Exploring other childhoods through quantitative secondary analyses of large scale surveys: opportunities and challenges for children's geographers

This paper considers the potential contribution of secondary quantitative analyses of large scale surveys to the investigation of 'other' childhoods. Exploring other childhoods involves investigating the experience of young people who are unequally positioned in relation to multiple, embodied, identity locations, such as (dis)ability, 'class', gender, sexuality, ethnicity and race. Despite some possible advantages of utilising extensive databases, the paper outlines a number of methodological problems with existing surveys which tend to reinforce adultist and broader hierarchical social relations. It is contended that scholars of children's geographies could overcome some of these problematic aspects of secondary data sources by endeavouring to transform the research relations of large scale surveys. Such endeavours would present new theoretical, ethical and methodological complexities, which are briefly considered.

Variograms of ancillary data to aid sampling for soil surveys

To provide reliable estimates for mapping soil properties for precision agriculture requires intensive sampling and costly laboratory analyses. If the spatial structure of ancillary data, such as yield, digital information from aerial photographs, and soil electrical conductivity (EC) measurements, relates to that of soil properties they could be used to guide the sampling intensity for soil surveys. Variograins of permanent soil properties at two study sites on different parent materials were compared with each other and with those for ancillary data. The ranges of spatial dependence identified by the variograms of both sets of properties are of similar orders of magnitude for each study site, Maps of the ancillary data appear to show similar patterns of variation and these seem to relate to those of the permanent properties of the soil. Correlation analysis has confirmed these relations. Maps of kriged estimates from sub-sampled data and the original variograrns showed that the main patterns of variation were preserved when a sampling interval of less than half the average variogram range of ancillary data was used. Digital data from aerial photographs for different years and EC appear to show a more consistent relation with the soil properties than does yield. Aerial photographs, in particular those of bare soil, seem to be the most useful ancillary data and they are often cheaper to obtain than yield and EC data.

Dung and nest surveys: estimating decay rates

1. Wildlife managers often require estimates of abundance. Direct methods of estimation are often impractical, especially in closed-forest environments, so indirect methods such as dung or nest surveys are increasingly popular. 2. Dung and nest surveys typically have three elements: surveys to estimate abundance of the dung or nests; experiments to estimate the production (defecation or nest construction) rate; and experiments to estimate the decay or disappearance rate. The last of these is usually the most problematic, and was the subject of this study. 3. The design of experiments to allow robust estimation of mean time to decay was addressed. In most studies to date, dung or nests have been monitored until they disappear. Instead, we advocate that fresh dung or nests are located, with a single follow-up visit to establish whether the dung or nest is still present or has decayed. 4. Logistic regression was used to estimate probability of decay as a function of time, and possibly of other covariates. Mean time to decay was estimated from this function. 5. Synthesis and applications. Effective management of mammal populations usually requires reliable abundance estimates. The difficulty in estimating abundance of mammals in forest environments has increasingly led to the use of indirect survey methods, in which abundance of sign, usually dung (e.g. deer, antelope and elephants) or nests (e.g. apes), is estimated. Given estimated rates of sign production and decay, sign abundance estimates can be converted to estimates of animal abundance. Decay rates typically vary according to season, weather, habitat, diet and many other factors, making reliable estimation of mean time to decay of signs present at the time of the survey problematic. We emphasize the need for retrospective rather than prospective rates, propose a strategy for survey design, and provide analysis methods for estimating retrospective rates.

Recent patterns of change in vegetation structure and tree composition of British broadleaved woodland: evidence from large-scale surveys

Evidence is presented of widespread changes in structure and species composition between the 1980s and 2003–2004 from surveys of 249 British broadleaved woodlands. Structural components examined include canopy cover, vertical vegetation profiles, field-layer cover and deadwood abundance. Woods were located in 13 geographical localities and the patterns of change were examined for each locality as well as across all woods. Changes were not uniform throughout the localities; overall, there were significant decreases in canopy cover and increases in sub-canopy (2–10 m) cover. Changes in 0.5–2 m vegetation cover showed strong geographic patterns, increasing in western localities, but declining or showing no change in eastern localities. There were significant increases in canopy ash Fraxinus excelsior and decreases in oak Quercus robur/petraea. Shrub layer ash and honeysuckle Lonicera periclymenum increased while birch Betula spp. hawthorn Crataegus monogyna and hazel Corylus avellana declined. Within the field layer, both bracken Pteridium aquilinum and herbs increased. Overall, deadwood generally increased. Changes were consistent with reductions in active woodland management and changes in grazing and browsing pressure. These findings have important implications for sustainable active management of British broadleaved woodlands to meet silvicultural and biodiversity objectives.

Can sentiment surveys pre-empt real estate market activities?

