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📢 #NewStudy in @thelancet #PlanetaryHealth by Wan, Gampe & Hajat, investigating an often-underrepresented factor in #ClimateHealth research: 𝗮𝗲𝗿𝗼𝘀𝗼𝗹𝘀 - tiny particles in the atmosphere that reflect sunlight & may have a net cooling effect 🌡️

🗝️-𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
💡 Aerosol-driven cooling masked hundreds of heat-related deaths in the 20th century
💡 Mid-range emissions scenario: heat-related deaths could rise 2–6× by 2100.

🔗 sciencedirect.com/science/arti

#outnow #newpaper science #geo #health #climatechange

#NewPaper out: Anne Reichmuth , Kühn I, Schmidt A, Doktor D (2025) Forested Natura 2000 sites under climate change: effects of tree species distribution shifts. Web Ecology 25: 59–89.

We have modelled and analysed the effect of possible tree species distribution shift in Norway spruce (Picea abies), European beech (Fagus sylvatica), and two oak species (Quercus petraea and Quercus robur), considered jointly on forested Natura 2000 sites, an EU-wide conservation area network. The modelling procedure was performed using 3 to 4 bio-climatic variables derived from 26 variables of the EURO-CORDEX Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations for the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 until 2098. Our results reveal a severe decline in Picea within Natura 2000 sites in central Europe and lower elevations and confirm a strong shift towards higher elevations and latitudes. This amounts to an 18 % absolute mean change (−18 % mean loss, 15 % mean gain). Quercus sp. reveal similar results, with 23 % absolute mean change (−23 % loss, 24 % gain) at Natura 2000 sites, whereas Fagus remains stable throughout the model results with 8 % absolute mean change (−7 % loss, 9 % gain). As ecosystems of any type are highly dynamic, climate change can lead to additional severe pressure on statically defined conservation goals and associated management activities.

doi.org/10.5194/we-25-59-2025

doi.orgForested Natura 2000 sites under climate change: effects of tree species distribution shiftsAbstract. Climate change can have severe impacts on tree species distributions. Models consistently show that tree species will follow climate towards higher elevations and latitudes. This has various effects on forest ecosystems. Forests have a slow dynamic compared to other ecosystems and are affected severely by tree species distribution shifts. Forested conservation areas with limited management reveal a slow adaptation process to a changing climate. In this study, we have modelled and analysed the effect of possible tree species distribution shift in Norway spruce (Picea abies), European beech (Fagus sylvatica), and two oak species (Quercus petraea and Quercus robur), considered jointly on forested Natura 2000 sites, an EU-wide conservation area network. The modelling procedure was performed using 3 to 4 bio-climatic variables derived from 26 variables of the EURO-CORDEX Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations for the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 until 2098. Our results reveal a severe decline in Picea within Natura 2000 sites in central Europe and lower elevations and confirm a strong shift towards higher elevations and latitudes. This amounts to an 18 % absolute mean change (−18 % mean loss, 15 % mean gain). Quercus sp. reveal similar results, with 23 % absolute mean change (−23 % loss, 24 % gain) at Natura 2000 sites, whereas Fagus remains stable throughout the model results with 8 % absolute mean change (−7 % loss, 9 % gain). The best model algorithms for all species were the generalised additive models (GAMs). As ecosystems of any type are highly dynamic, climate change can lead to additional severe pressure on statically defined conservation goals and associated management activities.

#NewPaper out

Maria Milanović et al. (2025) Successful alien plant species exhibit functional dissimilarity from natives under varied climatic conditions but not under increased nutrient availability. Journal of Vegetation Science 36: e70032. doi.org/10.1111/jvs.70032

Alien and native species increasing in their abundance did not differ in their leaf traits. We found significantly lower specific leaf area (SLA) with an increase in mean annual temperature and lower leaf Potassium with mean annual precipitation. For trait–environment relationships, when compared to native species, successful aliens exhibited an increase in leaf Phosphorus and a decrease in leaf Potassium with an increase in mean annual precipitation. Finally, aliens' SLA decreased in plots with higher mean annual temperatures.

#NewPublication #biodiversity #ecology #alienSpecies #functionalTraits #NutNet
#xp

#newPaper out with colleagues from UFZ, Environmental Agency Austria and Research Centre Jülich. We analysed in which regions of Europe the sites of the new eLTER infrastructure are underrepresented and how to adapt this to current and future environmental conditions simultaneously:

Ohnemus et al. (2025): Fitness for future: eLTER RI’s representation of climate and land use change. Ecol. Indic. 171 , art. 113159

doi.org/10.1016/j.ecolind.2025

#eLTER #LTER #newPublication
#xp

🌊 📄 #NewPaper by Jiachang Tu, Andrea Reimuth et al.! They developed indices for household vulnerability & #flood exposure in Ho Chi Minh City, revealing spatial patterns of #vulnerability.

🌧️ Ho Chi Minh City is flood-prone due to rapid #urbanization & #climatechange.

🗝️ #KeyFindings: social factors (e.g. health & housing) affect vulnerability more than flood experience; urban households face greater risks & independent adaptation measures are common.

