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.

Fox-hunting in England and Wales: its contribution to the management of woodland and other habitats

Hunting foxes with hounds has been a countryside pursuit in Britain since the 17th Century, but its effect nationally on habitat management is little understood by the general public. A survey questionnaire was distributed to 163 mounted fox hunts of England and Wales to quantify their management practices in woodland and other habitat. Ninety-two hunts (56%), covering 75,514 km(2), returned details on woodland management motivated by the improvement of their sport. The management details were verified via on-site visits for a sample of 200 woodlands. Following verification, the area of woodlands containing the management was conservatively estimated at 24,053 (+/- 2241) ha, comprising 5.9% of woodland area within the whole of the area hunted by the 92 hunts. Management techniques included: tree planting, coppicing, felling, ride and perimeter management. A case study in five hunt countries in southern England examined, through the use of botanical survey and butterfly counts, the consequences of the hunt management on woodland ground flora and butterflies. Managed areas had, within the last 5 years, been coppiced and rides had been cleared. Vegetation cover in managed and unmanaged sites averaged 86% and 64%, respectively, and managed areas held on average 4 more plant species and a higher plant diversity than unmanaged areas (Shannon index of diversity: 2.25 vs. 1.95). Both the average number of butterfly species (2.2 vs. 0.3) and individuals counted (4.6 vs. 0.3) were higher in the managed than unmanaged sites.

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.