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238 results for “body condition”
Urban Heat and Desert Wildlife: Rodent Body Condition Across a Gradient of Surface Temperatures in the greater Phoenix, Arizona (USA) metropolitan area (2019-2020)
We live-trapped wild rodents from seven field sites spanning three strata of land-surface temperatures in the Phoenix, Arizona (USA) metropolitan area. We captured 116 adult pocket mice (Chaetodipus spp. and Perognathus spp.) and Merriam’s kangaroo rats (Dipodomys merriami) during 2019 and 2020 from mountainous urban parks and open spaces. Animal body condition was quantified as percent body fat (i.e., fat mass divided by body mass). We used a noninvasive quantitative magnetic resonance instrument to measure body condition.
Data from: Mating tactic influences body condition loss in Rocky Mountain bighorn rams (Ovis canadensis)
<p>In polygynous mating systems, males often employ alternative mating tactics to enhance reproductive success. In Rocky Mountain bighorn sheep, the primary tactics are coursing, involving mating chases, and tending, involving mate guarding. While both tactics are energetically costly and can diminish body condition, it remains unclear whether the associated costs significantly differ and to what extent. Our study investigated the impact of mating tactics, specifically the proportion of time allocated to each, on body condition loss during the rutting season in bighorn sheep. Using a non-invasive photographic method to estimate body condition loss, we found that the proportion of time a male spent tending significantly correlated with body condition loss. In contrast, the percentage of time spent coursing did not show a significant effect. Age was associated with the choice of tactic, with younger males predominantly coursing, older males primarily tending, and some intermediate-aged males employing both tactics concurrently. Despite the higher energetic costs, our results reveal the flexibility in tactic usage and indicate that tending, while demanding, is a high-cost, high-gain strategy, as tending rams are known to sire more offspring.</p>
Maternal body condition affects the response of the gut microbiome to a widespread contaminant in larval spined toads
<p>Datasets (metadata and phyloseq object) </p> <p>Scripts used for the statistical analyses</p>
F I G U R E 5 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 5 Log–log plot of the relative condition factor (Krel) vs. standard length (cm) calculated from length–weight relationships (LWRs) of the species (a) Argyropelecus affinis, (b) Argyropelecus sladeni, (c) Ceratoscopelus warmingii, (d) Diaphus dumerilii, (e) Electrona risso, (f) Lampanyctus nobilis, (g) Lepidophanes guentheri, (h) Notoscopelus resplendens and (i) Scopelogadus mizolepis (Table 3). Geographic regions are indicated by linetype, symbol and colour (EQ–C, dotted line, dark-blue square; EQ–N, two-dashed line, turquoise triangle; LO–E, solid line, red circle; LO–W, dashed line, violet diamond). If present, vertical dashed grey line indicates breakpoint in the LWR estimated by segmented regression analysis (cf. Table 2)
F I G U R E 1 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 1 Stations in the eastern low-oxygen (LO–E), western low-oxygen (LO–W), northern equatorial (EQ–N) and central equatorial (EQ–C) regions of the eastern tropical North Atlantic sampled in this study
F I G U R E 4 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 4 Distribution of form factor a3.0 for 55 mesopelagic species related to (a) body shape, (b) taxonomic family and (c) species. Form factor calculated from Equation 2 using across-species slope of S = 1.358 based on 1223 fish species presented in equation 17 in Froese (2006)
F I G U R E 3 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 3 Scatter plot of mean log a (SL) over mean b for 55 mesopelagic species with information on body shape. Body shape:, elongated;, fusiform;, short-deep
F I G U R E 2 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 2 Frequency distribution of (a) mean log a (binwidth 0.2) and (b) mean exponent b (binwidth 0.1) based on 55 records (measured in centimetres and grams) of mesopelagic species of the eastern tropical North Atlantic during cruise WH383
Annotation table - Whole body transcriptomes of the tick Ixodes ricinus at different stage and feeding conditions
