
982 richness = 2 species).
983
984 Figure 3. SMDmax (predator polyculture compared to the most effective predator species in a
985 monoculture) for additive (n = 99) and substitutive (n = 115) designs; lines indicate ±95%
986 confidence intervals.
987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001
36 Ecology Page 38 of 94
1002 Figure 1
SMDmean 1.000
0.800
0.600 Functional 0.400 Prey richness >1 Phylogenetic diversity diversity 0.200
0.000
-0.200 Predator richness Size >2 Prey size ratiosmall -0.400 For Review Onlydifference Multimodel average paramter estimates paramter average Multimodel -0.600 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024
37 Page 39 of 94 Ecology
1025 Figure 2
SMDmax 1.000 0.800 0.600 Functional 0.400 Phylogenetic diversity diversity Size difference 0.200 0.000 -0.200 Prey size -0.400 Predator richness >2 -0.600 ratiosmall -0.800 For Review Only Multimodel average paramter estimates paramter average Multimodel -1.000 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047
38 Ecology Page 40 of 94
1048 Figure 3
0.6
0.4
0.2
0 max
-0.2 SMD
-0.4 -0.6 For Review Only -0.8 1049 Additive Substitutive 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061
39 Page 41 of 94 Ecology
Appendix S1 Search terms used in web of science: (predator OR predation OR natural enemy OR parasitoid) AND (richness OR biodiversity OR diversity) AND (pest OR prey OR suppression OR biocontrol OR biological control OR ecosystem function* OR ecosystem process* OR diversity-function) AND (insect* or invertebrate*) AND (experiment OR experimental OR manipulation) (predator OR predation OR natural enemy OR parasitoid) AND (pest OR prey OR suppression OR biocontrol OR biological control OR ecosystem function* OR ecosystem process* OR diversity-function) AND (insect* or invertebrate*) AND (experiment OR experimental OR manipulation OR cage OR mesocosm)
For Review Only
Ecology Page 42 of 94
Appendix S2
Studies included in the meta-analysis.
Acheampong, S. & Stark, J.D. (2004). Can reduced rates of pymetrozine and natural enemies control the cabbage aphid, Brevicoryne brassicae (Homoptera: Aphididae), on broccoli? International Journal of Pest Management, 50, 275–279. Alhmedi, A., Haubruge, E. & Francis, F. (2010). Intraguild interactions and aphid predators: biological efficiency of Harmonia axyridis and Episyrphus balteatus. Journal of Applied Entomology, 134, 34–44. Ajvad, F.T., Madadi, H. and Gharali, B. (2014). Influence of intraguild predation between Episyrphus balteatus and Hippodamia variegata on their prey. Arch. Phytopathol. Plant Protection, 47, 106-112.For Review Only Aquilino, K.M., Cardinale, B.J. & Ives, A.R. (2005). Reciprocal effects of host plant and natural enemy diversity on herbivore suppression: an empirical study of a model tritrophic system. Oikos, 108, 275–282. Asiry, K.A.M. (2011). The impacts of cereal-legume intercropping on biological control of cereal aphids within temperate agro-ecosystems. Doctoral Thesis. University of Reading. Ball, S.L., Woodcock, B.A., Potts, S.G. & Heard, M.S. (2015). Size matters: Body size determines functional responses of ground beetle interactions. Basic and Applied Ecology, 16, 621–628. Bjorkman, C. & Liman, A.-S. (2005). Foraging behaviour influences the outcome of predator-predator interactions. Ecological Entomology, 30, 164–169. Cardinale, B.J., Harvey, C.T., Gross, K. & Ives, A.R. (2003). Biodiversity and biocontrol: emergent impacts of a multi-enemy assemblage on pest suppression and crop yield in an agroecosystem. Ecology Letters, 6, 857–865. Cardinale, B.J., Weis, J.J., Forbes, A.E., Tilmon, K.J. & Ives, A.R. (2006). Biodiversity as both a cause and consequence of resource availability: a study of reciprocal causality in a predator-prey system. Journal of Animal Ecology, 75, 497–505. Chang, G.C. (1996). Comparison of Single Versus Multiple Species of Generalist Predators for Biological Control. Environmental Entomology, 25, 207–212. Cisneros, J. & Rosenheim, J. (1997). Ontogenetic change of prey preference in the generalist predator Zelus renardii and its influence on predator-predator interactions. Ecological Entomology, 22, 399–407. Denno, R.F., Mitter, M.S., Langellotto, G.A., Gratton, C. & Finke, D.L. (2004). Interactions between a hunting spider and a web-builder: consequences of intraguild predation and cannibalism for prey suppression. Ecological Entomology, 29, 566–577. Page 43 of 94 Ecology
Drieu, R. and Rusch, A. (2016). Conserving species‐rich predator assemblages strengthens natural pest control in a climate warming context. Agricultural and Forest Entomology, 19, 52-59. Dinter, A. (2002). Microcosm studies on intraguild predation between female erigonid spiders and lacewing larvae and influence of single versus multiple predators on cereal aphids. Journal of Applied Entomology, 126, 249-257. Erbilgin, N., Dahlsten, D.L. & Chen, P. (2004). Intraguild interactions between generalist predators and an introduced parasitoid of Glycaspis brimblecombei (Homoptera: Psylloidea). Biological Control, 31, 329–337. Evans, E.W. (1991). Intra versus interspecific interactions of ladybeetles (Coleoptera: Coccinellidae) attacking aphids. Oecologia, 87, 401–408. Fennel, J. (2013). Does host-plant nutrient supply affect the interaction of arthropod predators in a multi-species assemblage?For UnpublishedReview dissertation. Only Lancaster University. Ferguson, K.I. & Stiling, P. (1996). Non-additive effects of multiple natural enemies on aphid populations. Oecologia, 108, 375–379. Finke, D.L. & Denno, R.F. (2002). Intraguild Predation Diminished in Complex-Structured Vegetation: Implications for Prey Suppression. Ecology, 83, 643. Finke, D.L. & Denno, R.F. (2003). Intra-guild predation relaxes natural enemy impacts on herbivore populations. Ecological Entomology, 28, 67–73. Finke, D.L. & Denno, R.F. (2005). Predator diversity and the functioning of ecosystems: the role of intraguild predation in dampening trophic cascades. Ecology Letters, 8, 1299–1306. Flowers, R.W., Salom, S.M. & Kok, L.T. (2005). Competitive Interactions Among Two Specialist Predators and a Generalist Predator of Hemlock Woolly Adelgid, Adelges tsugae (Homoptera: Adelgidae), in the Laboratory. Environmental Entomology, 34, 664–675. Gable, J.T., Crowder, D.W., Northfield, T.D., Steffan, S.A. and Snyder, W.E., (2012). Niche engineering reveals complementary resource use. Ecology, 93, 1994-2000. Gardiner, M.M. & Landis, D.A. (2007). Impact of intraguild predation by adult Harmonia axyridis (Coleoptera: Coccinellidae) on Aphis glycines (Hemiptera: Aphididae) biological control in cage studies. Biological Control, 40, 386–395. Hogg, B.N. and Daane, K.M. (2011). Diversity and invasion within a predator community: impacts on herbivore suppression. Journal of Applied Ecology, 48, 453-461. Hogg, B.N. & Daane, K.M. (2014). The roles of top and intermediate predators in herbivore suppression: contrasting results from the field and laboratory. Ecological Entomology, 39, 149–158. Hogg, B.N. & Daane, K.M. (2015). Cascading effects of cannibalism in a top predator. Ecological Entomology, 40, 805–813. Ecology Page 44 of 94
Hogg, B.N., Wang, X.-G., Levy, K., Mills, N.J. & Daane, K.M. (2013). Complementary effects of resident natural enemies on the suppression of the introduced moth Epiphyas postvittana. Biological Control, 64, 125–131. Lester, P.J. & Harmsen, R. (2002). Functional and numerical responses do not always indicate the most effective predator for biological control: an analysis of two predators in a two-prey system. Journal of Applied Ecology, 39, 455–468. Losey, J.E. & Denno, R.F. (1998). Positive Predator-Predator Interactions: Enhanced Predation Rates and Synergistic Suppression of Aphid Populations. Ecology, 79, 2143-2152 Lucas, É. & Alomar, O. (2002). Impact of the presence of Dicyphus tamaninii Wagner (Heteroptera: Miridae) on whitefly (Homoptera: Aleyrodidae) predation by Macrolophus caliginosus (Wagner) (Heteroptera: Miridae). Biological Control, 25, 123–128. Mallampalli, N., Castellanos, I. & Barbosa, P. (2002). Evidence for intraguild predation by Podisus maculiventrisFor on a ladybeetle, Review Coleomegilla maculata:Only Implications for biological control of Colorado potato beetle, Leptinotarsa decemlineata. BioControl, 47, 387-398 Lewins, S.A. (2006). The Influence of Predator Species Richness on Prey Mortality: Implications to Conservation Biological Control. Unpublished Masters Thesis. University