Experimental evaluation of realized niche models for predicting responses of plant species to a change in environmental conditions

Abstract. We estimated, using logistic regression techniques, the realized niches of the four dominant species in an experimental marsh complex located in the Delta Marsh, Manitoba, Canada. These models were then used to predict the probability of occurrence of these species in selected elevation ranges when water levels were raised in 1985 either 0, 30 or 60 cm above the long-term normal water level. These realized-niche models were calculated using elevation and species data collected in 1980. After having been eliminated by two years of deep flooding, the emergent vegetation in this complex had been re-established during a drawdown beginning in either 1983 or 1984. Our hypothesis was that from 1985 to 1989 the frequencies of occurrence of species in selected elevation ranges would converge to their probabilities predicted from the 1980 logistic models. This was not borne out by our results. Actual frequencies and predicted probabilities of occurrence of a species were similar at best less than 40% and then mostly in the control (0 cm) treatment. The realized-niche models were not adequate to predict the distribution of emergents after an increase in water level in the short term because the emergent species did not migrate upslope. Emergent species in the medium and high treatments either (1) died out - Scolochloa festucacea and Scirpus lacustris - after 3 yr because they could not survive permanent flooding, (2) stayed where they were - Phragmites australis - because they were unable to move upslope through clonal growth, or (3) became more widespread - Typha glauca only because of the expansion of small local populations already established in 1985 in areas dominated formerly by other species.     

Unraveling of the polymorphic C lambda 2-C lambda 3 amplification and the Ke+Oz- polymorphism in the human Ig lambda locus

Two polymorphisms of the human Ig(lambda) (IGL) locus have been described. The first polymorphism concerns a single, 2- or 3-fold amplification of 5.4 kb of DNA in the C(lambda)2-C(lambda)3 region. The second polymorphism is the Mcg(-)Ke(+)Oz(-) isotype, which has only been defined via serological analyses in Bence-Jones proteins of multiple myeloma patients and was assumed to be encoded by a polymorphic C(lambda)2 segment because of its high homology with the Mcg(-)Ke(-)Oz(-) C(lambda)2 isotype. It has been speculated that the Mcg(-)Ke(+)Oz(-) isotype might be encoded by a C(lambda) gene segment of the amplified C(lambda)2-C(lambda)3 region. We now unraveled both IGL gene polymorphisms. The amplification polymorphism appeared to result from a duplication, triplication, or quadruplication of a functional J-C(lambda)2 region and is likely to have originated from unequal crossing over of the J-C(lambda)2 and J-C(lambda)3 region via a 2.2-kb homologous repeat. The amplification polymorphism was found to result in the presence of one to five extra functional J-C(lambda)2 per genome regions, leading to decreased Ig(kappa):Ig(lambda) ratios on normal peripheral blood B cells. Via sequence analysis, we demonstrated that the Mcg(-)Ke(+)Oz(-) isotype is encoded by a polymorphic C(lambda)2 segment that differs from the normal C(lambda)2 gene segment at a single nucleotide position. This polymorphism was identified in only 1.5% (2 of 134) of individuals without J-C(lambda)2 amplification polymorphism and was not found in the J-C(lambda)2 amplification polymorphism of 44 individuals, indicating that the two IGL gene polymorphisms are not linked.     

Modelling parasite aggregation: disentangling statistical and ecological approaches

The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts.