Geology topics

L. Huang

Publications and source records attributed to L. Huang.

2 recordsLinked to original sources

USGS2011

Microbial reduction of structural iron in interstratified illite-smectite minerals by a sulfate-reducing bacterium

Clay minerals are ubiquitous in soils, sediments, and sedimentary rocks and could coexist with sulfate‐reducing bacteria (SRB) in anoxic environments, however, the interactions of clay minerals and SRB are not well understood. The objective of this study was to understand the reduction rate and capacity of structural Fe(III) in dioctahedral clay minerals by a mesophilic SRB, Desulfovibrio vulgaris and the potential role in catalyzing smectite illitization. Bioreduction experiments were performed in batch systems, where four different clay minerals (nontronite NAu‐2, mixed‐layer illite‐smectite RAr‐1 and ISCz‐1, and illite IMt‐1) were exposed to D. vulgaris in a non‐growth medium with and without anthraquinone‐2,6‐disulfonate (AQDS) and sulfate. Our results demonstrated that D. vulgaris was able to reduce structural Fe(III) in these clay minerals, and AQDS enhanced the reduction rate and extent. In the presence of AQDS, sulfate had little effect on Fe(III) bioreduction. In the absence of AQDS, sulfate increased the reduction rate and capacity, suggesting that sulfide produced during sulfate reduction reacted with the phyllosilicate Fe(III). The extent of bioreduction of structural Fe(III) in the clay minerals was positively correlated with the percentage of smectite and mineral surface area of these minerals. X‐ray diffraction, and scanning and transmission electron microscopy results confirmed formation of illite after bioreduction. These data collectively showed that D. vulgaris could promote smectite illitization through reduction of structural Fe(III) in clay minerals.

Geobiology↗

USGS2010

Sampling considerations for disease surveillance in wildlife populations

Disease surveillance in wildlife populations involves detecting the presence of a disease, characterizing its prevalence and spread, and subsequent monitoring. A probability sample of animals selected from the population and corresponding estimators of disease prevalence and detection provide estimates with quantifiable statistical properties, but this approach is rarely used. Although wildlife scientists often assume probability sampling and random disease distributions to calculate sample sizes, convenience samples (i.e., samples of readily available animals) are typically used, and disease distributions are rarely random. We demonstrate how landscape-based simulation can be used to explore properties of estimators from convenience samples in relation to probability samples. We used simulation methods to model what is known about the habitat preferences of the wildlife population, the disease distribution, and the potential biases of the convenience-sample approach. Using chronic wasting disease in free-ranging deer (Odocoileus virginianus) as a simple illustration, we show that using probability sample designs with appropriate estimators provides unbiased surveillance parameter estimates but that the selection bias and coverage errors associated with convenience samples can lead to biased and misleading results. We also suggest practical alternatives to convenience samples that mix probability and convenience sampling. For example, a sample of land areas can be selected using a probability design that oversamples areas with larger animal populations, followed by harvesting of individual animals within sampled areas using a convenience sampling method.

Journal of Wildlife Management↗