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	<journal>
		<journal_title>Biogeosciences</journal_title>
		<journal_url>www.biogeosciences.net</journal_url>
		<issn>1726-4170</issn>
		<eissn>1726-4189</eissn>
		<volume_number>7</volume_number>
		<issue_number>1</issue_number>
		<publication_year>2010</publication_year>
	</journal>
	<doi>10.5194/bg-7-257-2010</doi>
	<article_url>http://www.biogeosciences.net/7/257/2010/</article_url>
	<abstract_html>http://www.biogeosciences.net/7/257/2010/bg-7-257-2010.html</abstract_html>
	<fulltext_pdf>http://www.biogeosciences.net/7/257/2010/bg-7-257-2010.pdf</fulltext_pdf>
	<start_page>257</start_page>
	<end_page>274</end_page>
	<publication_date>2010-01-20</publication_date>
	<article_title content_type="html">Process-based simulation of seasonality and drought stress in monoterpene emission models</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>R. Grote</name>
			<email>ruediger.grote@imk.fzk.de</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>T. Keenan</name>
		</author>
		<author numeration="3" affiliations="3">
			<name>A.-V. Lavoir</name>
		</author>
		<author numeration="4" affiliations="3">
			<name>M. Staudt</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany</affiliation>
		<affiliation numeration="2" content_type="html">CREAF, Autonomous University of Barcelona (UAB), 08139 Bellaterra, Barcelona, Spain</affiliation>
		<affiliation numeration="3" content_type="html">DREAM team, Centre d&apos;Ecologie Fonctionnelle et Evolutive â€“ Centre National pour la Recherche Scientifique UMR 5175 (CEFE-CNRS), 1919 Rte de Mende, 34293 Montpellier Cedex5, France</affiliation>
	</affiliations>
	<abstract content_type="html">Canopy emissions of volatile hydrocarbons such as isoprene and monoterpenes
play an important role in air chemistry. They depend on various
environmental conditions, are highly species-specific and are expected to be
affected by global change. In order to estimate future emissions of these
isoprenoids, differently complex models are available. However, seasonal
dynamics driven by phenology, enzymatic activity, or drought stress strongly
modify annual ecosystem emissions. Although these impacts depend themselves
on environmental conditions, they have yet received little attention in
mechanistic modelling.
&lt;br&gt;&lt;br&gt;
In this paper we propose the application of a mechanistic method for
considering the seasonal dynamics of emission potential using the &quot;Seasonal
Isoprenoid synthase Model&quot; (Lehning et al., 2001). We test this approach with
three different models (GUENTHER, Guenther et al., 1993; NIINEMETS,
Niinemets et al., 2002a; BIM2, Grote et al., 2006) that are developed for
simulating light-dependent monoterpene emission. We also suggest specific
drought stress representations for each model. Additionally, the proposed
model developments are compared with the approach realized in the MEGAN
(Guenther et al., 2006) emission model. Models are applied to a Mediterranean
Holm oak (&lt;i&gt;Quercus ilex&lt;/i&gt;) site with measured weather data.
&lt;br&gt;&lt;br&gt;
The simulation results demonstrate that the consideration of a dynamic
emission potential has a strong effect on annual monoterpene emission
estimates. The investigated models, however, show different sensitivities to
the procedure for determining this seasonality impact. Considering a drought
impact reduced the differences between the applied models and decreased
emissions at the investigation site by approximately 33% on average over
a 10 year period. Although this overall reduction was similar in all models,
the sensitivity to weather conditions in specific years was different. We
conclude that the proposed implementations of drought stress and internal
seasonality strongly reduce estimated emissions and indicate the
measurements that are needed to further evaluate the models.</abstract>
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</article>

