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6,861 results for “Animals”
FIG. 6 in The use of animals in Northern Mesoamerica, between the Classic and the Conquest (200-1521 AD). An attempt at regional synthesis on central Mexico
FIG. 6. — Hierarchical clustering of the: A, taxa; and B, sites analysed in the Canonical Analysis. Abbreviations: Aq., Aquatic animals; Can., Canids; Oth., Miscelanaous taxa; Exo., exotic animals; Ov., white-tailed deer; Art., other artiodactyls; Fel., felids; Sc., small carnivores; Lag., lagomorpha; Com., commensal animals; Tur, turkey; Rap., prey birds; Tiz., Tizayuca; Calix., Calixtlahuaca; Bar-Clas., Barajas Classic/Early Postclassic occupation; Bar-PCR, Barajas Late Postclassic occupation; E.S., El Salitre; Ang., Angamuco.
FIG. 5 in The use of animals in Northern Mesoamerica, between the Classic and the Conquest (200-1521 AD). An attempt at regional synthesis on central Mexico
FIG. 5. — Distribution of CA scores on: A, C1xC2 axes; and B, C1xC3 axes. Taxa bubbles surfaces represent their actual inertia in each plan. Sites and sup- plemental individuals are normalized to 1. Abbreviations: Aq., Aquatic animals; Can., Canids; Com., commensal animals; Ov., white-tailed deer; Tur, turkey.
FIG. 4 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 4. — La mouche parasite Hippobosca longipennis (Fabricius, 1805), découverte dans le pelage d'une momie de chiot d'époque romaine (site de El Deir, Égypte) (photo: J.-B. Huchet). Échelle: 1 mm.
FIG. 5 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 5. — Melophagus ovinus (Linnaeus, 1758), le parasite du mouton. Dessin d'une femelle par A. J. E. Terzi. (Copyright: Crédit Wellcome Library, London, Iconographic Collections, n° V0022537). Échelle: 1 mm.
FIG. 3 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 3. — Spécimen archéologique du pou du chien Trichodectes canis De Geer, 1778 (Site Inuit de Oakes Bay, HeCg-08, Labrador: 17e-18e siècles) (photo: F. Dussault, département d'Archéologie, Memorial University of Newfoundland, St. John's, Canada). Échelle: 250 µm.
FIG. 2 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 2.— Différences morphologiques entre la puce du chien et du chat: A, Ctenocephalides canis (Curtis, 1826), tête en vue latérale; B, Ctenocephalides felis (Bouché, 1835), idem (d'après Robinson 2005, modifiée).
FIG. 6 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 6. — Gasterophilus intestinalis, la mouche parasite du cheval. Dessin de A.J.E. Terzi (c. 1919) (Copyright: Crédit Wellcome Library,London, Iconographic Collections, n° V0022577). Échelle: 4 mm.
FIG. 8. — A in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 8. — A, momie de chiot d'époque romaine présentant une parasitose sévère (site de El Deir, Égypte) (photo: C. Callou, MNHN); B, détail de l'oreille gauche du chiot sévèrement infestée par la tique brune du chien Rhipicephalus sanguineus (photo: J.-B. Huchet); C, fresque provenant de la tombe d'Intef, région de Thèbes, Haute Égypte (Dra Abou el-Naga, c. 1473-1458 av. J.-C.) représentant un Canidae vraisemblablement parasité par des tiques (facsimile: Nina de Garis Davies, 1881-1965) – Numéro d'accès: 31.6.38. Image copyright © The Metropolitan Museum of Art, New York. Échelles: A, 10 cm; B, 10 mm.
FIG. 7 in L'animal-amphitryon : archéologie de l'ectoparasitisme
FIG. 7. — Gasterophilus intestinalis, larve de 3e stade. Dessin de A.J.E. Terzi (c. 1919) (Copyright: Crédit Wellcome Library, London, Iconographic Collections, n° V0022578ER). Échelle: 3 mm.