of Maryland Moreno-Ripoll, R., Gabarra, R., Symondson, W.O.C., King, R.A. and Agustí, N. (2014). Do the interactions among natural enemies compromise the biological control of the whitefly Bemisia tabaci?. Journal of Pest Science, 87, 133-141. Northfield, T.D., Snyder, G.B., Ives, A.R. & Snyder, W.E. (2010). Niche saturation reveals resource partitioning among consumers. Ecology Letters, 13, 338–348 Obrycki, J.J., Giles, K.L. & Ormond, A.M. (1998). Experimental assessment of interactions between larval Cole-omegilla maculata and Coccinella septempunctata (Coleoptera : Coccinellidae) in field cages. Environmental Entomology, 27, 1280–1288. Rosenheim, J.A. (2001). Source-Sink Dynamics for a Generalist Insect Predator in Habitats with Strong Higher-Order Predation. Ecological Monographs, 71, 93-116 Rosenheim, J.A., Limburg, D.D., Colfer, R.G., Fournier, V., Hsu, C.L., Leonardo, T.E. & Nelson, E.H. (2004a). Herbivore population suppression by an intermediate predator, Phytoseiulus macropilis, is insensitive to the presence of an intraguild predator: an advantage of small body size? Oecologia, 140, 577–585. Rosenheim, J.A., Glik, T.E., Goeriz, R.E. & Rämert, B. (2004b). Linking a predator’s foraging behavior with its effects on herbivore population suppression. Ecology, 85, 3362– 3372. Rosenheim, J.A., Wilhoit, L.R. & Armer, C.A. (1993). Influence of intraguild predation among generalist insect predators on the suppression of an herbivore population. Oecologia, 96, 439–449. Page 45 of 94 Ecology
Roubinet, E., Straub, C., Jonsson, T., Staudacher, K., Traugott, M., Ekbom, B. & Jonsson, M. (2015). Additive effects of predator diversity on pest control caused by few interactions among predator species. Ecological Entomology, 40, 362–371. Sigsgaard, L. (2007). Early season natural control of the brown planthopper, Nilaparvata lugens: the contribution and interaction of two spider species and a predatory bug. Bulletin of Entomological Research, 97, 533–544. Snyder, W.E. & Wise, D.H. (2001). Antipredator behavior of spotted cucumber beetles (Coleoptera : Chrysomelidae) in response to predators that pose varying risks. Environmental Entomology, 29, 35–42. Snyder, W.E., Snyder, G.B., Finke, D.L. & Straub, C.S. (2006). Predator biodiversity strengthens herbivore suppression. Ecology Letters, 9, 789–796. Sokol-Hessner, L. & Schmitz, O.J. (2002). Aggregate Effects of Multiple Predator Species on a Shared Prey. EcologyFor, 83, 2367-2372 Review Only Werling, B.P., Lowenstein, D.M., Straub, C.S. & Gratton, C. (2012). Multi-predator effects produced by functionally distinct species vary with prey density. Journal of Insect Science, 12, 1-7 Wilby, A., Anglin, L.A. & Nesbit, C.M. (2013). Plant species composition alters the sign and strength of an emergent multi-predator effect by modifying predator foraging behaviour. Plos One, 8, e70258. Wilby, A. & Orwin, K.H. (2013). Herbivore species richness, composition and community structure mediate predator richness effects and top-down control of herbivore biomass. Oecologia, 172, 1167–1177. Wilby, A., Villareal, S.C., Lan, L.P., Heong, K.L. & Thomas, M.B. (2005). Functional benefits of predator species diversity depend on prey identity. Ecological Entomology, 30, 497–501. Wiethoff, J., Poehling, H.M. & Meyhofer, R. (2004). Combining plant- and soil-dwelling predatory mites to optimise biological control of thrips. Experimental and Applied Acarology, 34, 239–261. Yasuda, H. & Kimura, T. (2001). Interspecific interactions in a tri-trophic arthropod system: effects of a spider on the survival of larvae of three predatory ladybirds in relation to aphids. Experimental and Applied Acarology., 98, 17–25.
Ecology Page 46 of 94
For Review Only
Carabidae. Definition Definition Predator actively searches and pursues prey. Example Example and prey. pursues actively searches Predator specialisation feeding or no with little diet Broad arthropod Predator species that predominantly hunt on plant foliage. foliage. on plant hunt that Predator predominantly species Miridae. and Coccinellidae Example the around the or ground hunt on predominantly Predators that ground and foliar to hunt in both are likely Predators that and Phalangiidae. Lycosidae domains. Examples pursuing to actively as opposed for prey waits Predator species a once actively and pursues then for prey waits Predator species Cocinnellidae. Example species. herbivore for particular a documented Lycosidae. species, herbivore particular for Specialisation documented intraguild not preclude does categorisation however this in species predator of the stage life across the Mean length body mm. base of plant. Example Example base plant. of species. Nabis prey. Examples species. Misumenops Example identified. prey been item has also includes category species. alternate prey This predation or Phytoseiulus. Example parasitoid species. Ecology
Active Generalist ForFoliar or plant Ground (BPG) base of Review Broad Sit (SW) and wait and pursue Ambush (AP) Only Specialist
Species functional trait categories and their definitions. and definitions. their categories trait functional Species Diet breadth S3 Appendix meta included in the ofthe each species for categorisations trait are the shown Also definitions. their and traits functional Table species of analysis. Table 1. Trait Habitat domain strategy Hunting Categories Body size (mm) Page 47 of 94 Page 48 of 94
J. J. J. .45 50. .45 50. .45 50. spotted spotted spotted ‐ ‐ 90, 90, , , . [Accessed . [Accessed Amblyseius 465 474. 465 474. Mid-Atlantic orchard Mid-Atlantic . [online] Available at: at: . Available [online] 465 474. 465 474. , , , . Ithaca, N.Y. Northeast Northeast N.Y. . Ithaca, 129 Eur. J. Entomol. Eur. J. Entomol. Eur. 129 , , , fallacis Agarwala, B.K. and Dixon, A.F. (1993). Kin Kin (1993). A.F. and B.K.Dixon, Agarwala, Agarwala, B.K. and Dixon, A.F. (1993). Kin Kin (1993). A.F. and B.K.Dixon, Agarwala, in and larval egg cannibalism recognition: (Coleoptera: Adalia bipunctata Coccinellidae). of two Ecology (2005). A. Pervez, a review. bipunctata: ladybird, Adalia in and larval egg cannibalism recognition: (Coleoptera: Adalia bipunctata Coccinellidae). of two Ecology (2005). A. Pervez, a review. bipunctata: ladybird, Adalia (2017). Appliedbio nomics. content/uploads/201 fallacis.pdf 4 Jul. 2017]. Hogmire, (1995). H. guide monitoring Service, Agricultural Engineering Regional https://www.appliedbio nomics.com/wp
(Neoseiulus) (Neoseiulus) Appl. Appl. Entomol. Appl. Entomol
4.5 0.5 3.25 Size (mm) Size (mm) Ref
Active Hunting Hunting strategy Ecology
Foliar domain domain
For Review Only Specialist
Ab_l Ab_a Specialist Foliar Active Af Specialist Foliar Active All the species included in the studies used in the meta analysis; their code used in analysis; trait categorisations for diet breadth, diet breadth, for categorisations in trait analysis; used code their meta analysis; in the used studies in the included species the All (adult) (adult) Table 2. Table 2. information. for trait used and sources (mm); body size mean and habitat strategy domain; hunting Predator Code Diet breadth Habitat (larvae) Adalia bipunctata Adalia bipunctata Adalia bipunctata Adalia bipunctata Amblyseius fallacis , , 627 14 , , , 46 54. , 46 54. Ecol. Ecol. 53 , Experimental Experimental
, 34, 239–261. 34, , 239–261.
Biol.l Control. Biol.l Biocontrol Sci.Techn Biocontrol , 49 158. , 49 158. 39 , , Cooperative Extension. Cooperative Extension. Evergreen Growers Supply. (2017). Supply. (2017). Growers Evergreen Available [online] cucumeris. Amblyseius at: https://www.evergreengrowers.com/thrips control/amblyseius cucumeris thrips control/amblyseius cucumeris.html 4 Jul. 2017]. [Accessed Meyhofer, H.M. & Poehling, J., Wiethoff, soil and plant Combining R. (2004). to optimise mites predatory dwelling and A. Enkegaard, N.V., Meyling, predation Intraguild (2004). H. Brødsgaard, aphid parasitoid the on Anthocoridae) colemani (Hhymenoptera: Aphidius Braconidae). 630. and prey Habitat L. (2010). Sigsgaard, and nemoralis A. nemorum (L.) Anthocoris Hemiptera (Fabricius) (Anthocoridae: Heteroptera). K.M. The (2014). and B.N. Daane, Hogg, in predators of top and roles intermediate results contrasting suppression: herbivore and laboratory. the field from and Applied Acarology and Applied biological control of thrips. thrips. control of biological by Anthocoris nemorum (Heteroptera: (Heteroptera: nemorum Anthocoris by bugs two predatory of the preferences Entomol.
0.4 3.5 Ecology
For Review Only Ac Specialist Foliar Active An_a Generalist Foliar Active Ap Generalist Broad Active 4.2 cucumeris cucumeris nemorum (adult) Amblyseius Anthocoris Anyphaena pacifica (juvenile) Page 49 of 94 Page 50 of 94 , 375 , 533 108 97 , , Oecologia B. Entomol. Res. Entomol. B. nomics. (2017). Aphidius (2017). nomics. dependent fecundity of the of the fecundity dependent ‐ Applied Applied Bio of College Agriculture University Cornell (Aphidius matricariae, A. colemani, A. ervi) ervi) colemani, A. A. matricariae, (Aphidius at: Available [online] Aphid Parasites. http://www.appliedbio nomics.com/wp [Accessed content/uploads/242 aphidius.pdf 4 Jul. 2017]. Non and P. Stiling, (1996). K.I. Ferguson, enemies natural of multiple additive effects aphid populations. on 379. Aphidius (2017). Applied Bio nomics. ervi) colemani, A. A. matricariae, (Aphidius at: Available [online] Aphid Parasites. http://www.appliedbio nomics.com/wp [Accessed content/uploads/242 aphidius.pdf 4 Jul. 2017]. Aphidoletes (2017). Life and Science. at: Available [online] aphidimyza. https://biocontrol.entomology.cornell.edu/pr 4 Jul. [Accessed edators/Aphidoletes.php 2017]. natural season Early L. (2007). Sigsgaard, planthopper, of the control brown speciesa and spider of two interaction 544. S. and S. Villareal, L., Sigsgaard, Toft, (2001). Diet and formosana Pardosa Atypena spiders Nilaparvata lugens: the contribution contribution and the lugens: Nilaparvata bug. predatory
3 2.5 2.5 2.5 2.5
Active Active Ecology
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For Review Only Specialist Specialist
Ae Aaphi Aflor Specialist Amat Specialist Foliar Active Foliar Active Afor Generalist Broad SW
(adult) (adult) matricariae (juvenile) aphidimyza aphidimyza (larvae) Aphidius ervi Aphidius Aphidoletes Aphidius floridaensis Aphidius Atypena formosana , , , 1298 35 (Doctoral , , , 285 295. , 285 295. 3 , , Feeding potential potential Feeding
Journal of Applied Ecology of Applied Journal Environ. Environ. Entomol. Agr. Forest Entomol. Forest Agr. , 453 461. , 453 461. Expert opinion. Expert opinion. (2012). S.V. Hanskumar, rice. rice. K.M. (2011). and B.N. Daane, Hogg, a within and predator invasion Diversity herbivore on impacts community: suppression. of evaluation safety and insecticidal sp.(carnea-group) Chrysoperla Of Entomology). Iari, Division dissertation, and K. Hamasaki, H., A., Mochizuki, Naka, cannibalism T. Larval (2006). Mitsunaga, between the intraguild predation and Chrysoperla green introduced lacewing, trash carrying indigenous and the carnea, desjardinsi Mallada green lacewing, case as a study Chrysopidae), (Neuroptera: effect potential nontarget of assessment. 1303. Salihah, Farid, Z., Sattar, A., M.M., Ulhaq, (2006). S.U.K. and Khattak, A., Usman, A. 48 mildei Cheiracanthium Spiders.us. (2017). and Spider) Pictures Sac (Longlegged at: [online] Available Identification. Spider http://www.spiders.us/species/cheiracanthiu 4 Jul. 2017]. [Accessed m mildei/ pseudoannulata, predators in irrigated irrigated in predators pseudoannulata,
12 5.17 4.85
Active Active Ecology
BPG Foliar
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Calathus Calathus fuscipes Chrysoperla Cheiracanthium Cheiracanthium mildei (juvenile) carnea (larvae) Page 51 of 94 Page 52 of 94 , , 1298 35 Ecol. Ecol. (Doctoral , , Feeding potential potential Feeding Environ. Environ. Entomol. , 1 8. , 1 8. Songklanakarin J Sci J Sci Songklanakarin J Sci Songklanakarin 28 28 , , Effect of different artificial diets on the on the diets artificial of Effect different (Chrysoperla carnea carnea (Chrysoperla Stephens). Technol (2012). S.V. Hanskumar, of evaluation safety and insecticidal sp.(carnea-group) Chrysoperla Of Entomology). Iari, Division dissertation, and K. Hamasaki, H., A., Mochizuki, Naka, cannibalism T. Larval (2006). Mitsunaga, between the intraguild predation and Chrysoperla green introduced lacewing, trash carrying indigenous and the carnea, desjardinsi Mallada green lacewing, case as a study Chrysopidae), (Neuroptera: effect potential nontarget of assessment. 1303. Salihah, Farid, Z., Sattar, A., M.M., Ulhaq, (2006). S.U.K. and Khattak, A., Usman, A. on the diets artificial of Effect different carnea (Chrysoperla Stephens). Technol R.F. (2005). and Denno, Finke, D.L. of functioning and the Predator diversity predation role of intraguild the ecosystems: cascades. trophic in dampening biology of adult green lacewing adult lacewing of green biology adult lacewing of green biology
4.85 7.55 Ecology
For Review Only Cp_l Cp_l Specialist Foliar Active Csal Generalist Broad Active Chrysoperla Chrysoperla (larvae) saltitans Clubiona plorabunda plorabunda , 93 97. , 93 97. 102 ,
1306. 93 Entomol. Exp. Appl. Exp. Entomol. 1299 , , 8
, Cornell University College of Agriculture of College Agriculture University Cornell Cornell University College of Agriculture of College Agriculture University Cornell Coccinella (2017). Life and Science. [4 July [Online]. 2017]. septempunctata. from: Available https://biocontrol.entomology.cornell.edu/pr Jul. 4 Accessed edators/Coccinella.php 2017]. Coccinella (2017). Life and Science. [4 July [Online]. 2017]. septempunctata. from: Available https://biocontrol.entomology.cornell.edu/pr Jul. 4 Accessed edators/Coccinella.php 2017]. of College Agriculture University Cornell Coleomegilla (2017). Life and Science. 2017]. Available [4 July [Online]. maculata. from: https://biocontrol.entomology.cornell.edu/pr Jul. [Accessed 4 edators/Coleomegilla.php. 2017]. The Coccinellidae (1985). R. D. Gordon, North of Mexico of America (Coleoptera) Entomological of York New Journal the Society, Vol. 2002. M.J.W., Copland, and I ıkber, A.A. Cycloneda aphid foods on of various Effects sanguinea. D.H. (2000). and Wise, Snyder, W.E. cucumber spotted behavior of Antipredator
Lett.
