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Monitoring Common and Scarce Breeding Birds in the Netherlands: Applying a Post-Hoc Stratification and Weighting Procedure to Obtain Less Biased Population Trends

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Monitoring Common and Scarce Breeding Birds in the Netherlands: Applying a Post-Hoc Stratification and Weighting Procedure to Obtain Less Biased Population Trends Revista Catalana d’Ornitologia 24:15-29, 2008 Monitoring common and scarce breeding birds in the Netherlands: applying a post-hoc stratification and weighting procedure to obtain less biased population trends Chris A.M. van Turnhout, Frank Willems, Calijn Plate, Arco van Strien, Wolf Teunissen, Arend van Dijk & Ruud Foppen The main objective of the Dutch Breeding Bird Monitoring Program (BMP) is to assess changes in population sizes of common and scarce breeding birds. Despite the large number of study plots, trends might be biased because plots are not equally distributed over the country. In this paper we present a post-hoc stratification and weighting procedure to correct for this non-random sampling. Indices and trends are first calculated for a number of species- specific strata (combinations of region, main habitat type and bird density class). Thereafter, the indices per stratum are weighted by population sizes (derived from an independently collected set of atlas data) and sampling effort per stratum. The procedure has a small but substantial effect on national trends, trends generally becoming less conservative. We believe that for the majority of breeding birds this procedure results in a substantial improvement of trends, and we will therefore continue the BMP in forthcoming years. Key words: monitoring, breeding birds, non-random design, trend analysis, stratification, weighting Chris A.M. van Turnhout*, Department of Environmental Science / Department of Animal Ecology & Ecophysiology, Institute for Wetland and Water Research, Radboud University Nijmegen, PO Box 9010, 6500 GL Nijmegen, The Netherlands. Frank Willems, Wolf Teunissen, Arend van Dijk & Ruud Foppen, SOVON Dutch Centre for Field Ornithology, Rijksstraatweg 178, 6573 DG Beek-Ubbergen, The Netherlands. Calijn Plate, Statistics Netherlands, PO Box 4000, 2270 JM Voorburg, The Netherlands. *Corresponding author: [email protected] Breeding birds are useful indicators of the state regional scale in population sizes of common and of the environment. Monitoring data therefore scarce breeding birds, including nine species in provide valuable information on the quality of the EU Bird Directive and 25 species on the nature and on the effectiveness of nature con- Dutch Red List (Van Beusekom et al. 2005). servation policy. Furthermore, such data are Because it is not possible to count all individu- useful for scientific research purposes, such as als to calculate the true trend in species abun- the evaluation of the effects of environmental dance, it is necessary to sample. An ideal mon- changes, (local) conservation measures and itoring scheme, resulting in accurate and habitat management (Furness & Greenwood representative population indices and trends, 1993, Freeman et al. 2007). would consist of a large number of randomly In 1984, SOVON and Statistics Netherlands selected study plots, and yearly participation of started the Breeding Bird Monitoring Program all observers from the beginning onwards. De- (BMP) in the Netherlands (Van Dijk 1992). The spite the relatively large number of study plots, main objective of this monitoring scheme is to the BMP is not such an ideal scheme. Not all assess yearly changes and trends at national and study plots are covered yearly, so it is necessary C. van Turnhout et al. Revista Catalana d’Ornitologia 24 (2008) to cope with missing values (Ter Braak et al. od of observations (to exclude non-breeding 1994). Moreover, because participants (mainly migrants). volunteers) are free to choose their study areas, All observers submit their data on standard plots are not equally distributed over Dutch re- forms. After a first check by the project coordi- gions and habitat types. Also, within a specific nator at SOVON, Statistics Netherlands per- habitat volunteers may have a preference for forms standardized checks using computer rou- the most attractive sites, i.e. those which are tines to detect possible errors. Observers check species-rich and have high bird densities. In and if necessary correct these errors. Between particular, within farmland, wet grasslands with 1984 and 2004 a total of 3374 different study high densities of meadow birds are oversampled, plots were covered, ranging from around 300 in comparison to dry grassland areas poor in per year in 1984 to a maximum of around 1750 species and numbers. This is no problem as long in 1998-2000. as trends between these strata are identical. However, if trends differ, the estimates of popu- Atlas data lation changes may be biased. Here we describe a method to correct for biased sampling, using Independently collected data from the second an independently collected set of atlas data. First Dutch breeding bird atlas (SOVON 2002) are we carried out a pilot study on meadow bird used to correct the BMP results. Fieldwork for population trends, on the basis of which we ap- the atlas was carried out using a sampling de- plied a