Four decades of fragmentation

27 09 2017

fragmented

I’ve recently read perhaps the most comprehensive treatise of forest fragmentation research ever compiled, and I personally view this rather readable and succinct review by Bill Laurance and colleagues as something every ecology and conservation student should read.

The ‘Biological Dynamics of Forest Fragments Project‘ (BDFFP) is unquestionably one of the most important landscape-scale experiments ever conceived and implemented, now having run 38 years since its inception in 1979. Indeed, it was way ahead of its time.

Experimental studies in ecology are comparatively rare, namely because it is difficult, expensive, and challenging in the extreme to manipulate entire ecosystems to test specific hypotheses relating to the response of biodiversity to environmental change. Thus, we ecologists tend to rely more on mensurative designs that use existing variation in the landscape (or over time) to infer mechanisms of community change. Of course, such experiments have to be large to be meaningful, which is one reason why the 1000 km2 BDFFP has been so successful as the gold standard for determining the effects of forest fragmentation on biodiversity.

And successful it has been. A quick search for ‘BDFFP’ in the Web of Knowledge database identifies > 40 peer-reviewed articles and a slew of books and book chapters arising from the project, some of which are highly cited classics in conservation ecology (e.g., doi:10.1046/j.1523-1739.2002.01025.x cited > 900 times; doi:10.1073/pnas.2336195100 cited > 200 times; doi:10.1016/j.biocon.2010.09.021 cited > 400 times; and doi:10.1111/j.1461-0248.2009.01294.x cited nearly 600 times). In fact, if we are to claim any ecological ‘laws’ at all, our understanding of fragmentation on biodiversity could be labelled as one of the few, thanks principally to the BDFFP. Read the rest of this entry »





Palaeo-ecology PhD scholarships

1 03 2017

scholarshipWith my new position as Matthew Flinders Fellow in Global Ecology at Flinders University, I am in the agreeable position to be able to offer two PhD scholarships to the best candidates from around the world. If you feel that you’re up to the challenge, I look forward to hearing from you.

These projects will be in the following palaeo-ecology topics:

PhD Project #1. Ecological networks to examine community cascades of Late Quaternary megafauna extinctions Read the rest of this entry »





Ice Age? No. Abrupt warmings and hunting together polished off Holarctic megafauna

24 07 2015
Oh shit oh shit oh shit ...

Oh shit oh shit oh shit …

Did ice ages cause the Pleistocene megafauna to go extinct? Contrary to popular opinion, no, they didn’t. But climate change did have something to do with them, only it was global warming events instead.

Just out today in Science, our long-time-coming (9 years in total if you count the time from the original idea to today) paper ‘Abrupt warmings drove Late Pleistocene Holarctic megafaunal turnover‘ led by Alan Cooper of the Australian Centre for Ancient DNA and Chris Turney of the UNSW Climate Change Research Centre demonstrates for the first time that abrupt warming periods over the last 60,000 years were at least partially responsible for the collapse of the megafauna in Eurasia and North America.

You might recall that I’ve been a bit sceptical of claims that climate changes had much to do with megafauna extinctions during the Late Pleistocene and early Holocene, mainly because of the overwhelming evidence that humans had a big part to play in their demise (surprise, surprise). What I’ve rejected though isn’t so much that climate had nothing to do with the extinctions; rather, I took issue with claims that climate change was the dominant driver. I’ve also had problems with blanket claims that it was ‘always this’ or ‘always that’, when the complexity of biogeography and community dynamics means that it was most assuredly more complicated than most people think.

I’m happy to say that our latest paper indeed demonstrates the complexity of megafauna extinctions, and that it took a heap of fairly complex datasets and analyses to demonstrate. Not only were the data varied – the combination of scientists involved was just as eclectic, with ancient DNA specialists, palaeo-climatologists and ecological modellers (including yours truly) assembled to make sense of the complicated story that the data ultimately revealed. Read the rest of this entry »





Avoiding genetic rescue not justified on genetic grounds

12 03 2015
Genetics to the rescue!

Genetics to the rescue!

I had the pleasure today of reading a new paper by one of the greatest living conservation geneticists, Dick Frankham. As some of CB readers might remember, I’ve also published some papers with Dick over the last few years, with the most recent challenging the very basis for the IUCN Red List category thresholds (i.e., in general, they’re too small).

Dick’s latest paper in Molecular Ecology is a meta-analysis designed to test whether there are any genetic grounds for NOT attempting genetic rescue for inbreeding-depressed populations. I suppose a few definitions are in order here. Genetic rescue is the process, either natural or facilitated, where inbred populations (i.e., in a conservation sense, those comprising too many individuals bonking their close relatives because the population in question is small) receive genes from another population such that their overall genetic diversity increases. In the context of conservation genetics, ‘inbreeding depression‘ simply means reduced biological fitness (fertility, survival, longevity, etc.) resulting from parents being too closely related.

Seems like an important thing to avoid, so why not attempt to facilitate gene flow among populations such that those with inbreeding depression can be ‘rescued’? In applied conservation, there are many reasons given for not attempting genetic rescue: Read the rest of this entry »





More species = more resilience

8 01 2014

reef fishWhile still ostensibly ‘on leave’ (side note: Does any scientist really ever take a proper holiday? Perhaps a subject for a future blog post), I cannot resist the temptation to blog about our lab’s latest paper that just came online today. In particular, I am particularly proud of Dr Camille Mellin, lead author of the study and all-round kick-arse quantitative ecologist, who has outdone herself on this one.

