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590 results for “Biological Control”
Dataset for: Multi-scale approach to biodiversity proxies of biological control service in European farmlands
<p>Dataset for the BiodivERsA COFUND Woodned project. Information on which spatio-temporal factors are simultaneously affecting crop pests and their natural enemies is required to improve conservation biological control practices. The study was conducted in 80 winter wheat crop fields distributed in three regions of North-western Europe (Brittany, Hauts-de-France and Wallonia), along intra-regional gradients of landscape complexity. Five taxa : aphids, slugs, spiders, carabids, and parasitoids were sampled for two consecutive years. We analysed the influence of regional, landscape and local factors on the abundance and species richness of crop-dwelling organisms, as proxies of the service/disservice they provide. Firstly, there was higher biocontrol potential in areas with mild winter climatic conditions. Secondly, natural enemy communities were less diverse and had lower abundances in landscapes with high crop and wooded continuities, contrary to slugs and aphids. Finally, field boundaries with grass strips were more favourable to spiders and carabids than boundaries formed by hedges, while the opposite was found for crop pests, with the latter being less abundant towards the centre of the fields. These results are quite unexpected because they show that hedgerows and woodlots should not be the unique cornerstones of agro-ecological landscape design strategies. We point out that combining woody and grassy habitats to take full advantage of the features and ecosystem services they both provide may promote sustainable agricultural ecosystems. It may be possible to both reduce pest pressure and promote natural enemies by accounting for taxa-specific antagonistic responses to multi-scale environmental characteristics.</p>
Data and code related to "Difficult control is related to instability in biologically inspired Boolean networks"
<p>This repository contains data and code related to the publication "Difficult control is related to instability in biologically inspired Boolean networks" by Bryan C. Daniels and Enrico Borriello.</p> <p>The python code in the `isolated_fixed_points_code` directory can be used to recreate all results in the paper. See the README.md file in the `isolated_fixed_points_code` directory for more information about how to run the code.</p> <p>The files `240916_cell_collective_ck_and_isolated_fp_data.csv`, `240916_iowa_database_ck_and_isolated_fp_data.csv`, and `240916_random_ck_and_isolated_fp_data.csv` contain data about the networks analyzed in the paper, including the number of attractors and mean control kernel size of each network.</p>
Biological and physical controls on multidecadal acidification in a eutrophic estuary
<p>Estuaries support many ecologically and economically important resources that are especially vulnerable to ocean acidification from rising anthropogenic CO<sub>2</sub>. However, complex local processes in estuaries complicate and may disguise long-term pH trends. For example, terrestrial nutrient runoff and marine coastal upwelling may exacerbate pH variability and declines. We investigated eutrophication impacts on acidification in a central California estuary, Elkhorn Slough, which receives high nutrient loads from intensive surrounding agriculture and upwelling of the California Current System. We examined drivers of acidification including nutrients, ecosystem metabolism, and upwelling by modelling pH trends over 20 years using a Generalized Additive Mixed Model at four sites from the National Estuarine Research Reserve Systemwide Monitoring Program and collected additional water samples to calculate aragonite saturation. Our models revealed acidification trends over two decades which were more pronounced near the marine inlet. Near the marine inlet, high nutrient levels and lower buffering are associated with the greatest rate of acidification in the estuary, which was four times greater than the trend from anthropogenic CO<sub>2</sub> alone. However, tidally restricted areas experienced a different acidification pattern. A tidally restricted site recorded higher mean pH and aragonite saturation and increased pH levels associated with stronger upwelling conditions supplying marine-sourced nutrients. Therefore, variable ecosystem metabolism and tidal cycles are threats to acidity in this location. The effects of enhanced seasonal cycles or long-term trends in different zones of the estuary have implications for monitoring with a temporal frequency and scale to capture coastal acidification risks in estuaries.</p>
Figure 2 in Aculus taihangensis (Acari: Prostigmata: Eriophyidae), a potential biological control agent identified from the highly invasive pest plant, tree of heaven, in Türkiye
Figure 2. Aculus taihangensis. Prodorsal shield and part of dorsal opisthosoma: A. Protogyne, B. Deutogyne.
Figure 4 in Aculus taihangensis (Acari: Prostigmata: Eriophyidae), a potential biological control agent identified from the highly invasive pest plant, tree of heaven, in Türkiye
Figure 4. Aculus taihangensis – Male: A. Prodorsal shield and part of dorsal opisthosoma, B. Coxigenital region.
Figure 5 in Aculus taihangensis (Acari: Prostigmata: Eriophyidae), a potential biological control agent identified from the highly invasive pest plant, tree of heaven, in Türkiye
Figure 5. Dense aggregation of Aculus taihangensis along the midrib of a leaflet of the tree of heaven.
Figure 1 in Aculus taihangensis (Acari: Prostigmata: Eriophyidae), a potential biological control agent identified from the highly invasive pest plant, tree of heaven, in Türkiye
Figure 1. Map of Türkiye showing the provinces from which leaf samples were collected from the tree of heaven in 2022 and 2023 (* indicates the site in Çanakkale Province at which the eriophyid mite, Aculus taihangensis, was collected).
FIGURE 4 in Confirming the identity of the Hypogeococcus species (Hemiptera: Pseudococcidae) associated with Harrisia martinii (Labour.) Britton (Cactaceae) in Australia: implications for biological control
FIGURE 4 Mean (± SE) development time in days of the first- and second-generation females, from the first nymph to adult emergence of the Australian Hypogeococcus (W = 39, p = 0.0545).
FIGURE 3 in Confirming the identity of the Hypogeococcus species (Hemiptera: Pseudococcidae) associated with Harrisia martinii (Labour.) Britton (Cactaceae) in Australia: implications for biological control
FIGURE 3 Phylogenetic trees based on COI sequence data (a) maximum likelihood (IQ-TREE) and (b) Bayesian (Mr. Bayes). Branch labels indicate the ultrafast bootstrap and SH-aLRT values for the maximum likelihood tree and posterior probabilities for the Bayesian tree. Paracoccus marginatus was used as the outgroup for both trees. The host plant family is followed by the country of collection. See Table S1 for further details on host plant species and specimen collection codes for Hypogeococcus. **Country of collection includes Argentina, Brazil, Puerto Rico, and the United States.
FIGURE 2 in Confirming the identity of the Hypogeococcus species (Hemiptera: Pseudococcidae) associated with Harrisia martinii (Labour.) Britton (Cactaceae) in Australia: implications for biological control
FIGURE 2 Phylogenetic trees based on EF1α sequence data (a) maximum likelihood (IQ-TREE) and (b) Bayesian (Mr. Bayes). Branch labels indicate the ultrafast bootstrap and SH-aLRT values for the maximum likelihood tree and posterior probabilities for the Bayesian tree. Planococcus ficus was used as the outgroup for both trees. The host plant family is followed by the country of collection. See Table S1 for further details on host plant species and specimen collection codes for Hypogeococcus.
FIGURE 5 in Confirming the identity of the Hypogeococcus species (Hemiptera: Pseudococcidae) associated with Harrisia martinii (Labour.) Britton (Cactaceae) in Australia: implications for biological control
FIGURE 5 (a) Mean (± SE) pre-oviposition period (days) of the first virgin females, the second virgin, and second mated female generations (H = 19.491, p <0.0001), means labelled with similar letters are not significantly different (Dunn's test, p <0.05); (b) realised fecundity of the first virgin females, the second virgin and second mated female generations (H = 1.2429, p = 0.5372).
FIGURE 1 in Confirming the identity of the Hypogeococcus species (Hemiptera: Pseudococcidae) associated with Harrisia martinii (Labour.) Britton (Cactaceae) in Australia: implications for biological control
FIGURE 1 The different morphological features of the Australian Hypogeococcus: Panels (a) and (b) show that the abdominal region has three circuli (1–3); panel (c) shows that the head region has two antennae (4), numerous slender capitate setae (5), and numerous multilocular pores (6); panel (d) shows the presence of numerous slender capitate setae (5) and numerous multilocular pores (6) in the abdominal region; panels (e) and (f) show that the posterior ventral area possess numerous multilocular pores (6) and numerous conical setae (7); panels (g) and (h) show the foreleg (8) with the curvature attachment point, mid-leg (9) and hindleg (10), both with attachment points ending in a bifurcation. These characters are consistent with Hypogeococcus pungens s.s.
FIGURE 1 in Biological control of weeds in Australia: the last 120 years
FIGURE 1 Number of weed biological control agent releases per decade (known deliberate releases only).
FIGURE 2 in Biological control of weeds in Australia: the last 120 years
FIGURE 2 Releases of plant pathogens per decade for weed biological control (known deliberate releases only).
Data and code repository for Science Advances submission: Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
<p>Data and codes related to the findings reported in the manuscript, "Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy", are deposited. Please refer to the notes located within each folder for further descriptions.</p>
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 3. Basic "Components" of Artificial and Biological (Brain-Controlled) Automation Systems
<p>Although basing on different concepts concerning their details, artificial and biological (brain-controlled) automation systems show common points concerning their principal components (see Figure 3).</p>
Figure 7 in Within-tree distribution and seasonal dynamics of Eutetranychus banksi and Euseius stipulatus (Acari: Tetranychidae, Phytoseiidae) on citrus: Implications for the biological control of the pest
Figure 7 Mean proportion of phytoseiids per leaf outside or inside the canopy (a), on the adaxial or abaxial side of the leaves (b), white or red coloured (c), and collected on fruits (d), whenE. banksi occurred or was absent. Capped bars represent ± standard error (SE). Significant differences are denoted with asterisks. Chi square contingency test:P <0.001.
Figure 1 in Within-tree distribution and seasonal dynamics of Eutetranychus banksi and Euseius stipulatus (Acari: Tetranychidae, Phytoseiidae) on citrus: Implications for the biological control of the pest
Figure 1 Mean number ofE. banksi(a–d) and phytoseiid mites (e–h) per leaf or per cm2 of leaves and fruits. Capped bars represent ± standard error (SE). Bars with different letters are significantly different (Wilcoxon rank-sum test).
Figure 5 in Within-tree distribution and seasonal dynamics of Eutetranychus banksi and Euseius stipulatus (Acari: Tetranychidae, Phytoseiidae) on citrus: Implications for the biological control of the pest
Figure 5 (a–d) Representation of the binomial (logit-link) generalized linear models (GLMs) showing the relationship between the proportion
Figure 3 in Within-tree distribution and seasonal dynamics of Eutetranychus banksi and Euseius stipulatus (Acari: Tetranychidae, Phytoseiidae) on citrus: Implications for the biological control of the pest
Figure 3 Seasonal relative abundance of motile forms of phytoseiid species in four (2018) and six (2019) citrus orchards. Percentage of each species per sampling is represented. The summer decline
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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.