Cottingham Kathryn L.

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Cottingham
First Name
Kathryn L.
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  • Article
    Association of cesarean delivery and formula supplementation with the intestinal microbiome of 6-week-old infants
    (American Medical Association, 2016-01-11) Madan, Juliette C. ; Hoen, Anne G. ; Lundgren, Sara N. ; Farzan, Shohreh F. ; Cottingham, Kathryn L. ; Morrison, Hilary G. ; Sogin, Mitchell L. ; Li, Hongzhe ; Moore, Jason H. ; Karagas, Margaret R.
    The intestinal microbiome plays a critical role in infant development, and delivery mode and feeding method (breast milk vs formula) are determinants of its composition. However, the importance of delivery mode beyond the first days of life is unknown, and studies of associations between infant feeding and microbiome composition have been generally limited to comparisons between exclusively breastfed and formula-fed infants, with little consideration given to combination feeding of both breast milk and formula.
  • Article
    Complexity in ecology and conservation : mathematical, statistical, and computational challenges
    (American Institute of Biological Sciences, 2005-06) Green, Jessica L. ; Hastings, Alan ; Arzberger, Peter ; Ayala, Francisco J. ; Cottingham, Kathryn L. ; Cuddingham, Kim ; Davis, Frank ; Dunne, Jennifer A. ; Fortin, Marie-Josee ; Gerber, Leah ; Neubert, Michael G.
    Creative approaches at the interface of ecology, statistics, mathematics, informatics, and computational science are essential for improving our understanding of complex ecological systems. For example, new information technologies, including powerful computers, spatially embedded sensor networks, and Semantic Web tools, are emerging as potentially revolutionary tools for studying ecological phenomena. These technologies can play an important role in developing and testing detailed models that describe real-world systems at multiple scales. Key challenges include choosing the appropriate level of model complexity necessary for understanding biological patterns across space and time, and applying this understanding to solve problems in conservation biology and resource management. Meeting these challenges requires novel statistical and mathematical techniques for distinguishing among alternative ecological theories and hypotheses. Examples from a wide array of research areas in population biology and community ecology highlight the importance of fostering synergistic ties across disciplines for current and future research and application.