References of "Rambal, Serge"
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See detailCombined effects of climate, resource availability, and plant traits on biomass produced in a Mediterranean rangeland
Chollet, Simon; Rambal, Serge; Fayolle, Adeline ULg et al

in Ecology (2014), 95(3), 737-748

Biomass production in grasslands, a key component of food provision for domestic herbivores, is known to depend on climate, resource availability, and on the functional characteristics of communities ... [more ▼]

Biomass production in grasslands, a key component of food provision for domestic herbivores, is known to depend on climate, resource availability, and on the functional characteristics of communities. However, the combined effects of these different factors remain largely unknown. The aim of the present study was to unravel the causes of variations in the standing biomass of plant communities using a long-term experiment conducted in a Mediterranean rangeland of Southern France. Two management regimes, sheep grazing and grazing associated with mineral fertilization, were applied to different areas of the study site over the past 25 years. Abiotic (temperature, available water, nutrients) and biotic (components of the functional structure communities) factors were considered to explain interannual and spatial variations in standing biomass in these rangelands. Standing biomass was highly predictable, with the best model explaining ;80% of variations in the amount of biomass produced, but the variation explained by abiotic and biotic factors was dependent on the season and on the management regime. Abiotic factors were found to have comparable effects in both management regimes: The amount of biomass produced in the spring was limited by cold temperatures, while it was limited by water availability and high temperatures in the summer. In the fertilized community, the progressive change in the functional structure of the communities had significant effects on the amount of biomass produced: the dominance of few productive species which were functionally close led to higher peak standing biomass in spring. [less ▲]

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See detailEvaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements
Hmimina, G.; Dufrêne, Eric; Pontailler, J.-Y. et al

in Remote Sensing of Environment (2013), (132), 145-158

Vegetation phenology is the st udy 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 ... [more ▼]

Vegetation phenology is the st udy 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, phenologicalmetrics are derived fromtime 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 fromradiometric data obtainedwith high accuracy fromground-basedmeasurements 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 in uence 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 in exion 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<oneweek). Phenologicalmetrics identical to those providedwith theMODIS Global Vegetation Phenology product (MDC12Q2) are less robust to data gaps, and they can be subject to large biases of approximately twoweeks 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 ismore 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. [less ▲]

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See detailClimate control of terrestrial carbon exchange across biomes and continents
Yi, Chuixiang; Ricciuto, Daniel; Li, Runze et al

in Environmental Research Letters (2010), 5(3),

Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating ... [more ▼]

Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid-and high-latitudes, (2) a strong function of dryness at mid-and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45 degrees N). The sensitivity of NEE to mean annual temperature breaks down at similar to 16 degrees C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence. [less ▲]

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See detailOn the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm
Reichstein, Markus; Falge, Eva; Baldocchi, Dennis et al

in Global Change Biology (2005), 11(9), 1424-1439

This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem ... [more ▼]

This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration (R-eco). In particular, we analyse the effect of the extrapolation of night-time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long-term data sets. For this analysis, we used 16 one-year-long data sets of carbon dioxide exchange measurements from European and US-American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of R-eco, derived from long-term (annual) data sets, does not reflect the short-term temperature sensitivity that is effective when extrapolating from night- to daytime. Specifically, in summer active ecosystems the long-term temperature sensitivity exceeds the short-term sensitivity. Thus, in those ecosystems, the application of a long-term temperature sensitivity to the extrapolation of respiration from night to day leads to a systematic overestimation of ecosystem respiration from half-hourly to annual time-scales, which can reach > 25% for an annual budget and which consequently affects estimates of GEP. Conversely, in summer passive (Mediterranean) ecosystems, the long-term temperature sensitivity is lower than the short-term temperature sensitivity resulting in underestimation of annual sums of respiration. We introduce a new generic algorithm that derives a short-term temperature sensitivity of R-eco from eddy covariance data that applies this to the extrapolation from night- to daytime, and that further performs a filling of data gaps that exploits both, the covariance between fluxes and meteorological drivers and the temporal structure of the fluxes. While this algorithm should give less biased estimates of GEP and R-eco, we discuss the remaining biases and recommend that eddy covariance measurements are still backed by ancillary flux measurements that can reduce the uncertainties inherent in the eddy covariance data. [less ▲]

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