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32 results for “phenological stages”
PixelCropRobot dataset: images of vegetables crops in different phenological stages taken in greenhouses
<p><em>Dataset created under the PixelCropRobot project, developed by FCUP, INESC TEC and FEUP.</em></p> <p><strong>Dataset folder:</strong></p> <blockquote> <p>This folder contains the images of each species in two formats (3456 × 4608 pixels and 864 × 1152 pixels), the annotations of the 864 × 1152 px. images, in Pascal VOC (.xml) and YOLO (.txt) formats and also a set of Python scripts useful for managing the dataset.</p> </blockquote> <p>The aim was to capture images of eight crops selected taking into account the length of the crop cycle (annual), the intensity of agricultural practices (mainly weed removal) and the low impact of pests and diseases.</p> <p>The images were captured using a smartphone (Huawei Mate 10 Lite), with 16 megapixels (MP) resolution (3456 × 4608 px.), in Professional mode (no flash, continuous autofocus, automatic ISO and shutter speed). Image collection took place at different hours of the day, with variable lighting conditions.</p> <p>The images are divided as follows (in parenthesis are the classes):</p> <ul> <li>Arugula - 312 (coty, minus9, plus9)</li> <li>Carrot - 533 (coty, smallleaves, carrot)</li> <li>Coriander - 321 (coty, smallleaves, coriander)</li> <li>Lettuce - 1426 (coty, minus9, plus9, ready)</li> <li>Radish - 494 (coty, smallleaves, bigleaves, root)</li> <li>Spinach - 270 (spinach, big)</li> <li>Swiss chard - 454 (coty, chard)</li> <li>Turnip - 313 (coty, smallleaves, turnip)</li> </ul> <p>To standardise the dataset, each image was renamed according to the corresponding EPPO (European and Mediterranean Plant Protection Organization) code and the date of creation of that image. The size of each image was also reduced four times (to 864 × 1152 pixels) to facilitate processing. For example, an image of lettuce captured on June 22 presents the name as follows: LACSA_Jun_22_x_864_1152.jpg.</p>
Large-scale and fine-grained phenological stage annotation of herbarium specimens datasets
<p>This upload is constituted of four datasets of specimens from American herbaria covering different levels of information precision and different floras - from temperate to equatorial.</p> <p>Three of these datasets consist of selected specimens from herbaria located in different geographic and environmental regions. Each specimen of these three datasets was annotated with the following fields: family, genus, species name, fertile / non-fertile, presence / absence of flower(s), presence / absence of fruit(s). The resulting dataset was composed of 163,233 herbarium specimens belonging to 7,782 species, 1,906 genera, and 236 families. Specimens were annotated as “fertile” if any reproductive structures were present, such as sporangia (ferns), cones (gymnosperms), flowers, or fruits (angiosperms). Non-fertile specimens were those that lacked any reproductive structures.</p> <p>The fourth dataset consists of 20,371 herbarium specimens from 11 genera in the sunflower family (<em>Asteraceae</em>). The main difference in this dataset is that it is annotated with fine-grained phenophase scores rather than presence/absence attributes (see description below).</p> <p>Each of these datasets is described below:</p> <ul> <li> <p>NEVP: this dataset of New England vascular plant (NEVP) specimens was produced by members of the Consortium of Northeastern Herbaria. The dataset comprises 42,658 digitized specimens that belong to 1,375 species and come from several North American institutions. Most of the specimens in this dataset are from the north-temperate region of the northeastern United States.</p> </li> <li> <p>FSU: this dataset was produced by the Florida State University's Robert K. Godfrey Herbarium (FSU), a collection that focuses on northern Florida and the U.S. Southeast Coastal Plain, one of North America's biodiversity hotspots. This dataset contains 54,263 digitized herbarium specimen records that belong to 3,870 species, making it the taxonomically richest dataset in this study. Most species in this dataset grow under subtropical or warm temperate conditions in the southeastern region of the United States.