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Title: Measuring water fluxes in forests: The need for integrative platforms of analysis

Abstract

To understand the importance of analytical tools such as those provided by Berdanier et al. (2016) in this issue of Tree Physiology, one must understand both the grand challenges facing Earth system modelers, as well as the minutia of engaging in ecophysiological research in the field. It is between these two extremes of scale that many ecologists struggle to translate empirical research into useful conclusions that guide our understanding of how ecosystems currently function and how they are likely to change in the future. Likewise, modelers struggle to build complexity into their models that match this sophisticated understanding of how ecosystems function, so that necessary simplifications required by large scales do not themselves change the conclusions drawn from these simulations. As both monitoring technology and computational power increase, along with the continual effort in both empirical and modeling research, the gap between the scale of Earth system models and ecological observations continually closes. In addition, this creates a need for platforms of model–data interaction that incorporate uncertainties in both simulations and observations when scaling from one to the other, moving beyond simple comparisons of monthly or annual sums and means.

Authors:
 [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); North Carolina State Univ., Raleigh, NC (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1330550
Grant/Contract Number:
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Tree Physiology
Additional Journal Information:
Journal Volume: 36; Journal Issue: 8; Journal ID: ISSN 0829-318X
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Ward, Eric J. Measuring water fluxes in forests: The need for integrative platforms of analysis. United States: N. p., 2016. Web. doi:10.1093/treephys/tpw065.
Ward, Eric J. Measuring water fluxes in forests: The need for integrative platforms of analysis. United States. doi:10.1093/treephys/tpw065.
Ward, Eric J. Tue . "Measuring water fluxes in forests: The need for integrative platforms of analysis". United States. doi:10.1093/treephys/tpw065. https://www.osti.gov/servlets/purl/1330550.
@article{osti_1330550,
title = {Measuring water fluxes in forests: The need for integrative platforms of analysis},
author = {Ward, Eric J.},
abstractNote = {To understand the importance of analytical tools such as those provided by Berdanier et al. (2016) in this issue of Tree Physiology, one must understand both the grand challenges facing Earth system modelers, as well as the minutia of engaging in ecophysiological research in the field. It is between these two extremes of scale that many ecologists struggle to translate empirical research into useful conclusions that guide our understanding of how ecosystems currently function and how they are likely to change in the future. Likewise, modelers struggle to build complexity into their models that match this sophisticated understanding of how ecosystems function, so that necessary simplifications required by large scales do not themselves change the conclusions drawn from these simulations. As both monitoring technology and computational power increase, along with the continual effort in both empirical and modeling research, the gap between the scale of Earth system models and ecological observations continually closes. In addition, this creates a need for platforms of model–data interaction that incorporate uncertainties in both simulations and observations when scaling from one to the other, moving beyond simple comparisons of monthly or annual sums and means.},
doi = {10.1093/treephys/tpw065},
journal = {Tree Physiology},
number = 8,
volume = 36,
place = {United States},
year = {Tue Aug 09 00:00:00 EDT 2016},
month = {Tue Aug 09 00:00:00 EDT 2016}
}

Journal Article:
Free Publicly Available Full Text
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Citation Metrics:
Cited by: 2works
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