Behavioral data and analyses of competitive interactions between invasive and native ant species [from Cordonnier et al. 2021, Animals]
<p>This README accompanies the files "data_Cordonnier_Animals.txt" & "script_Cordonnier_Animals.txt"</p> <p> </p> <p>Associated publication : </p> <p>The native ant <em>Lasius niger</em> can limit the access to resources of the invasive Argentine ant</p> <p>M. Cordonnier, O. Blight, E. Angulo, and F. Courchamp</p> <p>Published in <em>Animals</em></p> <p> <br> ********************************** CONTENTS *****************************<br> The data are in table form with TABs as variables field delimiters so they can be readily imported in any statistical package or spreadsheet program. Please, contact me if you need the file formatted otherwise. </p> <p> </p> <p>*******************************************************************************<br> Variable names and descriptions</p> <p> </p> <p>Status_Lh status of Linepithema humile (Colonizer or Resident) </p> <p>opp species of the opponent</p> <p>combirc combination of status and species interacting</p> <p>temp temperature during the test</p> <p>hygro hygrometry during the test</p> <p>categ interacting species combination</p> <p>n_deadtot_opp total number of dead opponent workers</p> <p>t_50dead_opp time when 50% of the opponent mortality load have been diagnosed</p> <p>t_interact time of the first interaction between L. humile and opponent workers</p> <p>t_maxfights time when the maximal number of simultaneous fights occurs</p> <p>ET_fights standard deviation of the numbers of fights over time</p> <p>mean_fights mean number of simultaneous fights during the contest</p> <p>n_deadtot_Lh total number of dead workers of L. humile</p> <p>t_50dead_Lh time when 50% of the L. humile mortality load have been diagnosed</p> <p>t_arena_opp time of the opponent entrance in the arena</p> <p>t_bait_opp time of opponent resources’ discovery</p> <p>t_maxarena_opp time when the max. number of opponent workers occurs in the arena</p> <p>mean_arena_opp mean number of opponent workers simultaneously present in the whole arena</p> <p>t_maxbait_opp time when the maximal number of opponent workers on the bait occurs</p> <p>mean_bait_opp mean number of opponent workers on the bait</p> <p>t_arena_Lh time of the entrance in the arena of L. humile</p> <p>t_maxarena_Lh time when the max. number of workers of L. humile occurs in the arena</p> <p>mean_arena_Lh mean number of L. humile workers simultaneously present in the whole arena</p> <p>n_totprey_Lh total number of preys brought by L. humile</p> <p>t_bait_Lh time of resources’ discovery by L. humile</p> <p>t_maxbait_Lh time when the maximal number of L. humile individuals on the bait occurs</p> <p>ETbait_Lh standard deviation of the numbers of L. humile workers on the bait over time</p> <p>mean_bait_Lh mean number of L. humile workers on the bait</p> <p>t_50prey_Lh time when 50% of the final prey load</p> <p> </p> <p>******************************** CONTACT *********************************<br> Please contact me at:</p> <p>Marion Cordonnier<br> e-mail: marion.cordonnier@hotmail.com</p> <p>*******************************************************************************</p> <p> </p>
tsammalex-data: Tsammalex 0.2 "domesticated animals"
<p>Christfried Naumann & Steven Moran & Guillaume Segerer & Robert Forkel (eds.) 2015. Tsammalex: A lexical database on plants and animals. Leipzig: Max Planck Institute for Evolutionary Anthropology. (Available online at http://tsammalex.clld.org)</p>
Supplementary material 1: Animation of BrainBox's workflow from: Open Neuroimaging Laboratory - Research Ideas and Outcomes 2: e9113 (08 May 2016) https://doi.org/10.3897/rio.2.e9113
Animation showing the different functionalities of BrainBox: opening a Magnetic Resonance Imaging volume, viewing it, and editing it collaboratively online.
Examination of head versus body heading may help clarify the extent to which animal movement pathways are structured by environmental cues?
<p>Understanding the processes that determine how animals allocate time to space is a major challenge, althoughit is acknowledged that summed animal movement pathways over time must define space-time use. The criticalquestion is then, what processes structure these pathways? Following the idea that turns within pathways mightbe based on environmentally determined decisions, we equipped Arabian oryx with head- and body-mounted tagsto determine how they orientated their heads – which we posit is indicative of them assessing the environment– in relation to their movement paths, to investigate the role of environment scanning in path tortuosity. Aftersimulating predators to verify that oryx look directly at objects of interest, we recorded that, during routinemovement, > 60% of all turns in the animals' paths, before being executed, were preceded by a change in headheading that was not immediately mirrored by the body heading: The path turn angle (as indicated by the bodyheading) correlated with a prior change in head heading (with head heading being mirrored by subsequent turnsin the path) twenty-one times more than when path turns occurred due to the animals adopting a body headingthat went in the opposite direction to the change in head heading. Although we could not determine what theobjects of interest were, and therefore the proposed reasons for turning, we suggest that this reflects the use ofcephalic senses to detect advantageous environmental features (e.g. food) or to detect detrimental features (e.g.predators). The results of our pilot study suggest how turns might emerge in animal pathways and we proposethat examination of points of inflection in highly resolved animal paths could represent decisions in landscapesand their examination could enhance our understanding of how animal pathways are structured.</p>