<p>Annotation table for a <em>de novo</em> assembled transcriptome of<em> Ixodes ricinus</em> in different stages and conditions.</p> <p>Description of the fields of each column (Trinotate results, and additionnal statistics):</p> <p>1. Contig_name: name of the contig (Trinity assembly)</p> <p>2. sprot_Top_BLASTX_hit: first hit of the blastx search against SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>3. TrEMBL_Top_BLASTX_hit: first hit of the blastx search against Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>4. RNAMMER: identification of non-coding RNAs</p> <p>5. prot_id: identifier of the predicted protein (TransDecoder)</p> <p>6. prot_coords: coordinates (start, end and strand) of the predicted protein on the contig</p> <p>7. sprot_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>8. TrEMBL_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>9. Pfam: result of the search against PfamA database</p> <p>10. SignalP: prediction of a signal peptide with SignalP</p> <p>11. TmHMM: prediction of a transmembrane domain with THMM</p> <p>12. eggnog: eggNOG database of orthologous genes (v3.0) assignation</p> <p>13. gene_ontology_blast: GO assignation based on blast results</p> <p>14. gene_ontology_pfam: GO assignation based on pfam results</p> <p>15. Contig_length: length of the contig in bp</p> <p>16. Busco_Id: name of the BUSCO (v1)</p> <p>17. Busco_status: status of the BUSCO (complete/fragmented/duplicated)</p> <p>18-32: Kallisto read counts for the 15 libraries</p> <p>A, B, C: unfed nymphs (replicates 1, 2, 3)</p> <p>D, E, F: partially fed nymphs (replicates 1, 2, 3)</p> <p>G, H, I: males (unfed) (replicates 1, 2, 3)</p> <p>J, K, L: unfed adult females (replicates 1, 2, 3)</p> <p>M, N, O: partially fed adult females (replicates 1, 2, 3)</p> <p>33. log2FoldChange_UnfedVsPartiallyFed: log fold change in base 2 of expression (comparison between "unfed" -including males- and "fed" ticks)</p> <p>34. pvalue_UnfedVsPartiallyFed: p-value of the comparison between "unfed" -including males- and "fed" ticks</p> <p>35. log2FoldChange_MaleVsFemale: log fold change in base 2 of expression (comparison between "males" and "females")</p> <p>36. pvalue_MaleVsFemale: p-value of the comparison between "males" and "females"</p> <p>37. log2FoldChange_NymphsVsAdults: log fold change in base 2 of expression (comparison between "nymphs" and "adults" -males and females-)</p> <p>38. pvalue_NymphsVsAdults: p-value of the comparison between "nymphs" and "adults" -males and females-)</p> <p> </p> <p> </p>
Goat-CNN: A Lightweight Convolutional Neural Network for Pose-Independent Body Condition Score Estimation in Goats
<p>Here we introduce the dataset utilized in our published paper entitled "<a href="https://www.sciencedirect.com/science/article/pii/S2666154324002114">Goat-CNN: A Lightweight Convolutional Neural Network for Pose-Independent Body Condition Score Estimation in Goats</a>".</p> <p>Contained within the "bcs" folder are all the videos collected for this study. Each video file is named with a format denoting its respective details. The first number signifies the sequence of collection, the second denotes the ear tag, and the final figure represents the body condition score (BCS) value.</p> <p>For example: "1_158734_2.50" indicates the first sampling of an animal with the ear tag "158734" and a BCS value of "2.50".</p> <p>Additionally, we provide two Python scripts in this repository. The first script, "Video2Frame.py", facilitates the splitting of videos into individual frames. The second script, "Frames2npy.py", converts these frames into two numpy-friendly files with the extension ".npy". These files contain both the images ("X_train_bcs300.npy") and their corresponding labels ("Y_train_bcs300.npy").</p> <p>Furthermore, for the convenience of swift experimentation, we have included the desired .npy files within the repository.</p> <p>To load these files into your Python environment, you can use the following code snippet:</p> <div> <div>th4figs = '/content/drive/MyDrive/compag_2023/'</div> <br> <div>path4images = "/content/drive/MyDrive/CodeRefarm/datasets/BCS/X_train_bcs300.npy"</div> <div>Xtrain = np.load(path4images)</div> <br> <div>path4labels = "/content/drive/MyDrive/CodeRefarm/datasets/BCS/Y_train_bcs300.npy"</div> <div>Ytrain = np.load(path4labels).astype(float)</div> <br> <div>print("X train : ", Xtrain.shape)</div> <div>print("Y train : ", Ytrain.shape)</div> <div> <div> <div> <div> <div> <div> <div> </div> </div> <div> </div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <div> <div> <div> <pre>X train : (5332, 300, 300, 3) Y train : (5332,)<br> </pre> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>
Figure 1 in Sexual differences on body condition in litter-dwelling scorpion Tityus pusillus Pocock, 1893 (Scorpiones: Buthidae)
Figure 1. Corporal condition parameters in Tityus pusillus Pocock, 1893 females and males. A) Body size. B) Fresh mass. C) Dry mass. D) Muscular mass. E) Lipid mass. F) Body condition. / Figura 1. Parámetros de la condición corporal en Tityus pusillus Pocock, 1893 hembras y machos. A) Tamaño del cuerpo. B) Masa fresca. C) Masa seca. D) Masa muscular. E) Masa lipídica. F) Condición corporal.
