An easy solution to a complicated issue

Biodiversity is important. That is a fact, and it would take a fool to deny it. Yet how important is it exactly? How much does it matter how many species an ecosystem has, or which? Ecologists have been searching for answers to these questions for decades now.

24542585418_c071a0bd05_o.jpg

The role of biodiversity – here a highly diverse tropical rainforest in St. Kitts – on the functioning of ecosystems has been the subject of study for decades.

A common approach to search for the role of biodiversity is through experiments with a very simple set-up: make artificial little ‘ecosystems’ with a varying amount of species in it (from 1 to 20 plant species, for example), give them the same treatment, and measure the effect of this varying species richness on the functioning of the ecosystem (through the production of biomass, for example).

Such experiments undeniably revealed that species richness is crucial, with every added species positively affecting the functioning of the ecosystem (albeit less and less significantly so with every extra species added).

 

Fig. 1

Fig. 1: simplified curve of an ecosystem function (i. e. biomass production) as a function of species richness, showing the positive, yet saturating, effect of increasing species richness in an ecosystem.

Yet there is more to biodiversity than species richness alone. What if you have 20 species in your ecosystem, yet one of them takes up 99 percent of the space, leaving only a tiny bit of space for the 19 others? While theoretically a very rich ecosystem, it does not feel like these 19 species can have much of an effect on ecosystem functioning, does it? It doesn’t. The level of dominance of one or a few species in an otherwise species rich ecosystem is expressed as ‘evenness’. A system with all species equally represented is  called ‘even’; a system with one or a few dominant species is named ‘uneven’.

36357524530_d554ee9943_o

Alpine tundra (here in northern Norway) is often highly uneven, as it is dominated by a few dwarf shrub species.

Now you could use the same type of experiments as before to try to unravel the role of this evenness on the functioning of the ecosystem. Unfortunately, this extra dimension makes the amount of combinations  virtually infinite. You would have to vary the relative dominance of several species at several different levels of species richness, and that requires a ton of artificial little ecosystems. For that reason, such experiments are much less frequently executed, and the exact role of evenness in ecosystem functioning had still to be proven conclusively.

And that is exactly where we step in. With our group, we came up with an easy solution for this complicated problem. In our latest paper in the journal Oikos, we show that there is no need for all these demanding experiments varying species evenness. The effects of evenness on ecosystem functioning can easily be derived from the existing richness experiments. It requires only a little trick, as the results of the latter are actually hiding the effects of evenness within them.

This little trick is nothing more than the realisation that a highly uneven ecosystem with one species being dominant, and all others having only one individual, is virtually the same as an ecosystem in which that dominant species is the only one present. Present or not, these individuals of the rare species on average only have the fraction of an impact on ecosystem functions like biomass production.

The great thing is: we already know the ecosystem functioning of the ecosystem with only one species (a monoculture) from the richness experiments, and this can thus simply be transformed to an estimated effect of high unevenness on ecosystem functioning.

Applying this little trick to real experimental data worked great. It also revealed that the effects of species richness and evenness on ecosystem functioning point in the same direction (and are both positive). Moreover, we can now see for all ecosystem functions that the positive effect of evenness increases with increasing richness of the ecosystem, without the need for resource-intensive experiments.

Simple as that.

38390737392_e964a825ee_o.jpg

A true loss of species and a loss of evenness within your species community both have similar negative effects on the functioning of your ecosystem. Picture showing rainforest in Martinique.

To get all the details on our trick, check out the paper!

Lembrechts JJ, De Boeck H, Liao J, Milbau A, Nijs I (2017). Effects of species evenness can be derived from species richness – ecosystem functioning relationships. Oikos. 10.1111/oik.04786.

This entry was posted in Science and tagged , , , , , , , , . Bookmark the permalink.

5 Responses to An easy solution to a complicated issue

  1. Erik says:

    Need to read it. But sounds a bit like partitioning selection from complementarity effects?

  2. Pingback: Our paper in Oikos | On top of the world

  3. steffen says:

    I am not quite sure I follow your reasoning. Specifically, you claim “Present or not, these individuals of the rare species on average only have the fraction of an impact on ecosystem functions like biomass production.”, but everybody who has weeded on the Exploratories already, knows that this is not true. There are some species that “just come from nowhere” and “take over the ecosystem, if not removed”; weeds. Doesn’t this invalidate the reasoning to a degree that what you claim here is only valid, when looking at relatively similar species within one plot (i.e. “only herbs” or “only trees”; but then again, there are also ruderals witin each of these groups)? Looking forward to your thoughts on this issue.

    • Thanks for your comment, and bringing up an interesting point we gave long debates as well.
      So there is a few things to answer it:
      First, yes indeed, most diversity experiments use only herbs or only trees, which makes interpretation a lot easier. More importantly, diversity experiments usually start off with all species on more or less the same terms. For a species richness-experiment to be about purely species richness only, you need it to be even, with all involved species more or less at the same level, which usually counts for both the amount of individuals ànd for the initial biomass. The more you derive from that initial evenness to start with, the less pure your richness-effects will be, and consequently the less valid the conversion using our approach would be.
      But even if you start off pretty even, there is some species that might grow a lot faster than others, as you point out correctly, that will skew the composition of your artificial ecosystem over time. When that happens, it becomes again much harder to see the pure richness effects through the increasing noise. This is the reason why experiments searching for pure biodiversity experiments are limited in time over which they can run: leave them running for so long that the species composition gets too dramatically skewed, and your pure initial richness effects will get intertwined with realized evenness effects. The latter has value of its own, of course, and several great studies have looked into this realized biodiversity as well, but it is important to make the difference.
      As these issues are inherent to experiments looking for the pure effects of initial species richness, and we limit our approach to the conversion of those experiments to initial species evenness, we feel that the approach is valid. Indeed, as a pure richness experiment will try to measure the effects before one weedy species takes over, we can assume that our virtual species – which is added in much lower densities than it is present in the richness experiment – will not have sufficient time to take over.
      Note that these pure biodiversity effects we are after here are because of these issues hard to deduce in real-life conditions, as they will always be intertwined with the effects of biotic interactions and other dynamics. The search for pure biodiversity effects is thus one for a hidden effect, that needs controlled conditions and ideally a set-up ‘frozen in time’ to deduce.
      Hope that answers the question!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s