</p> </li> <li> <p>CAY: this dataset comes from the IRD’s Herbarium of French Guiana (CAY). CAY is dedicated to the Guayana Shield flora, with a strong focus on tropical tree species. This dataset is composed of 66,312 herbarium specimens that belong to 3,024 species. All digitized specimens of this herbarium are accessible online. Most specimens were collected in the tropical rainforests of French Guiana, with the remaining specimens coming mostly from Suriname and Guyana.</p> </li> <li> <p>PHENO: this dataset includes 20,371 herbarium specimens of 139 species in the <em>Asteraceae</em> produced in a study of phenological trends in the U.S. Southeast Coastal Plain. The dataset is composed of specimen records from 57 herbaria. Each recorded specimen was annotated for quartile percentages (0, 25, 50, 75, or 100%) of (i) closed buds, (ii) buds transformed into flowers, and (iii) fruits. According to the distribution of these three categories for each specimen, a phenophase code was computed.</p> </li> </ul> <p> </p> <p><strong>Datasets format</strong></p> <p>These datasets are grouped in 3 tasks:</p> <ol> <li>fertility detection</li> <li>flowers and/or fruit detection</li> <li>phenophase classification</li> </ol> <p>The first 2 tasks are carried on the first 3 previous datasets and thus are based on the same set of images, unlike the third task which has its own disjoint set of images. This is why the dataset is presented into two separated files, one for each set of images.</p> <p><em>Fertility detection & flower/fruit detection</em></p> <p>These tasks are contained into the <em>herbarium_fertility_annotations.zip</em> archive. It consists of 3 files:</p> <ul> <li><em>metadata.csv</em>: general information about all the herbarium specimens for these tasks <ul> <li><em>id</em>: specimen identifier</li> <li><em>collection</em>: which of NEVP, FSU or CAY does the specimen come from</li> <li><em>herbarium</em>: institution of origin of the specimen, especially for NEVP collection</li> <li><em>clade</em>,<em> family</em>,<em> genus</em>,<em> species</em>: classification of the specimen</li> <li><em>URL</em>: URL of the scan</li> </ul> </li> <li><em>fertility_task.csv</em>: specific information regarding the fertility detection task <ul> <li><em>id</em>: specimen identifier</li> <li><em>is_fertile</em>: <em>True</em> if the specimen has an expression of fertility, <em>False</em> otherwise</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em>, <em>random_test</em>, <em>species_test</em> and <em>herbarium_test</em></li> </ul> </li> <li><em>flower_fruit_task.csv</em>: specific information regarding the flower/fruit detection task <ul> <li><em>id</em>: specimen identifier, note that in this case not all the specimen described in <em>metadata.csv</em> are included in this task</li> <li><em>has_flower</em>: <em>True</em> if the specimen has at least one flower, <em>False</em> otherwise</li> <li><em>has_fruit</em>: <em>True</em> if the specimen has at least one fruit, <em>False</em> otherwise</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em>, <em>random_test</em>, <em>species_test</em> and <em>herbarium_test</em></li> </ul> </li> </ul> <p><em>Phenophase classification</em></p> <p>These tasks are contained into the <em>herbarium_asteraceae_phenophase_annotations.zip</em> archive. It consists of a single file:</p> <ul> <li><em>annotations.csv</em>: <ul> <li><em>id</em>: specimen identifier</li> <li><em>URL</em>: URL of the scan</li> <li><em>genus</em>: genus of the specimen</li> <li><em>phenophase</em>: integer from 1 to 9 describing the phenophase of the specimen</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em> and <em>test</em></li> </ul> </li> </ul> <p> </p> <p><strong>Additional ressources</strong></p> <p>More information can be found in the related paper:<br> <em>Lorieul, T., K. D. Pearson, E. R. Ellwood, H. Goëau, J.-F. Molino, P. W. Sweeney, J. M. Yost, J. Sachs, E. Mata-Montero, G. Nelson, P. S. Soltis, P. Bonnet, and A. Joly. 2019. Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras. Applications in Plant Sciences 7(3): e1233.</em></p> <p>For an example of usage of these datasets as well as a baseline, see: <a href="http://doi.org/10.5281/zenodo.2549996">http://doi.org/10.5281/zenodo.2549996</a></p> <p> </p>
Figure 11 in Immature stages, phenology, distribution and host plants of the Andean Moon Moth Cercophana frauenfeldii Felder, 1862 (Lepidoptera: Saturniidae)
Figure 11 Larvae of C. frauenfeldii occurring on two host plants. (A) Last instar larva feeding on Cryptocarya alba (peumo). (B) Second instar larva feeding on Gomortega keule (queule) leaves.
