The Cardera moth overwinters and breeds in sub-Saharan Africa – Technology

The Cardera moth overwinters and breeds in sub-Saharan Africa – Technology

The cardero butterfly migrates every year between Africa and Europe, but where it spends the European winter and where it breeds is little known. Environmental models have indicated as few areas of the African tropics as possible, and now a team of scientists has confirmed them.

After two years of observation and extensive field studies, the team validated these models and located the winter breeding sites for these butterflies (Vanessa cardui), which breed in Kenya, Uganda, Cameroon, Benin and Ghana between October and February. Ivory Coast, Senegal, and Ethiopia, among others.

Details of the research, led by Gerard Talavera, researcher at the Botanical Institute of Barcelona (IBB, CSIC), and Roger Villa, from the Institute of Evolutionary Biology (IBE, CSIC-UPF), have been published in the journal Proceedings of the National Academy of Sciences (PNAS).

Migratory insects are essential to ecosystem function and services, but how and when they make their long journeys is a mystery to many species.

The Cardera butterfly, like the famous monarch butterfly that migrates between Canada and Mexico, is a “model” species for scientists, that is, it allows biological processes to be studied and extrapolated to similar species, “however, it is as important as its completion of the migration cycle,” Talavera explains in statements to EFE.

Recent research found that these butterflies could cross the desert from Europe in the fall, and return in late winter, but where they overwintered remained unknown.

Ecological Specialist Models (ENMs) have indicated potential geographic locations where these butterflies could find the conditions necessary to breed during the European winter months, but these predictions need to be validated by scientific fieldwork, which is what Talavera’s team did.

“The key was to investigate the environmental requirements for this species to be able to breed in Africa, which differs from those in Europe. Using ecological modeling methods with data from 1,268 breeding sites in 35 countries, we were able to make monthly predictions of potential African regions where they could They breed during the European winter.

To test modeling predictions, the team has undertaken multiple missions and established an extensive monitoring network for these butterflies in Africa, observations documenting as many as 280 new, previously unknown breeding sites.

In the field work, they also identified several host plants, including Zornia glochidiata and Pseudoconyza viscosa, that are essential for the development of this butterfly’s larvae.

In addition, the team also discovered that rainfall plays an important role in determining the migration dynamics of butterflies in sub-Saharan Africa, as these insects migrate after the rain-induced new vegetation grows.

“The vegetation allows them to breed from September to November in coastal areas and the northernmost savanna, and gradually move south to wetter regions and mountainous regions between December and February,” Talavera details.

“Since we discovered that these butterflies migrated through the desert, interest in understanding how they completed their cycle in Africa has increased. We now know for sure that their migration extends to 15,000 km and that it is the longest known migration route in butterflies,” adds Villa.

The authors conclude that tools such as specialized ecological modeling are key to helping predict and identify habitats for migratory species, and to contribute to conservation efforts and studies of habitat changes caused by factors such as climate change.

Talavera comments, “The dynamics of insect migration are largely unknown, and therefore we don’t know what environmental implications they might have.”

But in a world where “half of the species are insects and they represent a huge biomass, it is important to invest in their observation to understand their population dynamics on a macro scale and to predict possible changes in these dynamics that may have consequences as we do not yet know (biosafety, transmission of pathogens, epidemics). , changing food webs, etc.)”. EFE


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