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Title: EDANSA-2019: THE ECOACOUSTIC DATASET FROM ARCTIC NORTH SLOPE ALASKA
The arctic is warming at three times the rate of the global average, affecting the habitat and lifecycles of migratory species that reproduce there, like birds and caribou. Ecoacoustic monitoring can help efficiently track changes in animal phenology and behavior over large areas so that the impacts of climate change on these species can be better understood and potentially mitigated. We introduce here the Ecoacoustic Dataset from Arctic North Slope Alaska (EDANSA-2019), a dataset collected by a network of 100 autonomous recording units covering an area of 9000 square miles over the course of the 2019 summer season on the North Slope of Alaska and neighboring regions. We labeled over 27 hours of this dataset according to 28 tags with enough instances of 9 important environmental classes to train baseline convolutional recognizers. We are releasing this dataset and the corresponding baseline to the community to accelerate the recognition of these sounds and facilitate automated analyses of large-scale ecoacoustic databases. more »« less
We are sharing the Ecoacoustic Dataset from Arctic North Slope Alaska (EDANSA-2019), a dataset with audio samples collected from the area of 9000 square miles throughout the 2019 summer season on the North Slope of Alaska and neighboring regions.
There are over 27 hours of labeled data according to 28 tags with enough instances of 9 important environmental classes to train baseline convolutional recognizers.
Please see the following GitHub page for the accompanying publication, updates about the dataset, and baseline code: https://github.com/speechLabBcCuny/EDANSA-2019
Gibson, Timothy M.; Faehnrich, Karol; Busch, James F.; McClelland, William C.; Schmitz, Mark D.; Strauss, Justin V.(
, Geology)
null
(Ed.)
Abstract Detrital zircon U-Pb geochronology is one of the most common methods used to constrain the provenance of ancient sedimentary systems. Yet, its efficacy for precisely constraining paleogeographic reconstructions is often complicated by geological, analytical, and statistical uncertainties. To test the utility of this technique for reconstructing complex, margin-parallel terrane displacements, we compiled new and previously published U-Pb detrital zircon data (n = 7924; 70 samples) from Neoproterozoic–Cambrian marine sandstone-bearing units across the Porcupine shear zone of northern Yukon and Alaska, which separates the North Slope subterrane of Arctic Alaska from northwestern Laurentia (Yukon block). Contrasting tectonic models for the North Slope subterrane indicate it originated either near its current position as an autochthonous continuation of the Yukon block or from a position adjacent to the northeastern Laurentian margin prior to >1000 km of Paleozoic–Mesozoic translation. Our statistical results demonstrate that zircon U-Pb age distributions from the North Slope subterrane are consistently distinct from the Yukon block, thereby supporting a model of continent-scale strike-slip displacement along the Arctic margin of North America. Further examination of this dataset highlights important pitfalls associated with common methodological approaches using small sample sizes and reveals challenges in relying solely on detrital zircon age spectra for testing models of terranes displaced along the same continental margin from which they originated. Nevertheless, large-n detrital zircon datasets interpreted within a robust geologic framework can be effective for evaluating translation across complex tectonic boundaries.
Habitat connectivity is a key factor influencing species range dynamics. Rapid warming in the Arctic is leading to widespread heterogeneous shrub expansion, but impacts of these habitat changes on range dynamics for large herbivores are not well understood. We use the climate–shrub–moose system of northern Alaska as a case study to examine how shrub habitat will respond to predicted future warming, and how these changes may impact habitat connectivity and the distribution of moose (Alces alces). We used a 19 year moose location dataset, a 568 km transect of field shrub sampling, and forecasted warming scenarios with regional downscaling to map current and projected shrub habitat for moose on the North Slope of Alaska. The tall‐shrub habitat for moose exhibited a dendritic spatial configuration correlated with river corridor networks and mean July temperature. Warming scenarios predict that moose habitat will more than double by 2099. Forecasted warming is predicted to increase the spatial cohesion of the habitat network that diminishes effects of fragmentation, which improves overall habitat quality and likely expands the range of moose. These findings demonstrate how climate change may increase habitat connectivity and alter the distributions of shrub herbivores in the Arctic, including creation of novel communities and ecosystems.
