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555 results for “Woody”
Woody Cover Mapping in the Kruger National Park using Sentinel-1 time series and LiDAR data
<p>This data repository presents a workflow to derive woody cover information for the Kruger National Park, South Africa, from freely available Sentinel-1 C-Band time series and LiDAR data (modified from Smit et al. 2016) using machine learning (MLR and Ranger in R). The methodology is described in following publication:</p> <p><em>Urban, M., K. Heckel, C. Berger, P. Schratz, I.P.J. Smit, T. Strydom, J. Baade & C. Schmullius (2020): Woody Cover Mapping in the Savanna Ecosystem of the Kruger National Park Using Sentinel-1 C-Band Time Series Data. Koedoe.</em></p> <p>In order to derive woody cover percentage information, download all files into one folder and run the R-Files consecutively from 01_ to 04_. Follow the instruction within each of the R-Files, which are written as comments in the programming code.</p> <p>The data repository consist of the following files:</p> <p><strong>R-Files:</strong></p> <p>1. Script 1: 01_MLR_tune_spatial_final</p> <p>2. Script 2: 02_MLR_cross_validation_spatial_final</p> <p>3. Script 3: 03_MLR_RANGER_train_final</p> <p>4. Script 4: 04_MLR_prediction_woody_cover_final</p> <p> </p> <p><strong>Training dataset - ENVI FILE (layerstack of Sentinel-1 VH and VV backscatter between 2016 and 2017 and the woody cover reference derived from the LiDAR data) :</strong></p> <p>1. S1_A_VH_VV_16_17_lidar</p> <p> </p> <p><strong>Data for prediction - ENVI FILES (3 example regions in the Kruger National Park):</strong></p> <p>1. S1_A_VH_VV_16_17_subset_example_Letaba_Rest_Camp</p> <p>2. S1_A_VH_VV_16_17_subset_example_Lower_Sabie</p> <p>3. S1_A_VH_VV_16_17_subset_example_Pafuri</p> <p> </p> <p><strong>Final woody cover maps of the Kruger National Park:</strong></p> <p>1. xx_woody_cover_map_final.rar (contains final maps in 10m, 30m, 50m and 100m spatial resolution as .tif and a QGIS project)</p> <p> </p> <p><em>References:</em></p> <p>Smit, I.P.J., Asner, G.P., Govender, N., Vaughn, N.R. & Wilgen, B.W. van, 2016, ‘An examination of the potential efficacy of high-intensity fires for reversing woody encroachment in savannas’, <em>Journal of Applied Ecology</em>, 53(5), 1623–1633.</p>
Dataset of Invasion risks and social interest of non-native woody plants in urban parks of Spain
<p>Full datasets for the research entitled "Invasion risks and social interest of non-native woody plants in urban parks of Spain"</p>
Foliar stoichiometry of woody plants worldwide
<p>This data includes foliar N, P, K % in DW of mature leaves in woody plants worldwide. It also contains the georeferenced information and specie. It gathers data from 230 published articles, TRY database (<a href="http://www.try-db.org/TryWeb/dp.php),">http://www.try-db.org/TryWeb/dp.php),</a> ICP forest database (<a href="http://icp-forests.net/page/data-requests),">http://icp-forests.net/page/data-requests),</a> Tundra Trait Team and the Catalan Forest Inventory (Gracia et al., 2004).</p>
Unveiling the genetic networks: Exploring the dynamic interaction of photosynthetic phenotypes in woody plants across varied light gradients
<p><em>Background:</em></p> <p>Understanding the mechanisms by which genes control and regulate complex quantitative traits during periods of fluctuating resources remains a challenging and uncertain task in photosynthesis studies. Most studies have focused on the structure of photosynthesis, the photosynthetic response under stress, or the genetic mechanisms involved in photosynthetic effects and neglected the interactive genetic mechanism that governs various traits through significant quantitative trait loci (QTLs). Results In this study, we have developed a differential dynamic system that enables the identification of QTLs based on the photosynthetic phenotypic and genotypic data under varying levels of light intensity gradients. The framework not only allows for the assessment of the direct effects of QTLs on phenotypes but also captures how they influence interactions among phenotypes as light intensities change. We have analyzed the genetic effects and genetic variance, visualized the genetic network associated with photosynthesis interactions, and validated the effectiveness and stability of the DDS framework. Pivotal QTLs were identified individually to uncover the process and pattern of interaction. Through functional annotation, we made an intriguing discovery that seemingly unimportant QTLs can still have significant genetic effects on phenotypic changes through their regulation with other QTLs. Conclusions This finding emphasizes the significance of considering the interactive genetic architecture when seeking to understand the genetic interaction mechanism of photosynthesis in natural populations of woody plants. Moreover, our research provides a novel framework that can be extended to explore the interactive genetic architecture among organisms, contributing to a deeper understanding of stress resistance mechanisms in woody plants.</p>
Acer negundo (Aceraceae) - woody angiosperms - leaf
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf
Acer negundo (Aceraceae) - woody angiosperms - leaf - showing orientation on twig
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf - showing orientation on twig
Acer negundo (Aceraceae) - woody angiosperms - bark - of a large tree
Image of Acer negundo (Aceraceae) - woody angiosperms - bark - of a large tree
Acer negundo (Aceraceae) - woody angiosperms
Image of Acer negundo (Aceraceae) - woody angiosperms
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Acer negundo (Aceraceae) - woody angiosperms - leaf - showing orientation on twig
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf - showing orientation on twig
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Image of Acer negundo (Aceraceae) - woody angiosperms - leaf - whole upper surface
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Acer negundo (Aceraceae) - woody angiosperms - whole tree (or vine) - general
Image of Acer negundo (Aceraceae) - woody angiosperms - whole tree (or vine) - general
Acer negundo (Aceraceae) - woody angiosperms - whole tree (or vine) - general
Image of Acer negundo (Aceraceae) - woody angiosperms - whole tree (or vine) - general
Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
Image of Acer negundo (Aceraceae) - woody angiosperms - fruit - as borne on the plant
ScienceDex guides
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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)
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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.