ABSTRACTHydraulic fracturing, or ‘fracking’, involves the extraction of natural gas from shale formations deep underground using vertical and horizontal drilling technologies and vast quantities of chemically treated water injected into the wells under high pressure. Although commercial fracking has been underway in the USA since the 1990s, the industry is in its infancy elsewhere in the world. Rapid increases in gas production in the US have spurred interest in countries as far flung as the UK, China, Poland, Argentina and South Africa, although there is much uncertainty over potential gains and the environmental costs of the new technology (Buchan, 2013; European Commission, 2012a). In the UK, there are currently no companies actively fracking but several are undertaking exploratory drilling, and many policymakers, academics, environmental activists and energy industry specialists feel that the UK could be on the edge of a ‘fracking boom’. Some see fracking as a potential energy bonanza ensuring the UK's energy security well into the future, while others fear that it could bring significant harm to the environment and public health. In this article, we explore several dimensions of these uncertainties generally, and assess specifically some of the implications for the UK water environment. We also suggest ways in which the UK could learn from the experiences of fracking in the USA.

Spatial autocorrelation (SA)—the correlation among georeferenced observations arising from their relative locations in geographic space—has a history dating to the mid-1900s, although conceptual awareness of it dates back to the early 1900s. But SA is everywhere. It manifests itself in one- and two-dimensional synchronizations, exemplified by the experiment involving multiple metronomes sitting on a board that rests on two soda cans (illustrating an indirect, common factor SA source), or the aggregate flashing of fireflies created by their emission into the air of chemicals that stimulate nearby fireflies to light (illustrating a direct spatial interaction SA source). This latter outcome also can arise from mimicking behavior, as occurs with bandit bumble bees in a single meadow (i.e., when they rob a yellow rattler’s flower of nectar, their entry holes side in a given field tend to be unambiguously on only its left or right hand). The degree of organization in the geographic patterns that emerge signifies the level of positive SA. Such SA resulted in Heckscher discovering a new species of firefly in 2013. This type of SA is the basis of Nobel winner Schelling’s models of segregation, and The Economist (20 April 2013, p. 16) stating that regardless of class in Britain, geographical clusters of voters act like “political opinions derive from the air people breathe.” Moderate positive SA characterizes slider puzzles, magnetic sculpture toys, and television pictures. Meanwhile, negative SA relates to spatial patterns of competition. Although this nature of SA is rarely encountered in practice, it is illustrated by the Grand Prairie Independent School District’s (GPISD) attempts to increase the amount of money it receives from the state of Texas by holding annual events to attract students from surrounding school districts to attend its schools (Dallas Morning News, 9 January 2014); GPISD attempts to increase its enrollments by decreasing enrollments in its neighboring school districts. A timeline for the evolution of the SA concept helps establish its historically relevant literature. In the early 1800s, Laplace recognized autocorrelation—albeit serial for time series—by acknowledging that between day variations in barometric pressure readings tend to be much greater than within day readings. From 1914 to 1935, spatial series observational correlations were recognized by Student, then Yule, then both Stephan and Neprash, and then Fisher. This recognition set the stage for establishing the concept of SA. Moran and Geary did so in the early 1950s. In parallel, writing in French, Matheron and Krige also did so within the context of geostatistics. Next, more formal models of SA were formulated, first by Whittle, then by Mead, and finally by Cliff and Ord, whose numerous publications popularized the concept in the 1970s. One outcome of Cliff and Ord’s work was the coining of the phrase spatial econometrics in 1979 by Paelinck and Klaassen. Finally, as the century drew to a close, Griffith established the foundation of eigenvector spatial filtering, which extends SA analysis to the entire family of non-normal random variables.

ABSTRACTGround-ice exists widely on Mars and has been observed directly – the Phoenix Mars Lander revealed it in trenches only centimeters deep. The landscape surrounding Phoenix would not look out of place in the antarctic or in ice-age Europe – a stony plain patterned by a regular network of polygons. However, the generation of liquid water from ground-ice thaw on Mars is hotly debated. Models tell us that ground-ice on Mars cannot melt under current conditions, instead subliming directly to vapour without becoming liquid, and geomorphological evidence of sublimation is abundant. However, recent very high resolution images of Mars from HiRISE (High Resolution Imaging Science Experiment) now reveal suites of landforms consistent with ground-ice thaw and resulting liquid flows. These landforms first remind us of the importance of testing our models by observation, but might instead hint that the chemistry of Martian ground-ice allows it to thaw at unexpectedly low temperatures.

(2015). Research on young people's understandings of distant places. Geography: Vol. 100, No. 2, pp. 110-113.

ABSTRACTThis article discusses the importance of distinctions in the field of geography education. The aim is to help clarify the meaning of terms that are regularly contested, including education, geography, curriculum and pedagogy. The purpose is not to argue that boundaries between these categories are fixed, or that they cannot ever be transcended. Rather, a case is made that understanding what is distinctive about each aids the teacher in effective classroom teaching. In geography, three approaches are identified: spatial, areal and humanenvironment relations. Learning geography means combining disciplinary approaches with knowledge and skills: the curriculum. The article concludes by recognising the ways in which education, geography, curriculum and pedagogy are intimately connected.

The earth’s surface is heterogeneous in nature. This feature of the earth’s crust implies that the distribution in space of its natural resources is also varied. Most natural resources vary in a continuum rather than in a discrete way. However, our cognitive system works better in discretely classifying the world that surrounds us. Therefore, we divide all the observed features in nature into non-overlapping categories, through a process called “categorization.” Then we order, name, and group objects previously created in our minds in such categories, producing classifications, either consciously or unconsciously. Most of these classifications are hierarchical (splitting the natural continua in discernible classes by using nested classifications of increasing refinement). A scientific universal taxonomy is a mental construct that inventories the diversity of the universe studied at the global level by experts, such as living organisms, rocks, and soils, conforming to explicit rules. The diversity of a natural resource is based on these grounds. Therefore, the quantification of any diversity always depends on the number of classes and categories of the taxonomy used. As a corollary, the inventory of diversities will always suffer biases and limitations, being provisionally from a historical perspective. At first instance, the notion of diversity of a given natural resource is clear and intuitive. All naturalists recognize that some territories are more diverse than others, regardless of whether they are interested in species, soils, landforms, rocks, etc. Therefore, it is impossible to consider a particular naturalist as the founder of the analysis of diversity. In ecology, the first patterns and theories in biodiversity date back to the first decades of the 20th century. In contrast, the interest of the scientific community in the diversity of the abiotic natural resources began in the last decade of the 20th century, although it is possible to find some exceptional publications before that date. The starting point of this article goes back to the first attempts to operationalize the concept and the first indexes for its estimation.