Nicolas Lecomte

In bird species with precocial development, i.e. chicks acquire abilities to leave the nest soon after hatching, the nestling period during which parents warm their young in the nest by brooding them is short but critical to breeding success. The duration of the nestling period (DNP) depends on the hatching synchrony of eggs and the speed at which chicks acquire these abilities but may be indirectly affected by parental behaviour and temporal variations in temperature and predation. We assessed the effects of incubation strategy (bi- or uniparental), hatching start time, incubation initiation date and predation risk on the DNP in Arctic-breeding sandpipers. We found that the DNP was longer in biparental species (29.75 ± 8.95 h) compared with uniparental ones (25.82 ± 6.87 h) and was extended in nests where chicks began hatching during the colder ‘night’ hours. No effect of incubation initiation date or predation pressure was found on the DNP. We suggest that parental investment strategies and constraints related to circadian variations in temperature in chicks drive the DNP in Arctic-breeding sandpipers. These results help us better understand how different species may exhibit different behavioural responses during nesting to impending climate change.

Addressing urgent conservation issues, such as the drastic declines of North American migratory birds, requires creative, evidence‐based, efficient, and collaborative approaches. The abundance of over 50% of monitored North American shorebird populations has declined by over 50% since 1980. To address these declines, we developed a partnership of scientists and practitioners called the Shorebird Science and Conservation Collective (hereafter the collective ). The collective was founded to translate the combined findings of shorebird tracking data into on‐the‐ground conservation action. With advice from an advisory group, the collective acts as an intermediary whereby dedicated staff collate and analyze data contributions from scientists to support knowledge requests from conservation practitioners. In its first three years, data contributions from 75 organizations include over 7.1 million shorebird observations forming movement paths of 3420 individuals representing 36 species tracked across the Americas and have informed 18 conservation projects spanning education, land and species management, land conservation, and policy requests. Others engaged in translational science from big data could consider similar knowledge‐sharing models that prioritize usable data products, foster collaborative engagement between science experts and practitioners, build focused communities around topics or taxonomic groups, and employ a proof‐of‐concept phase to develop scalable solutions while making progress toward long‐term funding to sustain impact. As the volume of scientific data continues to grow, intermediaries, such as the collective, can be vital liaisons to rapidly integrate and interpret research to support conservation action. Dedicated to the memory of Shiloh Schulte and his conservation achievements for shorebirds.

Climate-driven phenological mismatches threaten avian reproduction by disrupting food availability during critical breeding stages. In marine ecosystems, time lags between environmental changes and their effects on food webs are challenging to model, yet they can have a profound impact on reproduction at higher trophic levels. We disentangle how oceanic and climatic variability influence the breeding phenology and success of a major predator species in the Southern Ocean, drawing on 24 years of data from 17,000 marked king penguins. We document a 19-day advancement in breeding phenology, alongside increased breeding success (44% in 2000 and 62% in 2023). A sliding-window analysis reveals that sea temperature and primary production in key foraging zones predict both phenology and breeding success, with lags up to several weeks and 2 years, respectively. The amplitude of their recent response, as well as their dependence on multiyear environmental conditions, underscores a potential vulnerability in a context of decreasing environment predictability. However, so far, king penguins appear to be keeping pace with environmental changes and demonstrate a remarkable resilience and important flexibility in the face of variable oceanographic conditions.

The rapid decline of global bird populations demands effective and efficient monitoring approaches, particularly for shorebirds, which are experiencing significant declines in abundance. Most shorebird monitoring programmes rely on visual surveys, but such surveys face significant challenges in remote locations such as the Arctic where high costs and logistical constraints limit survey effort and duration. We compared data collected from visual area search surveys and acoustic autonomous recording units (ARUs) for monitoring shorebird species in two large regions of Alaska's Arctic Coastal Plain in 2022–2023. We deployed ARUs at 130 sites (55 sites in Arctic National Wildlife Refuge [ANWR]; 75 in Teshekpuk Lake Special Area [TLSA]) where visual surveys were also conducted and examined differences in species richness, encounter rates and predicted distributions for 15 shorebird species. ARU surveys resulted in 50% higher species richness than visual surveys in ANWR and 33% higher at TLSA. Species accumulation curves demonstrated that ARUs required fewer plots to detect the maximum number of species. ARU data enabled species distribution modelling for additional species compared to visual data due to higher encounter rates, resulting in differences in predicted high‐use areas. Visual encounter rates were slightly higher for phalaropes than with ARUs in both regions. Additionally, several rare species were detected in the visual surveys but not in the ARU surveys (e.g. Wilson's Snipe, Western Sandpipers). Synthesis and applications . Our findings demonstrate that ARUs can effectively monitor shorebird species presence, offering advantages in temporal coverage and synchronous data collection across large spatial extents. This may be particularly important in remote regions where traditional monitoring approaches are challenging to implement and sustain.

Ecology and artificial intelligence (AI) are becoming increasingly intertwined. Originally, the intersection between the two disciplines was driven by a critical need for AI to help process rapidly growing volumes of ecological data. Early applications primarily entailed applying AI methods to automate relatively basic tasks, such as detecting blank images from camera traps. However, researchers in both disciplines are beginning to recognize the potential for transformative advances when AI is fully integrated into ecological research and conservation practice. This special feature presents research at the cutting edge of the AI–ecology interface, focusing on work that advances the state of both fields beyond proof‐of‐concept to true interdisciplinary insight. The papers in this collection reveal a maturing field that balances technical advancement with ecological relevance. They address both methodological challenges and the critical need for meaningful integration between computer science innovations and fundamental ecological questions. As a whole, this collection demonstrates the potential for AI to enhance both fundamental ecological understanding and applied conservation efforts, as well as to bridge the gap between scientific discovery and policy implementation. The special feature underscores the importance of genuine interdisciplinary collaboration in developing technologies that not only showcase technical prowess, but also address pressing ecological challenges and support evidence‐based decision‐making in biodiversity conservation.

