Gracious Wisp (Agriocnemis gratiosa)

View the above photo record (by Rob Dickinson) in OdonataMAP here.

Find the Gracious Wisp in the FBIS database (Freshwater Biodiversity Information System) here.

Family Coenagrionidae

Agriocnemis gratiosaGRACIOUS WISP


Very small size

Length up to 26mm; Wingspan attains 28mm.

Most similar to Agriocnemis falcifera (White-masked Wisp). The Gracious Wisp can be told apart by its round postocular spots that are not joined by a thin line. Additionally the male Gracious Wisp lacks the white moustache of the White-masked Wisp. These two species are the largest Southern African wisps which helps to separate them from the other smaller species.

Click here for more details on identification.

Agriocnemis gratiosa – Male
Okavango Delta, Botswana
Photo by Ryan Tippett


Associated with the fringes and clearings of coastal, swamp and dune forests. Occupies damp, grassy areas connected to slow-moving streams, pools, pans and marshes. Favours sites with a rich growth of tall grasses, ferns and other herbaceous plants. Often found in shady areas with dappled light.

Habitat – Near Kosi Bay, KwaZulu-Natal
Photo by Ryan Tippett


An unobtrusive species that hides low down among rank vegetation.

Most active from October to April. See Phenology below.

Status and Conservation

Scarce and very localised. In the IUCN Red List of Threatened Species it is listed as Vulnerable in South Africa, but of Least Concern overall.


A species of East and Southern Africa.

It has been recorded in Botswana, the Democratic Republic of the Congo, Kenya, Madagascar, Malawi, Mozambique, Namibia, South Africa, Sudan, Tanzania, Uganda, Zambia, and possibly Burundi.

In South Africa it is restricted to the coastal region of NE KwaZulu-Natal, reaching as far south as Amanzimtoti. Also found locally at a few scattered sites in the Lowveld of Mpumalanga and Limpopo.

Below is a map showing the distribution of records for Gracious Wisp 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.