Two new postdoctoral positions in ecological network & vegetation modelling announced

21 07 2017

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With the official start of the new ARC Centre of Excellence for Australian Biodiversity and Heritage (CABAH) in July, I am pleased to announce two new CABAH-funded postdoctoral positions (a.k.a. Research Associates) in my global ecology lab at Flinders University in Adelaide (Flinders Modelling Node).

One of these positions is a little different, and represents something of an experiment. The Research Associate in Palaeo-Vegetation Modelling is being restricted to women candidates; in other words, we’re only accepting applications from women for this one. In a quest to improve the gender balance in my lab and in universities in general, this is a step in the right direction.

The project itself is not overly prescribed, but we would like something along the following lines of inquiry: Read the rest of this entry »





Job: Research Fellow in Palaeo-Ecological Modelling

13 04 2017

© seppo.net

I have another postdoctoral fellowship to advertise! All the details you need for applying are below.

KEY PURPOSE 

Scientific data such as fossil and archaeological records used as proxy to reconstruct past environments and biological communities (including humans) are sparse, often ambiguous or contradictory when establishing any consensus on timing or routes of initial human arrival and subsequent spread, the timing or extent of major changes in climate and other environmental perturbations, or the timing or regional pattern of biological extinctions.

The Research Fellow (Palaeo-Ecological Modelling) will assist in addressing these problems by developing state-of-the-art analytical and simulation tools to infer regional pattern of both the timing of human colonisation and megafauna extinction based on incomplete and sparse dataset, and investigating past environmental changes and human responses to identify their underlying causes and consequences on Australia’s landscapes, biodiversity and cultural history.

ORGANISATIONAL ENVIRONMENT 

The position will be based in the School of Biological Sciences in the Faculty of Science & Engineering at Flinders University. Flinders University boasts a world-class Palaeontology Research Group (PRG) and the new Global Ecology Research Laboratory that have close association with the research-intensive South Australian Museum. These research groups contribute to building a dynamic research environment that explores the continuum of environmental and evolutionary research from the ancient to modern molecular ecology and phylogeography. The School of Biological Sciences is an integrated community researching and teaching biology, and has a long history of science innovation. The appointee will join an interdisciplinary school of approximately 45 academic staff. The teaching and research activities of the School are supported by a range of technical and administrative infrastructure services.

KEY RESPONSIBILITIES

The key responsibilities and selection criteria identified for this position should be read in conjunction with the Flinders University Academic Profiles for the relevant academic classification (scroll down to Academic Profiles).

The Research Fellow (Palaeo-Ecological Modelling) will work under the direction of the Project Chief Investigator, and will be required to: Read the rest of this entry »





Not 100% renewable, but 0% carbon

5 04 2017

635906686103388841-366754148_perfection1Anyone familiar with this blog and our work on energy issues will not be surprised by my sincere support of nuclear power as the only realistic solution to climate change in the electricity (and possibly transport and industrial heat) arena. I’ve laid my cards on the table in the peer-reviewed literature (e.g., see here, here, here, here, here & here) and the standard media, and I’ve even joined the board of a new environmental NGO that supports nuclear.

And there is hope, despite the ever-increasing human population, rising consumerism, dwindling resources, and the ubiquity of ideologically driven and ethically compromised politicians. I am hopeful for several reasons, including rising safety and reliability standards of modern nuclear technology, the continued momentum of building new fission reactors in many countries, and even the beginnings of real conversations about nuclear power (or at least, the first steps toward this) in countries where nuclear energy is currently banned (e.g., Australia). I’m also heartened by the fact that nearly every conservation scientists with whom I speak is generally supportive, or at least non-resistant, to the idea of nuclear power as part of the climate change solution. An open letter by our colleagues attests to this. In fact, every day that passes brings new evidence that we cannot ignore this solution any longer.

Even despite the evidence in support of implementing a strong nuclear component into climate change-mitigation strategies, one of the most frequent arguments for not doing so is that society can achieve all of its energy needs and simultaneously combat climate change by constructing 100% renewable-energy pathways. While it is an easy mantra to repeat because it feels right intrinsically to nearly everyone with an environmental conscience, as a scientist I also had to ask if such a monumental task is even technically feasible. Read the rest of this entry »





Job: Research Associate in Eco-epidemiological modelling

3 03 2017
myxo-rabbit

European rabbit infected with myxomatosis

Earlier this week I advertised two new PhD scholarships in palaeo-ecological modelling. Now we are pleased to advertise a six-month Research Associate position in eco-epidemiological modelling.

The position will be based in the School of Biological Sciences at Flinders University. Flinders University offers a dynamic research environment that explores the continuum of environmental and evolutionary research from the ancient to modern ecology. The School of Biological Sciences is an integrated community researching and teaching biology, and has a long history of science innovation.

