We're hoping these results can help identify geographic regions of highest priority for targeted forest management and raise alarm bells for these previously unidentified species that may be exposed to greatest risk.
Histogram showing species with highest predicted exposure to high severity fire, with the flammulated owl being the most exposed species.
We also identified species predicted to have greatest exposure to high severity fire (in the western US) across their global range, including some fire-loving species (White-headed Woodpecker, Mountain Quail) and fire-prone species (Flammulated Owl, Brown-capped Rosy-finch).
Bar plots showing how avian hotspots are distributed across predicted low and high severity fire.
We found ~30% of hotspots are expected to burn at high severity, and of those hotspots the majority were historically exposed to predominantly low severity regimes, indicating a significant mismatch between what the resident biodiversity is adapted to and what it may be exposed to in the future.
A series of maps of the western US showing where different aspects of avian diversity intersect with fire severity types.
Using eBird data products and forecasted fire severity we identified hotspots of bird species richness, functional richness, and community uniqueness and classified them into "areas of concern" or "refugia" based on whether they're predicted to burn at high or low severity.
Really proud of my paper with @ecologyofgavin.bsky.social, @grumpyunclesean.bsky.social, Andrew Stillman, and Courtney Davis out now in @natcomms.nature.com, which looks at the forecasted exposure of bird biodiversity to high severity fire in the western US. www.nature.com/articles/s41...
This is a real tour de force by Maria Isabel. This paper is, put together, a whole century of CPU time done with the help of Calcul Québec. We will also be moving some of the outputs to BON-in-a-Box, @geobon.org cloud-based tool to facilitate the reporting of biodiversity indicators.
We're hiring a full-time research software engineer for biodiversity & bioacoustics!
Position offers a strong research component with independence + research pub opportunities and real-world impact.
expected salary range $111K - $116K.
dse.berkeley.edu/news/were-hi...
Thought our experience earlier this year receiving 8 reviews, some of which were for the wrong paper, was a bizarre one-off. Apparently not!
Yes, a great time was had by all 👍👍👍
I’m recruiting a PhD and MSC student for fall 2026 working on the movement ecology and conservation of Mexican spotted owls in SW forests and rocky canyonlands. Exciting partnership with Los Alamos National Laboratory. Great vibrant lab group, high impact research! 🦉
gavinmjones.com/opportunities/
With all the conversation surrounding the environmental impact of AI, we decided to give our two cents on what it all means for ecologists! esajournals.onlinelibrary.wiley.com/doi/10.1002/...
Most major theories in ecology assume some sort of equilibrium, but only ~half of empirical tests acknowledge it & even fewer observed it in their system. Does this matter? How did the idea become so pervasive in ecology anyway? Find out in our new paper! onlinelibrary.wiley.com/doi/10.1111/...
Really excited to have been a part of this one! Hopefully sparks some conversation about what exactly we want our protected areas to *do*.
Shameless plug for my recent paper looking at this via functional traits - we found interesting local changes in functional structure but no general trends! onlinelibrary.wiley.com/doi/10.1111/...
Some postdoc work up now up as a preprint! ecoevorxiv.org/repository/v... Choosing sites for monitoring biodiversity is critical for robust inference - so which algorithm should you use to pick sites? We found similar performance for algos and outline the features that might influence your decision.
Two directed acyclic graphs showing causal relationships. The first shows a simple relationship between the presence of rare plant species (x), illustrated with icons of individual plants, and grassland productivity (y), illustrated with icons of grasses. There is an arrow going from x to y. The second shows the same relationship, but this time with omitted variables (u). The omitted variables include observed omitted variables (like precipitation) and unobserved omitted variables (like legacies of agricultural activity). These are illustrated with an icon of a rain cloud, a fence, and a shovel. There are dashed arrows going from the omitted variables to both x and y.
New paper from me + @lauradee.bsky.social on using causal inference methods and concepts in ecology! onlinelibrary.wiley.com/doi/10.1111/... (1/5)
I'd love to be added!
tl;dr: big changes can happen in the functional space even when species-based metrics look otherwise stable through time, and on the flip side, losses/gains of species or changes in species identity can have little to no impact on the functional space
Please dm me for a pdf if you're paywalled!
We also found that individual studies fell into four general groups: no change in species or functional metrics, functional diversity change independent of species change, loss of functional redundancy, and increasing species richness.
We found no trend across communities in functional richness, evenness, or divergence - in line with other species-based work. This also held true for almost all models of the means of individual trait axes.
My inaugural post is for my paper recently out in GEB! A contribution to the conversation around local biodiversity change, we reconstructed thousands of functional diversity time series to assess shifts in functional structure for bird & mammal communities. onlinelibrary.wiley.com/doi/10.1111/...
