Relevant bibliographies by topics / Predator-Prey

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Predator-Prey'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Predator-Prey"

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Xu, Changjin, and Peiluan Li. "Dynamics in a discrete predator-prey system with infected prey." Mathematica Bohemica 139, no. 3 (2014): 511–34. http://dx.doi.org/10.21136/mb.2014.143939.

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Clements, Hayley S., Craig J. Tambling, and Graham I. H. Kerley. "Prey morphology and predator sociality drive predator prey preferences." Journal of Mammalogy 97, no. 3 (February 22, 2016): 919–27. http://dx.doi.org/10.1093/jmammal/gyw017.

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Schmitz, Oswald. "Predator and prey functional traits: understanding the adaptive machinery driving predator–prey interactions." F1000Research 6 (September 27, 2017): 1767. http://dx.doi.org/10.12688/f1000research.11813.1.

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Predator–prey relationships are a central component of community dynamics. Classic approaches have tried to understand and predict these relationships in terms of consumptive interactions between predator and prey species, but characterizing the interaction this way is insufficient to predict the complexity and context dependency inherent in predator–prey relationships. Recent approaches have begun to explore predator–prey relationships in terms of an evolutionary-ecological game in which predator and prey adapt to each other through reciprocal interactions involving context-dependent expression of functional traits that influence their biomechanics. Functional traits are defined as any morphological, behavioral, or physiological trait of an organism associated with a biotic interaction. Such traits include predator and prey body size, predator and prey personality, predator hunting mode, prey mobility, prey anti-predator behavior, and prey physiological stress. Here, I discuss recent advances in this functional trait approach. Evidence shows that the nature and strength of many interactions are dependent upon the relative magnitude of predator and prey functional traits. Moreover, trait responses can be triggered by non-consumptive predator–prey interactions elicited by responses of prey to risk of predation. These interactions in turn can have dynamic feedbacks that can change the context of the predator–prey interaction, causing predator and prey to adapt their traits—through phenotypically plastic or rapid evolutionary responses—and the nature of their interaction. Research shows that examining predator–prey interactions through the lens of an adaptive evolutionary-ecological game offers a foundation to explain variety in the nature and strength of predator–prey interactions observed in different ecological contexts.
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Troy, Maria Holmgren. "Predator and Prey." Edda 104, no. 02 (May 18, 2017): 130–44. http://dx.doi.org/10.18261/issn.1500-1989-2017-02-04.

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Kraines, David P., and Vivian Y. Kraines. "Predator-Prey Model." College Mathematics Journal 22, no. 2 (March 1991): 160. http://dx.doi.org/10.2307/2686456.

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Agger, William A. "Predator and Prey." Annals of Internal Medicine 119, no. 6 (September 15, 1993): 526. http://dx.doi.org/10.7326/0003-4819-119-6-199309150-00014.

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Mehlum, Halvor, Karl Moene, and Ragnar Torvik. "Predator or prey?" European Economic Review 47, no. 2 (April 2003): 275–94. http://dx.doi.org/10.1016/s0014-2921(01)00194-5.

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Tilahun, Surafel Luleseged. "Prey predator hyperheuristic." Applied Soft Computing 59 (October 2017): 104–14. http://dx.doi.org/10.1016/j.asoc.2017.04.044.

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Hoppensteadt, Frank. "Predator-prey model." Scholarpedia 1, no. 10 (2006): 1563. http://dx.doi.org/10.4249/scholarpedia.1563.

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Purdy, Laurence J. "Predator and Prey." JAMA: The Journal of the American Medical Association 263, no. 4 (January 26, 1990): 523. http://dx.doi.org/10.1001/jama.1990.03440040062029.

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Dissertations / Theses on the topic "Predator-Prey"

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Bolohan, Noah. "Seasonal Variation in a Predator-Predator-Prey Model." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40899.

