Incorporating Natural Vegetation into the LUC Project Framework

A detailed description of the incorporation of natural vegetation within the larger LUC model framework is given. The approach focuses on first adapting and then coupling three existing vegetation models: BIOME3 (Haxeltine et al., 1996), BIOMEl (Prentice I.C. et al., 1992) and the CBM (Kurz W.A. et al., 1992). Section 1 concentrates on a description of the adaptations made to BIOME3 and BIOMEl and a comparison of the results obtained from a present climate run for Russia, Mongolia and China with the existing LUC natural vegetation data set. The three way model coupling methodology and usage within the larger LUC model framework is given in Section 2

Technical note: A simple theoretical model framework to describe plant stomatal "sluggishness" in response to elevated ozone concentrations

This is the final version. Available from European Geosciences Union (EGU) via the DOI in this record.Elevated levels of tropospheric ozone, O3, cause damage to terrestrial vegetation, affecting leaf stomatal functioning and reducing photosynthesis. Climatic impacts under future raised atmospheric greenhouse gas (GHG) concentrations will also impact on the net primary productivity (NPP) of vegetation, which might for instance alter viability of some crops. Together, ozone damage and climate change may adjust the current ability of terrestrial vegetation to offset a significant fraction of carbon dioxide (CO2) emissions. Climate impacts on the land surface are well studied, but arguably large-scale modelling of raised surface level O3effects is less advanced. To date most models representing ozone damage use either O3concentration or, more recently, flux-uptake-related reduction of stomatal opening, estimating suppressed land-atmosphere water and CO2fluxes. However there is evidence that, for some species, O3damage can also cause an inertial sluggishness of stomatal response to changing surface meteorological conditions. In some circumstances (e.g. droughts), this loss of stomata control can cause them to be more open than without ozone interference. To both aid model development and provide empiricists with a system on to which measurements can be mapped, we present a parameter-sparse framework specifically designed to capture sluggishness. This contains a single time-delay parameter τO3, characterizing the timescale for stomata to catch up with the level of opening they would have without damage. The larger the value of this parameter, the more sluggish the modelled stomatal response. Through variation of τO3, we find it is possible to have qualitatively similar responses to factorial experiments with and without raised O3, when comparing to reported measurement time series presented in the literature. This low-parameter approach lends itself to the inclusion of ozone-induced inertial effects being incorporated in the terrestrial vegetation component of Earth system models (ESMs).NERC-CEH National Capability FundNatural Environment Research Counci

Conversion from forests to pastures in the Colombian Amazon leads to contrasting soil carbon dynamics depending on land management practices

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordStrategies to mitigate climate change by reducing deforestation and forest degradation (e.g. REDD+) require country- or region-specific information on temporal changes in forest carbon (C) pools to develop accurate emission factors. The soil C pool is one of the most important C reservoirs, but is rarely included in national forest reference emission levels due to a lack of data. Here, we present the soil organic C (SOC) dynamics along 20 years of forest-to-pasture conversion in two subregions with different management practices during pasture establishment in the Colombian Amazon: high-grazing intensity (HG) and low-grazing intensity (LG) subregions. We determined the pattern of SOC change resulting from the conversion from forest (C3 plants) to pasture (C4 plants) by analysing total SOC stocks and the natural abundance of the stable isotopes (13) C along two 20-year chronosequences identified in each subregion. We also analysed soil N stocks and the natural abundance of (15) N during pasture establishment. In general, total SOC stocks at 30 cm depth in the forest were similar for both subregions, with an average of 47.1 ± 1.8 Mg C ha(-1) in HG and 48.7 ± 3.1 Mg C ha(-1) in LG. However, 20 years after forest-to-pasture conversion SOC in HG decreased by 20%, whereas in LG SOC increased by 41%. This net SOC decrease in HG was due to a larger reduction in C3-derived input and to a comparatively smaller increase in C4-derived C input. In LG both C3- and C4-derived C input increased along the chronosequence. N stocks were generally similar in both subregions and soil N stock changes during pasture establishment were correlated with SOC changes. These results emphasize the importance of management practices involving low-grazing intensity in cattle activities to preserve SOC stocks and to reduce C emissions after land-cover change from forest to pasture in the Colombian Amazon.This study was funded by AXA Research Fund (2012‐Doc‐University‐of‐Exeter‐NAVARRETE‐D)

Conversion from forests to pastures in the Colombian Amazon leads to differences in dead wood dynamics depending on land management practices

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordDead wood, composed of coarse standing and fallen woody debris (CWD), is an important carbon (C) pool in tropical forests and its accounting is needed to reduce uncertainties within the strategies to mitigate climate change by reducing deforestation and forest degradation (REDD+). To date, information on CWD stocks in tropical forests is scarce and effects of land-cover conversion and land management practices on CWD dynamics remain largely unexplored. Here we present estimates on CWD stocks in primary forests in the Colombian Amazon and their dynamics along 20 years of forest-to-pasture conversion in two sub-regions with different management practices during pasture establishment: high-grazing intensity (HG) and low-grazing intensity (LG) sub-regions. Two 20-year-old chronosequences describing the forest-to-pasture conversion were identified in both sub-regions. The line-intersect and the plot-based methods were used to estimate fallen and standing CWD stocks, respectively. Total necromass in primary forests was similar between both sub-regions (35.6 ± 5.8 Mg ha(-1) in HG and 37.0 ± 7.4 Mg ha(-1) in LG). An increase of ∼124% in CWD stocks followed by a reduction to values close to those at the intact forests were registered after slash-and-burn practice was implemented in both sub-regions during the first two years of forest-to-pasture conversion. Implementation of machinery after using fire in HG pastures led to a reduction of 82% in CWD stocks during the second and fifth years of pasture establishment, compared to a decrease of 41% during the same period in LG where mechanization is not implemented. Finally, average necromass 20 years after forest-to-pasture conversion decreased to 3.5 ± 1.4 Mg ha(-1) in HG and 9.3 ± 3.5 Mg ha(-1) in LG, representing a total reduction of between 90% and 75% in each sub-region, respectively. These results highlight the importance of low-grazing intensity management practices during ranching activities in the Colombian Amazon to reduce C emissions associated with land-cover change from forest to pasture.This study was funded by AXA Research Fund (2012-Doc-University-of-Exeter-NAVARRETE-D)

