Category Archives: Nature

Megafauna Extinction Linked To Human Ancestors

One of the glaring facts of human prehistory is the correlation of the rise of humans and the decline of megafauna—big game.  This pattern continues today, with simultaneously accelerating extinctions of large animals and booming human populations.

Many of us think this pattern is no coincidence.  We know that people will hunt anything and everything to extinction.  All those nasty little apes with their pointy sticks probably did in the giant sloths and other big beats.

Cautious souls reserve judgement, because it is certainly possible that some third factor, such as changing climate, led to both more humans and fewer game animals.  Just because we are killing everything in sight today doesn’t mean that humans wiped out ancient all the ancient fauna.

Given the sparse and uncertain data about exactly when and where humans lived, and when and where species went extinct, there is only circumstantial evidence one way or the other. Correlation is not causation.

So, what role did we humans and our cousins play in the large die off at the end of the Pleistocene?

This spring, a group of researchers published a study of mammalian extinctions and human expansion from the last 125,000 years [2].  The study worked with a dataset that includes mammalian body size distributions and biodiversity over time.

“We investigated the influence of these emerging and increasingly sophisticated hominin predators on continental and global mammalian biodiversity over the late Quaternary” ([2], p.310)

Of particular interest are five broad periods of time corresponding to the expansion of hominins (humans and cousins).

The analysis showed a clear relationship between size of the animals and likelihood of extinction, especially in the earlier periods.  This means that larger animals were consistently wiped out.  Notably, a similar analysis for periods before the Pleistocene (before homonins) do not show this pattern.  (The pattern is less visible in recent times, likely because everything is being wiped out at the same time.)

“As Neandertals, Denisovans, and humans spread across the globe over the late Quaternary, a highly size-biased extinc- tion followed, a pattern distinct in the Cenozoic mammal record. The subsequent downgrading of body size was severe and differentially targeted herbivores.”

This pattern is consistent with human hunting behavior, and is seen at the precise periods when humans were expanding.

One interesting conclusion from this data is that this pattern began very early, and, indeed, before Homo sapiens evolved from earlier Hominids.  This implies that our ancestors have been big game hunters from the beginning, and have been significantly impacting big game from forever.  (Nasty little apes with pointy sticks…)

This pattern has abated in recent ages because humans have come to dominate the Earth, and domesticated animals have replaced wild animals.  The study projects into the future, assuming that threatened species die out. In the future projections, the extinctions extend into smaller animals, indeed, nearly all wild mammals.

I was inspired to make my own plots from some of their data (I drew from Table S1, Supplemental materials).  These diagrams make plain the extremely rapid decline in animals with large body mass, and the key temporal pattern:  extinctions began very early in Africa and Eurasia, spread out to Australia and then the Americas.  This is, of course, the path of human occupation.

I drew arrows suggesting when humans arrived and expanded.  Note that these marks are impressionistic, dates and scales of human occupation are not well established.

(In these diagrams the last point is the projected future extinctions in then next 200 years, which is a precipitous drop.)

From [2] Supplemental Materials, Table S1. Horizontal axis is years (1000s), vertical axis is median body mass for surviving species. Lower median body mass means fewer large animals. Arrows suggest when major human infestations may have first occurred.

  1. Christopher Joyce, New Study Says Ancient Humans Hunted Big Mammals To Extinction, in All Things Considered. 2018, National Public Radio: Washington, DC.
  2. Felisa A. Smith, Rosemary E. Elliott Smith, S. Kathleen Lyons, and Jonathan L. Payne, Body size downgrading of mammals over the late Quaternary. Science, 360 (6386):310-313, 2018.



More On Pollinator Decline

It has been pretty clear for quite a while that neonicotinoids are probably bad for bees and other pollinators. Given the importance of pollinators to food production, this risk cannot be dismissed. But the exact risk is difficult to assess, and the benefits of the chemicals assure that regulations have become a political issue.

In recent years, European regulators have banned the products, which North America has not. A recent review by the EU has confirmed that the ban will be extended in Europe, despite objections from the manufacturers and farm lobbies [3].  At least part of the justification is the findings of hundreds of studies, which show a variety of levels of risk.

The objections note that Europe is out of line with the US and Canada, and the fact that there are a lot of things that are bad for bees. I’m not especially moved by these arguments, but the second point is certainly true.