Project background

Since 1996, Biosecurity South Australia has been running a capture-mark-recapture study on a European rabbit (Oryctolagus cuniculus) population located at Turretfield (~ 50 km north of Adelaide). Now into the 21st year, this is one of the world’s longest studies of its kind. Approximately every 8 weeks cage traps are reset and the population trapped over five days, with the captured rabbits weighed, sexed, tagged and blood-sampled. The study was established to investigate the epidemiology and efficacy of the two imported rabbit biocontrol agents, rabbit haemorrhagic disease virus (RHDV) and myxomatosis. To date, from 119 formal trapping events and RHDV-outbreak carcass-sampling trips, > 4500 rabbits have been monitored with > 8700 cELISA RHDV antibody tests and 7500 IgG, IgM and IgA RHDV antibody tests on sera (similarly for myxomatosis), and 111 RHDV-specific polymerase chain reaction (PCR) analyses run on tissue samples of the sampled rabbits. This represents an unparalleled dataset on rabbit survival, population fluctuations and disease dynamics. Read the rest of this entry »





One-two carbon punch of defaunation

30 04 2016

1-2 punchI’ve just read a well-planned and lateral-thinking paper in Nature Communications that I think readers of CB.com ought to appreciate. The study is a simulation of a complex ecosystem service that would be nigh impossible to examine experimentally. Being a self-diagnosed fanatic of simulation studies for just such purposes, I took particular delight in the results.

In many ways, the results of the paper by Osuri and colleagues are intuitive, but that should never be a reason to avoid empirical demonstration of a suspected phenomenon because intuition rarely equals fact. The idea itself is straightforward, but takes more than a few logical steps to describe: Read the rest of this entry »





How to find fossils

30 03 2016

Many palaeontologists and archaeologists might be a little put out by the mere suggestion that they can be told by ecologists how to do their job better. That is certainly not our intention.

Like fossil-hunting scientists, ecologists regularly search for things (individuals of species) that are rare and difficult to find, because surveying the big wide world for biodiversity is a challenge that we have faced since the dawn of our discipline. In fact, much of the mathematical development of ecology stems from this probabilistic challenge — for example, species distribution models are an increasingly important component of both observational and predictive ecology.

IMG_1277But the palaeo types generally don’t rely on mathematical models to ‘predict’ where fossils might be hiding just under the surface. Even I’ve done what most do when trying to find a fossil — go to a place where fossils have already been found and start fossicking. I’ve done this now with very experienced sedimentary geologists in the Flinders Rangers looking for 550 million year-old Ediacaran fossils, and most recently searching for Jurassic fossils (mainly ammonites) on the southern coast of England (Devon’s Jurassic Coast). My prized ammonite find is shown in the photo to the left.

If you’ve read anything on this blog before, you’ll probably know that I’m getting increasingly excited about palaeo-ecology, with particular emphasis on Australia’s late-Pleistocene and early Holocene mass-extinction of megafauna. So with a beautiful, brand-new, shiny, and quality-rated megafauna dataset1, we cheekily decided to take fossil hunting to the next level by throwing mathematics at the problem.

Just published2 in PloS One, I’m happy to announce our newest paper entitled Where to dig for fossils: combining climate-envelope, taphonomy and discovery models.

Of course, we couldn’t just treat fossil predictions like ecological ones — there are a few more steps involved because we are dealing with long-dead specimens. Our approach therefore involved three steps: Read the rest of this entry »





Sensitive numbers

22 03 2016
toondoo.com

A sensitive parameter

You couldn’t really do ecology if you didn’t know how to construct even the most basic mathematical model — even a simple regression is a model (the non-random relationship of some variable to another). The good thing about even these simple models is that it is fairly straightforward to interpret the ‘strength’ of the relationship, in other words, how much variation in one thing can be explained by variation in another. Provided the relationship is real (not random), and provided there is at least some indirect causation implied (i.e., it is not just a spurious coincidence), then there are many simple statistics that quantify this strength — in the case of our simple regression, the coefficient of determination (R2) statistic is a usually a good approximation of this.

In the case of more complex multivariate correlation models, then sometimes the coefficient of determination is insufficient, in which case you might need to rely on statistics such as the proportion of deviance explained, or the marginal and/or conditional variance explained.

When you go beyond this correlative model approach and start constructing more mechanistic models that emulate ecological phenomena from the bottom-up, things get a little more complicated when it comes to quantifying the strength of relationships. Perhaps the most well-known category of such mechanistic models is the humble population viability analysis, abbreviated to PVA§.

Let’s take the simple case of a four-parameter population model we could use to project population size over the next 10 years for an endangered species that we’re introducing to a new habitat. We’ll assume that we have the following information: the size of the founding (introduced) population (n), the juvenile survival rate (Sj, proportion juveniles surviving from birth to the first year), the adult survival rate (Sa, the annual rate of surviving adults to year 1 to maximum longevity), and the fertility rate of mature females (m, number of offspring born per female per reproductive cycle). Each one of these parameters has an associated uncertainty (ε) that combines both measurement error and environmental variation.

If we just took the mean value of each of these three demographic rates (survivals and fertility) and project a founding population of = 10 individuals for 1o years into the future, we would have a single, deterministic estimate of the average outcome of introducing 10 individuals. As we already know, however, the variability, or stochasticity, is more important than the average outcome, because uncertainty in the parameter values (ε) will mean that a non-negligible number of model iterations will result in the extinction of the introduced population. This is something that most conservationists will obviously want to minimise.

So each time we run an iteration of the model, and generally for each breeding interval (most often 1 year at a time), we choose (based on some random-sampling regime) a different value for each parameter. This will give us a distribution of outcomes after the 10-year projection. Let’s say we did 1000 iterations like this; taking the number of times that the population went extinct over these iterations would provide us with an estimate of the population’s extinction probability over that interval. Of course, we would probably also vary the size of the founding population (say, between 10 and 100), to see at what point the extinction probability became acceptably low for managers (i.e., as close to zero as possible), but not unacceptably high that it would be too laborious or expensive to introduce that many individuals. Read the rest of this entry »