Population Trend Analysis
The purpose of analysis is to draw correct conclusions on population trends occurring in species of interest. Many factors can influence the appearance of trends (apart from true changes in population size) and the magnitude of their effect should be estimated, and methods for reducing their influence put into place to reduce the possibility of data misinterpretation.
In order to produce a clear picture of the long-term trend for each species, GAMs (General Additive Models) have been used to fit a smooth line to each dataset. These smoothed curves are quite robust against random variation between years, except at the ends of the series where annual fluctuations and extreme outliers can have an unacceptably large impact on the first and last years. To counteract this problem, it is best not to use the first year of a survey as the baseline year, where the index equals 100, and in this report the year 1999 has been taken as the baseline year wherever possible. Most surveys start from 1997, although there are a few exceptions. The Field Survey starts from 1998, and some Hibernation Surveys and Colony Counts have additional earlier years of data for some species. Where these data are available and improve trend estimation, they have been included in the GAMs but as they comprise small amounts of data, the start year is still shown as 1997.
On the trend graphs for each species, crosses represent the calculated means (converted to the index scale) and the solid line represents the estimated trend from the GAM. Dotted lines show 95% confidence limits. In all cases, the estimate for the most recent year should be regarded as provisional and a dotted line is used on the graphs to indicate this. All graphs are shown from 1998 to 2011 for consistency.
GAM models can include covariates for factors that could influence the means (e.g. bat detector make, temperature). Generalised Linear Mixed Models (GLMMs) were used to investigate these factors, with any variables that were statistically significant with a biologically plausible relationship included in subsequent GAMs. GAM models were then fitted with and without the covariates, to compare the results. In most cases the differences between the two models were minimal, but for some of the field survey results bat detector type had a marked impact on results, due to the gradual change in the detectors used over time. For each species the analysis with covariates is reported when this achieves a marked increase in precision compared to the unadjusted trend.
The average annual percentage change is an approximation based on the assumption that the trend during the period considered is constant and linear. It is estimated by calculating the annual percentage change that would take the population from 100 in the base year to the index value in the current year.
Click here for a detailed explanation of GAMs
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