Ecological Modelling, the Coronavirus, and Why They’re Not A Perfect Match

Image Credit: Pharexia, Ratherous, AKS471883, Source Data from  Johns Hopkins University CSSEThe Centers for Disease Control and PreventionNew York TimesCNBC.

As it quickly became clear in late February and early March that COVID-19 was not going away anytime soon, attention turned to trying to figure out when and where the virus would spread. Epidemiologists and virologists have had their work cut out for them, trying to simultaneously reassure and warn people the world over about the dangers, the nature and the potential timeline of the virus.

So it came as somewhat of a surprise to see ecologists try and tip their hat into the ring. Early on in the pandemic, teams of ecologists sprang up, trying to use Species Distribution Models to predict the spread of the virus. And whilst this might sound helpful, many of these studies lacked collaboration with epidemiologists, and their predictions very quickly fell flat. Some studies suggested that areas like Brazil and Central Africa would be largely spared by the virus, which quickly turned out not to be the case. Flaws in the studies were spotted quite quickly by concerned members of both the ecological and epidemiological communities alike, and a few teams got started on responses.

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Aliens & Invaders & Exotics, Oh My: The Language of Invasive Biology

The Burmese python, which has spread throughout the Everglades in Florida as a result of accidental or intentional releases by pet owners (Image Credit: US NInvaders, Aliens, and tational Park ServicePublic Domain Mark 1.0, Image Cropped)

Language is important. It’s a lesson many biological scientists would have learned a long time ago if we hadn’t kept social sciences at such a wary arm’s length. Ecologists have a tendency to label and relabel ecological concepts (anyone up for a debate about the word ‘niche’?), species and even global phenomena (think global warming vs. climate change) based on anything from shifts in public perception to new findings that challenge our earlier labels.

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Measuring the Popularity of North American Birds

The largest owl in North America, the Snowy Owl. New research shows that this individuals size may help with his popularity among us humans, but his lack of colour might not (Image Credit: USFWS Mountain-Prairie, CC BY 2.0, Image Cropped)

Characterizing the cultural niches of North American birds (2019) Schuetz & Johnston, PNAS,

The Crux

For all our attempts to maintain objectivity in science, often the reality is that the more people value a bird species, the more likely our conservation efforts are to be successful through public support. As such, figuring out which birds are popular, and where, could give us some crucial information on where we’ll need to fight hardest to help species persist, and where our efforts at science communication could use some work.

This week we look at a novel paper that tries to assess which types of North American birds are popular with the public, and whether that popularity is confined only to their home states, or whether it is shown in surrounding areas as well.

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The Public and Private Faces of Birds with Professor Dan Baldassarre

More than perhaps any other taxa, birds have managed to associate themselves with the beauty of nature. An ecosystem devoid of bird calls just feels like it’s missing something, and whilst tigers, koalas and elephants might be the face of many a conservation movement, you can’t lure them to your backyard or local park with a simple feeder (at least I hope not). The bird-watching community worldwide is massive, and ranges from casual backyard birders to those who are willing to travel far and wide to see a new species.

For bird scientists, there are pros and cons to the public’s love affairs with birds. The bird community is a huge source of information and a great place to raise awareness of conservation issue. Yet at the same time, our idealisation of birds has led to a lot of misconceptions, both about their population health and their private lives.

Professor Dan Baldassare came into bird ecology through a fascination with animal behaviour. The author of the fantastic paper “The Deal With Birds” (which we’ll get into in a subsequent article, Dan has spent his academic career studying the lives of a range of birds, from the striking Northern Cardinal to the incredible vampire ground finch.

I spoke to Dan recently about our relationships with birds, some of the positives that have come from it, and how our perception of them may have blinded us to some of the realities of their lives.

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On Fish Dispersal and the Perpetual Evil of the Duck

Image Credit: Norbert Nagel, CC BY-SA 3.0, Image Credit

Woe betide my fishy ancestors, for I am come here today to vent my grievances at a paper so dastardly it has cast a tepid patina of anxiety on a LOT of the structured squabbling my colleagues and I call ‘research’.

