@rebeccalovell.bsky.social
Quantitative evolutionary ecologist 👩💻🐦🦋🌿 Currently a Postdoc at the University of Aberdeen (she/her)
Are you involved in ecological forecasting or prediction in Europe?
We’re mapping forecasting applications across the continent — from SDMs to observatories with predictive potential.
Submit here 👉 euro-ecoforecast.wordpress.com/forecasting-...
#EcologicalForecasting #EEFI #OpenScience
New paper out on the dangers of using patterns across spatial climate gradients to predict what will happen with changing climate. That includes species distribution modeling. Space-for-time substitution can be misleading in sign, not just the magnitude of effects.
www.nature.com/articles/s41...
Visual representation of common garden procedure.
Our common garden experiment with urban and forest great tits is out early view in Evolution! doi.org/10.1093/evol... @denisreale.bsky.social @annecharmantier.bsky.social
25.02.2025 11:11 — 👍 57 🔁 28 💬 1 📌 1Our results suggest that the reliability of space-for-time projections can be very context-dependent, even for a single species 🦋
But, we also show how spatiotemporal datasets provide an opportunity to test the key assumptions of causality and space-for-time transferability that underlie many SDMs.
Figure depicting spatial and temporal temperature-abundance and temperature-occuancy relationships for the orange tip butterfly in the UK, and the difference between these spatial and temporal slopes across the orange tip's range. Temperature generally has a positive effect on abundance and probability of presence in both space and time. Spatial and temporal temperature-occuapncy slopes are significantly different below 19.7°C, with the slope in time shallower than the slope in space. The slopes do not differ above 19.7°C, where both spatial and temporal slopes flatten. Temperature-abundance slopes do not differ at lower temperatures, but do differ above 16.4°C, where the temporal slope becomes increasingly shallower than the spatial slope.
We found that the level of equivalence between spatial and temporal temperature-distribution relationships varies across different temperatures within the species’ range 🌡️, with patterns differing between occupancy vs abundance 🦋
28.02.2025 16:20 — 👍 0 🔁 0 💬 1 📌 0We then apply a statistical approach that allows comparison of the spatial and temporal effects of temperature on two distribution metrics – occupancy (presence/absence) and abundance 🦋
28.02.2025 16:20 — 👍 0 🔁 0 💬 1 📌 0
Figure depicting the orange tip butterfly's lifecycle and the AICs of models including different temperature windows as predictors of orange tip abundance. A seasonal pattern in AICs is depicted, with models including temperatures in May-July of the previous year having the lowest AICs. This corresponds to a period where the Orange-tip adults, eggs and larvae are all present.
Using @ukbms.bsky.social records of the Orange-tip butterfly’s abundance in the UK, we first apply a sliding window approach to identify when in the year temperature is most predictive of abundance🌡️🦋…
28.02.2025 16:20 — 👍 0 🔁 0 💬 1 📌 0
Conceptual figure depicting possible patterns of spatial and temporal climate-distribution relationships that may be seen across a species' range. Spatial relationships are hump-shaped, with temporal relationships as local deviations from this curve. In some instances, spatial and temporal slopes are similar, meaning that a space-for-time substitution would be valid. In other instances, these slopes are in the same direction, but the response in time is shallower, consistant with a lagging response in time. Here, space-for-time substitution may be valid in the long-term. In some cases, the response in time is flat, or the spatial and temporal slopes are in opposite directions, suggesting that the climate variable is not having a causal effect. The level of similarity between spatial and temporal slopes may vary across a species' climate range.
Projecting species’ future distributions often involves ‘space-for-time substitutions’ where relationships between climate variables & species’ distributions are identified in space & then projected over time 🌍→⏰
This assumes that these relationships are causal & equivalent in space and time 🌍=⏰?
🦋 New paper out in @funecology.bsky.social! 🦋
Using the Orange-tip butterfly in the UK🦋, we test a key assumption of many species’ distribution models (SDMs): that climate effects on species’ distributions are equivalent over space🌍 versus time⏰
doi.org/10.1111/1365-2435.70005
🧵👇
Me with my viva cake. The cake has an Orange-tip butterfly and the words "Dr Becca" on it.
A printed copy of my thesis titled "Climate impacts on species’ distributions in space and time"
Very excited to say that earlier this month I passed my PhD viva! 🦋👩💻
Thanks to @lancasterlt.bsky.social and Jarrod Hadfield for a really interesting discussion, and of course to @allyphillimore.bsky.social for being the most wonderful supervisor! #PhDone
Alex Reiss giving a talk titled 'Repeated host shifting in the global radiation of gallwasps'
Another awesome talk from the group from Alex Reiss 🐝 #BES2024
12.12.2024 10:27 — 👍 1 🔁 0 💬 0 📌 0
Ilaria Lonero giving a talk on 'Incubation thermal niche and niche tracking in temperate passerine'
Megan Stamp giving a talk on the drivers of caterpillar community composition, in front of a slide introducing the Phenoweb transect.
Fantastic talks from my lab mates @ilarialonero.bsky.social and Megan Stamp 🐦🐛 #BES2024
11.12.2024 12:33 — 👍 11 🔁 1 💬 1 📌 0Excited to present my PhD research at #BES2024 today! 🌾Join me at 16:00 in Auditorium 1C as I dive into how species turnover and intraspecific trait plasticity shape grass community responses to grazing. See you there!
11.12.2024 09:05 — 👍 12 🔁 3 💬 0 📌 0
