Leaf Traits, Neighbors, and Abiotic Factors: Ways That Context Can Mediate the Impact of Invasive Species on Nitrogen Cycling

Species invasions are more prevalent than ever before. While the addition of a species can dramatically change critical ecosystem processes, factors that mediate the direction and magnitude of those impacts have received less attention. A better understanding of the factors that mediate invasion impacts on ecosystem functioning is needed in order to target which exotic species will be most harmful and which systems are most vulnerable. The role of invasion on nitrogen (N) cycling is particularly important since N cycling controls ecosystem services that provision human health, e.g. nutrient retention and water quality.

We conducted a meta-analysis and in-depth studies focused on the invasive grass species, Microstegium vimineum, to better understand how (i) plant characteristics, (ii) invader abundance and neighbor identity, and (iii) environmental conditions mediate the impacts of invasion on N pools and fluxes. The results of our global meta-analysis support the concept that invasive species and reference community traits such as leaf %N and leaf C:N are useful for understanding invasion impacts on soil N cycling, but that trait dissimilarities between invaded and reference communities are most informative. Regarding the in-depth studies of Microstegium, we did not find evidence to suggest that invasion increases net nitrification as other studies have shown. Instead, we found that an interaction between its abundance and the neighboring plant identify were important for determining soil nitrate concentrations and net nitrification rates in the greenhouse. In field, we found that variability in environmental conditions mediated the impact of Microstegium invasion on soil N pools and fluxes, primarily net ammonification, between sites through direct, indirect, and interactive pathways. Notably, we detected a scenario in which forest openness has a negative direct effect and indirect positive effect on ammonification in sites with high soil moisture and organic matter. Collectively, our findings suggest that dissimilarity in plant community traits, neighbor identity, and environmental conditions can be important drivers of invasion impacts on ecosystem N cycling and should be considered when evaluating the ecosystem impacts of invasive species across heterogeneous landscapes.

Thrombolysis in myocardial infarction risk score in an observation unit setting.

OBJECTIVE: The Thrombolysis in Myocardial Infarction (TIMI) score is a validated tool for risk stratification of acute coronary syndrome. We hypothesized that the TIMI risk score would be able to risk stratify patients in observation unit for acute coronary syndrome. METHODS: STUDY DESIGN: Retrospective cohort study of consecutive adult patients placed in an urban academic hospital emergency department observation unit with an average annual census of 65,000 between 2004 and 2007. Exclusion criteria included elevated initial cardiac biomarkers, ST segment changes on ECG, unstable vital signs, or unstable arrhythmias. A composite of significant coronary artery disease (CAD) indicators, including diagnosis of myocardial infarction, percutaneous coronary intervention, coronary artery bypass surgery, or death within 30 days and 1 year, were abstracted via chart review and financial record query. The entire cohort was stratified by TIMI risk scores (0-7) and composite event rates with 95% confidence interval were calculated. RESULTS: In total 2228 patients were analyzed. Average age was 54.5 years, 42.0% were male. The overall median TIMI risk score was 1. Eighty (3.6%) patients had 30-day and 119 (5.3%) had 1-year CAD indicators. There was a trend toward increasing rate of composite CAD indicators at 30 days and 1 year with increasing TIMI score, ranging from a 1.2% event rate at 30 days and 1.9% at 1 year for TIMI score of 0 and 12.5% at 30 days and 21.4% at 1 year for TIMI ≥ 4. CONCLUSIONS: In an observation unit cohort, the TIMI risk score is able to risk stratify patients into low-, moderate-, and high-risk groups.