Brandt M., Wigneron J.-P., Chave J., Tagesson T., Penuelas J., Ciais P., Rasmussen K., Tian F., Mbow C., Al-Yaari A., Rodriguez-Fernandez N., Schurgers G., Zhang W., Chang J., Kerr Y., Verger A., Tucker C., Mialon A., Rasmussen L.V., Fan L., Fensholt R. (2018) Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands. Nature Ecology and Evolution. : 1-9.EnllaçDoi: 10.1038/s41559-018-0530-6
The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was −0.05 petagrams of C per year (Pg C yr−1) associated with drying trends, and a net change of −0.02 Pg C yr−1 was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, −0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area. © 2018 The Author(s)
Schauman S., Verger A., Filella I., Peñuelas J. (2018) Characterisation of functional-trait dynamics at high spatial resolution in a mediterranean forest from sentinel-2 and ground-truth data. Remote Sensing. 10: 0-0.EnllaçDoi: 10.3390/rs10121874
The characterisation of functional-trait dynamics of vegetation from remotely sensed data complements the structural characterisation of ecosystems. In this study we characterised for the first time the spatial heterogeneity of the intra-annual dynamics of the fraction of absorbed photosynthetically active radiation (FAPAR) as a functional trait of the vegetation in Prades Mediterranean forest in Catalonia, Spain. FAPAR was derived from the Multispectral Instrument (MSI) on the Sentinel-2 satellite and validated by comparison with the ground measurements acquired in June 2017 at the annual peak of vegetation activity. The validation results showed that most of points were distributed along the 1:1 line, with no bias nor scattering: R2 = 0.93, p < 0.05; with a root mean square error of 0.03 FAPAR (4.3%). We classified the study area into nine vegetation groups with different dynamics of FAPAR using a methodology that is objective and repeatable over time. This functional classification based on the annual magnitude (FAPAR-M) and the seasonality (FAPAR-CV) from the data on one year (2016-2017) complements structural classifications. The internal heterogeneity of the FAPAR dynamics in each land-cover type is attributed to the environmental and to the specific species composition variability. A spatial autoregressive (SAR) model for the main type of land cover, evergreen holm oak forest (Quercus ilex), indicated that topographic aspect, slope, height, and the topographic aspect x slope interaction accounted for most of the spatial heterogeneity of the functional trait FAPAR-M, thus improving our understanding of the explanatory factors of the annual absorption of photosynthetically active radiation by the vegetation canopy for this ecosystem. © 2018 by the authors.
Fernández-Martínez M., Vicca S., Janssens I.A., Ciais P., Obersteiner M., Bartrons M., Sardans J., Verger A., Canadell J.G., Chevallier F., Wang X., Bernhofer C., Curtis P.S., Gianelle D., Grünwald T., Heinesch B., Ibrom A., Knohl A., Laurila T., Law B.E., Limousin J.M., Longdoz B., Loustau D., Mammarella I., Matteucci G., Monson R.K., Montagnani L., Moors E.J., Munger J.W., Papale D., Piao S.L., Peñuelas J. (2017) Atmospheric deposition, CO2, and change in the land carbon sink. Scientific Reports. 7: 0-0.EnllaçDoi: 10.1038/s41598-017-08755-8
Concentrations of atmospheric carbon dioxide (CO2) have continued to increase whereas atmospheric deposition of sulphur and nitrogen has declined in Europe and the USA during recent decades. Using time series of flux observations from 23 forests distributed throughout Europe and the USA, and generalised mixed models, we found that forest-level net ecosystem production and gross primary production have increased by 1% annually from 1995 to 2011. Statistical models indicated that increasing atmospheric CO2 was the most important factor driving the increasing strength of carbon sinks in these forests. We also found that the reduction of sulphur deposition in Europe and the USA lead to higher recovery in ecosystem respiration than in gross primary production, thus limiting the increase of carbon sequestration. By contrast, trends in climate and nitrogen deposition did not significantly contribute to changing carbon fluxes during the studied period. Our findings support the hypothesis of a general CO2-fertilization effect on vegetation growth and suggest that, so far unknown, sulphur deposition plays a significant role in the carbon balance of forests in industrialized regions. Our results show the need to include the effects of changing atmospheric composition, beyond CO2, to assess future dynamics of carbon-climate feedbacks not currently considered in earth system/climate modelling. © 2017 The Author(s).
Verger A., Filella I., Baret F., Peñuelas J. (2016) Vegetation baseline phenology from kilometric global LAI satellite products. Remote Sensing of Environment. 178: 1-14.EnllaçDoi: 10.1016/j.rse.2016.02.057
Land surface phenology derived from remotely sensed satellite data can substantially improve our macroecological knowledge and the representation of phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from the GEOCLIM climatology of leaf area index (LAI) estimated from 1-km SPOT-VEGETATION time series for 1999-2010. The phenological metrics were calibrated over an ensemble of ground observations of the timing of leaf unfolding and autumnal colouring of leaves. The start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests over Europe (and lilac shrubs over North America), improved as compared to those derived from MODIS-EVI and produced an overall root mean square error of 7 days (19 days) for the timing of the start of season, 15 for the end of season, and 16 for the length of season. The spatial patterns of the derived LAI phenology agreed well with those from MODIS-EVI and -NDVI, although the timing of the start, end, and length of season differed by about one month at the global scale, with higher uncertainties in areas of limited seasonality of the satellite signal and systematic biases due to the differences in the methodologies and datasets. The baseline LAI phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. © 2016 Elsevier Inc.
Vicca S., Balzarolo M., Filella I., Granier A., Herbst M., Knohl A., Longdoz B., Mund M., Nagy Z., Pintér K., Rambal S., Verbesselt J., Verger A., Zeileis A., Zhang C., Peñuelas J. (2016) Remotely-sensed detection of effects of extreme droughts on gross primary production. Scientific Reports. 6: 0-0.EnllaçDoi: 10.1038/srep28269
Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.
Verger A., Baret F., Weiss M., Filella I., Penuelas J. (2015) GEOCLIM: A global climatology of LAI, FAPAR, and FCOVER from VEGETATION observations for 1999-2010. Remote Sensing of Environment. 166: 126-137.EnllaçDoi: 10.1016/j.rse.2015.05.027
Land-surface modelling would benefit significantly from improved characterisation of the seasonal variability of vegetation at a global scale. GEOCLIM, a global climatology of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR)-both essential climate variables-and fraction of vegetation cover (FCOVER), is here derived from observations from the SPOT VEGETATION programme. Interannual average values from the GEOV1 Copernicus Global Land time series of biophysical products at 1-km resolution and 10-day frequency are computed for 1999 to 2010. GEOCLIM provides the baseline characteristics of the seasonal cycle of the annual vegetation phenology for each 1-km. pixel on the globe. The associated standard deviation characterises the interannual variability. Temporal consistency and continuity is achieved by the accumulation of multi-year observations and the application of techniques for temporal smoothing and gap filling. Specific corrections are applied over cloudy tropical regions and high latitudes in the Northern Hemisphere where the low number of available observations compromises the reliability of estimates. Artefacts over evergreen broadleaf forests and areas of bare soil are corrected based on the expected limited seasonality. The GEOCLIM data set is demonstrated to be consistent, both spatially and temporally. GEOCLIM shows absolute differences lower than 0.5 compared with MODIS (GIMMS3g) climatology of LAI for more than 80% (90%) of land pixels, with higher discrepancies in tropical and boreal latitudes. ECOCLIMAP systematically produces higher LAI values. The phenological metric for the date of maximum foliar development derived from GEOCLIM is spatially consistent (correlation higher than 0.9) with those of MODIS, GIMMS3g, ECOCLIMAP and MCD12Q2 with average differences within 14. days at the global scale. © 2015 Elsevier Inc.
Garbulsky M.F., Filella I., Verger A., Penuelas J. (2014) Photosynthetic light use efficiency from satellite sensors: From global to Mediterranean vegetation. Environmental and Experimental Botany. 103: 3-11.EnllaçDoi: 10.1016/j.envexpbot.2013.10.009
Recent advances in remote-sensing techniques for light use efficiency (LUE) are providing new possibilities for monitoring carbon uptake by terrestrial vegetation (gross primary production, GPP), in particular for Mediterranean vegetation types. This article reviews the state of the art of two of the most promising approaches for remotely estimating LUE: the use of the photochemical reflectance index (PRI) and the exploitation of the passive chlorophyll fluorescence signal. The theoretical and technical issues that remain before these methods can be implemented for the operational global production of LUE from forthcoming hyperspectral satellite data are identified for future research. © 2013 Elsevier B.V.
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