Journal ranks 2020

23 07 2021

This is the 13th year in a row that I’ve generated journal ranks based on the journal-ranking method we published several years ago.

There are few differences in how I calculated this year’s ranks, as well as some relevant updates:

  1. As always, I’ve added a few new journals (either those who have only recently been scored with the component metrics, or ones I’ve just missed before);
  2. I’ve included the new ‘Journal Citation Indicator’ (JCI) in addition to the Journal Impact Factor and Immediacy Index from Clarivate ISI. JCI “… a field-normalised metric, represents the average category-normalised citation impact for papers published in the prior three-year period.”. In other words, it’s supposed to correct for field-specific citation trends;
  3. While this isn’t my change, the Clarivate metrics are now calculated based on when an article is first published online, rather than just in an issue. You would have thought that this should have been the case for many years, but they’ve only just done it;
  4. I’ve also added the ‘CiteScore’ (CS) in addition to the Source-Normalised Impact Per Paper (SNIP) and SCImago Journal Rank (SJR) from Scopus. CS is “the number of citations, received in that year and previous 3 years, for documents published in the journal during that period (four years), divided by the total number of published documents … in the journal during the same four-year period”;
  5. Finally, you can access the raw data for 2020 (I’ve done the hard work for you) and use my RShiny app to derive your own samples of journal ranks (also see the relevant blog post). You can add new journal as well to the list if my sample isn’t comprehensive enough for you.

Since the Google Scholar metrics were just released today, I present the new 2020 ranks for: (i) 101 ecology, conservation and multidisciplinary journals, and a subset of (ii) 61 ‘ecology’ journals, (iii) 29 ‘conservation’ journals, (iv) 41 ‘sustainability’ journals (with general and energy-focussed journals included), and (v) 20 ‘marine & freshwater’ journals.

One final observation. I’ve noted that several journals are boasting about how their Impact Factors have increased this year, when they fail to mention that this is the norm across most journals. As you’ll see below, relative ranks don’t actually change that much for most journals. In fact, this is a redacted email I received from a journal that I will not identify here:

We’re pleased to let you know that the new Impact Factor for [JOURNAL NAME] marks a remarkable increase, as it now stands at X.XXX, compared to last year’s X.XXX. And what is even more important: [JOURNAL NAME] increased its rank in the relevant disciplines: [DISCIPLINE NAME].

Although the Impact Factor may not be the perfect indicator of success, it remains the most widely recognised one at journal level. Therefore, we’re excited to share this achievement with you, as it wouldn’t have been possible, had it not been for all of your contributions and support as authors, reviewers, editors and readers. A huge ‘THANK YOU’ goes to all of you!

What bullshit.

Anyway, on to the results:

Read the rest of this entry »

Interval between extremely wet years increasing?

16 07 2021

The other day I was playing around with some Bureau of Meteorology data for my little patch of the Adelaide Hills (free data — how can I resist?), when I discovered an interesting trend.

Living on a little farm with a small vineyard, I’m rather keen on understanding our local weather trends. Being a scientist, I’m also rather inclined to analyse data.

My first question was given the strong warming trend here and everywhere else, plus ample evidence of changing rainfall patterns in Australia (e.g., see here, here, here, here, here), was it drying out, getting wetter, or was the seasonal pattern of rainfall in my area changing?

I first looked to see if there was any long-term trend in total annual rainfall over time. Luckily, the station records nearest my farm go all the way back to 1890:

While the red line might suggest a slight decrease since the late 19th Century, it’s no different to an intercept-only model (evidence ratio = 0.84) — no trend.

