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4,243 results for “seasonality”
Seasonal orographic effect of North American Mountain Range at different levels and its remote control on tropical climate
<p><a name="OLE_LINK36"></a><a name="OLE_LINK37"></a><a name="OLE_LINK81"></a><a name="OLE_LINK6"></a><span><span><span><span>Orography significantly influences global climate patterns. </span></span></span></span><a name="OLE_LINK32"></a><a name="OLE_LINK33"></a><span><span><span><span><span><span>Previous studies show the North American Mountain Range (NAMR) impacts regional climates seasonally but have not thoroughly illustrated the seasonally different atmospheric responses in the lower and upper troposphere, respectively. </span></span></span></span></span></span><span><span><span><span><span>Using the Community Earth System Model version 1.2 with a slab ocean configuration, we investigate the NAMR’s seasonal impacts by simulating scenarios with and without the mountain range. Our findings reveal that the NAMR induces contrasting responses in sea surface temperature (SST) and precipitation off California in different seasons, indicating different underlying mechanisms. Through analysis of large-scale circulation and local energy budgets, we find that in summer, the NAMR reinforces the North Pacific High causing SST cooling and drying off California. This cooling propagates to the equatorial Pacific via anomalous northeasterlies, influencing the Intertropical Convergence Zone and initiating a climatic signal through the Pacific Meridional Mode, which crosses the equator and affects Southern Hemisphere temperatures. In winter, the NAMR reduces wind speed and evaporation, leading to SST warming off California, amplified by SST-cloud feedback. In the upper troposphere, we observe seasonal shifts in jet stream patterns: during winter, a weakened, equatorward-shifted jet over the Pacific and a strengthened, poleward-shifted branch over the Atlantic; in summer, the jet stream intensifies over and downstream of the mountains while weakening upstream. Our research highlights distinct seasonal mechanisms by which the NAMR influence climate patterns, linking mid-latitude climate variations to equatorial, cross-hemispheric and global changes.</span></span></span></span></span></p>
Seasonal RGB composites from Sentinel-2 (2017-2024) for Catalonia, Spain; Sétif, Algeria; Behia and Kafr Elsheihk Governates, Egypt; Marseille, France; Sicily, Italy.
<p>A dataset containing seasonal Sentinel-2 RGB images (2017 to 2024) for five case study areas of the TRANSITION project (https://www.transition-med.org/), funded by PRIMA (https://prima-med.org/). The areas are Catalonia, Spain; Sétif, Algeria; Behia and Kafr Elsheihk Governates, Egypt; Marseille, France; Sicily, Italy. The dataset can be useful for anyone looking to conduct agriculture-related research using Earth Observation data in these five areas.</p>
Datasets and R codes used for the analyses in "Seasonal variation in home range size of White-Backed Woodpeckers"
<p><strong>Abstract</strong></p> <p>Knowing a species’ area requirements is fundamental for species conservation. For the nominate subspecies of the White-backed Woodpecker<em> Dendrocopos leucotos</em>, a species of high conservation concern in Europe, estimates of the seasonal and year-round area requirements based on telemetry are missing. In the present study, we radio-tracked adult White-backed Woodpeckers in Central Europe and investigated bi-monthly home range sizes based on three home range estimators in relation to season, sex, body weight, and year. Home range size of 49 radio-tracked individuals varied depending on the used home range estimator, with minimum convex polygons (MCP) and autocorrelated kernel density estimation (AKDE) producing 1.6 – 1.8 and 2 – 3.3 times larger seasonal home ranges than traditional kernel density estimation (KDE). Moreover, home range sizes varied between seasons. Home ranges were smallest in February/March (predicted median home range sizes ranged from 35 ha with KDE to 88 ha with AKDE) and April/May (KDE: 30 ha, AKDE: 55 ha) and larger during the rest of the year (KDE: 48 – 67 ha, AKDE: 136 – 184 ha). The mean home range size of six individuals tracked in all seasons (calculated with all locations per individual) was 116 ha with KDE, 304 ha with MCP and 350 ha with AKDE. Our results highlight the importance of considering the full annual cycle when addressing area requirements of White-backed Woodpeckers and likely also of other species. Furthermore, our study shows that using multiple methods for home range estimation may be useful to obtain results that are both comparable with those of other studies and capture the range in which the true home range size is likely to be. For the conservation of the White-backed Woodpecker, we conclude that at least 116 to 350 ha of forest should be present for a pair.</p>
Fig. 5 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 5. (left column) Distribution-based Redundancy Analysis (db-RDA) ordination diagram of Lake Chapala with environmental variables (thick arrows), atherinopsids species (italic letters), sampling sites (numbers), and principal coordinates axes (thin arrows) at dry season (a: May of 1999) and rainy season (b: August of 1999; c: 2000). The fish are: jordani = Chirostoma jordani; consocium = Chirostoma consocium; labarcae = Chirostoma labarcae. The environmental variables are: Temp = temperature, DO = dissolved oxygen, Sal = salinity. In figure 5c shallow sites are in italic and deep sites in regular.