15 5.5 7.6 5.5 4.75
Active Ecology
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For Review Only Specialist
Csem_l Csem_a Csem_a Specialist Foliar Active Cmac_a Specialist Foliar Csang Active Specialist Foliar Csod Active Generalist BPG Active (larvae) (larvae) Coccinella Coccinella Coccinella Coccinella (adult) Coleomagilla (adult) maculata Cycloneda Cyclotrachelus septempunctata septempunctata septempunctata septempunctata sanguinea (adult) sodalis Page 53 of 94 Page 54 of 94 , 15 , 531 533 531 533 , 35 42. , 35 42. 29 27, , , 241–246. 241–246. , 82
J. Asia-Pacific J. Entomol. Asia-Pacific J. Pest Sci., J. Pest
Environ. Entomol. Environ. Biopol. (2017). Episyrphus balteatus. balteatus. Episyrphus (2017). Biopol. response to predators that pose varying varying that pose to response predators risks. Heong, L.P., Lan, S.C., Villareal, Wilby, A., Functional (2005). M.B. & K.L. Thomas, Entomology, identity. Ecological on prey 30, 497–501. S.A. and M.A. Trewick, Minor, R., Kant, koinobiont a in gain (2012). Fitness hosts of by parasitising Aphidiidae) ages. different 83 87. Biology (2014). D.M. Korat, N.K., Karad, rapae of Diaeretiella morphometry and of aphids*. a parasitoid (Mclntosh) Sci., J. Agric. Karnataka Effect of R. (2009). Agustí, Gabarra, N., of Dicyphus and agedensity insect adult on Miridae) Wagner (Heteroptera: tamaninii at: [online] Available http://www.biopol.nl/en/solutions/biological Wheeler, A. G. (2000). Predacious plant Predacious (2000). G. Wheeler, A. of economic (eds.), Heteroptera Panizzi p FL. Raton, Boca press, importance. CRC 657–693 progeny. progeny. bugs (Miridae),. In C. W. Scaefer and A. R. A. and In C. W. Scaefer (Miridae),. bugs beetles (Coleoptera: Chrysomelidae) in in Chrysomelidae) beetles (Coleoptera: benefits of predator species diversity depend depend diversity species benefits predator of (Hymenoptera: Diaeretiella rapae parasitoid
15 4.5 2.85 2.15
Active Ecology
Foliar
For Review Only Specialist
Eb Dr Dr Specialist Foliar Active Dt Generalist Foliar Active Cl_a Cl_a Specialist Foliar Active
tamaninii (nymph) tamaninii Cyrtorhinus Cyrtorhinus lividipennis (adult) balteatus (larvae) Episyrphus Episyrphus Diaeretiella rapae Diaeretiella Dicyphus ‐ , 1110 72 , Romero, R., Romero, ‐ Journal of Applied of Applied Journal , , 249 257. Pest Manag. Sci. Pest 126 , , Hernández, C.V., Sánchez C.V., Hernández, ‐ control/aphids/hoverfly/episyrphus Fundora, L., Ramirez Fundora, L., ‐ pest on studies Microcosm A. Dinter, (2002). (Penn State Entomology of Department intraguild predation between female female intraguild between predation larvae and lacewing and spiders erigonid predators versus single multiple influence of aphids. cereal on & M.G. Telfer, D.R. P.R., Harvey, Nellist, British atlas of Provisional (eds) 2002. & Volumes 1 Araneae), (Arachnida, spiders Centre. Records Biological 2. Huntingdon: European Earwigs (2017). University). [online] of Entomology). (Department at: Available http://ento.psu.edu/extension/factsheets/ear Jul. 2017]. [Accessed wigs 4 Bao Sánchez (2016). N. Desneux, and J. Martínez, of Geocoris predation punctipes Intraguild and its influence eremicus on Eretmocerus Trialeurodes whitefly of the control on the vaporariorum. 1116. Beneficial (2011). Pests Sheet. Utah Fact [online] Bugs. Big Eyed Bugs: True Expert opinion. balteatus/ [Accessed 4 Jul. 2017]. Jul. 2017]. 4 [Accessed balteatus/ Entomology
2.25 13.5
SW Active Ecology
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auricularia auricularia Geocoris oris punctipes* (adult) Erigone Erigone atra Forficula pallens and pallens and Geoc Page 55 of 94 Page 56 of 94 , 566 577. , 566 577. 29 , Animal Diversity Animal Diversity
1 11 1 11 171, , Ecol. Ecol. Entomol. Oecologia builder: consequences of intraguild of intraguild consequences builder:
Available at: Available ofMichigan University (Penn State Entomology of Department http://extension.usu.edu/files/publications/fa Jul. 4 [Accessed ctsheet/big eyed bugs.pdf 2017]. Langellotto, M.S., Mitter, R.F., Denno, (2004). D.L. Finke, and Gratton, G.A., C. and a spider a hunting between Interactions web ‐ suppression. D., Lewis, S.M., Murphy, Wimp, G.M., Van Tull, R., Ambikapathi, Douglas, M.R., (2013). and R.F. Denno, C. L.A., Gratton, patterns influences mode Predator hunting food and epigeic from grazing prey of use webs. convergens Hippodamia Web. (2017). [online] lady Available beetle). (convergent at: http://animaldiversity.org/accounts/Hippoda Jul. 2017]. [Accessed 4 mia_convergens/ Animal Diversity ofMichigan University convergens Hippodamia Web. (2017). [online] lady Available beetle). (convergent at: http://animaldiversity.org/accounts/Hippoda Jul. 2017]. [Accessed 4 mia_convergens/ and Tiger Ground (2017). University). Carabidae) (Coleoptera: Beetles predation and cannibalism for prey cannibalism for and predation
6.3 6.75 14.5
Active Active Ecology
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Haxy_a Hpen Haxy_l Haxy_l Generalist Foliar Active Gt Gt Generalist BPG SW 3 axyridis (larvae) axyridis (larvae) (adult) Grammonota Grammonota trivitatta axyridis (adult) Harmonia Harmonia Harpalus Harmonia Harmonia pennsylvanicus
Entomolgy and Entomolgy (Department of Entomology). [online] of Entomology). (Department of Florida University and Entomolgy of Florida University Available at: Available http://ento.psu.edu/extension/factsheets/grou [Accessed 4 Jul. 2017]. nd beetles Carolina of North Beetles Eastern at: [online] Available Agriculture. http://www4.ncsu.edu/~dorr/Insects/Predato rs/Ground_Beetle/Ground_Beetles1_final.p Jul. 2017]. 4 df [Accessed Hippodamia convergens. [online] Available [online] convergens. Available Hippodamia at: http://entnemdept.ufl.edu/creatures/BENEFI CIAL/convergent_lady_beetle.html 4 Jul. 2017]. [Accessed Animal Diversity ofMichigan University convergens Hippodamia Web. (2017). [online] lady Available beetle). (convergent at: http://animaldiversity.org/accounts/Hippoda Jul. 2017]. [Accessed 4 mia_convergens/ [online] convergens. Available Hippodamia at: http://entnemdept.ufl.edu/creatures/BENEFI CIAL/convergent_lady_beetle.html 4 Jul. 2017]. [Accessed NC State University. (2017). The Ground The Ground (2017). University. NC State Nematology. (2017). convergent ladybug convergent ladybug (2017). Nematology. convergent ladybug (2017). Nematology.
6 5.5
Active Active Ecology
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Hc_a Hc_l convergens convergens (adult) convergens (larvae) Hippodamia Hippodamia Hippodamia Page 57 of 94 Page 58 of 94 , 1586 39 , ed. Corvallis, Or. Dept. of Or. Corvallis, Dept. ed. nd Environ. Entomol. Environ. Entomology, Oregon State University State University Oregon Entomology, to the Collins guide 1986. M., Chinery, University of Michigan Animal Diversity Animal Diversity ofMichigan University convergens Hippodamia Web. (2017). [online] lady Available beetle). (convergent at: http://animaldiversity.org/accounts/Hippoda Jul. 2017]. [Accessed 4 mia_convergens/ at PDF http://mint.ippc.orst.edu/ladybeetfact.pdf from: B., Hall, Mooney, R., Berry, modified and Insects (1998). D. and P.Delaney, in the Importance of Economic Mites Europe. and Britain western insects of p Collins. 258 London: S.A. and Juliano, H. R., Allahyari, Farhadi, larval and of response (2010). Functional variegata of Hippodamia adult stages different to Coccinellidae) (Coleoptera: (Hemiptera: fabae of Aphis densities Aphididae). 1592. 1592. and L. Parra, J., Sheriff, R., Rebolledo, cycles, seasonal Life, 2009. Aguilera, A., Hippodamia fluctuation of population and Northwest. Northwest. 2
4 5.5 5.45
Active Ecology
Foliar
For Review Only Specialist
Ht_l Hs_l Hs_l Specialist Foliar Active Hv_l Specialist Foliar Active variegata (larvae) (larvae) variegata tredecimpunctata tredecimpunctata (larvae) Hippodamia Hippodamia Hippodamia Hippodamia sinuata (larvae) Hippodamia , 35– 29 , Experimental Experimental Cornell releases Cornell releases Chilean J. Agr. Chilean J. Agr. , 34, 239–261. 34, , 239–261. . [online] Available at: Available [online] . , 292 298. , Environmental Entomology Environmental 69 , , variegata (Goeze)(coleoptera: (Goeze)(coleoptera: variegata mites Killer (2017). Biological Services. coccinellidae), in the Central of Central plain La the in coccinellidae), Chile. region, Araucanía Expert opinion. (2001). D.H. Wise, Snyder, & W.E. cucumber spotted behavior of Antipredator varying that pose to response predators risks. 42. Biological Services, – aculeifer) (Hypoaspis at: Available [online] Australia. http://www.biologicalservices.com.au/produ 4 Jul. [Accessed cts/killer mites 23.html 2017]. Meyhofer, H.M. & Poehling, J., Wiethoff, soil and plant Combining R. (2004). to optimise mites predatory dwelling (2017). Chronicle. Cornell Cornell Chronicle Cornell http://news.cornell.edu/stories/2009/11/corn ell releases predator beetle battle hemlock Kok, L.M., Humble, G.M.G., Zilahi Balogh, and Applied Acarology and Applied Res. biological control of thrips. thrips. control of biological beetles (Coleoptera : Chrysomelidae) Chrysomelidae) in beetles : (Coleoptera predator beetle to battle hemlock pest | pest hemlock to battle beetle predator [Accessed 4 Jul. 2017]. pest
3 0.6
Active Ecology
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For Review Only Specialist
Hacul Hh Hh Generalist BPG Active 19.5 Lnig Specialist Foliar Active nigrinus nigrinus aculeifer aculeifer Hypoaspis Hypoaspis Hogna helluo Hogna helluo Laricobius Page 59 of 94 Page 60 of 94 J. J. , , , , 138 138 , , , , Cornell releases Cornell releases , 147 152. , 147 152. 20 , , , 1143 1151. 1143 1151. , . [online] Available at: Available [online] . 99 Canadian Entomol. Canadian Canadian Entomol. Canadian , , Biol. Control Biol. 595 601. 595 601. L.T. and Salom, S.M. (2006). Morphology Morphology S.M. (2006). L.T. and Salom, of Laricobius nigrinus (Coleoptera: (Coleoptera: nigrinus of Laricobius of the hemlock a predator Derodontidae), adelgid. woolly (2017). Chronicle. Cornell and J. Fargues, Couton, L. O., Bonato, Macrolophus of preference (2006). Feeding on Miridae) (Heteroptera: caliginosus Trialeurodes and tabaci Bemisia Aleyrodidae). (Homoptera: vaporariorum Alomar, (2001). O. and Lucas, E. as an caliginosus (Wagner) Macrolophus zoophytophagous the for intraguild prey Wagner (Heteroptera: tamaninii Dicyphus Miridae). Expert opinion. 595 601. 595 601. Cornell Chronicle Cornell http://news.cornell.edu/stories/2009/11/corn ell releases predator beetle battle hemlock Kok, L.M., Humble, G.M.G., Zilahi Balogh, Morphology S.M. (2006). L.T. and Salom, (Coleoptera: nigrinus of Laricobius of the hemlock a predator Derodontidae), adelgid. woolly
Econ. Entomol. Econ. predator beetle to battle hemlock pest | pest hemlock to battle beetle predator [Accessed 4 Jul. 2017]. pest
2.69 3.25 Ecology
For Review Only Lnig_l Lnig_l Specialist Foliar Active Mc Generalist Foliar Active Mpik Generalist Foliar Active 8 nigrinus (larvae) nigrinus caliginosus Laricobius Laricobius Macrolophus Marpissa pikei , 66 , , 601 , , 497 137 , 30 , , Biol. Control Biol. New York: Springer. p Springer. York: New Ecol. Ecol. Entomol.
