When isn’t size everything?

Biodiversity is best protected in large, undisturbed areas; but it seems that not every species will be represented in the largest habitat patches in a landscape. Why?

* See also my essay in The Revelator

Dating back to the 1970s ecologists have been interested (which for scientists generally means disagreeing) in why groups of small patches of habitat often (in fact, nearly always) contain more species than a single large patch of equivalent area. The whole thing blew up when Jared Diamond published six principles for conservation reserve design, based on his research in marine archipelagos, the species-area relationship and MacArthur & Wilson’s theory of island biogeography.

Diamond’s first principle states: A large reserve is better than a small reserve (principle A), for two reasons: the large reserve can hold more species at equilibrium, and it will have lower extinction rates (Diamond 1975, Biol. Cons. 7:129). 

The second part, that extinction rates are lower in larger reserves is pretty uncontroversial even now. To be fair, the first part is also true if you compare only a single small site with a single large site – but that is really more a statement of a well known pattern in ecology known as the species-area relationship rather than a design principle. People soon began wondering if it that part about holding more species was true if multiple small patches of an equivalent area were compared with that single large patch. Probably not as it turns out – a number of authors, starting with Daniel Simberloff and Lawrence Abele writing in the journal Science, made their alternative views on this clear.

Simberloff and Abele suggested that the species-area relationship could be used to argue the opposite conclusion. In a back-of-the-envelope illustration, they showed that unless the large reserve contained nearly every species in the landscape, then two smaller patches of equal area will hold more species. And the more pieces you broke the area into, the more additional species they would collectively contain. These exchanges initiated a long-standing debate in conservation biology as to whether it was better to have a Single Large or Several Small reserves for species conservation. It is known as the SLOSS debate.

People then started getting interested in testing support for the two sides of the SLOSS argument with their data. One way you can do this (at least visually) is by plotting two curves on the same set of axes. Both curves show how many species you accumulate as you combine patches (the y-axis), for the amount of area found in the patches (the x-axis). The difference comes from the way the sites are combined – specifically the order. One curve is built by taking the patches in order of increasing size starting with the smallest, then adding the second smallest and so on until you have combined all of the patches. The other curve plots the same information, only it is calculated by combining patches from the largest to the smallest. For a given amount of accumulated area, the differences can be quite pronounced (as illustrated in the figure below for some wetland plant data from South Australia).

Comparison of the number of species accumulated when combining sites in order of their size. Starting with the smallest site and then adding the next smallest and so on, the blue curve results. Doing the opposite and starting with the largest and adding the second largest and so on, the salmon coloured curve results. For a given proportion of wetland habitat area accumulated, many more species are found in a collection of smaller sites than in the equivalent area spread among larger sites.  Data are vascular plants from 76 Fleurieu Peninsula wetlands and are freely available on the Aekos portal website.


James Quinn & Susan Harrison first introduced the method of comparing the two size-ordered curves and in the same paper analyzed 30 published datasets. They found that in 29 of these the small-to-large order saturated (reached the total number of species) before the large-to-small curve.

Apart from sparking an enduring debate about the relative virtues of single large vs. several small reserves (missing the point a little in my view), this pattern has generated rather little interest. I think there are two interesting aspects to it. First off: why? Why should the diversity of many plant and animal species consistently assemble this way in very different types of patchy island-like habitats?

Second, it is well known that smaller habitat patches in a landscape are more vulnerable to complete loss (this even has a name: ‘attrition’). For example, the smaller a patch is, the more vulnerable it is to extreme climatic cycles (which ponds or wetlands you would expect to dry out first in an extended drought?). They are also easier to clear and generally lack formal protection. The most likely outcome in a human-dominated landscape would be conversion to some human land use.

So perhaps the question we should be asking is how would the loss of these smaller patches affect diversity in that habitat type across the landscape?  If the rapid accumulation of species for a given amount of area is simply widespread generalist species, then loss of small patches would not matter – at least for species numbers. But if they contain some of the rarer species in the landscape, then species diversity could be impacted. This was exactly the question that inspired our recent paper in the journal Global Change Biology.

We first compiled 175 published datasets for all types of discrete habitats. By ‘discrete’ I mean patches of some sort of habitat that were surrounded by some sort of non-habitat. So we included wetlands, ponds and lakes, oceanic and nearshore island archipelagos and even sky islands formed by high-altitude zones of mountain peaks. We also included artificially discrete habitat types – that is remnant fragments of forest or grassland. And we included all types of plants and animals. The only real criterion I had was that the data were something close to a full census of all the species in each surveyed patch.

We then simulated the destruction of the smallest patches to a total of 10 or 20% of the total area and calculated whether any species would be lost from that network of patches. Over 80% of datasets indicated at least some species would indeed be removed, even if all of the largest patches and their species were preserved. That did not surprise me, but the proportion of species that would be lost was a little unsettling. Because even if those smallest patches destroyed represent only 10% of the total area contained in all the patches, on average between 7 and 9% of species would be lost.

That might not sound like much, but it is an outrageously high proportion. By way of comparison, the most widely used species-loss model based on reductions in area (the backwards species-area relationship, described here) would predict about 3% species loss for a 10% loss of area. And this model is prone to over-predict extinctions in continuous habitat areas.

