Once upon a time,
The Rostocker Pfeilstorch, found in 1822, demonstrated that birds migrated rather than hibernating or changing form in winter. Image: Wikipedia.
the study of animal migration was as rich with lore as Greek mythology. People thought that migrating birds hibernated at the bottom of lakes over the winter months or bloomed from flowers each spring. Some believed that birds flew to the moon to stay warm, while still others suggested they turned into mice.
Theories surrounding the origins of seasonal birds accumulated rapidly, until a fateful day in 1822, when a white stork crash landed outside of Rostock, Germany with a hand-carved arrow piercing its neck. Researchers tracked the arrow’s origin to a single tribe in central Africa, who had made the arrow from a local wood and shot the bird months before. This African arrow in the neck of a German migrating stork was the beginning of an entirely new way of thinking.
This famous stork, known as Rostocker Pfeilstorch (now stuffed and on display at the University of Rostock), inspired the development of bird banding and animal telemetry, which radically accelerated our understanding of global movement and the connections between ecology and geography. Over time, scientists came to realize that space was its own ecological mechanism and that migration provided the valuable function of stitching geographic space together.
For me, this story underscores just how important it is to consider space, time, and the movement connecting them when studying patterns in the natural world. It was impossible to understand the notion of bird migration until we scaled up our thinking to include travel to far-away places. I can’t help but wonder…
what else might we be misunderstanding because of a limited spatial perspective?
Let’s explore an example.
It is easy to forget that we are living on a moving surface (i.e. a rotating planet!) and that our understanding of the natural world is affected by the movement of the world beneath us. This short video of Mario demonstrates this principle nicely. At the beginning of the video, it appears easy to measure the distance that Mario is jumping up and down. But when the background stops moving (and we realize that Mario is actually moving in a circle), we learn that the linear measurements we took at the beginning of the video are actually incomplete.
My approach to discovery:
I believe science works best when we integrate 3 tools:
Theory
Finding mathematical tools that are able to mechanistically describe the way emergent properties form in nature. I have a fondness for geometry, which plays nicely with the math of Einstein’s theory of relativity.
Simulation
Explore the universe of outcomes possible from the simple set of rules laid out in the theory. Watching models behave under many different conditions points me to the best situations for drawing experimental contrasts.
Experiment
Design microcosms to mimic the mathematical equations and look for places where experimental results are disagreeing with theory or where I can show contrasts between competing candidate mechanisms.
Current Projects
Transport networks as an emergent property of relative motion.
Transport systems move mass and energy along transport networks. These systems emerge as fractal geographic shapes in systems where internal objects are organized according to relative movement speeds (e.g. like cities). I am adopting lessons learned from studying these emergent patterns in urban environments and applying them to our thinking about management and future planning.
My efforts to demonstrate this mechanism to the scientific community will play out over the three acts described below:
Ecological transport networks for urban planners
Question: Is it better to design urban conservation corridors as dendritic fractals rather than nearest-neighbor webs?
Hypothesis: Corridors designed as fractal transportation networks will function better than webs because transport systems (the mechanism here) allow all of the individuals in the system to all concurrently move the mass and energy they need to persist.
Methods: Modeling different flow systems through urban environments using different models for transport networks and fitting those models to animal movement data.
Identifying transport networks in ecological data
Question: Individuals spatially segregate in space so that there are areas with fast movement and slow movement that relate to each other according to the fractal relationships described in the UPTN project.
Hypothesis: We can identify transport networks in natural systems using movement data to identify areas with fast and slow movement regimes that relate to eachother spatially according to fractal scaling rules.
Methods: Use Movebank data to identify transport networks using entropy measures of individual movement trajectories.
Tracking individual movement in engraved spaces
Question: Can we experimentally isolate transport networks as the mechanism of fractal emergent design in spatial movement?
Hypothesis: We should be able to demonstrate the emergence of fractals via engraved spaces by allowing different patterns to emerge from populations living in different spatial configurations.
Methods: Engrave spaces along a gradient of fractal to web shapes and have large Caenorhabditis elegans colonies on those spaces. Use computer vision to track their movements to record the emergence of movement networks within the constrained space. Response variable is a measure of efficiency for movement networks that form under each special configuration.
Future Research Directions
I am launching a modern spatial ecology lab developing three flagship projects:
Designing spatial corridor networks
Using transport networks to design a future where both human and non-human species are free to move as much as they require to meet their energetic and resource needs. I am testing these designs using the Caenorhabditis elegans microcosm system developed as part of my current postdoc.
Rescuing moving species from extinction
I have previously shown several successful examples of evolutionary rescue using a Tribolium microcosm experimental system in the past and now I am extending those experiments into spatial corridor networks to study our ability to rescue urban populations living in constrained urban spatial networks.
Modeling movement trajectories
I have previously shown that pole-to-pole migrants travel along an analemma path as they stay stationary relative to the sun. What I am developing now is an extension to that model that allows for species that spend part of the day in a nest, attached to Earth, and part of the day flying, referencing the sun. We are using move bank data to characterize the relative contribution that attached and detached movement make to creating a realized migratory path.
On-going Experiments
Can assisted migration save moving populations from extinction?
Question: Can assisted migration" rescue populations that are failing to keep up with their moving climate?
Hypothesis: if we artificially increase dispersal speed in populations failing to keep up with their moving habitat, then we can rescue those populations from extinction.
Method: We expose replicate populations to a speed that is drive them to extinction in 5 generations and then expose half of those treatments to transplanting 100 individuals from the trailing edge to the leading edge to see if you can rescue them from extinction.
Results: Assisted migration can save populations from extinction over the course of 6-12 generations, but it only has a very narrow window of success and misplaced interventions can drive populations to extinction faster.
3 types of rescue to help species adapt to change
Question: What is the relative contribution of genes vs. demography vs. unassisted evolution in colonization events.
Hypothesis: we can experimentally isolate the relative contribution of genetics and demographics in colonization by varying the genetic diversity and demographic size of the founding population and using the growth rate of the population over time as a response variable.
Method: We used Triboleum castaneum microcosms to replicate repeated colonization across a gradient of habitats and initial population sizes. In these colonization events and censused those populations each generation to monitor the response in population growth rate.
Results: We found that genes where more important than demographics in creating a successful colonizing population, but that it was easier for those genes to play that positive role when colonizing populations where larger. We also found that evolution was capable of rescuing populations in distress.
Migratory birds don’t move, we do.
Question: Relative contribution between solar cues and Earth’s surface in determining avian migration routes and timing. Migratory birds stay stationary relative to the sun and we move under then on a spinning Earth
Hypothesis: Relative contribution between solar cues and Earth’s surface in determining avian migration routes and timing. Migratory birds stay stationary relative to the sun and we move under then on a spinning Earth
Method: Relative contribution between solar cues and Earth’s surface in determining avian migration routes and timing. Migratory birds stay stationary relative to the sun and we move under then on a spinning Earth
Results: Relative contribution between solar cues and Earth’s surface in determining avian migration routes and timing. Migratory birds stay stationary relative to the sun and we move under then on a spinning Earth
Quantitative approaches to sleuthing human history
Question: Relative contribution between inheritance, sharing, and forced replacement in the spread of agriculture through human cultures.
Hypothesis: Relative contribution between inheritance, sharing, and forced replacement in the spread of agriculture through human cultures.
Method: Relative contribution between inheritance, sharing, and forced replacement in the spread of agriculture through human cultures.
Results: Relative contribution between inheritance, sharing, and forced replacement in the spread of agriculture through human cultures.