Today’s subject is one I’ve touched on before, but to my knowledge, the relationship between ‘diversity’ (simply put, ‘more species’) and ecosystem resilience (i.e., resisting extinction) has never been demonstrated so elegantly. Not only is the study elegant (admission: I am a co-author and therefore my opinion is likely to be biased toward the positive), it demonstrates the biodiversity-stability hypothesis in a natural setting (not experimental) over a range of thousands of kilometres. Finally, there’s an interesting little twist at the end demonstrating yet again that ecology is more complex than rocket science.

Despite a legacy of debate, the so-called diversity-stability hypothesis is now a widely used rule of thumb, and its even implicit in most conservation planning tools (i.e., set aside areas with more species because we assume more is better). Why should ‘more’ be ‘better’? Well, when a lot of species are interacting and competing in an ecosystem, the ‘average’ interactions that any one species experiences are likely to be weaker than in a simpler, less diverse system. When there are a lot of different niches occupied by different species, we also expect different responses to environmental fluctuations among the community, meaning that some species inherently do better than others depending on the specific disturbance. Species-rich systems also tend to have more of what we call ‘functional redundancy‘, meaning that if one species providing an essential ecosystem function (e.g., like predation) goes extinct, there’s another, similar species ready to take its place. Read the rest of this entry »





Cleaning up the rubbish: Australian megafauna extinctions

15 11 2013

diprotodonA few weeks ago I wrote a post about how to run the perfect scientific workshop, which most of you thought was a good set of tips (bizarrely, one person was quite upset with the message; I saved him the embarrassment of looking stupid online and refrained from publishing his comment).

As I mentioned at the end of post, the stimulus for the topic was a particularly wonderful workshop 12 of us attended at beautiful Linnaeus Estate on the northern coast of New South Wales (see Point 5 in the ‘workshop tips’ post).

But why did a group of ecological modellers (me, Barry Brook, Salvador Herrando-Pérez, Fréd Saltré, Chris Johnson, Nick Beeton), ancient DNA specialists (Alan Cooper), palaeontologists (Gav Prideaux), fossil dating specialists (Dizzy Gillespie, Bert Roberts, Zenobia Jacobs) and palaeo-climatologists (Michael Bird, Chris Turney [in absentia]) get together in the first place? Hint: it wasn’t just the for the beautiful beach and good wine.

I hate to say it – mainly because it deserves as little attention as possible – but the main reason is that we needed to clean up a bit of rubbish. The rubbish in question being the latest bit of excrescence growing on that accumulating heap produced by a certain team of palaeontologists promulgating their ‘it’s all about the climate or nothing’ broken record.

Read the rest of this entry »





Biogeography comes of age

22 08 2013

penguin biogeographyThis week has been all about biogeography for me. While I wouldn’t call myself a ‘biogeographer’, I certainly do apply a lot of the discipline’s techniques.

This week I’m attending the 2013 Association of Ecology’s (INTECOL) and British Ecological Society’s joint Congress of Ecology in London, and I have purposefully sought out more of the biogeographical talks than pretty much anything else because the speakers were engaging and the topics fascinating. As it happens, even my own presentation had a strong biogeographical flavour this year.

Although the species-area relationship (SAR) is only one small aspect of biogeography, I’ve been slightly amazed that after more than 50 years since MacArthur & Wilson’s famous book, our discipline is still obsessed with SAR.

I’ve blogged about SAR issues before – what makes it so engaging and controversial is that SAR is the principal tool to estimate overall extinction rates, even though it is perhaps one of the bluntest tools in the ecological toolbox. I suppose its popularity stems from its superficial simplicity – as the area of an (classically oceanic) island increases, so too does the total number of species it can hold. The controversies surrounding such as basic relationship centre on describing the rate of that species richness increase with area – in other words, just how nonlinear the SAR itself is.

Even a cursory understanding of maths reveals the importance of estimating this curve correctly. As the area of an ‘island’ (habitat fragment) decreases due to human disturbance, estimating how many species end up going extinct as a result depends entirely on the shape of the SAR. Get the SAR wrong, and you can over- or under-estimate the extinction rate. This was the crux of the palaver over Fangliang He (not attending INTECOL) & Stephen Hubbell’s (attending INTECOL) paper in Nature in 2011.

The first real engagement of SAR happened with John Harte’s maximum entropy talk in the process macroecology session on Tuesday. What was notable to me was his adamant claim that the power-law form of SAR should never be used, despite its commonness in the literature. I took this with a grain of salt because I know all about how messy area-richness data can be, and why one needs to consider alternate models (see an example here). But then yesterday I listened to one of the greats of biogeography – Robert Whittaker – who said pretty much the complete opposite of Harte’s contention. Whittaker showed results from one of his papers last year that the power law was in fact the most commonly supported SAR among many datasets (granted, there was substantial variability in overall model performance). My conclusion remains firm – make sure you use multiple models for each individual dataset and try to infer the SAR from model-averaging. Read the rest of this entry »