A case in point is that honey bees are also suffering from epidemics of viruses, as well as effects of chemical agents.  A recent study expands the picture to shows that three viruses that plague honey bees are also found in hoverflies [1]. These insects visit the same flowers as domestic and wild bees.

The evidence from this study is not conclusive, but it certainly raises the possibility that hoverflies and other insects may transmit these viruses from bee to bee; or they may have other roles in the transmission of the diseases.

With so many nasty things happening to our pollinators, all at the same time, it’s difficult to be optimistic about their fate.

Or our own.

  1. Emily J. Bailes, Kaitlin R. Deutsch, Judit Bagi, Lucila Rondissone, Mark J. F. Brown, and Owen T. Lewis, First detection of bee viruses in hoverfly (syrphid) pollinators. Biology Letters, 14 (2) 2018.
  2. Helen Briggs, New clues to decline of bees and other pollinators, in BBC News – Science & Environment. 2018.
  3. Helen Briggs, Pesticides put bees at risk, European watchdog confirms, in BBC News – Science & Environment. 2018.

Study Investigates Honey Bee Networks

One of the cool things about bees is that they are highly social animals.  Over the last century or so, we have learned that bees share food, communicate information, and work together in ways that have stretched concepts of “animal intelligence” and supposedly unique human attributes.


This month a research group at University of Illinois at Urbana Champaign (which is becoming a hive of bee research) report a new study of bee socializing [1].  The goal is to measure the interactions in a bee hive as a temporal network –not just who talks to who, but when.

To observe these interactions, they tagged all the individual bees with tiny (2.1mm2 ) barcodes, they call “bCodes” .  High resolution digital images were recorded every second, and image processing was used to detect Trophallaxis interactions (face to face touching while feeding).  This yielded a wealth of detailed who-what-when data for the observed hives.

Fig. 1. Assay for automatically monitoring social interactions (trophallaxis) in honeybee colonies. (A) Experimental setup. Bees were housed in a glass-walled observation hive (a) that contained a one-sided honeycomb and was connected to a hole in the wall allowing unlimited access to the outdoors for foraging. The hive was illuminated with eight infrared LED lights mounted on an aluminum frame (b). To facilitate automatic image analysis, the honeycomb was backlit with an array of infrared lights mounted behind the hive (c, hidden). Images were recorded with a high-resolution monochrome camera (d) that controlled the infrared lights via a breakout board (e). A standard personal computer (f) controlled the camera and stored images. Some cables are omitted for visual clarity. (B) Typical image obtained from this system, showing barcoded bees inside the observation hive. Outlines reflect whether a barcode could be decoded successfully (green), could not be decoded (red), or was not detected (no outline). The hive entrance is in the lower-right corner. (Inset) Close-up of two bees that were automatically detected performing trophallaxis. ( From [1] )

The data shows that, like human social networks, the bee interactions are “bursty” (i.e., interactions are bunched).  However, unlike human networks, the bee network propagates information faster than the comparison random networks.

The data from this study could not determine the mechanism that causes the relatively fast propagation through the network. The study did show that this propagation was robust when the network was perturbed, indicating that it doesn’t depend on the particular bees or their personal (apial?) history. The researchers note that the insects (probably) do not recognize each other as individuals, so they interact opportunistically.

Rapid spreading of information is one thing, but the same interaction is conducive to rapid spread of disease. Therefore, it seems likely that colonies will self-organize to slow transmission of diseases, perhaps “by dynamically adapting interaction patterns to the health status of individual bees.

If confirmed in further research, these findings might be an important model for other networks.  It would be particularly interesting to learn if and how bees might adapt or moderate interactions to optimize both communication and resistance to disease, i.e., selectively speed and slow propagation.

  1. Tim Gernat, Vikyath D. Rao, Martin Middendorf, Harry Dankowicz, Nigel Goldenfeld, and Gene E. Robinson, Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks. Proceedings of the National Academy of Sciences, 2018.
  2. Claudia Lutz, Reach out and feed someone: Automated system finds rapid honey bee communication networks, in – News. 2018.



Migrating Birds Animation

One of the many cool things about birds (AKA, the avian dinosaurs) is their amazing long distance seasonal migration.  For many species, it’s hard to describe their home territory, because they traverse multiple continents every year.

Researchers at the Cornell Laboratory of Ornithology have been studying the migration routes of many different species, to discover patterns.  The general idea is that the challenges of migrating (e.g., a long continuous flight over water) are the same for any bird, so species may well evolve common solutions.