J. Appl. Entomol. J. Appl. . International Rice Research Research Rice International Trophic and guild interactions interactions in and guild Trophic Brodeur, J. and Boivin, G. G. eds., Boivin, and Brodeur, J. Sampathkumar, Mohan, M., C., Shanker, Expert opinion. 2006. 2006. control. biological 249 (2013). and N.J. Mills, Bürgi, L.P. history and life strategy Developmental a successful ictericus, traits of Meteorus light exotic brown the of resident parasitoid in moth California. apple 173 182. Expert opinion. Heong, L.P., Lan, S.C., Villareal, Wilby, A., 2005. Functional M.B., and K.L. Thomas, identity. on prey 501. G., 2013. and Katti, C. M., Lydia, Micraspis of significance Functional in Coleoptera) discolor (F.)(Coccinellidae: ecosystem. rice 609. (1989). Rapusas, H.R. and B.M. Shepard, brown sp. on Micraspis cycle Life of (Philippines) benefits of predator species diversity depend depend diversity species benefits predator of and rice (BPH) planthopper pollen. Newsletter
6 10 4.5 5.15
Active AP Ecology
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Metioche Metioche vittaticollis (adult) mid instar) Micraspis crocea crocea Micraspis Misumenops (two Meteorus Meteorus ictericus Page 61 of 94 Page 62 of 94
nd , 338–348 , 338–348 13 , 275–282. , 275–282. , 108 , Oikos Ecology Letters Ecology ed. Corvallis, Or.: Dept. of of Entomology, Dept. Or.: ed. Corvallis, State Oregon University Yasuda, H. & Kimura, T. (2001). & Kimura, Yasuda, H. & B.J. Ives, Cardinale, Aquilino, K.M., Interspecific interactions in a tri trophic tri trophic in a interactions Interspecific the on of a effects spider arthropod system: predatory larvae of three survival of to aphids. Experimental ladybirds in relation 98, 17–25 Applied and Acarology., Expert opinion. T. (2001). & Kimura, Yasuda, H. tri trophic in a interactions Interspecific the on of a effects spider arthropod system: predatory larvae of three survival of to aphids. Experimental ladybirds in relation 98, 17–25 Applied and Acarology., effects of host plant Reciprocal A.R. (2005). on enemy herbivore natural diversity and a model of an study empirical suppression: tritrophic system. saturation Niche Snyder, (2010). W.E. among partitioning resource reveals consumers. and P. B., Hall, Mooney, R., Berry, and of Mites Insects (1998). Delaney, D. 2 the Northwest. in Importance Economic and P. B., Hall, Mooney, R., Berry, and of Mites Insects (1998). Delaney, D. Northfield, T.D., Snyder, G.B., Ives, A.R. & Ives, A.R. G.B., Snyder, Northfield, T.D.,
6 8 7.5
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nd , , , 85 , , Hedo, M., Insect Sci. Insect ‐ Ecology doi:10.1111/1744 7917.12361 doi:10.1111/1744 7917.12361 Luna, M.G. and Urbaneja, A. (2016). A. and (2016). M.G.Urbaneja, Luna, competitive and predation Intraguild tenuis Nesidiocoris between displacement 2 biological Dicyphus and maroccanus, pests. tomato in agents control Economic Importance in the Northwest. 2 the Northwest. in Importance Economic ed. Corvallis, Or.: Dept. of of Entomology, Dept. Or.: ed. Corvallis, State Oregon University G.M., Trafelet Smith, M., Matsumura, W.F. and Fagan, D.L., C., Finke, Gratton, intraguild R.F. Does Denno, (2004). perspective. stoichiometric and D.J. Giberson, Marriott, S.M., Changes in (2009). D.B., McCorquodale, of geographic ranges and the status and (Coccinellinae) Beetles Lady Canadian candidates for risk the of selection Report. Part Foundation assessment. 1. Nesidiocoris (2017). Biological Services. Biological Services, – (Nesidiocoris tenuis) at: Available [online] Australia. http://www.biologicalservices.com.au/produ [Accessed 4 Jul. cts/nesidiocoris 28.html 2017]. G., Pérez Gervassio, Nadia, S., Colfer, D.D., Limburg, Rosenheim, J.A., C.L., Leonardo, V., Hsu, Fournier, R.G., 2601 2615. 2601 2615. predation enhance predator performance? A A performance? predator enhance predation
2.5 Ecology
For Review Only Nser Nser Generalist Foliar Active Nten 5.35 Generalist Foliar Active Nest Generalist Foliar SW 2 tenuis (nymph) tenuis (nymph) Naemia seriata Naemia seriata Nesidiocoris rufipes Nesticodes Page 63 of 94 Page 64 of 94 , , Ecology Journal of Applied of Applied Journal , , 249 257. 126 , , , 140, 577–585. 2) , 577–585. 140, 85, 3362–3372. 85, 3362–3372. T.E. & Nelson, E.H. (2004a) Herbivore Herbivore (2004a) E.H. T.E. & Nelson, on studies Microcosm A. Dinter, (2002). Colfer, D.D., Limburg, Rosenheim, J.A., intraguild predation between female female intraguild between predation larvae and lacewing and spiders erigonid predators versus single multiple influence of aphids. cereal on C.L., Leonardo, V., Hsu, Fournier, R.G., Herbivore (2004a) E.H. T.E. & Nelson, an intraguild of the presence to insensitive Scheme Recording and Spider Harvestman for Oedothorax Summary (2017). website. at: [online] Available (Araneae). apicatus http://srs.britishspiders.org.uk/portal/p/Sum [Accessed 4 mary/s/Oedothorax+apicatus Jul. 2017]. insensitive to the presence of an intraguild an intraguild of the presence to insensitive Oecologia & R.E. Goeriz, T.E., Glik, Rosenheim, J.A., a predator’s Linking B. (2004b) Rämert, on effects its behavior with foraging suppression. population herbivore population suppression by an intermediate an intermediate by suppression population is macropilis, predator, Phytoseiulus body size? an of small advantage predator: population suppression by an intermediate an intermediate by suppression population is macropilis, predator, Phytoseiulus body size? an of small advantage predator: Entomology
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Orius tristicolor tristicolor Orius 585. 585. – . [online] Available at: . Available [online] , , 577 , 164 169. , 164 169. 140 , , 30 New Zealand Journal Journal of Zoology New Zealand , , , 3362–3372. , 3362–3372. , 247 255 , 247 255 85 oligota The genus (1976). Williams, S.A. New in Staphylinidae) (Coleoptera: Zealand. 3 Oecologia of College Agriculture University Cornell & R.E. Goeriz, T.E., Glik, Rosenheim, J.A., a predator’s Linking B. (2004b) Rämert, on effects its behavior with foraging suppression. population herbivore (2017). Life and Science. and insidiosus O. https://biocontrol.entomology.cornell.edu/pr 4 Jul. 2017]. [Accessed edators/Orius.php Orthotylus (Miridae) (2017). Bantock, T. [online] Britishbugs.org.uk. marginalis. at: Available https://www.britishbugs.org.uk/heteroptera/ Miridae/orthotylus_marginalis.html 4 Jul. 2017]. [Accessed Liman, (2005). A.S. and Björkman, C. outcome behaviour the influences Foraging interactions. predator–predator of R.F. (2005). and Denno, Finke, D.L. of functioning and the Predator diversity predation role of intraguild the ecosystems: cascades. trophic in dampening Entomol.
