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Abstract Contributory science—including citizen and community science—allows scientists to leverage participant‐generated data while providing an opportunity for engaging with local community members. Data yielded by participant‐generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts.The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases.We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation,detectability,samplingandpreference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data.Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the freePlain Language Summaryfor this article on the Journal blog. 

Human-wildlife interactions continue to increase due to anthropogenic disturbances, with some interactions resulting in conflict. Leveraging a taxa’s bias for a particular sensory cue is a promising management avenue for reducing the potential and realized negative consequences of human-wildlife conflict. For instance, many avian species heavily depend on acoustic communication, and acoustic cues can provide opportunities to reduce conflict with various avian species. The monk parakeet (Myiopsitta monachus) is a gregarious parrot native to South America that has established populations worldwide and is considered an urban and agricultural pest in parts of its native and introduced ranges. We conducted playback experiments with a captive population of monk parakeets to evaluate auditory cues that may be useful for designing management protocols. Our experiment evaluated the efficacy of two stimuli: predator vocalizations as potential repulsion and conspecific vocalizations as potential attraction stimuli for parakeets. We measured two responses: (1) categorical group-level behavioral responses and (2) time to cease vigilance and return to behavior prior to playback. In the repulsion playbacks, monk parakeets were repelled by predator vocalizations in 80% of trials and took longer to cease vigilance and return to baseline behavior compared to attraction playbacks. In the attraction playbacks, monk parakeets exhibited vigilant behavior and weak or no attraction to the stimulus, with attraction only being observed in 10% of trials. Our results demonstrate that predator playbacks may be particularly useful for completing management objectives, such as temporary removal from a location.