In 2016 they reported a study of the migrations of over 4,000 species across the Western Hemisphere [1]. The data was taken from the eBird citizen science database, which records millions of sightings from amateur birders.

The basic idea is to calculate a geographical midpoint for the population of each species each day.  The resulting estimates give a “path” and “velocity” for each species’ annual migration. The researchers then selected 118 of the species to study the convergence of migratory trajectories.

The basic finding is, as expected,  that birds that migrate across oceans and land follow paths that are constrained by the respective geography.

Birds that migrate across oceans follow similar geographic tracks and flight patterns (speed, distance, etc.).  This shows that at a population level, “the more stringent requirements and greater risks arising from transoceanic migration, in combination with the seasonal environmental and atmospheric constraints occurring within the region, resulted in species sharing similar broad-scale migration strategies” ([1], p.5)

This pattern can be seen in an animation [2]. Some species fly up the spine of land, others fly across the Gulf of Mexico. And in particular, the species flying north bound across the Gulf of Mexico “bunch up” quite visibly.

Each dot represents a single bird species; the location represents the average of the population for each day of the year (see paper for a more precise explanation of the “average location”). (From [2])

This is a nice study that makes good use of this awesome citizen science data set. (No surprise that birders have the best citizen science—they’ve been doing it for centuries.)

These findings are a summary that doesn’t tell the whole story, of course.  It is widely reported that birds time their migration over water to find favorable weather conditions, and may vary their path to deal with local conditions.  These variations are not visible in this study, though eBird might eventually provide sufficient data to reveal such details.

It is also true that the observations are surely incomplete, especially out at sea where there are few people and the birds are continuously flying.

Obviously, this study can be augmented by other observations, using radar and other remote sensing.


  1. Frank A. La Sorte, Daniel Fink, Wesley M. Hochachka, and Steve Kelling, Convergence of broad-scale migration strategies in terrestrial birds. Proceedings of the Royal Society B: Biological Sciences, 283 (1823) 2016.
  2. Pat Leonard, Mesmerizing Migration: Watch 118 Bird Species Migrate Across a Map of the Western Hemisphere, in All About Birds. 2018.
  3. Brian L. Sullivan, Jocelyn L. Aycrigg, Jessie H. Barry, Rick E. Bonney, Nicholas Bruns, Caren B. Cooper, Theo Damoulas, André A. Dhondt, Tom Dietterich, Andrew Farnsworth, Daniel Fink, John W. Fitzpatrick, Thomas Fredericks, Jeff Gerbracht, Carla Gomes, Wesley M. Hochachka, Marshall J. Iliff, Carl Lagoze, Frank A. La Sorte, Matthew Merrifield, Will Morris, Tina B. Phillips, Mark Reynolds, Amanda D. Rodewald, Kenneth V. Rosenberg, Nancy M. Trautmann, Andrea Wiggins, David W. Winkler, Weng-Keen Wong, Christopher L. Wood, Jun Yu, and Steve Kelling, The eBird enterprise: An integrated approach to development and application of citizen science. Biological Conservation, 169:31-40, 2014/01/01/ 2014.


A New Index of Introduced and Invasive Species

Shyama Pagad and colleagues report this winter on a new Global Register of Introduced and Invasive Species (GRIIS) [2].

 For centuries, human trade and migration and general moving about has carried along a massive movement of other species, deliberately or accidentally introducing species into new ecosystems.  While some introductions have been harmless or even beneficial, invasive species have too often had large and harmful impacts on the natives. Some invaders have pushed out entire populations of plants and animals, eating, killing, or just outcompeting other species.  Others have carried new diseases, or otherwise indirectly harmed native species.

The researchers note that to date, there isn’t adequate information about these biological invasions or their impacts. As a first step toward understanding what is happening and what actions might be taken to prevent or mitigate harm, they are constructing a checklist of invasive species for countries.

One aspect of this work is to harmonize various data sources. The use the Darwin Core metadata standard which I hadn’t heard of. (This is obviously named with reference to the patriarch of web metadata, the Dublin Core standard, which I helped boot up  in 1995.)

The initial dataset was populated by reviewing published reports in public repositories.  These reports were used to determine the species and the fact that it is invasive in a specific geographical area.

The resulting dataset has thousands of entries from 20 countries around the globe.  The entries indicate both presence and documented ecological impact, if any.

This list took a lot of work, and I hope it will be useful. Ideally, this consistant checklist will improve reporting and aid in monitoring trends.

