Table 2.
Sampling locations | Baseline tick density/activity | Population trend | Month of peak tick density/activity | Tick aggregation | P-value |
---|---|---|---|---|---|
Appelscha |
1.5 |
1.5 |
6.1 |
2.7 |
<0.01 |
Bilthoven |
3.4 |
0.0 |
6.7 |
1.4 |
0.07 |
Ede |
45.0 |
11.9 |
6.4 |
1.1 |
0.05 |
Eijsden |
10.7 |
0.0 |
6.1 |
1.1 |
0.08 |
Gieten |
5.5 |
18.4 |
6.2 |
0.5 |
<0.01 |
Hoog Baarlo |
67.4 |
−11.4 |
6.6 |
1.1 |
<0.01 |
Kwade hoek |
3.5 |
0.0 |
6.4 |
0.4 |
1.00 |
Montferland |
25.2 |
0.0 |
6.7 |
0.4 |
0.09 |
Schiermonnikoog |
1.5 |
3.4 |
6.8 |
0.5 |
0.02 |
Twiske |
22.0 |
0.0 |
6.0 |
0.7 |
0.30 |
Vaals |
10.0 |
0.0 |
6.5 |
0.2 |
0.64 |
Veldhoven |
32.8 |
0.0 |
6.7 |
0.7 |
0.11 |
Wassenaar | 0.0 | 6.2 | 5.8 | 0.4 | <0.01 |
Increasing trends are indicated by positive estimates for the coefficient b in the linear function (Experimental procedures), decreasing trends by negative estimates. Baseline is equal to the intercept a in the linear function describing the tick density/activity per drag area. Population trend is the change in tick density/activity per year; it is equal to the coefficient b in the linear function multiplied by 2π. Peak month is equal to the parameter τ in the cosine function describing the annual seasonality. Tick aggregation is equal to the parameter k in the negative binomial distribution. Estimates are maximum likelihood estimates for each sampling location. Study sites with significant trends are shown in bold.