Estimating species occurrence, abundance, and detection probability using zero-inflated distributions

Researchers have developed methods to account for imperfect detection of species with either occupancy (presence absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Optimal biomass allocation in heterogeneous environments in a clonal plant—Spatial division of labor

When interconnected ramets of clonal plants are growing in heterogeneous environments, ramets may specialize to uptake locally abundant resources rather than scarce resources. This biomass allocation pattern may result in more efficient sharing of resources through physiological integration and an overall benefit to the plants (spatial division of labor; DoL).     

Swelling related to ettringite crystal formation in chromite ore processing residue

Several million tons of Chromite Ore Processing Residue (COPR) were deposited at two sites in New Jersey and Maryland, USA, and over time they exhibited extensive heaving phenomena. Ettringite, a needle-shaped mineral and an expansive mineral commonly recognized in the literature concerning cement- and soil, has been identified extensively in numerous COPR samples collected from these sites. It was therefore believed that ettringite formation and its crystal growth are strongly associated with COPR heaving. We investigated the correlation between ettringite and the heaving phenomena in COPR materials that contained no initial ettringite. Two identical COPR samples were exposed to a 4% w/w sulfate solution (25°C, 50°C) in a confined swell test apparatus. Both swell test samples were analyzed by means of X-ray powder diffraction. The peak intensities of newly formed ettringite were more pronounced in the sample tested at 50°C, and swell development was only observed in this sample. Scanning electron microscopy analyses revealed well-crystallized ettringite needles exceeding 40 μm in length for this sample, while ettringite crystals less than 15 μm in length formed in the sample tested at 25°C. Therefore, the results suggest that the quantity of ettringite and the extent of crystallization play a key role in the heave of COPR.     

“Applicability of the t-Test for Detecting Trends in Water Quality Variables,” by Robert H. Montgomery and Jim C. Loftis2

Montgomery and Loftis (1987) have listed several situations for which the t-test does not accurately reproduce Type I errors, and should therefore be avoided. Characteristics common to water quality data (skewness or other non-normality, presence of outliers and less-thans) also reduce the power of the t-test, in relation to nonparametric alternatives. Thus if one is interested in reaching correct decisions when trends or differences exist, and not just when they do not, the t-test should not be considered “robust” (in the sense of being generally applicable) when its assumptions are violated. Further, t-tests assume that differences in means are relevant (the mean is a good measure of central tendency), and that data groups differ by some additive amount. When all of these assumptions are recognized, and in light of the availability of truly robust and comparatively powerful non-parametric alternatives, we believe there is little applicability of the t-test for detecting trends or differences in water quality variables.     

A novel role of computers in the natural products field

We describe several computer programs developed in our laboratory as aids in the determination of unknown molecular structures. These programs include CONGEN [1], for determination of all plausible structural candidates; REACT [2, 3], for simulation of sequences of chemical reactions; and STRUCC, for evaluating candidates and planning new experiments. We stress the importance of symbiosis between chemist and computer, the combination building on their respective strengths to increase the speed and accuracy of structural assignments.     

First-trimester alpha-fetoprotein screening for Down syndrome

Screening for Down syndrome and other chromosomal aneuploidies by biochemical parameters in maternal serum is well established for the second trimester. With screening as late as 16 weeks of gestation, the option of chorionic villus sampling (CVS) unfortunately is lost. In our study population, the maternal serum alpha-fetoprotein (MSAFP) concentration was determined in 2471 women in the first trimester immediately prior to CVS. Although in this sample MSAFP tended to be lower in Down syndrome (DS) pregnancies than in pregnancies with a chromosomally normal fetus, at this early gestational age neither a fixed cut-off level of 0·5 multiples of the normal median (MOM) nor one of 0·6 MOM was suitable for identifying pregnancies at higher risk for DS. This also applied to trisomy 18, although on average MSAFP in trisomy 18 pregnancies was lower than in normal and DS pregnancies.