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Variability in ecosystemCO2 exchange

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Are temporal variations of leaf traits responsible forseasonal and inter-annual variability in ecosystem CO2exchange?Siyan Ma*,1, Dennis D. Baldocchi1, Stefania Mambelli2and Todd E. Dawson1,21Ecosystem Sciences Division, Department of Environmental Science, Policy, and Management, University of Californiaat Berkeley, 130 Mulford Hall #3114, Berkeley, California 94720, USA; and2Department of Integrative Biology and Centerfor Stable Isotope Biogeochemistry, University of California, Berkeley, California 94720, USASummary1. Seasonal and inter-annual variability in ecosystem carbon dioxide (CO2) exchange is attrib-uted to numerous climate drivers. However, climate effects on metabolism often override ecolog-ical functions. This study seeks insight into which biological and ecological processes influencetemporal patterns of ecosystem productivity in natural ecosystems.2. The specific objectives of this study are to (i) identi fy seasonal and inter-annual patterns ofecosystem-level photosynthesis in relation to climatic conditions, (ii) exami ne and compare sea-sonal and inter-annual variations in leaf traits for annual grasses and oak trees across multipleyears, and (iii) explore interactions among leaf traits and ecosystem-level photosynthesis acrossmultiple seasons and years.3. We conducted this study in a woody savanna and open grassland in California, USA. Ecosys-tem-level photosynthetic rates of annual grasses (Agrass) and oak tree canopy (Acanopy) werededuced from eddy covariance measurements over a 7-year period (2001 and 2007). In conjunc-tion, we sampled grass and oak leaves at weekly to monthly intervals and constructed a multi-year time series of leaf nitrogen concentration (N), leaf mass per unit area (LMA), leaf carbonconcentration (C), and leaf carbon stable isotope discrimination (D).4. Given the same grass community age or tree canopy age, inter-annual variations of the photo-synthetic rates were up to 1–2 gC m)2day)1for annual grasses and oak trees while the two typesof vegetation were exposed to different, wide ranges of inter-annual climate fluctuations: up to5 C in daily mean soil temperature, 15% in soil moisture, and 10 mol m)2day)1in photosyn-thetically active radiation.5. While both grass and oak leaf traits varied seasonally and inter-annually, they experiencedtemporal patterns and seasonal peaks that were distinct from one another. Multi-year means ofgrass leaf N, C, D, and LMA were 2Æ3%, 40Æ8%, 22Æ6& and 71Æ3gm)2, respectively; multi-yearmeans of oak leaf N, C, D, and LMA were 1 Æ9%, 45Æ1%, 20Æ5& and 132 g m)2, respectively.6. Based on the analysis of variance, seasonal and inter-annual terms were associated with Agrassor Acanopyup to 90% or 81%. On the other hand, variations in leaf N, LMA, C, D, and theirinteractions could statistically explain about 53% and 26% of variations in Agrassand Acanopy,respectively.7. We discussed possible biological and ecological processes involved in regulating seasonal andinter-annual variability in ecosystem-level photosynthesis. Clearly, seasonal and inter-annua lvariation in ecosystem photosynthesis was strongly associated with the dynamics of leaf traits.Key-words: annual grasses, ecosystem ecology, eddy-covariance method, gas exchange of CO2,gross primary productivity, Mediterranean-type climate, Quercus douglasii (blue oak)*Correspondence author. E-mail: [email protected] 2010 The Authors. Journal compilation 2010 British Ecological SocietyFunctional Ecology 2010 doi: 10.1111/j.1365-2435.2010.01779.xIntroductionPlants in natural environments experience a wide variety ofenvironmental stresses (e.g. drought, temperature extremes,low light levels, and nutrient limitations). When any type orcombination of these stresses occurs, it is common thatplants reduce their growth, as triggered by their systemicfeedbacks (Chapin 1991). These stresses can also modulatestructural and functional leaf traits, such as leaf area andmass, chemical concentration (e.g. nitrogen), life span, andphotosynthetic rate (Damesin, Rambal & Joffre 1998b;Niinemets 2001). Efforts have been made to understandinteractions between plants and environments, but earlierstudies have focused on differences in interactions betweenplants and environments within or across species, oftenbased on single snap shots in seasons or years (Reich et al.1991a; Reich, Walters & Ellsworth 1997; Adams, White &Lenton 2004). When the flow of energy and matter into andout of an ecosystem is of interest, measurements at the eco-system level provide a better bird’s-eye view of the func-tional types of vegetation over longer time series. Thisprogress requires a hierarchical or across-scale approach tounderstand the complex systems (O’Neill et al. 1986). Forexample, it is important to understand why net ecosystemproductivity, an ecosystem-level variable to approximatelymeasure integrated growth of plants in ecosystem, is highlyvariable over seasons and years. This study seeks insightinto which biological and ecological processes influencetemporal patterns of ecosystem productivity in natural eco-systems.The eddy-covariance method has been for decades a reli-able, direct way to measure ecosystem-level carbon dioxide(CO2) exchanges in the field (Baldocchi 2003, 2008), and eco-system-level photosynthetic rates can now be derived fromintensive measurements of gas exchange (Baldocchi & Vogel1996; Misson et al. 2007; Baldocchi 2008). This techniquemakes it possible to monitor photosynthesis across differenttime scales—from a half hour to multiple years. Such time-intensive measurements clearly illustrate that ecosystemmetabolisms are highly variable across seasons and years innumerous ecosystems, and the majority of variabilityreported across these diverse biomes is attributed to tempera-tures, water, and light levels (Goulden et al. 1996; Saigusaet al. 2005; Ma et al. 2007).Climate effects on metabolism are strong and often over-ride ecological functions (Hui, Luo & Katul 2003; Richard-son et al. 2007) even though ecological functions are criticalfor interpreting flux data across climate and ecological spacesand for parameterizing ecosystem models (Moorcroft 2006).How to tease biological and ecological mechanisms apartfrom climate controls on temporal patterns in ecosystem pho-tosynthesis remains a challenge (Baldocchi & Wilson 2001;Hui, Luo & Katul 2003; Richardson et al. 2007; Wang et al.2007).The approach of this study is to link measurements of


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