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Seasonal shifts in predation habits, from a generalist in the summer to a specialist in the winter, have been documented for the great horned owl (Bulbo virginialis) in the boreal forest. This shift occurs largely due to varying prey availability. There is little study of this switching behaviour in the current literature. Since season length is predicted to change under future climate scenarios, it is important to understand resulting effects on species dynamics. Previous work has been done on a two-species seasonal model for the great horned owl and its focal prey, the snowshoe hare (Lepus americanus). In this thesis, we extend the model by adding one of the hare's most important predators, the Canadian lynx (Lynx canadensis). We study the qualitative behaviour of this model as season length changes using tools and techniques from dynamical systems. Our main approach is to determine when the lynx and the owl may invade the system at low density and ask whether mutual invasion of the predators implies stable coexistence in the three-species model. We observe that, as summer length increases, mutual invasion is less likely, and we expect to see extinction of the lynx. However, in all cases where mutual invasion was satisfied, the three species stably coexist.
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Martin, Annik. "Predator-prey models with delays and prey harvesting." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0016/MQ49407.pdf.

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Lindström, Torsten. "Predator-prey systems and applications." Licentiate thesis, Luleå tekniska universitet, 1991. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25928.

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Liu, Shouzong. "AGE-STRUCTURED PREDATOR-PREY MODELS." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1577.

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In this thesis, we study the population dynamics of predator-prey interactions described by mathematical models with age/stage structures. We first consider fixed development times for predators and prey and develop a stage-structured predator-prey model with Holling type II functional response. The analysis shows that the threshold dynamics holds. That is, the predator-extinction equilibrium is globally stable if the net reproductive number of the predator $\mathcal{R}_0$ is less than $1$, while the predator population persists if $\mathcal{R}_0$ is greater than $1$. Numerical simulations are carried out to demonstrate and extend our theoretical results. A general maturation function for predators is then assumed, and an age-structured predator-prey model with no age structure for prey is formulated. Conditions for the existence and local stabilities of equilibria are obtained. The global stability of the predator-extinction equilibrium is proved by constructing a Lyapunov functional. Finally, we consider a special case of the maturation function discussed before. More specifically, we assume that the development times of predators follow a shifted Gamma distribution and then transfer the previous model into a system of differential-integral equations. We consider the existence and local stabilities of equilibria. Conditions for existence of Hopf bifurcation are given when the shape parameters of Gamma distributions are $1$ and $2$.
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Bodey, T. W. "Impacts of predator manipulations on island predator and prey populations." Thesis, Queen's University Belfast, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515898.

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Gourley, Stephen Alexander. "Nonlocal effects in predator prey systems." Thesis, University of Bath, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332378.

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Chrobok, Viktor. "Harvesting in the Predator - Prey Model." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-10510.

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The paper is focused on the Predator-Prey model modified in the case of harvesting one or both populations. Firstly there is given a short description of the basic model and the sensitivity analysis. The first essential modification is percentage harvesting. This model could be easily converted to the basic one using a substitution. The next modification is constant harvesting. Solving this system requires linearization, which was properly done and brought valuable results applicable even for the basic or the percentage harvesting model. The next chapter describes regulation models, which could be used especially in applying environmental policies. All reasonable regulation models are shown after distinguishing between discrete and continuous harvesting. The last chapter contains an algorithm for maximizing the profit of a harvester using econometrical modelling tools.
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Johannesen, Asa. "Predator-prey interactions in aquatic environments." Thesis, University of Leeds, 2013. http://etheses.whiterose.ac.uk/7556/.

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In the first half of this thesis, I have focused on predator ability to locate prey using olfaction and how prey aggregation and turbulence affect prey detection. In chapter 2 I investigate the ability of three spined sticklebacks to compensate for loss of visual cues by using olfaction and find that they can use olfactory cues but that these most likely help the fish detect prey rather than locate prey. In chapter 3 I explore the effect of prey aggregation as an anti-predator strategy when avoiding an olfactory predator and find that aggregated prey survive longer than do dispersed prey. In order to further investigate why this may be, I carried out an experiment using Gammarus pulex as the predator where I recorded search time as a function of prey group size. I found that similarly to detection distance, search time relates to the square root of the number of prey. Finally, I investigate the effect that turbulence in flowing water may have on prey group detection using three spined sticklebacks in a y-maze. I find that risk of detection increases with prey group size but that turbulence lowers this risk. This may mean that there are thresholds below which size prey groups can benefit from turbulence as a ‘sensory refuge’ thus avoiding predators. In the second part of my thesis I focus on the interactions between a cleaner fish and a parasite in an aquaculture setting focusing on whether said fish is useful as a cleaner in industry. I carry out experiments to investigate the use of lumpfish as salmon cleaners in terms of cleaning efficiency and behaviour. I find that while some lumpfish do clean salmon, the required circumstances are still unknown and that further work including selective breeding, personality and effects of tanks is necessary.
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Miner, Jeffrey G. "Turbidity-mediated predator-prey interactions among piscivores, prey fishes, and zooplankton /." The Ohio State University, 1990. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487685204970099.

