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      Asymmetry in reproduction strategies drives evolution of resistance in biological control systems

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          Abstract

          The success of biological control may depend on the control agent co-evolving with its target pest species, precluding the emergence of resistance that often undermines chemical control. However, recent evidence of a decline in attack rates of a sexual pest weevil by its asexual parasitoid suggests that evolutionary arms races may not prevent the emergence of resistance if the host and parasitoid do not have reproductive strategies that generate equal amounts of genetic variation. To understand how these asymmetries in reproductive strategies may drive the emergence of resistance, we combined life history data from two pest weevils and their parasitoids (one sexual and one asexual) in the New Zealand pastoral ecosystem, with a population dynamic model that allows the coevolution of hosts and parasitoids. We found that the ratio of the genetic variance of hosts to parasitoids was a key determinant of the emergence of resistance. Host resistance eventually occurred unless the parasitoids had considerably greater additive genetic variance than their host. The higher reproductive rate of asexual parasitoids did little to offset the cost of reduced additive genetic variance. The model predictions were congruent with long-term parasitism rates observed in the field for both of the pests considered (one with a sexual and one with an asexual parasitoid). We then explored the consequences of introducing two parasitoids with different reproductive strategies that attack the same sexual host. The model showed that the sexually reproducing parasitoid always out-competed the asexually reproducing one. Our study shows that any asymmetry in reproductive strategies is extremely important for predicting the long-term success of biological control agents. Fortunately, introduction of sexually reproducing individuals after an initial introduction of asexual strains may overcome the problems of host resistance. We conclude that evolution must be considered when evaluating the long-term outcomes of importation biological control.

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          A methodology for performing global uncertainty and sensitivity analysis in systems biology.

          Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.
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            Insect Behavioral and Morphological Defenses Against Parasitoids

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              A Conceptual Framework for Integrated Pest Management

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 December 2018
                2018
                : 13
                : 12
                : e0207610
                Affiliations
                [1 ] Bio-Protection Research Centre, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
                [2 ] Bio-Protection Research Centre, Lincoln University, Lincoln, New Zealand
                [3 ] AgResearch Ltd., Christchurch, New Zealand
                [4 ] Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire, United Kingdom
                University of Minnesota, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist. SLG affiliation to AgResearch Ltd. does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-4462-139X
                http://orcid.org/0000-0003-0057-6969
                Article
                PONE-D-18-18404
                10.1371/journal.pone.0207610
                6300327
                30566468
                9e329e5b-f13d-45a5-b9d8-8acfa0b0ab37
                © 2018 Casanovas et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 20 June 2018
                : 2 November 2018
                Page count
                Figures: 3, Tables: 3, Pages: 20
                Funding
                Funded by: Bio-Protection Research Centre
                This work was funded by the New Zealand Tertiary Education Commission via the BioProtection Research Centre based at Lincoln University, New Zealand. AgResearch provided support in the form of salary for author SLG, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of this author are articulated in the ‘author contributions’ section.
                Categories
                Research Article
                Biology and Life Sciences
                Species Interactions
                Parasitism
                Biology and Life Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Parasitism
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Parasitism
                Biology and Life Sciences
                Parasitology
                Parasite Evolution
                Biology and Life Sciences
                Agriculture
                Pests
                Insect Pests
                Weevils
                Biology and Life Sciences
                Agriculture
                Pest Control
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Genetics
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Medicine and Health Sciences
                Parasitic Diseases
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogenesis
                Host-Pathogen Interactions
                Custom metadata
                All data used in this study have been published elsewhere before. The doi numbers for the relevant papers are as follows: doi: 10.1073/pnas.1618416114 doi: 10.2307/2404313 doi: 10.1080/09583150050044493 doi: 10.1016/0167-8809(89)90021-2 doi: 10.2307/2403617 doi: 10.1017/S000748530001138X doi: 10.1080/09583159650039386 doi: 10.2307/2404280 doi: 10.3390/insects8030067

                Uncategorized
                Uncategorized

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