Éditeur(s) : Elsevier
Résumé : The distribution and speciation of mercury (Hg) in air, rain, and surface waters from the artificial tropical lake of Petit-Saut in French Guiana were investigated during the 2003/04 period. In the air, total gaseous mercury (TGM) at the dam station averaged 12 +/- 2 pmol m(-3) of which > 98% was gaseous elemental mercury (GEM). GEM distribution depicted a day-night cycling with high concentrations (up to 15 pmol m(-3)) at dawn and low concentrations (down to 5 pmol m(-3)) at nightfall. Reactive gaseous mercury (RGM) represented < 1% of the GEM with a mean concentration of 4 3 fmol m(-3). Diel RGM variations were negatively related to GEM. In the rain, the sum of all Hg species in the unfiltered (HgTUNF) averaged 16 +/- 112 pmol L-1. Temporal distribution of HgTUNF exhibited a pattern of high concentrations during the late dry seasons (up to 57.5 pmol L-1) and low concentrations (down to 2.7 pmol L-1) in the course of the wet seasons. Unfiltered reactive (HgRUNF), dissolved gaseous (DGM) and monomethyl (MMHgUNF.) Hg constituted 20, 5 and 5% of HgTUNF, respectively. All measured Hg species were positively related and displayed negative relationships with the pH of the rain. In the reservoir surface waters, dissolved total mercury (HgTD) averaged 3.4 +/- 1.2 pmol L-1 of which 10% consisted of DGM. DGM showed a trend of high concentrations during the dry seasons (480 +/- 270 finol L-1 and lower (230 +/- 130 finol L-1) in the course of the wet seasons. Diel variations included diurnal photo-induced DGM production (of about 60 firiol L-1 h(-1)) coupled to minute to hour oxidation/ reduction cycles (of > 100 firiol L-1 amplitude). Finally, calculated atmospheric Hg inputs to the Petit-Saut reservoir represented 14 mot yr(-1) whereas DGM evasion reached 23 mol yr(-1). Apportionment among forms of Hg deposition indicated that up to 75% of the total Hg invasive flux follows the rainfall pathway. (C) 2007 Elsevier B.V. All rights reserved.
Science of The Total Environment (0048-9697) (Elsevier), 2007-10 , Vol. 385 , N. 1-3 , P. 132-145

Droits : 2007 Elsevier B.V. All rights reserved
http://archimer.ifremer.fr/doc/2007/publication-3329.pdf
DOI:10.1016/j.scitotenv.2007.06.013
http://archimer.ifremer.fr/doc/00000/3329/

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 Elsevier
Résumé : absent
ISSN: 0034-4257

hal-01019844
https://hal.archives-ouvertes.fr/hal-01019844
DOI : 10.1016/j.rse.2012.03.012