Thanks for this solution! I'm getting some great use fitting simple non-linear models to small datasets where the compilation >> sampling time.
18.01.2026 19:06
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Thanks for this solution! I'm getting some great use fitting simple non-linear models to small datasets where the compilation >> sampling time.
Pleased to announce that we are looking for a post-doc to join @wesnerlab.bsky.social to study the relationship between body size, temperature and nutrients in stream ecosystems. Position details can be found here: yourfuture.sdbor.edu/postings/45969
Happy to answer any questions!
One of those is like "I think it's spelled Iraan but it's somewhere roundaboutsch'ere"
The mass loss time series in our data set were better or equivalently fit to 2-3 parameter models compared to the usual 1 parameter negative exponential model that generates k. There's a lot of time-varying breakdown rates to explore and analyze in nature!
Time series showing A) Lagging, B) Constant, and C) Leading decomposition trajectories, with common analytical decomposition model fits to each time series. Panel D) shows the Weibull model fit for every time series in the data set. Negative exponential (constant decay) is equivalent to the Weibull fit when Weibull alpha = 1.
Litter decomposition in streams is usually studied by calculating a breakdown rate, k, which assumes that the rate is constant through time - ever wondered how generally that assumption holds? Just accepted in L&O Letters: www.researchgate.net/publication/...
So exciting to see @freyaolsson.bsky.social's forecast synthesis paper officially published today!
"What can we learn from 100,000 freshwater forecasts? A synthesis from the NEON Ecological Forecasting Challenge"
doi.org/10.1002/eap....
Thanks!
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Howdy. New pub using high frequency dissolved oxygen profiles and machine learning in some southern US reservoirs. with @nicolewagner.bsky.social, Thad Scott, Dennis Trolle, Anders Nielsen, and Jeff Sadler. aslopubs.onlinelibrary.wiley.com/doi/10.1002/...