Data for "Re-weighing the 5% tagging recommendation: assessing the potential impacts of tags on the behavior and body condition of bats"
<p>Database as tab-delimited (.csv) associated with the publication: </p> <p>Meierhofer M.B., et al. (2024) Re-weighing the 5% tagging recommendation: assessing the potential impacts of tags on the behavior and body condition of bats. <em>Mammal Review.</em></p> <p>Please refer to the main publication for a detailed description. An explanation of the database is available in the Metadata file uploaded alongside the database. R code to reproduce the analysis pipeline is available on GitHub:</p> <p>https://github.com/melissameierhofer/Meta-5-Rule.git</p>
Data from: Wildfire smoke impacts the body condition and capture rates of birds in California
<p>Despite the increased frequency with which wildfire smoke now blankets portions of world, the effects of smoke on wildlife, and birds in particular, are largely unknown. We used two decades of banding data from the San Francisco Bay Bird Observatory to investigate how fine particulate matter (PM<sub>2.5</sub>) – a major component and indicator of wildfire smoke – influenced capture rates and body condition of 21 passerine or near-passerine bird species. Across all study species, we found a negative effect of acute PM<sub>2.5</sub> exposure and a positive effect of chronic PM<sub>2.5</sub> exposure on avian capture rates. Together, these findings are indicative of decreased bird activity or local site removal during acute periods of wildfire smoke, but increased activity or site colonization under chronic smoke conditions. Importantly, we also observed a negative relationship between chronic PM<sub>2.5</sub> exposure and body mass change in individuals with multiple captures per season. Our results indicate that wildfire smoke likely influences the health and behavior of birds, ultimately contributing to a shift in activity and body condition, with differential short-term versus long-term impacts. Although more research is needed on the mechanisms driving these observed changes in bird health and behavior, as well as validation of these relationships in more areas, our results suggest that wildfire smoke is a potentially frequent large-scale environmental stressor to birds that deserves increasing attention and recognition.</p>
Fig. 4 in Endoparasites in a Norwegian moose (Alces alces) population - Faunal diversity, abundance and body condition
Fig. 4. Counts of abomasal nematodes in moose, hunted during the licensed hunting season, autumn 2013, in Hedmark county, Norway, in relation to slaughter weight, gender (F – females [black]; M – males [grey]) and body condition index (poor – BCI <0 [open circles]; good – BCI> 0 [filled circles]). The lines show model predictions from a quasi-Poisson generalised linear model explaining 72.4% of the deviance. The lines show the model predictions for individuals with BCI equal to 1st and 3rd quartiles.
Fig. 3. A in Endoparasites in a Norwegian moose (Alces alces) population - Faunal diversity, abundance and body condition
Fig. 3. A box–whisker plot showing the prevalence of infection with protostrongylid larvae (dorsal spine larvae) in moose hunted during the licensed hunting season, autumn 2013, in Hedmark county, Norway, in relation to age. The median (solid black line), quartiles (ends of boxes) with the whiskers indicating the variability outside the quartiles, and extreme outliers, individual points, are shown.
Fig. 1 in Endoparasites in a Norwegian moose (Alces alces) population - Faunal diversity, abundance and body condition
Fig. 1. Histogram of number of parasite groups (parasite diversity) found in individual moose (n = 30) shot during the licensed hunting season, autumn 2013, in Hedmark county, Norway.
Fig. 2 in Microclimate and host body condition influence mite population growth in a wild bird-ectoparasite system
Fig. 2. Distribution of nest mite population sizes estimated when nests were placed in a Berlese funnel after nestlings had fledged. All nests began the experiment with the same population size (100 live mites), mimicking identical transmission, but ending population sizes 30–35 days later were highly variable. This suggests that factors of the nest environment or hosts may be playing an important role in mite population growth.
Fig. 4 in Microclimate and host body condition influence mite population growth in a wild bird-ectoparasite system
Fig. 4. The relationship between the substrate the nest was built on: concrete, metal, or wood (y-axis) and the number of mites estimated in the field when chicks were 12 days old. Nests built on wooden substrates had significantly more mites compared to nests built on concrete or metal substrates. This graph was made using raw data, but models reported in the text included site as a random effect.
Fig. 3 in Microclimate and host body condition influence mite population growth in a wild bird-ectoparasite system
Fig. 3. Relationship between the number of non-mite arthropods (x-axis) and nest mites (y-axis) that were recovered when experimental nests were removed from the field after nestlings fledged and placed in a Berlese funnel. Nests with more arthropods had significantly fewer nest mites. This graph was made using raw data, but models reported in text had a Poisson distribution and included site as a random effect.
Figures 3-4 in Blood metabolites as predictors to evaluate the body condition of Neopelma pallescens (Passeriformes: Pipridae) in northeastern Brazil
Figures 3-4. Spearman's correlation between Body Condition Index (BCI) and glucose concentration for breeding (3) (N = 28) and non-breeding (4) (N = 46) individuals of N. pallescens in Reserva Biológica de Guaribas, PB. The breeding period of N. pallescens started at the end of July (P1) and climaxed in January (P3). It occurred throughout Figure 2. Monthly samples sizes of captured individuals of N. palles- the rainy and dry seasons. Glucose concentrations showed cens in Reserva Biológica de Guaribas, PB. Recaptured individuals significant variation during the developmental phases of brood are not included. patches with a higher concentration in P3 (Fig. 5) (ANOVA, F = 5.39, p = 0.01). Tukey's test showed significant values only The glucose concentration was negatively correlated with between P1 and P3 (Tukey's Test, P2-P1: p = 0.76, P3-P1 = 0.01, body condition (Table 1). Further analyses showed that the glu- P3-P2: p = 0.05).
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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.