Here’s the R code to do that analysis (you can download the data here, or provide your own data in the same format):

dat <- read.table("monthlyprecipdata.csv", header=T, sep=",")

precip.yr.sum <- xtabs(dat$Monthly.Precipitation.Total..millimetres. ~ dat$Year)
precip.yr.sum <- precip.yr.sum[-length(precip.yr.sum)]
year.vec <- as.numeric(names(precip.yr.sum))

plot(year.vec, as.numeric(precip.yr.sum), type="l", pch=19, xlab="year", ylab="annual precipitation (mm)")
fit.yr <- lm(precip.yr.sum ~ year.vec)
abline(fit.yr, lty=2, lwd=2, col="red")
abline(h=mean(as.numeric(precip.yr.sum)),lty=2, lwd=3)

# functions
AICc <- function(...) {
  models <- list(...)
  num.mod <- length(models)
  AICcs <- numeric(num.mod)
  ns <- numeric(num.mod)
  ks <- numeric(num.mod)
  AICc.vec <- rep(0,num.mod)
  for (i in 1:num.mod) {
    if (length(models[[i]]$df.residual) == 0) n <- models[[i]]$dims$N else n <- length(models[[i]]$residuals)
    if (length(models[[i]]$df.residual) == 0) k <- sum(models[[i]]$dims$ncol) else k <- (length(models[[i]]$coeff))+1
    AICcs[i] <- (-2*logLik(models[[i]])) + ((2*k*n)/(n-k-1))
    ns[i] <- n
    ks[i] <- k
    AICc.vec[i] <- AICcs[i]

delta.AIC <- function(x) x - min(x) ## where x is a vector of AIC
weight.AIC <- function(x) (exp(-0.5*x))/sum(exp(-0.5*x)) ## Where x is a vector of dAIC <- function(x) ((( as.numeric(x$null.deviance) - as.numeric(x$deviance) )/ as.numeric(x$null.deviance))*100) ## % change in deviance, where x is glm object

linreg.ER <- function(x,y) { # where x and y are vectors of the same length; calls AICc, delta.AIC, weight.AIC functions
  fit.full <- lm(y ~ x); fit.null <- lm(y ~ 1)
  AIC.vec <- c(AICc(fit.full),AICc(fit.null))
  dAIC.vec <- delta.AIC(AIC.vec); wAIC.vec <- weight.AIC(dAIC.vec)
  ER <- wAIC.vec[1]/wAIC.vec[2]
  r.sq.adj <- as.numeric(summary(fit.full)[9])

linreg.ER(year.vec, as.numeric(precip.yr.sum))
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‘Living’ figures

8 07 2021

Have you ever constructed a database and then published the findings, only to realise that after the time elapsed your database is already obsolete?

This is the reality of scientific information today. There are so many of us doing so many things that information accumulates substantially in months, if not weeks. If you’re a geneticist, this probably happens for many datasets on the order of days.

While our general databasing capacity worldwide has improved enormously over the last decade with the transition to fully online and web-capable interactivity, the world of scientific publication still generally lags behind the tech. But there is a better way to communicate dynamic, evolving database results to the public.

Enter the ‘living figure’, which is a simple-enough concept where a published figure remains dynamic as its underlying database is updated.

We have, in fact, just published such a living figure based on our paper earlier this year where we reported the global costs of invasive species.

That paper was published based on version 1 of the InvaCost database, but a mere three months after publication, InvaCost is already at version 4.

Read the rest of this entry »

Losing half of tropical fish species as corals disappear

30 06 2021

When snorkelling in a reef, it’s natural to think of coral colonies as a colourful scenography where fish act in a play. But what would happen to the fish if the stage went suddenly empty, as in Peter Brook’s 1971 Midsummer Night’s Dream? Would the fish still be there acting their roles without a backdrop?

This question is not novel in coral-reef science. Ecologists have often compared reef fish diversity and biomass in selected localities before and after severe events of coral mortality. Even a temporary disappearance of corals might have substantial effects on fish communities, sometimes resulting in a local disappearance of more than half of local fish species.

Considering the multiple, complex ways fish interact with — and depend on — corals, this might appear as an obvious outcome. Still, such complexity of interactions makes it difficult to predict how the loss of corals might affect fish diversity in specific contexts, let alone at the global scale.

