Elusive Skimmer (Orthetrum rubens)

The photo above (by Andrew & Heather Hodgson) can be viewed in OdonataMAP here.

Find this species in the FBIS database (Freshwater Biodiversity Information System) here.

Family Libellulidae

Orthetrum rubens ELUSIVE SKIMMER


Medium sized

Length up to 43mm; Wingspan reaches 66mm.

Both sexes are highly distinctive and easily recognised. The bright maroon colour on the thorax is diagnostic and unique.

Males are most similar to Orthetrum caffrum (Two-striped Skimmer). Both species show a pair of diagonal white stripes on the thorax sides. In Orthetrum rubens the stripes are broad and of uneven width with a black border only along the upper edge. Orthetrum caffrum has narrower stripes that are even in width and with thin black edging along the upper and lower edges. Orthetrum caffrum may also have reddish-brown surfaces on the thorax but this tends to be dull and more brown than red.

Females are even more distinctive than the males and are unlikely to be mistaken for another species.

Click here for more details on identification.

Orthetrum rubens – Male
Stettynsberg, Western Cape
Photo by Andrew and Heather Hodgson
Orthetrum rubens – Female
Stettynsberg, Western Cape
Photo by Andrew and Heather Hodgson


Inhabits open, high altitude seeps, bogs and marshes. Occurs up to 1300m above sea level.

Habitat – Mountain seep
Hawequas Mountains, Western Cape
Photo by Corne Rautenbach


Not much is known about the behaviour of this species. Perches on vegetation above boggy ground and seeps.

On the wing from October to February.

Status and Conservation

Seemingly rare and highly localised. Listed as Endangered in the IUCN Red List of Threatened Species.


Orthetrum rubens is endemic to South Africa where it is restricted to high mountainous terrain in the Cape fold mountains of the Western Cape.

Below is a map showing the distribution of records for Elusive Skimmer in the OdonataMAP database as at February 2020.

The next map below is an imputed map, produced by an interpolation algorithm, which attempts to generate a full distribution map from the partial information in the map above. This map will be improved by the submission of records to the OdonataMAP section of the Virtual Museum.

Ultimately, we will produce a series of maps for all the odonata species in the region. The current algorithm is a new algorithm. The objective is mainly to produce “smoothed” maps that could go into a field guide for odonata. This basic version of the algorithm (as mapped above) does not make use of “explanatory variables” (e.g. altitude, terrain roughness, presence of freshwater — we will be producing maps that take these variables into account soon). Currently, it only makes use of the OdonataMAP records for the species being mapped, as well as all the other records of all other species. The basic maps are “optimistic” and will generally show ranges to be larger than what they probably are.

These maps use the data in the OdonataMAP section of the Virtual Museum, and also the database assembled by the previous JRS funded project, which was led by Professor Michael Samways and Dr KD Dijkstra.

Dragonfly Atlas: Megan Loftie-Eaton, Ryan Tippett, Rene Navarro & Les Underhill
Dragonfly Atlas: Megan Loftie-Eaton, Ryan Tippett, Rene Navarro & Les Underhill
Megan Loftie-Eaton is our communications, social media and citizen science projects coordinator. Prior to her work for the BDI, she coordinated OdonataMAP, the Atlas of African Odonata. Ryan Tippett is an enthusiastic contributor to Citizen Science and has added many important and interesting records of fauna and flora. He has been a member of the VMU since 2014 and has currently submitted over 11000 records. He is also on the expert identification panel for the OdonataMAP project. Rene Navarro is the genius behind the Virtual Museum. Prof Les Underhill has been Director of the Animal Demography Unit (ADU) at the University of Cape Town since it started in 1991. Although citizen science in biology is Les’s passion, his academic background is in mathematical statistics.