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Predator diet can play an important role in facilitating detection of predation risk among prospective prey, and such detection should have adaptive significance in reducing mortality in environments where not all predators confer similar risk. In the laboratory, we tested behavioural and morphological responses of tadpoles from two congeneric frog species (bullfrog ( Rana catesbeiana Shaw, 1802) and mink frog ( Rana septentrionalis Baird, 1854)) to cues from an odonate predator (genus Aeshna Fabricius, 1775). In a separate experiment we found that both frog species had similar baseline vulnerability to Aeshna predation, implying that species’ responses to predators feeding on conspecific vs. congeneric prey also would be similar. Both species reduced their activity in the presence of predators feeding on tadpoles of either species vs. those fed invertebrates (Libellulidae) or not subjected to predators (controls). Bullfrog tadpoles grew bigger than controls when exposed to predators fed mink frog tadpoles only, whereas mink frogs failed to show a comparable response. Neither species exhibited changes in shape that were attributable to predator diet. Our results suggest that closely related frog species do not distinguish between predators feeding on conspecific vs. congeneric prey, implying that selection favours generalized antipredator responses when prey species are subject to similar predation risk.

Besides the evaluation of the volume of standing trees, goals of forest inventories include collecting geophysical information and monitoring fragile ecosystems. In the province of Quebec, Canada, their implementation faces challenging methodological problems. The survey area covers a large territory that is hardly accessible and has a diverse forest. The main operational goals are to spread the sampled plots throughout the survey area and to capture, in the sample, the forest heterogeneity while keeping the cost at a reasonable level. In many inventories, a two‐dimensional systematic sampling design is applied, and the rich auxiliary information is only used at the estimation stage. We show how to use modern and advanced sampling techniques to improve the planning of forest inventories and meet complex operational goals. For the Quebec forest inventory, we build a two‐stage sampling design that has clusters of plots to optimize field work and predetermined sample sizes for forest types. Constraints of spreading the sample in the whole territory and of balancing according to auxiliary variables are also implemented. To meet these requirements, we use unequal inclusion probabilities, balanced sampling, highly stratified balanced sampling, and sample spreading. The impact of these novel techniques on the implementation of requirements and on the precision of survey estimates is investigated using Quebec inventory data. Copyright © 2015 John Wiley & Sons, Ltd.

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