Inês Silva
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ecoisilva.bsky.social
Inês Silva
@ecoisilva.bsky.social
270 followers 330 following 120 posts
Postdoctoral researcher at CASUS, Germany, studying animal movement and road interactions. Interested in #MovementEcology, #RoadEcology, and #BatConservation.

Developer of the R Shiny application 'movedesign':
https://github.com/ecoisilva/movedesign.
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ecoisilva.bsky.social
This workflow has been fully implemented into the latest version of the #movedesign R Shiny app, making it easy for researchers to test and optimize their animal tracking sampling strategies! The package is now available on CRAN #rstats github.com/ecoisilva/movedesign
Graphical abstract for a manuscript titled "Too few, too many, or just right? Optimizing sample sizes for population-level inferences in animal tracking projects". The workflow has been fully implemented in the movedesign Shiny application and R package, allowing users to easily test sampling strategies and assess the reliability of space-use and movement metrics, ultimately promoting more rigorous and impactful wildlife research and conservation.
August 4, 2025 at 6:33 AM
ecoisilva.bsky.social
We found that researchers should favor sampling parameters (duration or interval, depending on the target) over population sample size to reduce bias. However, a larger sample size is crucial to increase precision and capture high individual variation.
A multi-panel figure shows how relative error (%) in population-level estimates changes with population sample size (m) across different sampling durations (2 months, 4 months, 1 year, 3 years, 9 years) for African buffalo tracking data. The top row displays results without resampling, and the bottom row with resampling. Each panel contains scatter points and error bars for relative error at each sample size, colored by whether the error falls within a ±5% threshold (blue for true, red for false). Shorter durations (left panels) show higher, more negative bias and larger error bars, with many red points, while longer durations (right panels) show reduced bias and more points within the error threshold.
August 4, 2025 at 6:33 AM
ecoisilva.bsky.social
Can I be added? 😄
June 19, 2025 at 1:04 PM
ecoisilva.bsky.social
You have been added 😄
May 19, 2025 at 9:33 PM
ecoisilva.bsky.social
Done 😄
April 23, 2025 at 11:10 AM
ecoisilva.bsky.social
Added 😄
April 23, 2025 at 11:09 AM
ecoisilva.bsky.social
I updated the feed generator, so it should be better now! Let me know if it happens again in the future.
April 23, 2025 at 9:01 AM
ecoisilva.bsky.social
Done! 😄
April 23, 2025 at 8:14 AM