Mathematical model improves predictions for species facing climate change
UCLA life scientists developed and tested a comprehensive mathematical model to track the health of populations exposed to environmental change. The research was published on 2 December 2011 in the journal Science.
I fotgot to post this. I wrote it a few months ago. Ooops… It remains valid, regardless. (I really wanted to include some wolf pictures too, no luck though).
The usage is novel, in that it unifies so many sub-fields (population biology, ecology, genetics, life-span and offspring information) in a single predictive model. Doing so enables the model to be run with changes to any given variable, such as temperature, and see the effect on many aspects of a population. For the sake of convenience, let’s refer to this as a one-to-many type model (but only for describing input-to-output).
Prior species-based environmental models were not one-to-many. Instead, they were one-to-one. This meant they were limited to analyzing single relationships, such as the effect of food availability on population size.
Species ecosystems aren’t as complex as other dynamic natural systems. Weather systems and forecasting models such as those used by the NOAA are on the extreme end of a hypothetical complexity scale. They might be more accurately described as many-to-many input-output models! They would be inappropriate for species ecosystems, in part because the environmental field data is not sufficiently robust to support such sophisticated (high-strung?) models.
Wolves
This model was developed with input from wildlife scientists. The most extensive collaboration was with the group who introduced wolves to Yellowstone Park in 1995. The project was intended to control elk and bison overpopulation. It was successful. Deteriorated forest was restored. And much more.
The presence of wolves in Yellowstone Park created an effect known as a
trophic cascade — allowing many species, such as songbirds, beavers and grizzly bears, to thrive again
Meanwhile, elk and bison populations returned to more balanced levels.
Applications
Regarding use for climate change, one of the UCLA researchers said this about the model:
We are not effective at stopping global warming, but perhaps we could identify ways to alter or enrich habitats to mitigate environmental effects…
This is where the Yellowstone Park wolves, and associated project data collected over a 15 year interval, was relevant. That data was used for calibration and testing the model during development.
We could build scenarios for predicting whether a species has no chance of recovery [to guide timing and focus of] planned protection efforts.
Results
Gradual, sustained change over time has more impact on a given species within an ecosystem than frequent changes that fluctuate within the same upper and lower boundaries.
See Scientists develop complex mathematical model with improved predictive accuracy for climate change impact, UCLA Newsroom, December 02, 2011 for more details, and photos.
