Welcome to the Research Roundup: a collection of highlights from the latest Husker research and creative activity.

Fairy(wren) godfathers

Fairywrens — small, vibrant birds native to Australia — are among the animals that practice cooperative breeding, whereby offspring are reared by not just their parents but so-called helpers, too. Though ecologists generally understand the benefits and costs of cooperative breeding, they haven’t totally untangled how environmental conditions can influence the amount of cooperative breeding, and subsequent group sizes, within a given species.

The School of Biological Sciences’ Allison Johnson and Daizaburo Shizuka led a search for answers in two species, purple-backed and superb fairywrens, that inhabit the same region of southeastern Australia. That region encompasses both the cool, wet climate of the South Pacific coast and the hot, arid climate of the Outback. But whereas the two species often share habitats, the motivations and benefits of their cooperative breeding differ. In purple-backed fairywren communities, the practice appears to increase the number of offspring. Cooperative breeding among superb fairywrens, by contrast, fails to directly benefit reproduction. Instead, a lack of breeding opportunities for young males may encourage them to stick around as helpers, waiting their turn for potential mates.

The team found that purple-backed fairywrens enduring the scorching, bone-dry conditions of the Outback lived in groups up to twice the size of the purple-backed fairywrens that inhabited the comparatively milder, wetter coast. As for the superb fairywrens? Just the opposite: When living along the coast, their groups grew to roughly 1.5 times the size of their counterparts in the desert.

The researchers suspect that the opposing trends in group size reflect the differences in cooperative breeding. If reproductive success among purple-backed fairywrens can depend in part on helpers, then those helpers likely become even more essential amid the unforgiving conditions and scarce resources of the Outback, resulting in larger groups. Because cooperative breeding in superb fairywrens arises from a surplus of young males looking for love, though, those males should only be inclined to remain as helpers — and pad group numbers — when living in the milder climes that limit their own breeding opportunities.

A dry run

The growth of the global population — nearly 8 billion now, expected to approach 10 billion by 2050 — would be motivation enough to continue breeding and refining crops that can yield more food amid challenging conditions. A parallel increase in the number and severity of droughts, which already contributed to roughly two-thirds of the world’s yield losses over the past 50 years, has only heightened the urgency.

To speed the pace of analyzing how crop varieties respond to drought for the sake of developing those more resistant to it, Husker researchers rely on the Greenhouse Innovation Center. There, conveyor belts ferry corn, sorghum and other plants through various chambers that record the crops with cameras. Some of those cameras see as people do, taking in just the visible portion of the electromagnetic spectrum. Others are hyperspectral, capturing wavelengths from the visible but also the near-infrared portion of the spectrum — those beyond human sight. By using both types of cameras to image plants at regular intervals, then comparing the responses of well-hydrated crops to those deprived of water, researchers can rapidly assess the drought resilience of different crop varieties.

The School of Natural Resources’ Sruti Das Choudhury, Tala Awada and Anastasios Mazis recently joined the School of Computing’s Ashok Samal in developing two algorithms that could help extract yet more information from the imagery generated at the greenhouse. One of those algorithms analyzes a series of visible-spectrum images to predict the onset of drought stress in plants that are drooping but have yet to undergo the discoloration that can stem from dehydration. The other algorithm, which relies on hyperspectral imagery, can essentially map that stress in specific parts of a plant by analyzing the reflection signatures of pixels from the digital images, then classifying each as stressed or unstressed.

When the team compared the percentage of stress-detected pixels against the water content of a plant’s soil, they found a strong correlation between the two — suggesting that the hyperspectral algorithm was performing as intended. The appearance of those pixels also corresponded with the other algorithm’s prediction of drought stress in the plant as a whole.

Together, the researchers said, the algorithms should help better differentiate between crop varieties that are susceptible vs. resistant to drought. Though the team used cotton plants in its case study, the algorithms should prove generalizable to any plant species and even other stressors, including heat and salinity.