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4,243 results for “seasonality”
Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources
<p>This directory contain the climate indices from CESM ensemble hindcasts during period 1900-2014 that are used for a manuscript ("Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources") submitted for Geophysical Research Letters.</p> <p>Description: </p> <p>The PNA index is defined by using the pointwise method , i.e., a linear combination of the normalized 500 hPa geopotential height anomalies (Z) at the four active centers: PNA = 1/4[Z(20°N, 160°W) – Z (45°N, 165°W) + Z (55°N, 115°W) – Z (30°N, 85°W)].The predicted seasonal mean PNA index is calculated based on the CESM monthly mean 500 hPa geopotential height prediction in December, January and February (DJF), i.e., with a 2-month lead time. The ensemble mean PNA index is the mean of 20 ensemble seasonal mean PNA indices. </p> <p>The predicted seasonal mean Niño 3.4 index is calculated as the area average of SSTA in the domain of 170°W-120°W, 5°S-5°N based on the CESM monthly mean SST in December, January and February (DJF), i.e., with a 2-month lead time. The linear signal of global warming is filtered out from the SSTA. The ensemble mean Niño index is the mean of 20 ensemble seasonal mean Niño 3.4 indices. </p> <p>The predicted seasonal mean PDO index is calculated as the time series associated with the first leading empirical orthogonal function (EOF) pattern of the winter mean (DJF) North Pacific SSTA (north of 20°N) based on the CESM monthly mean SST in December, January and February (DJF), i.e., with a 2-month lead time. The linear signal of global warming is filtered out from the SSTA. The ensemble mean PDO index is the mean of 20 ensemble seasonal mean PDO indices.<br> </p>
Water vapor vertical distribution on Mars during perihelion season of MY 34 and MY 35 with ExoMars-TGO/NOMAD observations [Dataset]
<p>1. Description of methods used for collection/generation of data:<br> NOMAD SO channel acquires transmittance spectra at different diffraction orders sounding the limb of the Martian atmosphere in solar occultation. It uses an echelle grating with a density of ∼4 lines/mm in a litrow configuration. An Acousto-Optical Tunable Filter (AOTF) is used to select different spectral windows (with a width that varies from 20 to 35 cm−1). Each window corresponds to the desired diffraction order to be used during the atmospheric scan. The spectral resolution of the SO channel is λ/∆λ=20,000.<br> After spectral calibration, the inversion problem is solved by fitting the data with a forward model and the vertical profiles are obtained.</p> <p>2. Methods for processing the data:<br> For the H2O inversion we use the Retrieval Control Program (RCP) developed at Institut für Meteoriologie und Klimaforschung (IMK), which incorporates the Karlsruhe Optimized and Precise Radiative transfer Algorithm (KOPRA) forward model. After providing an a priori, a first-guess and the measured spectra, RCP solves the inversion problem iteratively until the convergence of the solution. The IMK-IAA level-2 processor relies on multi-parameter non-linear least squares fitting of measured and modeled spectra (von Clarmann et al., 2003). Further information about RCP and the inversion problem can be found in (Jurado Navarro et al., 2016).<br> Retrievals of NOMAD diffraction orders 134 (3011-3035 cm−1) and 168 (3775-3805 cm−1) have been obtained and merged when collocated.</p>
Variations of the urban PM2.5 chemical components and corresponding light extinction for three heating seasons in the Guanzhong Plain, China
<p>The basic data of the thesis “Variations of the urban PM2.5 chemical components and corresponding light extinction for three heating seasons in the Guanzhong Plain, China”.</p>
Population density does not affect seasonal regulation of reproductive physiology in male water voles
<p>Most small rodent species display cyclic fluctuations in their population density. The mechanisms behind these cyclical variations are not yet clearly understood. Density-dependent effects on reproductive function could affect these population variations. The fossorial water vole ecotype, Arvicola terrestris, undergoes a multi-year cycle dynamic with outbreak peaks. Here, we monitored different water vole populations over three years, in spring and autumn, to evaluate whether population density be related to male reproductive physiology. Our results show an effect of season and inter-annual factors in testes mass, plasmatic testosterone level, and androgen-dependent seminal vesicles mass. By contrast, population density does not affect any of these parameters, thus suggesting a lack of modulation of population dynamics of population density.</p>
Unravelling the role of thyroid hormones in seasonal neuroplasticity in European Starlings (Sturnus vulgaris)
