A Comparison of Predation Rates Measured by Various Types of Sentinel Prey

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types of sentinel prey

Rebecca K. Nagya,b, Nancy A. Schellhornb† and Myron P. Zaluckia

aSchool of Biological Sciences, The University of Queensland, St Lucia, Qld 4072, Australia bCSIRO, Brisbane, Qld 4001, Australia

†RapidAim, Brisbane, Qld 4000, Australia

Acknowledgements Thanks goes to UQAuthor Manuscript Gatton for allowing access to their property to conduct this research. Thanks also to Anna Marcora for her help procuring insects from Narrabri and Dr Lynda Perkins for her help with statistics. R.K.N.’s research is funded by the Australian

2 MRS. REBECCA NAGY (Orcid ID : 0000-0002-5562-7957)

5 Article type : Advances in Methodology

7 Formatted: Left, Line spacing: Multiple 1.08 li 8 Corresponding author mail id: [email protected] Formatted: Font: 12 pt

9 Fresh, frozen or fake: a comparison

10 of predation rates measured by

11 various types of sentinel prey

13 Rebecca K. Nagya,b, Nancy A. Schellhornb and Myron P. Zaluckia

14 aSchool of Biological Sciences, The University of Queensland, Brisbane, Qld 4072, Australia

15 bCSIRO, Brisbane, Qld 4001, Australia

18 Abstract

19 Arthropod predators and parasitoids support the health and functioning of the world’s

20 ecosystems, most notably by supplying biological control services to agricultural landscapes. Author Manuscript

22 observation and measurement of arthropod predation is difficult. The use of sentinel prey is

23 one method to measure predator impact; however, despite widespread use, few studies

24 have compared predation on different prey types within a single experiment. This study

25 evaluated the predation rates on four sentinel prey items in grass and wheat fields in south-

26 east Queensland, Australia. Attack rates on live and dead Helicoverpa armigera eggs, and

27 dead H. armigera larvae and artificial plasticine larvae, were compared and the predators

28 that were attracted to each prey type were documented with the use of field cameras. There

29 was no significant difference in predation rates between sentinel eggs, while dead larvae

30 were significantly more attacked than artificial larvae. Prey were attacked by a diverse range

31 of predators, including ants, beetles, various nymph and juvenile insects and small

32 mammals. Different predators were active in grass and crop fields, with predator activity

33 peaking around dawn and dusk. The same trends were observed within and between the

34 two habitats studied, providing a measure of confidence in the sentinel prey method. A

35 range of different sentinel prey types could be suitable for use in most comparative studies;

36 however, each prey type has its own benefits and limitations, and these should be carefully

37 evaluated to determine which is most suitable to address the research questions.

40 Keywords

41 Predation; grassland; crop; Helicoverpa armigera; plasticine

44 Introduction Author Manuscript

46 habitats. Predation is one of the most important ecosystem services, as it has the ability to

47 alter the structure and stability of entire ecosystems. Predation can influence all ecosystem

48 levels, from individual organisms (determining colour, body size, behaviour and life history),

49 to populations (size and stability) and whole communities (species abundance and diversity,

50 regulating herbivore abundance and reducing resource depletion effects) (Powell, Walton, &

51 Jervis, 1996; Sam, Remmel, & Molleman, 2015; Sih, Crowley, McPeek, Petranka, &

52 Strohmeier, 1985). Insects are arguably the largest and most diverse group on the planet,

53 and are also valuable predators, with one quarter of all insect species believed to be

54 predatory or parasitic in at least one life-history stage (Gullan & Cranston, 2014). Insect

55 predators are most well known for their role in agricultural biological control programs, with

56 the economic value of insect-mediated pest control estimated to be over $4.5 billion annually

57 in the US alone (Losey & Vaughan, 2006).

58 Almost every ecosystem in the world benefits from insect predation services; however,

59 measuring and quantifying predators’ impact on their prey is challenging, and the reliability of

60 such evaluations are often questionable (Furlong & Zalucki, 2010; Losey & Vaughan, 2006).

61 Direct observation and measurement of insect predation is very difficult, due to the small

62 size of arthropods, their speed, cryptic habitats, infrequency of their attacks, frequent night

63 activity and the fact predation often leaves no evidence (Low, Sam, McArthur, Posa, &

64 Hochuli, 2014; Powell et al., 1996). As a result, predator presence, absence and density are

65 often measured and impact is inferred – a two-fold increase in predator density is presumed

66 to result in a two-fold increase in predation. This is rarely the case, however, and not a good

67 measure of likely predator effectiveness (Howe, Lövei, & Nachman, 2009; Macfadyen,

68 Davies, & Zalucki, 2015). Informed decisions regarding pest control and Integrated Pest

69 Management (IPM) cannot be made without some “more realisticdirect” evidence of the

70 impact of natural enemy activity (Macfadyen et al., 2015; Zalucki, Furlong, Schellhorn,

71 Macfadyen, & Davies, 2015). Author Manuscript

73 making, and several methods have been developed to achieve this, including direct field

74 observation, use of sentinel prey, exclusion cage studies, use of in-field cameras and video

75 recording and gut content identification (Hughes et al., 1973; Macfadyen et al., 2015; Powell

76 et al., 1996; Sunderland, 1987). The use of sentinel prey involves monitoring the

77 disappearance of, or damage to, prey items provided by the researchers, and is one of the

78 easiest and most commonly used methods to obtain a direct, quantitative measure of

79 predation pressure under field conditions (Howe et al., 2009; Powell et al., 1996). There is

80 considerable flexibility in using sentinel prey: previous studies have used prey from a range

81 of insect orders (most commonly Lepidoptera, Coleoptera and Hemiptera), at every life stage

82 (egg, larvae, nymph, adult and pupae), either live or dead (Lövei & Ferrante, 2017). Another

83 potential ‘prey’ item gaining popularity in recent years is artificial sentinel prey – dummies,

84 created most often from plasticine, and used in place of insect ‘real’ prey (Howe et al., 2009;

85 Lövei & Ferrante, 2017). While certain characteristics of artificial prey may influence attack

86 rate, either positively or negatively, the use of dummy prey has certain advantages that may

87 still make it a suitable option for comparative studies. Artificial prey does not move or

88 behave as true prey might and lacks any potential chemical cues; however, it is cheap and

89 fast to produce, does not require mass rearing and predators can often be identified by

90 marks left in the plasticine (Lövei & Ferrante, 2017).

91 Considering the vast range of potential sentinel prey available, it is surprising that very few

92 studies have compared and evaluated several different sentinel prey types in a single study

93 (Ferrante, Barone, & Lövei, 2017; Peisley, Saunders, & Luck, 2016; Sam et al., 2015). All

94 prey have benefits and limitations, and will be better suited for certain studies over others.

95 Understanding how potential prey options perform in relation to each other is important to

96 ensure the most suitable prey are utilised to address the research questions.

97 This study evaluates the predation rates of four commonly used sentinel prey types.

98 Predation of live and dead Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) eggs, Author Manuscript

100 cameras were used to observe the predators that were attracted to each prey type. This

101 study was conducted in grass and wheat fields to determine whether the observed trends

102 were consistent across different habitat types.

103

104

105 Materials and Methods

106 Study region

107 This study was undertaken at the University of Queensland’s Gatton Campus (27.5521°S,

108 151.3356°E) in the Lockyer Valley, located 80 km west of Brisbane in south-east

109 Queensland, Australia. The region has a humid subtropical climate with hot, humid

110 summers (mean maximum 30-32°C), mild to cool winters (mean maximum 20-23°C) and

111 annual rainfall averaging 750-800 mm. It is a mixed farming region, with fertile soils and

112 intensively cultivated, dominated by vegetable crops, while also supporting fodder crop

113 production, mostly grains and lucerne, and beef and dairy cattle farming.

114 One grass and one crop site were selected, 2.5 km apart. The crop was winter wheat (mid

115 grain-fill, approx. BBCH 85; Lancashire et al., 1991), and was surrounded by other wheat

116 fields and small cattle holding yards (Figure 1a). The grassland was a 50 m wide shallow,

117 grassy dry drainage ditch between a pasture and a recently planted cropped field (Figure

118 1b). The ditch and adjacent pasture were regularly grazed, and at the time of the

119 experiment the grass was long and ready to be grazed upon completion of the experiment.

120 This experiment ran over three consecutive days in mid-September 2017.

121

122 Sentinel prey Author Manuscript

124 H. armigera eggs, dead H. armigera larvae and artificial larvae modelled from plasticine.

125

126 Live and dead eggs

127 H. armigera pupae were obtained from CSIRO Narrabri, their sexes determined and placed

128 into buckets, with approximately ten males and ten females per bucket. Buckets had

129 vermiculite in the bottom and large holes cut into the lids, which were covered with nappy

130 liners to easily observe moth emergence. The buckets were kept in a controlled

131 environment room (CER) at 25C and 55% humidity under a 14:10 day:night light cycle.

132 Honey water (2 g honey, 2 g sugar and 0.2 g ascorbic acid dissolved in 100 mL water) was

133 placed into the buckets a day before the pupae were predicted to begin emerging to provide

134 food for the moths. Upon emergence, the buckets were lined with thick, light green A4 paper

135 and the nappy liner in the bucket lid was replaced with the same paper, cut to size and with

136 breathing holes punched out. Once egg laying began, this paper was changed daily and

137 placed into the freezer to kill any eggs. These eggs were frozen for 1-3 d and used for the

138 experiments (Figure 2a). On the days of the experiment, the paper was collected from the

139 moth buckets, cut into 2-3 cm ‘cards’ and these egg cards were placed into the field as the

140 live egg sentinel prey (Figure 2b). All cards contained ten eggs.

141

142 Dead larvae

143 Early-instar larvae were obtained from CSIRO Narrabri and kept on diet trays in the same

144 CER as the moth buckets. Once the desired size was reached (4th-5th instar; approx. 3.5

145 mm x 30 mm – corresponding to the size of the artificial larvae), larvae were killed by

146 freezing (-20° C) and stored there until use (3-5 d). The frozen larvae were glued onto 3 x 3

147 cm squares of the same thick green paper used for the egg cards using superglue (Loctite Author Manuscript

149 ambient temperature by the time they were placed into the field (Figure 2c).

150

151 Artificial larvae

152 Dummy larvae were created out of plasticine (Educational Colours, Victoria, Australia) using

153 a garlic press, creating larvae approximately 3.5 mm x 30 mm. Four colours of plasticine

154 were mixed together in an attempt to create mottled, realistic-looking larvae (Olive green

155 RM500COG, Terracotta RM500CTC, Light green RM500CGR and Brown RM500CBRN).

156 Gloves were worn while handling the plasticine to prevent contaminating the models with

157 human scent (Sam et al., 2015). The dummy larvae were glued onto 3 x 3 cm squares of

158 the same thick green paper used for the egg cards using superglue (Loctite gel control super

159 glue, Ohio, USA), before being placed into the field (Figure 2d).

160

161 Field design and methodology

162 A 20 m x 25 m plot was located at each site: one plot in the grass field and one in the wheat

163 crop. A randomised complete block design was used, with each plot divided into five 5 x 20

164 m rectangular blocks and each of these blocks containing one sample each of the four

165 different prey types, placed 5 m apart in a random order. One sample of sentinel eggs

166 consisted of a single egg card with ten eggs, either alive or dead. One sample of sentinel

167 larvae comprised three larvae, either dead or artificial, placed within a 30 cm diameter area.

168 All prey types were pinned onto upturned condiment cups (3 x 4 cm diameter x 3 cm height)

169 that were secured to the ground, elevating them slightly off the ground to avoid damage from

170 dirt or other debris. Two controls of each prey type were placed per field. Controls

171 consisted of prey items double-bagged in small mesh bags, each closed tightly with a

172 drawstring, and tied to vegetation at ground level within a 30 cm diameter area of the Author Manuscript

174 experiment was repeated three times over consecutive days.

175 Field cameras (Redleaf trail cameras (RD1006), Shenzhen Redleaf Technology Co., Ltd,

176 China) were set up to record one of each prey type at each of the two field sites (Figure 3).

177 Cameras positions were randomly selected and changed daily, along with the prey cards.

178 These cameras were attached to metal stands held in place with a tent peg, and sat 30 cm

179 above the prey items, facing downwards. Cameras took photographs every ten seconds,

180 and their infrared sensor ability allowed photographs to be taken during the night.

181

182 Egg parasitism

183 Upon return to the lab, all egg cards were pinned onto styrofoam boards and stored in

184 styrofoam boxes at room temperature. The cards were checked daily and all emerged

185 larvae were killed. Larval emergence was assumed finished after two days of finding no new

186 larvae. Once emergence was completed, egg cards were placed into individually labelled

187 vials and stored in a cardboard box at room temperature for several weeks before being

188 checked for the emergence of any parasitoids.

189

190 Prey analysis

191 Photographs of all prey samples were taken before and after being placed into the field. Egg

192 predation rates were assessed by counting the number of missing eggs on each card, while

193 larval predation was calculated by recording the number of larvae damaged or eatenNumber

194 of missing eggs from each egg card and the number of larvae damaged or eaten were

195 recorded, with these presumed to be due to predation. Marks left in the plasticine of the

196 artificial larvae allowed the number of predation events and type of insect/s attacking to be

197 determined (chewing or piercing insects, small mammals or unknown) using several Author Manuscript

199 al., 2009; Low et al., 2014).

200 Data collected from the field cameras was analysed using the open-source video processing

201 software VirtualDub to work through the photos and record each time a prey item was

202 approached or attacked by a predator. ‘Approaches’ were defined as a predator arriving on

203 the prey card, but leaving without attempting to attack the prey. ‘Attacks’ were defined as a

204 predator clearly attacking and/or eating the prey item or, in the case of very tiny insects that

205 were not clear in the photos, remaining in a single spot for an extended period and

206 appearing to feed on the prey (minimum time 1 min; majority > 1 h). All animals that

207 attacked or approached prey items were identified if possible and the time of day for each

208 event was recorded.

209

210 Data analysis

211 No parasitoids emerged from the egg cards; therefore, no measure of parasitism is included

212 in the results. None of the control larvae experienced any predation, while only two of the 24

213 control egg cards were missing eggs. These live egg cards were missing one and two eggs

214 per card, respectively, equating to just 2.5% of live eggs missing.

215 Predation rates of sentinel eggs (live and dead) and larvae (dead and artificial) were

216 analysed separately using logistic regression (i.e. generalised linear models (GLMs) with a

217 binomial error distribution, or quasibinomial in the case of overdispersion). Models were

218 created using all measured variables, including sampling time (sampling day 1, 2 or 3), field

219 type (grass or crop), field position (block number and location within each block) and prey

220 type (live or dead eggs, dead or artificial larvae), and simplified. Interactions between prey

221 type and field position, and prey type and field type, were included in the analysis. Analysis

222 of Variance (ANOVA) was used to determine significance in the simplified model.

223 Differences in predation of the individual prey types between the grass and crop fields were Author Manuscript

225 Models were created using variables including sampling time, field type and field position,

226 and simplified.Logistic regression was used to analyse predation rates of sentinel eggs (live

227 and dead) and larvae (dead and artificial) separately as a function of sampling time, field

228 type, field position and prey type. Differences in predation of the individual prey types

229 between the grass and crop fields were also analysed using logistic regression. Logistic

230 regression is a generalised linear model (GLM) with a binomial distribution, or quasibinomial

231 in the case of overdispersion. All analyses were performed in R (version 3.4; R Core Team,

232 2017; RRID: SCR_001905) using a significance level of p < 0.05.

233

234

235 Results

236 Comparison of sentinel eggs and larvae

237 No significant effect of time was found for either eggs or larvae; therefore, data for the three

238 sampling days was compiledcombined for further analysis. Across both fields, 11% of live

239 eggs and 8% of dead eggs were removed during the three days of exposure. Eggs in the

240 grassland were preyed upon more often than eggs in cropped fields (ANOVA, Chi-square =

241 13.639, df = 1, p < 0.001; Figure 4). Prey type alone did not account for a significant

242 proportion of the variation in predation rates (ANOVA, Chi-square = 0.7516, df = 1, p =

243 0.386); however, predation on different prey types was varied dependingent on their location

244 of prey in the fields (ANOVA, Chi-square = 13.09, df = 4, p = 0.011).

245 During the three days of exposure, 89% dead larvae and 21% artificial larvae were damaged

246 across both fields. Dead larvae were preyed upon significantly more than artificial larvae

247 (ANOVA, Chi-square = 96.224, df = 1, p < 0.001). Field type was important in determining

248 whether larvae were vulnerable to predation (ANOVA, Chi-square = 16.263, df = 1, p < Author Manuscript

250 preyed upon more often in the crop.

251

252

253 Predation of artificial larvae

254 Of the 90 artificial larvae exposed during the experiment, 19 showed evidence of predation.

255 Chewing arthropods were responsible for 48% of the observed predation, 33% of predation

256 was attributed to small mammals, 14% to piercing insects and 5% of predation marks were

257 unidentified (Figure 5). Attack rates in the two fields did not differ, with 10 larvae showing

258 evidence of predation retrieved from the grass field and 9 larvae from the crop (Figure 6).

259 Chewing arthropods were the dominant predators in both the grass and the crop,

260 responsible for half of the observed predation in each field.

261

262

263 Field camera analysis of predators

264 Analysis of field camera photos gave some insight into the diversity and activity of the

265 predators attacking the sentinel prey (Figure 7). Field cameras observed predator activity

266 throughout the entire 24 h exposure period, except between midday and 15:00, which

267 coincided with the time prey and cameras were being collected and/or deployed (Figure 8).

268 Activity in the cropped field peaked at dusk before dropping and remaining consistent

269 throughout the night. In the grass field, predator activity peaked at dawn and dusk, and

270 steadily decreased throughout both the day and night (sunrise and sunset occurred just

271 before 06:00 and 18:00, respectively). Author Manuscript

273 a total of 57 individuals observed with the crop field cameras opposed to 40 individuals

274 observed in with the grassland cameras. However, attack rates were highest in the

275 grassland: 48% of the predators observed with the cameras attacked their prey in the

276 grassland, opposed to just 23% of observed predators in the crop. Small mammals and

277 beetles were the dominant predators observed in the crop, while grassland predation was

278 dominated by ants, beetles, and tiny juvenile and unidentified insects.

279 Dead larvae were observed to experience the highest attack rates from the widest range of

280 predators, with beetles, ants and small mammals their most dominant predators (Figure 9).

281 Sentinel eggs were more likely to be attacked by tiny insects such as beetles and mirid

282 nymphs and other immature insects. The field cameras did not observe any predation of

283 artificial larvae in either field, or dead eggs in the crop.

284

285

286 Discussion

287 Different sentinel prey types experienced different levels of predation; however, the same

288 similar trends in predation were observed within and for most prey types between the

289 different habitats studied. This suggests that for simple comparison studies, a range of

290 different sentinel prey types could be relied upon to provide a suitable indication of predator

291 activity within and between different habitats. Alternatively, using several prey types

292 together in a single experiment can provide greater insight into the natural enemy community

293 and should be considered. Each prey type has unique benefits and limitations, and these

294 should be carefully considered and evaluated if a realistic estimate of predation is required.

295

296 Live and dead sentinel eggs Author Manuscript

298 rates observed in this study were unexpected (Ehler, 2006; Gardiner, Prajzner, Burkman,

299 Albro, & Grewal, 2014; Phillips & Gardiner, 2016). Sentinel eggs are useful as they are

300 immobile and can be produced quickly in large numbers; however, maintaining egg-laying

301 cultures is time consuming and live eggs often have a small window of opportunity for use in

302 the field before hatching. These issues are often overcome by freezing the eggs, effectively

303 killing them to prevent untimely hatching and allowing them to be stored until needed

304 (Blaauw & Isaacs, 2015; Gardiner et al., 2014; Werling, Meehan, Robertson, Gratton, &

305 Landis, 2011). This study observed no significant differences between predation rates of live

306 or dead eggs; however, live eggs did record slightly higher predation rates and were

307 observed to be attacked by a wider range of predators than dead eggs, suggesting . This

308 suggests that some predators may show a greater attraction to live eggsprey may be

309 preferred by predators and therefore provide more realistic results. Our results also

310 indicated that predation on different prey types was dependent on the location of prey in the

311 fields, with prey placed in certain locations being preyed upon more often than those

312 elsewhere in the field. This may be a result of specific foraging strategies employed by

313 grassland predators, such as ants. While ants were not observed to feed on the sentinel

314 eggs during this experiment, they are known to be important predators in grassland habitats

315 (Nemec, 2014; Sanders & Platner, 2007; Wills & Landis, 2018) and prey on H. armigera

