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© 2014 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections. The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type. Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is years (95 per cent confidence interval). On average, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75° north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semi-arid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.

The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections. The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type. Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is 23(+7)(-4) years (95 per cent confidence interval). On average, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75° north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semi-arid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.

This study investigated the microbial degradation of (14)C-labelled hexadecane, octacosane, phenanthrene and pyrene and considered how degradation might be optimised in three genuinely hydrocarbon-contaminated soils from former petroleum refinery sites. Hydrocarbon mineralisation by the indigenous microbial community was monitored over 23 d. Hydrocarbon mineralisation enhancement by nutrient amendment (biostimulation), hydrocarbon degrader addition (bioaugmentation) and combined nutrient and degrader amendment, was also explored. The ability of indigenous soil microflora to mineralise (14)C-target hydrocarbons was appreciable; ≥ 16% mineralised in all soils. Generally, addition of nutrients or degraders increased the rates and extents of mineralisation of (14)C-hydrocarbons. However, the addition of nutrients and degraders in combination had a negative effect upon (14)C-octacosane mineralisation and resulted in lower extents of mineralisation in the three soils. In general, the rates and extents of mineralisation will be dependent upon treatment type, nature of the contamination and adaptation of the ingenious microbial community., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.

Level I and II fugacity approaches were used to model the environmental distribution of benzene, anthracene, phenanthrene, 1-methylphenanthrene and benzo[a]pyrene in a four phase biopile system, accounting for air, water, mineral soil and non-aqueous phase liquid (oil) phase. The non-aqueous phase liquid (NAPL) and soil phases were the dominant partition media for the contaminants in each biopile and the contaminants differed markedly in their individual fugacities. Comparison of three soils with different percentage of organic carbon (% org C) showed that the % org C influenced contaminant partitioning behaviour. While benzene showed an aqueous concentration worthy of note for leachate control during biopiling, other organic chemicals showed that insignificant amount of chemicals leached into the water, greatly reducing the potential extent of groundwater contamination. Level II fugacity model showed that degradation was the dominant removal process except for benzene. In all three biopile systems, the rate of degradation of benzo(a)pyrene was low, requiring more than 12 years for soil concentrations from a spill of about 25 kg (100 mol) to be reduced to a concentration of 0.001 microgg(-1). The removal time of 1-methylphenanthrene and either anthracene or phenanthrene was about 1 and 3 years, respectively. In contrast, benzene showed the highest degradation rate and was removed after 136 days in all biopile systems. Overall, this study confirms the association of risk critical contaminants with the residual saturation in treated soils and reinforces the importance of accounting for the partitioning behaviour of both NAPL and soil phases during the risk assessment of oil-contaminated sites.