Focusing on species-specific fish-coral associations reveals an inconsistent picture with local-scale empirical observations. When looking at the fraction of local fish diversity that strictly depends on corals for food and other more generic habitat requirements (such as shelter and reproduction), the global picture suggests that most fish diversity in reef locality might persist in the absence of corals. 

The mismatch between this result and the empirical evidence of a stronger coral dependence suggests the existence of many hidden ecological paths connecting fish to corals, and that those paths might entrap many fish species for which the association to corals is not apparent.

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Is the IPCC finally catching up with the true severity of climate change?

24 06 2021

I’m not in any way formally involved in either the IPCC or IPBES, although I’ve been involved indirectly in analysing many elements of both the language of the reports and the science underlying their predictions.

Today, The Guardian reported that a leaked copy of an IPCC report scheduled for release soon indicated that, well, the climate-change situation is in fact worse than has been previously reported in IPCC documents.

If you’re a biologist, climatologist, or otherwise-informed person, this won’t come as much of a surprise. Why? Well, the latest report finally recognises that the biosphere is not just some big balloon that slowly inflates or deflates with the whims of long-term climate variation. Instead, climate records over millions of years show that the global climate can and often does shift rapidly between different states.

This is the concept of ‘tipping points’.

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A domesticated planet

15 06 2021

The abundance of wild animals is regressing speedily as the number of domesticated animals and persons keeps escalating. Such demographic contrast signals that we urgently need to modify our model of subsistence and our interaction with Mother Nature.

If we had to choose between a biodiverse landscape and one hosting a monoculture of pine trees with ruminating cattle, many would take the first option. Biodiversity has an aesthetic value to humans, and also gives us free services like pollination, climate regulation, freshwater depuration or soil formation (1, 2). That is why the mounting rates of biodiversity loss have propelled a multi-angled debate about whether the Earth is experiencing the sixth mass extinction (3, 4) and how biodiversity should be managed to secure our access to ecosystem services (5, 6).

Think individuals, not species

A different way of approaching the biodiversity crisis consists of examining trends in the number of wild animals, with not so much emphasis on the variety of species. Thus, the Living Planet Report 2020, published by the World Wildlife Fund, has compiled thousands of scientific studies about > 21,000 populations of wild vertebrates studied over time (> 4,000 species represented) and concluded that, on average, the number of individuals per population has diminished by 70% since the 1970s (7).

Biomass (birds and mammals) in Planet Earth measured in Giga-tonnes of Carbon (Gt C) (8) for people (red), domesticated animals (blue) and wildlife (green). The pie chart compares those three groups in modern times, and the barplot reports values for mammals from prehistory (~100.000 years ago) to now. Overpopulation of humans and domesticated animals currently outnumbers the biomass of wildlife.

On the other hand, Yinon Bar-On et al. (8) quantified that the biomass of humans and our domesticated mammals currently multiplies the biomass of wild mammals by a factor of 10, and there are 3 kg of humans and poultry for every kg of wild birds (see video featuring this study).

Not only that, during the last 100,000 years through which anatomically modern humans have thrived from a handful of bands of African hunter-gatherers to complex societies living in metropolis, the cattle industry has ended up quadrupling the global biomass of mammals (8).

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… some (models) are useful

8 06 2021

As someone who writes a lot of models — many for applied questions in conservation management (e.g., harvest quotas, eradication targets, minimum viable population sizes, etc.), and supervises people writing even more of them, I’ve had many different experiences with their uptake and implementation by management authorities.

Some of those experiences have involved catastrophic failures to influence any management or policy. One particularly painful memory relates to a model we wrote to assist with optimising approaches to eradicate (or at least, reduce the densities of) feral animals in Kakadu National Park. We even wrote the bloody thing in Visual Basic (horrible coding language) so people could run the module in Excel. As far as I’m aware, no one ever used it.

Others have been accepted more readily, such as a shark-harvest model, which (I think, but have no evidence to support) has been used to justify fishing quotas, and one we’ve done recently for the eradication of feral pigs on Kangaroo Island (as yet unpublished) has led directly to increased funding to the agency responsible for the programme.

