The Water of Life

Image credit: Muséum de Toulouse, CC BY-SA 4.0, via Wikimedia Commons

Top-down response to spatial variation in productivity and bottom-up response to temporal variation in productivity in a long-term study of desert ants (2022) Gibb et al., Biology Letters, https://doi.org/10.1098/rsbl.2022.0314

The Crux

Ecosystem productivity can tell us a lot about how an ecosystem functions. The more productive an ecosystem is, the more life it can support. But productivity doesn’t just affect the diversity or number of species within an ecosystem, it affects how those species interact, from the large carnivores you find at the upper levels, to the plants and bacteria down the ‘bottom’.

Within ecosystems, the strength of a top-down process (something influencing those upper levels) vs. a bottom-up process (something influencing the lower levels) depends on how much primary productivity there is. Primary production occurs when a species makes its own energy instead of eating something else, and when there is a lot of it going around, it often allows the carnivores at the upper trophic levels to suppress the population numbers of herbivores. That means that while a bottom-up process may end up affecting the herbivores, a top-down process (like the hunting of carnivores) might impact the entire ecosystem.

On the other side of the spectrum, when there is little primary productivity, there aren’t usually as many carnivores suppressing the herbivore populations. A bottom-up process will increase herbivore numbers, making these bottom-up processes more important in these low-productivity systems. This is known as the Exploitation Ecosystem Hypothesis (EEH).

Did You Know: Ecosystem Productivity

Ecosystem productivity is a measure of how much biological mass an ecosystem produces, and is measured as a units of mass, per unit surface area, per unit time (i.e., grams per meter squared per day). At its simplest, think about it like the flow of energy through an ecosystem. Energy comes from the sun (or other abiotic sources), which is then captured and used by primary producers like plants. Those primary producers are then consumed by primary consumers (like herbivores), which are in turn consumed by secondary consumers (like predators). The more energy there is, the more primary producers there can be, which means there can be more primary consumers, which means there can be more secondary consumers, and so forth.

What They Did

Using data from a 22-year survey of ants in the sand dunes of the Simpson Desert in Australia, the authors quantified how ants responded to spatial and temporal variation in productivity. Ants make a great model system for this kind of question, because although they are usually thought of as omnivores, they can also act as primary consumers, generalists, or even specialized predators.

Due to the EEH, the authors predicted that they would detect greater effects on secondary consumers (measured as activity rates) in the more productive habitats like dune swales (the valley-like areas between dune crests), due to a top-down effect of the increased productivity on the secondary consumers. In contrast, temporal increases in productivity (due to rain) are likely to be too quick to generate an effect on the entire ecosystem, instead it should only have a bottom-up effect on the primary consumer ants (in the form of greater activity rates), but not the secondary consumers.

What They Found

In line with their predictions, the authors found that generalist ants were more active in the dune swales (the more productive location) than in the dune crests. They also found that they were more active in the spring (the more productive season) than in winter. Primary consumers, like seed harvesting ants, increased their activity during seeding and with long-term precipitation, but there was no difference in their activity rates between the dune crests and swales. Results from statistical models confirmed these differences in activity between the crests and swales, with this effect of position being three times as strong on the predators relative to the other groups.

A dune crest, an area that is much less productive than the swales (not shown here, but they would be to the left and right of this crest). Image credit: Fabio Rose, CC0, via Wikimedia Commons

Problems?

I can’t find any major faults in this study, the authors did a great job of using a long-term dataset to conduct an elegant set of analyses to determine how ecosystem productivity structured trophic systems. My only issue is that it’s left me insatiably curious as to how these dynamics play out in other systems in other, more productive ecosystems like forests. Utilizing a desert as a model system is a great start, and future researchers can use the methods laid out in this paper to ask the same questions in other habitats.

So What?

The results from this detailed study have shown that both spatial and temporal variation in ecosystem productivity has the potential to shape ecological communities. Of interest is how these results showed that both the magnitude and scale of this variation may be as important as the dimension (i.e., space and time). This is an exciting initial step in understanding the effects of variation in ecosystem productivity, and like today’s authors I am looking forward to seeing the results from other long-term datasets.


Dr. Adam Hasik is an evolutionary ecologist and Zuckerman Postdoctoral Fellow interested in the ecological and evolutionary dynamics of host-parasite interactions who lives right next door to some dune crests and swales, though neither seems particularly productive. You can read more about his research and his work for Ecology for the Masses here, see his personal website here, or follow him on Twitter here.

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