Estimating the Density of Honeybee Colonies across Their Natural Range to Fill the Gap in Pollinator Decline Censuses

Although pollinator declines are a global biodiversity threat, the demography of the western honeybee (Apis mellifera) has not been considered by conservationists because it is biased by the activity of beekeepers. To fill this gap in pollinator decline censuses and to provide a broad picture of the current status of honeybees across their natural range, we used microsatellite genetic markers to estimate colony densities and genetic diversity at different locations in Europe, Africa, and central Asia that had different patterns of land use. Genetic diversity and colony densities were highest in South Africa and lowest in Northern Europe and were correlated with mean annual temperature. Confounding factors not related to climate, however, are also likely to influence genetic diversity and colony densities in honeybee populations. Land use showed a significantly negative influence over genetic diversity and the density of honeybee colonies over all sampling locations. In Europe honeybees sampled in nature reserves had genetic diversity and colony densities similar to those sampled in agricultural landscapes, which suggests that the former are not wild but may have come from managed hives. Other results also support this idea: putative wild bees were rare in our European samples, and the mean estimated density of honeybee colonies on the continent closely resembled the reported mean number of managed hives. Current densities of European honeybee populations are in the same range as those found in the adverse climatic conditions of the Kalahari and Saharan deserts, which suggests that beekeeping activities do not compensate for the loss of wild colonies. Our findings highlight the importance of reconsidering the conservation status of honeybees in Europe and of regarding beekeeping not only as a profitable business for producing honey, but also as an essential component of biodiversity conservation.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

Error sensitive historical GIS: Identifying areal interpolation errors in time series data

Historical GIS has the potential to re-invigorate our use of statistics from historical censuses and related sources. In particular, areal interpolation can be used to create long-run time-series of spatially detailed data that will enable us to enhance significantly our understanding of geographical change over periods of a century or more. The difficulty with areal interpolation, however, is that the data that it generates are estimates which will inevitably contain some error. This paper describes a technique that allows the automated identification of possible errors at the level of the individual data values.

Are People Changing Address Less? An Analysis of Migration within England and Wales, 1971–2011, by Distance of Move

Expectations of migration and mobility steadily increasing in the longer term, which have a long currency in migration theory and related social science, are at odds with the latest US research showing a marked decline in internal migration rates. This paper reports the results of research that investigates whether England and Wales have experienced any similar change in recent decades. Using the Office for National Statistics Longitudinal Study (ONS-LS) of linked census records, it examines the evidence provided by its 10-year migration indicator, with particular attention to a comparison of the first and latest decades available, 1971-1981 and 2001-2011. This suggests that, as in the USA, there has been a marked reduction in the level of shorter-distance (less than 10km) moving that has involved almost all types of people. In contrast to this and to US experience, however, the propensity of people to make longer-distance address changes between decennial censuses has declined much less, largely corroborating the results of a companion study tracking the annual trend in rates of between-area migration since the 1970s (Champion and Shuttleworth, 2016).

Relationships Between Deprivation and the Self-reported Health of Older People in Northern Ireland

Objectives: There are few studies on relationships between deprivation and the self-reported health of people aged over 64 years, and no studies fully representative of Northern Ireland’s older population. This paper addresses this gap. Methods: Deprivation of older people as reported in the 2001 and 2011 Censuses and the relationship with self-reported health are analyzed over a ten-year span using multilevel modeling. The data are from the Northern Ireland Longitudinal Study (NILS) linked to 2001-11 Census returns. Deprivation measures include housing tenure, property-value, access to a car, educational, employment and area-level income-deprivation. Results: Older people suffering deprivation face a significant health disadvantage over a ten-year time span. Discussion: This health disadvantage is stronger in men than in women, likely due to conservative gender roles prevalent among Northern Ireland’s older population, leading to psychological distress among deprived men. The analysis found strongly significant area-level effects, aggravating the health impact of deprivation.

People and places: Understanding geographical accuracy in administrative data from the census and healthcare systems

Administrative systems such as health care registration are of increasing importance in providing information for statistical, research, and policy purposes. There is thus a pressing need to understand better the detailed relationship between population characteristics as recorded in such systems and conventional censuses. This paper explores these issues using the unique Northern Ireland Longitudinal Study (NILS). It takes the 2001 Census enumeration as a benchmark and analyses the social, demographic and spatial patterns of mismatch with the health register at individual level. Descriptive comparison is followed by multivariate and multilevel analyses which show that approximately 25% of individuals are reported to be in different addresses and that age, rurality, education, and housing type are all important factors. This level of mismatch appears to be maintained over time, as earlier migrants who update their address details are replaced by others who have not yet done so. In some cases, apparent mismatches seem likely to reflect complex multi-address living arrangements rather than data error.