According to Altmetrics (and the online tool I developed to get paper-level Altmetric information quickly), only 3 of the 16 of what I’d call my most ‘applied modelling’ papers have been cited in policy documents:

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Cartoon guide to biodiversity loss LXVI

29 05 2021

Here is the third set of biodiversity cartoons for 2021. See full stock of previous ‘Cartoon guide to biodiversity loss’ compendia here.

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Killing (feral) cats quickly (and efficiently)

20 05 2021

I’m pleased to announce the publication of a paper led by Kathryn Venning (KV) that was derived from her Honours work in the lab. Although she’s well into her PhD on an entirely different topic, I’m overjoyed that she persevered and saw this work to publication.

Here, killa, killa, killa, killa …

As you probably already know, feral cats are a huge problem in Australia. The are probably the primary reason Australia leads the world in mammal extinctions in particular, and largely the reason so many re-introduction attempts of threatened marsupials fail miserably only after a few years.

Feral cats occupy every habitat in the country, from the high tropics to the deserts, and from the mountains to the sea. They adapt to the cold just as easily as they adapt to the extreme heat, and they can eat just about anything that moves, from invertebrates to the carcases of much larger animals that they scavenge.

Cats are Australia’s bane, but you can’t help but be at least a little impressed with their resilience.

Still, we have to try our best to get rid of them where we can, or at least reduce their densities to the point where their ecological damage is limited.

Typically, the only efficient and cost-effective way to do that is via lethal control, but by using various means. These can include direct shooting, trapping, aerial poison-baiting, and a new ‘smart’ method of targeted poison delivery via a prototype device known as a Felixer™️. The latter are particularly useful for passive control in areas where ground-shooting access is difficult.

A live Felixer™️ deployed on Kangaroo Island (photo: CJA Bradshaw 2020)

A few years back the federal government committed what might seem like a sizeable amount of money to ‘eradicate’ cats from Australia. Yeah, good luck with that, although the money has been allocated to several places where cat reduction and perhaps even eradication is feasible. Namely, on islands.

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Everything you always wanted to know about conservation (but were afraid to ask)

14 05 2021

While some of us still might imagine the conservationist as a fancy explorer discovering new species in a remote corner of the world, or collecting samples while drowning in mud, a growing portion of conservation science nowadays consists of asking people about their ideas and behaviours.

Needless to say, this approach produces a fair share of awkward, if not dangerous, situations. After all, who likes the idea of completing a questionnaire from the fisheries office, asking about compliance with harvest limitations or licence fees? Or, even worse, who fancies being asked about the possession of illegally traded wildlife? 

Many conservationists would really like to have this valuable information, but at the same time it is clear that these questions put people at great discomfort. This leads to biased estimates of important behaviours affecting conservation. This is where specialised questioning techniques can help.

Specialised questioning techniques aim to prevent researchers, or anyone else, to trace back individual answers. Many do so by adding noise with a known distribution to individual answers. Then, when all answers are pooled, this noise is ruled out with statistical approaches. Noise can come from a randomising device (e.g. a die), like in the randomised response technique:

Individual answers can also be masked by asking respondents not to indicate if they engaged in a certain behaviour, but by asking them, out of a list of sensitive and non-sensitive behaviours, to indicate the number in which they engaged. This is the case of the unmatched count technique (a.k.a list experiments):

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Mapping the ‘super-highways’ the First Australians used to cross the ancient land

4 05 2021

Author provided/The Conversation, Author provided

There are many hypotheses about where the Indigenous ancestors first settled in Australia tens of thousands of years ago, but evidence is scarce.

Few archaeological sites date to these early times. Sea levels were much lower and Australia was connected to New Guinea and Tasmania in a land known as Sahul that was 30% bigger than Australia is today.

Our latest research advances our knowledge about the most likely routes those early Australians travelled as they peopled this giant continent.

