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Consistent forest loss estimates are important to understand the role of forest loss and deforestation in the global carbon cycle, for biodiversity studies, and to estimate the mitigation potential of reducing deforestation. To date, most studies have relied on optical satellite data and new efforts have greatly improved our quantitative knowledge on forest dynamics. However, most of these studies yield results for only a relatively short time period or are limited to certain countries. We have quantified large-scale forest loss over a 21-year period (1990–2010) in the tropical biomes of South America using remotely sensed vegetation optical depth (VOD). This passive microwave satellite-based indicator of vegetation water content and vegetation density has a much coarser spatial resolution than optical data but its temporal resolution is higher and VOD is not impacted by aerosols and cloud cover. We used the merged VOD product of the Advanced Microwave Scanning Radiometer (AMSR-E) and Special Sensor Microwave Imager (SSM/I) observations, and developed a change detection algorithm to quantify spatial and temporal variations in forest loss dynamics. Our results compared reasonably well with the newly developed Landsat-based Global Forest Change (GFC) maps, available for the 2001 onwards period (r2 = 0.90 when comparing annual country-level estimates). This allowed us to convert our identified changes in VOD to forest loss area and compute these from 1990 onwards. We also compared these calibrated results to PRODES (r2 = 0.60 when comparing annual state-level estimates). We found that South American forest exhibited substantial interannual variability without a clear trend during the 1990s, but increased from 2000 until 2004. After 2004, forest loss decreased again, except for two smaller peaks in 2007 and 2010. For a large part, these trends were driven by changes in Brazil, which was responsible for 56 % of the total South American forest loss area over our study period according to our results. One of the key findings of our study is that while forest loss decreased in Brazil after 2005, increases in other countries partly offset this trend suggesting that South American forest loss as a whole decreased much less than that in Brazil.

In this study we analyzed sediment trap time series from five tropical sites to assess seasonal variations in concentrations and fluxes of long-chain diols (LCDs) and associated proxies with emphasis on the long-chain diol index (LDI) temperature proxy. For the tropical Atlantic, we observe that generally less than 2 % of LCDs settling from the water column are preserved in the sediment. The Atlantic and Mozambique Channel traps reveal minimal seasonal variations in the LDI, similar to the two other lipid-based temperature proxies TEX86 and U37K′. In addition, annual mean LDI-derived temperatures are in good agreement with the annual mean satellite-derived sea surface temperatures (SSTs). In contrast, the LDI in the Cariaco Basin shows larger seasonal variation, as do the TEX86 and U37K′. Here, the LDI underestimates SST during the warmest months, which is possibly due to summer stratification and the habitat depth of the diol producers deepening to around 20–30 m. Surface sediment LDI temperatures in the Atlantic and Mozambique Channel compare well with the average LDI-derived temperatures from the overlying sediment traps, as well as with decadal annual mean SST. Lastly, we observed large seasonal variations in the diol index, as an indicator of upwelling conditions, at three sites: in the eastern Atlantic, potentially linked to Guinea Dome upwelling; in the Cariaco Basin, likely caused by seasonal upwelling; and in the Mozambique Channel, where diol index variations may be driven by upwelling from favorable winds and/or eddy migration.

In this study we have analyzed sediment trap time series from five tropical sites to assess seasonal variations in concentrations and fluxes of long-chain diols (LCDs) and associated proxies with emphasis on the Long chain Diol Index (LDI). For the tropical Atlantic, we observe that generally less than 2 % of LCDs settling from the water column are preserved in the sediment. The Atlantic and Mozambique Channel traps reveal minimal seasonal variations in the LDI, similar to the TEX86 and UK´37. However, annual mean LDI-derived temperatures are in good agreement with the annual mean satellite-derived sea surface temperatures (SSTs). In the Cariaco Basin the LDI shows larger seasonal variation, as do the TEX86 and UK´37. Here, the LDI underestimates SST during the warmest months, which is likely due to summer stratification and the habitat depth of the diol producers deepening to around 20 to 30 m. Surface sediment LDI temperatures in the Atlantic and Mozambique Channel compare well with the average LDI-derived temperatures from the overlying sediment traps, as well as with decadal annual mean SST. Lastly, we observed large seasonal variations in the Diol Index, as indicator of upwelling conditions, at three sites, potentially linked to Guinea Dome upwelling (Eastern Atlantic), seasonal upwelling (Cariaco Basin) and seasonal upwelling and/or eddy migration (Mozambique Channel).

Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research.