Fig. 3 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 3. GAM results for May and August of site influence on fish density to show differential distribution of species in Lake Chapala. a: Chirostoma jordani; b: Chirostoma consocium; c: Chirostoma labarcae. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).
Fig. 2 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 2. GAM results for May of environmental characteristics influence on fish density. a: effect of depth (m) on Chirostoma jordani; b: effect of temperature (°C) on C. jordani; c: effect of salinity on C. consocium. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).
Fig. 1 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 1. Map of Lake Chapala, Mexico. Numbers in bold represent sample sites and numbers in italic lake depths.
Fig. 5 in Seasonal changes in the gonadossomatic index, allometric condition factor and sex ratio of an auchenipterid catfish from eastern Amazonia
Fig. 5. Bimonthly variation in the raw data (a,c) and mean values (b, d) for the condition factor (K) in juvenile (a, b) and adult (c, d) male of the Auchenipterichthys longimanus collected from July 2008 to July 2009 in the Caxiuanã National Forest.
Fig. 1 in Seasonal changes in the gonadossomatic index, allometric condition factor and sex ratio of an auchenipterid catfish from eastern Amazonia
Fig. 1. Sampling area in the National Forest of Caxiuanã, Pará State, showing the rivers where the fish were collected. Curuá River - Ferreira Penna Research Station (ECFPn), Caxiuanã River; Puraquequara River and Caquajó River. Some black spots represent more than one collection site.
Fig. 4 in Seasonal changes in the gonadossomatic index, allometric condition factor and sex ratio of an auchenipterid catfish from eastern Amazonia
Fig. 4. Bimonthly variation in the raw data (a,c) and mean values (b, d) of the gonadosomatic index (GSI) for female (a, b) and male (c, d) of the catfish Auchenipterichthys longimanus collected from July 2008 to July 2009 in the Caxiuanã National Forest.
Floral preferences of mountain bumble bees are constrained by functional traits but flexible through elevation and season
Patterns of resource use by animals can clarify how ecological communities have assembled in the past, how they currently function, and how they are likely to respond to future perturbations. Bumble bees (Hymentoptera: Bombus spp.) and their floral hosts provide a diverse yet tractable system in which to explore resource selection in the context of plant-pollinator networks. Under conditions of resource limitation, the ability of bumble bees species to coexist should depend on dietary niche overlap. In this study, we report patterns and dynamics of floral morphotype preferences in a mountain bumble bee community based on ~13,000 observations of bumble bee floral visits recorded along a 1400 m elevation gradient. We found that bumble bees are highly selective generalists, rarely visiting floral morphotypes at the rates predicted by their relative abundances. Preferences also differed markedly across bumble bee species, and these differences were well-explained by variation in bumble bee tongue length, generating patterns of preference similarity that should be expected to predict competition under conditions of resource limitation. Within species, though, morphotype preferences varied by elevation and season, possibly representing adaptive flexibility in response to the high elevational and seasonal turnover of mountain floral communities. Patterns of resource partitioning among bumble bee communities may determine which species can coexist under the altered distributions of bumble bees and their floral hosts caused by climate and land use change.
