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Harte Lab Research

The Harte lab studies the effects of human actions on, and the linkages among, biogeochemical processes, ecosystem structure and function, biodiversity, and climate. Research spans a range of scales from plot to landscape to global, and utilizes field investigations and mathematical modeling. A long term goal of the group is to understand the dependence of human well being on the health of ecosystem processes.  

 

Two broad areas of research are currently under investigation.

1.       The Effects of Climate Warming on Ecosystem Processes

Global climate change may alter terrestrial systems on local to landscape scales in ways that, in aggregate, can affect climate. Such potential feedbacks include a climate-induced shift in the amount of carbon sequestered in terrestrial ecosystems, a change in the rate of methane consumption by methanogenic bacteria, and alteration of the land surface albedo as a consequence of altered plant species composition. The goal of this research is to improve our ability to reliably forecast the sign and magnitude of such feedbacks across a range of spatial and temporal scales. Our empirical strategy consists of combining experimental field manipulations with observations along landscape-scale natural climatic gradients. Combined with relatively simple mechanistically-based models, manipulation and gradient analyses provide a basis for understanding short and long term effects of climate change over a range of spatial scales.

Our study sites consist of montane meadows and conifer forest on the Western Slope of the Colorado Rockies and montane grazing land in the Tibetan Plateau.

Our research has shown that:

  • There are significant physical, biogeochemical, and biotic responses of montane meadow ecosystems to manipulated climate change.
  • Some of these responses result in feedback effects, which on a larger scale could further alter climate.
  • Many ecological responses to manipulated climate are transient, species-specific, and/or contingent on ambient annual climate.
  • The combination of manipulation experiments and analysis of patterns along natural climate gradients provides a useful means of understanding ecosystem responses to climate change on temporal and spatial scales longer than that accessible under manipulation experiments alone.
  • Our findings refute the naive notion that a simple "space-for-time" substitution allows prediction of ecological responses to climate change based solely on observation of spatial patterns of ecological variables along climate gradients. At the same time, however, our combined observational, manipulative, and theoretical approach is pointing the way to how such gradient analyses can be usefully exploited to predict both short- and long-term ecosystem responses to climate change.

Future research will extend these insights into ecosystem-climate feedback and scaling along several directions:

  1. Extending radiometric data on plant species albedo to landscape and regional scales and estimating the importance of plant-albedo feedback to global warming.
  2. Extending results to additional habitat types and testing our understanding of how climate and other factors control community composition and the quantity of carbon stored as soil organic matter.
  3. Understanding how biodiversity modulates ecosystem response to climate change and how climate change will affect biodiversity.
  4. Investigating how vegetation change and erosion events influence carbon sequestration and the surface energy balance in the Marin headlands of California.

2.       The Distribution and Abundance of Species

We have previously shown that the single fundamental assumption of self-similarity in the distribution of species across a landscape is mathematically equivalent to an empirical relationship in ecology, the widely cited and tested power-law form of the species-area relationship (SAR). The SAR relates the number of species found in a patch of habitat to the area of that patch and the power-law form expresses the relationship with the equation S=cAz.

We also shown that under specified assumptions self similarity leads to:

  • A "commonality" formula that describes the fraction of species in common to two patches as a function of patch size an inter-patch distance.
  • An endemics-area relationship characterizing the dependence of the number of species unique to patch on the area of that patch.
  • A formula for the dependence of species richness on the shape of censused patches. 
  • A unique species-abundance distribution.
  • A power-law relationship between species range and abundance.
  • The dependence on abundance of an aggregation index describing how clumped are the individuals within each species.

The theory of self-similarity thus provides an overarching framework linking numerous ecological relationships to one another. However, a power law behavior for the SAR or for the other measures of spatial pattern listed above is only observed at best over limited scale ranges and for some, but not all, taxa and habitats. Recently, the group has been developing a more comprehensive theory of spatial pattern in ecology that can encompass the limiting case of self similarity but also illuminates the circumstances under which power-law behavior is not expected. In this new theory, knowledge of the species-abundance distribution completely determines the shape of the SAR and all of the other patterns itemized above. Tests of this more comprehensive theory using data from a serpentine grassland system in California and wet and a dry tropical forest sites in Central America are underway. Ongoing work seeks to derive the fundamental statistical assumption of the theory from a dynamical model describing birth, death, and dispersal of individuals.

Last Updated ~ November 19, 2005