<p class="MsoNormal">Thyroid hormones clearly play a role in the seasonal regulation of reproduction, but any role they might play in song behavior and the associated seasonal neuroplasticity in songbirds remains to be elucidated. To pursue this question, we first established seasonal patterns in the expression of thyroid hormone regulating genes in male European starlings employing in situ hybridization methods. Thyroid hormone transporter LAT1 expression in the song nucleus HVC was elevated during the photosensitive phase, pointing towards an active role of thyroid hormones during this window of possible neuroplasticity. In contrast, DIO3 expression was high in HVC during the photostimulated phase, limiting the possible effect of thyroid hormones to maintain song stability during the breeding season. Next, we studied the effect of hypothyroidism on song behavior and neuroplasticity using i<em>n vivo </em>MRI. Both under natural conditions as with methimazole treatment, circulating thyroid hormone levels decreased during the photosensitive period, which coincided with the onset of neuroplasticity. This inverse relationship between thyroid hormones and neuroplasticity was further demonstrated by the negative correlation between plasma T3 and the microstructural changes in several song control nuclei and cerebellum. Furthermore, maintaining hypothyroidism during the photostimulated period inhibited the increase in testosterone, confirming the role of thyroid hormones in activating the hypothalamic–pituitary–gonadal (HPG) axis. The lack of high testosterone levels influenced the song behavior of hypothyroid starlings, while the lack of high plasma T4 during photostimulation affected the myelination of several tracts. Potentially, a global reduction of circulating thyroid hormones during the photosensitive period is necessary to lift the brake on neuroplasticity imposed by the photorefractory period, whereas local fine-tuning of thyroid hormone concentrations through LAT1 could activate underlying neuroplasticity mechanisms. Whereas an increase in circulating T4 during the photostimulated period potentially influences the myelination of several white matter tracts, which stabilizes the neuroplastic changes. Given the complexity of thyroid hormone effects, this study is a steppingstone to disentangle the influence of thyroid hormones on seasonal neuroplasticity.</p>
Focal vs. faecal: Seasonal variation in the diet of wild vervet monkeys from observational and DNA metabarcoding data
<p>1. Assessing the diet of wild animals reveals valuable information about their ecology and trophic relationships that may help elucidate dynamic interactions in ecosystems and forecast responses to environmental changes.</p> <p>2. Advances in molecular biology provide valuable research tools in this field. However, comparative empirical research is still required to highlight strengths and potential biases of different approaches. Therefore, this study compares environmental DNA and observational methods for the same study population and sampling duration.</p> <p>3. We employed DNA metabarcoding assays targeting plant and arthropod diet items in 823 faecal samples collected over 12 months in a wild population of an omnivorous primate, the vervet monkey (<em>Chlorocebus pygerythrus</em>). DNA metabarcoding data were subsequently compared to direct observations.</p> <p>4. We observed the same seasonal patterns of plant consumption with both methods, however, DNA metabarcoding showed considerably greater taxonomic coverage and resolution compared to observations, mostly due to the construction of a local plant DNA database. We found a strong effect of season on variation in plant consumption largely shaped by the dry and wet seasons. The seasonal effect on arthropod consumption was weaker but feeding on arthropods was more frequent in spring and summer, showing overall that vervets adapt their diet according to available resources. The DNA metabarcoding assay outperformed also direct observations of arthropod consumption in both taxonomic coverage and resolution.</p> <p>5. Combining traditional techniques and DNA metabarcoding data can therefore not only provide enhanced assessments of complex diets or reveal trophic interactions to the benefit of wildlife conservationists and managers but also opens new perspectives for behavioural ecologists studying whether diet variation in social species is induced by environmental differences or might reflect selective foraging behaviours.</p>
A seasonal analysis of aerosol NO3- sources and NOx oxidation pathways in the Southern Ocean marine boundary layer
<p>This dataset includes coarse mode atmopsheric nitrate concentration and isotopic composition from the Southern Ocean marine boundary layer in summer (2018/19), winter (2019) and spring (2019). Environmental data (temperature, SLP and relative humidity) are also included.</p>
Data from: Effects of manipulated food availability and seasonality on innate immune function in a passerine
