ALBERT

Description: According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) roughly contributes with a quarter (~ 10–12 PgCO2e.yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice and livestock. In spite of the importance of this sector, it is unclear where are the regions in the planet with AFOLU emissions hotspots, and how uncertain these emissions are. Here we present a novel spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°), for the tropics, for the period 2000–2005. Our data highlight: i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (75 %) and to their uncertainties (98 %), iii) higher gross fluxes from forests coincide with higher uncertainties, making agricultural hotspots more appealing for effective mitigation action, and iv) a lower contribution of non-CO2 agricultural emissions to the total gross budget (ca. 25 %) with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions 8.2 (5.5–12.2) were in the range of other databases 8.4 and 8.0 PgCO2e.yr−1 (FAOSTAT and EDGAR respectively), but we offer a spatially detailed benchmark for monitoring progress on reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties, will assist national policy makers, investors and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

Description: The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000–2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU “Hotspots”, “Houghton”, “Baccini”, and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5–12.2), 8.4, and 8.0 Pg CO2 eq. yr−1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8–10), 5.9, 5.9, and 5.4 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5–2.5), 2.5, 2.1, and 2.0 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

Description: The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates remain, however, highly uncertain, jeopardizing the mitigation effectiveness of this sector. Global comparisons of AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding on the reasons behind these differences. Here we compare a diversity of AFOLU emission datasets (e.g. FAOSTAT, EDGAR, the newly developed AFOLU "Hotspots", "Houghton", "Baccini", and EPA) and estimates given in the Fifth Assessment Report, for the tropics (2000–2005), to identify plausible explanations for the differences in: i) aggregated gross AFOLU emissions, and ii) disaggregated emissions by sources, and by gases (CO2, CH4, N2O). We also aim to iii) identify countries with low agreement among AFOLU datasets, to navigate research efforts. Aggregated gross emissions were similar for all databases for the AFOLU: 8.2 (5.5–12.2), 8.4 and 8.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT and EDGAR respectively), Forests: 6.0 (3.8–10), 5.9, 5.9 and 5.4 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and Agricultural sectors: 1.9 (1.5–2.5), 2.0, 2.1, and 2.0 Pg CO2e. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating by sources, continents, and gases, particularly for the forest sector (fire leading the differences). Agricultural emissions were more homogeneous, especially livestock, while croplands were the most diverse. CO2 showed the largest differences among datasets. Cropland soils and enteric fermentation led the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (e.g. carbon-only vs multi-gas assessments, definitions, land use versus land cover, etc), in methods (Tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc) and in assumptions (e.g. carbon neutrality of certain emissions, instantaneous emissions release, etc) that call for more complete and transparent documentation for all the available datasets. Enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

Description: According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) contributes roughly a quarter ( ∼  10–12 Pg CO2e yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice, and livestock. In spite of the importance of this sector, it is unclear where the regions with hotspots of AFOLU emissions are and how uncertain these emissions are. Here we present a novel, spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°) for the tropics for the period 2000–2005. Our data highlight the following: (i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; (ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (69 %) and to their uncertainties (98 %); (iii) higher gross fluxes from forests, which coincide with higher uncertainties, making agricultural hotspots appealing for effective mitigation action; and (iv) a lower contribution of non-CO2 agricultural emissions to the total gross emissions (ca. 25 %), with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions of 8.0 (5.5–12.2) were in the range of other databases (8.4 and 8.0 Pg CO2e yr−1 in FAOSTAT and the Emissions Database for Global Atmospheric Research (EDGAR) respectively), but we offer a spatially detailed benchmark for monitoring progress in reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties will assist national policy makers, investors, and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.

Description: Conversion of natural forest to other land uses could lead to significant changes in catchment hydrology, but the nature of these changes has been insufficiently investigated in tropical montane catchments, especially in Africa. To address this knowledge gap, we identified stream water sources and flow paths in three tropical montane sub-catchments (27–36 km2) with different land use (natural forest, smallholder agriculture and commercial tea plantations) within a 1 021 km2 catchment in the Mau Forest Complex, Kenya. Weekly samples were collected from stream water, precipitation and soil water for 75 weeks and analysed for stable water isotopes (δ2H and δ18O) for mean transit time estimation, whereas trace element samples from stream water and potential end members were collected over a period of 55 weeks for end member mixing analysis. Stream water mean transit time was similar (~ 4 years) in the three sub-catchments, and ranged from 3.2–3.3 weeks in forest soils and 4.5–7.9 weeks in pasture soils at 15 cm depth to 10.4–10.8 weeks in pasture soils at 50 cm depth. The contribution of springs and wetlands to stream discharge increased from 18, 1 and 48 % during low flow to 22, 51 and 65 % during high flow in the natural forest, smallholder agriculture and tea plantation sub-catchments, respectively. The dominant stream water source in the tea plantation sub-catchment was spring water (56 %), while precipitation was dominant in the smallholder agriculture (59 %) and natural forest (45 %) sub-catchments. These results confirm that catchment hydrology is strongly influenced by land use, which could have serious consequences for water-related ecosystem services, such as provision of clean water.

Description: Conversion of natural forest (NF) to other land uses could lead to significant changes in catchment hydrology, but the nature of these changes has been insufficiently investigated in tropical montane catchments, especially in Africa. To address this knowledge gap, we aimed to identify stream water (RV) sources and flow paths in three tropical montane sub-catchments (27–36 km2) with different land use (natural forest, NF; smallholder agriculture, SHA; and commercial tea and tree plantations, TTP) within a 1021 km2 catchment in the Mau Forest complex, Kenya. Weekly samples were collected from stream water, precipitation (PC) and mobile soil water for 75 weeks and analysed for stable isotopes of water (δ2H and δ18O) for mean transit time (MTT) estimation with two lumped parameter models (gamma model, GM; and exponential piston flow model, EPM) and for the calculation of the young water fraction. Weekly samples from stream water and potential endmembers were collected over a period of 55 weeks and analysed for Li, Na, Mg, K, Rb, Sr and Ba for endmember mixing analysis (EMMA). Solute concentrations in precipitation were lower than in stream water in all catchments (p 

Description: Agricultural catchments in the tropics often generate high concentrations of suspended sediments following the conversion of natural ecosystems. The eroded fine particles are generally enriched with carbon (TC) and nutrients (TN and TP) originating from the topsoil of agricultural land. Sediment-associated TC, TN and TP are an important loss to the terrestrial ecosystem and tightly connected to an increase in riverine particulate TC and nutrient export. Soil nutrient depletion can limit crop growth and yields, whereas an excess of nutrients in streams can cause eutrophication in freshwater systems. Streams in East Africa, with widespread land conversion from forests to agriculture, are expected to receive high loads of sediment-associated TC, TN and TP. In this study, we assess the effect of land use on particulate TC, TN and TP concentrations. Suspended sediments (time-integrated, manual-event-based and automatic-event-based sediment samples) were analysed for TC, TN and TP concentrations collected at the outlet of a natural montane forest (35.9), a tea-tree plantation (33.3) and a smallholder agriculture (27.2 km2) catchment in western Kenya during a wet sampling period in 2018 and a drier sampling period in 2019. Particulate TC, TN and TP concentrations were up to 3-fold higher (p