Publications by authors named "C Narr"

Progress in the field of ecological stoichiometry has demonstrated that the outcome of ecological interactions can often be predicted a priori based on the nutrient ratios (e.g., carbon: nitrogen: phosphorus, C:N:P) of interacting organisms.

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The nutrient content of host resources can influence the abundance of parasites within an ecosystem, but linking specific nutrients in a host to the abundance of different parasite taxa remains a challenge. Here, we work to forge this link by quantifying the relationship between the nutrient content of specific infection sites and the abundance of multiple parasite taxa within the digestive tract of largemouth bass () collected from the Mississippi River. To generate a mechanistic understanding of these relationships, we tested four basic predictions: (1) the nutrient content of different host tissues (infection sites) varies within and across hosts, (2) the nutrient content of parasite genera differs from that of their host tissue(s), (3) the nutrient content of parasite genera differ from one another and (4) the nutrient content of host tissues is related to the nutrient content and abundance of parasite genera.

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Given the numerous barriers to accessing child and adolescent eating disorder treatment, there is a need for innovation in how this care is delivered. Primary care-based eating disorder treatment has established proof-of-concept, yet it is unclear whether this model can bridge the treatment-access gap. This retrospective chart review study compared demographic and illness characteristics of 106 adolescents (M age = 15.

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Evidence-based treatments have been developed for a range of pediatric mental health conditions. These interventions have proven efficacy but require trained pediatric behavioral health specialists for their administration. Unfortunately, the widespread shortage of behavioral health specialists leaves few referral options for primary care providers.

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Ecological inference requires integrating information across scales. This integration creates a complex spatial dependence structure that is most accurately represented by fully non-stationary models. However, ecologists rarely use these models because they are difficult to estimate and interpret.

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