Land carbon models underestimate the severity and duration of drought’s impact on plant productivity View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Hannah R. Kolus, Deborah N. Huntzinger, Christopher R. Schwalm, Joshua B. Fisher, Nicholas McKay, Yuanyuan Fang, Anna M. Michalak, Kevin Schaefer, Yaxing Wei, Benjamin Poulter, Jiafu Mao, Nicholas C. Parazoo, Xiaoying Shi

ABSTRACT

The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0-6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO2. More... »

PAGES

2758

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-39373-1

DOI

http://dx.doi.org/10.1038/s41598-019-39373-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112394029

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30808971


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39373-1'

N-Triples is a line-based linked data format ideal for batch operations.

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Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-019-39373-1'


 

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