Theoretical Integration
Background
The Theoretical Integration component aims to advance the science by:
- Developing diagnostic procedures for recognizing ecological tipping points or other undesirable ecosystem changes such that society can make informed decisions
- Improving methods to separate ecological signal from noise
We will then use the science to:
- Provide society with better metrics to assess whether an observed or predicted ecosystem change represents a danger to critical ecosystem services or other land-management goals (e.g., the specific mandates legislated for national or state parks, Forest Service, BLM lands, etc., or specific goals of various NGOs)
- Provide methods and information for evaluating and guiding land-management decisions
What we see today is the end result of biological processes that converge from many different temporal and spatial scales—for example, trees that have generation times in excess of a century interacting with rodents that have generation times less than a year; selection acting instantaneously on an individual whose response is constrained by a genome that took millions of years to evolve; rapid spread of new pathogens that decimate species that have dominated for millennia; a migrating species who becomes a part of different ecosystems in different parts of the year; or the loss of a species that has “always” been there.
The net result is that everywhere we look we can see ecological change, but in many cases we still do not know how to recognize which changes are meaningful. An apt analogy is the difference between weather and climate, weather being the day-to-day fluctuations, climate being the decadal, century, or longer averages that define what we regard as normal for a place. We know most about 'ecological weather'—the short-term, rapid fluctuations that are essentially the 'noise' in biological systems. But we still know very little about the 'ecological climate'— essentially the 'signal' that a given ecosystem is operating within normal, healthy bounds.
Given global climate change combined with other impacts to biological systems—habitat fragmentation, invasive species, and human population growth—distinguishing ecological signal from ecological noise has become more than an academic exercise. It is absolutely essential to recognizing when we are about to lose ecosystem services we rely on (for example, clean water provided by filtration and cleansing through soil microbes, or healthy fisheries), or whole ecosystems which society has long valued and sought to conserve (for example, national parks or coral reefs).
Ecological theory already predicts that such important ecosystem losses are not gradual. Rather, ecosystems are thought to change very dramatically and suddenly when they hit “tipping points,” shifting from conditions that indicate ecological health, like a productive lake full of many different species, to an unhealthy state, for example, a green, algae-filled morass where few species can live. Such “state-shifts” are particularly worrisome, in that once the threshold is crossed, it is difficult, in some cases impossible, to return to the original healthy state, at least over time scales meaningful to people.
Research Agenda
What biological theory does not yet do well is recognize when we are on the verge of ecological tipping points. Therefore our goal is to clearly characterize the early warning signs that precede crossing ecological thresholds, in time to avoid undesirable effects. Our approach will emphasize the following.
- Use integrated analyses of fossil, historic, and modern biological data to:
- Define benchmarks of “normal” for ecosystems in metrics like species composition, species diversity, abundance, trophic structure, food-webs, genetic diversity, population structure, importance of keystone species, pace of local and global extinctions, etc.
- Understand the shortcomings and gaps in current predictive models such as ecological niche modeling, and past and future climate predictions, thereby improving accuracy of biological-response forecasts.
- Identify which kinds of species, and which levels in the biological hierarchy—genes, populations, species, communities, etc.—hold the most information for predicting detrimental consequences of global change, i.e., identify “canaries in the coal mine.”
- Use theoretical models to provide ranges of reasonable expectations for conserving genetic diversity, populations, species, landscapes, and ecosystem services in specified areas (from global to local scales) by:
- Developing models that explore how humans interact with and limit or enhance survival of other species, using ecological first-principles, such as metabolic theory, energetic constraints, and maximum entropy approaches. For example, we envision energy-flow models that predict how many and what kinds of species a region can feasibly support, given human population sizes and needs for resources both globally and locally.
- Improving existing ecological models to make them more effective in addressing critical conservation and land-use issues, for example: using species-area models to predict extinction intensities; using neutral theory to predict how communities might be expected to change in composition and species-abundance in fragmented versus non-fragmented landscapes; understanding the links between ecological variation in space and ecological variation in time; understanding the relationship between metabolic constraints, “fossil” energy released from fossil fuels, and global species diversity.
Faculty contacts
Group Leaders: Anthony Barnosky and Charles Marshall
Participating Faculty & Staff: