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29 results for “vegetation sampling”
Data from: Timing of vegetation sampling does not influence associations between visual obstruction and turkey nest survival in a montane forest
Evaluating relationships between ecological processes that occur concurrently is complicated by the potential for such processes to covary. Ground-nesting birds rely on habitat characteristics that provide concealment from predators; this protection often is provided by vegetation at the nest. Recently, researchers have raised concern that measuring vegetation at nest fate introduces a bias, as vegetation at successful nests is measured later in the growing season. This bias can lead to an erroneous conclusion that plant height is positively associated with nest survival. However, if the features that provide concealment are invariant during the incubation period, no bias should be expected, and the timing of measurement is less influential. We used data collected from 98 nests to evaluate whether there is evidence that such a bias exists in a study of wild turkey (Meleagris gallopavo) nesting in a forest ecosystem. We modelled nest survival as a function of visual obstruction and other covariates of interest. At unsuccessful nests, we collected visual obstruction readings at both the date of nest failure and the projected hatch date and compared survival estimates generated using both sets of vegetation data. In contrast to studies in other systems, we found little evidence that the timing of vegetation sampling influenced conclusions regarding the association between visual obstruction and survival; model selection and estimates of nest survival were similar regardless of when vegetation data were collected. The dominant hiding cover at most of our nests was provided by evergreen shrubs; slow growth of these plants likely prevent appreciable changes in visual obstruction during incubation. When considered with a growing body of literature, our results suggest that the influence of timing of sampling depends on the study system. When designing future studies, investigators should consider the structures that provide nest concealment and whether phenology is confounded with nest survival.
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
1. Plant communities are attracting increased interest in connection with forest and landscape inventories due to society's interest in ecosystem services. However, the acquisition of accurate information about plant communities poses several methodological challenges. Here we investigate the use of presence-absence sampling with the aim to monitor state and change of plant density. We study what plot sizes are informative, i.e. the estimators should have as high precision as possible. 2. Plant occurrences were modeled through different Poisson processes and tests were developed for assessing the plausibility of the model assumptions. Optimum plot sizes were determined by minimizing the variance of the estimators. While state estimators of similar kind as ours have been proposed in previous studies, our tests and change estimation procedures are new. 3. We found that the most informative plot size for state estimation is 1.6 divided by the plant density, i.e. if the true density is 1 plant per square meter the optimum plot size is 1.6 square meters. This is in accordance with previous findings. More importantly, the most informative plot size for change estimation was smaller and depended on the change patterns. We provide theoretical results as well as some empirical results based on data from the Swedish National Forest Inventory. 4. Use of too small or too large plots resulted in poor precision of the density (and density change) estimators. As a consequence, a range of different plot sizes would be required for jointly monitoring both common and rare plants using presence-absence sampling in monitoring programmes.
Vegetation samples at the permanent plots of LTER site "Appennino Centrale: Velino-Duchessa" (1993-2023)
<p>The present dataset comprises observations spanning from 1993 to 2023, focusing on biotic parameters collected from six permanent plots included into the LTER site “Appennino Centrale: Velino-Duchessa” (<a href="https://deims.org/12c79ecb-7890-4b75-9655-0883dacd8a29">https://deims.org/12c79ecb-7890-4b75-9655-0883dacd8a29</a>), located in Central Italy above the timberline (2125-2225 m a.s.l.). Specifically, it includes a synthesis of phytosociological relevés collected, according the Braun-Blanquet approach (coverage scale as modified by Pignatti) in 6 permanent plots of 10x10 m (https://deims.org/dataset/0c540fe8-1984-11e5-a766-005056ab003f), representative of two high-elevation plant communities (alpine tundra, <em>Saxifrago speciosae-Silenetum ceniasiae,</em> and snow-bed grassland, <em>Trifolio thalii-Festucetum microphyllae).</em> Species are named according to Flora d'Italia (Pignatti, 1982). The site, managed by Carabinieri, Forest and Environmental Protection Department, is part of the site “IT01- Apennines - High elevation Ecosystems – Italy” (<a href="https://deims.org/70b5c2bd-b0c3-4132-8988-f527893bfa42">https://deims.org/70b5c2bd-b0c3-4132-8988-f527893bfa42</a>) which belongs to the Long Term Ecological Research national and international networks (LTER-Italy, LTER-Europe and ILTER). The data collection started in 1993 and it is continuously updated every year.</p>
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
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Data from: Timing of vegetation sampling does not influence associations between visual obstruction and turkey nest survival in a montane forest
Open the record for dataset details and reuse information.
Trinity assembly of Powdery mildew of vegetable samples lesion fom Italy PM
<p>De novo Trinity assembly RNA seq</p>
SMEX02 Regional Vegetation Sampling Data, Iowa, Version 1
This data set contains the vegetation parameters plant height, row spacing, stand density, and leaf area index (LAI) as part of the Soil Moisture Experiment 2002 (SMEX02).
SMEX02 Watershed Vegetation Sampling Data, Walnut Creek, Iowa, Version 1
This data set contains vegetation parameters as part of the Soil Moisture Experiment 2002 (SMEX02).
Determination of natural radioactivity levels in soil samples from irrigated vegetable farming land in and around Addis Ababa, Ethiopia
<p>This dataset contains 11 data files obtained from a high purity Germanium gamma spectrometry while analysing surface soil samples gathered from vegetable producing area in and around Addis Ababa. The measurement was done in the Ethiopian radiation protection authority laboratory, Addis Ababa, Ethiopia, from August 11 to September 7, 2022. The purpose of the measurement was to evaluate activity concentrations and associated radiological dangers in surface soil from vegetable agricultural area. </p>
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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.