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Foliar
For Review Only Generalist
Otri Pl_a Pl_a Generalist Broad Active Omarg Omarg Generalist Foliar SW 6.4 (adult) (adult) Orius tristicolor Orius tristicolor (adult) (adult) Orthotylus marginali Pardosa littoralis Pardosa littoralis Page 65 of 94 Page 66 of 94 , , 2367 The The 83 , , , 179 186. , 179 186. J. J. Anim. , 447 449. , 447 449. 33 Ecology ., ., 11 ,
1306. , , 1299 Res. Popul. Ecol Popul. Res. 8
, , 752 760. 78, R.F. A Denno, (2009). and D. Lewis, enhances habitat suitability in seasonal shift subsidy. annual predator an Spiders. Common to Singapore A Guide (pardosa spider wolf (2017). pond http://habitatnews.nus.edu.sg/guidebooks/sp iders/text/Pardosa_pseudoannulata.htm 4 Jul. 2017]. [Accessed and E.G. Rubia, Heong, S. Bleih, K.L., spider, wolf of the preference (1991). Prey et (Boesenberg Pardosa pseudoannulata Strand). (2002). Schmitz, O.J. and L. Sokol Hessner, multiple effects predator of Aggregate a prey. shared species on 2372. 2372. of two orb Predators (1983). Horton, C.C. Araneidae). web (Araneae, spiders Table Identification. Spider TGSpId: Grape clarus. Phidippus (2017). TGSpID Factsheet at: [online] Available http://itp.lucidcentral.org/id/table grape/tgspid/html/fsheet_phidippus_clarus.h Jul. 2017]. 4 tm [Accessed pseudoannulata). [online] Available at: [online] Available pseudoannulata). Letters Ecol. Journal of Arachnology Journal
Ecology
For Review Only Pp Pp Generalist BPG Active Prim Generalist 8.5 Broad Active 8.7 Pardosa Pardosa pseudoannulata Phidippus rimator
, 291 52 ,
, 577–585. , 577–585. Exp. Acarol. Exp. Appl. 140 , , Kreiter, S., and M.S. Tixier, M., Okassa, and molecular 2010. Morphological and persimilis of Phytoseiulus diagnostics (Acari: macropilis Phytoseiulus Phytoseiidae). Expert opinion. Phalangium opilio | NatureSpot. NatureSpot. [online] | opilio Phalangium at: Available http://www.naturespot.org.uk/species/phalan Jul. 2017]. 4 [Accessed gium opilio Expert opinion. Colfer, D.D., Limburg, Rosenheim, J.A., C.L., Leonardo, V., Hsu, Fournier, R.G., Herbivore (2004). E.H. T.E. & Nelson, an intraguild of the presence to insensitive Oecologia Animal Diversity ofMichigan University mira. [online] Pisaurina Web. (2017). at: Available http://animaldiversity.org/accounts/Pisaurin 2017]. Jul. 4 [Accessed a_mira/ (2002). Schmitz, O.J. and L. Sokol Hessner, multiple effects predator of Aggregate 303. 303. population suppression by an intermediate an intermediate by suppression population is macropilis, predator, Phytoseiulus body size? an of small advantage predator: NatureSpot. (2017). Phalangium opilio opilio Phalangium NatureSpot. (2017).
14 0.5 10.5 3.75
Active AP Ecology
BPG Broad
For Review Only Generalist Generalist
Phil Popi Pmacro Pmacro Specialist Foliar Active Pmir Generalist Foliar SW
macropilis macropilis (adult) (adult) Philonthus sp sp Philonthus Phalangium opilio Phytoseiulus Phytoseiulus Pisaurina mira Page 67 of 94 Page 68 of 94 , , 83 , , Ecology species on a shared prey. a prey. shared species on of College Agriculture University Cornell of College Agriculture University Cornell .2367 2372. .2367 2372. Podisus (2017). Life and Science. at: Available [online] maculiventris. https://biocontrol.entomology.cornell.edu/pr 2017]. Jul. [Accessed 4 edators/Podisus.php and Entomolgy of Florida University [online] Say. maculiventris Podisus at: Available http://entnemdept.ufl.edu/creatures/benefici [Accessed 4 al/podisus_maculiventris.htm Jul. 2017]. Podisus (2017). Life and Science. at: Available [online] maculiventris. https://biocontrol.entomology.cornell.edu/pr 2017]. Jul. [Accessed 4 edators/Podisus.php and Entomolgy of Florida University [online] Say. maculiventris Podisus at: Available http://entnemdept.ufl.edu/creatures/benefici [Accessed 4 al/podisus_maculiventris.htm Jul. 2017]. J., Su, B., Yang, Men, Ouyang, X., F., Ge, and (2012). F. Z. Y., Zhao, Zhang, beetle, the predatory Maize benefits provide japonica (Thunberg), to Propylea Nematology. (2017). Spined soldier bug Spined (2017). Nematology. soldier bug Spined (2017). Nematology.
4.5 5.65 10.75
Active Active Ecology
Foliar Foliar
For Review Only Generalist Generalist
Pmac_a Pmac_n Pjap_l Pjap_l Specialist Foliar Active s (larvae) (larvae) maculiventris maculiventris (adult) maculiventris (nymph) Podisus Podisus Podisu Propylea japonica Propylea japonica
. [online] [online] . , 228 235. , 228 235. , p.e44379. p.e44379. , Eur. J. J. Eur. 7 32 , , , , Animal Diversity Animal Diversity
PloS One PloS , 149. , 149. Rabidosa rabida Rabidosa Biol. Control Biol. 104 , , University ofMichigan University aphids in cotton. in aphids B.Z. Hua, and Zhang, S.Z., F. Zhang, for types prey of various (2007). Suitability japonica of Propylea the development Coccinellidae). (Coleoptera: Dahlsten, K.R., D.L., K.M., Daane, Sime, R.L. (2005). and Zuparko, J.W. Andrews, Riek bliteus of Psyllaephagus biology The of a parasitoid Encyrtidae), (Hymenoptera: lerp (Hemiptera: psyllid the red gum Psylloidea). NatureSpot. [online] | Pterostichus madidus at: Available http://www.naturespot.org.uk/species/black Jul. 2017]. [Accessed 4 clock beetle Expert opinion. Web. (2017). Available at: Available http://animaldiversity.org/accounts/Rabidos
Pterostichus melanarius | NatureSpot. | melanarius Pterostichus at: [online] Available http://www.naturespot.org.uk/species/pteros 4 Jul. 2017]. [Accessed tichus melanarius Expert opinion. potential to enhance biological control for for control biological enhance potential to Beetle Clock Black NatureSpot. (2017). Entomol. melanarius Pterostichus NatureSpot. (2017).
