Connecting the data landscape of long‐term ecological studies: The SPI‐Birds data hub (original) (raw)
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The Avian Knowledge Network (AKN) is an international collaboration of academic, nongovernment, and government institutions with the goal of organizing observations of birds into an interoperable format to enhance access, data visualization and exploration, and scientifi c analyses. The AKN uses proven cyberinfrastructure and informatics techniques as the foundation of its development. Data are made available via secure and managed pathways. Additionally, data visualization and exploration tools are made available by a broad and diverse community of developers, analysts, and biologists. Through the development of tools and standardized data organization models, new analysis techniques are being developed that explore data fusion and federation techniques that allow the investigation of patterns of bird occurrence across multiple datasets. Finally, the Avian Knowledge Alliance uses the AKN and consists of a distributed network of nodes that provide regional or thematic access to decision support tools and other applications to support research and bird conservation across a variety of spatial scales.
Developing indicators for European birds
Philosophical Transactions of The Royal Society B: Biological Sciences, 2005
The Royal Society for the Protection of Birds, The Lodge, Sandy, Bedfordshire SG19 2DL, UK
Monitoring the world's bird populations with community science data
Systematic monitoring of species across their geographic ranges is a critical part of conservation but it is resource-intensive, costly, and difficult to organize and maintain in the long-term. Large-scale community science programs like eBird may improve our ability to monitor bird populations, particularly in tropical regions where formal studies are lacking. Here, we estimated population trends for nearly 9000 bird species using global eBird birdwatching data and compared our trends to the population trends designated by BirdLife International. We calculated the rate of agreement between eBird and BirdLife trends and examined the effects of latitudinal affiliation, threat status, number of eBird checklists, eBird trend, BirdLife trend and BirdLife trend derivation on the rate of agreement. We also used a randomization approach to compare observed rates of agreement with the rates of agreement expected by chance alone. We show that the rate of agreement was marginally better than expected by chance and improved significantly for temperate region species of Least Concern with more checklists, and species that eBird or BirdLife identified as increasing. Our results suggest that eBird data are not currently adequate for monitoring populations of the majority of the world's bird species, especially in the developing world where systematic surveys are essential. Increased local participation in community science initiatives like eBird may improve our ability to effectively monitor species. Furthermore, it is important to assess the accuracy of BirdLife trends and the manner in which they are derived, especially for species where BirdLife and eBird data trends disagree.
Journal of Biogeography, 2004
Aim To assess the relative roles of environment and space in driving bird species distribution and to identify relevant drivers of bird assemblage composition, in the case of a fine-scale bird atlas data set.Location The study was carried out in southern Belgium using grid cells of 1 × 1 km, based on the distribution maps of the Oiseaux nicheurs de Famenne: Atlas de Lesse et Lomme which contains abundance for 103 bird species.Methods Species found in < 10% or > 90% of the atlas cells were omitted from the bird data set for the analysis. Each cell was characterized by 59 landscape metrics, quantifying its composition and spatial patterns, using a Geographical Information System. Partial canonical correspondence analysis was used to partition the variance of bird species matrix into independent components: (a) ‘pure’ environmental variation, (b) spatially-structured environmental variation, (c) ‘pure’ spatial variation and (d) unexplained, non-spatial variation.Results The variance partitioning method shows that the selected landscape metrics explain 27.5% of the variation, whilst ‘pure’ spatial and spatially-structured environmental variables explain only a weak percentage of the variation in the bird species matrix (2.5% and 4%, respectively). Avian community composition is primarily related to the degree of urbanization and the amount and composition of forested and open areas. These variables explain more than half of the variation for three species and over one-third of the variation for 12 species.Main conclusions The results seem to indicate that the majority of explained variation in species assemblages is attributable to local environmental factors. At such a fine spatial resolution, however, the method does not seem to be appropriated for detecting and extracting the spatial variation of assemblages. Consequently, the large amount of unexplained variation is probably because of missing spatial structures and ‘noise’ in species abundance data. Furthermore, it is possible that other relevant environmental factors, that were not taken into account in this study and which may operate at different spatial scales, can drive bird assemblage structure. As a large proportion of ecological variation can be shared by environment and space, the applied partitioning method was found to be useful when analysing multispecific atlas data, but it needs improvement to factor out all-scale spatial components of this variation (the source of ‘false correlation’) and to bring out the ‘pure’ environmental variation for ecological interpretation.
Reviving a Legacy Citizen Science Project to Illuminate Shifts in Bird Phenology
International Journal of Zoology, 2012
Climate change has been of high interest to both the scientific community and the public at large since the phenomenon was first suggested. Subsequently, and with growing evidence of its impending ramifications, numerous studies have attempted to illuminate climate change impacts on bird migration. Migration is a key event in the annual cycle in the reproductive success of birds, and changes in migration in response to climate may indicate that species populations are at risk. Previous studies report earlier arrival dates in response to climate change in many bird species, although specific mechanisms are often difficult to explain at broad spatial and temporal scales. Using a newly revived dataset of historical migration cards for over 870 species and spanning 90 years throughout North America, we are developing an historical baseline of bird arrival dates to compare with contemporary records. Here we chronicle the history and reemergence of the North American Bird Phenology Progra...