Why we won't tell you when tropical ants fly

Type in a location near the equator and Dealate's species list won't hand you a month. That's not an oversight. It's deliberate, and it's worth saying why, because everywhere else on this blog the answer is the opposite: pin the country, name the month, cite the paper.

Nuptial flights above and below the tropics run on a temperate clock. Day length changes through the year, so does soil temperature, and a species settles into a window because the conditions it needs only line up in that window. Lasius niger flies in July because July is when a British garden reliably gets warm enough, humid enough, and calm enough at the same time. That's a real season, and it's forecastable.

Near the equator, day length barely moves and soil temperature barely moves with it. What does move, sharply and unpredictably, is rainfall. A lot of tropical ant biology runs off rain the way temperate biology runs off temperature, and rain doesn't keep a calendar the way the sun does.

The best-documented case is a leafcutter ant, Atta vollenweideri, studied over 23 swarm events in northern Argentina. Flights only happened once cumulative rainfall over the preceding month reached at least 64 mm, about 2.5 inches. Even then, alates stayed in the mound until air temperature on the days following rain rose above 26 °C, 79 °F, with the actual takeoff clustering closer to 32 °C, about 90 °F. Rain was the gate, heat was the trigger, and neither one arrives on a schedule.

That's one well-studied genus in one region. It's a real result, and it's also exactly the kind of finding that shouldn't be generalised past its own species. Extrapolating an Argentine leafcutter's rain threshold onto, say, a Malaysian Oecophylla colony would be inventing a fact, not reporting one.

There's a second problem underneath the first one. Everywhere else, the model works in hemispheres: a species' northern-hemisphere flight months get mirrored six months later for the southern hemisphere, because the seasons genuinely flip across the equator. Right at the equator, though, that trick just doesn't have anywhere to go. A location a few degrees either side of it isn't clearly in one hemisphere's seasonal system or the other, so the mirroring logic stops working at more or less the exact latitude where you'd need it most.

Dealate draws the line at 23.5 degrees, the tropic latitude itself, and below it the model deliberately falls back to a season-neutral, rain-and-heat-driven baseline rather than forcing a temperate-shaped window onto a place that doesn't have one. A handful of well-studied genera, leafcutters among them, get their own dedicated rules instead of the fallback. Most tropical genera don't have that research yet, and get the honest neutral baseline.

It would be easy enough to fill the gap. Pick a plausible-sounding month for a tropical species, publish it, and almost nobody would check. Nobody near the equator is going to email in a correction the way a British keeper would over a wrong week for Lasius flavus.

The reasoning behind Dealate's forecast is public precisely so that a claim like that could be checked, and a made-up tropical season would fail that check the moment someone with real fieldwork looked at it. So the app says nothing instead. That's a smaller feature for readers near the equator today, and honestly a bit of an anticlimax after all this build-up. But it's the only version of this worth trusting anywhere.

The methodology page covers the same instinct applied elsewhere in the model: publish the reasoning, withhold the parts that aren't backed by real data yet. Why the forecast and your garden disagree is the temperate-latitude version of the same honesty problem, at a much smaller scale.

The Atta vollenweideri rainfall and temperature thresholds are from Staab, M. & Kleineidam, C.J. (2014), Initiation of swarming behavior and synchronization of mating flights in the leaf-cutting ant Atta vollenweideri, Myrmecological News 19: 93 to 102, 23 swarm events recorded in northern Argentina between 2004 and 2010. The full source list behind the forecast model is set out on the methodology page.