Little Skimmer (Orthetrum abbotti)

View the above photo record (by Richard Johnstone) in OdonataMAP here.

Find the Little Skimmer in the FBIS database (Freshwater Biodiversity Information System) here.

Family Libellulidae

Orthetrum abbotti LITTLE SKIMMER


Small size

Length up to 38mm; Wingspan attains 60mm.

The smallest Orthetrum species in the region. In males the combination of small size, long, yellow pterostigmas and indistinct ‘spectacles on the face are often enough for a positive identification. However, fully pruinose males are best identified by the distinct shape of the secondary genitalia. They most resemble Orthetrum hintzi (Dark-shouldered Skimmer), which is slightly larger.

Females can be recognised by the long, yellow pterostigmas and plain, mostly unmarked thorax sides.

Click here for more details on identification of the Little Skimmer.

Orthetrum abbotti – Male
Eastern Shores, iSimangaliso Wetland Park – KwaZulu-Natal
Photo by Ryan Tippett


Inhabits boggy ground associated with marshes and seeps. Also found at marshy pools adjoining streams. Favours sites that are rich in emergent sedge and grasses. Mostly found in fairly open grassland habitats.

Habitat – Eastern Shores, iSimangaliso Wetland Park.
Photo by Ryan Tippett


Hunts from a perch and usually returns to the same grass or sedge stem. The flight is fairly slow and weak. Confiding and generally reluctant to fly.

Status and Conservation

Locally common in South Africa. It is listed as of Least Concern in the IUCN Red List of Threatened Species. Primarily found in natural habitats.


Orthetrum abbotti is found throughout most of Sub-Saharan Africa. It also occurs in parts of the Middle-East and on Madagascar.

In South Africa it is found mainly in the Eastern and Central areas with localised populations in parts of the Eastern and Western Cape provinces. It is more common inland than along the coast.

Below is a map showing the distribution of records for Little 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.