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334 results for “temporal variation”
Fig. 3 in Temporal variation in the behavior of Apis mellifera (Hymenoptera: Apidae) and Lycastrirhyncha nitens (Diptera: Syrphidae) on Pontederia sagittata (Commelinales: Pontederiaceae) inflorescences in relation to nectar availability
Fig. 3. Mean (± 95 % CI) number and duration of the foraging events recorded by Apis mellifera (A, B) and Lycastrirhyncha nitens (C, D) on inflorescences of L (black circle), M (gray circle) and S (white circle) morphs of Pontederia sagittata during daily periods of video-recording.
Fig. 2 in Temporal variation in the behavior of Apis mellifera (Hymenoptera: Apidae) and Lycastrirhyncha nitens (Diptera: Syrphidae) on Pontederia sagittata (Commelinales: Pontederiaceae) inflorescences in relation to nectar availability
Fig. 2. Total activity time (± 95 % CI) of Apis mellifera and Lycastrirhyncha nites on inflorescences of L (black circle), M (gray circle) and S (white circle) morphs of Pontederia sagittata during daily periods of video-recording.
Fig. 1 in Temporal variation in the behavior of Apis mellifera (Hymenoptera: Apidae) and Lycastrirhyncha nitens (Diptera: Syrphidae) on Pontederia sagittata (Commelinales: Pontederiaceae) inflorescences in relation to nectar availability
Fig. 1. Position of styles and stamens and differences in pollen size in the three floral morphs of Pontederia sp. a) long-styled [L], b) mid-styled [M] and c) shortstyled [S] (Zomlefer 1994). Legitimate pollinations are indicated by arrows.
Raw data for: Spatial and temporal variation in farmland bird nesting ecology: Implications for effective Corn Bunting Emberiza calandra conservation
<p>These are raw data accompanying the study "<span>Spatial and temporal variation in farmland bird nesting ecology: Implications for effective Corn Bunting Emberiza calandra conservation</span>". All information on data origin, data analysis, and derived implications will be available with the original publiation.</p>
Fig. 3 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 3. Predicted relationships between NAO winter index and the probability of seropositivity for Toxoplasma gondii in all cats sampled; (a) juveniles and (b) adults. Points represent the observed seoprevalence values with 95% confidence intervals as whiskers. A median farm density (0.68 farm/km2) was used to calculate the predictions (full line). Minimal farm density (0 farm/km2) observed among sampled communes was used to calculate the minimal predictions of the model (dotted lines). High values of farm density (2 and 4 farms/km2) were used to calculate the maximal predictions of the model (dashed and dotted-dashed lines).
Fig. 2 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 2. Interannual variations in Toxoplasma gondii seroprevalence in the three types of cats standardised by age (bars) during the study period. Line segments represent the 95% confidence intervals for seroprevalence, and the numbers in brackets indicate the sample sizes. Wildcats (Felis s. silvestris), domestic cats (Felis s. catus) and hybrids are pooled.
Fig. 1 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 1. European wildcat (Felis s. silvestris) distribution in France (grey area; Léger et al., 2008; Say et al., 2012), and locations of samples from domestic cats (Felis s. catus), wildcats and their hybrids. Cat types are represented by different symbols (see the bottom left of the map). One location might correspond to several individuals (1, 2, 3, or 8), the size of the dot being proportional to the number (indicated at the right of the symbols) of individuals collected in each commune.
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. Models of Cyathocotyle bushiensis (Cb) and Sphaeridiotrema spp. (Sg) metacercarial prevalence (prev) and intensity (int) in the waterbodies we studied in northern Minnesota during 2011‾2013; a) East Winnibigoshish index area, b) West Winnibigoshish index area, c) Lower Twin Lake, d) Crow Wing River, e) White Earth ponds, f) Shell River. Depth_cm is water depth at the sampling location. Dist.scaup is the minimum Euclidean distance between a given waypoint and the nearest point sampled under a raft of scaup in either the same season, or up to two seasons prior in that same year. Log.abund is the log transformed snail abundance at a sampling point. Size.mean is the mean snail size at a sampling point. Year2012 and Year2013 are comparisons between samples collected in 2011 vs 2012 and 2011 vs 2013, respectively.
Fig. 3 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 3. Average intensity of (a) Cyathocotyle bushiensis (Cb) and (b) Sphaeridiotrema spp. (Sg) metacercariae in each of the waterbodies studied in northcentral Minnesota during nine seasons in 2011‾2013 with 95% confidence intervals. Note that waterbody specific y-axis scales are used to highlight differences within a waterbody.
Fig. 2 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 2. Average prevalence of (a) Cyathocotyle bushiensis (Cb) and (b) Sphaeridiotrema spp. (Sg) metacercariae in each of the waterbodies studied in northcentral Minnesota during nine seasons in 2011‾2013 with 95% confidence intervals.
Fig. 1 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 1. Map of study area in northcentral Minnesota depicting the study lakes with county boundaries, within the state and USA.
Figure 4 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 4 Habitus of collected species of Megalomus Rambur, 1842 (Neuroptera, Hemerobiidae) and their geographical distribution in Neotropics; red circles = previous records, red stars = new records. A-B, M. impudicus (Gerstaecker, 1888). C-D, M. rafaeli Penny & Monserrat, 1985. E-F, M. ricoi Monserrat, 1997.
Figure 10 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 10 Species distributions of Hemerobiidae (Neuroptera) along altitudinal gradient in five areas in the Atlantic rainforest of São Paulo state, Brazil, collected between October 2009 and December 2011. asl = above sea level, PEI = Parque Estadual Intervales, PEMD = Parque Estadual Morro do Diabo, PESM/NSV = Parque Estadual da Serra do Mar, Núcleo Santa Virgínia, PESM/NP = Parque Estadual da Serra do Mar, Núcleo Picinguaba and EEJI = Estação Ecológica Juréia-Itatins.
Figure 1 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 1 Map of Brazil with the original extension of the Atlantic rainforest biome in black color and map of the São Paulo state with the collection sites. PEI = Parque Estadual Intervales, PEMD = Parque Estadual Morro do Diabo, PESM/NSV = Parque Estadual da Serra do Mar, Núcleo Santa Virgínia, PESM/NP = Parque Estadual da Serra do Mar, Núcleo Picinguaba and EEJI = Estação Ecológica Juréia-Itatins. Image sources: www.wwf.org.br and Google Earth.
Figure 2 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 2 Habitus of collected species of Hemerobius Linnaeus, 1758 (Neuroptera, Hemerobiidae) and their geographical distribution in Neotropics; red circles = previous records, red stars = new records. A-B, H. cubanus Banks, 1930. C-D, H. edui Monserrat, 1991. E-F, H. gaitoi Monserrat, 1996.
Figure 6 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 6 Habitus of collected species of Sympherobius Banks, 1904 (Neuroptera, Hemerobiidae) and their geographical distribution in Neotropics; red circles = previous records, red stars = new records. A-B, S. ariasi Penny & Monserrat, 1985. C-D, S. mirandus (Navás, 1920).
Figure 8 in Diversity and temporal variation of brown lacewings (Neuroptera, Hemerobiidae) from Atlantic rainforest areas in southeastern Brazil
Figure 8 Genera of Hemerobiidae (Neuroptera) collected monthly with Malaise traps in five areas of Atlantic rainforest of São Paulo State, Brazil, between October 2009 and December 2011. A, Nusalala Navás, 1913. B, Hemerobius Linnaeus, 1758. C, Megalomus Rambur, 1842. D, Notiobiella Banks, 1909. E, Sympherobius Banks, 1904.
Figure 5 in Diversity and spatio-temporal variation of Anopheles (Diptera: Culicidae) before and after the construction of the Jirau hydroelectric plant, state of Rondônia, Brazil
Figure 5 Canonical correlation analysis (CCA) ordering diagram between environmental factors and Anopheles species in the pre (a) and post-construction (b) phases of the Jirau hydroelectric plant: Relative Humidity of the air (R. H%); Temp (Temperature ° C); Subtitle: Anopheles albit – An. albitarsis; Anopheles argyrit – An. argyritarsis; Anopheles benar – An. benarrochi; Anopheles braz – An. braziliensis; Anopheles darl – An. darlingi; Anopheles evan – An.evansae; Anopheles mattog – An. mattogrossensis; Anopheles mediop – An. mediopunctatus; Anopheles osw – An. oswaldoi; Anopheles per – An. peryassui; Anopheles rang – An. rangeli; Anopheles trian – An. triannulatus.
Figure 3 in Diversity and spatio-temporal variation of Anopheles (Diptera: Culicidae) before and after the construction of the Jirau hydroelectric plant, state of Rondônia, Brazil
Figure 3 Density of Anopheles species (x) in the sampled months (January to August) before (a) and after (March to October) the construction (b) of the Jirau hydroelectric w plant, in Rondônia, Brazil.
Figure 1 in Diversity and spatio-temporal variation of Anopheles (Diptera: Culicidae) before and after the construction of the Jirau hydroelectric plant, state of Rondônia, Brazil
Figure 1 Sampling points of anophelines in the area covered by the Jirau hydroelectric plant, in the stretch between the locations of Jaci Paraná and Abunã (squares), in the pre (black) and post-construction (gray) phases.
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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.