Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
The exchanges of carbon, water and energy between the atmosphere and the Amazon basin have global implications for the current and future climate. Here, the global atmospheric inversion system of the Monitoring of Atmospheric Composition and Climate (MACC) service is used to study the seasonal and interannual variations of biogenic CO 2 fluxes in Amazonia during the period 2002–2010. The system assimilated surface measurements of atmospheric CO 2 mole fractions made at more than 100 sites over the globe into an atmospheric transport model. The present study adds measurements from four surface stations located in tropical South America, a region poorly covered by CO 2 observations. The estimates of net ecosystem exchange (NEE) optimized by the inversion are compared to an independent estimate of NEE upscaled from eddy-covariance flux measurements in Amazonia. They are also qualitatively evaluated against reports on the seasonal and interannual variations of the land sink in South America from the scientific literature. We attempt at assessing the impact on NEE of the strong droughts in 2005 and 2010 (due to severe and longer-than-usual dry seasons) and the extreme rainfall conditions registered in 2009. The spatial variations of the seasonal and in-terannual variability of optimized NEE are also investigated. While the inversion supports the assumption of strong spatial heterogeneity of these variations, the results reveal critical limitations of the coarse-resolution transport model, the surface observation network in South America during the recent years and the present knowledge of modelling uncertainties in South America that prevent our inversion from capturing the seasonal patterns of fluxes across Amazonia. However, some patterns from the inversion seem consistent with the anomaly of moisture conditions in 2009.
ISSN: 1680-7316

hal-01557375
https://hal.univ-lorraine.fr/hal-01557375
https://hal.univ-lorraine.fr/hal-01557375/document
https://hal.univ-lorraine.fr/hal-01557375/file/acp-15-8423-2015.pdf
DOI : 10.5194/acp-15-8423-2015-supplement

Éditeur(s) : HAL CCSD Elsevier
Résumé : Vegetation phenology is the study of the timing of seasonal events that are considered to be the result of adaptive responses to climate variations on short and long time scales. In the field of remote sensing of vegetation phenology, phenological metrics are derived from time series of optical data. For that purpose, considerable effort has been specifically focused on developing noise reduction and cloud-contaminated data removal techniques to improve the quality of remotely-sensed time series. Comparative studies between time series composed of satellite data acquired under clear and cloudy conditions and from radiometric data obtained with high accuracy from ground-based measurements constitute a direct and effective way to assess the operational use and limitations of remote sensing for predicting the main plant phenological events. In the present paper, we sought to explicitly evaluate the potential use of MODerate resolution Imaging Spectroradiometer (MODIS) remote sensing data for monitoring the seasonal dynamics of different types of vegetation cover that are representative of the major terrestrial biomes, including temperate deciduous forests, evergreen forests, African savannah, and crops. After cloud screening and filtering, we compared the temporal patterns and phenological metrics derived from in situ NDVI time series and from MODIS daily and 16-composite products. We also evaluated the effects of residual noise and the influence of data gaps in MODIS NDVI time series on the identification of the most relevant metrics for vegetation phenology monitoring. The results show that the inflexion points of a model fitted to a MODIS NDVI time series allow accurate estimates of the onset of greenness in the spring and the onset of yellowing in the autumn in deciduous forests (RMSE <= one week). Phenological metrics identical to those provided with the MODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately two weeks or more during the autumn phenological transitions. In the evergreen forests, in situ NDVI time series describe the phenology with high fidelity despite small temporal changes in the canopy foliage. However, MODIS is unable to provide consistent phenological patterns. In crops and savannah, MODIS NDVI time series reproduce the general temporal patterns of phenology, but significant discrepancies appear between MODIS and ground-based NDVI time series during very localized periods of time depending on the weather conditions and spatial heterogeneity within the MODIS pixel. In the rainforest, the temporal pattern exhibited by a MODIS 16-day composite NDVI time series is more likely due to a pattern of noise in the NDVI data structure according to both rainy and dry seasons rather than to phenological changes. More investigations are needed, but in all cases, this result leads us to conclude that MODIS time series in tropical rainforests should be interpreted with great caution. (C) 2013 Elsevier Inc. All rights reserved.
ISSN: 0034-4257

hal-01032407
https://hal.archives-ouvertes.fr/hal-01032407
DOI : 10.1016/j.rse.2013.01.010

Éditeur(s) : HAL CCSD Wiley
Résumé : Understanding the mechanisms generating species distributions remains a challenge, especially in hyperdiverse tropical forests. We evaluated the role of rainfall variation, soil gradients and herbivory on seedling mortality, and how variation in seedling performance along these gradients contributes to habitat specialisation. In a 4-year experiment, replicated at the two extremes of the Amazon basin, we reciprocally transplanted 4638 tree seedlings of 41 habitat-specialist species from seven phylogenetic lineages among the three most important forest habitats of lowland Amazonia. Rainfall variation, flooding and soil gradients strongly influenced seedling mortality, whereas herbivory had negligible impact. Seedling mortality varied strongly among habitats, consistent with predictions for habitat specialists in most lineages. This suggests that seedling performance is a primary determinant of the habitat associations of adult trees across Amazonia. It further suggests that tree diversity, currently mostly harboured in terra firme forests, may be strongly impacted by the predicted climate changes in Amazonia.
ISSN: 1461-023X

hal-01531751
https://hal.archives-ouvertes.fr/hal-01531751
DOI : 10.1111/ele.12661
PRODINRA : 387284