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2,007 results for “ecological species”
Data from: Seasonal and annual differences in the foraging ecology of two gull species breeding in sympatry and their use of fishery discards
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Data from: Ecological strategies in stable and disturbed environments depend on species specialisation
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Data from: Species’ ecological functionality alters the outcome of fish stocking success predicted by a food-web model
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Data from: Genomic data detect corresponding signatures of population size change on an ecological time scale in two salamander species
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Data from: Ecological impacts of invasive alien species along temperature gradients: testing the role of environmental matching
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Data from: Laboratory maintenance does not alter ecological and physiological patterns among species: a Drosophila case study
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Data from: Strengths and potential pitfalls of hay-transfer for ecological restoration revealed by RAD-seq analysis in floodplain Arabis species
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Data from: Post-fledging behavioral ecology of migratory songbirds: How do fledgling activity rates vary across species?
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Data from: Ecological traps for large-scale invasive species control: predicting settling rules by recolonising American mink post-culling
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Links between prey assemblages and poison frog toxins: a landscape ecology approach to assess how biotic interactions affect species phenotypes
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Data-driven identification of reliable sensor species to predict regime shifts in ecological networks
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Transcriptome analyses during fruiting body formation in Fusarium graminearum and Fusarium verticillioides reflect species life history and ecology
GEO Series GSE61865. Fusarium graminearum; Fusarium verticillioides. 12 samples. Type: Expression profiling by high throughput sequencing.
Widespread and adaptive alterations in genome-wide gene expression associated with ecological divergence of two Oryza species
GEO Series GSE71044. Oryza rufipogon; Oryza nivara. 42 samples. Type: Expression profiling by high throughput sequencing.
Figure 8 from: Ossowska E, Guzow-Krzemińska B, Kolanowska M, Szczepańska K, Kukwa M (2019) Morphology and secondary chemistry in species recognition of Parmelia omphalodes group – evidence from molecular data with notes on the ecological niche modelling and genetic variability of photobionts. MycoKeys 61: 39-74. https://doi.org/10.3897/mycokeys.61.38175
Figure 8 Distribution of suitable niches of P. omphalodes (A) and P. pinnatifida (B) in America.
FIG. 7 in The genus Navicordulia Machado & Costa, 1995 (Insecta, Odonata, Corduliidae s.str.): new species, identification key for males and data on ecology and distribution
FIG. 7. — Rock-bottomed stream near locus typicus, Barruol Mounts. Photo by Stéphane Brûlé.
Figure 1 from: Souza RCR, Pompeu PS (2020) Ecological separation by ecomorphology and swimming performance between two congeneric fish species. Zoologia 37: 1-8. https://doi.org/10.3897/zoologia.37.e47223
Figure 1 Experimental apparatus of swimming capacity showing the test region and flow direction.
Data from: Machine learning to classify animal species in camera trap images: applications in ecology
Motion‐activated cameras ("camera traps") are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses. We trained machine learning models using convolutional neural networks with the ResNet‐18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out‐of‐sample (or "out‐of‐distribution" in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out‐of‐sample dataset from Tanzania, containing a faunal community that was novel to the model. The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out‐of‐sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies. The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non‐invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our r package makes these methods accessible to ecologists.
Figure 3 from: Gutermann W, Jang T-S, Kästner A, Prehsler D, Reich D, Berger A, Flatscher R, Gilli C, Hofbauer M, Lachmayer M, Sander R, Sonnleitner M, Mucina L (2024) Thliphthisa sapphus (Rubiaceae, Rubieae), a new species from Lefkada (Ionian Islands, Greece) and its ecological position. PhytoKeys 241: 65-79. https://doi.org/10.3897/phytokeys.241.119144
Figure 3 Mitotic chromosomes and karyotype of Thliphthisa sapphus (2n = 4x = 44). Scale bar: 5 μm.
Figure 1 from: Liu S, Xu T-M, Song C-G, Zhao C-L, Wu D-M, Cui B-K (2022) Species diversity, molecular phylogeny and ecological habits of Cyanosporus (Polyporales, Basidiomycota) with an emphasis on Chinese collections. MycoKeys 86: 19-46. https://doi.org/10.3897/mycokeys.86.78305
Figure 1 The geographical locations of the Cyanosporus species distributed in China.
Figure 10 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 10 Amphilochus hamatus. Mouthparts. IINH37894. Scale bars: 0.1 mm.
ScienceDex guides
Understand access before you commit
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)
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.