Acaulescence promotes speciation and shapes the distribution patterns of palms in Neotropical seasonally dry habitats
<p>Rainforests have been a source of lineages to open and seasonally dry habitats throughout Angiosperm evolution, especially in the Neotropics. However, the underlying mechanisms that allow such shifts remain poorly understood at large spatial scales. Here, we test whether acaulescence (an underground stem or a very short stem concealed in the ground) has affected the colonization and speciation in Neotropical seasonally dry habitats by <span>cocosoid palms</span> (Cocoseae). Acaulescent species maintain their growth underground, which increases their chances of survival from prolonged seasonal dry season and frequent fires. We use an integrative approach based on trait‐dependent diversification models, phylogenetic comparative methods, and ecological niche models. We found that shifts towards acaulescent growth form were accompanied by evolutionary transitions to seasonally dry habitats. Acaulescent lineages had higher speciation rates than non-acaulescent ones.<i> </i>However, the interaction between acaulescence and seasonally dry habitats had no significant effect on Cocoseae speciation rates. Acaulescent palms are primarily distributed in Neotropical seasonally dry habitats and non-acaulescent palms are concentrated in Amazonian rainforests. Our results suggest that an underground stem, with high carbohydrate and water storage capacity, is a preadaptation by which rainforest lineages were able to colonize and diversify in new fire-prone, increasingly seasonal and drier adaptive zones. The projected global expansion of dry seasonal habitats requires an understanding of how drought-avoidance functional traits evolve and how they are linked to seasonally dry habitats. Our results are, thus, a step forward in determining plant response mechanisms to drier and seasonal conditions.</p>
Dataset for "Long-term fluxes of carbonyl sulfide and their seasonality and interannual variability in a boreal forest"
<p>The final dataset used in manuscript "Long-term fluxes of carbonyl sulfide and their seasonality and interannual variability in a boreal forest" by Vesala et al. (2022). The dataset contains carbonyl sulfide (COS) and carbon dioxide (CO2) eddy covariance flux data and in-situ meteorological data measured at Hyytiälä forest in Juupajoki, Southern Finland, as well as meteorological drivers for SiB4 simulations and SiB4 simulated COS flux at the Hyytiälä grid cell from January 2013 to December 2017. Raw data are available upon request from the author.</p>
Model-informed target product profiles of long-acting- injectables for use as seasonal malaria prevention: code and simulation data
<p>This simulation data set and code reproduces the Figures and analysis of PLOS Global Public Health peer-reviewed article </p> <p><strong>Model-informed target product profiles of long-acting-injectables for use as seasonal malaria prevention</strong></p> <p>Authors:</p> <p>Lydia Burgert<sup>1, 2</sup>, Theresa Reiker<sup>1, 2</sup>, Monica Golumbeanu<sup>1,2</sup>, Jörg J. Möhrle<sup>1, 2, 3</sup>, Melissa A. Penny*<sup>1, 2</sup></p> <p> </p> <p><sup>1</sup> Swiss Tropical and Public Health Institute, Basel, Switzerland</p> <p><sup>2</sup> University of Basel, Basel, Switzerland</p> <p><sup>3 </sup>Medicines for Malaria Venture, Geneva, Switzerland</p> <p>*Corresponding author: <a href="mailto:melissa.penny@unibas.ch">melissa.penny@unibas.ch</a></p>
Process Controls on Flood Seasonality in Brazil - link to data and plots
<p>This data set and plots of circular histograms accompany the paper "Process Controls on Flood Seasonality in Brazil" at Geophysical Research Letters (<a href="https://doi.org/10.1029/2021GL096754">https://doi.org/10.1029/2021GL096754</a>). In this paper, we investigate the relationship between the seasonality of floods, maximum annual rainfall, and maximum annual soil moisture data of 886 basins in Brazil for 1980-2015 to shed light on process controls of flood generation.</p>
Data and scripts for: Genetic dissection of seasonal vegetation index dynamics in maize through aerial based high-throughput phenotyping