316 eggs (Mansfield, Elias, & Lytton-Hitchins, 2003; Van Den Berg & Cock, 2010). Ants are

317 central place foragers (Bell, 1990), and the spatial variation in their nest locations can result

318 in spatial variation in predation of stationary prey, as seen in this experiment. One major

319 limitation with sentinel eggs is that while removed eggs are easily observed and recorded,

320 eggs that have been damaged by tiny sucking insects can be difficult to distinguishdamage

321 to eggs by tiny sucking insects can be difficult to identify. Our field cameras picked up

322 several tiny insects, including beetles, mirid nymphs and other juvenile insects, that spent

323 minutes to hours feeding on eggs and leaving little to no easily identifiable evidence. These Author Manuscript

325 therefore egg predation may be slightly underestimated as a result.

326

327 Dead and artificial larvae

328 Dead larvae experienced higher rates of predation attack than artificial larvae. However,

329 field cameras observed that scavengers, including cockroaches and flies, were attracted to

330 the dead larvae, potentially leading to inflated estimates of predation. More reliable methods

331 for utilising larvae as sentinel prey could include using live larvae that have been

332 immobilised, tethered or otherwise contained to keep them in one place. While several

333 studies have applied these methods (Dupuy & Ramirez, 2019; Frank, Wratten, Sandhu, &

334 Shrewsbury, 2007; Greenop et al., 2019; Lowenstein, Gharehaghaji, & Wise, 2017;

335 Mathews, Bottrell, & Brown, 2004; Zou et al., 2017), they present their own challenges and

336 only small numbers of larvae are likely to be deployed in field experiments as they are time-

337 consuming. Artificial larvae, on the other hand, are quick and easy to create and can be

338 deployed rapidly in large numbers; however, the low rates of predation observed in this

339 study suggest that many predators are not attracted and thus predation rates estimated from

340 artificial prey may be underestimated (Lövei & Ferrante, 2017). Despite this concern, several

341 comparative studies have used artificial prey with apparent success, suggesting they may be

342 suitable and informative for certain types of studies (Ferrante et al., 2014; Howe, Nachman,

343 & Lövei, 2015; Loiselle & Farji Brener, 2002; Tvardikova & Novotny, 2012). Future research

344 comparing predation of live‐ and artificial larvae would be valuable, particularly if

345 accompanied by field camera or video monitoring equipment to identify the attacking

346 predators.

347

348 Field cameras complement sentinel prey experiments Author Manuscript

350 one that should be more widely utilised. Using sentinel prey alone is already a commonly

351 used method for assessing field predation rates, so the addition of camera or video

352 monitoring adds little additional work for potentially significant gain. Previous studies have

353 used monitoring equipment to assess predation of a range of pest species, with valuable

354 results (Frank et al., 2007; Merfield, Wratten, & Navntoft, 2004; Phillips & Gardiner, 2016;

355 Zou et al., 2017). For example, camera monitoring of brown planthoppers in rice determined

356 that frogs played a prominent role in controlling the pest, yet their contribution ad thus far

357 been largely unrecognised (Zou et al., 2017). Camera and video monitoring equipment

358 provides data that areis not possible to obtain with other methods, such as the predator

359 species responsible for predation events, the time of day, duration and frequency of attacks,

360 quantity of prey consumed and any instances of scavenging or secondary predation. This

361 information affords a more complete understanding of the predator-prey dynamics in the

362 environment under study, filling a significant knowledge gap that currently exists in biocontrol

363 research.

364 The biggest issues with using camera or video equipment in the field is the cost of

365 purchasing the equipment, potentially often difficult or time consuming deployment, potential

366 equipment theft or vandalism, time spent reviewing output and the quality of the output.

367 Many arthropod predators are most active around dawn and dusk and many important

368 predators are nocturnal (Merfield et al., 2004); thus, a significant proportion of predator

369 activity will be captured under infrared light, which can result in somewhat grainy pictures

370 from which identifying very small arthropods can be challenging. For example,

371 approximately half of the photos analysed for this experiment, and around 53% of predator

372 activity, were captured under infrared light. Despite these issues, field cameras provide a

373 unique and informative insight into predator activity under field conditions. Understanding

374 not only the level of predation services being provided to an area, but which predators are Author Manuscript

376 pest management decision making.