For this result to arise, it must mean that rather a lot of species are found only in those smaller patches. For me, the most interesting thing about the analysis was comparing the patterns of species loss among the datasets and trying to figure out why that is. Although the size-ordered species loss curve for every dataset was unique, there were four clear types of patterns that they could be grouped into. These are interesting because they give us some hints about why it is so commonly the case that some species are found only in those smallest patches.

What happens to species diversity when you remove patches of habitat from the smallest to the largest? Each point shows how many species are lost from the network (on the y-axis) for the proportion of the total area you have accumulated (x-axis). The solid line shows how many species we should expect if species were randomly found in patches and the dashed lines show the uncertainty in that model. Although the shapes of the curves were different for every dataset they all fell into one of four different types of pattern. In panel (a) it does not matter how many small patches were destroyed, no species were lost. This was most common in mammals. In panel (b) species loss was random and this was common in highly disturbed habitats. In the step pattern (c), loss of most small patches does not matter, but occasionally, loss of a single patch leads to loss of species.  Plants and invertebrates lost more species due to their more segregated distributions, mainly following the step and d. linear pattern.

For larger animals we would expect that small patches are a poor to totally unviable habitat and only the most common, generalist species would be found in them. For those species, you could probably destroy all the small patches and still lose no species. And that is exactly what you see in what I called the threshold pattern (top left panel (a) of the figure). That accounted for the roughly 20% of datasets that lost no species and these were mostly vertebrates.

In highly disturbed situations, we might expect more random patterns of occupancy. In that case it is likely that a few species might happen to occur in only the smallest patches. Again, this is consistent with what I found in about 12% of datasets. These included temporary ponds, weeds in vacant lots and also migratory breeding birds that re-colonize each year. The common theme there seems to be regular, high levels of disturbance.

The most interesting and most common (~45% of datasets) pattern for me was what I called the step pattern (panel c, top right). Here you could ‘safely’ throw out most small patches without any species loss, but every now and then removing a patch led to the loss of one or more species. Like the threshold model, it featured a nearly horizontal line on the left side (indicating that few species were lost as small patches were destroyed) and only started to show rapid species loss above some threshold size. But here it was different, because some of those small patches did support species not found in larger patches.

I could imagine two situations where the step pattern could arise. First, maybe some of the small patches were unique in their environmental conditions – maybe a fresh groundwater spring in a largely saline landscape supporting locally rare, less salt-adapted species.

Second, if some species have a minimum patch size threshold, might not some species have a maximum size threshold – patches that are too big for them to live in? The number one reason I can think of for that has to do with predators. If the things that like to eat you need a certain size habitat to exist (say fish in a pond), you might intentionally choose to live in smaller habitats to avoid them. Bill Resetarits at the University of Mississippi has demonstrated exactly this type of pro-small-patch selection behaviour in aquatic beetles and mosquitos in pond mesocosms.

Finally, there were about 20% of datasets where almost every patch destroyed contained some species not found in other patches (lower right, panel d. I called this the linear pattern, but it was not always such a straight line as this dataset). The pattern was most common in more diverse taxa like insects and plants, which require only small areas (at least relative to what humans might call small) to obtain enough resources to live. So this pattern seems to be driven by the scale at which organisms experience environmental heterogeneity – that is, it relates to the breadth of the niche that organism inhabits and it’s energy requirements.

It’s worth considering possible reasons why this pattern might show up in data, but not accurately reflect on-ground reality. Sampling design is a prime candidate, where researchers might (intentionally or not) avoid sampling small patches they know (or believe) to be lacking in species of interest. This seems likely, but I have no way to test it. It is also possible that larger patches are harder to census and rare species were simply easier to spot in the smaller patches. I don’t think that is the case though because there was no evidence of any relationship between survey effort and species loss. Similarly, the proportion of species lost had nothing to do with the sizes of the patches – so if it is just incomplete sampling of larger patches, it is remarkably consistent across scales.

But taking it on face value, I got a few take homes from the work. On the down side, if we were to lose a lot of small patches over a short period of time because of climatic extremes, or if small patches were just being incrementally cleared over time, then it seems likely we will lose some species from that landscape as a result. There is probably rather little we can do about extreme climatic events, but we can educate, encourage and legislate to prevent on-going intentional clearance of natural habitat patches.

I prefer to view it as evidence that preserving every patch of habitat in the landscape is probably of more tangible biodiversity value than I at least had realized. Importantly, the question of who lives where is about habitat quality. And habitat quality is in the eye of the beholder. Size it seems can be a rather poor proxy for habitat quality. That means that even small and isolated patches of habitat could contain species not found anywhere else in that landscape at the moment.

Finally, it’s worth noting that managing a landscape for species diversity is not everyone’s cup of tea. And also that the big headlines on biodiversity loss typically refer to biodiverse hotspots and global, not local, species loss. Fair enough. But my view on that is if we are managing our landscapes sustainably, then most of the native species that are around now, will still be there in a few decades time. The number of individuals in each species will vary depending on seasonal and other cycles and local populations will inevitably blink in and out. But if every time we get around to counting, we find fewer species in the landscape than the last time? Well – it’s hard to be neutral about that.