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Experimental warming in forests Pathogen mediation of forest diversity Experimental warming in forests Funding DOE Climate change is likely to affect tree recruitment in forests of the temperate zone enough to change species abundances and distributions. Projected increases in surface temperatures of between 2 and 8C over the 21st century will alter recruitment including germination, growth and mortality. Our experiments examine the effects of air and soil warming on recruitment in mixed deciduous forests in southern New England and in the Piedmont region of North Carolina. Air and soil warming experiments in two eastern deciduous forest sites--Harvard Forest in central Massachusetts and Duke Forest in the Piedmont region of North Carolina--share a number of tree species including red, black and white oaks and sugar and red maples, and are respectively near the cool and warm ends of the ranges of several species (near northern limits of black oak, white oak, and tulip poplar; southern limits of sugar maple, sweet birch, and chestnut oak). Over the course of the four-year study we will make a number of plant community and biogeochemical measurements in addition to measurements of soil and air temperature, relative humidity and soil moisture. For the seeds, we will track germination, growth (height and diameter) and survival, and for the seedlings we will track growth and survival. Spring and fall phenology of the seedlings will also be measured. To help us interpret the plant responses to warming, we will make measurements of leaf-level photosynthesis, net N mineralization and N concentrations in green leaves, and biomass allocation to aboveground and belowground plant parts in a final harvest at the end of the study. Collaborators: Dave Bell, Jim Clark, Rob Dunn, Aaron Ellison, Jerry Melillo, Jackie Mohan, Carl Salk Pathogen mediation of forest diversity Funding NSF Plant pathogens are often invoked as an important mechanism for controlling tree seedling growth and survival. Their early life stage effects could ultimately serve an important role in shaping forest community structure and maintaining tree species diversity. Despite their potential importance, relatively little is known about the role and identity of pathogens in temperate forest ecosystems. The goals of this research are to: (1) characterize the fungal and oomycete pathogens causing seedling disease and mortality for a number of important southeastern US forest tree species; and (2) test a classic ecological hypothesis which predicts that host-specific pathogens drive spatial patterns of seedling recruitment. These objectives are being accomplished through a combination of field experiments and laboratory analyses. Mixed-species plots of tree seedlings have been planted along a natural soil moisture gradient in two mixed hardwood stands in North Carolina. Field sites have been wellcharacterized with respect to tree demography and are outfitted with a wireless sensor network that collects high-frequency data on relevant abiotic covariates. Pathogens are isolated and identified using both cultural as well as modern DNA-based molecular methods. The results of this study combine these multiple sources of information into an emergent picture of the role of seedling pathogens in forest community dynamics. Collaborators: Jim Clark, Michelle Hersh, Rytas Vilgalys Large-Scale Wireless Sensor Networks for Observation of Ecosystem Processes Funding: NSF IDEA-0308498 Progress in an array of technologies, including microelectronic sensing and computation, wireless communication, and the self-assembly of autonomous devices into cooperative networks has inspired the vision of wireless sensor networks. While networks of intelligent agents transparently embedded into our physical environment could advance human welfare in a number of domains, research indicates that any successful wireless sensor network must be carefully optimized for its application. One of the most compelling of these applications is dense spatio-temporal sensing of environments to enable better understanding of environmental and ecosystem processes across multiple scales. Our goals are to (i) test this hypothesis in three rigorous field studies, (ii) bootstrap the application of wireless sensor network technology in many applications, and (iii) build awareness of the benefits of the technology to society, and improve collaboration between engineering and the sciences. The instrumentation development component of this project builds on a successful seed effort in which we have constructed a small proof-of-concept wireless environmental sensing network. We will build a "distributed instrument"---a prototype network comprising hundreds of palm-sized wireless sensors. In anticipation of this prototype development, we have paid careful attention to ensuring that our networking technology would successfully scale up to hundreds and thousands of sensors at up to landscape geographic scales. The prototype network technology will be deployed
to enable a new degree of data quality in three diverse field
studies. First, we will probe the role of the role of fine-scale
environmental phenomena in the maintenance of ecosystem diversity
in two Eastern US forests. The second experiment maps the complexity
of microclimates in the crowns of the coastal redwoods of California.
