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1,342 results for “pest”
Raw sequence of: Field investigation- and dietary metabarcoding-based screening of arthropods that prey on primary tea pests
<p><span>Predatory natural enemies play key functional roles in </span><span>biological control</span><span>.</span><span> Abundant </span><span>predatory arthropod species</span> <span>have been recorded</span><span> in tea plantation ecosystems.</span><span> However, few studies have comprehensively evaluated the control effect of predatory arthropods on tea pests in the field. We performed a one-year field investigation and collected predatory arthropods and pests in the tea </span><span>canopy.</span><span> Total 7,931 predatory arthropod individuals were collected, and </span><em><span>Coleosoma blandum</span></em><span> (Araneae, Theridiidae) was the most abundant species in the studied tea plantation. The population dynamics between <em>C. blandum</em> and four main tea pest species (<em>Aleurocanthus spiniferus, Empoasca onukii, Ectropis grisescens</em> and <em>Scopula subpunctaria</em>) were established using the individual number of predators and pests in each month. The results showed that the occurrence of </span><span>C. blandum</span> <span>showed high synchronism</span><span> with the occurrence of <em>A. spiniferus, Em. onukii </em>and <em>Ec. grisescens</em></span><span>. </span><span>The prey spectrum of <em>C. blandum</em> was </span><span>further analyzed using DNA metabarcoding. Among prey species, <em>A. spiniferus, Em. onuki</em>i and <em>Ec. grisescens</em> were included, and the relative abundance and positive rates of target DNA fragments of <em>A. spiniferus </em>were </span><span>obviously</span><span> greater</span> <span>than</span><span> those of other two pests.</span></p>
Bocage landscape restricts the gene flow of pest vole populations
<p><span><span>The population dynamics of most animal species inhabiting agroecosystems may be determined by landscape characteristics, with agricultural intensification and reduction of natural habitats influencing dispersal patterns. Increasing landscape complexity would thus benefit endangered species by providing different ecological niches, but it could also lead to undesired effects in species that can act as crop pests and disease reservoirs. We tested the hypothesis that a highly variegated landscape influences the dispersal, and hence patterns of genetic structure, in agricultural pest voles. Ten populations of fossorial water vole, <i>Arvicola scherman</i>, located in a bocage landscape in Atlantic NW Spain were studied using DNA microsatellite markers and a graph-based model. The results showed a strong isolation-by-distance pattern with a strong and significant genetic correlation at smaller geographic scales, while genetic differentiation at larger geographic scales indicated a hierarchical pattern of up to eight genetic clusters. A metapopulation-type structure was observed, immersed in a landscape with a low proportion of suitable habitats. Matrix scale rather than matrix heterogeneity <i>per se</i> may have an important effect upon determining gene flow, acting as a demographic sink. The identification of sub-populations, considered to be independent management units, allows the establishment of feasible population control efforts in this area.<b> </b>These insights support the use of agro-ecological tools aimed at recreating enclosed field systems when planning integrated managements for controlling patch-dependent species such as grassland voles.</span></span></p>
Datasets from: The distribution of covert natural enemies of a globally invasive crop pest, the fall armyworm, in Africa; enemy-release and spillover events
<p>These datasets are for the analyses carried out in paper in Journal of Animal Ecology titled 'The distribution of covert natural enemies of a globally invasive crop pest, the fall armyworm, in Africa; enemy-release and spillover events.' The authors of the paper are Amy J. Withers, Annabel Rice, Jolanda de Boer, Philip Donkersley, Aislinn J. Pearson, Gilson Chipabika, Patrick Karangwa, Bellancile Uzayisenga, Benjamin A. Mensah, Samuel Adjei Mensah, Phillip Obed Yobe Nkunika, Donald Kachigamba, Judith A. Smith, Christopher M. Jones and Kenneth Wilson<span>.