Hampshire and Isle of Wight Butterfly and Moth Society
Hampshire and Isle of Wight Butterfly and Moth Society
| Family: | Nymphalidae |
| Subfamily: | Heliconiinae |
| Genus: | Argynnis |
| Species: | paphia |
| Authority: | (Linnaeus, 1758) |
This butterfly is our largest fritillary and gets its name from the beautiful streaks of silver found on the underside of the wings. The bright orange male is quite distinctive as it flies powerfully along woodland rides, pausing only briefly to feed or investigate anything with an orange hue that could be a potential mate. The male has four distinctive black veins on its forewings that contain special "androconial" scales that are used in courtship. These veins are known as "sex brands". The female is paler than the male, has rounder wings and more-prominent spots. In England and Wales, the Silver-washed Fritillary is found in woodlands south of a line between Montgomeryshire in the west and East Kent in the east, with a few scattered colonies elsewhere, including those in Westmorland and West Lancashire. This species is also widely distributed in Ireland, but is absent from Scotland, the Isle of Man and the Channel Islands.
| #Individuals | #Tetrads | 2023 | 2024 | Abundance Trend | 2023 | 2024 | Distribution Trend |
|---|---|---|---|---|---|
| 4777 | 1783 | -62% | 227 | 160 | -29% |
| #Records | #Individuals | Earliest Record | Latest Record | |
|---|---|---|---|---|
| All Records | 30,647 | 122,143 | Late May 1893 | 27/09/2021 |
| 2024 | 886 | 1,783 | 12/6/2024 | 4/9/2024 |
| Location | Date | Quantity | |
|---|---|---|---|
| Earliest Record | Hillier Gardens | 12/6/2024 | 2 |
| Latest Record | Bramshott Common | 4/9/2024 | 1 |
| Highest Count | Micheldever Wood | 17/7/2024 | 35 |
One of the issues with 'raw' trend data is that there is inherent bias based on the number of recorders. For example, the number of individuals and populated tetrads recorded are likely to increase if there is an increase in the number of recorders. In order to remove this bias, the normalised trends use data that has been recalculated using the average number of recorders over the trend period. This normalisation gives a much better picture of the true trends.
Average #Recorders: 172.44
Average #Recorders: 172.44