Actually, I shouldn’t vent too harshly on the sarcopterygiites, those ancient lobe-finned ancestors of ours and their close cousins the regular fish. Birds, as always, are the main culprit here. An abhorrent series of mutations that messed up a perfectly good reptile.

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Pride in Science

Image credit: Joint Base Langley-Eustis,Va, CC0 1.0

Scientists face many challenges during their professional lives, but one prevalent problem that doesn’t get the attention that it deserves is that of the LGBTQIA+ (hereafter “queer”) community and the lack of inclusiveness in science. In honor of Pride Month, I wanted to take the time to highlight some of the challenges facing queer scientists and what we can do as a society to better ourselves.

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Hey You… Take a Sad Estimator and Make it Better: The Rao Blackwell Theorem

Image Credit: Bureau of Land Management, CC BY 2.0, Image Cropped

A common goal of ecologists is to understand the population abundance of a particular species. We might be looking for the California condor as part of assessing how well the recovery project is going. This requires some field work, going out to a variety of sites and counting animals that we see. How do we choose which sites to go to?  Even in the era of camera traps, we still need to know where to put our extra set of eyes. It would be a shame to have a particular camera not get any action due to an unlucky placement. We don’t have infinite time and money after all!

If a species is fairly prevalent, a random sample of sites might let us see plenty of animals. However, we know species distributions are rarely even across a given region. More likely the species is a bit more rare in certain areas (especially for our critically endangered condor) and/or individuals tend to cluster together. A random sample could lead us to a bunch of unfruitful site visits, despite the fact that the species is quite common in other areas close to those sites.

Adaptive Sampling

But what if we had a little information about the uneven distribution of condors? Adaptive sampling methods allow us to incorporate information about the structure that we’ve observed so far to help us decide where to sample next.

We head out, starting with a small random sample of sites to visit. For every site that we see at least one condor, we also sample all of the site’s neighbors. We keep doing this until we fail to see a condor at any of the previous sites’ neighbors. At that point we’ve reached the end of the cluster. We refer to sites that don’t have any condors but who are in the neighborhood of a site that does as an “edge unit.”

Now we have more information about sites where condors are actually present, but it comes at a cost. The sample mean abundance or even the mean of cluster means can be biased under this type of adaptive sampling design (since it’s no longer completely random). What do we do with this data now?

Luckily there are other estimators of abundance which account for this bias out there. (Want the details? Check out this review.) A simple estimator takes advantage of the fact that our sampling started with a small random sample. We could consider the sample mean of this starting sample as a simple estimator of condor abundance. But we went through all this trouble to collect additional data using a new sampling method. Can we do better than this simple approach?

The Rao-Blackwell Theorem

Now it’s time to switch gears and learn about some statistics theory. I promise it’ll be (relatively) painless. There is an important theorem that tells us how to improve estimators of a particular parameter of interest. In our case, the theorem will help us find a better way to estimate abundance than taking the sample mean of our starting sample. Sign us up!

The Rao-Blackwell theorem tells us that if we have an estimator, then we can obtain a new estimator that is never worse than the original. How do we do that? We take the conditional expectation of the original estimator given a sufficient statistic T. This becomes our new, Rao-Blackwellized, estimator.

That sounds great, but what is a sufficient statistic? Informally, a function of the data T is sufficient if we can’t learn anything more about the parameter of interest from the distribution of the data if we already know what T is. For example, if we are trying to estimate the population mean, we could do so using only the sample mean as our T. We wouldn’t need any of the original sample data to make a decision about our estimate, hence the sample mean is sufficient.

Calyampudi Radhakrishna Rao and David Blackwell, whom the theorem is named after (Image Credits: Prateek Karandikar, George, M. Bergman, CC BY-SA 4.0)

What do we mean by an estimator being better? The new Rao-Blackwellized estimator will have a mean-squared error that is less than or equal to the original. In fact, more general versions of the theorem even let us pick our favorite loss function (as long as it only has global optima, which many commonly used ones do), and this is still true. Score!

In our adaptive sampling example, the sufficient statistic is the set of unique observations, labeled with their site ID. In our data collection process we might revisit particular sites if they are neighbors of multiple condor sightings. We don’t need information about the double counting to help us estimate average abundance, hence the unique observations are sufficient.