<p>Plant phenotyping under field conditions plays an important role in agricultural research. Efficient and accurate high-throughput phenotyping strategies enable a better connection between genotype and phenotype. Unmanned aerial vehicle-based high-throughput phenotyping platforms (UAV-HTPPs) provide novel opportunities for large-scale proximal measurement of plant traits with high efficiency, high resolution, and low cost. The objective of this study was to use time series normalized difference vegetation index (NDVI) extracted from UAV-based multispectral imagery to characterize its pattern across development and conduct genetic dissection of NDVI in a large maize population. The time series NDVI data from the multispectral sensor were obtained at 5 time points across the growing season for 1,752 diverse maize accessions with a UAV-HTPP. Cluster analysis of the acquired measurements classified 1,752 maize accessions into 2 groups with distinct NDVI developmental trends. To capture the dynamics underlying these static observations, penalized-splines (P-splines) model was used to obtain genotype-specific curve parameters. Genome-wide association study (GWAS) using static NDVI values and curve parameters as phenotypic traits detected signals significantly associated with the traits. Additionally, GWAS using the projected NDVI values from the P-splines models revealed the dynamic change of genetic effects, indicating the role of gene-environment interplay in controlling NDVI across the growing season. Our results demonstrated the utility of ultra-high spatial resolution multispectral imagery, as that acquired using a UAV-based remote sensing, for genetic dissection of NDVI.</p>
Data and code from: Seasonal variation in the response to a toxin-producing cyanobacteria in Daphnia
<p>Data and code accompanying: </p> <p>Hegg, Radersma & Uller. 2022. Seasonal variation in the response to a toxin-producing cyanobacteria in Daphnia. Freshwater Biology, accepted.</p> <p><strong>Abstract</strong></p> <ol> <li>Many populations of water fleas (<em>Daphnia</em>) are exposed to algal blooms dominated by microcystin-producing cyanobacteria. However, the severity of these effects on <em>Daphnia</em> fitness remain poorly understood in natural populations. </li> <li>We investigated seasonal changes in body size, reproduction and survival of <em>Daphnia</em> <em>longispina</em> individuals from five eutrophic lakes in southern Sweden. We tested whether individuals collected before, during or following algal blooms differed in their reproduction and survival when experimentally exposed to microcystin-producing cyanobacteria. </li> <li>The concentration of microcystin in the lakes was significantly higher during summer and autumn compared to spring, but there were substantial differences between lakes. The reproductive output of individuals declined consistently over the season, and this decline was stronger for <em>Daphnia</em> collected during periods of, or lakes from, high microcystin concentration. There was little evidence that individuals adapted to the toxin over the season. </li> <li>The strong seasonal changes in body size, reproduction and survival in these <em>Daphnia</em> <em>longispina</em> appears to be partly caused by variation in the abundance of toxin-producing cyanobacteria. Populations were unable to adapt sufficiently quickly during summer and autumn to recover from the negative effects of microcystin. We therefore suggest that seasonal increases in tolerance to microcystin-producing cyanobacteria have limited effects on the eco-evolutionary dynamics between <em>Daphnia</em> and phytoplankton.</li> </ol>
Long-term simulation of snow cover and its potential impacts on seasonal frost dynamics in croplands across southern Canada
<p><em>In northern climes, accurate simulation of thermal and hydrological budgets for farmlands during overwintering conditions is crucial to both an accurate prediction of spring flooding and the successful management of nutrient losses. As snow cover influences soil freezing dynamics, it has been hypothesized that reduced snow cover due to warmer winters might increase the depth and duration of frozen soil conditions. Nonetheless, such impacts remain poorly understood and, given the difficulty in measuring the depth of frozen soil, no long-term field experiment has documented these potential effects. The present study was designed to test this hypothesis. Drawing upon observed snow depth and soil temperature data collected from six research farms across Southern Canada over various time spans from 1989 to 2020, the Root Zone Water Quality Model, integrated with the Simultaneous Heat and Water model, was calibrated and validated. The potential influence of warmer winter on shifts in soil frost dynamics was evaluated by estimating the depth and duration of frozen soil for each farmland site under various RCP temperature scenarios using the RZ-SHAW model. Soil frozen depth in Eastern site increased with the increase of RCP temperature scenarios in some years, but decreased under the highest RCP temperature scenario. The monthly relationship between snow depth and soil frozen depth was determined through partial correlation analysis. Snow was most effective in alleviating soil freezing in the months of January and February, a period when snow cover depth was least affected by warming air temperatures. This paper suggests that Global warming induced-snow cover reduction would be site-specific and is </em>more likely to occur in <em>regions where energy lost through reduced snow cover would outweigh the energy gained through warmer air temperature.</em></p>
