2 resultados para Nmr Structure And Dymanics Of Asc2
em DigitalCommons@University of Nebraska - Lincoln
Resumo:
An investigation was made of the communities of gill monogene genus Dactylogyrus (Platyhelminthes, Monogenea) and the populations of blackspot parasite (Platyhelminthes, Trematoda) of Pimephales promelas, Notropis stramineus, and Semotilus atromaculatus in 3 distinct sites along the 3 converging tributaries in southeastern Nebraska from 2004 to 2006. This work constitutes the first multi-site, multi-year study of a complex community of Dactylogyrus spp. and their reproductive activities on native North American cyprinid species. The biological hypothesis that closely related species with direct lifecycles respond differently to shared environmental conditions was tested. It was revealed that in this system that, Cyprinid species do not share Dactylogyrus species, host size and sex are not predictive of infection, and Dactylogyrus community structure is stable, despite variation in seasonal occurrence and populations among sites. The biological hypothesis that closely related species have innate differences in reproductive activities that provide structure to their populations and influence their roles in the parasite community was tested. It was revealed that in this system, host size, sex, and collection site are not predictive of reproductive activities, that egg production is not always continuous and varies in duration among congeners, and that recruitment of larval Dactylogyrus is not continuous across parasites’ reproductive periods. Hatch timing and host availability, not reproductive timing, are the critical factors determining population dynamics of the gill monogenes in time and space. Lastly, the biological hypothesis that innate blackspot biology is responsible for parasite host-specificity, host recruitment strategies and parasite population structure was tested. Field collections revealed that for blackspot, host size, sex, and collection month and year are not predictive of infection, that parasite cysts survive winter, and that host movement is restricted among the 3 collection sites. Finally, experimental infections of hosts with cercaria isolated from 1st intermediate snail hosts reveal that cercarial biology, not environmental circumstances, are responsible for differences in infection among hosts.
Resumo:
1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.