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      Effects of Lethal Bronzing Disease, Palm Height, and Temperature on Abundance and Monitoring of Haplaxius crudus

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          Abstract

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          Phytopathogen-induced changes often affect insect vector feeding behavior and potentially pathogen transmission. The impacts of pathogen-induced plant traits on vector preference are well studied in pathosystems but not in phytoplasma pathosystems. Therefore, the study of phytoplasma pathosystems may provide important insight into controlling economically important phytoplasma related diseases. In this study, we aimed to understand the impacts of a phytoplasma disease in palms on the feeding preference of its potential vector. We investigated the effects of a palm-infecting phytoplasma, lethal bronzing (LB), on the abundance of herbivorous insects. These results showed that the potential vector, Haplaxius crudus, is more abundant on LB-infected than on healthy palms. In contrast, other insects are more abundant on healthy over infected-palms or have no difference between the infection status of palms. Additionally, we further examined the impacts of LB, palm height, temperature, and their interactive effects on H. crudus abundance, and the results revealed significant interactive effects of these factors on H. crudus abundance. These results suggest the involvement of multiple biotic and abiotic factors influencing vector preference. The results of the interactive impacts of phytoplasma, palm height, and temperature on vector preference in natural settings provide useful information for optimizing vector monitoring and disease management strategies.

          Abstract

          Insect vector feeding preference and behavior play important roles in pathogen transmission, especially for pathogens that solely rely on insect vector transmission. This study aims to examine the effects of the 16SrIV-D phytoplasma, the causal agent of lethal bronzing (LB) disease of palms, on associated auchenorrhynchan insects. The numbers of auchenorrhynchans collected during weekly surveys during a yearlong study using yellow sticky traps were analyzed. The cumulative number of H. crudus was 4.5 times greater on phytoplasma-infected relative to non-infected palms. Other auchenorrhynchans showed no difference between phytoplasma-infected and non-infected palms or were greater on non-infected rather than on infected palms. Furthermore, we examined the effects of LB, palm height, temperature, and the interactive effects of these factors on H. crudus abundance. When the palms were infected with LB, at low temperature, H. crudus was more abundant on shorter than taller palms; however, H. crudus was more abundant on taller than shorter palms at the median and higher temperatures. These results may indicate that H. crudus prefers LB-infected palms over non-infected palms. The interactive effects of LB, palm heights, and temperature further suggest that vector monitoring and disease management should be optimized according to seasonal variation in temperature.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Using observation-level random effects to model overdispersion in count data in ecology and evolution

            Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation). Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE), where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r 2), which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.
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              Herbivory in global climate change research: direct effects of rising temperature on insect herbivores

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                Author and article information

                Journal
                Insects
                Insects
                insects
                Insects
                MDPI
                2075-4450
                30 October 2020
                November 2020
                : 11
                : 11
                : 748
                Affiliations
                [1 ]Fort Lauderdale Research and Education Center, Department of Entomology and Nematology, University of Florida, 3205 College Ave., Ft. Lauderdale, FL 33314, USA; sn21377@ 123456ufl.edu (N.S.); ahumphries@ 123456ufl.edu (A.R.H.); ehelmick@ 123456ufl.edu (E.E.H.); bbahder@ 123456ufl.edu (B.W.B.)
                [2 ]School of Biological Sciences, University of Nebraska-Lincoln, 412 Manter Hall, Lincoln, NE 68588, USA; cclee@ 123456huskers.unl.edu
                [3 ]Department of Entomology and Nematology, University of Florida, 1881 Natural Area Dr., Gainesville, FL 32608, USA; hahnp@ 123456ufl.edu
                Author notes
                [* ]Correspondence: defenmou@ 123456ufl.edu ; Tel.: +1-954-577-6352
                Author information
                https://orcid.org/0000-0003-4620-727X
                Article
                insects-11-00748
                10.3390/insects11110748
                7692074
                33143096
                c1821351-32f2-4a51-a6d6-7a497838ada3
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 05 October 2020
                : 28 October 2020
                Categories
                Article

                insect vector,phytoplasma,vector preference,interactive effects,hemiptera,cixiidae

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