Daniel G. Dick: Exploring the relationship between different measures of functional redundancy

Daniel G. Dick: Exploring the relationship between different measures of functional redundancy

In this blog post, Daniel G. Dick, a public education and geoscience communication postdoctoral fellow at McMaster University, Canada, discusses his study “Measuring functional redundancy using generalized Hill numbers”, which has been shortlisted for Functional Ecology’s 2023 Haldane Prize for Early Career Researchers.

About the Paper

Whether an ecological community can withstand an external perturbation (such as rapid global warming) is thought to be largely determined by certain ecosystem-level properties, such as species diversity and functional redundancy. The literature regarding how best to quantify these properties is wide-ranging and complex, and many of the most widely-used metrics can behave in counter-intuitive and hard to understand ways. For example, functional redundancy (a property generally taken to refer to the fraction of a community that plays a non-unique ecological role) can be measured in several different ways. Redundancy can be quantified as an absolute (e.g., “This community can afford to lose 5 species”) or relative property (e.g., “This community can afford to lose 25% of species”), and levels of redundancy can be expressed using a wide variety of units (e.g., probabilities, units of information, effective numbers of species). My manuscript set out to clarify the relationship between these different methods of quantifying functional redundancy, while arguing that a specific relative redundancy metric outperforms the other methods.

The Ilulissat Icefjord in western Greenland, nearby where the author recently conducted research on microbial functional redundancy (Credit: Daniel G. Dick)

Previous authors had shown that the most widely used taxonomic (e.g., the Gini-Simpson index, Shannon entropy) and functional diversity indices (e.g., Rao’s quadratic entropy, Ricotta and Szeidl’s generalized Shannon entropy) are directly related to one another, and fundamentally differ only in terms of the weight they give to rare/common species. Because the choice of how to weight rare/common species can potentially change the outcome of a study, a unified quantitative approach (commonly known as the Hill numbers framework) that includes all possible weighting schemes is widely used in contemporary ecological research. Following these earlier findings, a growing number of researchers have noted that the most widely used functional redundancy indices are related in the same way and can also be restated using a Hill numbers framework. Despite this, the literature on the behaviour of these Hill number-based redundancy metrics is quite sparse. Given all this, a key goal of my paper was filling this gap, elucidating and explaining the behaviour of these Hill number-based redundancy metrics in such a way that would be easily understood by the majority of ecologists. Perhaps the most surprising finding was the observation that when comparing absolute levels of functional redundancy in two or more communities using a Hill numbers framework, the rank ordering of communities can be extremely misleading if the communities differ in terms of species richness.  

Shallow marine communities found in areas like this rocky outcrop in Ilulissat, Greenland contain a staggering array of microbial species, with implications for levels of functional redundancy in the region. Tools like the ones described in my recent manuscript could potentially help us make sense of community stability in areas like this (Credit: Daniel G. Dick)
About the Research

I firmly believe that artificial datasets, constructed to clearly feature certain ecological properties, are the ideal way to test our intuitions about how a given quantitative method behaves. Once you understand how a given method works in a constrained and controlled environment, it becomes easier to understand what the approach is telling you about a real-world community. While I believe my manuscript helped elucidate some of the ways these different redundancy metrics behave, there is still ample opportunity to continue exploring these techniques. Recent research has shown that existing taxonomic and functional diversity indices are connected in more ways than just the weight they give to rare/common species, which suggests that existing functional redundancy metrics can be further generalized. In doing this, the resulting metrics may display even more surprising behaviours, with implications for the communities we study with these tools.   

About the Author
Daniel G. Dick on a recent research trip in western Greenland (Credit: Daniel G. Dick).

I am currently a public education and geoscience communication postdoctoral fellow at McMaster University in Canada, where I work closely with the Association of Professional Geoscientists of Ontario (APGO) Education Foundation. Through my work with the APGO Education Foundation, I aim to bring cutting-edge geoscientific, environmental, and ecological research to the public, through direct outreach, social media, and freely available interactive educational exhibits (e.g., educational hiking guides known as GeoTrails). I am a National Geographic Explorer and was recently awarded a Lindblad Expeditions-National Geographic Visiting Scientist grant, which allowed me to conduct research on board the Lindblad Expeditions ship National Geographic Explorer as the vessel sailed along the west coast of Greenland. I used this opportunity to collect environmental DNA data related to functional redundancy in the region and will be using this data to further test the redundancy metrics described in my manuscript.

Ostracod fossils, seen on a recent research expedition in the Arctic (Credit: Daniel G. Dick)

I became an ecologist through a fairly roundabout process. I began my academic career studying archaeology and evolutionary anthropology, before transitioning over to more general paleontological research focusing on non-human organisms in my PhD at the University of Toronto. During this time, I gradually developed an interest in statistical ecology, which led me to conduct studies like the one described here. The somewhat unorthodox blend of paleontological and statistical research I conducted in my PhD resulted in my dissertation being awarded the Fraser Code Best PhD Thesis Award from the Department of Chemical and Physical Sciences at the University of Toronto Mississauga. If I had one piece of advice for someone in my field, it would be to follow your research interests wherever they lead you – remember that you are not locked into one type of research!

You can find Daniel on Twitter (@danielgdick), Instagram (@danielgdick), and TikTok (@fossilist).

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