Lucia Widow (Palpopleura lucia)

The photo above (by Diana Russell) can be viewed in OdonataMAP here.

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

Family Libellulidae

Palpopleura lucia LUCIA WIDOW

Identification

Small size

Length reaches 32mm; Wingspan attains 53mm.

An easily recognisable species. Most similar to Palpopleura portia, but that species has a pale pruinose blue, rather than black upper thorax. It also shows far less black in the wings.

Females of the two species are closely similar, but those of Palpopleura lucia generally show more black in the wings and usually have a smoky ‘shadow’ area in the hind wings below the black.

Click here for more details on identification.

Palpopleura lucia – Male
Near Hluhluwe, KwaZulu-Natal
Photo by Ryan Tippett
Palpopleura lucia – Female
Near Kosi Bay, KwaZulu-Natal
Photo by Ryan Tippett

Habitat

Palpopleura lucia has a wide habitat tolerance. It prefers the still waters of lakes, pans,dams, ponds, floodplains and marshes. It also occupies the slow moving sections of rivers and streams. Favours well vegetated habitats with an abundance of emergent reeds, sedge, grass etc. Mostly restricted to hot, humid savanna regions.

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

Behaviour

A very conspicuous and eye-catching species. Males sit prominently on exposed perches over the water. The flight is fast and fluttering.

On the wing from October to May, but flies year-round in many places.

Status and Conservation

Common and widespread. Listed as of Least Concern in the IUCN Red List of Threatened Species. An adaptable dragonfly that readily makes use of man-made habitats.

Distribution

Palpopleura lucia is widespread over most of Sub-Saharan Africa. It is excluded only from the driest regions of NE Africa and the dry and Winter-rainfall parts of Southern Africa.

Below is a map showing the distribution of records for Lucia Widow 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.