🔗 sciencedirect.com/science/arti

Our new #OpenScience paper is out in Scientific Reports today! My coauthors and I jokingly called it "the masterpiece" because it wraps up a research line I began during my PhD ... 10 years ago! Here's a quick thread on the backstory and what we found. [1/X]
nature.com/articles/s41598-024 @psycholinguistics @psycholinguistic #psycholinguistics #psycholinguistique #phonetic #phonetics #NewPaper #NewArticle #ScienceMastodon

NatureMapping the spectrotemporal regions influencing perception of French stop consonants in noise - Scientific ReportsUnderstanding how speech sounds are decoded into linguistic units has been a central research challenge over the last century. This study follows a reverse-correlation approach to reveal the acoustic cues listeners use to categorize French stop consonants in noise. Compared to previous methods, this approach ensures an unprecedented level of detail with only minimal theoretical assumptions. Thirty-two participants performed a speech-in-noise discrimination task based on natural /aCa/ utterances, with C = /b/, /d/, /g/, /p/, /t/, or /k/. The trial-by-trial analysis of their confusions enabled us to map the spectrotemporal information they relied on for their decisions. In place-of-articulation contrasts, the results confirmed the critical role of formant consonant-vowel transitions, used by all participants, and, to a lesser extent, vowel-consonant transitions and high-frequency release bursts. Similarly, for voicing contrasts, we validated the prominent role of the voicing bar cue, with some participants also using formant transitions and burst cues. This approach revealed that most listeners use a combination of several cues for each task, with significant variability within the participant group. These insights shed new light on decades-old debates regarding the relative importance of cues for phoneme perception and suggest that research on acoustic cues should not overlook individual variability in speech perception.
ZenodoIntegrating Large Language Models in Political Discourse Studies on Social Media: Challenges of Validating an LLMs-in-the-loop PipelineThe integration of Large Language Models (LLMs) into research workflows has the potential to transform the study of political content on social media. This essay discusses a validation protocol addressing three key aspects of LLM-integrated research: the versatility of LLMs as general-purpose models, the granularity and nuance in LLM-uncovered narratives, and the limitations of human assessment capabilities. The protocol includes phases for fine-tuning and validating a binary political classifier, evaluating cluster coherence, and assessing machine-generated cluster label accuracy. We applied this protocol to validate an LLMs-in-the-loop research pipeline designed to analyze political content on Facebook during the Italian general elections of 2018 and 2022. Our approach classifies political links, clusters them by similarity, and generates descriptive labels for clusters. This methodology presents unique validation challenges, prompting a reevaluation of accuracy assessment strategies. By sharing our experiences, this essay aims to guide social scientists in employing LLM-based methodologies, highlighting challenges and advancing recommendations for colleagues intending to integrate these tools for political content analysis on social media.

📣 New Paper in @Nature Cities 📣

📄 nature.com/articles/s44284-024

🌊 How do coastal cities adapt to #ClimateChange? Wannewitz et al. (2024) show: There are differences in scope, strategies & actors involved across coastal cities with different income levels.

🏙️ in high income countries: City governments mostly take action for adaptation & implement technical & institutional responses.

🏙️ in middle & low income countries: relying on individuals.

Junxiang Luo, a postdoc in the lab of Hiromasa Takemura, discovered a new perceptual phenomenon occurring in daily life. Partially occluded digital numbers can become perceptually ambiguous, leading to bistable interpretations.

With psychophysical experiments, we were able to evaluate the mechanism behind this phenomenon.

News article: sciencedaily.com/releases/2024

Full paper: jov.arvojournals.org/article.a

#newpaper in the next issue of "Neural Networks" !

"A robust event-driven approach to always-on object recognition"

by @antoine_grimaldi , Victor Boutin, Sio-Hoi Ieng, Ryad Benosman and myself - available #opensource at laurentperrinet.github.io/publ

Main contributions:

  • Builds an adaptive, event-based #neuromorphic pattern recognition architecture inspired by neuroscience and capable of always-on decision, i.e. the decision can be made whenever it is needed - just like most living systems!

In a #newpaper from my group, led by David Nielsen, we incorporated coastal permafrost as a new component of an #EarthSystemModel.

This allowed us to quantify that #coastal #permafrost erosion weakens the Arctic Ocean #CO2 uptake from the atmosphere by 7-14%.

This exerts a positive biogeochemical feedback on #climate, increasing atmospheric CO2 by 1–2 TgC yr−1 per °C of increase in global surface air temperature.

Find out more here👇
nature.com/articles/s41558-024
#ilyinaScience

📝 Just published: Our extensive study of 🤩 face emojis 🤗 : frequencies, emotional ratings, meanings.
🤔 Ever wanted to know the difference between 😄 and 😁 - here it is!
Paper: doi.org/10.3758/s13428-024-024
Face emoji data: tscheffler.github.io/2024-Face
#emojis #linguistics #psychology #study #newPaper

SpringerLinkAffective, semantic, frequency, and descriptive norms for 107 face emojis - Behavior Research MethodsWe introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties.