Effects of neonicotinoid pesticide pollution of Dutch surface water on ...

Combining species abundance and imidacloprid concentrations
Measurements <strong>of</strong> imidacloprid concentrations in the Netherlands were available from
bestrijdingsmiddelenatlas.nl, but only for the years 1998 and 2003‐2007. Therefore, only the
Limnodata sample data for those years could be analysed. Due to the nature <strong>of</strong> the data,
comparing species abundance before the application <strong>of</strong> <strong>neonicotinoid</strong> <strong>pesticide</strong>s began, and
during application, was not possible.
The distribution <strong>of</strong> the locations at which imidacloprid concentrations were measured is
shown in Figure 4a; the locations at which abundance was assessed for the order Diptera are
shown in Figure 4b.
Fig. 4a. Positions <strong>of</strong> 579 imidacloprid measurement
locations
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Fig 4b. Positions <strong>of</strong> the 4479 Limnodata measurement
locations for Diptera
The files with the amounts <strong>of</strong> organisms found per location per date, and those with
imidacloprid concentration per location per date, were combined through a PHP script
coupled to a MySQL database in which the imidacloprid measurements and the abundance
data were stored. PHP stands for ‘Hypertext Preprocessor’ and is a scripting language
originally meant for creating dynamic websites; MySQL is a system which acts as a server
and can provide access to databases to many users (Wikipedia, 2010).
The PHP script did the following:
For each row <strong>of</strong> species abundance data, search for data points in the imidacloprid
concentrations file, which fall within a specified time frame and within a radius <strong>of</strong> 50 m
from the sampling location;
If more than one concentration measurement meets these requirements, take the
unweighted average <strong>of</strong> these. This value is entered in the resulting file as imi0. If no
values are found, imi0 = 0;
Was imi0 > 0? If so, also enter its value as imi1, the value for a 1 km radius. If not, check
again within a radius <strong>of</strong> 1 km and again take the unweighted average <strong>of</strong> all values found;