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), geneticists, 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 »





Software tools for conservation biologists

8 04 2013

computer-programmingGiven the popularity of certain prescriptive posts on ConservationBytes.com, I thought it prudent to compile a list of software that my lab and I have found particularly useful over the years. This list is not meant to be comprehensive, but it will give you a taste for what’s out there. I don’t list the plethora of conservation genetics software that is available (generally given my lack of experience with it), but if this is your chosen area, I’d suggest starting with Dick Frankham‘s excellent book, An Introduction to Conservation Genetics.

1. R: If you haven’t yet loaded the open-source R programming language on your machine, do it now. It is the single-most-useful bit of statistical and programming software available to anyone anywhere in the sciences. Don’t worry if you’re not a fully fledged programmer – there are now enough people using and developing sophisticated ‘libraries’ (packages of functions) that there’s pretty much an application for everything these days. We tend to use R to the exclusion of almost any other statistical software because it makes you learn the technique rather than just blindly pressing the ‘go’ button. You could also stop right here – with R, you can do pretty much everything else that the software listed below does; however, you have to be an exceedingly clever programmer and have a lot of spare time. R can also sometimes get bogged down with too much filled RAM, in which case other, compiled languages such as PYTHON and C# are useful.

2. VORTEX/OUTBREAK/META-MODEL MANAGER, etc.: This suite of individual-based projection software was designed by Bob Lacy & Phil Miller initially to determine the viability of small (usually captive) populations. The original VORTEX has grown into a multi-purpose, powerful and sophisticated population viability analysis package that now links to its cousin applications like OUTBREAK (the only off-the-shelf epidemiological software in existence) via the ‘command centre’ META-MODEL MANAGER (see an examples here and here from our lab). There are other add-ons that make almost any population projection and hindcasting application possible. And it’s all free! (warning: currently unavailable for Mac, although I’ve been pestering Bob to do a Mac version).

3. RAMAS: RAMAS is the go-to application for spatial population modelling. Developed by the extremely clever Resit Akçakaya, this is one of the only tools that incorporates spatial meta-population aspects with formal, cohort-based demographic models. It’s also very useful in a climate-change context when you have projections of changing habitat suitability as the base layer onto which meta-population dynamics can be modelled. It’s not free, but it’s worth purchasing. Read the rest of this entry »





Want to work with us?

22 03 2013
© Beboy-Fotolia

© Beboy-Fotolia

Today we announced a HEAP of positions in our Global Ecology Lab for hot-shot, up-and-coming ecologists. If you think you’ve got what it takes, I encourage you to apply. The positions are all financed by the Australian Research Council from grants that Barry Brook, Phill Cassey, Damien Fordham and I have all been awarded in the last few years. We decided to do a bulk advertisement so that we maximise the opportunity for good science talent out there.

We’re looking for bright, mathematically adept people in palaeo-ecology, wildlife population modelling, disease modelling, climate change modelling and species distribution modelling.

The positions are self explanatory, but if you want more information, just follow the links and contacts given below. For my own selfish interests, I provide a little more detail for two of the positions for which I’m directly responsible – but please have a look at the lot.

Good luck!

CJA Bradshaw

Job Reference Number: 17986 & 17987

The world-leading Global Ecology Group within the School of Earth and Environmental Sciences currently has multiple academic opportunities. For these two positions, we are seeking a Postdoctoral Research Associate and a Research Associate to work in palaeo-ecological modelling. Read the rest of this entry »





Science immortalised in cartoon

1 02 2013

Well, this is a first for me (us).

I’ve never had a paper of ours turned into a cartoon. The illustrious and brilliant ‘First Dog on the Moon‘ (a.k.a. Andrew Marlton) who is chief cartoonist for Australia’s irreverent ‘Crikey‘ online news magazine just parodied our Journal of Animal Ecology paper No need for disease: testing extinction hypotheses for the thylacine using multispecies metamodels that I wrote about a last month here on ConservationBytes.com.

Needless to say, I’m chuffed as a chuffed thing.

Enjoy!

Stripey





Translocations: the genetic rescue paradox

14 01 2013

helphindranceHarvesting and habitat alteration reduce many populations to just a few individuals, and then often extinction. A widely recommended conservation action is to supplement those populations with new individuals translocated from other regions. However, crossing local and foreign genes can worsen the prospects of recovery.

We are all hybrids or combinations of other people, experiences and things. Let’s think of teams (e.g., engineers, athletes, mushroom collectors). In team work, isolation from other team members might limit the appearance of innovative ideas, but the arrival of new (conflictive) individuals might in fact destroy group dynamics altogether. Chromosomes work much like this – too little or too much genetic variability among parents can break down the fitness of their descendants. These pernicious effects are known as ‘inbreeding depression‘ when they result from reproduction among related individuals, and ‘outbreeding depression‘ when parents are too genetically distant.

