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Conservation prioritization requires knowledge about organism distribution and density. This information is often inferred from models that estimate the probability of species occurrence rather than from models that estimate species abundance, because abundance data are harder to obtain and model. However, occurrence and abundance may not display similar patterns and therefore development of robust, scalable, abundance models is critical to ensuring that scarce conservation resources are applied where they can have the greatest benefits. Motivated by a dynamic land conservation program, we develop and assess a general method for modeling relative abundance using citizen science monitoring data. Weekly estimates of relative abundance and occurrence were compared for prioritizing times and locations of conservation actions for migratory waterbird species in California, USA. We found that abundance estimates consistently provided better rankings of observed counts than occurrence estimates. Additionally, the relationship between abundance and occurrence was nonlinear and varied by species and season. Across species, locations prioritized by occurrence models had only 10-58% overlap with locations prioritized by abundance models, highlighting that occurrence models will not typically identify the locations of highest abundance that are vital for conservation of populations.

The feeding of human milk (milk from the infant's own mother; excluding donor milk) during the NICU stay reduces the risk of short-and long-term morbidities in premature infants, including: enteral feed intolerance; nosocomial infection; necrotizing enterocolitis (NEC); chronic lung disease (CLD); retinopathy of prematurity (ROP); developmental and neurocognitive delay; and rehospitalization after NICU discharge.1 -29 The mechanisms by which human milk provides this protection are varied and synergistic, and appear to change over the course of the NICU stay.30 , 31 In brief, these mechanisms include specific human milk components that are not present in the milk of other mammals, such the type and amount of long-chain polyunsaturated fatty acids and digestible proteins, and the extraordinary number of oligosaccharides (approximately 130). 32 Human milk also contains multiple lines of undifferentiated stem cells, with the potential to impact a variety of health outcomes through the lifespan.33 Other human milk mechanisms change over the course of lactation in a manner that complements the infant's nutritional and protective needs. These mechanisms include immunological, anti-infective, anti-inflammatory, epigenetic, and mucosal membrane protecting properties.34 -41 Thus, human milk from the infant's mother cannot be replaced by commercial infant or donor human milk, and the feeding of human milk should be a NICU priority.Recent evidence suggests that the impact of human milk on improving infant health outcomes and reducing the risk of prematurity-specific morbidities appears to be linked to specific critical exposure periods in the post-birth period during which the exclusive use of human milk and the avoidance of commercial formula may be most important. 29-31, 42, 43 Similarly, there are other periods when high doses, but not necessarily exclusive use of human milk, may be important. This chapter will review the concept of "dose and exposure period" for human milk feeding in the NICU to precisely measure and benchmark the amount and timing of human milk use in the NICU. Similarly, the critical exposure periods when exclusive or high doses of human milk appear to have the greatest impact on specific

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 data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a ‘Big Data’ approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird’s data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a ‘sensor calibration’ approach to measure individual variation in eBird participant’s ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.

Citizen science, big data, and a habitat marketplace enable dynamic habitat for migratory birds in California’s Central Valley.