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Well, this a puzzle 🧐

The CV models of iNaturalist & ObsIdentify are all over the place with IDing this small flea beetle. They suggest genus Neocrepidodera, among others, but it lacks any dimples on its thorax & elytra.

I reckon it might be Aphthona cyparissiae, as it was on Eurphorbia cypressas.

But ... ?

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A small beetle seen side on on a green eurphorbia plant. The beetle is an amber shade overall, the darker head and thorax smooth and shiny, with black compound eyes. The elytra seem to be partly transparent, showing the lighter wings below – there is quite a lot of patterning. There is a v-shaped region at the top of the elytra which is darker. The legs are mahogany brown, the hind femora very chunky, marking it as a flea beetle. The antennae are segmented, brown and then black at the end. The same beetle seen head on, showing its dark compound eyes and black mouth parts. The same beetle seen side-on and from above, showing the light wings under the transparent amber eyltra. The rear of the abdomen is black and striated. The black tips of the antennae are more clearly seen here. Another shot from in front and above, showing the contrast between the dark amber head and thorax, and the much lighter elytra.

#photography #macrophotography #bugoftheday #heidelberg #insectsofmastodon #backgardenentomology

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Commenti (3)

As I said, the CV models of iNat & ObsIdentify picked either Neocrepidodera ferruginea or N. transversa, or other flea beetles depending on the picture, but with little confidence.

Both are relatively common in Germany, while Aphthona cyparissiae, the brown dot leafy spurge flea beetle, is definitely not: just 9 observations on iNat to date.

But overall, judging from the semi-transparent wing cases & lack of dimples on them, it is a better fit.

Plus it was on the right plant, cypress spurge.

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@markmccaughrean@mastodon.social

CV is such a mess with ants. Especially the male ants.

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flea beetle IDs are exactly where these classifiers fall apart. they lean hard on coarse color and shape, and the fine cues like thorax dimples or puncture patterns barely register in the training data. your manual key beats the model here because you're using the diagnostic feature it never learned to weight.

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