Seeds on the Run: A Model of Seed Dispersal. Sara Garnett, Michael Kuczynski , Anne Royer GK-12 workshop 12/5/12. On the run?. Most organisms don’t spend their whole lives in the place they were born Dispersal: movement of organisms away from a given population or parent Natal, adult
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Seeds on the Run:A Model of Seed Dispersal Sara Garnett, Michael Kuczynski, Anne Royer GK-12 workshop 12/5/12
On the run? • Most organisms don’t spend their whole lives in the place they were born • Dispersal: movement of organisms away from a given population or parent • Natal, adult • Many reasons dispersal may be beneficial
Reasons for Dispersal Natal dispersal Adult dispersal Reduce competition with relatives Avoid inbreeding Find better habitat, resources
Effects of Dispersal • Clear benefits to dispersal • Avoid inbreeding • Reduce competition, lower population densities • Make use of better habitats • Why is there variation in dispersal ability? • How does this variation affect communities?
Why does dispersal matter? In the early 1970s, two ecologists were trying to figure out why the many species of trees found in tropical forests were so evenly distributed. They started with dispersal. Winnie Hallwachs Westsocnat.com Dan Janzen Joseph Connell
Null hypothesis Two mature trees growing in a forest are setting and dispersing lots of seed. Where would you expect most of the resulting seedlings to grow? aha-soft.com archigraphs.com
Null hypothesis Seeds, and seedlings, end up mostly clustered under the parent tree. aha-soft.com archigraphs.com
Predict It! (Graph #1) Number of seedlings near far Distance from mother tree
Null hypothesis If we assume dispersal alone dictates where adult trees will be, what distribution of adult trees would this result in? aha-soft.com archigraphs.com
Null hypothesis aha-soft.com aha-soft.com aha-soft.com archigraphs.com archigraphs.com archigraphs.com
Null hypothesis – fail! What we actually see looks more like this. aha-soft.com aha-soft.com aha-soft.com archigraphs.com archigraphs.com archigraphs.com
What could turn this into this? aha-soft.com aha-soft.com aha-soft.com aha-soft.com archigraphs.com archigraphs.com archigraphs.com archigraphs.com
HINT #1 the tropics are full of diversity, but it’s not all spider monkeys and morpho butterflies
HINT #2 • Specialist organisms are especially common in the tropics – many herbivores and disease organisms tend to attack a single victim species. • Do you think they would prefer to feed in high-density or low-density patches? aha-soft.com archigraphs.com
Predict It! (Graph #2) Likelihood of seedling survival high low Seedling density
The Janzen-Connell Hypothesis • Most seeds fall near the tree • Specialist diseases and herbivores will be more abundant in those high-density areas • Seedlings near the parent tree will experience higher mortality rates • Rare seeds that disperse far are most likely to survive to adulthood
The Janzen-Connell Hypothesis Janzen 1970 I = # seeds per unit area P = probability that seed will mature PRC = “Population Recruitment Curve,” I*P. The likelihood of an adult tree ending up there.
Can we use these assumptions to build a model (game) that works (produces predicted results)? • Your seeds are more likely to land close to the mother tree • Seeds that land close to the tree are more likely to have bad things happen to them
The Environment • The game board consists of three zones representing different distances of dispersal from the parent plant 1 2 3
Game pieces (aka: fun with tiddlywinks!) • Seeds/plants are represented by tiddlywinks • When you begin your turn you take control of a new seed • Role a die to see how far the seed disperses • 1-3 = Zone 1 • 4,6 = Zone 2 • 6 = Zone 3 =
Decide your fate! • After your seed has dispersed draw a fate card to see what will happen to your seed • If you have any other plants on the board they must also draw a fate card
End of the game • After each player has gone through 10 turns the game ends
Time to graph! • Add up the number of seeds/plants in each zone and graph this data • Calculate the average height (number of tiddlywinks) for the plants in each zone and graph this data • Report your group’s data to the entire class so we can create graphs of the pooled data
Extensions • Do you think our game-model worked – produced results that reflect the hypothesis? If not, what would you change to make it work? (This is the process theoretical biologists use!) • Can you think of other mechanisms that could create this pattern? How would you model them in game form?