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A timeline for the urbanization of wild birds: The case of the lesser kestrel

The Lesser kestrel (Falco naumanni) evolved as a separate species in the Old-World kestrel radiation starting in the late Miocene. Given that the first cities were erected in the Holocene, this urban colonial raptor has only become a major town dweller recently in its evolutionary history. Today, more than 95% of lesser kestrel colonies in Spain and other Mediterranean countries are on buildings, and the remaining few are on rocky outcrops, that may have been the original nesting substrate for this cavity-nesting bird. Lesser kestrel fossils are well represented in cave sites, and their paleontological distribution, spanning from the Early Paleolithic to the Epipaleolithic, agrees well with its current breeding distribution. According to classical sources, such as the works of Columella and Pliny the Elder, and the presence of a skeletal remain in a Roman villa near Madrid, lesser kestrels may have nested in buildings and in urban settings for at least 2000e2500 years. However, there are no surviving colonies in structures older than 1400 years in Andalusia, nor in Spain. For a sample of 349 colonies on ancient buildings, a majority of the structures had been erected between the 15th and 17th centuries, this putting a time limit of about 300-600 years to the existence of those seemingly immemorial colonies. For specific towns and buildings, written references for the presence of lesser kestrel colonies do not go back more than two centuries. In fact, the Cathedral of Sevilla may be the structure with the longest continuous occupation by lesser kestrels recorded up to present time, from 1834 to 2020. Lesser kestrels were possibly too common in human settlements in the past as to be noted as special. This may explain the scarcity of references to the species until the 19th century. In any case, the same lack of information affects the other major Eurasian urban birds, as no timeline exist for the urbanization process of any other bird species. Here authors propose that lesser kestrels became urban breeders when both adequate cavities in buildings and cereal fields, where they capture their invertebrate prey, became available in their breeding range, several millennia ago. However, urban colonies, in contrast with the ones on stable geological substrates, have been forced to move from building to building when older ones became ruinous or were rebuilt, but new structures with suitable cavities became available throughout History. informacion[at]ebd.csic.es: Negro et al (2020) A timeline for the urbanization of wild birds: The case of the lesser kestrel. Quaternary Sci Rev https://doi.org/10.1016/j.quascirev.2020.106638


https://www.sciencedirect.com/science/article/pii/S0277379120306004?via%3Dihub
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The challenges of building Essential Biodiversity Variables

The challenges of building Essential Biodiversity Variables

Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, the challenges of a ‘Big Data' approach to building global EBV data products across taxa and spatiotemporal scales is assessed, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), 11 key workflow steps are identified that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. These steps are illustrated with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and an overview of current data and metadata standards is provided. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals. informacion[at]ebd.csic.es: Kissling et al (2017) Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale. Biol Rev Doi 10.1111/brv.12359

 


http://onlinelibrary.wiley.com/doi/10.1111/brv.12359/abstract