</span></p> <p><span><span> </span></span><span>Invasive species pose a significant threat to biodiversity and agriculture worldwide, and here we investigated the prevalence of natural enemies in fall armyworm</span><span> (</span><em>Spodoptera frugiperda</em><span>) </span><span>in Africa</span><span>. </span><span>This study aimed to identify which microbial pathogens are present in invasive fall armyworm, and determine the geographical, meteorological, and temporal variables that influence prevalence. </span><span>Larval samples were screened from Malawi, Rwanda, Kenya, Zambia, Sudan, and Ghana for the presence of four different microbial natural enemies; two nucleopolyhedroviruses, Spodoptera frugiperda NPV (SfMNPV) and Spodoptera exempta NPV (SpexNPV); the fungal pathogen </span><em>Metarhizium rileyi</em><span>;</span><span> and the bacterium </span><em>Wolbachia</em><span>. One dataset (</span>ALL_diseaseprevalence_year_season<span>) includes the results of this screening for all four microbial nartural enemies and sampling information, the other dataset (</span>SfMNPVprevalence_weather_topographic_temporal_variables<span>) includes the results for SfMNPV and sampling information alongside variables relating to temperature, rainfall, elevation, growing season and time since the fall armyworm first arrived in each country. These variables were used to investigate whether SfMNPV prevalence was affected by</span><span> </span><span>geographical, meteorological or temporal variables.</span></p>
FIGURES 1−6 in Syncola crypsimorpha (Meyrick, 1922) (Gelechioidea: Blastobasidae): A new pest species associated with cultured lac in India
FIGURES 1−6. Adult forewing patterns and adult features of Syncola crypsimorpha and S. pulverea. 1, Forewing pattern of S. crypsimorpha. 2, Forewing pattern of S. pulverea. 3, Head of S. crypsimorpha, lateral view. Arrow indicates labial palpus ex- tending above vertex of head. 4, Base of antenna showing an unmodfied first flagellomere of S. crypsimorpha. Arrow indicates unmodified first flagellomere. 5, Forewing venation of S. crypsimorpha. Arrow indicates pterostigma between Sc and R 1. 6, Hindwing venation of S. sp. n.crypsimorpha.
FIGURES 11−12 in Syncola crypsimorpha (Meyrick, 1922) (Gelechioidea: Blastobasidae): A new pest species associated with cultured lac in India
FIGURES 11−12. Female genitalia of Syncola crypsimorpha and S. pulverea. Fig. 11, S. crypsimorpha. 12, S. pulverea.
FIGURES 7−10 in Syncola crypsimorpha (Meyrick, 1922) (Gelechioidea: Blastobasidae): A new pest species associated with cultured lac in India
FIGURES 7−10. Male genitalia of Syncola crypsimorpha and S. pulverea. Fig. 7, S. crypsimorpha. Genital capsule. Fig. 8, phallus. Fig. 9, S. pulverea, Genital capsule. Fig. 10, phallus.
Implications of climate change for environmental niche overlap between five Cuscuta pest species and their two main host crop species
<p><span>Some parasitic plants are major pests in agriculture, but how this might be affected by climate change remains largely unknown. In this study, we assessed this for five generalist holoparasitic <em>Cuscuta </em>species (<em>Cuscuta approximata, C. australis, C. chinensis, C. europaea, C. japonica</em>) and two of their main Leguminosae host crop species (<em>Glycine max </em>and <em>Medicago sativa</em>). For each of the five <em>Cuscuta </em>species and the two crop species, we ran MaxEnt models, using climatic and soil variables to predict their potential current distributions and potential future distributions for 2070. We ran species distribution models for all seven species for multiple climate-change scenarios, and tested for changes in the overlap of suitable ranges of each crop with the five parasites. We found that annual mean temperature and isothermality are the main bioclimatic factors determining the suitable habitats of the <em>Cuscuta </em>species and their hosts. </span><span>For both host species, the marginally to optimally suitable area will increase by 2070 for all four RCP scenarios. For most of the <em>Cuscuta </em>species, the marginally to optimally suitable area will also increase. As the suitable area for both the hosts and the parasites will overall increase, Schoener's D, indicating the relative overlap in suitable area, will change only marginally. However, the absolute area of potential niche overlap may increase up to six-fold by 2070. Overall, our results indicate that larger parts of the globe will become suitable for both host species, but that they could also suffer from <em>Cuscuta </em>parasitism in larger parts of their suitable ranges.</span></p>
Fig. 2 in Inferring Ancestry and Divergence Events in a Forest Pest Using Low-Density Single-Nucleotide Polymorphisms
Fig. 2. Population tree inferred by TreeMix using all 42 sampling sites across the mountain pine beetle range. Terminal branches are labeled using locality information (see Supp Fig. 1 [online only] for further detail) and migration arrows are colored according to migration weight.
Fig. 3. Scenario 9 in Inferring Ancestry and Divergence Events in a Forest Pest Using Low-Density Single-Nucleotide Polymorphisms
Fig. 3. Scenario 9 was identified as the 'best' from 11 competing phylogeographic scenarios. This scenario represents an east-to-west colonization route with stable population sizes in which cluster 4 is derived from clusters 1 and 3 through admixture. Terminal branch labels are consistent with the five STRUCTURE clusters identified (Fig. 1). T = time expressed as number of generations assuming one generation per year; R = inferred migration rate.
