Forest Hawker (Zosteraeschna usambarica)

View the above photo record (by Gerhard Diedericks) in OdonataMAP here.

Find the Forest Hawker in the FBIS database (Freshwater Biodiversity Information System) here.

Family Aeshnidae

Zosteraeschna usambaricaFOREST HAWKER


Medium – large size

Length up to 45mm; Wingspan reaches 83mm.

The sexes are similar but females either lack the blue saddle or it is very reduced. Females also have amber outer wings.

Zosteraeschna usambarica is closely similar to the Friendly Hawker (Zosteraeschna minuscula), but differs in having a pentagon shaped marking on the forehead and triangle shaped green markings on the shoulders. The diagonal stripes on the sides of the thorax are also a brighter shade of green in Zosteraeschna usambarica.

Click here for more details on identification of the Forest Hawker.

Zosteraeschna usambarica – Male
Near Sabi, Mpumalanga
Photographs by Gerhard Diedericks


Associated with high altitude forest and forest-edge environments. It inhabits streams, ponds, marshes and dams, both inside and outside the forest. It will also hunt over grasslands bordering forests. Prefers indigenous forests but also makes use of exotic plantations.


Highly aerial, spending most of its time in flight. Patrols, to and fro along a chosen route over the wetland. The flight is fast and direct. Hangs vertically from a perch while at rest.

Status and Conservation

Rare and localised in South Africa. It is listed for South Africa as being Vulnerable in the IUCN Red List of Threatened Species. It is vulnerable to the loss of wetland habitats due to the spread of commercial forestry and agriculture. This species does occupy exotic plantations, provided associated wetlands remain intact.


Zosteraeschna usambarica has a highly fragmented distribution that ranges from South Africa to Zimbabwe, Mozambique, Malawi, Tanzania and Kenya.

Below is a map showing the distribution of records for Forest Hawker 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.