<p>1. The innate immune system is essential for survival, yet many immune traits are highly variable between and within individuals. In recent years, attention has shifted to the role of environmental factors in modulating this variation. A key environmental factor is food availability, which plays a major role in shaping life-histories, and may affect resource allocation to immune function through its effect on nutritional state.</p> <p>2. We developed a technique to permanently increase foraging costs in seed-eating birds, and leveraged this technique to study the effects of food availability on the innate immune system over a three-year period in 230 zebra finches housed in outdoor aviaries. The immune components we studied were haptoglobin, ovotransferrin, nitric oxide, natural antibodies through agglutination, complement-mediated lysis, and killing capacity of <em>Escherichia</em> <em>coli</em> and <em>Candida</em> <em>albicans</em>, covering a broad spectrum of the innate immune system. We explored effects of food availability in conjunction with other potentially important variables: season, age, sex, and manipulated natal brood size.</p> <p>3. Increased foraging costs affected multiple components of the immune system, albeit in a variable way. Nitric oxide and agglutination levels were lower under harsh foraging conditions, while Escherichia coli killing capacity was increased. Agglutination levels also varied seasonally, but only at low foraging costs. <em>C</em>. <em>albicans</em>' killing capacity was lower in winter, and even more so for animals in harsh foraging conditions that were raised in large broods. Effects of food availability on ovotransferrin were also seasonal, and only apparent in males. Haptoglobin levels were independent of foraging costs and season.</p> <p>4. Males had higher levels of immune function than females for 3 of the measured immune traits. Innate immune function was independent of age and manipulated natal brood size.</p> <p>5. Our finding that food availability affects innate immune function suggests that fitness effects of food availability may at least partially be mediated by effects on the immune system. However, food availability effects on innate immunity varied in direction between traits, illustrating the complexity of the immune system and precluding conclusions on the level of disease resistance.</p>
Fig. 3 in Yearly and seasonal changes in species composition of hornets (Hymenoptera: Vespidae) caught with bait traps on the Sea of Japan coast
Fig. 3. Seasonal abundance of Vespa ducalis collected by bait traps at Sakata Park and
Fig. 2 in Yearly and seasonal changes in species composition of hornets (Hymenoptera: Vespidae) caught with bait traps on the Sea of Japan coast
Fig. 2. Seasonal abundance of Vespa analis collected by bait traps at Sakata Park and
Fig. 4 in Yearly and seasonal changes in species composition of hornets (Hymenoptera: Vespidae) caught with bait traps on the Sea of Japan coast
Fig. 4. Nonmetric multidimensional scaling (NMDS) plot comparing hornet species
Figure 6 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 6. Cluster analysis of medium and large mammal communities' similarity between 19 Atlantic Forest remnants in São Paulo, southeastern Brazil (including a single remnant in Paraná, Brazil). AGPE = Água do Peão; AGUA = Aguapeí State Park; AMBO = Amadeu Botelho Private Nature Reserve; CBSP = Carlos Botelho State Park; COSM = Matão de Cosmópolis; ESAL = Estrela da Alcídia Água Sumida; ISP = Intervales State Park; LUNO = Lua Nova; MATU = Maturi; MDSP = Morro do Diabo State Park; MGFR = Morro Grande Forest Reserve; PBES = Ponte Branca (Black Lion Tamarin Ecological Station); SBNP = Serra da Bocaina National Park; SEIR = Seis R; SMES = Santa Maria Água Sumida (Black Lion Tamarin Ecological Station); SMA = Santa Maria Forest; STMO = Santa Mônica; TUES = Tucano (Black Lion Tamarin Ecological Station).
Figure 5 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 5. Carnivora, Artiodactlya, and Perissodactyla recorded in Santa Maria fragment. (A) Puma concolor; (B) Leopardus pardalis; (C) Panthera onca; (D) Cerdocyon thous; (E) Chrysocyon brachyurus; (F) Mazama rufa; (G) Dicotyles tajacu; (H) Tapirus terrestris.
Figure 7 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 7. Scatterplot of non-volant mammal species richness according to fragment area in 14 Atlantic Forest fragments of Pontal do Paranapanema, São Paulo, Southeastern Brazil. The study site, Santa Maria is represented by a blue triangle. AGPE = Água do Peão; ARIZ = Fazenda Arizona; ASES = Água Sumida (Black Lion Tamarin Ecological Station); ESAL = Estrela da Alcídia; LUNO = Lua Nova; MATU = Maturi; MDSP = Morro do Diabo State Park; NOPO = Nova Pontal; PBES = Ponte Branca (Black Lion Tamarin Ecological Station); SASE = São Sebastião; SEIR = Seis R; STMO = Santa Mônica; TUES = Tucano (Black Lion Tamarin Ecological Station).
Figure 1 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 1. Santa Maria forest fragment and its location in Pontal do Paranapanema, São Paulo, southeastern Brazil. Note the small creek (Ribeirão Água Sumida) that passes on its southern edges and the SPV-035 road along its northeastern edge. Green are native forest remnants and blue are the rivers and creeks.
