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
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).
A fine-scale analysis reveals microgeographic hotspots maximizing infection rate between a parasite and its fish host (2021) Mathieu-Bégné et al., Functional Ecology, https://doi.org/10.1111/1365-2435.13967
Image credit: Viridiflavus via Wikimedia Commons, CC BY-SA 3.0
Interactions between hosts and parasites can be broken down into two broad stages: the encounter filter and the compatibility filter. The encounter filter determines whether a parasite actually comes in contact with a host, through either a spatial or temporal overlap. After the encounter filter comes the compatibility filter, the stage at which a parasite either successfully infects a host and takes the resources needed, or is successfully repelled by the host. Though the encounter filter must come before the compatibility filter, most studies tend to focus on the compatibility filter. Yet for a parasite to successfully encounter a host, many obstacles must first be overcome.
Parasites tend to be very small, and hosts tend to be rare. Furthermore, many hosts move around the environment and/or are only available to a parasite at specific times of the year. Finally, in many cases the environment that a single host can occupy is huge. With all of these difficulties facing parasites, it is not surprising that they have evolved many different strategies to effectively find hosts.
However, some species don’t appear to display these strategies. For them to succeed, it is possible that they distribute themselves in a non-random (see Did You Know?) fashion in the environment, clumping together to form “hot-spots” of infection. Other studies have investigated this “hot-spot” phenomenon before, but tended to focus on larger spatial scales, anywhere from hundreds to thousands of meters. Today’s authors wanted to understand if investigations at much smaller spatial scales (i.e., ~10 meters or less) could provide further insight into the spatial aggregation of parasites.
Community ecology, as a relatively new discipline, is fraught with challenges. Here, we look at why an hour spent talking about those challenges may make you feel like the PhD student pictured above (Image Credit: Lau Svensson, CC BY 2.0, Image Cropped)
Anyone who has forayed any small distance into academia will probably understand the following quote by Aristotle.
“The more you know, the more you realize you don’t know.”
According to Stewart Lee, participating in further education means embarking on a “quest to enlarge the global storehouse of all human understanding”. This might be true, yet venturing into academia also means that the more answers you learn to challenging scientific questions, the more questions get opened up. It’s the circle of academic life.
When animals like these wolves travel in packs, spotting one individual means we’re more likely to spot another soon after. So how do we come up with a reliable population estimate in situations like these? (Image Credit: Eric Kilby, CC BY-SA 2.0, Image Cropped)
The thought of an ecologist may conjure the image of a scientist spending their time out in the field counting birds, looking for moss, studying mushrooms. Yet whilst field ecologists remain an integral part of modern ecology, the reality is that much of the discipline has come to rely on complex models. These are the processes which allow us to estimate figures like the 1 billion animals that have died in the recent Australian bushfires, or the potential spread of species further polewards as climate change warms our planet.
When fish like this goby aggregate, the density of their nests can often have a big impact on their success (Image Credit: Laszlo Ilyes, CC BY 2.0, Image Cropped)
Spatial and temporal patterns of nest distribution influence sexual selection in a marine fish (2018) Wong et al.,
Oikos, doi: 10.1111/oik.05058
When we monitor the fluctuations of a population, we often look at vital rates, a huge part of which is reproductive success. The success that males have in siring offspring can be hugely influenced by the density of a population, particularly when it comes to a breeding ground.
Larger males will often outcompete smaller males on such grounds, however in many species these males will often reach reproductive limits, at which point smaller males can benefit. Smaller males may also fare better in less dense populations, where females lack other individuals to compare them to. Our study today looks at variations in reproductive success of a nest-breeding fish species over two levels of density.