The BorrowBike

The BorrowBike is turning UP\u27s bike rental system from an inconvenient process to a hassle-free swipe of a card. BorrowBike\u27s smart lock and online web application streamlines the check-out process and allows bikes to be rented at any time of the day.https://pilotscholars.up.edu/egr_project/1025/thumbnail.jp

Science Priorities for Seamounts: Research Links to Conservation and Management

Seamounts shape the topography of all ocean basins and can be hotspots of biological activity in the deep sea. The Census of Marine Life on Seamounts (CenSeam) was a field program that examined seamounts as part of the global Census of Marine Life (CoML) initiative from 2005 to 2010. CenSeam progressed seamount science by collating historical data, collecting new data, undertaking regional and global analyses of seamount biodiversity, mapping species and habitat distributions, challenging established paradigms of seamount ecology, developing new hypotheses, and documenting the impacts of human activities on seamounts. However, because of the large number of seamounts globally, much about the structure, function and connectivity of seamount ecosystems remains unexplored and unknown. Continual, and potentially increasing, threats to seamount resources from fishing and seabed mining are creating a pressing demand for research to inform conservation and management strategies. To meet this need, intensive science effort in the following areas will be needed: 1) Improved physical and biological data; of particular importance is information on seamount location, physical characteristics (e.g. habitat heterogeneity and complexity), more complete and intensive biodiversity inventories, and increased understanding of seamount connectivity and faunal dispersal; 2) New human impact data; these shall encompass better studies on the effects of human activities on seamount ecosystems, as well as monitoring long-term changes in seamount assemblages following impacts (e.g. recovery); 3) Global data repositories; there is a pressing need for more comprehensive fisheries catch and effort data, especially on the high seas, and compilation or maintenance of geological and biodiversity databases that underpin regional and global analyses; 4) Application of support tools in a data-poor environment; conservation and management will have to increasingly rely on predictive modelling techniques, critical evaluation of environmental surrogates as faunal “proxies”, and ecological risk assessment

Ocean-scale prediction of whale shark distribution

Aim: Predicting distribution patterns of whale sharks (Rhincodon typus, Smith 1828) in the open ocean remains elusive owing to few pelagic records. We developed multivariate distribution models of seasonally variant whale shark distributions derived from tuna purse-seine fishery data. We tested the hypotheses that whale sharks use a narrow temperature range, are more abundant in productive waters and select sites closer to continents than the open ocean. Location: Indian Ocean. Methods: We compared a 17-year time series of observations of whale sharks associated with tuna purse-seine sets with chlorophyll a concentration and sea surface temperature data extracted from satellite images. Different sets of pseudo-absences based on random distributions, distance to shark locations and tuna catch were generated to account for spatiotemporal variation in sampling effort and probability of detection. We applied generalized linear, spatial mixed-effects and Maximum Entropy models to predict seasonal variation in habitat suitability and produced maps of distribution. Results: The saturated generalized linear models including bathymetric slope, depth, distance to shore, the quadratic of mean sea surface temperature, sea surface temperature variance and chlorophyll a had the highest relative statistical support, with the highest percent deviance explained when using random pseudo-absences with fixed effect-only models and the tuna pseudo-absences with mixed-effects models (e.g. 58% and 26% in autumn, respectively). Maximum Entropy results suggested that whale sharks responded mainly to variation in depth, chlorophyll a and temperature in all seasons. Bathymetric slope had only a minor influence on the presence. Main conclusions: Whale shark habitat suitability in the Indian Ocean is mainly correlated with spatial variation in sea surface temperature. The relative influence of this predictor provides a basis for predicting habitat suitability in the open ocean, possibly giving insights into the migratory behaviour of the world’s largest fish. Our results also provide a baseline for temperature-dependent predictions of distributional changes in the future.Ana Sequeira, Camille Mellin, David Rowat, Mark G. Meekan and Corey J. A. Bradsha