Fig. 1 in Inferring Ancestry and Divergence Events in a Forest Pest Using Low-Density Single-Nucleotide Polymorphisms
Fig. 1. Map of mountain pine beetle sites throughout western North America. Each site is represented by a pie chart depicting the average assignment (Q values) of individuals to one of five STRUCTURE clusters (K = 5).
FIGURE 3 in A newly recognised species that has been confused with the global polyphagous pest scale insect, Coccus hesperidum Linnaeus (Hemiptera: Coccomorpha: Coccidae)
FIGURE 3. Adult female of Coccus praetermissus Lin & Tanaka, sp. n. ANT: antenna; AP: anal plate; DA: dorsal areolations; DMD: dorsal microduct; DS: dorsal seta; DT: dorsal tubercle; DTD: dorsal tubular duct; LG: leg; MP: multilocular pore; MS: marginal setae; PAP: preantennal pore; POP: preopercular pores; SP: spiracular pore; SSP: stigmatic spines; VMD: ventral microduct; VTD: ventral tubular duct. Scale bars: 200 µm for ANT, AP; 100 µm for DA, LG; 50 µm for SSP; 10 µm for other details.
FIGURE 2 in A newly recognised species that has been confused with the global polyphagous pest scale insect, Coccus hesperidum Linnaeus (Hemiptera: Coccomorpha: Coccidae)
FIGURE 2. The Maximum Clade Credibility (MCC) tree from analysis of the concatenated dataset (2827 bp). Specimen codes of Coccus hesperidum s. s. (apices of dorsal setae pointed) are in dark blue and those of C. praetermissus sp. n. (apices of dorsal setae bluntly rounded) are in light blue. The tree was rooted using C. penangensis. Branch support is indicated on internal branches (MP bootstrap/Bayesian posterior probability). Only bootstrap values ± 70% and posterior probabilities ± 0.95 are shown. The coloured squares under branches indicate that the branch was present in analyses of that gene. Branch support from individual genes are not shown within C. formicarii (Chinese and Taiwanese populations) and C. hesperidum s. s. Abbreviations as per Table 1.
FIGURE 1. Coccus hesperidum L. A in A newly recognised species that has been confused with the global polyphagous pest scale insect, Coccus hesperidum Linnaeus (Hemiptera: Coccomorpha: Coccidae)
FIGURE 1. Coccus hesperidum L. A. Mature adult females on papaya, Carica papaya, in Colombia. B. Young adult females and nymphs tended by Camponotus ants, in Brazil. Photographs by T. Kondo.
Supplementary material 9 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Unconstrained ordination of wing band areas: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing band areas between males and females (a) Ceratitis anonae, Ceratitis fasciventris and Ceratitis rosa and (b) genotypic clusters A, F1, F2, R1, R2.
Supplementary material 8 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Unconstrained ordination of wing landmarks: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing landmarks between males and females (a) Ceratitis anonae, Ceratitis fasciventris and Ceratitis rosa and (b) genotypic clusters A, F1, F2, R1, R2.
Supplementary material 6 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Preliminary methodological experiment: unconstrained ordination of wing band areas: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing band areas of 14 Ceratitis rosa specimens across sexes, wings (LW: left wing, RW: right wing), repeated images of the same wing (1, 2), repeated measures of the same image (A, B).
Supplementary material 4 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Wing landmarks and wing band areas: Explanation note: Position of wing landmarks and wing band areas (numbers according to Suppl. material 3).
Supplementary material 3 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Wing landmarks and wing band areas: Explanation note: List of wing landmarks and wing band areas considered in this study.
Supplementary material 2 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Map of sampling locations: Explanation note: Number of sampled specimens for each morphospecies are indicated in parentheses.
Supplementary material 15 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 489-506. https://doi.org/10.3897/zookeys.540.9724
Morphometric differences across genotypic clusters (wing band areas): Explanation note: PERMANOVA and a posteriori comparisons (t-statistic) testing differences in multivariate patterns of wing band areas among morphospecies (Ceratitis anonae, Ceratitis fasciventris, Ceratitis rosa). d.f.: degrees of freedom; MS: mean square estimates; F: pseudo-F. Probability of Monte Carlo simulations: n.s.: not significant a P<0.05; ***: P<0.001, **: P<0.01; *: P<0.05 (after False Discovery Rate Correction for repeated a posteriori comparisons).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.