And in the third field study, we will determine the effects of
scale on eddy covariance measurements of ecosystem energy balance
in Northern Arizona. Collaborators: Pankaj Agarwal, Carla Ellis, Paul Flikkema, Alan Gelfand, Kamesh Munagala, Jun Yang Recent publications:
Automated methods for generating high-resolution GIS data bases from remotely sensed data Funding: NSF SEII 0430693 Consequences of global change for land cover, carbon cycles, and biodiversity loss involve complex interactions at fine scales, such as resource availability in forest understories, to regional land-cover, climate, and CO2. Among the most important challenges in the study of global change is the need for high-resolution forest attribute data over extended regions that could be used to understand how regional and local influences together influence ecosystems. Our research will allow us to acquire, analyze, and distribute high-resolution GIS databases of important environmental attributes with regional coverage. The principal computer science problem is to develop new techniques to extract forest attributes in the form of GIS databases from remotely sensed data collected by low cost instruments. The computer science research will focus on building an aerial data acquisition system for collecting high quality, high-resolution digital images and other remote sensing data, and a suite of analysis tools for creating GIS databases of environmental attributes with sub-meter geo-registration and elevation accuracies. Key to achieving this level of accuracy is the ability to automatically produce and incorporate high-resolution digital elevation maps of the forest canopy. Collaborators: Jim Clark, Howard Schultz, Thomas Millette, Mike Wolosin.
Funding: NSF DEB-0089769 Anticipated rapid climatic change over the next decades to centuries raises the concern that plant populations will be unable to migrate fast enough to track changing environmental conditions. Migration rates depend on dispersal of seed and on barriers to population spread, such as mountain ranges, large water bodies, and urban and agricultural land use. Range expansions at the end of the last ice age provide evidence that populations paced a global change in the past, but current evidence does not indicate how fast these migrations occurred. Our study will help determine the pathways of past population spread and provide insights into to rates at which migrations occurred. We are constructing maps of chloroplast DNA variation across the
ranges of common eastern North American tree species. Such maps
reveal the "genetic fingerprint" of late-glacial refugia
and post-glacial migration routes and are complementary to existing
fossil pollen data. The maps of post-glacial migration we develop
will provide a framework for analysis of population expansion.
Results will be used to test hypotheses concerning how growth
of trees and dispersal of seed affect the potential of plants
to track rapid environmental change. Recent publications:
Forest dynamics and
environmental change Understanding how forests respond to environmental change requires models that extrapolate from short-term observations to long-term (decade to century) dynamics. The current "gap dynamic" paradigm does this extrapolation under the assumption that recruitment is governed by conditions within canopy gaps 30 m in diameter. Much empirical evidence and our experimental tests of the paradigm suggest that diversity in many forests may depend on much larger canopy gaps than assumed in the models now used to forecast forest response to global change. If the underlying assumptions of the models are unrealistic, then predictions under novel environments of the future are likely misleading. We are conducting a series of field experiments
and model tests to demonstrate gap sizes at which recruitment
limitation is severe and whether maintenance of forest diversity
depends on large gaps. Field studies will both test for specific
life history stages at which recruitment limitation occurs and
the factors responsible for limitation, while also providing parameter
estimates for modeling studies.
New computational approaches
for forest dynamics Funding: NSF BDEI 0131905, NSF DEB 0425465 Understanding the mechanisms responsible for diversity of forests requires data and modeling approaches that accommodate the high dimensionality of natural systems, while retaining the capacity to focus on key variables. Most modeling approachestend to ignore the dominant sources of variability in data, treating them as 'error' or 'noise'. Biotic diversity typifies the challenges represented by complex systems. The 'mechanisms' used to explain it are primarily deterministic (e.g., tradeoffs among species in terms of competitive ability, colonization capacity, and life history traits), whereas it is well-known that stochastic (unmeasured) factors not only dominate, but, in themselves can promote diversity. This project exploits new computational methods for both inverse
estimation and forward simulation to evaluate the efficacy of
diversity mechanisms in natural systems. Inverse estimation makes
use of hierarchical Bayes (HB) model structures to test assumptions
of diversity mechanisms. Advances of the 1990's provide a common
framework that admits nearly all high-dimensional problems. It
will be used here to evaluate the deterministic differences
together with the broad overlap among species. Unusually
large and long-term sets, available from previous studies, provide
a rich source of empirical evidence. Forward
simulation methods will be developed to test predicitions of diversity
mechanisms and to evaluate the contributions of those mechanisms
to overall forest dynamics. Results should provide new insight
into the factors that control diversity in nature (as opposed
to in simple models), which is a basic requirement for wise stewardship
of forest resources and biotic diversity. Collaborators: Pankaj Agarwal, Sukhendu Chakraborty, Benoit Courbaud, Mike Dietze, Sathish Govindarajan, Sean McMahon, Hai Yu Recent publications:
Succession and rising
CO2 As part of Duke's Free Air CO2 Enrichment
(FACE) experiment we are examining the effects CO2 fumigation
on an intact loblolly pine stand. We are focussing on the potential
for CO2 to affect recruitment and early success of plant populations
by way of changes in fecundity and seedling growth and survival.
We have thus far observed large increases in pine seed production
and differential effects on seedling success. Recent publications
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