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Multiscale scenarios for nature futures Targets for human development are increasingly connected with targets for nature, however, existing scenarios do not explicitly address this relationship. Here, we outline a strategy to generate scenarios centred on our relationship with nature to inform decision-making at multiple scales.

Abstract:This paper addresses the future of environmental assessment (EA)

Lightweight, portable unmanned aerial vehicles (UAVs) or ‘drones’ are set to become a key component of a water resource management (WRM) toolkit, but are currently not widely used in this context. In practical WRM there is a growing need for fine-scale responsive data, which cannot be delivered from satellites or aircraft in a cost-effective way. Such a capability is needed where water supplies are located in spatially heterogeneous dynamic catchments. In this review, we demonstrate the step change in hydrological process understanding that could be delivered if WRM employed UAVs. The paper discusses a range of pragmatic concepts in UAV science for cost-effective and practical WRM, from choosing the right sensor and platform combination through to practical deployment and data processing challenges. The paper highlights that multi-sensor approaches, such as combining thermal imaging with fine-scale structure-from-motion topographic models, are currently best placed to assist in WRM decision-making because they provide a means of monitoring the spatio-temporal distribution of sources, sinks, and flows of water through landscapes. The manuscript highlights areas where research is needed to support the integration of UAVs into practical WRM, for example, in improving positional accuracy through integration of differential global positioning system sensors, and developing intelligent control of UAV platforms to optimize the accuracy of spatial data capture.

Appropriate measurement of competitive balance is central to the economic analysis of professional sports leagues. We examine the distributional properties of the ratio of standard deviations (RSD) of points percentages, the most widely used measure of competitive balance in the sports economics literature, in comparison with other standard-deviation-based measures. Simulation methods are used to evaluate the effects of changes in season length on the distributions of competitive balance measures for different distributions of the strengths of teams in a league. The popular RSD measure performs as expected only in cases of perfect balance; if there is imbalance in team strengths, its distribution is sensitive to changes in season length. It is therefore not recommended for comparisons of competitive balance for different sports leagues with different numbers of teams and/or games played. (JEL L83, D63, C63) * We are grateful to the co-editor, Jeff Borland, and an anonymous referee for their very helpful and constructive suggestions.