For birds, maintaining an optimal nest temperature is critical for early‐life growth and development. Temperatures deviating from this optimum can affect nestling growth and fledging success with potential consequences on survival and lifetime reproductive success. It is therefore particularly important to understand these effects in relation to projected temperature changes associated with climate change. Targets set by the 2015 Paris Agreement aim to limit temperature increases to 2°C, and, with this in mind, we carried out an experiment in 2017 and 2018 where we applied a treatment that increased Great TitParusmajornest temperature by approximately this magnitude (achieving an increase of 1.6°C, relative to the control) during the period from hatching to fledging to estimate how small temperature differences might affect nestling body size and weight at fledging and fledging success. We recorded hatching and fledging success and measured skeletal size (tarsus length) and body mass at days 5, 7, 10, and 15 posthatch in nestlings from two groups of nest boxes: control and heated (+1.6°C). Our results show that nestlings in heated nest boxes were 1.6% smaller in skeletal size at fledging than those in the cooler control nests, indicating lower growth rates in heated boxes, and that their weight was, in addition, 3.3% lower. These results suggest that even fairly small changes in temperature can influence phenotype and postfledging survival in cavity‐nesting birds. This has the potential to affect the population dynamics of these birds in the face of ongoing climatic change, as individuals of reduced size in colder winters may suffer from decreased fitness.

Future climatic scenarios forecast increases in average temperatures as well as in the frequency, duration, and intensity of extreme events, such as heatwaves. Whereas behavioral adjustments can buffer direct physiological and fitness costs of exposure to excessive temperature in wild animals, these may prove more difficult during specific life stages when vagility is reduced (e.g., early developmental stages). By means of a nest cooling experiment, we tested the effects of extreme temperatures on different stages of reproduction in a cavity‐nesting Mediterranean bird of prey, the lesser kestrel (Falco naumanni), facing a recent increase in the frequency of heatwaves during its breeding season. Nest temperature in a group of nest boxes placed on roof terraces was reduced by shading them from direct sunlight in 2 consecutive years (2021 and 2022). We then compared hatching failure, mortality, and nestling morphology between shaded and non‐shaded (control) nest boxes. Nest temperature in control nest boxes was on average 3.9°C higher than in shaded ones during heatwaves, that is, spells of extreme air temperature (>37°C for ≥2 consecutive days) which hit the study area during the nestling‐rearing phase in both years. Hatching failure markedly increased with increasing nest temperature, rising above 50% when maximum nest temperatures exceeded 44°C. Nestlings from control nest boxes showed higher mortality during heatwaves (55% vs. 10% in shaded nest boxes) and those that survived further showed impaired morphological growth (body mass and skeletal size). Hence, heatwaves occurring during the breeding period can have both strong lethal and sublethal impacts on different components of avian reproduction, from egg hatching to nestling growth. More broadly, these findings suggest that the projected future increases of summer temperatures and heatwave frequency in the Mediterranean basin and elsewhere in temperate areas may threaten the local persistence of even relatively warm‐adapted species.

The use of Unmanned Aerial Vehicles (UAVs) to monitor large colonies of seabirds avoids challenges associated with conventional methods, but manual image processing is expensive. Development of semi-automated analytical methods rely on high image spatial resolution, which requires a trade-off between securing low area coverage and high spatial resolution flying at low altitude vs high area coverage but low spatial resolution flying at higher altitudes. Increasing individual bird detection probabilities requires maximizing contrast between target and background, which can be enhanced using thermal sensors. We applied a semi-automatic analytical method to multispectral UAV derived imagery to count a mixed breeding colony of Herring Gulls (Larus argentatus) and Lesser Blackbacked Gulls (L. fuscus). We trained the computer to detect different image classes by their spectral signature in several orthomosaics obtained from UAV flights at different altitudes using different cameras. Highest agreement with the manual counts was achieved by low flying (20 m) using the highest camera resolution (97.7 ± 1.1% for the Herring Gulls, omission error 2.6%, commission error 0.5%; 94.8 ± 1.8% for Lesser Black-backed Gulls, omission error 6.5%, commission error 1.6%). Method precision varied between trials, confirming the importance of low altitude flying with high quality cameras, and a 40% reduction in detection noise from adding a thermal sensor.

Long-term monitoring of breeding seabirds is fundamental for assessing the conservation status of their populations. Whereas traditional monitoring is often time consuming and has disadvantages, such as observer bias or disturbance to the breeding grounds, the use of uncrewed aerial vehicles (UAVs or drones) has proven to be an efficient alternative by allowing non-invasive monitoring of inaccessible areas. Nonetheless, the use of drones for monitoring wild populations brings forth a new challenge, namely the handling of large amounts of data (images), usually negating the efficiency of the previous steps. Diverse methodologies have been developed to deal with this issue, but they usually involve the use of commercial software, that reduces the accessibility of users with limited resources. We tested if the popular free software ImageJ could compete in terms of efficiency (i.e. accuracy and processing time) with other commercial software. We obtained similar values of agreement between manual and semiautomated total counts of individuals (99.1%), reducing the analysis duration fivefold. In addition, we propose a correction factor in the detection of incubating individuals based on the assessment of the individual behaviour of 10% of the birds present in each colony. Following this correction, we were able to estimate the total number of incubating birds with a 103.5% agreement with manual counts, reducing the time invested up to threefold. Thus, we show support for the use of free software (ImageJ) as a good low-cost alternative for users of drone imagery in assessing breeding birds and as a conservation tool.