Aim: Many populations of migratory birds are currently declining. Understanding space use throughout the entire annual cycle, as well as migratory connectivity (i.e., geographic linkage of individuals and populations across different stages of the annual cycle), can improve our ability to identify factors driving population declines and influencing extinction risk. The main objectives of our study were to (i) document the space use and phenology of migration during the non‐breeding period and (ii) quantify the degree of migratory connectivity across the range of the American Golden‐Plover ( Pluvialis dominica ) breeding across the North American Arctic. Location: American Golden‐Plovers that breed across their entire breeding range (northern North America) and migrate up to their main wintering site located in South America. Methods: We used archival light‐level geolocators to track the migration. We quantified migratory connectivity based on the non‐breeding range spread of all individuals and the breeding population spread. We used Mantel tests to evaluate whether the relative spatial configuration of the sampled breeding area was preserved on the non‐breeding ground. Results: We identified 13 and 7 stopover sites used during the fall (post‐breeding, southbound) and spring (pre‐breeding, northbound) migrations, respectively, and one main site used during the wintering period. We highlight stopover sites that were previously unknown and show the transatlantic and transpacific routes used by plovers during migration. We found that individuals breeding in proximity tended to be closer to each other during brief and highly limited portions of the non‐breeding period. Broadly, individuals from different breeding populations were well mixed during the wintering period and throughout most of the spring and fall migrations. Main Conclusions: Overall, the migratory connectivity of American Golden‐Plovers is relatively low for most of the non‐breeding period, suggesting that breeding populations separated by large distances should be similarly affected by disturbances and changes encountered at some migratory stopovers and in the wintering area.

Climate change is reshaping Arctic ecosystems, heightening the risk of vector-borne diseases caused by pathogens such as California serogroup (CSG) viruses, including Jamestown Canyon virus (JCV) and Snowshoe Hare virus (SSHV). Despite their emerging public health threat, data on Arctic mosquito populations and CSG virus prevalence remain limited. To address this gap, we conducted a 3-yr mosquito surveillance program at 8 sites across northern Canada and the United States, engaging local community members in mosquito collection through a standardized protocol using a butterfly net. From 4,038 sampled mosquitoes, we identified 18 species—17 of which were from the genus Aedes Meigen, 1818. We also reported new distribution records for Aedes euedes Howard, Dyar, & Knab, 1913, Aedes implicatus Vockeroth, 1954, and Aedes spencerii (Theobald, 1901). JCV was detected in 10 mosquito species across 7 sites, while SSHV was detected in just one species at a single site. Notably, JCV was found in Ae. euedes, Aedes impiger (Walker, 1948), and Aedes pionips Dyar, 1919 for the first time in North America. JCV was detected in Cambridge Bay, Nunavut, where only 3 Arctic mosquito species were present, none of which are recognized as potential JCV vectors. This finding raises the possibility of undocumented vector species or a previously unrecognized transmission role for Arctic mosquitoes. The broad distribution of JCV across species and locations suggests widespread enzootic transmission, underscoring the need to reassess the potential of Arctic mosquitoes as disease vectors in a rapidly changing climate.

Climate-driven phenological mismatches threaten avian reproduction by disrupting food availability during critical breeding stages. In marine ecosystems, time lags between environmental changes and their effects on food webs are challenging to model, yet they can have a profound impact on top-predator reproduction. We disentangle how oceanic and climatic variability influence the breeding phenology and success of a keystone seabird of the Southern Ocean drawing on 24 years of data from 17,000 marked king penguins. We document an exceptional 19-day advancement in breeding phenology, alongside increased breeding success (44% in 2000, 62% in 2023). A sliding-window analysis reveals that sea temperature and primary production in key foraging zones predict both phenology and breeding success, with lags ranging from several weeks to two years. While king penguins appear to be keeping pace with current changes, their dependence on multi-year environmental conditions underscores the vulnerability of top predators to unpredictable, fast-changing, and more frequent extreme conditions.

Across the world, human (anthropophonic) sounds add to sounds of biological (biophonic) and geophysical (geophonic) origin, with human contributions including both speech and technophony (sounds of technological devices). To characterize society’s contribution to the global soundscapes, we used passive acoustic recorders at 139 sites across 6 continents, sampling both urban green spaces and nearby pristine sites continuously for 3 years in a paired design. Recordings were characterized by bird species richness and by 14 complementary acoustic indices. By relating each index to seasonal, diurnal, climatic and anthropogenic factors, we show here that latitude, time of day and day of year each predict a substantial proportion of variation in key metrics of biophony—whereas anthropophony (speech and traffic) show less predictable patterns. Compared to pristine sites, the soundscape of urban green spaces is more dominated by technophony and less diverse in terms of acoustic energy across frequencies and time steps, with less instances of quiet. We conclude that the global soundscape is formed from a highly predictable rhythm in biophony, with added noise from geophony and anthropophony. At urban sites, animals experience an increasingly noisy background of sound, which poses challenges to efficient communication.