New study improves remote sensing detection of effects of strong droughts on photosynthesis of forests
24 June 2016
The new technique couples directly to a photochemical process in the leaves, while earlier techniques mainly used visual changes such as leaf browning.
Remote sensing enables estimation of photosynthesis (gross primary production or GPP) by forests and other ecosystems from space. A satellite detects the emitted or reflected radiation by the investigated surface. This signal is then used to calculate various vegetation indicators, some of which are a proxy for green biomass, which relates to photosynthesis. Other indices provide information about the photochemical processes in leaves and can thus improve remotely-sensed estimation of GPP.
GPP data are crucial to assess the feedbacks of ecosystems to the climate system. Vegetation is a crucial buffer for atmospheric CO2 (see also this article). Understanding GPP variability in a world undergoing climate change is therefore important. Sara Vicca, Manuela Balzarolo (Global Change Excellence Centre, Research Group Plant Ecology) and their international colleagues investigated the performance of multiple satellite indicators to detect the effects of strong drought on GPP. Drought periods will increase in severity in the near future due to climate change, but how this could affect large scale photosynthesis in forest and grassland ecosystems, remains difficult to predict. Satellite data have great potential to improve our knowledge about drought responses, but they have yet to demonstrate their ability to capture drought effects on photosynthesis.
Sara: “While plant activity and photosynthesis in forests can be strongly reduced in response to drought, drought often does not immediately cause leaf browning or defoliation. Usually the latter visual ecosystem characteristics are at the base of the satellite indicator variability. As a result, short-term variability in photosynthesis during drought is difficult to assess using remote sensing. This can compromise our estimates of forest photosynthesis and growth in dry periods.”
In their detailed study, Sara and Manuela now show that one particular indicator, the “Photochemical Reflectance Index” (PRI), is particularly good at estimating drought effects that do not directly affect forest browning and defoliation. This is due to the fact that rather than a visual variable, the PRI directly measures xanthophyll cycle activity. Xanthophyll can be activated by the plant to protect against strong light. They adjust the energy distribution at leaf level and provide an indication of photosynthetic light use efficiency. In other words, instead of being indicative of green biomass, PRI is indicative of the physiology in the leaves.
Sara: “The results improve our capability to assess large scale effects of severe drought on ecosystem carbon balances. This is particularly important for forests, where visual indicators do often not directly change with drought. By directly assessing a process, we can now detect previously invisible changes. Our study also shows that this is less important for grasslands: here browning usually coincides immediately with drought.”
The results were published in the multidisciplinary journal Scientific Reports.
Multiple remote sensing signals, including PRI, were correlated to gross primary production (GPP), here for a beech forest in Hesse (France). While MODIS’ GPP product (modGPP) did not capture the considerable drought effect that was observed in the field from 2003 until 2006, sPRIn (PRI normalized for absorbed light) did detect this drought effect.