Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest. (20th January 2014)

• Record Type: Journal Article
• Authors: Rowland, Lucy; Hill, Timothy Charles; Stahl, Clement; Siebicke, Lukas; Burban, Benoit; Zaragoza‐Castells, Joana; Ponton, Stephane; Bonal, Damien; Meir, Patrick; Williams, Mathew
• Is Part Of: Global change biology. Volume 20:Number 3(2014:Mar.)
• Page Start: 979
• Page End: 991
• Publication Date: 2014-01-20
• Subjects: Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.12375
• Languages: English
• ISSNs: 1354-1013

Abstract

<abstract abstract-type="main" id="gcb12375-abs-0001"> <title>Abstract</title> <p>The relative contribution of gross primary production and ecosystem respiration to seasonal changes in the net carbon flux of tropical forests remains poorly quantified by both modelling and field studies. We use data assimilation to combine nine ecological time series from an eastern Amazonian forest, with mass balance constraints from an ecosystem carbon cycle model. The resulting analysis quantifies, with uncertainty estimates, the seasonal changes in the net carbon flux of a tropical rainforest which experiences a pronounced dry season. We show that the carbon accumulation in this forest was four times greater in the dry season than in the wet season and that this was accompanied by a 5% increase in the carbon use efficiency. This seasonal response was caused by a dry season increase in gross primary productivity, in response to radiation and a similar magnitude decrease in heterotrophic respiration, in response to drying soils. The analysis also predicts increased carbon allocation to leaves and wood in the wet season, and greater allocation to fine roots in the dry season. This study demonstrates implementation of seasonal variations in parameters better enables models to simulate observed patterns in data. In particular, we highlight the necessity to simulate the seasonal patterns of heterotrophic respiration to accurately simulate the net carbon flux seasonal tropical forest.</p> </abstract>