15 17 1.54 17.5
Active AP Ecology
BPG BPG
For Review Only Generalist Generalist
Pmad Rrab Pblit Pblit Specialist Foliar Active Pmel Generalist BPG Active
bliteus (adult) bliteus (adult) melanarius madidus madidus Pterostichus Pterostichus Rabidosa rabida Psyllaephagus Psyllaephagus Pterostichus Page 69 of 94 Page 70 of 94 , , 83 , ,
Salticus Salticus Ecology Agricultural and Forest Forest and Agricultural , 19, , 52 59. 19, | Arkive. [online] Available at: at: [online] Available Arkive. | rich predator assemblages assemblages predator rich ‐ http://www.arkive.org/zebra spider/salticus Jul. 2017]. 4 [Accessed scenicus/#text=All a_rabida [Accessed 4 4 Jul. 2017]. [Accessed a_rabida of College Agriculture University Cornell (2002). Schmitz, O.J. and L. Sokol Hessner, multiple effects predator of Aggregate a prey. shared species on Conserving (2016). R. A. and Drieu, Rusch, species climate a control in pest strengthens natural context. warming spider Zebra Arkive. (2017). Sasajiscymnus (2017). Life and Science. at: [online] Available tsugae. https://biocontrol.entomology.cornell.edu/pr [Accessed 4 Jul. edators/sasajiscymnus.php 2017]. of College Agriculture University Cornell Sasajiscymnus (2017). Life and Science. at: [online] Available tsugae. https://biocontrol.entomology.cornell.edu/pr [Accessed 4 Jul. edators/sasajiscymnus.php 2017]. behavior with foraging a predator’s Linking population herbivore effects on its 3362–3372. Ecology, 85, suppression. .2367 2372. .2367 2372. scenicus Entomology
1.9 0.35 0.48
Active Ecology
Foliar
For Review Only Specialist
Stsu Sscen Sscen Generalist Broad Active 7 Stsu_l Specialist Foliar Ssiph Specialist Active Foliar Active Sasajiscymnus Sasajiscymnus Salticus scenicus Salticus scenicus tsugae Sasajiscymnus tsugae (larvae) Stethorus siphonulus siphonulus
, 453 461. , 453 461. 48 , , NatureSpot. | | Tachyporus hypnorum hypnorum - Tachyporus , 577 585. , 577 585. [Accessed 4 Jul. 2017]. Jul. 2017]. [Accessed 4 J. J. Ecol. Appl. 140 , ,
http://www.naturespot.org.uk/species/tachyp Evergreen growers. (2017). Stethorus Stethorus (2017). growers. Evergreen http://www.evergreengrowers.com/stethorus punctillum spider mite destroyer.html 4 Jul. 2017]. [Accessed Colfer, D.D., Limburg, Rosenheim, J.A., C.L., Leonardo, V., Hsu, Fournier, R.G., Herbivore (2004). E.H. T.E. and Nelson, an intraguild of the presence to insensitive Oecologia orus hypnorum two of histories Life (1997). M.K. Petersen, in the hypnorum, Tachyporus of University Swedish agroecosystem. Agricultural Sciences. Vancouver. K.M. (2011). and B.N. Daane, Hogg, a within and predator invasion Diversity herbivore on impacts community: suppression. Tachyporus hypnorum hypnorum Tachyporus [online] Available at: at: [online] Available punctillum. [online] Available at: at: Available [online] punctillum. an intermediate by suppression population is macropilis, predator, Phytoseiulus body size? an of small advantage predator: lampros and Bembidion beetles, predaceous NatureSpot. (2017). NatureSpot. (2017).
3.5 Ecology
For Review Only Thyp Thyp Generalist Broad Active Tmel Generalist Broad SW 1.735 Tachyporus Tachyporus hypnorum (adult) Theridion melanurum Page 71 of 94 Page 72 of 94
- , . [online] [online] . ZooKeys , 83, 643.; , 2 643.; 83, Theridion melanurum melanurum Theridion
Ecology 535 548. 535 548. 79, , 1 114 , 1 114 (1988). R.C. H.J., Froeschner. Thomas, of Bugs or True of the Heteroptera, Catalog States. Continental United and the Canada Theridion melanurum | NatureSpot | melanurum Theridion Pest Orchard State University Washington Typhlodromus (2017). Online. Management at: Available [online] occidentalis. http://jenny.tfrec.wsu.edu/opm/displaySpeci 4 Jul. 2017]. [Accessed es.php?pn=830 Intraguild R.F. (2002) & Denno, Finke, D.L. Complex in Diminished Predation for Prey Implications Structured Vegetation: Suppression. in Fabricius Zelus Genus Hart, E.R. (1986). Northern and Canada, States, the United Reduviidae). Ent. Ann. (Hemiptera: Mexico Soc. Am. Leiden, Publishers. Academic Brill Available at: Available http://www.naturespot.org.uk/species/theridi Jul. 2017]. [Accessed 4 on melanurum Plant of the Revision (2012). Henry, T.J. (Hemiptera, Tytthus Genus Bug Phylinae). Miridae, Heteroptera, 220 A.R. (2000). C.W., Panizzi Schaefer CRC importance. economic Heteroptera of NatureSpot. NatureSpot. (2017). Netherlands. Netherlands.
0.6 2.34 13.2 Ecology
For Review Only Zren_a Zren_a Generalist Foliar Active Tpy Tpy Specialist Tvag Foliar Specialist Active Foliar Active (adult) (adult) Typhlodromus Typhlodromus Tytthus vagus (adult) Zelus renardii Zelus renardii pyri pyri Ann. Ent. Ent. Ann.
Press, Boca Raton, FL, 828. Raton, FL, Press, Boca Hart, E.R. (1986). Genus Zelus Fabricius in Fabricius Zelus Genus Hart, E.R. (1986). Northern and Canada, States, the United Reduviidae). (Hemiptera: Mexico . Am Soc. 535 548. 79, (1988). R.C. H.J., Froeschner. Thomas, Bugs of or True of the Heteroptera, Catalog States. Continental United and the Canada Leiden, Publishers. Academic Brill A.R. (2000). C.W., Panizzi Schaefer CRC importance. economic Heteroptera of 828. Raton, FL, Press, Boca Netherlands. Netherlands.
8.75 Ecology
For Review Only Zren_n Zren_n Generalist Foliar Active (nymph) (nymph)
Zelus renardii Zelus renardii Page 73 of 94 Page 74 of 94 Ecology
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(body (body
large large 0.44 0.43 - 1.00 1.00 (mm) (mm) 0.75 0.75 * * size Prey large
0.26 0.62 0.62 1.00 -0.41 ratio
small
0.05 ratio - 1.00 0.62 0.62
(body size ratio between the smallest predator and prey). prey). and predator smallest the between size(body ratio Size Size difference 0.01 1.00 0.01 0.45 0.03 0.03 -0.44 -0.41 between between predators small small Ecology
0.04 Size of Size of smallest (mm)* - 0.60 1.00 0.82 0.11 -0.04 -0.26 0.75 0.11 predator predator
0.05 0.43 Size of Size of largest (mm)* 1.00 - 0.26 -0.26 0.45 0.60 0.82 For predator Review Only
* = body size ratio between the smallest predator and prey prey and predator smallest the = body between size ratio = body size ratio between the largest predator and prey and prey largest predator the between size ratio = body Pearson correlation coefficient between predator-prey size variables. Correlation where r >0.5 have been in highlighted in in bold. in highlighted been have >0.5 where r size Correlation variables. predator-prey between coefficient correlation Pearson
* * large small small large small size ratio between the largest predator and prey) was included instead of ratio instead included was and prey) largest predator the size ratio between
Table 1. Ratio Size difference = mean pairwise distance in body size between the predator species the species predator size between in body distance pairwise = mean Size difference Size of largest predator (mm) predator Size of largest ratio Appendix S4 S4 Appendix where ratio results the model is 1). shown Also (Table size variables and prey body collinearity predator between the Table showing (mm)* predator Size of smallest predators between Size difference ratio size Prey (mm) other collinearity variables. with level aof high to analysis due from removed * variable was with indicates Parameters marked Ratio Page 75 of 94 Page 76 of 94 Weight Weight weight Relative
c 446.481 446.481 0.058 0.134 447.260 447.260 0.040 0.091 447.097 447.097 0.043 0.099 447.615 447.615 0.033 0.076 AIC 447.570 447.570 0.034 0.078 445.671 445.671 446.136 0.087 0.069 0.201 0.159 447.616 447.616 0.033 0.076 447.378 447.378 0.037 0.086 Ecology
(predator polyculture compared to the mean of the component predator species in monocultures). monocultures). in species predator component to of the the mean compared polyculture (predator For Review Only large mean mean
model subset for SMD model subset c Functional diversity Functional diversity Size Functional difference + diversity Functional diversity + Predator richness + Size difference difference Size + richness Predator Functional + diversity Functional diversity + Phylogenetic diversity diversity Phylogenetic Functional + diversity Functional diversity + Prey size Prey Functional + diversity Functional diversity + Phylogenetic diversity + Size difference + difference Size diversity Phylogenetic Functional + diversity Functional diversity + Predator richness richness Predator Functional + diversity Functional diversity + Prey richness richness Prey Functional + diversity Functional diversity + ratio Functional + diversity models models . . 2AIC large large Rank Rank Model Table 2 Ratio 1 2 8 8 3 3 9 9 4 4 5 5 6 6 7 7
0.016 0.018 0.09 0.019 0.065 0.491 0.834 Ecology (predator polyculture compared to the mean of the component predator species species predator component of the the mean compared to polyculture (predator mean mean 0.102 0.102 0.233 -0.287 -0.009 -0.009 0.334 -0.037 Estimate Estimate Importance CI bound lower 95% upper 95% CI bound 0.016 0.016 0.167 -0.058 0.010 0.010 0.086 -0.045 -0.003 -0.003 0.078 -0.024 -0.002 -0.002 0.076 0.452 -0.020 1.000 0.070 For Review Only
Multimodel averaged parameter estimates estimates for SMD averaged parameter Multimodel
.
