Inter-annual variability of Net Ecosystem Productivity for a temperate mixed forest: A predominance of carry-over effects?

Abstract

A B S T R A C TThis study presents twenty years of Net Ecosystem Productivity estimations obtained using eddy covariance in a mixed forest, dominated by beech with sparse conifers, at the Vielsalm station, in the Belgian Ardennes.First the quality and reliability of the data set is discussed. An uncertainty analysis showed that if, on one hand, the site heterogeneity and set-up changes may strongly affect yearly NEP estimates, questioning thus the total carbon budget relevance, on the other hand, robust inter-annual anomalies may be obtained as long as a site dedicated data treatment is carefully applied. A validation of the anomalies by comparison with a growth index derived from tree ring measurements is given. The resulting anomalies (range: [−206; + 123] g C m −2 yr −1 , standard deviation: 93 g C m −2 yr −1 ) being larger than their own uncertainty (∼30 g C m −2 yr −1 ), an inter-annual variability analysis is possible.This analysis shows that the sources of NEP inter-annual variability at the Vielsalm station are multiple but the most prominent causes are biotic processes driven by carry-over effects of preceding meteorological events. The lowest observed NEP, in 2000, resulted from a bark beetle attack probably prompted by an early frost event in 1998. Besides, the robust lagged correlation between NEP anomalies and mean vapor pressure deficit during the preceding vegetation season also suggests a carry-over effect of water limitation during the previous year on the beech NEP. Mechanisms driving this carry-over effect are supposedly linked to tree physiology, which is confirmed by a dependency of canopy photosynthetic capacity to previous year water limitation. Some hypotheses, involving biomass allocation and bud formation, are proposed to explain its lagged impact on canopy photosynthetic capacity.Other causes of NEP inter-annual variability are the radiation during the current vegetation season and the temperature at the end of the winter but the latter variable rather indicates an effect on the conifers interspersed in the plot. Overall, the photosynthetic capacity combined with these two factors explained about 75% of NEP inter-annual variability.

Controls of forest age and ecological memory effects on biosphere-atmosphere CO2 exchange

“…This means that both the current climate conditions and the ones of the previous months or years control NEE seasonal cycle in such an ecosystem. These findings confirmed the existence of different ecosystem type-specific memory or lagged effects (Aubinet et al, 2018).…”

“…Similarly, evidence with regard to the vegetation and climate's ecological memory effects has been provided. For instance, spring temperature seems to have variable memory effects on subsequent summer and autumn ecosystem productivity (Buermann et al, 2018), while Aubinet et al (2018) found a dependency of the current ecosystem functioning to previous year water limitation. This evidence points at the need to understand the sensitivity of global ecosystems to past-time climate variability and disturbances.…”

“…Extensive research has been done to understand climate and disturbance memory effects on CO 2 fluxes (i.e. NEE, GPP, and ecosystem respiration (ER)) (Aubinet et al, 2018;Desai, 2014;Molen et al, 2011;Shen et al, 2016;Zhang et al, 2015b;Zielis et al, 2014). However, given the complexity of NEE responses to disturbances and climate extremes and highly non-linear processes, the legacies of these events on CO 2 fluxes remain unclear (Frank et al, 2015;Vicca et al, 2014), and thus they are rarely implemented in current C cycle models.…”

“…While mean seasonal variations of climate and vegetation control most of the spatiotemporal patterns of the terrestrial CO 2 fluxes ) (Chapter 4), several in-situ studies provide evidence that both past climate conditions and disturbances can significantly influence the contemporary spatiotemporal patterns of the terrestrial CO 2 fluxes. For instance, the lag effects of water limitations (Aubinet et al, 2018;Desai, 2014;Liu et al, 2018;Shen et al, 2016) and antecedent air temperature conditions can have either adverse or beneficial effects on vegetation productivity from seasonal to decadal timescales (Buermann et al, 2018;Zhang et al, 2015b;Zielis et al, 2014). Furthermore, climate extreme events (e.g.…”

“…This could suggest that the climatic conditions of the previous years (e.g. water limitations (Aubinet et al, 2018;Desai, 2014), increased precipitation (Shen et al, 2016), or minimum air temperature during spring of the previous year (Zielis et al, 2014)) not only control NEE seasonal patterns in deciduous forests but also mean seasonal vegetation fluctuations. It was therefore probable that seasonal leaf physiology due to leaf aging also drived the residual seasonal patterns (Rodríguez-Calcerrada et al, 2012).…”