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Supriatna, Asep K. "Optimal harvesting theory for predator-prey metapopulations /." Title page, contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09phs959.pdf.

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Books on the topic "Predator-Prey"

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Press, Sara. Predator/prey. San Francisco: Biscuit Roller Editions, 2006.

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Predator and prey. New York: Pocket Pulse, 2001.

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Predator and prey. New York: Macmillan/McGraw-Hill, 2008.

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Perry, Steve. Aliens vs. predator prey. New York: Bantam Books, 1994.

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Perry, Steve. Aliens vs. predator prey. New York: Bantam Books, 1994.

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1944-, Barbosa Pedro, and Castellanos Ignacio, eds. Ecology of predator-prey interactions. New York: Oxford University Press, 2005.

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Sidorovich, V. E. Analysis of vertebrate predator-prey community. Minsk: Tesey, 2011.

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Young, Euan. Skua and penguin: Predator and prey. Cambridge: Cambridge University Press, 1994.

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Martyn, Page, and Bailey John 1951-, eds. Pike: The predator becomes the prey. Marlborough: Crowood, 1985.

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Simionescu-Badea, C. L. Forced prey-predator models with delays. Wien: Österreichische Studiengesellschaft für Kybernetik, 1985.

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Book chapters on the topic "Predator-Prey"

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Iannelli, Mimmo, and Andrea Pugliese. "Predator-prey models." In UNITEXT, 145–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03026-5_6.

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Hastings, Alan. "Predator-Prey Interactions." In Population Biology, 151–80. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2731-9_8.

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Ruth, Matthias, and James Lindholm. "Predator-Prey Dynamics." In Dynamic Modeling for Marine Conservation, 43–53. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4613-0057-1_3.

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Wetzel, Robert G., and Gene E. Likens. "Predator-Prey Interactions." In Limnological Analyses, 257–62. New York, NY: Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4757-3250-4_17.

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Gaylord, Richard J., and Kazume Nishidate. "Predator-Prey Ecosystems." In Modeling Nature, 143–54. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4684-9405-1_14.

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Swishchuk, Anatoly, and Jianhong Wu. "Predator-Prey Models." In Evolution of Biological Systems in Random Media: Limit Theorems and Stability, 187–207. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-1506-5_8.

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Wetzel, Robert G., and Gene E. Likens. "Predator-Prey Interactions." In Limnological Analyses, 241–45. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4757-4098-1_17.

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Hannon, Bruce, and Matthias Ruth. "Predator-Prey Models." In Dynamic Modeling, 204–11. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0211-7_18.

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Caraveo, Camilo, Fevrier Valdez, and Oscar Castillo. "Predator-Prey Model." In A New Bio-inspired Optimization Algorithm Based on the Self-defense Mechanism of Plants in Nature, 13–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05551-6_4.

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Peterson, James K. "Predator–Prey Models." In Calculus for Cognitive Scientists, 289–354. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-287-877-9_10.

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Conference papers on the topic "Predator-Prey"

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Padirac, Adrien, Alexandre Baccouche, Fujii Teruo, Andre Estevez-Torres, and Yannick Rondelez. "Predator prey molecular landscapes." In European Conference on Artificial Life 2013. MIT Press, 2013. http://dx.doi.org/10.7551/978-0-262-31709-2-ch113.

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Mullan, Rory, David H. Glass, and Mark McCartney. "Modelling Prey in Discrete Time Predator-Prey Systems." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.447.

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Free, Brian A., Matthew J. McHenry, and Derek A. Paley. "Non-deterministic Predator-Prey Model with Accelerating Prey." In 2018 Annual American Control Conference (ACC). IEEE, 2018. http://dx.doi.org/10.23919/acc.2018.8430786.

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Lan, Gongjin, Jiunhan Chen, and A. E. Eiben. "Evolutionary predator-prey robot systems." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3322033.

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Mobilia, Mauro, Ivan T. Georgiev, and Uwe C. Täuber. "Spatial stochastic predator-prey models." In Stochastic Models in Biological Sciences. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2008. http://dx.doi.org/10.4064/bc80-0-16.

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Mortuja, Md Golam, Mithilesh Kumar Chaube, and Santosh Kumar. "Predator-prey model with proportional prey harvesting and prey group defense." In 2ND INTERNATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS: ICMTA2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0108625.

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KHAN, Q. J. A., and M. AL-LAWATIA. "PREDATOR - PREY RELATIONS FOR MAMMALS WHERE PREY SUPPRESS BREEDING." In Proceedings of the Satellite Conference of ICM 2010. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814338820_0017.

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Mukhopadhyay, Sumona, and Henry Leung. "Cluster Synchronization of Predator Prey Robots." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.470.

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WANG, WENDI. "STABILITY OF STRUCTURED PREY-PREDATOR MODEL." In Proceedings of the 13th Conference on WASCOM 2005. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773616_0070.

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Seitbekova, Yerkezhan, and Timur Bakibayev. "Predator-Prey Interaction Multi-Agent Modelling." In 2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2018. http://dx.doi.org/10.1109/icaict.2018.8747087.

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Reports on the topic "Predator-Prey"

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Osborn, Thomas R., Charles Meneveau, and Houshuo Jiang. Bio-Physical Coupling of Predator-Prey Interactions. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629735.

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Osborn, Thomas, and Charles Meneveau. Bio-physical Coupling of Predator-prey Interactions. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada634770.

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Lundgren, Jonathan, Moshe Coll, and James Harwood. Biological control of cereal aphids in wheat: Implications of alternative foods and intraguild predation. United States Department of Agriculture, October 2014. http://dx.doi.org/10.32747/2014.7699858.bard.

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The overall objective of this proposal is to understand how realistic strategies for incorporating alternative foods into wheat fields affect the intraguild (IG) interactions of omnivorous and carnivorous predators and their efficacy as biological control agents. Cereal aphids are a primary pest of wheat throughout much of the world. Naturally occurring predator communities consume large quantities of cereal aphids in wheat, and are partitioned into aphid specialists and omnivores. Within wheat fields, the relative abilities of omnivorous and carnivorous predators to reduce cereal aphids depend heavily on the availability, distribution and type of alternative foods (alternative prey, sugar, and pollen), and on the intensity and direction of IG predation events within this community. A series of eight synergistic experiments, carefully crafted to accomplish objectives while accounting for regional production practices, will be conducted to explore how cover crops (US, where large fields preclude effective use of field margins) and field margins (IS, where cover crops are not feasible) as sources of alternative foods affect the IG interactions of predators and their efficacy as biological control agents. These objectives are: 1. Determine the mechanisms whereby the availability of alternative prey and plant-provided resources affect pest suppression by omnivorous and carnivorous generalist predators; 2. Characterize the intensity of IGP within generalist predator communities of wheat systems and assess the impact of these interactions on cereal aphid predation; and 3. Evaluate how spatial patterns in the availability of non-prey resources and IGP affect predation on cereal aphids by generalist predator communities. To accomplish these goals, novel tools, including molecular and biochemical gut content analysis and geospatial analysis, will be coupled with traditional techniques used to monitor and manipulate insect populations and predator efficacy. Our approach will manipulate key alternative foods and IG prey to determine how these individual interactions contribute to the ability of predators to suppress cereal aphids within systems where cover crop and field margin management strategies are evaluated in production scale plots. Using these strategies, the proposed project will not only provide cost-effective and realistic solutions for pest management issues faced by IS and US producers, but also will provide a better understanding of how spatial dispersion, IG predation, and the availability of alternative foods contribute to biological control by omnivores and carnivores within agroecosystems. By reducing the reliance of wheat producers on insecticides, this proposal will address the BARD priorities of increasing the efficiency of agricultural production and protecting plants against biotic sources of stress in an environmentally friendly and sustainable manner.
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Arnould, John P. Using Animal-Borne Cameras to Quantify Prey Field, Habitat Characteristics and Foraging Success in a Marine Top Predator. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541895.

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Arnould, John P. Using Animal-Borne Cameras to Quantify Prey Field, Habitat Characteristics and Foraging Success in a Marine Top Predator. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada573143.

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Arnould, John P. Using Animal-Borne Cameras to Quantify Prey Field, Habitat Characteristics and Foraging Success in a Marine Top Predator. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada598114.

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Heinz, Kevin, Itamar Glazer, Moshe Coll, Amanda Chau, and Andrew Chow. Use of multiple biological control agents for control of western flower thrips. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7613875.bard.

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The western flower thrips (WFT), Frankliniella occidentalis (Pergande), is a serious widespread pest of vegetable and ornamental crops worldwide. Chemical control for Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae) on floriculture or vegetable crops can be difficult because this pest has developed resistance to many insecticides and also tends to hide within flowers, buds, and apical meristems. Predatory bugs, predatory mites, and entomopathogenic nematodes are commercially available in both the US and Israel for control of WFT. Predatory bugs, such as Orius species, can suppress high WFT densities but have limited ability to attack thrips within confined plant parts. Predatory mites can reach more confined habitats than predatory bugs, but kill primarily first-instar larvae of thrips. Entomopathogenic nematodes can directly kill or sterilize most thrips stages, but have limited mobility and are vulnerable to desiccation in certain parts of the crop canopy. However, simultaneous use of two or more agents may provide both effective and cost efficient control of WFT through complimentary predation and/or parasitism. The general goal of our project was to evaluate whether suppression of WFT could be enhanced by inundative or inoculative releases of Orius predators with either predatory mites or entomopathogenic nematodes. Whether pest suppression is best when single or multiple biological control agents are used, is an issue of importance to the practice of biological control. For our investigations in Texas, we used Orius insidiosus(Say), the predatory mite, Amblyseius degeneransBerlese, and the predatory mite, Amblyseius swirskii(Athias-Henriot). In Israel, the research focused on Orius laevigatus (Fieber) and the entomopathogenic nematode, Steinernema felpiae. Our specific objectives were to: (1) quantify the spatial distribution and population growth of WFT and WFT natural enemies on greenhouse roses (Texas) and peppers (Israel), (2) assess interspecific interactions among WFT natural enemies, (3) measure WFT population suppression resulting from single or multiple species releases. Revisions to our project after the first year were: (1) use of A. swirskiiin place of A. degeneransfor the majority of our predatory mite and Orius studies, (2) use of S. felpiaein place of Thripinema nicklewoodi for all of the nematode and Orius studies. We utilized laboratory experiments, greenhouse studies, field trials and mathematical modeling to achieve our objectives. In greenhouse trials, we found that concurrent releases of A.degeneranswith O. insidiosusdid not improve control of F. occidentalis on cut roses over releases of only O. insidiosus. Suppression of WFT by augmentative releases A. swirskiialone was superior to augmentative releases of O. insidiosusalone and similar to concurrent releases of both predator species on cut roses. In laboratory studies, we discovered that O. insidiosusis a generalist predator that ‘switches’ to the most abundant prey and will kill significant numbers of A. swirskiior A. degeneransif WFTbecome relatively less abundant. Our findings indicate that intraguild interactions between Orius and Amblyseius species could hinder suppression of thrips populations and combinations of these natural enemies may not enhance biological control on certain crops. Intraguild interactions between S. felpiaeand O. laevigatus were found to be more complex than those between O. insidiosusand predatory mites. In laboratory studies, we found that S. felpiaecould infect and kill either adult or immature O. laevigatus. Although adult O. laevigatus tended to avoid areas infested by S. felpiaein Petri dish arenas, they did not show preference between healthy WFT and WFT infected with S. felpiaein choice tests. In field cage trials, suppression of WFT on sweet-pepper was similar in treatments with only O. laevigatus or both O. laevigatus and S. felpiae. Distribution and numbers of O. laevigatus on pepper plants also did not differ between cages with or without S. felpiae. Low survivorship of S. felpiaeafter foliar applications to sweet-pepper may explain, in part, the absence of effects in the field trials. Finally, we were interested in how differential predation on different developmental stages of WFT (Orius feeding on WFT nymphs inhabiting foliage and flowers, nematodes that attack prepupae and pupae in the soil) affects community dynamics. To better understand these interactions, we constructed a model based on Lotka-Volterra predator-prey theory and our simulations showed that differential predation, where predators tend to concentrate on one WFT stage contribute to system stability and permanence while predators that tend to mix different WFT stages reduce system stability and permanence.
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