377

378 Conclusions

379 While any sentinel prey type could be suitable for use in most comparative studies, allcan

380 provide useful information in comparative studies, the various kinds of sentinel prey have

381 their own benefits and limitations, with some likely to provide more realistic measures of

382 predation pressure than others. For smaller studies with fewer sentinels, utilising prey that

383 attracts a greater proportion of attacks may be most beneficial, while larger studies may

384 prefer the rapid creation and deployment of artificial prey, allowing the large numbers of prey

385 to negate the potentially lower predation rates of individuals but enable comparison among

386 treatments. Alternatively, studies targeting specific predator species or groups require

387 careful selection of prey type as different predators are attracted to different prey, while

388 using several types of prey together can result in greater insight about the natural enemy

389 community. Therefore, potential prey types should be carefully considered and evaluated

390 when designing experiments to determine which is most suitable to address the research

391 questions.

392

393

394 Conflicts of interest

395 None.

396

397

398 Author ContributionAuthor Manuscript

400 Rebecca K. Nagy conducted experiments, collected and analysed data, and wrote the first

401 version of the manuscript.

402 Nancy A. Schellhorn and Myron P. Zalucki edited the manuscript.

403 All authors read and approved the manuscript.

404

405

406 Data availability Statement

407 The datasets generated and analysed during this study are available in UQ eSpace at

408 https://doi.org/10.14264/uql.2019.762.

409

410

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531 Author Manuscript

533 Figure legends

534 Figure 1. The (a) wheat crop and (b) wide grassy ditch used for sentinel prey experiments, 535 as seen during the experimental period.

536

537 Figure 2. Sentinel prey: (a) dead H. armigera eggs; (b) live H. armigera eggs; (c) dead H. 538 armigera larvae; and (d) artificial plasticine larvae.

539

540 Figure 3. Cameras set up in (a) grass and (b) wheat crop.

541

542 Figure 4. Mean predation (± SE) of different sentinel prey in the grass (light grey) and crop 543 (dark grey) fields. Symbols (***) denote significance (p < 0.001) between grass and crop 544 fields for each prey type (Live eggs: ANOVA, Chi-square = 16.159, df = 1, p < 0.001; Dead 545 eggs: ANOVA, Chi-square = 31.827, df = 1, p < 0.001; Dead larvae: ANOVA, Chi-square = 546 24.274, df = 1, p < 0.001).

547

548 Figure 5. Examples of predation of artificial larvae by (a) chewing arthropods and (b) small 549 mammals.

550

551 Figure 6. Total number of predation events on artificial larvae by a range of predators in 552 grass (light grey) and cropped (dark grey) fields.

553

554 Figure 7. Camera output showing (a) ant, (b) mouse and (c) juvenile Reduviid feeding on 555 prey.

556

557 Figure 8. Predator activity, represented by the total number of predators observed on the 558 sentinel prey cards, in the grass (light greyblack line) and crop fields (dark grey line) fields 559 during the 24 h exposure period. Deployment and collection occurred between 14:00-15:00 Author Manuscript

562

563 Figure 9. Predators responsible for attacking different sentinel prey in the grass (left) and 564 crop (right) fields during the 24 h exposure period. Author Manuscript

(a) (b)

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(a) (b)

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(a) (b)

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*** Grass 100 Crop

SE) 80 ±

40 *** *** Meanpredation (%) ( 20

0 Live eggs Dead eggs Dead larvae Artificial larvae

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(a) (b)

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6 Grass 5 Crop

1 Numberpredation of events

0 Chewing insects Piercing insects Small mammals Unknown

Predators

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(a) (b) (c)

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16 Grass 14 Crop 12

2 Numberpredator of approaches

0 Deployment 18:00 - 21:00 - 00:00 - 03:00 - 06:00 - 09:00 - 12:00 - - 18:00 21:00 00:00 03:00 06:00 09:00 12:00 collection

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20 Small mammal 18 Unidentified insect 16 Immature insect 14 Mirid nymph 12 Wasp/fly 10 Cockroach 8 Ant 6 Beetle 4 Numberpredator of attacks 2 0 Live Dead Dead Artificial Live Dead Dead Artificial eggs eggs larvae larvae eggs eggs larvae larvae GRASS CROP

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