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.
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
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
- 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
- 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:
- Extending radiometric data
on plant species albedo to landscape and regional scales and estimating
the importance of plant-albedo feedback
to global warming.
- 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.
- Understanding how biodiversity
modulates ecosystem response to climate change and how climate change
will affect biodiversity.
- Investigating how vegetation
change and erosion events influence carbon sequestration and the
surface energy balance in the Marin headlands
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
- 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
- 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