Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

Within the marine environment, aerial surveys have historically centred on apex predators, such as pinnipeds, cetaceans and sea birds. However, it is becoming increasingly apparent that the utility of this technique may also extend to subsurface species such as pre-spawning fish stocks and aggregations of jellyfish that occur close to the surface. In light of this, we tested the utility of aerial surveys to provide baseline data for 3 poorly understood scyphozoan jellyfish found throughout British and Irish waters: Rhizostoma octopus, Cyanea capillata and Chrysaora hysoscella. Our principal objectives were to develop a simple sampling protocol to identify and quantify surface aggregations, assess their consistency in space and time, and consider the overall applicability of this technique to the study of gelatinous zooplankton. This approach provided a general understanding of range and relative abundance for each target species, with greatest suitability to the study of R. octopus. For this species it was possible to identify and monitor extensive, temporally consistent and previously undocumented aggregations throughout the Irish Sea, an area spanning thousands of square kilometres. This finding has pronounced implications for ecologists and fisheries managers alike and, moreover, draws attention to the broad utility of aerial surveys for the study of gelatinous aggregations beyond the range of conventional ship-based techniques.

Application of air quality combination forecasting to Bogota

The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. © 2014 Elsevier Ltd.