simplified approach to all other breed- sign based on the Dutch national grid, which ing bird species. consists of 1,674 5x5 km squares (henceforth referred to as atlas squares). In every atlas square eight (out of 25) 1x1 km squares were systemati- Materials and methods cally selected, in which presence/absence of all breeding birds was assessed during two standar- Breeding Bird Monitoring Program (BMP) dized one hour visits. Fieldwork was carried out in 1998-2000. Using geostatistical interpolation The Dutch Breeding Bird Monitoring program techniques (stratified ordinary kriging; Burrough is based on the method of intensive territory & McDonnel 1998) a relative density (proba- mapping in study plots (Hustings et al. 1985; bility of occurrence) was calculated for all Bibby et al. 1997). All common and scarce 1x1 km squares, based on the observations in breeding birds in the Netherlands are covered. 12 surrounding squares with the same habitat. The scheme consists of five modules, focused For further details, see SOVON (2002). on either all species or specified groups or hab- itats (scarce species, raptors, meadow birds, ur- Calculation of indices and trends ban areas). Fieldwork and interpretation me- thods are highly standardized and are described Yearly changes in numbers of species are pre- in detail in a manual (Van Dijk 1985; Van Dijk sented as indices. From 1990 onwards, sampling 2004). Between March and July all plots (10 efforts are sufficient to calculate indices for ap- to 500 hectares in size) are visited 5-10 times. proximately 100 species. Indices are calculated Size of study plots, as well as the number, tim- using TRIM-software (Pannekoek & Van Strien ing and duration of visits, depend on habitat 2005), specifically developed for the analysis of type and species coverage. All birds with terri- time series of counts with missing data, and tory or nest-indicative behaviour (e.g. song, pair based on loglinear Poisson regression. The re- bond, display, alarm, nests) are recorded on gression model estimates year and site factors field maps. At the end of the season, species- using the observed counts. Subsequently the specific interpretation criteria are used to de- model is used to predict the missing counts. In- termine the number of territories per species dices and standard errors are calculated using a (Van Dijk 2004). Interpretation criteria focus complete data set with the predicted counts re- on the type of behaviour observed, the number placing the missing counts. Overdispersion, de- of observations required (depending on species- viations from Poisson distribution, and serial specific detection probabilities), and the peri- correlation are taken into account. 16 Monitoring breeding birds in the Netherlands Figure 1. Location of BMP study plots in the Netherlands 2000-2004. Only plots which are studied in at least two years are included. Localització dels punts de mostratge del programa de seguiment d’ocells nidificants d’Holanda el 2000-2004. Únicament es van incloure els punts els quals s’havien prospectat dos anys. The national indices are calculated using a types (Figure 2). Indices and trends are first cal- post-hoc stratification and weighting procedure, culated for each stratum separately (stratified to correct for the unequal distribution of study imputing of missing values). Thereafter, the in- plots over Dutch regions (Figure 1) and habitat dices per stratum are combined into a national 17 C. van Turnhout et al. Revista Catalana d’Ornitologia 24 (2008) land (arable land, grassland, hedgerows), wood- land (deciduous, coniferous and mixed forest), heathland (dry and wet heathland, bog and in- land drift sand), freshwater marsh, salt marsh, coastal dunes and urban habitats (city, suburb, industrial zone, park). Species-specific bird density is used as a stratification variable because trends may differ between core areas with high densities (result- ing from favourable habitat quality) and mar- ginal areas with low densities (resulting from unfavourable habitat quality). We distinguish three classes: areas with high, medium and low densities. For each species all 1x1 km2 are sor- ted according to relative density, based on atlas data. The top 15% squares are arbitrarily classi- fied as high-density areas, the next highest 30% as medium-density areas and the remaining 55% as low-density areas. For all species, strata are defined where spe- cies occur in substantial numbers, with strata being the combinations of physio-geographic region, main habitat type and bird density (the Figure 2. Relative distribution of main habitat types latter for meadow birds only, see result section). within the Netherlands (relative area; upper) and in the BMP sample (relative number of study plots; lower). The stratification is done based on the expert Distribució relativa del tipus d’ hàbitats principals a judgement of two breeding bird specialists at Holanda (àrea relativa, dalt) i la mostra del BMP SOVON. Strata are lumped if the minimum (nombre relatiu de punts de mostratge, baix) number of positive plots per year since 1990 is less than five (based on experience of Statistics Netherlands). Strata are lumped according to index, weighted by population sizes and sam- either region or main habitat type, depending pling effort per stratum.
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