Evaluation of land surface models in reproducing satellite derived leaf area index over the high-latitude northern hemisphere. Part II: Earth system models

PublishedJournal ArticleLeaf Area Index (LAI) is a key parameter in the Earth System Models (ESMs) since it strongly affects land-surface boundary conditions and the exchange of matter and energy with the atmosphere. Observations and data products derived from satellite remote sensing are important for the validation and evaluation of ESMs from regional to global scales. Several decades' worth of satellite data products are now available at global scale which represents a unique opportunity to contrast observations against model results. The objective of this study is to assess whether ESMs correctly reproduce the spatial variability of LAI when compared with satellite data and to compare the length of the growing season in the different models with the satellite data. To achieve this goal we analyse outputs from 11 coupled carbon-climate models that are based on the set of new global model simulations planned in support of the IPCC Fifth Assessment Report. We focus on the average LAI and the length of the growing season on Northern Hemisphere over the period 1986-2005. Additionally we compare the results with previous analyses (Part I) of uncoupled land surface models (LSMs) to assess the relative contribution of vegetation and climatic drivers on the correct representation of LAI. Our results show that models tend to overestimate the average values of LAI and have a longer growing season due to the later dormancy. The similarities with the uncoupled models suggest that representing the correct vegetation fraction with the associated parameterizations; is more important in controlling the distribution and value of LAI than the climatic variables. © 2013 by the authors.This work was funded by the European Commission’s 7th Framework Programme under Grant Agreements number 238366 (GREENCYCLESII project) and 282672 (EMBRACE project)

INFERNO: a fire and emissions scheme for the UK Met Office's Unified Model

Warm and dry climatological conditions favour the occurrence of forest fires. These fires then become a significant emission source to the atmosphere. Despite this global importance, fires are a local phenomenon and are difficult to represent in a large-scale Earth System Model (ESM). To address this, the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO) was developed. INFERNO follows a reduced complexity approach and is intended for decadal to centennial scale climate simulations and assessment models for policy making. Fuel flammability is simulated using temperature, relative humidity, fuel density as well as precipitation and soil moisture. Combining flammability with ignitions and vegetation, burnt area is diagnosed. Emissions of carbon and key species are estimated using the carbon scheme in the JULES land surface model. JULES also possesses fire index diagnostics which we document and compare with our fire scheme. Two meteorology datasets and three ignition modes are used to validate the model. INFERNO is shown to effectively diagnose global fire occurrence (R = 0.66) and emissions (R = 0.59) through an approach appropriate to the complexity of an ESM, although regional biases remain

Investigating the response of leaf area index to droughts in southern African vegetation using observations and model-simulations

In many regions of the world, frequent and continual dry spells are exacerbating drought conditions, which have severe impacts on vegetation biomes. Vegetation in southern Africa is among the most affected by drought. Here, we assessed the spatiotemporal characteristics of meteorological drought in southern Africa using the standardized precipitation evapotranspiration index (SPEI) over a 30-year period (1982–2011). The severity and the effects of droughts on vegetation productiveness were examined at different drought timescales (1- to 24-month timescales). In this study, we characterized vegetation using the leaf area index (LAI) after evaluating its relationship with the normalized difference vegetation index (NDVI). Correlating the LAI with the SPEI, we found that the LAI responds strongly (r=0.6) to drought over the central and southeastern parts of the region, with weaker impacts (r<0.4) over parts of Madagascar, Angola, and the western parts of South Africa. Furthermore, the latitudinal distribution of LAI responses to drought indicates a similar temporal pattern but different magnitudes across timescales. The results of the study also showed that the seasonal response across different southern African biomes varies in magnitude and occurs mostly at shorter to intermediate timescales. The semi-desert biome strongly correlates (r=0.95) to drought as characterized by the SPEI at a 6-month timescale in the MAM (March–May; summer) season, while the tropical forest biome shows the weakest response (r=0.35) at a 6-month timescale in the DJF (December–February; hot and rainy) season. In addition, we found that the spatial pattern of change of LAI and SPEI are mostly similar during extremely dry and wet years, with the highest anomaly observed in the dry year of 1991, and we found different temporal variability in global and regional responses across different biomes. We also examined how well an ensemble of state-of-the-art dynamic global vegetation models (DGVMs) simulate the LAI and its response to drought. The spatial and seasonal response of the LAI to drought is mostly overestimated in the DGVM multimodel ensemble compared to the response calculated for the observation-based data. The correlation coefficient values for the multimodel ensemble are as high as 0.76 (annual) over South Africa and 0.98 in the MAM season over the temperate grassland biome. Furthermore, the DGVM model ensemble shows positive biases (3 months or longer) in the simulation of spatial distribution of drought timescales and overestimates the seasonal distribution timescales. The results of this study highlight the areas to target for further development of DGVMs and can be used to improve the models' capability in simulating the drought–vegetation relationship