A comparison of the variability of biological nutrients against depth and potential density.

The main biogeochemical nutrient distributions, along with ambient ocean temperature and the light field, control ocean biological productivity. Observations of nutrients are much sparser than physical observations of temperature and salinity, yet it is critical to validate biogeochemical models against these sparse observations if we are to successfully model biological variability and trends. Here we use data from the Bermuda Atlantic Time-series Study and the World Ocean Database 2005 to demonstrate quantitatively that over the entire globe a significant fraction of the temporal variability of phosphate, silicate and nitrate within the oceans is correlated with water density. The temporal variability of these nutrients as a function of depth is almost always greater than as a function of potential density, with he largest reductions in variability found within the main pycnocline. The greater nutrient variability as a function of depth occurs when dynamical processes vertically displace nutrient and density fields together on shorter timescales than biological adjustments. These results show that dynamical processes can have a significant impact on the instantaneous nutrient distributions. These processes must therefore be considered when modeling biogeochemical systems, when comparing such models with observations, or when assimilating data into such models.

Rich and famous: recognition-based judgment in the Sunday Times rich list

Recognition as a cue to judgment in a novel, multi-option domain (the Sunday Times Rich List) is explored. As in previous studies, participants were found to make use of name recognition as a cue to the presumed wealth of individuals. Names that were recognized were judged to be the richest name from amongst the set presented at above chance levels. This effect persisted across situations in which more than one name was recognized; recognition was used as an inclusion criterion for the sub-set of names to be considered the richest of the set presented. However, when the question was reversed, and a “poorest” judgment was required, use of recognition as an exclusion criterion was observed only when a single name was recognized. Reaction times when making these judgments also show a distinction between “richest” and “poorest” questions with recognition of none of the options taking the longest time to judge in the “richest” question condition and full recognition of all the names presented taking longest to judge in the “poorest” question condition. Implications for decision-making using simple heuristics are discussed.

When does ignorance make us smart? Additional factors guiding heuristic inference

“Fast & frugal” heuristics represent an appealing way of implementing bounded rationality and decision-making under pressure. The recognition heuristic is the simplest and most fundamental of these heuristics. Simulation and experimental studies have shown that this ignorance-driven heuristic inference can prove superior to knowledge based inference (Borges, Goldstein, Ortman & Gigerenzer, 1999; Goldstein & Gigerenzer, 2002) and have shown how the heuristic could develop from ACT-R’s forgetting function (Schooler & Hertwig, 2005). Mathematical analyses also demonstrate that, under certain conditions, a “less-is-more effect” will always occur (Goldstein & Gigerenzer, 2002). The further analyses presented in this paper show, however, that these conditions may constitute a special case and that the less-is-more effect in decision-making is subject to the moderating influence of the number of options to be considered and the framing of the question.

The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no com- parison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling ap- proaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.

Modelling the global coastal ocean

Shelf and coastal seas are regions of exceptionally high biological productivity, high rates of biogeochemical cycling and immense socio-economic importance. They are, however, poorly represented by the present generation of Earth system models, both in terms of resolution and process representation. Hence, these models cannot be used to elucidate the role of the coastal ocean in global biogeochemical cycles and the effects global change (both direct anthropogenic and climatic) are having on them. Here, we present a system for simulating all the coastal regions around the world (the Global Coastal Ocean Modelling System) in a systematic and practical fashion. It is based on automatically generating multiple nested model domains, using the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled to the European Regional Seas Ecosystem Model. Preliminary results from the system are presented. These demonstrate the viability of the concept, and we discuss the prospects for using the system to explore key areas of global change in shelf seas, such as their role in the carbon cycle and climate change effects on fisheries.

Civic geographies of architectural enthusiasm

In this short intervention, we introduce the display and walking tour that formed our contribution to the ‘civic geographies’ exhibition and session at the Royal Geographical Society (with IBG) Annual Conference in July 2012. We then move on to explore the notion of ‘civic geographies’ in relation to the architectural enthusiasm, specifically a strong emotional attachment to buildings, exhibited by members of The Twentieth Century Society. In doing so, we suggest that a more critical account of the role of enthusiasm in the civic realm is required for two important reasons: first, because such groups can be understood to be doing geography beyond the academy in the civic realm; and second, because enthusiast knowledges and practices are active in the (re)constitution of civic landscapes of various kinds. Enthusiasts participate in caring for buildings, preserving heritage, making community spaces, as well as creating and curating local histories. An understanding of who is participating in making these civic geographies, why, how, and with what consequences, is therefore crucial.