Year-round recordings of bearded seal calls were collected in the northeastern edge of the Chukchi Continental Slope (Alaska, within the Arctic Circle) in 2016–2017, 2018–2019, and 2019–2020. While the underwater vocalizations of bearded seals are often analyzed manually or using automatic detections manually validated, in this article, a detection and classification system (DCS) based on the You Only Look Once Version 5 (YOLOV5) algorithm is proposed. With YOLOV5, the network learns how to detect and classify these marine mammals’ calls using the principle of computer vision for object detection in images where bounding boxes enclose the objects of interest. During training, validation, and testing, YOLOV5 achieved an accuracy of 96.54%, 93.36%, and 93.87%, respectively. The DCS was applied to the three-yearlong dataset, and an analysis of the vocal behavior of the bearded seals showed that there exists a geographical dependence where this species prefers shallower water depths in the Chukchi Continental Slope. Another advantage of using YOLOV5 over other typical DCS is that the predicted bounding boxes have embedded statistical information about the vocalization, such as the duration, bandwidth, and center frequency of the signals. This additional information equips biologists with statistical data that facilitate the analysis of animal vocal behavior.
Curasi, Salvatore R.; Fetcher, Ned; Hewitt, Rebecca E.; Lafleur, Peter M.; Loranty, Michael M.; Mack, Michelle C.; May, Jeremy L.; Myers-Smith, Isla H.; Natali, Susan M.; Oberbauer, Steven F.; et al(
, Environmental Research Letters)
Abstract
Foundation species have disproportionately large impacts on ecosystem structure and function. As a result, future changes to their distribution may be important determinants of ecosystem carbon (C) cycling in a warmer world. We assessed the role of a foundation tussock sedge (Eriophorum vaginatum) as a climatically vulnerable C stock using field data, a machine learning ecological niche model, and an ensemble of terrestrial biosphere models (TBMs). Field data indicated that tussock density has decreased by ∼0.97 tussocks per m2over the past ∼38 years on Alaska’s North Slope from ∼1981 to 2019. This declining trend is concerning because tussocks are a large Arctic C stock, which enhances soil organic layer C stocks by 6.9% on average and represents 745 Tg C across our study area. By 2100, we project that changes in tussock density may decrease the tussock C stock by 41% in regions where tussocks are currently abundant (e.g. −0.8 tussocks per m2and −85 Tg C on the North Slope) and may increase the tussock C stock by 46% in regions where tussocks are currently scarce (e.g. +0.9 tussocks per m2and +81 Tg C on Victoria Island). These climate-induced changes to the tussock C stock were comparable to, but sometimes opposite in sign, to vegetation C stock changes predicted by an ensemble of TBMs. Our results illustrate the important role of tussocks as a foundation species in determining future Arctic C stocks and highlight the need for better representation of this species in TBMs.
Çoban, Enis Berk, Perra, Megan, Pir, Dara, and Mandel, Michael I. EDANSA-2019: THE ECOACOUSTIC DATASET FROM ARCTIC NORTH SLOPE ALASKA. Retrieved from https://par.nsf.gov/biblio/10450599. Workshop on the Detection and Classification of Acoustic Scenes and Events .
Çoban, Enis Berk, Perra, Megan, Pir, Dara, & Mandel, Michael I. EDANSA-2019: THE ECOACOUSTIC DATASET FROM ARCTIC NORTH SLOPE ALASKA. Workshop on the Detection and Classification of Acoustic Scenes and Events, (). Retrieved from https://par.nsf.gov/biblio/10450599.
Çoban, Enis Berk, Perra, Megan, Pir, Dara, and Mandel, Michael I.
"EDANSA-2019: THE ECOACOUSTIC DATASET FROM ARCTIC NORTH SLOPE ALASKA". Workshop on the Detection and Classification of Acoustic Scenes and Events (). Country unknown/Code not available. https://par.nsf.gov/biblio/10450599.
@article{osti_10450599,
place = {Country unknown/Code not available},
title = {EDANSA-2019: THE ECOACOUSTIC DATASET FROM ARCTIC NORTH SLOPE ALASKA},
url = {https://par.nsf.gov/biblio/10450599},
abstractNote = {The arctic is warming at three times the rate of the global average, affecting the habitat and lifecycles of migratory species that reproduce there, like birds and caribou. Ecoacoustic monitoring can help efficiently track changes in animal phenology and behavior over large areas so that the impacts of climate change on these species can be better understood and potentially mitigated. We introduce here the Ecoacoustic Dataset from Arctic North Slope Alaska (EDANSA-2019), a dataset collected by a network of 100 autonomous recording units covering an area of 9000 square miles over the course of the 2019 summer season on the North Slope of Alaska and neighboring regions. We labeled over 27 hours of this dataset according to 28 tags with enough instances of 9 important environmental classes to train baseline convolutional recognizers. We are releasing this dataset and the corresponding baseline to the community to accelerate the recognition of these sounds and facilitate automated analyses of large-scale ecoacoustic databases.},
journal = {Workshop on the Detection and Classification of Acoustic Scenes and Events},
author = {Çoban, Enis Berk and Perra, Megan and Pir, Dara and Mandel, Michael I.},
}
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