Read more: The First Australians grew to a population of millions, much more than previous estimates

We are beginning to get a picture not only of where those first people landed in Sahul, but how they moved throughout the continent.

Navigating the landscape

Modelling human movement requires understanding how people navigate new terrain. Computers facilitate building models, but they are still far from easy. We reasoned we needed four pieces of information: (1) topography; (2) the visibility of tall landscape features; (3) the presence of freshwater; and (4) demographics of the travellers.

We think people navigated in new territories — much as people do today — by focusing on prominent land features protruding above the relative flatness of the Australian continent. Read the rest of this entry »

Population of First Australians grew to millions, much more than previous estimates

30 04 2021

Shutterstock/Jason Benz Bennee

We know it is more than 60,000 years since the first people entered the continent of Sahul — the giant landmass that connected New Guinea, Australia and Tasmania when sea levels were lower than today.

But where the earliest people moved across the landscape, how fast they moved, and how many were involved, have been shrouded in mystery.

Our latest research, published today shows the establishment of populations in every part of this giant continent could have occurred in as little as 5,000 years. And the entire population of Sahul could have been as high as 6.4 million people.

This translates to more than 3 million people in the area that is now modern-day Australia, far more than any previous estimate.

Read more: We mapped the ‘super-highways’ the First Australians used to cross the ancient land

The first people could have entered through what is now western New Guinea or from the now-submerged Sahul Shelf off the modern-day Kimberley (or both).

But whichever the route, entire communities of people arrived, adapted to and established deep cultural connections with Country over 11 million square kilometres of land, from northwestern Sahul to Tasmania.

A map showing a much larger landmass as Australia is joined to both Tasmania and New Guinea due to lower sea levels

Map of what Australia looked like for most of the human history of the continent when sea levels were lower than today. Author provided

This equals a rate of population establishment of about 1km per year (based on a maximum straight-line distance of about 5,000km from the introduction point to the farthest point).

That’s doubly impressive when you consider the harshness of the Australian landscape in which people both survived and thrived.

Previous estimates of Indigenous population

Various attempts have been made to calculate the number of people living in Australia before European invasion. Estimates vary from 300,000 to more than 1,200,000 people. Read the rest of this entry »

No, you can’t argue the Medieval warm period is evidence that today’s climate change isn’t all that bad

23 04 2021
As this reconstructed village shows, Vikings made it as far as Newfoundland during the Medieval warm period. Wikimedia/Dylan Kereluk, CC BY-SA

Frédérik Saltré, Flinders University and Corey J. A. Bradshaw, Flinders University

What was the Medieval warm period? What caused it, and did carbon dioxide play a role?

We are living in a world that is getting warmer year by year, threatening our environment and way of life.

But what if these climate conditions were not exceptional? What if it had already happened in the past when human influences were not part of the picture?

The often mentioned Medieval warm period seems to fit the bill. This evokes the idea that if natural global warming and all its effects occurred in the past without humans causing them, then perhaps we are not responsible for this one. And it does not really matter because if we survived one in the past, then we can surely survive one now.

But it’s just not that simple.

Read more: 2,000 years of records show it’s getting hotter, faster

The Medieval climate anomaly

This Medieval period of warming, also known as the Medieval climate anomaly, was associated with an unusual temperature rise roughly between 750 and 1350 AD (the European Middle Ages). The available evidence suggests that at times, some regions experienced temperatures exceeding those recorded during the period between 1960 and 1990. Read the rest of this entry »

Attack of the alien invaders: pest plants and animals leave a frightening $1.7 trillion bill

19 04 2021


They’re one of the most damaging environmental forces on Earth. They’ve colonised pretty much every place humans have set foot on the planet. Yet you might not even know they exist.

We’re talking about alien species. Not little green extraterrestrials, but invasive plants and animals not native to an ecosystem and which become pests. They might be plants from South America, starfish from Africa, insects from Europe or birds from Asia.

