Sönke Twietmeyer
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Sönke Twietmeyer
@soenketwietmeyer.bsky.social
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Reposted by Sönke Twietmeyer
bfn-de.bsky.social
Gemeinsam mit dem @rote-liste-zentrum.bsky.social haben wir die neue Rote Liste der #Raubfliegen Deutschlands veröffentlicht. Das Ergebnis ist alarmierend: Jede zweite Art ist bestandsgefährdet oder ausgestorben❗️
www.bfn.de/pressemittei...
#RoteListe #Biodiversität #Naturschutz #CitizenScience
Die Große Wolfsfliege (Dasypogon diadema) ist eine Raubfliegenart, die regelmäßig Wespen und andere Hautflügler erbeutet. (Foto: Tommy Kästner)
December 3, 2025 at 11:04 AM
Reposted by Sönke Twietmeyer
wild-ecol-cons.bsky.social
Important new paper on #wildcat vehicle collisions!🐈

A use-availability model mapped collision risk across Germany's roads, showing that existing mitigation measures are well placed, but more roads require intervention to support wildcat populations.🚗

📖 Read more here: doi.org/10.1016/j.je...
Graphical Abstract of paper. Abstract: Roads are a major driver of habitat fragmentation, creating mosaic-structured landscapes where some species can adapt, and others struggle to survive. In increasingly fragmented landscapes, highly mobile species, including mammalian carnivores, are frequently exposed to roads as they move between habitat patches to access resources such as shelter and prey. However, understanding the factors influencing carnivores' road mortality in human-modified landscapes remains limited, partly due to a lack of data at broad spatial scales. Yet, the European wildcat (Felis silvestris) serves as an ideal model species to examine carnivore-vehicle collision risk across diverse environmental conditions, as it occupies large home ranges in diverse habitats. We conducted the first national-scale assessment of wildcat-vehicle collisions, applying a use-availability framework to 827 recorded collisions across Germany. Our study reveals a complex interplay of factors influencing wildcat road mortality in heavily fragmented and heterogeneous landscapes. The highest collision risk occurred on roads with intermediate to high expected traffic volumes, posted speed, and widths. Collision risk was higher in favourable habitats characterised by minimal built-up areas and low road density. The risk peaked in areas with moderate to dense tree cover and increased with higher habitat diversity, corresponding to areas where both refuge and hunting grounds occur. Using our model, we mapped wildcat-vehicle collision risk across Germany's road network, validating that existing mitigation measures are well placed and highlighting road sections where further intervention is needed to support the persistence of wildcat populations.
December 1, 2025 at 5:22 PM
Reposted by Sönke Twietmeyer
wild-ecol-cons.bsky.social
Our new research demonstrates how AI can reduce the time needed for classification of camera trap images. 📸

Using deep learning, automated analysis achieves 90% accuracy in identifying European wildlife, streamlining population monitoring across Germany. 🦊🐗

📜Read more: doi.org/10.1002/rse2...
Camera traps and deep learning enable efficient large‐scale density estimation of wildlife in temperate forest ecosystems
We tested the effect of using a readily available deep learning algorithm for animal species classification on the population density estimates of eight wild mammal species in 10 protected areas (Da)...
doi.org
September 11, 2025 at 2:08 PM
Reposted by Sönke Twietmeyer
mpi-animalbehav.bsky.social
Hey Camera Trappers 📸🐺🐗🦌🦅Snapshot Europe is back for 2025!
Join us in deploying cameras this Sept-Oct. Help build a crucial snapshot of European biodiversity. Learn more & express interest here ▶️ app.wildlifeinsights.org/initiatives/...
Spread the word and help expand our community across Europe🙏
Alpine ibex (Capra ibex) captured in Stelvio National Park, Italy
July 8, 2025 at 1:10 PM