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1,604 results for “Wintering”
Quercus macrocarpa (Fagaceae) - whole tree (or vine) - winter
Image of Quercus macrocarpa (Fagaceae) - whole tree (or vine) - winter
Fagus grandifolia (Fagaceae) - whole tree (or vine) - winter
Image of Fagus grandifolia (Fagaceae) - whole tree (or vine) - winter
Diospyros virginiana (Ebenaceae) - whole tree (or vine) - winter
Image of Diospyros virginiana (Ebenaceae) - whole tree (or vine) - winter
Diospyros virginiana (Ebenaceae) - whole tree (or vine) - winter
Image of Diospyros virginiana (Ebenaceae) - whole tree (or vine) - winter
Gymnocladus dioicus (Fabaceae) - whole tree (or vine) - winter
Image of Gymnocladus dioicus (Fabaceae) - whole tree (or vine) - winter
Quercus phellos (Fagaceae) - whole tree (or vine) - winter
Image of Quercus phellos (Fagaceae) - whole tree (or vine) - winter
Quercus palustris (Fagaceae) - whole tree (or vine) - winter
Image of Quercus palustris (Fagaceae) - whole tree (or vine) - winter
Platanus occidentalis (Platanaceae) - whole tree (or vine) - winter
Image of Platanus occidentalis (Platanaceae) - whole tree (or vine) - winter
Platanus occidentalis (Platanaceae) - whole tree (or vine) - winter
Image of Platanus occidentalis (Platanaceae) - whole tree (or vine) - winter
Typical Winter TGF lightning: vertical negative leader progression features and charge structures
<p>This dataset contains the detailed parameters of 14 events in the “Winter TGF lightning characteristics and charge structures”. Positioning results from DALMA.</p>
IR Lab Cologne/Jena/Kassel Winter Term 2024/2025
<h1>The Datasets for the Information Retrieval Courses in Cologne/Jena/Kassel in Winter Term 2024/2025</h1> <p>This repository contains resources coupled to <a href="https://arxiv.org/pdf/2103.02280.pdf">ir_datasets</a> and <a href="https://webis.de/publications.html?q=tira#froebe_2023e">TIREx</a> for IR courses that focus their hands-on labs on shared tasks. During the <a href="https://tira.io/task-overview/ir-lab-wise-2024">IR exercises in winter term 2023/2024</a>, we collaboratively developed and evaluated IR systems in a shared task style setup, covering corpus creation, system development, and statistical analysis. The resulting artifacts, i.e., the documents, topics, runs, relevance judgments can be browsed at <a href="https://tira.io/task-overview/ir-lab-wise-2024">https://tira.io/task-overview/ir-lab-wise-2024</a>. This zenodo artifact contains all of the underlying datasets used and produced during the course together with instructions on how to easily access the data using ir_datasets.</p> <p> </p> <p>The artifact in this dataset include the following files:</p> <ul> <li>subsampled-ms-marco-deep-learning-20241201-training-inputs.zip containing the training inputs, i.e., containing the document corpus and the topics.</li> <li>subsampled-ms-marco-deep-learning-20241201-training-truths.zip containing the training truth to evaluate and tune systems, i.e., the topics and relevance judgments.</li> </ul> <h2>Accessing the Data with ir_datasets</h2> <p>We provide wrapper code to easily access the resources with ir_datasets:</p> <pre><code># this loads a patched version of ir_datasets that can load resources from TIRA from tira.third_party_integrations import ir_datasets training_dataset = ir_datasets.load('ir-lab-wise-2024/subsampled-ms-marco-deep-learning-20241201-training')</code></pre> <p>Similarly, the same is possible with the ir_datasets integration to PyTerrier:</p> <pre><code>from tira.third_party_integrations import ensure_pyterrier_is_loaded import pyterrier as pt # this patches ir_datasets and loads PyTerrier so that it can load resources from TIRA and can run in the TIRA sandbox ensure_pyterrier_is_loaded() training_dataset = pt.datasets.get_dataset('irds:ir-lab-wise-2024/subsampled-ms-marco-deep-learning-20241201-training')</code></pre> <p> </p>
Formation of winter barrier layers in the northern South China Sea: A study based on Argo profiling data from 2008 to 2020
<p>The data was used in the paper “Formation of winter barrier layers in the northern South China Sea: A study based on Argo profiling data from 2008 to 2020”.</p> <p>The data include interpolated Argo temperature/salinity (T/S) profiles for the period 2008-2020 in the 15°N–23°N, 109°E–121°E region, as well as derived mixed layer depth (MLD), isothermal layer depth (ILD), and barrier layer thickness (BLT). The original archival data were obtained from the French Argo Data Center (ftp://ftp.ifremer.fr/ifremer/argo/geo/pacific_ocean).</p>
Simulated winter snow, soil thermal regime, and artificial drainage dynamics under climate change.
<p>This dataset provides simulated winter subsurface drainage outputs from the calibrated Root Zone Water Quality Model–Simultaneous Heat and Water (RZ-SHAW) and four machine-learning models (Cubist, LSTM, Multilinear, SVM) for five agricultural research sites across Eastern Canada (Alfred, Harrow, Kentville, Ottawa-Greenbelt, and St-Emmanuel). The simulations span from 1950 to 2100 under the high-emission climate change scenario RCP8.5, derived from the Canadian Regional Climate Model Large Ensemble (CANRCM4 LE).</p> <p>Included in this repository are:</p> <ul> <li> <p>Winter drainage volume's future projections from 1950 to 2100 the RZ-SHAW and machine-learning models.</p> </li> <li> <p>RZ-SHAW simulated future projections from 1950 to 2100 in snow cover, soil thermal conditions, subsurface drainage volume and frequency, evaporation, surface runoff, and soil water storage.</p> </li> </ul> <p>This dataset also contains simulated annual crop yield projections (kg/hectare) from 1950 to 2100 the five sites Alfred (corn), Harrow (corn and soybean), Kentville (corn), Ottawa (corn), St-Emmanuel (corn). Simulations were performed using the RZ-SHAW model under RCP8.5 climate change scenario. Each site's data includes annual grain yield values and Sen's slope trend analysis with Mann-Kendall significance test results.</p> <p>Users should note the following important limitations when interpreting these yield projections:</p> <ol> <li>Simplified Crop Growth Parameters: The crop module was implemented primarily to account for crop residue effects on winter soil conditions, not for yield prediction. No calibration was performed for crop growth parameters.</li> <li>No Nutrient Stress: Simulations were run without nitrogen or phosphorus limitations for simplicity, which may overestimate yields in scenarios where nutrient availability would be constraining.</li> <li>Fixed Management Practices: Planting and harvest dates were held constant throughout the simulation period (1950-2100) based on historical averages, which becomes increasingly unrealistic under future climate conditions.</li> <li>No CO₂ Fertilization Effect: Atmospheric CO₂ concentration changes were not incorporated, potentially underestimating photosynthetic responses in future climate scenarios.</li> <li>Limited Stress Responses: The model's representation of heat stress, drought tolerance, and other physiological responses to extreme conditions may not fully capture crop responses under future climate scenarios.</li> <li>No Adaptation Strategies: The simulations do not account for potential adaptations such as cultivar changes, shifting planting dates, or irrigation implementation that would likely occur in response to changing conditions.</li> </ol>
Bridging the gap between total peroxyl radical observations and models by measuring OH reactivity to improve estimates of ozone production: a case study from the 24th Winter Olympics Games-
Open the record for dataset details and reuse information.
Data from: Vertical sexual habitat segregation in a wintering migratory songbird
<p>Sexual habitat segregation during the wintering period is a widespread phenomenon and has important implications for the ecology and conservation of migratory birds. We studied Black-and-white Warblers (<i>Mniotilta varia) </i>wintering in second-growth scrub and old-growth mangrove forest in Jamaica to quantify sexual habitat segregation and explore whether patterns of habitat occupation have consequences on physical condition. We then used this information along with a body size analysis and simulated territorial intrusions to assess whether behavioral dominance or habitat specialization was responsible for habitat segregation. Based on standardized capture data, we found that females were more abundant than males in both scrub and mangrove forests. Foraging observations, however, suggested vertical segregation within each habitat, with females foraging primarily near the ground and males in the mid-canopy and canopy, indicating that our sex ratio estimates may be biased. Using 2 measures of body condition, we show that males were in better body condition than females, regardless of habitat. We found that males were on average slightly larger than females, and home range analysis and simulated territorial intrusions indicated that males were more territorial than females. We argue that the observed vertical sexual habitat segregation is likely caused by behavioral dominance rather than habitat specialization. Winter body condition is known to carry-over to affect migration timing, reproductive success, and annual survival in other songbirds, and therefore sexual habitat segregation may have important implications for year-round population dynamics in Black-and-white Warblers.</p>
Effects of temperature on seed dormancy and germination of the coastal dune plant Viola grayi: Germination phenology and responses to winter warming