These species can threaten the health of plants and animals, including humans. And they cause huge economic harm. Our research, recently published in the journal Nature, puts a figure on that damage. We found that globally, invasive species cost US$1.3 trillion (A$1.7 trillion) in money lost or spent between 1970 and 2017.

The cost is increasing exponentially over time. And troublingly, most of the cost relates to the damage and losses invasive species cause. Meanwhile, far cheaper control and prevention measures are often ignored.

Yellow crazy ants attacking a gecko
Yellow crazy ants, such as these attacking a gecko, are among thousands of invasive species causing ecological and economic havoc. Dinakarr, CC0, Wikimedia Commons

An expansive toll

Invasive species have been invading foreign territories for centuries. They hail from habitats as diverse as tropical forests, dry savannas, temperate lakes and cold oceans.

They arrived because we brought them — as pets, ornamental plants or as stowaways on our holidays or via commercial trade.

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The biggest and slowest don’t always bite it first

13 04 2021

For many years I’ve been interested in modelling the extinction dynamics of megafauna. Apart from co-authoring a few demographically simplified (or largely demographically free) models about how megafauna species could have gone extinct, I have never really tried to capture the full nuances of long-extinct species within a fully structured demographic framework.

That is, until now.

But how do you get the life-history data of an extinct animal that was never directly measured. Surely, things like survival, reproductive output, longevity and even environmental carrying capacity are impossible to discern, and aren’t these necessary for a stage-structured demographic model?

Thylacine mum & joey. Nellie Pease & CABAH

The answer to the first part of that question “it’s possible”, and to the second, it’s “yes”. The most important bit of information we palaeo modellers need to construct something that’s ecologically plausible for an extinct species is an estimate of body mass. Thankfully, palaeontologists are very good at estimating the mass of the things they dig up (with the associated caveats, of course). From such estimates, we can reconstruct everything from equilibrium densities, maximum rate of population growth, age at first breeding, and longevity.

But it’s more complicated than that, of course. In Australia anyway, we’re largely dealing with marsupials (and some monotremes), and they have a rather different life-history mode than most placentals. We therefore have to ‘correct’ the life-history estimates derived from living placental species. Thankfully, evolutionary biologists and ecologists have ways to do that too.

The Pleistocene kangaroo Procoptodon goliah, the largest and most heavily built of the  short-faced kangaroos, was the largest and most heavily built kangaroo known. It had an  unusually short, flat face and forwardly directed 
eyes, with a single large toe on each foot  (reduced from the more normal count of four). Each forelimb had two long, clawed fingers  that would have been used to bring leafy branches within reach.

So with a battery of ecological, demographic, and evolutionary tools, we can now create reasonable stochastic-demographic models for long-gone species, like wombat-like creatures as big as cars, birds more than two metres tall, and lizards more than seven metres long that once roamed the Australian continent. 

Ancient clues, in the shape of fossils and archaeological evidence of varying quality scattered across Australia, have formed the basis of several hypotheses about the fate of megafauna that vanished during a peak about 42,000 years ago from the ancient continent of Sahul, comprising mainland Australia, Tasmania, New Guinea and neighbouring islands.

There is a growing consensus that multiple factors were at play, including climate change, the impact of people on the environment, and access to freshwater sources.

Just published in the open-access journal eLife, our latest CABAH paper applies these approaches to assess how susceptible different species were to extinction – and what it means for the survival of species today. 

Using various characteristics such as body size, weight, lifespan, survival rate, and fertility, we (Chris Johnson, John Llewelyn, Vera Weisbecker, Giovanni Strona, Frédérik Saltré & me) created population simulation models to predict the likelihood of these species surviving under different types of environmental disturbance.

Simulations included everything from increasing droughts to increasing hunting pressure to see which species of 13 extinct megafauna (genera: Diprotodon, Palorchestes, Zygomaturus, Phascolonus, Procoptodon, Sthenurus, Protemnodon, Simosthenurus, Metasthenurus, Genyornis, Thylacoleo, Thylacinus, Megalibgwilia), as well as 8 comparative species still alive today (Vombatus, Osphranter, Notamacropus, Dromaius, Alectura, Sarcophilus, Dasyurus, Tachyglossus), had the highest chances of surviving.

