Habitat use and hybridisation between the Rocky Mountain sculpin (Cottus sp.) and slimy sculpin (Cottus cognatus)

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On the bias produced by quality scores in meta-analysis,and a hierarchical view of proposed solutions

Results from better quality studies should in some sense be more valid or more accurate than results from other studies, and as a consequence should tend to be distributed differently from results of other studies. To date, however, quality scores have been poor predictors of study results. We discuss possible reasons and remedies for this problem. It appears that 'quality' (whatever leads to more valid results) is of fairly high dimension and possibly non-additive and nonlinear, and that quality dimensions are highly application-specific and hard to measure from published information. Unfortunately, quality scores are often used to contrast, model, or modify meta-analysis results without regard to the aforementioned problems, as when used to directly modify weights or contributions of individual studies in an ad hoc manner. Even if quality would be captured in one dimension, use of quality scores in summarization weights would produce biased estimates of effect. Only if this bias were more than offset by variance reduction would such use be justified. From this perspective, quality weighting should be evaluated against formal bias-variance trade-off methods such as hierarchical (random-coefficient) meta-regression. Because it is unlikely that a low-dimensional appraisal will ever be adequate (especially over different applications), we argue that response-surface estimation based on quality items is preferable to quality weighting. Quality scores may be useful in the second stage of a hierarchical response-surface model, but only if the scores are reconstructed to maximize their correlation with bias.     

Modeling flight activity and population dynamics of the pine engraver, Ips pini, in the Great Lakes region: effects of weather and predators over short time scales

Ascertaining the relative effects of factors such as weather and predation on population dynamics, and determining the time scales on which they operate, is important to our understanding of basic ecology and pest management. In this study, we sampled the pine engraver Ips pini (Say) (Coleoptera: Scolytidae) and its predominant predators Thanasimus dubius (F.) (Coleoptera: Cleridae) and Platysoma cylindrica (Paykull) (Coleoptera: Histeridae) in red pine plantations in Wisconsin, USA, over 2 years. We sampled both the prey and predators using flight traps baited with the synthetic aggregation pheromone of I. pini. Flight models were constructed using weather variables (temperature and precipitation), counts of bark beetles and their predators, and temporal variables to incorporate possible effects of seasonality. The number of I. pini per weekly collection period was temperature dependent and decreased with the number of predators, specifically T. dubius in 2001 and P. cylindrica in 2002. The number of predators captured each week was also weather dependent. The predators had similar seasonal phenologies, and the number of each predator species was positively correlated with the other. Including a term for the number of prey did not improve the model fits for either predator for either year. Our results suggest that exogenous weather factors strongly affect the flight activity of I. pini, but that its abundance is also affected by direct density-dependent processes acting over weekly time scales. Adult predation during both colonization and dispersal are likely processes yielding these dynamics.