Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ). 相似文献
Lower Palaeogene extrusive igneous rocks of the Faroe Islands Basalt Group (FIBG) dominate the Faroese continental margin, with flood basalts created at the time of breakup and separation from East Greenland extending eastwards into the Faroe‐Shetland Basin. This volcanic succession was emplaced in connection with the opening of the NE Atlantic; however, consensus on the age and duration of volcanism remains lacking. On the Faroe Islands, the FIBG comprises four main basaltic formations (the pre‐breakup Lopra and Beinisvørð formations, and the syn‐breakup Malinstindur and Enni formations) locally separated by thin intrabasaltic sedimentary and/or volcaniclastic units. Offshore, the distribution of these formations remains ambiguous. We examine the stratigraphic framework of these rocks on the Faroese continental margin combining onshore (published) outcrop information with offshore seismic‐reflection and well data. Our results indicate that on seismic‐reflection profiles, the FIBG can be informally divided into lower and upper seismic‐stratigraphic packages separated by the strongly reflective A‐horizon. The Lower FIBG comprises the Lopra and Beinisvørð formations; the upper FIBG includes the Malinstindur and Enni formations. The strongly reflecting A‐horizon is a consequence of the contrast in properties of the overlying Malinstindur and underlying Beinisvørð formations. Onshore, the A‐horizon is an erosional surface, locally cutting down into the Beinisvørð Formation; offshore, we have correlated the A‐horizon with the Flett unconformity, a highly incised, subaerial unconformity, within the juxtaposed and interbedded sedimentary fill of the Faroe‐Shetland Basin. We refer to this key regional boundary as the A‐horizon/Flett unconformity. The formation of this unconformity represents the transition from the pre‐breakup to the syn‐breakup phase of ocean margin development in the Faroe–Shetland region. We examine the wider implications of this correlation considering existing stratigraphic models for the FIBG, discussing potential sources of uncertainty in the correlation of the lower Palaeogene succession across the Faroe–Shetland region, and implications for the age and duration of the volcanism. 相似文献
碳酸盐岩风化吸收的大气CO2主要以HCO3-形式连续地经由河流从大陆输送到海洋,成为陆地生态系统的重要碳汇。目前主要河流流域的碳酸盐岩风化碳汇估算存在不确定性,分布格局尚不清晰。基于GEMS-GLORI全球河流数据库提供的全球10万km 2以上主要河流流域多年平均监测数据,利用水化学径流法估算出全球主要河流流域碳酸盐岩对CO2的吸收速率为0.43±0.15 Pg CO2 yr -1,平均CO2吸收通量为7.93±2.8 t km -2 yr -1。CO2吸收通量在不同气候带下差异显著,热带和暖温带CO2年吸收速率占全球主要河流流域年吸收速率的62.95%。冷温带CO2年吸收速率占全球主要河流流域的33.05%,仅次于热带地区。本文划分出全球CO2吸收通量的9个关键带,关键带的交汇处CO2吸收通量较高。喀斯特出露流域碳酸盐岩对CO2吸收通量的均值为8.50 t km -2 yr -1,约为非喀斯特流域的3倍。全球喀斯特出露流域碳酸盐岩风化碳汇在全球碳循环、水循环及碳收支平衡估算研究方面占据重要地位。 相似文献
We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.