Species Portfolio Effects Dominate Seasonal Zooplankton Stabilization Within a Large Temperate Lake
<p>The raw data file is available online for public access (<a href="https://data.ontario.ca/dataset/lake-simcoe-monitoring">https://data.ontario.ca/dataset/lake-simcoe-monitoring</a>). Download the 1980-2019 csv files and open up the file named "Simcoe_Zooplankton&Bythotrephes.csv". Copy and paste the zooplankton sheet into a new excel file called "Simcoe_Zooplankton.csv". The column ZDATE in the excel file needs to be switched from GENERAL to SHORT DATE so that the dates in the ZDATE column read "YYYY/MM/DD". Save as .csv in appropriate R folder. The data file "simcoe_manual_subset_weeks_5" is the raw data that has been subset for the main analysis of the article using the .R file "Simcoe MS - 5 Station Subset Data". The .csv file produced from this must then be manually edited to remove data points that do not have 5 stations per sampling period as well as by combining data points that should fall into a single week. The "simcoe_manual_subset_weeks_5.csv" is then used for the calculation of variability, stabilization, asynchrony, and Shannon Diversity for each year in the .R file "Simcoe MS - 5 Station Calculations". The final .R file "Simcoe MS - 5 Station Analysis contains the final statistical analyses as well as code to reproduce the original figures. Data and code for main and supplementary analyses are also available on GitHub (https://github.com/reillyoc/ZPseasonalPEs). </p> <p> </p>
UAV outputs and associated field measurement of the herbaceous of a Sahelian Rangeland during the wet season in Northern Senegal
<p>This dataset contains UAV outputs (mosaic and digital surface model) and field measurement of vegetation (shapefile) that were made in northern Senegal.</p> <p><strong>Site gradient measurement</strong></p> <p>The data was collected on a plot of the Centre of Zootechnical Researches of Dahra / ISRA during 2020 rainy season (from July 19, 2020, to September 17, 2020). The average rainfall for the period 1981-2018 was ranging from 221 mm.y-1 to 468 mm. y-1. The vegetation in the field is a herbaceous savannah where <em>Vachellia tortilis</em> and <em>Balanites aegyptiaca</em> are the dominant trees.</p> <p><strong>Field measurement.</strong></p> <p><strong>UAV flight plan</strong></p> <p>We used two different drones : Bluegrass and Anafi of Parrot. The Bluegrass of Parrot was used from 19/07/2020 to 04/08/2020. The Bluegrass flights were done at 60 meters of altitude, with a speed of 2 m s<sup>-1</sup>, and 90% of overlap rate between images, on a double grid of 100 m x 100 m. Anafi of Parrot was used for the rest of the season. The Anafi flights were done at 60 meters of altitude, with a speed of 2 m s<sup>-1</sup>, and 90% of overlap rate between images, on a double grid of 100 m x 100 m and the angle of inclination of the camera fixed at 80°. The flights have been done with PIX4D capture application at earlier in the day every two days. A total of 61 drone flights were conducted over the rainy season.</p> <p><strong>Herbaceous Biomass</strong></p> <p>Every two days , after drone flight, herbaceous measurements were carried out, in three plots of 1 m² distributed respectively under the crown of a tree, at the edge of the crown, and at a distance from the edge of the crown equal to the height of the tree. These plots were rotated among the trees in the field until all four azimuths of trees were covered.We collected Fresh mass and dry mass.</p> <p><strong>Image analysis.</strong></p> <p>The drone images taken for each day of collect, were analyzed in the software PIX4DMapper (Pix4D SA, Lausanne, Switzerland) by the Structure from Motion method. We used precisely the 3D mapping option of the software. Then for each flight we computed and exported an orthophotograph and a digital surface model.</p> <p><strong>Data organization</strong></p> <p>The data contains :</p> <ul> <li>DSM that contains the surface model in tiff</li> <li>Mosaic that the orthomosaic in tiff.</li> <li>Data that contains the shapefile with the position and table with the field measurements</li> </ul>
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)
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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.