EFSA Opinion Update of risks for animal health related to the presence of ochratoxin A (OTA) in feed: Annexes on Occurrence data in feed submitted to EFSA
<p>Annexes to EFSA's Update Opinion on the risks for animal health related to the presence of OTA in feed. Annex B includes the occurrence data in feed extracted from EFSA Data Warehouse for the period from 2012 to 2021. Annex C contains the occurrence data expressed in dry matter following analysis and cleansing of the dataset as detailed in EFSA's Opinion. Annex D lists the samples of 'Compound feed' and other feed materials except forage expressed in whole weight. The number of samples across some of the feed categories differ among the two annex C and D because in few cases the moisture content was not reported (and no assumption on the moisture could be done), precluding the conversion of the analytical results to either whole weight or dry matter. </p>
Explaining and predicting animal migration under global change
<p class="MsoNormal"><span>Many migratory species are declining due to global environmental change. Yet, their complex annual cycles make unravelling the impacts of potential drivers such as climate and land-use change on migrations a major challenge. Identifying where, when, and how threatening processes impact species' migratory journeys and population dynamics is crucial for identifying effective conservation actions. Here, we describe how a new migration modelling framework – Spatially-explicit Adaptive Migration Models (SAMMs) – can simulate the optimal behavioural decisions required to migrate across open land- or seascapes varying in character over space and time, without requiring predefined behavioural rules. Models of adaptive behaviour have been used widely in theoretical ecology but have great untapped potential in real-world contexts. Applying adaptive behaviour models across open environments will allow users to explore flexibility in how migratory strategies respond to environmental change and the consequences of migrants not being able to adapt to change. We outline how SAMMs can be used to model migratory journeys through aerial, terrestrial, and aquatic environments, demonstrating their potential using a case study on the common cuckoo (<em><span>Cuculus canorus</span></em>) and comparing modelled to observed behaviours. SAMMs offer a tool to identify the key threats faced by migratory species and to predict how they will adapt future migratory journeys in response to changing environmental conditions.</span></p>
Presence and proportion of plants in biodiversity inventories conducted by undergraduate students enrolled in animal-related courses
<p>Dataset on biodiversity inventories conducted by 110 undergraduate students enrolled in animal-related courses using the iNaturalist platform.</p>
Figure 8. Living animals. A, B, Berghia verruciconnis from Huelva. C, Berghia columbina from Huelva. D, E, Spurilla neapolitana from Huelva. F in The family Aeolidiidae Gray, 1827 (Gastropoda Opisthobranchia) from Brazil, with a description of a new species belonging to the genus Berghia Trinchese, 1877
Figure 8. Living animals. A, B, Berghia verruciconnis from Huelva. C, Berghia columbina from Huelva. D, E, Spurilla neapolitana from Huelva. F, Spurilla neapolitana from El Grove.
Figure 1. Living animals. A, Anteaeolidiella indica from Praia dos Ossos. B in The family Aeolidiidae Gray, 1827 (Gastropoda Opisthobranchia) from Brazil, with a description of a new species belonging to the genus Berghia Trinchese, 1877
Figure 1. Living animals. A, Anteaeolidiella indica from Praia dos Ossos. B, Berghia benteva from Praia de Armação (10-mm-long specimen). C, D, Berghia benteva from Praia dos Ossos (18- and 19-mm-long specimens). E, Berghia creutzbergi from Praia de Armação (13-mm-long specimen). F, Berghia marcusi sp. nov., from Praia de Armação (dorsal view, 12-mm-long specimen). G, Berghia marcusi sp. nov. (ventral view of the same specimen). H–J, Spurilla neapolitana from Praia de Armação. K, Spurilla neapolitana from Praia dos Ossos.
Figure 34. Living animals. A in A phylogenetic analysis and systematic revision of the cryptobranch dorids (Mollusca, Nudibranchia, Anthobranchia)
Figure 34. Living animals. A, Paradoris indecora, Southern Spain, photo by D. Moreno. B, Otinodoris sp. (CASIZ 073238), photo by T. M. Gosliner. C, Sebadoris nubilosa, Seychelles, photo by T. M. Gosliner. D, Conualevia marcusi, La Paz Bay, Baja California Sur.
Figure 4. Living animals. A in A phylogenetic analysis and systematic revision of the cryptobranch dorids (Mollusca, Nudibranchia, Anthobranchia)
Figure 4. Living animals. A, Doris pseudoargus (CASIZ 121105). B, Doris immonda (CASIZ 089023), photo by T. M. Gosliner. C, Doris granulosa (CASIZ 073536), photo by T. M. Gosliner. D, Discodoris boholiensis (CASIZ 083654), photo by T. M. Gosliner. E, Discodoris ketos, San Pedrillo, Puntarenas, Costa Rica, photo by T. M. Gosliner. F, Thordisa rubescens (CASIZ 015860), photo by T. M. Gosliner. G, Aphelodoris antillensis (CASIZ 077289), photo by T. M. Gosliner. H, Peltodoris atromaculata (CASIZ 119474). I, Peltodoris nobilis, Monterey Bay, California, photo by A. Smith.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.