large Parameter Parameter Predator richness >2 Predator >2 richness in monocultures). Prey richness and predator richness estimate is the difference between the reference level (predator richness = 2 species and 2 species = richness (predator level the between reference is difference the estimate richness predator and richness Prey in monocultures). Size difference Size difference Table 3 size Prey ratio >1 richness Prey diversity Phylogenetic diversity Functional prey richness = 1 species). Parameter in bold indicate that the variable was included in the highest ranked model. model. ranked in the highest included was that the variable in bold indicate Parameter species). prey = richness 1 Page 77 of 94 Page 78 of 94
0.242 0.154 0.139 0.132 0.130 0.111 0.094 Relative Relative weight
0.086 0.055 0.049 0.047 0.046 0.039 0.033 Weight
544.817 545.133 545.806 545.036 545.482 543.920 545.170
c AIC
Ecology
large
(predator polyculture compared to the most effective predator species in a monoculture). a monoculture). in species predator effective most to the compared polyculture (predator
For Reviewlarge Only max max models models model subset for SMD model subset c large Predator richness + Functional diversity diversity Functional Predator + richness difference Size + diversity Functional Predator + richness ratio + diversity Functional Predator + richness diversity Phylogenetic + diversity Functional Predator + richness Functional diversity ratio + Functional diversity Size difference + Functional diversity ratio . . 2AIC max max Rank Rank Model Table Table 4 SMD 1 2 3 4 5 6 7
0.282 0.083 0.885 0.017 0.148 -0.180 -0.180 -0.029 -0.029 0.057 -0.143 -0.143 -0.464 -0.464 Ecology (predator polyculture compared to the most effective predator species in a a in species predator effective most the compared to polyculture (predator max max 0.052 0.052 0.132 -0.006 -0.006 0.248 Estimate Estimate Importance 95% CI bound lower bound upper 95% CI -0.030 -0.030 0.249 For -0.158 Review 0.471 0.666 1.000 Only Multimodel averaged parameter estimates estimates for SMD averaged parameter Multimodel
.
large monoculture). Predator richness estimate is the difference between the reference level (predator richness = 2). Parameter in bold indicate that the the that in bold indicate Parameter = 2). richness level (predator the between reference the is difference estimate richness monoculture). Predator model. ranked the highest included in variable was Table Table 5 Parameter diversity Phylogenetic Size difference ratio >2 richness Predator diversity Functional Page 79 of 94 Ecology Page 80 of 94
Appendix S5
Funnel plots to assess publication bias.
Figure 1. Funnel plots for SMDmean showing the effect size plotted against the a) standard error, b) sampling variance, c) inverse standard error and the d) inverse sampling variance for each point.
Figure 2. Funnel plots for SMDmax showing the effect size plotted against the a) standard error, b) sampling variance,For c) inverseReview standard error andOnly the d) inverse sampling variance for each point.
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1a)
Ecology Page 82 of 94
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1b)
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1c)
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1d)
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2a)
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2b)
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2c)
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2d) Page 89 of 94 Ecology
Appendix S6
Model 2AICc subset for SMDmean and SMDmax metrics.
SMDmean
Table 1. 2AICc model subset for SMDmean (predator polyculture compared to the mean of the
component predator species in monocultures).
Rank Model AICc Weight Relative weight 1 Functional diversity 445.671 0.070 0.145 2 Functional diversityFor + SizeReview difference Only446.136 0.055 0.115 3 Functional diversity + ratiosmall 446.167 0.054 0.113 4 Functional diversity + Phylogenetic diversity 446.481 0.046 0.097 5 Functional diversity + Size difference + ratiosmall 446.860 0.038 0.080 6 Functional diversity + Prey size + ratiosmall 446.906 0.037 0.078 Functional diversity + Phylogenetic diversity + 7 Size difference 447.097 0.034 0.071 8 Functional diversity + Predator richness 447.260 0.031 0.065 Functional diversity + Phylogenetic diversity + 9 ratiosmall 447.266 0.031 0.065 10 Functional diversity + Prey richness 447.378 0.030 0.062 Functional diversity + Predator richness + Size 11 difference 447.615 0.026 0.055 12 Functional diversity + Prey size 447.616 0.026 0.055
Ecology Page 90 of 94
SMDmax
Table 2. 2AICc model subset for SMDmax (predator polyculture compared to the most effective predator species in a monoculture).
Rank Model AICc Weight Relative weight 1 Predator richness + Functional diversity + 542.820 0.090 0.267 ratiosmall 2 Predator richness + Functional diversity + 543.295 0.071 0.211 ratiosmall + Prey size 3 Predator richness + Functional diversity 543.920 0.052 0.154 4 Predator richness + Functional diversity + Size 544.029 0.049 0.146 difference + ratiosmall 5 Predator richnessFor + Functional Review diversity + Only544.398 0.041 0.121 Phylogenetic diversity + ratiosmall 6 Predator richness + Functional diversity + Size 544.817 0.033 0.099 difference
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Appendix S7
Analysis of the individual traits diet breadth, hunting strategy and habitat domain on SMDmean
(predator polyculture compared to the mean of the component predator species in monocultures) and SMDmax (predator polyculture compared to the most effective predator species in a monoculture). A functional diversity only model has also been included for comparison.
SMDmean
Table 1. 2AICc modelFor subset for Review SMDmean. Only
Rank Model AICc Weights Relative weight 1 Diet breadth 443.960 0.479 0.709 2 Diet breadth + Hunting strategy 445.743 0.197 0.291
Table 2. Multimodel averaged parameter estimates for SMDmean. Parameter Estimate Importance 95% CI lower bound 95% CI upper bound Hunting strategy 0.023 0.291 -0.098 0.144 Diet breadth 0.371 1.000 0.096 0.646
Table 3. Functional diversity only model for SMDmean.
AICc = 445.671 Parameter Estimate 95% CI lower bound 95% CI upper bound Functional diversity 0.453 0.072 0.831
SMDmax
Table 4. 2AICc model subset for SMDmax.
Rank Model AICc Weights Relative weight 1 Diet breadth 547.266 0.220 0.278 2 Hunting strategy 547.864 0.163 0.206 3 Diet breadth + Hunting strategy 547.882 0.162 0.204 4 Null model 547.942 0.157 0.198 5 Diet breadth + Habitat domain 549.028 0.091 0.115
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Table 5. Multimodel averaged parameter estimates for SMDmax. Parameter Estimate Importance 95% CI lower bound 95% CI upper bound Habitat domain 0.012 0.115 -0.058 0.082 Hunting strategy 0.084 0.410 -0.17 0.338 Diet breadth 0.141 0.596 -0.179 0.461
Table 6. Functional diversity only model for SMDmax.
AICc = 545.170 Parameter Estimate 95% CI lower bound 95% CI upper bound Functional diversity 0.458 0.051 0.865 For Review Only
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Appendix S8
As study design had a significant effect on the SMDmax metric (predator polyculture compared to the most effective predator species in a monoculture) (see Main paper; Table 3). We re- analysed SMDmax removing additive design studies that did not account for predator density.
This left 140 data points from a total of 26 studies. The model results from this subset of data supported our main result that functional diversity had a positive effect on SMDmax (Table 1 and 2). The only difference was the absence of ratiosmall from the 2AICc subset. However, our main analysis showed Forlarge variation Review of the impact of Onlyratiosmall on SMDmax. Thus, indicating no clear positive or negative effect of this variable.
Table 1. 2AICc model subset for SMDmax .
Rank Model AICc Weight Relative weight 1 Functional diversity + Predator richness 355.877 0.122 0.385 2 Functional diversity + Predator richness + 356.524 0.089 0.279 Phylogenetic diversity 3 Functional diversity + Predator richness + 357.294 0.060 0.190 Prey size 4 Functional diversity + Predator richness + 357.794 0.047 0.148 Size difference
Table 2. Multimodel average parameter estimates for SMDmax. Predator richness estimate is the difference between the reference level (predator richness = 2 species). Parameters in bold indicate that the variable was included in the highest ranked model.
Parameter Estimate Importance 95% CI lower bound 95% CI upper bound Size difference 0.002 0.148 -0.01 0.014 Prey size -0.023 0.189 -0.122 0.076 Phylogenetic diversity 0.161 0.278 -0.412 0.734 Predator richness >2 -0.487 1.000 -0.794 -0.18 Functional diversity 0.688 1.000 0.067 1.309
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