Pavon-Jordan, D. | Search bioRxiv

bioRxiv2025

Vulnerability and adaptations to climate change in EU protected areas: a Natura 2000 managers' perspective

The Natura 2000 (N2K) network is a key conservation instrument in the European Union, but its effectiveness is challenged by climate change. We surveyed 382 N2K managers to investigate their perceptions of climate change and related site adaptation strategies. Warming and precipitation shifts were frequently perceived as threats, with vulnerability of N2K sites highest in the Mediterranean and lowest in the Boreal region. Our results suggest that the official N2K site information stored in the Standard Data Forms greatly under-report managers assessment of vulnerability. Around half of the surveyed managers implemented adaptation strategies, which, when characterised following a Resist-Accept-Direct framework, aimed not only at resisting, but also at directing and accepting the effects of climate change. Managers also highlighted the need for scientific knowledge on local vulnerability and increased funding to improve the implementation of adaptation strategies inside protected areas.

ecology↗

bioRxiv2023

Snowmobile noise alters bird vocalization patterns during winter and pre-breeding season

Noise pollution poses a significant threat to ecosystems worldwide, disrupting animal communication and causing cascading effects on biodiversity. In this study, we focus on the impact of snowmobile noise on avian vocalizations during the non-breeding winter season, a less-studied area in soundscape ecology. We developed a pipeline relying on deep learning methods to detect snowmobile noise and applied it to a large acoustic monitoring dataset collected in Yellowstone National Park. Our results demonstrate the effectiveness of the snowmobile detection model in identifying snowmobile noise and reveal an association between snowmobile passage and changes in avian vocalization patterns. Snowmobile noise led to a decrease in the frequency of bird vocalizations during mornings and evenings, potentially affecting winter and pre-breeding behaviors such as foraging, predator avoidance and successfully finding a mate. However, we observed a recovery in avian vocalizations after detection of snowmobiles during mornings and afternoons, indicating some resilience to sporadic noise events. These findings emphasize the need to consider noise impacts in the non-breeding season and provide valuable insights for natural resource managers to minimize disturbance and protect critical avian habitats. The deep learning approach presented in this study offers an efficient and accurate means of analyzing large-scale acoustic monitoring data and contributes to a comprehensive understanding of the cumulative impacts of multiple stressors on avian communities. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/548680v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1deda15org.highwire.dtl.DTLVardef@1bfa2e4org.highwire.dtl.DTLVardef@5f2cc2org.highwire.dtl.DTLVardef@739ecd_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