Figure 4 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 4. Didelphidae, Xenarthra, Primates and Rodentia recorded in Santa Maria fragment. (A) Marmosa paraguayana; (B) Didelphis albiventris; (C) Gracilinanus microtarsus; (D) Euphractus sexcinctus; (E) Dasypus novemcinctus (preyed); (F) Tamandua tetradactyla; (G) Sapajus nigritus; (H) Leontopithecus chrysopygus; (I) Dasyprocta azarae; J) Oecomys cleberi.
Figure 3 in High richness of non-volant mammals in a seasonal forest fragment in southeastern Brazil
Figure 3. Locations of the 18 medium and large mammal inventories (green dots) that were compared to the mammal community of Santa Maria forest fragment (red square). Atlantic Forest remnants (sensu Ribeiro et al., 2009), are in light gray. AGPE = Água do Peão (Ditt et al., 1999); AGUA = Aguapeí State Park (Faria & Pires, 2010); AMBO = Amadeu Botelho Private Nature Reserve (Reale et al., 2014); CBSP = Carlos Botelho State Park (Brocardo et al., 2012); COSM = Matão de Cosmópolis (Magioli et al., 2014); ESAL = Estrela da Alcídia Água Sumida (Ditt et al., 1999); ISP = Intervales State Park (de Vivo & Gregorin, 2001); LUNO = Lua Nova (Ditt et al., 1999); MATU = Maturi (Ditt et al., 1999); MDSP = Morro do Diabo State Park (Faria & Pires, 2006); MGFR = Morro Grande Forest Reserve (Negrão & Valladares-Pádua, 2006); PBES = Ponte Branca (Black Lion Tamarin Ecological Station) (Valladares-Pádua, 2007); SBNP = Serra da Bocaina National Park (Delciellos et al., 2012); SEIR = Seis R (Ditt et al., 1999); SMES = Santa Maria Água Sumida (Black Lion Tamarin Ecological Station) (Valladares-Pádua, 2007); SMA = Santa Maria Forest (this study); STMO = Santa Mônica (Ditt et al., 1999); TUES = Tucano (Black Lion Tamarin Ecological Station) (Valladares-Pádua, 2007).
Figure 3 in Seasonality effect on ant (Hymenoptera: Formicidae) activity in an ecotonal environment in the state of Piauí, Brazil
Figure 3. Non-metric multidimensional scaling – NMDS of ant composition according to seasonality in an ecotonal area between the Caatinga and Cerrado biomes at Floriano, Piauí, Brazil.
Figure 2 in Seasonality effect on ant (Hymenoptera: Formicidae) activity in an ecotonal environment in the state of Piauí, Brazil
Figure 2. Number of ant species (average values) collected according to the seasons studied in a transition area between the Caatinga and Cerrado biomes in Floriano, Piauí, Brazil. The lines link the number of species caught in each collection point.
Seasonality modulates habitat cover effects on avian cross-boundary responses and spillover
Species cross-boundary response is a key mechanism affecting species spillover into agricultural fields. However, temporal changes in edge permeability, which may depend on the seasonal availability of resources in both matrix and native habitats, remain poorly understood. Here we tested how edge crossing behavior and the associated spillover of birds into sun coffee plantations respond to landscape structure and seasonality. We monitored the movement of six insectivorous understory bird species (four forest-specialists and two forest-generalists) using an automated telemetry system along a gradient of forest cover (7-60%) during two seasons (dry vs. wet) at nine sampling sites at the Brazilian Atlantic forest. We monitored 116 individuals and obtained a total of 15,129 bird detections across seasons. Bird resistance to crossing edges was strongly driven by an interaction between seasonality and forest cover in the surrounding landscape, with higher resistance to crossing edges along the dry season and in landscapes with lower amount of forest cover. Furthermore, spillover patterns in plantations were driven by an interaction between forest cover and distance from forest edges, but this was most pronounced for forest-specialist bird species. Forest-specialists moved more intensively and farther from edges in more forested landscapes, whereas forest-generalists showed similar patterns of occupation regardless of forest cover and isolation. Our study contributes to a better understanding of avian cross-boundary responses and spillover in response to landscape structure across seasons and the factors driving bird movement decisions in anthropogenic landscapes. There are a myriad of possible mechanisms governing movement decisions, and these mechanisms may interact in complex ways and remain important foci for research within fields of tropical ecology and evolution in the tropics.
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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.