<p>PREMISE: In temperate sand dunes, rising air temperature owing to climate change could not only further elevate surface soil temperatures during summers but also drastically change the range of soil temperatures in other seasons. Winter warming may shift the timing of seed germination of dune species that require cold stratification for dormancy release.</p> <p>METHODS: We assessed the effects of temperature on dormancy and germination of <i>Viola grayi</i> seeds and evaluated whether winter warming could affect its germination phenology by conducting germination experiments and analyzing soil temperature data in cold and warm winters.</p> <p>RESULTS: <i>Viola grayi</i> seeds were dormant when dispersed in spring. One-month moist-chilling treatment (4°C) effectively released dormancy, while short, intermittent lower temperatures (alternating 20/5°C) did not. Continuous higher temperatures induced secondary dormancy in non-dormant seeds. During a cold, snowy winter, the surface soil temperatures of the sand dune remained at 0–2°C for approximately one month owing to the accumulated snow, while the period of such stable low soil temperatures was much shorter during a warm, less snowy winter, and the highest soil temperature class reached 20–25°C. These results suggest that dispersed seeds germinate in the following spring after winter chilling, but they may remain dormant after warm winters.</p> <p>CONCLUSIONS: With winter warming, prolonged seed dormancy and associated germination delay could occur in <i>V. grayi</i> seeds. Assessing the minimum requirements for dormancy release and the potential to form persistent soil seed banks is important for judging the necessity and urgency of conservation efforts for temperate dune species.</p>
Data from: Northwest range shifts and shorter wintering period of an Arctic seabird in response to four decades of changing ocean climate
<p>Climate change is altering the marine environment at a global scale, with some of the most dramatic changes occurring in Arctic regions. These changes may affect the distribution and migration patterns of marine species throughout the annual cycle. Species distribution models have provided detailed understanding of the responses of terrestrial species to climate changes, often based on observational data; biologging offers the opportunity to extend those models to migratory marine species that occur in marine environments where direct observation is difficult. We used species distribution modelling and tracking data to model past changes in the non-breeding distribution of thick-billed murres <em>Uria lomvia</em> from a colony in Hudson Bay, Canada, between 1982 and 2019. The predicted distribution of murres shifted during fall and winter.</p> <p>The largest shifts have occurred for fall migration, with range shits of 211 km west and 50 km north per decade, compared with a 29 km shift west per decade in winter. Regions of range expansions had larger declines in sea ice cover, smaller increases in sea surface temperature, and larger increases in air temperature than regions where the range was stable or declining. Murres migrate in and out of Hudson Bay as ice forms each fall and melts each spring. Habitat in Hudson Bay has become available later into the fall and earlier in the spring, such that habitat in Hudson Bay was available for 21 d longer in 2019 than in 1982. Clearly, marine climate is altering the distribution and annual cycle of migratory marine species that occur in areas with seasonal ice cover.</p>
FIGURE 2 in Dothidea kunmingensis, a novel asexual species of Dothideaceae on Jasminum nudiflorum (winter jasmine) from Southwestern China
FIGURE 2. Dothidea kunmingensis (KUMCC 21-0083 holotype) on decaying stem of Jasminum nudiflorum (a‒k) and on PDA after 4 weeks (1‒x). a, b. Conidiomata on a decaying stem of Jasminum nudiflorum. c. Vertical sections through conidioma. d. Conidioma wall. e, f, o, p. Conidiogenous cells and developing conidia. g–j, r–x. Conidia. k. Germinating conidia. l–m. Culture characteristics on PDA after 2 weeks (l = from above, m = from below). n. Conidiomata on PDA after 4 weeks. q. Conidiogenous cell and conidiophore. Scale bars: c = 30 µm, d = 10 µm, e = 5 µm, f = 10 µm, g–j = 5 µm, k = 20 µm, o = 5 µm, p–r = 10 µm, s–x = 2 µm.
FIGURE 1. Phylogenetic tree obtained inferred from 69 taxa and 4287 in Dothidea kunmingensis, a novel asexual species of Dothideaceae on Jasminum nudiflorum (winter jasmine) from Southwestern China
FIGURE 1. Phylogenetic tree obtained inferred from 69 taxa and 4287 sites of a combined SSU, LSU, ITS, tub2 and tef1-α sequence dataset. Numerical values at the nodes indicate maximum likelihood bootstrap support (MLBS) and posterior probabilities (PP) in this order. Bootstrap support values for ML higher than 70 % and PP higher than 0.95 are indicated at the node. Ex-type strains are in bold font; the newly generated sequence is in blue bold font.
FIGURE. Microscopic structures of Rhodocollybia tablensis a, b, e, f (PAN238), c, d (KaiR343) a. Basidia. b. Basidiospores. c. Cheilocystidia. d. Pleurocystidia. e. Stipitipellis with caulocystidia. f. Pileipellis with terminal cells. Bars a, b and c = 10 µm, d, e and f = 20 µm. Drawings by H. Lotz-Winter. in New and interesting species of Agaricomycetes from Panama
FIGURE. Microscopic structures of Rhodocollybia tablensis a, b, e, f (PAN238), c, d (KaiR343) a. Basidia. b. Basidiospores. c. Cheilocystidia. d. Pleurocystidia. e. Stipitipellis with caulocystidia. f. Pileipellis with terminal cells. Bars a, b and c = 10 µm, d, e and f = 20 µm. Drawings by H. Lotz-Winter.
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