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting the demand and supply activities. Our focus lies on sector-specific surveys targeting the players from the supply-side of both residential and non-residential real estate markets. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework, we test the efficacy of these indices by comparing them with other coincident indicators in predicting real estate returns. Overall, our analysis suggests that sentiment indicators convey important information which should be embedded in the modeling exercise to predict real estate market returns. Generally, sentiment indices show better information content than broad economic indicators. The goodness of fit of our models is higher for the residential market than for the non-residential real estate sector. The impulse responses, in general, conform to our theoretical expectations. Variance decompositions and out-of-sample predictions generally show desired contribution and reasonable improvement respectively, thus upholding our hypothesis. Quite remarkably, consistent with the theory, the predictability swings when we look through different phases of the cycle. This perhaps suggests that, e.g. during recessions, market players’ expectations may be more accurate predictor of the future performances, conceivably indicating a ‘negative’ information processing bias and thus conforming to the precautionary motive of consumer behaviour.

DIRTMAP: the geological record of dust.

Atmospheric dust is an important feedback in the climate system, potentially affecting the radiative balance and chemical composition of the atmosphere and providing nutrients to terrestrial and marine ecosystems. Yet the potential impact of dust on the climate system, both in the anthropogenically disturbed future and the naturally varying past, remains to be quantified. The geologic record of dust provides the opportunity to test earth system models designed to simulate dust. Records of dust can be obtained from ice cores, marine sediments, and terrestrial (loess) deposits. Although rarely unequivocal, these records document a variety of processes (source, transport and deposition) in the dust cycle, stored in each archive as changes in clay mineralogy, isotopes, grain size, and concentration of terrigenous materials. Although the extraction of information from each type of archive is slightly different, the basic controls on these dust indicators are the same. Changes in the dust flux and particle size might be controlled by a combination of (a) source area extent, (b) dust emission efficiency (wind speed) and atmospheric transport, (c) atmospheric residence time of dust, and/or (d) relative contributions of dry settling and rainout of dust. Similarly, changes in mineralogy reflect (a) source area mineralogy and weathering and (b) shifts in atmospheric transport. The combination of these geological data with process-based, forward-modelling schemes in global earth system models provides an excellent means of achieving a comprehensive picture of the global pattern of dust accumulation rates, their controlling mechanisms, and how those mechanisms may vary regionally. The Dust Indicators and Records of Terrestrial and MArine Palaeoenvironments (DIRTMAP) data base has been established to provide a global palaeoenvironmental data set that can be used to validate earth system model simulations of the dust cycle over the past 150,000 years.

Flat, flatter, flattest: the English Heritage wetland surveys in retrospect

Since 1973, English Heritage has supported four major regional surveys of England's wetlands- in the Somerset Levels, the Fens of Eastern England, the wetlands of the northwest of England and the Humber wetlands. Each of these projects developed a range of methods and techniques particular to the landscape that was studied and the results from the surveys reflect this diversity of approach. This paper compares and contrast these approaches, and evaluates their effect on the overall results of each of these surveys.

Time-lapse geophysical investigations over known archaeological features using electrical resistivity imaging and earth resistance

Electrical methods of geophysical survey are known to produce results that are hard to predict at different times of the year, and under differing weather conditions. This is a problem which can lead to misinterpretation of archaeological features under investigation. The dynamic relationship between a ‘natural’ soil matrix and an archaeological feature is a complex one, which greatly affects the success of the feature’s detection when using active electrical methods of geophysical survey. This study has monitored the gradual variation of measured resistivity over a selection of study areas. By targeting difficult to find, and often ‘missing’ electrical anomalies of known archaeological features, this study has increased the understanding of both the detection and interpretation capabilities of such geophysical surveys. A 16 month time-lapse study over 4 archaeological features has taken place to investigate the aforementioned detection problem across different soils and environments. In addition to the commonly used Twin-Probe earth resistance survey, electrical resistivity imaging (ERI) and quadrature electro-magnetic induction (EMI) were also utilised to explore the problem. Statistical analyses have provided a novel interpretation, which has yielded new insights into how the detection of archaeological features is influenced by the relationship between the target feature and the surrounding ‘natural’ soils. The study has highlighted both the complexity and previous misconceptions around the predictability of the electrical methods. The analysis has confirmed that each site provides an individual and nuanced situation, the variation clearly relating to the composition of the soils (particularly pore size) and the local weather history. The wide range of reasons behind survey success at each specific study site has been revealed. The outcomes have shown that a simplistic model of seasonality is not universally applicable to the electrical detection of archaeological features. This has led to the development of a method for quantifying survey success, enabling a deeper understanding of the unique way in which each site is affected by the interaction of local environmental and geological conditions.