Climate change affects timing of reproduction in many bird species, but few studies have investigated its influence on annual reproductive output. Here, we assess changes in the annual production of young by female breeders in 201 populations of 104 bird species (N = 745,962 clutches) covering all continents between 1970 and 2019. Overall, average offspring production has declined in recent decades, but considerable differences were found among species and populations. A total of 56.7% of populations showed a declining trend in offspring production (significant in 17.4%), whereas 43.3% exhibited an increase (significant in 10.4%). The results show that climatic changes affect offspring production through compounded effects on ecological and life history traits of species. Migratory and larger-bodied species experienced reduced offspring production with increasing temperatures during the chick-rearing period, whereas smaller-bodied, sedentary species tended to produce more offspring. Likewise, multi-brooded species showed increased breeding success with increasing temperatures, whereas rising temperatures were unrelated to reproductive success in single-brooded species. Our study suggests that rapid declines in size of bird populations reported by many studies from different parts of the world are driven only to a small degree by changes in the production of young.

Small mammals, and particularly rodents, are common inhabitants of farmlands, where they play key roles in the ecosystem, but when overabundant, they can be major pests, able to reduce crop production and farmers’ incomes, with tangible effects on the achievement of Sustainable Development Goals no 2 (SDG2, Zero Hunger) of the United Nations. Farmers do not currently have a standardized, accurate method of detecting the presence, abundance, and locations of rodents in their fields, and hence do not have environmentally efficient methods of rodent control able to promote sustainable agriculture oriented to reduce the environmental impacts of cultivation. New developments in unmanned aerial system (UAS) platforms and sensor technology facilitate cost-effective data collection through simultaneous multimodal data collection approaches at very high spatial resolutions in environmental and agricultural contexts. Object detection from remote-sensing images has been an active research topic over the last decade. With recent increases in computational resources and data availability, deep learning-based object detection methods are beginning to play an important role in advancing remote-sensing commercial and scientific applications. However, the performance of current detectors on various UAS-based datasets, including multimodal spatial and physical datasets, remains limited in terms of small object detection. In particular, the ability to quickly detect small objects from a large observed scene (at field scale) is still an open question. In this paper, we compare the efficiencies of applying one- and two-stage detector models to a single UAS-based image and a processed (via Pix4D mapper photogrammetric program) UAS-based orthophoto product to detect rodent burrows, for agriculture/environmental applications as to support farmer activities in the achievements of SDG2. Our results indicate that the use of multimodal data from low-cost UASs within a self-training YOLOv3 model can provide relatively accurate and robust detection for small objects (mAP of 0.86 and an F1-score of 93.39%), and can deliver valuable insights for field management with high spatial precision able to reduce the environmental costs of crop production in the direction of precision agriculture management.

The combined actions of climatic variations and landscape barriers shape the history of natural populations. When organisms follow their shifting niches, obstacles in the landscape can lead to the splitting of populations, on which evolution will then act independently. When two such populations are reunited, secondary contact occurs in a broad range of admixture patterns, from narrow hybrid zones to the complete dissolution of lineages. A previous study suggested that barn owls colonized the Western Palearctic after the last glaciation in a ring-like fashion around the Mediterranean Sea, and conjectured an admixture zone in the Balkans. Here, we take advantage of whole-genome sequences of 94 individuals across the Western Palearctic to reveal the complex history of the species in the region using observational and modeling approaches. Even though our results confirm that two distinct lineages colonized the region, one in Europe and one in the Levant, they suggest that it predates the last glaciation and identify a secondary contact zone between the two in Anatolia. We also show that barn owls recolonized Europe after the glaciation from two distinct glacial refugia: a previously identified western one in Iberia and a new eastern one in Italy. Both glacial lineages now communicate via eastern Europe, in a wide and permeable contact zone. This complex history of populations enlightens the taxonomy of Tyto alba in the region, highlights the key role played by mountain ranges and large water bodies as barriers and illustrates the power of population genomics in uncovering intricate demographic patterns.

Rodent pests cause extensive damage to agricultural crops worldwide. Farmers’ ability to monitor rodent activity and damage within crops is limited due to their inability to simultaneously survey vast agricultural areas for rodent activity, the inability to enter certain fields, and the difficulty of monitoring rodent numbers, as well as using traps due to trap shyness and high labor costs. Drones can potentially be used to monitor rodent numbers and damage because they can cover large areas quickly without damaging crops and carry sensors that provide high-resolution imagery. Here, we investigated whether rodent activity (Levant voles Microtus guentheri and house mice Mus musculus) is related to vegetation health and biomass in Alfalfa (Medicago sativa) fields. We used a drone to photograph one hundred and twenty 10 × 10 m plots in nine fields and calculate the plots’ normalized difference vegetation index (NDVI) and biomass. On each plot, we also trapped rodents, counted rodent burrows, and evaluated the harvested dry crop yield. The number of burrows was positively related to the number of Levant voles trapped (F_1,110 = 12.08, p < 0.01) and negatively related to the number of house mice trapped (F_1,110 = 5.23, p < 0.05). Biomass extracted from drone images was positively related to the yield harvested by hand (F_1,83 = 3.81, p < 0.05). Farmers, therefore, can use burrow counting in place of trapping Levant voles, and biomass estimates from drones can be used in place of manual yield calculations. NDVI (F_1,95 = 73.14, p < 0.001) and biomass (F_1,95 = 79.58, p < 0.001) were negatively related to the number of Levant voles trapped, and the number of burrows were not related to the number of house mice trapped. We demonstrate that drones can be used to assist farmers in determining the Levant vole presence and damage within crop fields to control rodents using precision agriculture methods, such as adding rodenticides in specific areas, thus increasing efficiency and decreasing the amount of pesticides used.

Islands, and the particular organisms that populate them, have long fascinated biologists. Due to their isolation, islands offer unique opportunities to study the effect of neutral and adaptive mechanisms in determining genomic and phenotypical divergence. In the Canary Islands, an archipelago rich in endemics, the barn owl (Tyto alba), present in all the islands, is thought to have diverged into a subspecies (T. a. gracilirostris) on the eastern ones, Fuerteventura and Lanzarote. Taking advantage of 40 whole-genomes and modern population genomics tools, we provide the first look at the origin and genetic makeup of barn owls of this archipelago. We show that the Canaries hold diverse, long-standing and monophyletic populations with a neat distinction of gene pools from the different islands. Using a new method, less sensitive to structure than classical F_ST, to detect regions involved in local adaptation to insular environments, we identified a haplotype-like region likely under selection in all Canaries individuals and genes in this region suggest morphological adaptations to insularity. In the eastern islands, where the subspecies is present, genomic traces of selection pinpoint signs of adapted body proportions and blood pressure, consistent with the smaller size of this population living in a hot arid climate. In turn, genomic regions under selection in the western barn owls from Tenerife showed an enrichment in genes linked to hypoxia, a potential response to inhabiting a small island with a marked altitudinal gradient. Our results illustrate the interplay of neutral and adaptive forces in shaping divergence and early onset speciation.