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1.
Am Nat ; 195(6): 964-985, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32469660

RESUMO

Understanding how nutrients flow through food webs is central in ecosystem ecology. Tracer addition experiments are powerful tools to reconstruct nutrient flows by adding an isotopically enriched element into an ecosystem and tracking its fate through time. Historically, the design and analysis of tracer studies have varied widely, ranging from descriptive studies to modeling approaches of varying complexity. Increasingly, isotope tracer data are being used to compare ecosystems and analyze experimental manipulations. Currently, a formal statistical framework for analyzing such experiments is lacking, making it impossible to calculate the estimation errors associated with the model fit, the interdependence of compartments, and the uncertainty in the diet of consumers. In this article we develop a method based on Bayesian hidden Markov models and apply it to the analysis of N15-NH4+ tracer additions in two Trinidadian streams in which light was experimentally manipulated. Through this case study, we illustrate how to estimate N fluxes between ecosystem compartments, turnover rates of N within those compartments, and the associated uncertainty. We also show how the method can be used to compare alternative models of food web structure, calculate the error around derived parameters, and make statistical comparisons between sites or treatments.


Assuntos
Ecossistema , Cadeia Alimentar , Modelos Estatísticos , Nitrogênio/metabolismo , Compostos de Amônio/química , Animais , Luz , Cadeias de Markov , Isótopos de Nitrogênio , Plantas/metabolismo , Rios , Trinidad e Tobago , Água/química
2.
Ecology ; 97(11): 3154-3166, 2016 11.
Artigo em Inglês | MEDLINE | ID: mdl-27870030

RESUMO

Decades of ecological study have demonstrated the importance of top-down and bottom-up controls on food webs, yet few studies within this context have quantified the magnitude of energy and material fluxes at the whole-ecosystem scale. We examined top-down and bottom-up effects on food web fluxes using a field experiment that manipulated the presence of a consumer, the Trinidadian guppy Poecilia reticulata, and the production of basal resources by thinning the riparian forest canopy to increase incident light. To gauge the effects of these reach-scale manipulations on food web fluxes, we used a nitrogen (15 N) stable isotope tracer to compare basal resource treatments (thinned canopy vs. control) and consumer treatments (guppy introduction vs. control). The thinned canopy stream had higher primary production than the natural canopy control, leading to increased N fluxes to invertebrates that feed on benthic biofilms (grazers), fine benthic organic matter (collector-gatherers), and organic particles suspended in the water column (filter feeders). Stream reaches with guppies also had higher primary productivity and higher N fluxes to grazers and filter feeders. In contrast, N fluxes to collector-gatherers were reduced in guppy introduction reaches relative to upstream controls. N fluxes to leaf-shredding invertebrates, predatory invertebrates, and the other fish species present (Hart's killifish, Anablepsoides hartii) did not differ across light or guppy treatments, suggesting that effects on detritus-based linkages and upper trophic levels were not as strong. Effect sizes of guppy and canopy treatments on N flux rates were similar for most taxa, though guppy effects were the strongest for filter feeding invertebrates while canopy effects were the strongest for collector-gatherer invertebrates. Combined, these results extend previous knowledge about top-down and bottom-up controls on ecosystems by providing experimental, reach-scale evidence that both pathways can act simultaneously and have equally strong influence on nutrient fluxes from inorganic pools through primary consumers.


Assuntos
Peixes/fisiologia , Cadeia Alimentar , Luz , Rios , Animais , Biomassa , Dinâmica Populacional , Trinidad e Tobago , Clima Tropical , Água/química
3.
Appl Clin Inform ; 7(2): 227-37, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27437036

RESUMO

OBJECTIVES: To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. MATERIALS AND METHODS: We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. RESULTS: A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. CONCLUSION: Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.


Assuntos
Sistemas de Apoio a Decisões Clínicas/estatística & dados numéricos , Enfermagem/métodos , Humanos
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