A factorial design experiment as a pilot study for noninvasive genetic sampling

Noninvasive genetic sampling has increasingly been used in ecological and conservation studies during the last decade. A major part of the noninvasive genetic literature is dedicated to the search for optimal protocols, by comparing different methods of collection, preservation and extraction of DNA from noninvasive materials. However, the lack of quantitative comparisons among these studies and the possibility that different methods are optimal for different systems make it difficult to decide which protocol to use. Moreover, most studies that have compared different methods focused on a single factor – collection, preservation or extraction – while there could be interactions between these factors. We designed a factorial experiment, as a pilot study, aimed at exploring the effect of several collection, preservation and extraction methods, and the interactions between them, on the quality and amplification success of DNA obtained from Asiatic wild ass (Equus hemionus) faeces in Israel. The amplification success rates of one mitochondrial DNA and four microsatellite markers differed substantially as a function of collection, preservation and extraction methods and their interactions. The most efficient combination for our system integrated the use of swabs as a collection method with preservation at ?20 °C and with the Qiagen DNA Stool Kit with modifications as the DNA extraction method. The significant interaction found between the collection, preservation methods and the extraction methods reinforces the importance of conducting a factorial design experiment, rather than examining each factor separately, as a pilot study before initiating a full‐scale noninvasive research project.     

Modeling Black-Tailed Deer Population Dynamics Using Structured and Unstructured Approaches

Abstract: We used cohort analysis to reconstruct the female segment of a Columbian black-tailed deer (Odocoileus hemionus columbianus) population from 1979 to 2000 in the western Cascades of Washington, USA. We used reconstructed population estimates and age class representations to analyze relationships between population change and female density, forage availability, and weather influences. We applied stage structured and unstructured modeling approaches and used information-theoretic methods to select the best models. We used habitat covariates to develop predictive functions for fertility and survival parameters in structured models. The best structured and unstructured models were composed of combinations of factors including population density, forage availability, and winter weather. Structured and unstructured models could assist with management of black-tailed deer by providing the ability to predict deer population change given covariate values.