Data and computation
Countries contributing with their data.
The data come from 21 countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Italy, Latvia, Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland, United Kingdom.
Data from Estonia cover now longer time period (1983 - 2006) and more species as compared with previous version. Data from Belgium come from two regional monitoring schemes in Wallonia and Brussels covering the period until 2005. Data from former West Germany was treated separately from the data from former East Germany (for computation procedure only). Countries within the same group (region) used for calculation regional and European indices (see also below) are in the same colour.
Country/region Region(group of countries) First year Last year Austria WE 1998 2006 Belgium-Brussels1) WE 1992 2005 Belgium-Wallonia1) WE 1990 2005 Bulgaria SEE 2004 2006 Czech Republic CEE 1982 2006 Denmark WE 1976 2006 Estonia CEE 1983 2006 Finland NE 1975 2006 France2) SE 1989 2006 Germany East3) CEE 1991 2006 Germany West3) WE 1989 2006 Hungary CEE 1999 2006 Italy SE 2000 2006 Latvia CEE 1995 2006 Netherlands WE 1990 2006 Norway NE 1995 2006 Poland CEE 2000 2006 Portugal SE 2004 2006 Republic of Ireland WE 1998 2006 Spain SE 1996 2006 Sweden NE 1975 2006 Switzerland WE 1999 2006 United Kingdom WE 1966 2006
WE - West Europe
NE - North Europe
SE - South Europe
SEE - Southeast Europe
CEE - Central & East Europe
First year - first year of data time series in a country/region
Last year - last year of data time series in a country/region
Time series for individual species from national schemes could be shorter in some cases.
1) Data for Belgium were combined from Wallonia and Brussels and cover the period untill 2005.
2) Data in France come from two schemes, old and new one, data from both schemes were combined.
3) Data for Germany were combined from schemes in former East and West Germany.
In order to estimate missing values in countries with shorter time series with TRIM (a process analogical to production of indices at national level) we made groups of countries where we expect similar changes in bird trends. Thus we avoid e.g. estimating missing values in south European country using data from the North. Then, yearly totals for missing years for countries within a group were estimated.
Weighting factor for each country and species was calculated as population size (geometric mean of population minimum and maximum provided by Birds in Europe 2 (BirdLife International 2004) divided by estimated (model) scheme year total for the same years.
Combined year totals and their standard errors for whole group were then calculated using weighting factors.
Overview of computation steps incl. groups of countries:
Data quality control
National data on species trends were checked using criteria:
1. Data should be available from countries which host at least 50 % of ┤PECBMS European┤ population of a species. ┤PECBMS Europe┤ - countries included in our definition of Europe for assesment of abundant and widespread species. Includes countries which contribute actively by data provision or are supposed to provide data by 2010. These are: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Republic of Ireland, Romania, Slovakia, Spain, Sweden, Switzerland, United Kingdom.
However, some parts of countries (states) listed above were not used and their population not considered in the assesment. These are: Faroe Islands and Greenland, Svalbard, Azores, Madeira, Canary Islands, Gibraltar.
2. Suspicious national data were detected using following criteria (see below) and all suspicious national trends were examined in detail. National species indices were excluded from the computation in cases when suspicious results were not justified as reflecting real population changes. This procedure included consultations with coordinators of national monitoring schemes.
National species data were examined as suspicious when:
Despite several species were excluded from an analysis using these criteria, European index of some species could not be estimated because of poor data. Such species were excluded as well.
The computation was done using automation system developed by the Statistics Netherlands.
European and regional species were checked for their use for production of indicators too. If a species index is classified as ┤Uncertain┤* AND index value is >>>> 200% or <<<< 5 %, then the species index and data quality was examined in details. This criteria was considered as indicative, final decision taken (i.e. species to be potentially excluded from an indicator) considers also whether a species was used already in previous versions of the indicators, whether better data can be expected in near future and whether index fluctuation is believed to be caused either by poor data or by reasons not linked directly to habitat quality. This rather conservative approach is used in order to prevent bigger influence of subjective decision.
Four species were excluded at European level: Milvus migrans, Milvus milvus, Crex crex and Dendrocopos medius. The same assessment has been done for all versions of indicators produced.
Similarly as in case of species indices, the indicators were produced automation system provided by the Statistics Netherlands and also by hands and outputs were compared.
*1) Trend classification
The multiplicative overall slope estimate (trend value) in TRIM is converted into one of the following categories. The category depends on the overall slope as well as its 95% confidence interval (= slope +/- 1.96 times the standard error of the slope).