Unfornuately, I suspect that it will not be very useful.

First of all, the product this heroic effort is incomplete.  The data themselves are variable and probably spotty.  I note that Canada has entries for 1500 species, while Brazil has less than 800.  I’m pretty sure that there aren’t twice as many invaders in Canada as Brazil, so we know the data is very incomplete.

As in the case of the Dublin Core, there are deep semantic problems with both the metadata and the dataset itself. I’ll note that the broad categories of “terrestiral” or “freshwater” are nearly useless scientifically and pragmatically.

Worse, the use of countries as the geographical unit of reference is dubious. While small jurisdictions, especially islands, are ecologically relevant “provinces”, continental scale countries like Canada, Brazil, or China are scarcely reasonable ecological units.  An invasion likely affects a particular ecosystem, not a whole country, so the fact that some part of a country might be invaded is pretty useless information.

Indeed, the researchers specifically had to deal with cases where a species is native to one part of a country, and is invading another part of the same country.  So, in these cases, the same country is both native to, and invaded by, some species.  This puts the entire concept of “invasion” in question.

In any case, the actual point of the data is to track the status and progress invaders through ecosystems and across “boundaries” of ecosystems—not human nation states.  Information at this level of granularity are not especially useful.

For example, Zebra mussels  (Dreissena polymorpha) are listed for 30 countries including Canada where they are a major problem.  These entries tell use very little about the spread of this species over the past two centuries.  The relevant geography is not countries, but freshwater systems.

The bottom line is that this dataset is a nice piece of work, but it almost certainly will not be particularly useful in its current form.  It needs way more data, and it needs way more detailed metadata to be really useful.

  1. Helen Briggs, Global register lists alien species, in BBC News – Science & Environment. 2018.
  2. Shyama Pagad, Piero Genovesi, Lucilla Carnevali, Dmitry Schigel, and Melodie A. McGeoch, Introducing the Global Register of Introduced and Invasive Species. Scientific Data, 5:170202, 01/23/online 2018.


Bees Attracted to Fungicide

We’re still trying to figure out what is happening to the honey bees and other pollinators.  It seems likely that agricultural pesticides are killing bees, but the connection is not straightforward.  How are bees encountering the chemicals? How do bees accumulate the chemicals, apparently through long term exposure to low doses? What doses are fatal?

New research from Illinois adds an alarming factor:  foraging bees are attracted to an agricultural fungicide—in some concentrations.  I.e., one common agricultural chemical appears to “taste good” to bees, so they will bring food to the nest with these compounds. [1]

Working at the University of Illinois Pollinatarium, just down the road from me, the researchers conducted a really pretty experiment. They presented free flying bees with choices between sugar water plus a contaminant and sugar water control.  Measuring which sample was consumed reflects the bees’ ability to discriminate and preference for each choice.

As is common in research on this topic, the results are complicated.

The bees were attracted to some naturally occurring chemicals which are thought to be beneficial to bees and colonies. Bees avoided some chemicals, such as caffeine (which is really bad for bees, I’m sure).

The bees avoided or showed no strong preference for other agricultural chemicals, which may suggest that they cannot detect them and/or they are not recognized as potentially harmful.

However, one chemical, chlorothalonil, seemed to be preferred by the bees, at least at low concentrations.  This preference would mean that foragers will selectively bring back food containing this fungicide, potentially accumulating larger concentrations in the hive.

This is important because it means that low concentrations of this chemical might have a large impact on hives, because the foragers will selectively bring it to the hive.  Indeed, chlorothalonil is commonly found contaminating bee hives.

In order to protect pollinators, fungicides are typically applied at night, with the assumption that the overnight interval is sufficient for avoiding adverse outcomes. However, in addition to the risk of direct exposure, this study suggests that the concentration of residues that persist through the next day” ([1]. p. 5)

This is a nice really study, with an elegant and powerful methodology. Nice work, all.

This kind of semi-natural behavioral study have some potential weaknesses.

The measures could not detect behavioral differences among individual bees from the same hive, or from different hives.  It is possible that some bees have different capacity to detect or different preference for the chemicals tested.  If so, the averages reported would be misleading, overlooking potential variation in their foraging. (Such differences could be important, as they would suggest the possibility of natural selection on these behaviors.)

The researchers also point out that the effects of the chemicals also depend on other non-foraging bees. The foragers hand off the food to receivers, who might experience ill effects or reject the contaminated food.  It is also possible that other bees could signal the foragers to avoid some food sources, even if the foragers have a preference.. This social signal might be delayed, which might not be seen in the data of this study.

It is also true that the free flying situation is open to confounding factors, such as weather, which may depress or otherwise influence foraging at different times.  These chance factors might have influenced some of the conditions and not others. Obviously, further studies are needed to replicate the findings.

I’ll also note that the study indicates that different low concentrations may have different behavioral responses.  Clearly, there should be further study of different concentrations, to characterize this more carefully.

  1. Ling-Hsiu Liao, Wen-Yen Wu, and May R. Berenbaum. 2017. “Behavioral responses of honey bees (Apis mellifera) to natural and synthetic xenobiotics in food.” Scientific Reports 7 (1):15924. doi: 10.1038/s41598-017-15066-5
  2. Diana Yates. 2018. “Agricultural fungicide attracts honey bees, study finds.” College of Liberal Arts & Sciences – News, January 11.

How flowering plants conquered the world

Back in the days of the dinosaurs, there were lots of ferns and other plants. (Yum, yum.)

But in the Cretaceous a new line, the angiosperms—flowers—emerged and flourished, and soon dominated the Earth. (A whole lot of new yummy!)

Just how did these new life forms emerge and achieve success so rapidly and completely?  What features or circumstances enabled these plants to out compete other plants?

This month Kevin A. Simonin and Adam B. Roddy report a new theory of what is special about angiosperms [2].

The underlying concepts depend on deep biochemical details of photosynthesis, which depends on the availability of water inside the leaves. Leaves are exposed to air from which CO2 is absorbed, but maintaining phtosynthesis requires the leaves not dry out. So, “increasing leaf surface conductance to CO2 also requires increasing rates of leaf water transport in order to avoid desiccation” ([2]. p. 2).

Water transport is, in turn, limited by the size of cells in the plant. “eaves with many small stomata and a high density of veins can maintain higher rates of gas exchange than leaves with fewer, larger stomata and larger, less numerous veins” ([2], p. 2)

The third piece of the argument is that of the many factors that influence the size of cells in a plant, the minimum size of a cell is constrained by the size of its nuclear material, which is primarily its genome. Plants vary greatly in the number of genes, and larger genomes generally have larger cells.

The idea, then, is that plants with smaller genomes can develop smaller cells, with higher density. This leads to higher water transport and higher photosynthesis.

S&R support this hypothesis with a survey of 400 (contemporary) plant species. The data show strong correlation between genome size and cell size and density, and as a consequence, with gas transport. These relationships hold across all plants.

The evolutionary story, then, is about the ‘strategic’ downsizing of genomes. Over time, plants evolve larger and smaller genomes through various mechanisms. S&R argue that in the Cretaceous, some species developed smaller genomes, and “genome downsizing expands the range of final cell size that is possible” ([2], p. 8).  This plasticity increases the potential breath of habitats, as well as higher maximum productivity.

The bottom line is that Cretaceous angiosperms, and only the angiosperms, developed smaller genomes, which “allowed them to outcompete other plants in almost every terrestrial ecosystem” ([2], p. 9), even in the face of world wide declines in atmospheric CO2 levels.  The rest, as they say, is evolutionary history.


Flowers are one of the signatures of planet Earth (we could as well call it “Planet Flower”), and we humans deeply love and connect with them.  They are also entwined with the development of animal life.  In the millennia after they emerged, they coevolved with pollinators (bees!) and herbivores (dinosaurs!), and spread to fill the land with color and scent and munchy goodness.

But this study suggests that the original success over other plants is due to very fundamental biochemical and mechanical processes.  That’s pretty cool.

Our current Anthropocene Age is pressing hard on these glorious life forms. Loss of habitat and encroachment of human activities are threatening many species and whole ecosystems. Humans coevolved with plants, and it is far from clear how humans will fare in future with a dramatically changed plantscape.

  1. Helen Briggs, How flowering plants conquered the world, in BBC News – Science & Environment. 2018.
  2. Kevin A. Simonin and Adam B. Roddy, Genome downsizing, physiological novelty, and the global dominance of flowering plants. PLOS Biology, 16 (1):e2003706, 2018.

Genome downsizing physiological novelty and the global dominance of flowering plants

PS.  Some good names for bands:

Rapid genome downsizing
Diffusivity of Water in Air
The Gymnosperms