It has become routine in ecology to assume that
biodiversity is, at
least to some degree, responsible for the functioning of ecological
communities. This notion is now the foundation of a major argument in
favour of conservation, though some do question it. As usual, the
extent to which it is true critically depends on the precise
definitions used for both biodiversity and ecosystem function. If we
define biodiversity as the system’s total functional information, then
function rather obviously follows from that. For this reason, we
believe the
ideas presented on this website cast a strong light on the Biodiversity
- Ecosystem Function debate.
Below we show one of the most comprehensive BEF relations, generated by
simulation of ecological communities, to date (Fung et al., 2015). The
graph shows the effect of gradually removing 'species'
(from right to left on the x-axis), from a system of originally several
thousand (though only the simulated 'fish' species are removed).
Clearly there is a systematic relationship between the production rate
(growth and reproduction of fish) and species richness. However,
production rate is a single and rather crude measure of ecological
function and it is not surprising that in this measure, we see evidence
of considerable functional redundancy among 'species'. What is really
happening here is that as species are lost, others take up the workload
of production in compensation, but gradually the extra workload for
each of those fewer and fewer remaining species becomes relatively
greater - they fall behind in their compensating and the curve dips
down. This has little to do with information, but that is because it is
so crude a representation of both biodiversity and function. We would
like to develop a more sophisticated simulation, but that currently
awaits the necessary funding.
In this figure, you see the effect of
reducing (or increasing) species diversity on the function of biomass
production. The jagged scatter is a result of random species
deletions (each individual species makes a different contribution to
total production and they were selected for deletion at random). The
red line shows what happens when the system is
not allowed to adjust to a new equilibrium (rebalance). The black line
shows the effect of this rebalancing in which the remaining species are
able to adjust to the loss of the removed species. The dashed lines
show statistical models of the biodiversity-function relationship. The
Michaelis Mentin function fits best. The overall result is a prediction
that as species are lost, we would find it hard to detect in total
production, until perhaps as many as half had gone. By that time it
might be too late - it certainly would be for the species lost. Of
course the obvious answer to this is to regularly survey the whole
system, checking that all the species are still present. The practical
impediment to that is that it would cost a lot more money than is
allocated to this sort of work: we are often left trying to imply the
biodiversity from signals like the commercial landings of fish.
In practice, fishing, forestry and other human activities are not
affecting species at random: typically the largest, longest living and
highest in foodchains (trophic level) organisms are most at risk. Fung
et al. 2015, went on to examine the effect of deleting species in rank
order and the result was even more striking.
Deleting
in reverse order of trophic level (green line) actually caused an
initial increase in ecosystem function, before it crashed down after
about 2/3 of the species had been eliminated. Conversely, deleting in
reverse order of the biomass of individual species populations (red
line) resulted in a curve that declined sharply as the first few
species were deleted and gradually smoothed out, but at significantly
lower production than all the other scenarios. The, often assumed,
Michaelis-Menten shape was lost in both these cases and clearly only
pertains to random species deletion. Since overfishing typically
depleats species from highest to lowest trophic level, the green line
is to be expected and this may explain the prevalence of sudden crashes
in heavily exploited systems such as the Grand Banks cod fishery (which
might never recover).
Apart from the obvious practical importance of these curves, what they
show is that the function of the species, not their identity is what
determines the shape of the BEF relation. In this case, despite its
aparent complexity, the system is really very simple: just made up of
predator-prey (trophic) relations and the only function represented is
that of consuming. The only difference among the species here is their
trophic level. So the question which arises is what would the curve
look like if we had included all the ecological interactions, including
parasitism and mutualism? Further, the connections among the organisms
are not random, nor so simply ordered as in the fish example in Fung et
al. (2015). Indeed, the specific web of interconnections of a real
ecological community are an embodiment of functional information in
themselves.
Fung, T. Farnsworth, K.D. Reid, D.G., Rossberg A.G. (2015).
Impact of biodiversity loss on production in complex marine food webs
mitigated by prey-release. Nature Comms. 6. 10.1038/ncomms7657