Figure 7 in Immature stages, phenology, distribution and host plants of the Andean Moon Moth Cercophana frauenfeldii Felder, 1862 (Lepidoptera: Saturniidae)
Figure 7 Cercophana frauenfeldii cocoon.(A) Collected from rocky substrate at Laguna Torca National Reserve, Vichuquén, Chile.(B-D) Cocoons from larvae reared at the laboratory. (E-F) Details of the silk thread arrangement in the cocoon.
Figure 2 in Immature stages, phenology, distribution and host plants of the Andean Moon Moth Cercophana frauenfeldii Felder, 1862 (Lepidoptera: Saturniidae)
Figure 2 Cercophana frauenfeldii larva head. (A) Trisegmented Antenna (TrA); (B) Details of the mouthparts, Labrum (Lb) and Mandibles (Man). (C) Hypopharyngeal complex, showing Maxillary Palpi (MaP) and Spinneret (Spn); and (D) Stemmata (Ste) arrangement.
Fig. 1 in Phenological stages of a soybean crop affect the number of mating pairs and egg load in Rhyssomatus nigerrimus (Coleoptera: Curculionidae) females under natural conditions
Fig. 1. Effect of soybean crop phenological stages on matings per linear meter of Rhyssomatus nigerrimus pairs.Estimated values are 95% confidence intervals ±SE.
Fig. 2 in Phenological stages of a soybean crop affect the number of mating pairs and egg load in Rhyssomatus nigerrimus (Coleoptera: Curculionidae) females under natural conditions
Fig. 2. Effect of time of day on matings per linear meter of Rhyssomatus nigerrimus copulating in the R7 phenological stage in a soybean crop. Estimated values are 95% confidence intervals ±SE.
Fig. 3 in Effect of forest microhabitat and larval stage on overwintering survival, development, and phenology of Spathius galinae (Hymenoptera: Braconidae), biological control agent of emerald ash borer, Agrilus planipennis (Coleoptera: Buprestidae)
Fig. 3. Proportion of dead (A) and diapaused (B) Spathius galinae by stage at time of deployment, and overwintering microhabitat. Fate was determined by dis- secting all logs once emergence was complete. Letters of the same type and case within the same subfigure indicate significance when data are considered by stage alone (P <0.05).
Fig. 2 in Effect of forest microhabitat and larval stage on overwintering survival, development, and phenology of Spathius galinae (Hymenoptera: Braconidae), biological control agent of emerald ash borer, Agrilus planipennis (Coleoptera: Buprestidae)
Fig. 2. Deployment jar for logs containing emerald ash borer larvae parasitized by Spathius galinae. Logs were inserted in floral foam in 3.8 L polyethylene terephthalate jar with 2 mesh cutouts for ventilation and excess water drain- age. The jar was attached to the tree by resting the bottom of the jar on 2 nails hammered into the tree while a length of wire wrapped around the 2 nails on either side of the jar. Another wire looped around the neck of the jar and was fastened to the nail at the top. Water was added to the jars as needed to ensure adequate hydration of the logs and larvae.
Fig. 1. Experimental microhabitats near the USDA-ARS Louis A in Effect of forest microhabitat and larval stage on overwintering survival, development, and phenology of Spathius galinae (Hymenoptera: Braconidae), biological control agent of emerald ash borer, Agrilus planipennis (Coleoptera: Buprestidae)
Fig. 1. Experimental microhabitats near the USDA-ARS Louis A. Stearns Laboratory in Newark, Delaware, USA. Letters indicate habitat type and approximate experiment locations: (A) mature forest, a larger, more mature wooded area; (B) urban forest, small, highly disturbed woodlot.
Fig. 4 in Effect of forest microhabitat and larval stage on overwintering survival, development, and phenology of Spathius galinae (Hymenoptera: Braconidae), biological control agent of emerald ash borer, Agrilus planipennis (Coleoptera: Buprestidae)
Fig. 4. Survival analysis of Spathius galinae emergence from urban (A) and mature forest (B) sites over time by stage at time of deployment.
