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Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of(More)
The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions.(More)
The Cornell Laboratory of Ornithology's mission is to interpret and conserve the earth's biological diversity through research, education, and citizen science focused on birds. Over the years, the Lab has accumulated one of the largest and longest-running collections of environmental data sets in existence. The data sets are not only large, but also have(More)
Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird(More)
In this paper we demonstrate a practical approach to interaction detection on real data describing the abundance of different species of birds in the prairies east of the southern Rocky Mountains. This data is very noisy-predictive models built from this data perform only slightly better than baseline. Previous approaches for interaction detection,(More)
In this paper we describe eBird, a citizen-science project that takes advantage of human observational capacity and machine learning methods to explore the synergies between human computation and mechanical computation. We call this model a Hu-man/Computer Learning Network, whose core is an active learning feedback loop between humans and machines that(More)
— Although citizen science projects can engage a very large number of volunteers to collect volumes of data, they are susceptible to issues with data quality. Our experience with eBird, which is a broad-scale citizen science project to collect bird observations, has shown that a massive effort by volunteer experts is needed to screen data, identify outliers(More)