Investigation of the benefits of adaptive sampling over random sampling show that the efficiency gains (less work for more information) depend on whether the within-network variance is large enough. Since we often expect large variability in the abundance of a species even within clusters of sites, this is good news for ecologists.

Why is this theorem so important? It basically means that if we design an estimator, even if it’s a wild guess, we always have a concrete way to improve it. This is especially helpful if finding even a starting point for an estimator is hard. Think about how complicated our new design is; we need all the help we can get.

Let’s close with some info on the people behind this theorem. Both of the theorem’s namesakes are powerhouses in the field of statistics. Calyampudi Radhakrishna Rao is an Indian-American mathematician and statistician who has won a variety of awards including the prestigious National Medal of Science (he also has a bound named after him). Read more about him here. David Blackwell was an American mathematician and statistician with his own set of accolades including being a member of the National Academy of Sciences (he was the first African American to be included). Learn more about him from the transcript of his oral history.

Have a quantitative term or concept that mystifies you? Want it explained simply? Suggest a topic for next month →  @sastoudt

The Varying Roles of Indigenous, Government, and Private Protected Areas in Conservation

The Gawler Ranges, an area of Indigenous protected land in South Australia (Image Credit: Korkut Tas, CC BY-SA 3.0, Image Cropped)

Differences among protected area governance types matter for conserving vegetation communities at-risk of loss and fragmentation (2020) Archibald et al., Biological Conservation, 247,

The Crux

The designation of Protected Areas (PAs) has been a key tool in the fight to retain biodiversity and restore ecosystems globally. Designating a region as protected goes a long way to ensuring the survival of a wide rage of species, both locally and on much larger scales. In recent decades, private PAs have been growing in number, and on top of that, 7.8 million squared kilometres worldwide are now registered as Indigenous PAs. As a result, conservation goals are often formed with all three types of protected area in mind.

There has been ample research showing that all three types of PA have been effective in conserving wildlife and habitat types. But all three have different characteristics, both in governance and allocation. Today’s authors wanted to find out whether they protected different types of habitat, and what that could mean for conservation policy going forward.

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Esther Ngumbi: Food Security in the Face of Climate Change

One of the few positives to come out of a recent spate of catastrophic weather events has been the fact that climate change is now nigh on undeniable, and more people than ever are working to prevent its future effects. Yet there are parts of the world in which climate change is more than the progenitor of random disasters, where it has become an everyday reality.

One such area is sub-Saharan Africa. Despite being one of the poorest regions of the world, it’s also a region that has enormous potential for agricultural transformation, helping to solve not only local food crises, but global ones as well. A prominent example is Kenya, where the agricultural sector contributes to over half of the Gross Domestic Product, and provides food and employment for more than 80% of the population. Working for Kenya and other countries in the region is the chance to avoid mistakes made by other regions in the past, as they benefit both from hindsight and improved technology. Yet working against them is that encroaching threat of climate change.

It’s a topic that Assistant Professor Esther Ngumbi, of the University of Illinois has been vocal about. Esther grew up on a farm in rural Kenya, and has witnessed the effects of increased drought and weather variability over the last decade. Esther’s work on food security in Africa has seen her work published in everything from the Journal of Chemical Ecology to Times Magazine.

At 2019’s BES Annual meeting, I got the chance to speak to Esther about everything from African governments to the shifting of climate baselines.

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The Bird Watching Community: Citizen Science at its Finest

Image Credit: Warrieboy, CC BY-SA 4.0, Image Cropped

It’s 5 o’clock in the morning. Whilst the sun has yet to rise and everyone is fast asleep, dedication and passion have awakened you. With a comfortable set of hiking boots, a thermos filled with coffee or tea and a pair of binoculars around your neck you venture into the local forest or mountain area. Hours you spent there searching, looking and listening. When you finally see those recognizable shades of pale brown and chestnut dashing by, or hear that distinctive, vibrant melody interspersed with prolonged pew-pew’s and swift chook-chook’s, you realize that it was well worth waking up so early.

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