We compared the results to what we know about the timing of extinction for different megafauna species derived from dated fossil records. We expected to confirm that the most extinction-prone species were the first species to go extinct – but that wasn’t necessarily the case.

While we did find that slower-growing species with lower fertility, like the rhino-sized wombat relative Diprotodon, were generally more susceptible to extinction than more-fecund species like the marsupial ‘tiger’ thylacine, the relative susceptibility rank across species did not match the timing of their extinctions recorded in the fossil record.

Indeed, we found no clear relationship between a species’ inherent vulnerability to extinction — such as being slower and heavier and/or slower to reproduce — and the timing of its extinction in the fossil record.

In fact, we found that most of the living species used for comparison — such as short-beaked echidnas, emus, brush turkeys, and common wombats — were more susceptible on average than their now-extinct counterparts.

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One trillion dollars!

1 04 2021

Or thereabouts.

Let’s step back to 2015. In a former life when I was at another institution, I had the immense fortune and pleasure to spend six months on sabbatical in a little village just south of Paris working with my friend and colleague, Franck Courchamp, at Université Paris-Sud (now Université Paris-Saclay).

Sure, I felt a bit jammy living there with my daughter in a beautiful house just down the street from two mouth-watering pâtisseries and three different open marchés. We ate well. We picked mushrooms on the weekends or visited local châteaux. We went into the city and visited overwhelmingly beautiful museums at our leisure. We drank good champagne (well, I did, not my eight-year old). We had communal raclettes.

But of course, I was primarily there to do research with Franck and his lab, despite the obvious perks.

While I busied myself with several tasks while there, one of our main outputs was to put together the world’s first global database of the costs of invasive insects, which we subsequently published in 2016.

But that was only the beginning. With funding that started off the process with insects, Franck persevered and hired postdocs and took on more students to build the most comprehensive database of all invasive species ever compiled — InvaCost.

I cannot stress enough how massive an undertaking this was. It’s not simply a big list of all the cost estimates in existence, it’s also a detailed assessment of cost reliability, standardisation, and contextualisation. I’m not sure I would have had the courage to do this myself.

While the database itself has already been published, today we are pleased to announce the publication in Nature of the main results — High and rising economic costs of biological invasions worldwide — led by Christophe Diagne (one of the nicest people I’ve ever met), and co-authored by Boris Leroy, Anne-Charlotte Vaissière, Rodolphe Gozlan, David Roiz, Ivan Jarić, Jean-Michel Salles, me, and Franck Courchamp (of course).

Herein we described how the economic costs of invasive alien species accumulated since 1970 are tremendous, and that they have been steadily increasing over time.

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How to avoid reduce the probability of being killed by a shark

31 03 2021

Easy. Don’t go swimming/surfing/snorkelling/diving in the ocean.

“Oh, shit”

Sure, that’s true, but if you’re like many Australians, the sea is not just a beautiful thing to look at from the window, it’s a way of life. Trying telling a surfer not to surf, or a diver not to dive. Good luck with that.

A few years ago, I joined a team of super-cool sharkologists led by Charlie ‘Aussie-by-way-of-Belgium shark-scientist extraordinaire Huveneers, and including Maddie ‘Chomp’ Thiele and Lauren ‘Acid’ Meyer — to publish the results of some of the first experimentally tested shark deterrents.

It turns out that many of the deterrents we tested failed to show any reduction in the probability of a shark biting, with only one type of electronic deterrent showing any effect at all (~ 60% reduction).

Great. But what might that mean in terms of how many people could be saved by wearing such electronic deterrents? While the probability of being bitten by a shark is low globally, even in Australia (despite public perceptions), we wondered if the number of lives saved and injuries avoided was substantial.

