1. Monitoring schemes for butterflies in the United Kingdom and the Ne
therlands are aimed at the detection of long-term trends. It is useful
to examine the power of these schemes to detect trends in a given per
iod of time. 2. The approach was based on an A NOVA-model, and the tre
nds were compared with the random population changes from one year to
another. Several assumptions were made for simplicity's sake: autocorr
elation in the data was ignored and only linear trends in log(10) (N 1) transformed data were examined. 3. The relevant variance component
s to examine were the year-to-year variances and year-by-site variance
s. These were estimated from the time series of the British Butterfly
Monitoring Scheme, Year-to-year variances appeared to be higher in nor
thern Britain than in other regions. In addition, variance components
were related to the voltinism of species. 4. Power assessment was base
d on the estimates of variance components and on the number of samplin
g sites. In the British scheme, for 37 out of 51 species studied a dec
rease of 50% or less is detectable with a power of 80% within a 20-yea
r period. In the Dutch scheme such a decrease is detectable for 29 out
of 47 species. 5. Because the schemes lack power for a number of spec
ies, several strategies are discussed to enhance power. For species pr
esent at less than 25 sites, it is most effective to increase the numb
er of sampling sites where they are present, if that is possible in pr
actice. But for species that are present at more than 50 sites, a furt
her increase hardly improves the power. For these species, it is more
efficient to adjust the data for weather conditions than to increase t
he number of sites, 6. The assumptions we made hardly affect the resul
ts for common species. But for rare species the results are more or le
ss questionable, To get better estimates of the power, methods to asse
ss power for monitoring schemes need to be developed that treat count
data as discrete random variables.