Tracking phenological distributions and interaction potential across life stages
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Phenological stages of deciduous plants were observed at a long term experimental moist acidic tussock tundra site, Arctic LTER 1996 Toolik Lake, AK.
Phenological stages of deciduous plants were observed at a long term experimental moist acidic tussock tundra site (Arctic LTER) near Toolik Field Station, AK. Also, ITEX maximum growth measurements were recorded on August 19th (moist tussock tundra). Experimental treatments at each site included factorial NxP, greenhouse and shadehouse and were begun in 1989. See 96gspheg.html and 96gsphsg. html for phenological data on evergreen and sedge species.
Phenological stages of evergeen plants were observed at a long term experimental moist tussock tundra site (Arctic LTER) 1996 near Toolik Lake, AK.
Phenological stages of evergeen plants were observed at a long term experimental moist acidic tussock tundra (Arctic LTER) in 1996 near Toolik Lake, AK. Also, ITEX maximum growth measurements were recorded on August 19th (moist tussock tundra). Experimental treatments at each site included factorial NxP, greenhouse and shadehouse and were begun in 1989. See 96gsphdc and 96gsphsg for phenological data on deciduous and sedge species.
Phenological stages of sedges were observed at a long term experimental moist tussock tundra site and a long-term experimental wet sedge tundra sites (Arctic LTER) for 1996 near Toolik Lake, AK.
Phenological stages of sedges were observed at a long term experimental moist tussock tundra site and a long-term experimental wet sedge tundra sites near Toolik Lake, AK. Also, ITEX maximum growth measurements were recorded on August 19th (moist tussock tundra). Experimental treatments at each site included factorial NxP, greenhouse and shadehouse and were begun in 1989. See 96gsphdc.html and 96gsphsg.html for phenological data on deciduous and evergeen species.
Local reflects global: Life-stage dependent changes in the phenology of coastal habitat use by North Sea herring
<p>Climate warming is affecting the suitability and utilisation of coastal habitats by marine fishes around the world. Phenological changes are an important indicator of population responses to climate-induced changes but remain difficult to detect in marine fish populations. The design of large-scale monitoring surveys does not allow fine-grained temporal inference of population responses, while the responses of ecologically and economically important species groups such as small pelagic fish are particularly sensitive to temporal resolution. Here, we use the longest, highest-resolution time series of species composition and abundance of marine fishes in northern Europe to detect possible phenological shifts in the small pelagic North Sea herring. We detect a clear forward temporal shift in the phenology of nearshore habitat use by small juvenile North Sea herring. This forward shift can best be explained by changes in water temperatures in the North Sea. We find that reducing the temporal resolution of our data to reflect the resolution typical of larger surveys makes it difficult to detect phenological shifts and drastically reduces the effect sizes of environmental covariates such as seawater temperature. Our study therefore shows how local, long-term, high-resolution time series of fish catches are essential to understand the general phenological responses of marine fishes to climate warming and to define ecological indicators of system-level changes.</p>
The niche through time: Considering phenology and demographic stages in plant distribution models
<p>Species distribution models (SDMs) are widely used to infer species-environment relationships, predict spatial distributions, and characterise species' environmental niches. While the importance of space and spatial scales is widely acknowledged in SDM applications, temporal components of the niche are rarely addressed. We discuss how phenology and demographic stages affect model inference in plant SDMs. Ignoring conspicuousness and timing of phenological stages may bias niche estimates through increased observer bias, while ignoring stand age may bias niche estimates through temporal mismatches with environmental variables, especially during times of rapid global warming. We present different methods to consider phenology and demographic stages in plant SDMs, including the selection of causal, spatiotemporally explicit predictors, and the calibration of stage-specific SDMs. Based on a case study with citizen science data, we illustrate how spatiotemporal SDMs provide deeper insights on the coincidence of range and phenological shifts under climate change. The proliferation of digitally available biodiversity and citizen science data increasingly allows considering time explicitly in SDMs. This offers a more mechanistic understanding of plant distributions, and more robust predictions under global change, especially if the reporting of phenological stages and age is facilitated and promoted by relevant data portals.</p>
Local reflects global: Life-stage dependent changes in the phenology of coastal habitat use by North Sea herring
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Drivers of phenological transitions in the seedling life stage
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The niche through time: Considering phenology and demographic stages in plant distribution models
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