Testing the accuracy of methods for reconstructing ancestral states of continuous characters.

Many methods are available for estimating ancestral values of continuous characteristics, but little is known about how well these methods perform. Here we compare six methods: linear parsimony, squared-change parsimony, one-parameter maximum likelihood (Brownian motion), two-parameter maximum likelihood (Ornstein-Uhlenbeck process), and independent comparisons with and without branch-length information. We apply these methods to data from 20 morphospecies of Pleistocene planktic Foraminifera in order to estimate ancestral size and shape variables, and compare these estimates with measurements on fossils close to the phylogenetic position of 13 ancestors. No method produced accurate estimates for any variable: estimates were consistently less good as predictors of the observed values than were the averages of the observed values. The two-parameter maximum-likelihood model consistently produces the most accurate size estimates overall. Estimation of ancestral sizes is confounded by an evolutionary trend towards increasing size. Shape showed no trend but was still estimated very poorly: we consider possible reasons. We discuss the implications of our results for the use of estimates of ancestral characteristics.     

Influence of arm position on measurement of blood pressure.

A series of measurements of blood pressure in normotensive and hypertensive subjects showed that measurements made with a sphygmomanometer with the arm dependent by the side were consistently higher than those made with the arm horizontal at heart level. The mean difference in a group of 90 hypertensive outpatients was 11/12 mm Hg. Failure to appreciate the importance of arm position may lead to erroneous measurements of blood pressure. This has important implications for clinical practice and research.     

Application of polyethyleneimine cellulose for the class separation of steroidal carboxylic acids from neutral steroids and pigments in urine

Metabolites of corticosteroids that contain the 21-oic acid moiety are found in human urine. The acids from neutral steroids and urinary pigments have been separated by passing the mixture through a column of polyethyleneimine cellulose. The acids adhering to the column are quantitatively eluted with dilute formic acid. The purified preparation is suitable for derivatization and chromatographic analysis.     

Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides

Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically considered an improvement over simply comparing the amount of herbicides applied by weight. Herbicides are treated differently compared to other pesticide groups when calculating the EIQ, and therefore, it is important to understand how different risk factors affect the EIQ for herbicides. The purpose of this work was to evaluate the suitability of the EIQ as an environmental indicator for herbicides. Simulation analysis was conducted to quantify relative sensitivity of the EIQ to changes in risk factors, and actual herbicide EIQ values were used to quantify the impact of herbicide application rate on the EIQ Field Use Rating. Herbicide use rate was highly correlated with the EIQ Field Use Rating (Spearman’s rho >0.96, P-value <0.001) for two herbicide datasets. Two important risk factors for herbicides, leaching and surface runoff potential, are included in the EIQ calculation but explain less than 1% of total variation in the EIQ. Plant surface half-life was the risk factor with the greatest relative influence on herbicide EIQ, explaining 26 to 28% of the total variation in EIQ for actual and simulated EIQ values, respectively. For herbicides, the plant surface half-life risk factor is assigned values without any supporting quantitative data, and can result in EIQ estimates that are contrary to quantitative risk estimates for some herbicides. In its current form, the EIQ is a poor measure of herbicide environmental impact.