ALBERT

Description: Forests play a crucial role by regulating the global and local weather through the exchange of atmospheric gases and water vapor. The present study aims to study the intra-annual variability of net ecosystem exchange (NEE) of carbon dioxide in a sal (Shorea robusta) dominated moist deciduous forest in India by integrating eddy covariance (EC) data and Biome-Biogeochemical Cycle (Biome-BGC) model. The study also attempts to address the spatial variability of NEE with respect to phenology. Monthly average NEE were estimated using a calibrated Biome-BGC model and the spatial NEE was mapped using random forest (RF) regression algorithm. Phenology metrics were generated using the moderate resolution imaging spectrometer (MODIS) enhanced vegetation index product (MOD13A2) and its relationship with the estimated NEE was studied. RF regression model for monthly average spatial NEE estimation was built with an R2 of 0.84 and % RMSE of 3.68%. The study revealed that the NEE at the regional scale can be estimated using the basic meteorological variables like mean temperature, vapor pressure deficit, minimum temperature and total precipitation. Biome-BGC model output showed that the sal forest of the study area acted as a net sink of carbon in almost all months of 2015, except April to June. Peak NEE value (− 2.80 to − 2.96 g C m−2 day−1) was observed during October month. Annual NEE of sal forest in 2015 was found to be − 526.87 g C m−2 year−1. With the start of season (end of June), sal forest showed an increasing trend in NEE while decreasing trend was observed at the end of season (end of October). The study showed the applicability of Biome-BGC model in Indian forest when integrated with EC data. The study also highlighted the utility of RF in capturing the spatial variability of NEE over large area.

Description: Temperature and salinity reconstructions for two 1000-year high-resolution sedimentary records, located at the boundary between Atlantic and Arctic surface waters on the North Icelandic shelf, are based on transfer functions and oxygen isotopes for planktonic and benthic foraminifera. There is a general increase of Arctic Water indicator species at the transition from the Medieval Warm Period into the Little Ice Age (LIA) and a subsequent return of Atlantic Water indicator species towards the end of the LIA and in the 20th century. The timing of the reconstructed temperature changes, both at the beginning and at the end of the LIA, appears to be slightly different for the different water masses. The earliest temperature change is seen in the bottom and subsurface waters, where a cooling is reconstructed as early as AD 1150-1200 at both locations, whereas previously published diatom-based and alkenone-based sea-surface temperature reconstructions show a change at AD 1300, coinciding with the air temperature shift in the area. Our results show the need of a thorough understanding of the oceanography in the study area, as well as the different living habitat for the biological proxies used for the temperature estimates.

Description: Planktic and benthic foraminifera 14C measurements, published in Rafter et al. (2019) in GRL. These are a companion dataset to the benthic foraminifera 14C measurements published by Rafter et al. (2018) in Climate of the Past.

Description: This dataset contains the collection of published Uk'37, Uk37 and Mg/Ca records spanning the mid-to late Holocene and used in the analyses of Laepple&Huybers, EPSL 2014 and Laepple&Huybers, PNAS 2014. It is largely based on Leduc et al. (2010).