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We demonstrated the ability of a mechanistic habitat selection model to predict habitat selection of brown trout (Salmo trutta) and mountain whitefish (Prosopium williamsoni) during summer and winter conditions in the Blacksmith Fork River, Utah. By subtracting energy costs and losses from the gross energy intake rate (GEI) obtained through simulation of prey capture, the model calculates the potential net energy intake rate (NEI) of a given stream position, which is essentially the rate of energy intake available for growth and reproduction. The prey capture model incorporates the size, swimming speed, and reaction distance of the fish; the velocity, depth, temperature, and turbidity of the water; and the density and size composition of the drifting invertebrates. The results suggest that during both summer and winter, the brown trout and mountain whitefish in our study reach avoided locations providing low NEI and preferred locations providing a high ratio of NEI to the swimming cost (SC) at the focal position of the fish (NEI/SC). This supports the idea that the drift-feeding fish in this study selected stream positions that provided adequate NEI for the least amount of swimming effort.

Surveys of colonial-nesting waterbirds are needed to assess population trends and gain insight into the health of wetland ecosystems. Use of unmanned aerial systems (UAS) for such surveys has increased over the past decade, but possible sources of bias in surveys conducted with UAS have not been examined. We examined possible visibility biases associated with using a UAS to survey waterbird colonies in cypress-tupelo watersheds and coastal island habitats in Texas in 2016. We used known numbers of four waterbird decoy types, including Black Skimmers (Rynchops niger), terns, and white-and dark-plumaged herons, to estimate their detectability in each habitat. Six observers independently counted decoys from aerial imagery mosaics taken with a consumer-grade, off-the-shelf quadcopter drone. We used generalized linear mixed-effects models to estimate detection probabilities of each decoy type. Black Skimmers at the coastal island had a detection probability of just 53%. Detectability of both white-and dark-plumaged herons was lower in the canopied cypress-tupelo habitat than the coastal island. In addition, cloud cover > 50% further reduced detectability of white heron decoys in cypress-tupelo habitat. Use of the double-count method yielded biased-low abundance estimates for white-and dark-plumaged herons in canopied sites, suggesting that habitat differences were a greater source of bias than observer error. Black Skimmers were the only decoy type to be imperfectly detected at the coastal island, a surprising result given the stark contrast of their plumage with their sand and shell nesting substrate. Our results indicate that UAS-derived photographic surveys are prone to low detection probabilities at sites where vegetation occludes nests. In habitats without canopy, however, UAS surveys show promise for obtaining accurate counts of terns, white herons, and dark herons. 4 Corresponding author. monitoreos utilizando UAS son prometedores para obtener conteos precisos de gaviotas y garzas blancas y oscuras.

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