Joren Snoeks finished his MSc thesis at KULeuven and joins us to study the ecological and evolutionary role of ancient granite inselbergs in landscapes. Besides from his PhD, Joren will also teach a number of practicals in our BSc program.
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In a new paper out in Scientific Reports, we use a matrix population model to test how sensitive populations of fairy shrimps are to changes in climate. The stepwise modeling procedure allows to calculate the long term population growth as a measure of fitness. If it is positive, the population will survive, if it is negative it will not. It does this by calculating, for each generation, how many eggs would be produced based on known life history traits of the species and a measure of environmental quality of the inundation (in this case represented by inundation length).
For most species it is very difficult to know how they would respond to changes in climate. However, for our fairy shrimp we have a lot of background information that allows us to make educated guesses about which life history traits could be important. We know for this species that it requires a specific amount of time to reproduce which is related to how long a pool can hold water and on the conditions they need to hatch. We also know how much eggs they can produce per day, how many eggs hatch during each inundation etc…
The length of these inundations is one environmental parameter (of many) that will change under changing climates. But it is an important one that is directly linked to fitness. Shorter inundations means less inundations that are long enough for reproduction.
We were – and are – still ignorant about how these species will respond to these changes. However, the model does allow us to test which life history traits could be important to maintain long term survival of the populations. As such it shows which traits could help populations to survive.
One of the conclusions of the study is that, when inundations are short, it would be beneficial to make sure that a lower fraction of eggs would hatch during a given inundation. Such a mechanism could be an example of a risk spreading theory that is consistent with predictions of evolutionary bet hedging theory.
It is still a simplistic model, so it does not tell us how things will go in the future. It does not capture tradeoffs among life history traits nor the evolutionary potential of the populations. Yet, it still narrows down the range of possible future scenarios of these populations by showing what the consequences for population survival would be if populations could respond adaptively or plastically and change there life history traits.
Falko wrote a great summary for his recent idea paper in Frontiers of Biogeography!
No matter at which scale you look at it, nature is remarkable.
Like many others, I was taught ecology in a very hierarchical way: individual organisms are part of a wider populations of species, collections of species form communities and communities come together to make up ecosystems. Similarly, single trees are nested within forests, which aggregate to form biomes. I’m sure you can come up with many comparable examples.
The trouble with such neat spatial hierarchies is that they lure us into believing that if patterns appear similar at several different spatial scales, then the processes leading to these patterns should also be similar. It’s so easy to assume that nature is like a set of Russian Dolls: each daughter exactly the same as its mother, only slightly smaller. But this is not necessarily the case.
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A joint inter university collaboration was set up between the Flemish universities and the Nelson Mandela institute of Science and Technology in Arusha, Tanzania. The project was officially launched in September 2013. Within the project, which will run for at least six years, I will be supervising a PhD student working on the ecology of wetlands in the Pangani floodplain. The aim is investigate the impact of variation in hydrology and anthropogenic disturbance on wetland functioning and biodiversity, quantify ecosystem services and formulate more effective management strategies.
During the 2013 expedition we sampled a total of 600 rock pools from 50 inselbergs in Western Australia. The dataset wil be used to get more insight in the drivers of diversity patterns across spatial scales.