• Energy Research

The characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. Here we present the most detailed and rigorous national-scale assessment of aboveground woody biomass carbon stocks and dynamics for Kenya to date. A non-parametric random forest algorithm was trained to retrieve aboveground woody biomass carbon (AGBC) for the year 2014 ± 1 and forest disturbances for the 2014–2017 period using in situ forest inventory plot data and satellite Earth Observation (EO) data. The ecosystem carbon cycling of Kenya’s forests and wooded grassland were assessed using a model-data fusion framework, CARDAMOM, constrained by the woody biomass datasets from this study as well as time series information on leaf area, fire events and soil organic carbon. Our EO-derived AGBC stocks were estimated as 140 Mt C for forests and 199 Mt C for wooded grasslands. The total AGBC loss during the study period was estimated as 1.89 Mt C with a dispersion below 1%. The CARDAMOM analysis estimated woody productivity to be three times larger in forests (mean = 1.9 t C ha−1 yr−1) than wooded grasslands (0.6 t C ha−1 yr−1), and the mean residence time of woody C in forests (16 years) to be greater than in wooded grasslands (10 years). This study stresses the importance of carbon sequestration by forests in the international climate mitigation efforts under the Paris Agreement, but emphasizes the need to include non-forest ecosystems such as wooded grasslands in international greenhouse gas accounting frameworks.

AbstractQuantifying landscape‐scale methane (CH4) fluxes from boreal and arctic regions, and determining how they are controlled, is critical for predicting the magnitude of any CH4 emission feedback to climate change. Furthermore, there remains uncertainty regarding the relative importance of small areas of strong methanogenic activity, vs. larger areas with net CH4 uptake, in controlling landscape‐level fluxes. We measured CH4 fluxes from multiple microtopographical subunits (sedge‐dominated lawns, interhummocks and hummocks) within an aapa mire in subarctic Finland, as well as in drier ecosystems present in the wider landscape, lichen heath and mountain birch forest. An intercomparison was carried out between fluxes measured using static chambers, up‐scaled using a high‐resolution landcover map derived from aerial photography and eddy covariance. Strong agreement was observed between the two methodologies, with emission rates greatest in lawns. CH4 fluxes from lawns were strongly related to seasonal fluctuations in temperature, but their floating nature meant that water‐table depth was not a key factor in controlling CH4 release. In contrast, chamber measurements identified net CH4 uptake in birch forest soils. An intercomparison between the aerial photography and satellite remote sensing demonstrated that quantifying the distribution of the key CH4 emitting and consuming plant communities was possible from satellite, allowing fluxes to be scaled up to a 100 km2 area. For the full growing season (May to October), ~ 1.1–1.4 g CH4 m−2 was released across the 100 km2 area. This was based on up‐scaled lawn emissions of 1.2–1.5 g CH4 m−2, vs. an up‐scaled uptake of 0.07–0.15 g CH4 m−2 by the wider landscape. Given the strong temperature sensitivity of the dominant lawn fluxes, and the fact that lawns are unlikely to dry out, climate warming may substantially increase CH4 emissions in northern Finland, and in aapa mire regions in general.

The European Space Agency (ESA) released a Call for Proposals for the next Earth Explorer Core Mission in March 2005, with the aim to select the 7th Earth Explorer (EE-7) mission for launch in the next decade. Twenty-four proposals were received and subject to scientific and technical assessment. Six candidate missions were selected and further investigated in the preliminary feasibility studies (Phase 0). One of these missions is BIOMASS, which has recently been selected to proceed to Phase-A. BIOMASS is a response to the urgent need for greatly improved mapping of global biomass and the lack of any current space systems capable of addressing this need.

