Parasitological Data as Monitors of Environmental Health

When an appropriate fish host is selected, analysis of its parasites offers a useful, reliable, economical, telescoped indication or monitor of environmental health. The value of that information increases when corroborated by another non-parasitological technique. The analysis of parasites is not necessarily simple because not all hosts serve as good models and because the number of species, presence of specific species, intensity of infections, life histories of species, location of species in hosts, and host response for each parasitic species have to be addressed individually to assure usefulness of the tool. Also, different anthropogenic contaminants act in a distinct manner relative to hosts, parasites, and each other as well as being influenced by natural environmental conditions. Total values for all parasitic species infecting a sample cannot necessarily be grouped together. For example, an abundance of numbers of either species or individuals can indicate either a healthy or an unhealthy environment, depending on the species of parasite. Moreover, depending on the parasitic species, its infection, and the time chosen for collection/examination, the assessment may indicate a chronic or acute state of the environmental health. For most types of analyses, the host should be one that has a restricted home range, can be infected by numerous species of parasites, many of which have a variety of additional hosts in their life cycles, and can be readily sampled. Data on parasitic infections in the western mosquitofish (Gambusia affinis), a fish that meets the criteria in two separate studies, illustrate the usefulness of that host as a model to indicate both healthy and detrimentally influenced environments. In those studies, species richness, intensity of select species, host resistance, other hosts involved in life cycles, and other factors all relate to site and contaminating discharge.

Health Assessment of Weddell Seals, Leptonychotes weddellii, in McMurdo Sound, Antarctica

The demography of Weddell seals in eastern McMurdo Sound, Antarctica, has been well studied during the past three decades (e.g. Stirling 1971; Siniff et al. 1977; Testa and Siniff 1987; Hastings and Testa 1998; Gelatt et al. 2001). Detailed life-history data are available on thousands of seals tagged as pups in McMurdo Sound, making this population a rich resource for wildlife health studies because health parameters can be evaluated in the light of reproductive histories and genetic relationships of several generations of tagged seals. Recently, evidence of exposure to diseases generally associated with domestic animals and feral wildlife has been detected in Antarctic wildlife (Austin and Webster 1993; Olsen et al. 1996; Gardner et al. 1997; Retamal et al. 2000; Foster et al. 2002) and this has generated concern and debate regarding the risks of disease introduction to Antarctic wildlife. Antibodies to viruses that have caused large die-offs in phocids in other areas of the world have been detected in Weddell seals (Bengtson et al. 1991), and there is a historical report of a mass die-off of crabeater seals that may have had a viral etiology (Laws and Taylor 1957).

Genetic Mapping of Quantitative Trait Loci Associated with Bioenergy Traits, and The Assessment of Genetic Variability in Sweet Sorghum (Sorghum bicolor (L.). Moench)

Sweet sorghum, a botanical variety of sorghum is a potential source of bioenergy because high sugar levels accumulate in its stalks. The objectives of this study were to explore the global diversity of sweet sorghum germplasm, and map the genomic regions that are associated with bioenergy traits. In assessing diversity, 142 sweet sorghum accessions were evaluated with three marker types (SSR, SRAP, and morphological markers) to determine the degree of relatedness among the accessions. The traits measured (anthesis date [AD], plant height [PH], biomass yield [BY], and moisture content [MC]) were all significantly different (P<0.05) among accessions. Morphological marker clustered the accessions into five groups based on PH, MC and AD. The three traits accounted for 92.5% of the variation. There were four and five groups based on SRAP and SSR data respectively classifying accessions mainly on their origin or breeding history. The observed difference between SSR and SRAP based clusters could be attributed to the difference in marker type. SSRs amplify any region of the genome whereas SRAP amplify the open reading frames and promoter regions. Comparing the three marker-type clusters, the markers complimented each other in grouping accessions and would be valuable in assisting breeders to select appropriate lines for crossing. In evaluating QTLs that are associated with bioenergy traits, 165 recombinant inbred lines (RILs) were planted at four environments in Nebraska. A genetic linkage map constructed spanned a length of 1541.3 cM, and generated 18 linkage groups that aligned to the 10 sorghum chromosomes. Fourteen QTLs (6 for brix, 3 for BY, 2 each for AD and MC, and 1 for PH) were mapped. QTLs for the traits that were significantly correlated, colocalized in two clusters on linkage group Sbi01b. Both parents contributed beneficial alleles for most of traits measured, supporting the transgressive segregation in this population. Additional work is needed on exploiting the usefulness of chromosome 1 in breeding sorghum for bioenergy.

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

An Assessment of Local Peoples Opinions of Community Conservation Initiatives in Relation to Livelihood Strategies in Kenya

Abstract This paper analyzed the changing livelihood strategies in Kenya, and their cultural impacts via a literature review. I then combined this understanding with the data I collected while in Kenya to examine the opinions local people have of community conservation initiatives, based on their changing livelihood strategies. I expected to find that the following factors would have an affect on the opinions local community members have of community conservation initiatives: livelihood strategy, gender, ethnicity, whether or not they believe the distribution of benefits coming from wildlife conservation is equitable, what issues they would like to see improved within community conservation initiatives, and their overall satisfaction with community conservation initiatives. Through correlation tests done using SPSS (Statistical Package for Social Scientists) I found that all five of these factors do influence the perceptions local community members have of community conservation initiatives within the Amboseli region in Kenya.