| 1. |
- Knauer, Jürgen, et al.
(author)
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Towards physiologically meaningful water-use efficiency estimates from eddy covariance data
- 2018
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 24:2, s. 694-710
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Journal article (peer-reviewed)abstract
- Intrinsic water-use efficiency (iWUE) characterizes the physiological control on the simultaneous exchange of water and carbon dioxide in terrestrial ecosystems. Knowledge of iWUE is commonly gained from leaf-level gas exchange measurements, which are inevitably restricted in their spatial and temporal coverage. Flux measurements based on the eddy covariance (EC) technique can overcome these limitations, as they provide continuous and long-term records of carbon and water fluxes at the ecosystem scale. However, vegetation gas exchange parameters derived from EC data are subject to scale-dependent and method-specific uncertainties that compromise their ecophysiological interpretation as well as their comparability among ecosystems and across spatial scales. Here, we use estimates of canopy conductance and gross primary productivity (GPP) derived from EC data to calculate a measure of iWUE (G1, “stomatal slope”) at the ecosystem level at six sites comprising tropical, Mediterranean, temperate, and boreal forests. We assess the following six mechanisms potentially causing discrepancies between leaf and ecosystem-level estimates of G1: (i) non-transpirational water fluxes; (ii) aerodynamic conductance; (iii) meteorological deviations between measurement height and canopy surface; (iv) energy balance non-closure; (v) uncertainties in net ecosystem exchange partitioning; and (vi) physiological within-canopy gradients. Our results demonstrate that an unclosed energy balance caused the largest uncertainties, in particular if it was associated with erroneous latent heat flux estimates. The effect of aerodynamic conductance on G1 was sufficiently captured with a simple representation. G1 was found to be less sensitive to meteorological deviations between canopy surface and measurement height and, given that data are appropriately filtered, to non-transpirational water fluxes. Uncertainties in the derived GPP and physiological within-canopy gradients and their implications for parameter estimates at leaf and ecosystem level are discussed. Our results highlight the importance of adequately considering the sources of uncertainty outlined here when EC-derived water-use efficiency is interpreted in an ecophysiological context.
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| 2. |
- Mahecha, Miguel D., et al.
(author)
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Detecting impacts of extreme events with ecological in situ monitoring networks
- 2017
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:18, s. 4255-4277
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Journal article (peer-reviewed)abstract
- Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR), identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log-log space. For instance, networks with approximate to 100 randomly placed sites in Europe yield a >= 90% chance of detecting the eight largest (typically very large) extreme events; but only a >= 50% chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON) reliably detect the largest extremes, but that the extreme event detection rates are not higher than would be achieved by randomly designed networks. Spatio-temporal expansions of ecological in situ monitoring networks should carefully consider the size distribution characteristics of extreme events if the aim is also to monitor the impacts of such events in the terrestrial biosphere.
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| 3. |
- Meroni, Michele, et al.
(author)
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Assimilation of satellite observations for the estimation of Savanna gross primary production
- 2015
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In: 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. - 9781479979295 ; , s. 3416-3418
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Conference paper (peer-reviewed)abstract
- Monitoring vegetation gross primary production (GPP) is required for both carbon balance studies and early warning systems aiming to detect unfavorable crop and pasture conditions. This manuscript describes the assimilation of MODIS observations by a simple process model, fed by meteorological data (temperature, incident radiation and rainfall) and linked with a canopy reflectance model, to estimate GPP. GPP simulations are benchmarked against eddy covariance data collected in a semi-arid environment of a sparse Savanna in the Sudan.
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