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Pangeo for geolocating fish using biologging data

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<p>In biologging, a small device attached to an animal is used to track its behaviour and environment. This data enables biologists to gain a better understanding of its movement, its preferred habitats, and the environmental conditions it needs to thrive, all of which is essential for the future protection of natural resources. For that, it is crucial to have georeferenced data of biological processes, such as fish migration, over a spatial and temporal range.</p><p>Since it is challenging to track fish directly in the water, models have been developed to geolocate fish from the high resolution temperature and pressure time series obtained from the data storage tag. In particular, reconstructing the trajectories of seabass using the temporal temperature changes obtained from biologging devices has been studied since 2010 (https://doi.org/10.1016/j.ecolmodel.2015.10.024). These fish tracks are computed based on the likelihood of the temperature data obtained from the fish tag and reference geoscience data such as satellite observations and ocean physics model output. A high temporal and spatial resolution of the reference data plays a key role in the quality of the fish trajectories. However, the size and accessibility of these data sets as well as the computing power required to process high resolution data remain technical barriers.</p><p>As the Pangeo ecosystem has been developed  to solve such challenges in geoscience, we can take advantage of it in biologging. We use libraries such as intake, kerchunk, and fsspec to quickly load the data, xarray, pint, and dask to compute and hvplot and jupyter to display the results. The pangeo software stack enables us to easily access the data and compute high resolution fish tracks in a scalable and interactive manner. </p>
Title: Pangeo for geolocating fish using biologging data
Description:
<p>In biologging, a small device attached to an animal is used to track its behaviour and environment.
This data enables biologists to gain a better understanding of its movement, its preferred habitats, and the environmental conditions it needs to thrive, all of which is essential for the future protection of natural resources.
For that, it is crucial to have georeferenced data of biological processes, such as fish migration, over a spatial and temporal range.
</p><p>Since it is challenging to track fish directly in the water, models have been developed to geolocate fish from the high resolution temperature and pressure time series obtained from the data storage tag.
In particular, reconstructing the trajectories of seabass using the temporal temperature changes obtained from biologging devices has been studied since 2010 (https://doi.
org/10.
1016/j.
ecolmodel.
2015.
10.
024).
These fish tracks are computed based on the likelihood of the temperature data obtained from the fish tag and reference geoscience data such as satellite observations and ocean physics model output.
A high temporal and spatial resolution of the reference data plays a key role in the quality of the fish trajectories.
However, the size and accessibility of these data sets as well as the computing power required to process high resolution data remain technical barriers.
</p><p>As the Pangeo ecosystem has been developed  to solve such challenges in geoscience, we can take advantage of it in biologging.
We use libraries such as intake, kerchunk, and fsspec to quickly load the data, xarray, pint, and dask to compute and hvplot and jupyter to display the results.
The pangeo software stack enables us to easily access the data and compute high resolution fish tracks in a scalable and interactive manner.
 </p>.

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