Leaf area index (LAI) is an emergent property of vascular plants closely linked to primary production and surface energy balance. LAI can vary by an order of magnitude among Arctic tundra communities and is closely associated with plant functional type. We examined topographic controls on vegetation type and LAI distribution at two different scales in an Arctic tundra ecosystem in northern Sweden. `Micro-scale' measurements were made at 0.2-m resolution over a 40 m × 40 m domain, while `macro-scale' data were collected at approximately 10-m resolution over a 500 m × 500 m domain. Tundra LAI varied from 0.1-3.6 at the micro-scale resolution, and from 0.1-1.6 at the macro-scale resolution. The correlation between dominant vascular species and LAI at the micro-scale (r2 = 0.40) was greater than the correlation between dominant vegetation and LAI at the macro-scale (r2 = 0.14). At the macro-scale, LAI was better explained by topographic parameters and spatial auto-correlation (pseudo r2 = 0.32) than it was at the micro-scale (r2 = 0.16). Exposure and elevation were significantly but weakly correlated with LAI at the micro-scale, while on the macro-scale the most significant explanatory topographic variable was elevation (r2 = 0.12). The distribution of plant communities at both scales was significantly associated with topography. Shrub communities, dominated by Betula nana, were associated with low elevation sites at both scales, while more exposed and/or high elevation sites were dominated by cryptogams. Synthesis. Dominant vegetation, topography and LAI were linked at both scales of investigation but, for explaining LAI, topography became more important and dominant vegetation less important at the coarser scale. The explanatory power of dominant species/functional type for LAI variation was weaker at coarser scales, because communities often contained more than one functional type at 10 m resolution. The data suggest that remotely sensed topography can be combined with remotely sensed optical measurements to generate a useful tool for LAI mapping in Arctic environments.

AbstractArctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub‐Arctic tundra are leaf area index (LT) and total foliar nitrogen (NT). LT and NT have been shown to be tightly coupled across PFTs in sub‐Arctic tundra vegetation, which simplifies up‐scaling by allowing quantification of the main drivers of P from remotely sensed LT. Our objective was to test the LT–NT relationship across multiple Arctic latitudes and to assess LT as a predictor of P for the pan‐Arctic. Including PFT‐specific parameters in models of LT–NT coupling provided only incremental improvements in model fit, but significant improvements were gained from including site‐specific parameters. The degree of curvature in the LT–NT relationship, controlled by a fitted canopy nitrogen extinction co‐efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (NM), and we show for the first time that LT–NT coupling is achieved across latitudes via canopy‐scale trade‐offs between NM and leaf mass per unit leaf area (LM). Site‐specific parameters provided small but significant improvements in models of P based on LT and moss cover. Our results suggest that differences in LT–NT coupling between sites could be used to improve pan‐Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.

12 páginas.- 7 figuras.- 3 tablas.- referencias Under climate change, severe and recurrent droughts can reduce forest production and cause widespread tree dieback. The response of different vegetation types to climate change can vary greatly and, therefore, must be individually assessed. This study was carried out in a Mediterranean oak forest (Quercus pyrenaica) subject to seasonal summer drought. To examine the response of the forest to the climate conditions predicted under climate change, a Soil–Vegetation–Atmosphere Transfer model [SPA, Williams, M., Rastetter, E.B., Fernandes, D.N., Goulden, M.L., Wofsy, S.C., Shaver, G.R., Melillo, J.M., Munger, J.W., Fan, S.M., Nadelhoffer, K.J. 1996. Modelling the soil-plant-atmosphere continuum in a Quercus–Acer stand at Harvard Forest: the regulation of stomatal conductance by light, nitrogen and soil/plant hydraulic properties. Plant, Cell, Environment 19, 911–927] was used. The model was parameterized using mostly local measurements (independent of the verification data) and tested against in situ sap flow measurements obtained during year 2007. The predictions of the model were broadly consistent with the observed dynamics of sap flow (the model explained 71% of the variance in daily transpiration and 75% of half-hourly sap flow), leaf water potentials and soil water content. Once the model had been validated, simulations were carried out under warmer and dryer conditions. Predicted warmer conditions (4 °C) caused a moderate increase in total simulated transpiration. Less frequent precipitation (40% longer dry periods between rainfall events) had very little effect on transpiration. In contrast, transpiration was reduced by 17% when the soil water reserves at the beginning of the summer were lower than in 2007, corresponding to those measured in a very dry year (2005). The reduction was exacerbated when changes in temperature and rainfall were also considered (up to 28% decline in transpiration). The higher atmospheric CO2 concentrations (712 ppm) simulated together with climate change, did not prevent the decline in tree water use or soil water storage at the end of the summer. All scenarios caused the soil water storage to reach extremely low values at the end of the dry season (a minimum of 25 mm). It is concluded that climate change is likely to have a negative impact on tree water use and soil water resources in the study area, increasing the water deficit by as much as 30%. This study was fully supported by the Spanish Ministry of Science and Technology (REN2003-00381 Project) and the Spanish Ministry of Environment (RESEL Project). We thank Carlos Morán and Ana Cano for their assistance in fieldwork and Dr. Rodrigo Figueira for his helpful suggestions on an earlier version of the manuscript. Peer reviewed