CB_OutbreedingDepression Photo
Location of the two USA sites providing spawners of largemouth bass for the experiments by Goldberg et al. (3): the Kaskaskia River (Mississipi Basin, Illinois) and the Big Cedar Lake (Great Lakes Basin, Wisconsin). Next to the map is shown an array of three of the 72-litre aquaria in an indoor environment under constant ambient temperature (25 ◦C), humidity (60%), and photoperiod (alternate 12 hours of light and darkness). Photo courtesy of T. Goldberg.

Recent studies have revised outbreeding depression in a variety of plants, invertebrates and vertebrates (1, 2). An example is Tony Goldberg’s experiments on largemouth bass (Micropterus salmoides), a freshwater fish native to North America. Since the 1990s, the USA populations have been hit by disease from a Ranavirus. Goldberg et al. (3) sampled healthy individuals from two freshwater bodies: the Mississipi River and the Great Lakes, and created two genetic lineages by having both populations isolated and reproducing in experimental ponds. Then, they inoculated the Ranavirus in a group of parents from each freshwater basin (generation P), and in the first (G1) and second (G2) generations of hybrids crossed from both basins. After 3 weeks in experimental aquaria, the proportion of survivors declined to nearly 30% in G2, and exceeded 80% in G1 and P. Clearly, crossing of different genetic lineages increased the susceptibility of this species to a pathogen, and the impact was most deleterious in G2. This investigation indicates that translocation of foreign individuals into a self-reproducing population can not only import diseases, but also weaken its descendants’ resistance to future epidemics.

A mechanism causing outbreeding depression occurs when hybridisation alters a gene that is only functional in combination with other genes. Immune systems are often regulated by these complexes of co-adapted genes (‘supergenes’) and their disruption is a potential candidate for the outbreeding depression reported by Goldberg et al. (3). Along with accentuating susceptibility to disease, outbreeding depression in animals and plants can cause a variety of deleterious effects such as dwarfism, low fertility, or shortened life span. Dick Frankham (one of our collaborators) has quantified that the probability of outbreeding depression increases when mixing takes place between (i) different species, (ii) conspecifics adapted to different habitats, (iii) conspecifics with fixed chromosomal differences, and (iv) populations free of genetic flow with other populations for more than 500 years (2).

A striking example supporting (some of) those criteria is the pink salmon (Oncorhynchus gorbuscha) from Auke Creek near Juneau (Alaska). The adults migrate from the Pacific to their native river where they spawn two years after birth, with the particularity that there are two strict broodlines that spawn in either even or odd year – that is, the same species in the same river, but with a lack of genetic flow between populations. In vitro mixture of the two broodlines and later release of hybrids in the wild have shown that the second generation of hybrids had nearly 50% higher mortality rates (i.e., failure to return to spawn following release) when born from crossings of parents from different broodlines than when broodlines were not mixed (4).

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The biggest go first

11 12 2012
© James Cameron

© James Cameron

The saying “it isn’t rocket science” is a common cliché in English to state, rather sarcastically, that something isn’t that difficult (with the implication that the person complaining about it, well, shouldn’t). But I really think we should change the saying to “it isn’t ecology”, for ecology is perhaps one of the most complex disciplines in science (whereas rocket science is just ‘complicated’). One of our main goals is to predict how ecosystems will respond to change, yet what we’re trying to simplify when predicting is the interactions of millions of species and individuals, all responding to each other and to their outside environment. It becomes quickly evident that we’re dealing with a system of chaos. Rocket science is following recipes in comparison.

Because of this complexity, ecology is a discipline plagued by a lack of generalities. Few, if any, ecological laws exist. However, we do have an abundance of rules of thumb that mostly apply in most systems. I’ve written about a few of them here on ConservationBytes.com, such as the effect of habitat patch size on species diversity, the importance of predators for maintaining ecosystem stability, and that low genetic diversity doesn’t exactly help your chances of persisting. Another big one is, of course, that in an era of rapid change, big things tend to (but not always – there’s that lovely complexity again) drop off the perch before smaller things do.

The prevailing wisdom is that big species have slower life history rates (reproduction, age at first breeding, growth, etc.), and so cannot replace themselves fast enough when the pace of their environment’s change is too high. Small, rapidly reproducing species, on the other hand, can compensate for higher mortality rates and hold on (better) through the disturbance. Read the rest of this entry »