In a new paper just published today in Royal Society Open Science, we attempted to answer that question.

To predict how many people could avoid shark bites if they were using properly donned electronic deterrents that demonstrate some capacity to dissuade sharks from biting, we examined the century-scale time series of shark bites on humans in Australia. This database — the ‘Australian Shark Attack File‘ — is one of the most comprehensive databases of its kind.

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A perfect storm of global ineptitude

18 03 2021

Given the ‘success’ (i.e., a lot of people seem to be reading it) of our recent Ghastly Future paper, I thought it would be interesting to go back and have a look at what we wrote in our 2015 book Killing the Koala on the subject. I think you’ll find that if anything we were probably overly optimistic.

An updated digest of that material follows.

When your accountant tells you to reduce expenditure, you do it or risk bankruptcy; when your electrician tells you the wiring in your house is dodgy, you replace it or risk your family dying in an avoidable fire; when your doctor tells you your cholesterol is too high, you cut back fat intake (and/or take cholesterol-reducing drugs) or risk a heart attack.

Yet few with any real political or financial power heed the warnings of environmental scientists. It is not just a few of us either — globally, ecologists, conservation biologists and environmental scientists are united in telling the world (for decades now) that growth in population and consumption cannot go on forever. They have been united in telling us if we do not clean up our planet, our life-support systems could ultimately fail.

There are now nearly eight billion people on Earth, and median projections suggest that the population will grow to ten billion or more by the end of the century. Some analyses indicate that with present technologies, Earth could only sustainably support indefinitely some 5 billion people under best-case scenarios, but assuming similar proportions of poverty and suffering as we have today. Others imply that 5 billion could be many too many.

As a result, humanity is entering that near-perfect storm of problems driven by overpopulation, overconsumption, gross inequalities, and the use of needlessly environmentally damaging technologies. The problems include the intertwined dilemmas of loss of the biodiversity that runs human life-support systems, climate disruption, energy shortages, global toxification, alteration of critical biogeochemical cycles, shortages of water, soil, mineral resources and farmland, and increasing probability of vast epidemics (as COVID-19 poignantly exemplifies).

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Cartoon guide to biodiversity loss LXV

10 03 2021

Here is the second set of biodiversity cartoons for 2021. See full stock of previous ‘Cartoon guide to biodiversity loss’ compendia here.

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Recreational hunting, conservation and livelihoods: no clear evidence trail

2 03 2021
Enrico Di Minin, University of Helsinki; Anna Haukka, University of Helsinki; Anna Hausmann, University of Helsinki; Christoph Fink, University of Helsinki; Corey J. A. Bradshaw, Flinders University; Gonzalo Cortés-Capano, University of Helsinki; Hayley Clements, Stellenbosch University, and Ricardo A. Correia, University of Helsinki

In some African countries, lion trophy hunting is legal. Riaan van den Berg

In sub-Saharan Africa, almost 1,400,000 km² of land spread across many countries — from Kenya to South Africa — is dedicated to “trophy” (recreational) hunting. This type of hunting can occur on communal, private, and state lands.

The hunters – mainly foreign “tourists” from North America and Europe – target a wide variety of species, including lions, leopards, antelopes, buffalo, elephants, zebras, hippopotamus and giraffes.

Read more: Big game: banning trophy hunting could do more harm than good

Debates centred on the role of recreational hunting in supporting nature conservation and local people’s livelihoods are among the most polarising in conservation today.

On one hand, people argue that recreational hunting generates funding that can support livelihoods and nature conservation. It’s estimated to generate US$200 million annually in sub-Saharan Africa, although others dispute the magnitude of this contribution.

On the other hand, hunting is heavily criticised on ethical and moral grounds and as a potential threat to some species.

Evidence for taking a particular side in the debate is still unfortunately thin. In our recently published research, we reviewed the large body of scientific literature on recreational hunting from around the world, which meant we read and analysed more than 1000 peer-reviewed papers.

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