The integration of survey data with the filtered citizen science data resulted in improved inference and increased the extent and accuracy of distribution models on shorebirds for the Central Valley. To accomplish this, we integrated high-resolution survey data on shorebirds in the northern Central Valley of California with observations in eBird for the entire region that were filtered to improve their quality. We explore these trade-offs by applying a simplified approach of filtering citizen science data to resemble structured survey data and analyse both sources of data under a common framework. However, there are perceived trade-offs of combining highly structured, scientific survey data with largely un-structured, citizen science data. Citizen science has been signalled as an increasingly important source to fill in data gaps where information is needed to make comprehensive and robust inferences on species distributions. However, collecting information at relevant scales is often cost prohibitive, although it is essential for framing the broader context of more focused research and conservation efforts. Information on species’ habitat associations and distributions, across a wide range of spatial and temporal scales, is a fundamental source of ecological knowledge.
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