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Title: Integrating ecology into biotechnology

Authors:
; ;
Publication Date:
Research Org.:
Joint Genome Institute (JGI)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1153513
Resource Type:
Journal Article
Resource Relation:
Journal Name: Current Opinion in Biotechnology; Journal Volume: 18; Journal Issue: 3
Country of Publication:
United States
Language:
English

Citation Formats

Katherine D,McMahon, Hector Garcia,Martin, and Philip,Hugenholtz. Integrating ecology into biotechnology. United States: N. p., 2007. Web. doi:10.1016/j.copbio.2007.04.007.
Katherine D,McMahon, Hector Garcia,Martin, & Philip,Hugenholtz. Integrating ecology into biotechnology. United States. doi:10.1016/j.copbio.2007.04.007.
Katherine D,McMahon, Hector Garcia,Martin, and Philip,Hugenholtz. Fri . "Integrating ecology into biotechnology". United States. doi:10.1016/j.copbio.2007.04.007.
@article{osti_1153513,
title = {Integrating ecology into biotechnology},
author = {Katherine D,McMahon and Hector Garcia,Martin and Philip,Hugenholtz},
abstractNote = {},
doi = {10.1016/j.copbio.2007.04.007},
journal = {Current Opinion in Biotechnology},
number = 3,
volume = 18,
place = {United States},
year = {Fri Jun 01 00:00:00 EDT 2007},
month = {Fri Jun 01 00:00:00 EDT 2007}
}
  • Recent decades have seen tremendous increases in the quantity of empirical ecological data collected by individual investigators, as well as through research networks such as FLUXNET (Baldocchi et al., 2001). At the same time, advances in computer technology have facilitated the development and implementation of large and complex land surface and ecological process models. Separately, each of these information streams provides useful, but imperfect information about ecosystems. To develop the best scientific understanding of ecological processes, and most accurately predict how ecosystems may cope with global change, integration of empirical and modeling approaches is necessary. However, true integration - inmore » which models inform empirical research, which in turn informs models (Fig. 1) - is not yet common in ecological research (Luo et al., 2011). The goal of this workshop, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research (BER) program, was to bring together members of the empirical and modeling communities to exchange ideas and discuss scientific practices for increasing empirical - model integration, and to explore infrastructure and/or virtual network needs for institutionalizing empirical - model integration (Yiqi Luo, University of Oklahoma, Norman, OK, USA). The workshop included presentations and small group discussions that covered topics ranging from model-assisted experimental design to data driven modeling (e.g. benchmarking and data assimilation) to infrastructure needs for empirical - model integration. Ultimately, three central questions emerged. How can models be used to inform experiments and observations? How can experimental and observational results be used to inform models? What are effective strategies to promote empirical - model integration?« less
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  • Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less