Integrated pest management: theoretical insights from a threshold policy

Costa, Michel Iskin da Silveira; Faria, Lucas Del Bianco

doi:10.1590/s1519-566x2010000100001

Cited by 23 publications

(10 citation statements)

References 27 publications

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“…This directly shows the presence of significant selective fitness disadvantage for homozygotes at the tc_ rph2 locus. Field population based fitness studies [26-29] on phosphine resistant insect strains of R. dominca, T. castaneum, Sitophilus oryzae , Cryptolestes ferrugineus and Oryzaephilus surinamensis reported the existence of biological fitness cost associated with phosphine resistance.…”

Section: Discussionmentioning

confidence: 99%

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

et al. 2013

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BackgroundNext-generation sequencing technology is an important tool for the rapid, genome-wide identification of genetic variations. However, it is difficult to resolve the ‘signal’ of variations of interest and the ‘noise’ of stochastic sequencing and bioinformatic errors in the large datasets that are generated. We report a simple approach to identify regional linkage to a trait that requires only two pools of DNA to be sequenced from progeny of a defined genetic cross (i.e. bulk segregant analysis) at low coverage (<10×) and without parentage assignment of individual SNPs. The analysis relies on regional averaging of pooled SNP frequencies to rapidly scan polymorphisms across the genome for differential regional homozygosity, which is then displayed graphically.ResultsProgeny from defined genetic crosses of Tribolium castaneum (F4 and F19) segregating for the phosphine resistance trait were exposed to phosphine to select for the resistance trait while the remainders were left unexposed. Next generation sequencing was then carried out on the genomic DNA from each pool of selected and unselected insects from each generation. The reads were mapped against the annotated T. castaneum genome from NCBI (v3.0) and analysed for SNP variations. Since it is difficult to accurately call individual SNP frequencies when the depth of sequence coverage is low, variant frequencies were averaged across larger regions. Results from regional SNP frequency averaging identified two loci, tc_rph1 on chromosome 8 and tc_rph2 on chromosome 9, which together are responsible for high level resistance. Identification of the two loci was possible with only 5-7× average coverage of the genome per dataset. These loci were subsequently confirmed by direct SNP marker analysis and fine-scale mapping. Individually, homozygosity of tc_rph1 or tc_rph2 results in only weak resistance to phosphine (estimated at up to 1.5-2.5× and 3-5× respectively), whereas in combination they interact synergistically to provide a high-level resistance >200×. The tc_rph2 resistance allele resulted in a significant fitness cost relative to the wild type allele in unselected beetles over eighteen generations.ConclusionWe have validated the technique of linkage mapping by low-coverage sequencing of progeny from a simple genetic cross. The approach relied on regional averaging of SNP frequencies and was used to successfully identify candidate gene loci for phosphine resistance in T. castaneum. This is a relatively simple and rapid approach to identifying genomic regions associated with traits in defined genetic crosses that does not require any specialised statistical analysis.

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Section: Discussionmentioning

confidence: 99%

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

et al. 2013

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“…The modeling of IPM could be conveyed by means of the alteration of the per capita mortality rates of all components of the model, m s " Ps and m g " Pg , for the specialist and the generalist predator, respectively, where " Ps and " Pg are the per capita mortality coefficients inflicted upon the predator(s) by chemicals used in IPM; correspondingly, (r i " Ni ) and K Ni (1 " Ni /r i ) [i D p,e] for the prey species. This framework was employed in the analysis of an IPM with a generalist and specialist predator subject to a threshold policy, in order to maintain pest prey species at a low level while preserving the endemic species (Costa and Faria 2010).…”

Section: Continuous Time Modeling In Biological Control and Integratementioning

confidence: 99%

Ecological Modelling Applied to Entomology

Ferreira¹,

Godoy²

2014

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This series features volumes of selected contributions from workshops and conferences in all areas of current research activity in applied mathematics. Besides an overall evaluation, at the hands of the publisher, of the interest, scientific quality, and timeliness of each proposal, every individual contribution is refereed to standards comparable to those of leading mathematics journals. This series thus proposes to the research community well-edited and authoritative reports on newest developments in the most interesting and promising areas of mathematical research today.More information about this series at Additional material to this book can be downloaded from http://extras.springer.com

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“…In other words, the three types of strategies aim to reduce the number of pests below the economic injury level (EIL), i.e., the environment is not destroyed [37]. TPC, a control strategy, is implemented once the number of pests reaches and exceeds the ET [38][39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Sliding Dynamics of a Filippov Forest‐Pest Model with Threshold Policy Control

et al. 2019

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A novel Filippov forest-pest system with threshold policy control (TPC) is established while an economic threshold (ET) is used to guide switching. The aim of our work is to address how to reasonably and successfully control pests by means of sliding dynamics for the Filippov system. On the basis of the above considerations, conditions for the existence and stability of equilibria of subsystems are addressed, and the sliding segments and several types of equilibria of the proposed system are defined. These equilibria include the regular/virtual equilibrium, pseudoequilibrium, boundary equilibrium, and tangent point. Further, not only are the relations between nullclines and equilibria of the Filippov system discussed, but the relations between pseudoequilibrium, nullclines, and the sliding segment are discussed. More importantly, four cases of sliding bifurcations of the Filippov system with respect to different types of equilibria of subsystems are investigated, and the corresponding biological implications concerning integrated pest management (IPM) are analyzed. Our results show that the points of intersection between nullclines are equilibria of the system, and the two endpoints of the sliding segment are on the nullclines. It is also verified that the pseudoequilibrium is the point of intersection of the sliding segment and nullclines of the Filippov system, and the pseudoequilibrium exists on the sliding segment. More interestingly, sliding dynamics analysis reveals that the Filippov system has sliding limit cycles, a bistable state and a stable refuge equilibrium point, and the optimal time and strategy for controlling pests are provided.

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Integrated pest management: theoretical insights from a threshold policy

Cited by 23 publications

References 27 publications

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

Ecological Modelling Applied to Entomology

Sliding Dynamics of a Filippov Forest‐Pest Model with Threshold Policy Control

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