Last semester, I wrote about the process of bee identification as I used DiscoverLife to work on sorting our bee
inventory. This semester, I’ve been doing something similar: pollen
identification. Pollen identification has a range of applications, from fossil
dating to track the evolution of plants to plant
physiological studies to studies on the foraging behavior
of pollinators. In our recent pollen foraging project, we are looking at
the diversity of pollen collected by honeybees in different treatments – that
is, a normal colony, and a colony with an experimentally impaired communication
system. Our goal is to see whether honeybees use communication to collect a
great diversity of pollen, or if its function is more like how it works in
nectar foraging, where the colony shares information to converge collectively
on the best resources. There are reasons to suspect either strategy – pollen
diversity seems to be valuable in honeybee diet, but some pollen sources
could be more fruitful than others – so it will be interesting to see in which
direction our data points.
So, basically, we have many samples of pollen that were
collected from each colony during the experiment using
a pollen trap, and I made microscope
slides of those samples to get a representative sense of their diversity.
For the past few weeks, the task has been to distinguish between and count the
types of pollen on the slides, and to identify those types. But unlike the
process of taxonomically sorting bees or other biota, the world of pollen
sorting doesn’t avail me of nice tools like DiscoverLife. And since this was
really my first time looking at pollen under a microscope, I often found myself
asking some of the same questions as Jingnan
in his computer vision project: is this blob-looking-thing different from
that other blob-looking-thing and why?
As it turns out, pollen grains that generally look like
blobs actually have a range of detailed surface characteristics and different
shapes. The image below from the Dartmouth Electron Microscopy Facility gives a
sense of just how unique different pollen types can be.
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Image 1. Pollen diversity viewed through an electron microscope
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Unfortunately, the bee lab does not have an electron
microscope to play with. Our microscope does show some level of detail, and we
can clearly see different types of pollen. These images are representative of
what I was looking at in my slides. You can see that in some cases, discrimination
is pretty easy; in others, not so much.
Image 2. California buckwheat (Eriogonum fasciculatum) pollen in one of our samples
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Image 3. Solanum umbelliferum pollen
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You can also see that even pollen grains of the same type
may appear different in size, detail, and so on. What kind of criteria could we
use to draw the line between normal variability within a “type” (family,
species, etc.), or variability that defines different types? There are a few
basic characteristics visible under our microscope that I used to discern
pollen types: some examples include the shape of the grain, the presence of
one or more furrows, surface texture, and the number and shapes of apertures
(image 4). For example, I would have been able to distinguish the E.
fasciculatum pollen (image 2) from S. umbelliferum (image 3) because E.
fasciculatum appears tricolpate. Even though these characteristics don’t
necessarily always correspond to a certain taxon (e.g. many taxa are
monoporate), they are good indicators of similarity to use when looking at
reference slides of previously collected and identified samples. After doing
some sketches of pollen collected during summertime surveys at the BFS in 2015
and 2016, I pick a few possible matches among the reference slides for each
slide that I made, and use those characteristics to decide if they could be the
same. Some characteristics that seemed less reliable included small variations
in the size of the grain, though general size is a helpful grouping factor.
This method, while time-intensive, worked quite often. As
expected for southern California during the summertime, I identified a lot of
buckwheat pollen. But most of the pollen types I identified got catalogued as
“unknown #1, #2, #3…”. They didn’t match anything in our reference slides,
though they appeared multiple times in our own samples. Since we’re mostly
interested in looking at pollen diversity, we can deal with counting unknowns
as long as we recognize what’s the same and what’s different, but it might be
good down the road to get a sense of what exactly the bees are foraging on. It
could be that they’re foraging on flowers in people’s gardens, which would
explain why they don’t match any of our references. After all, the foraging
radius of bees is
known to reach, or perhaps even exceed, seven miles, and our field station
is surrounded on all sides by suburbia. In the future, we might be able to do some genetic analysis on
our samples to identify what’s in them.
Image Credits
[1] image from the Dartmouth College Electronic Microscope
Facility
[2], [3], [4] image taken by Saul Gonzales
[5] image taken by Tessa Finley
[6] image from the Paleoecology department website of Universität Bern, originally published in G.
Lang (1994).
Further
Reading
Pernal, Stephen F., and Robert W. Currie. “The Influence of Pollen Quality on Foraging Behavior in Honeybees (Apis Mellifera L.).” Behavioral Ecology and Sociobiology 51, no. 1 (December 1, 2001): 53–68.
Williams, Joseph H. “The Evolution of Pollen Germination Timing in Flowering Plants: Austrobaileya Scandens (Austrobaileyaceae).” AoB Plants 2012 (January 1, 2012): pls010.
Wilson, Erin E., C. Sheena Sidhu, Katherine E. LeVan, and David A. Holway. “Pollen Foraging Behaviour of Solitary Hawaiian Bees Revealed through Molecular Pollen Analysis.” Molecular Ecology 19, no. 21 (November 2010): 4823–29.



Would be cool if one could use the 3D printer and make pollen Christmas ornaments!
ReplyDeleteThat is an awesome idea! But how to design them? We need a tiny 3D scanner too.
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