National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system

Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

Results from the Covered Catchment Experiment at Gårdsjön, Sweden, after ten years of clean precipitation treatment

The Covered Catchment Experiment at Gordsjon is a large scale forest ecosystem manipulation, where acid precipitation was intercepted by a 7000 m(2) plastic roof and replaced by 'clean precipitation' sprinkled below the roof for ten years between 1991 and 2001. The treatment resulted in a strong positive response of runoff quality. The runoff sulphate, inorganic aluminium and base cations decreased, while there was a strong increase in runoff ANC and a moderate increase in pH. The runoff continued to improve over the whole duration of the experiment. The achieved quality was, however, after ten years still considerably worse than estimated pre-industrial runoff at the site. Stable isotopes of sulphur were analysed to study the soil sulphur cycling. At the initial years of the experiment, the desorption of SO4 from the mineral soil appeared to control the runoff SO4 concentration. However, as the experiment proceeded, there was growing evidence that net mineralisation of soil organic sulphur in the humus layer was an additional source of SO4 in runoff. This might provide a challenge to current acidification models. The experiment convincingly demonstrated on a catchment scale, that reduction in acid deposition causes an immediate improvement of surface water quality even at heavily acidified sites. The improvement of the runoff appeared to be largely a result of cation exchange processes in the soil due to decreasing concentrations of the soil solution, while any potential change in soil base saturation seemed to be less important for the runoff chemistry over the short time period of one decade. These findings should be considered when interpreting and extrapolating regional trends in surface water chemistry to the terrestrial parts of ecosystems.

Adaptation of the Integrated Nitrogen Model for Catchments (INCA) to seasonally snow-covered catchments

Testing of the Integrated Nitrogen model for Catchments (INCA) in a wide range of ecosystem types across Europe has shown that the model underestimates N transformation processes to a large extent in northern catchments of Finland and Norway in winter and spring. It is found, and generally assumed, that microbial activity in soils proceeds at low rates at northern latitudes during winter, even at sub-zero temperatures. The INCA model was modified to improve the simulation of N transformation rates in northern catchments, characterised by cold climates and extensive snow accumulation and insulation in winter, by introducing an empirical function to simulate soil temperatures below the seasonal snow pack, and a degree-day model to calculate the depth of the snow pack. The proposed snow-correction factor improved the simulation of soil temperatures at Finnish and Norwegian field sites in winter, although soil temperature was still underestimated during periods with a thin snow cover. Finally, a comparison between the modified INCA version (v. 1.7) and the former version (v. 1.6) was made at the Simojoki river basin in northern Finland and at Dalelva Brook in northern Norway. The new modules did not imply any significant changes in simulated NO3- concentration levels in the streams but improved the timing of simulated higher concentrations. The inclusion of a modified temperature response function and an empirical snow-correction factor improved the flexibility and applicability of the model for climate effect studies.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.

Impulsiveness as a timing disturbance: neurocognitive abnormalities in attention-deficit hyperactivity disorder during temporal processes and normalization with methylphenidate.

We argue that impulsiveness is characterized by compromised timing functions such as premature motor timing, decreased tolerance to delays, poor temporal foresight and steeper temporal discounting. A model illustration for the association between impulsiveness and timing deficits is the impulsiveness disorder of attention-deficit hyperactivity disorder (ADHD). Children with ADHD have deficits in timing processes of several temporal domains and the neural substrates of these compromised timing functions are strikingly similar to the neuropathology of ADHD. We review our published and present novel functional magnetic resonance imaging data to demonstrate that ADHD children show dysfunctions in key timing regions of prefrontal, cingulate, striatal and cerebellar location during temporal processes of several time domains including time discrimination of milliseconds, motor timing to seconds and temporal discounting of longer time intervals. Given that impulsiveness, timing abnormalities and more specifically ADHD have been related to dopamine dysregulation, we tested for and demonstrated a normalization effect of all brain dysfunctions in ADHD children during time discrimination with the dopamine agonist and treatment of choice, methylphenidate. This review together with the new empirical findings demonstrates that neurocognitive dysfunctions in temporal processes are crucial to the impulsiveness disorder of ADHD and provides first evidence for normalization with a dopamine reuptake inhibitor.

Gender stereotyping and decision processes: extending and reversing the gender bias in fame judgements

M. R. Banaji and A. G. Greenwald (1995) demonstrated a gender bias in fame judgments—that is, an increase in judged fame due to prior processing that was larger for male than for female names. They suggested that participants shift criteria between judging men and women, using the more liberal criterion for judging men. This "criterion-shift" account appeared problematic for a number of reasons. In this article, 3 experiments are reported that were designed to evaluate the criterion-shift account of the gender bias in the false-fame effect against a distribution-shift account. The results were consistent with the criterion-shift account, and they helped to define more precisely the situations in which people may be ready to shift their response criterion on an item-by-item basis. In addition, the results were incompatible with an interpretation of the criterion shift as an artifact of the experimental situation in the experiments reported by M. R. Banaji and A. G. Greenwald. (PsycINFO Database Record (c) 2010 APA, all rights reserved)

Implicit and explicit processes in a second-language learning task

Two experiments examined the learning of a set of Greek pronunciation rules through explicit and implicit modes of rule presentation. Experiment 1 compared the effectiveness of implicit and explicit modes of presentation in two modalities, visual and auditory. Subjects in the explicit or rule group were presented with the rule set, and those in the implicit or natural group were shown a set of Greek words, composed of letters from the rule set, linked to their pronunciations. Subjects learned the Greek words to criterion and were then given a series of tests which aimed to tap different types of knowledge. The results showed an advantage of explicit study of the rules. In addition, an interaction was found between mode of presentation and modality. Explicit instruction was more effective in the visual than in the auditory modality, whereas there was no modality effect for implicit instruction. Experiment 2 examined a possible reason for the advantage of the rule groups by comparing different combinations of explicit and implicit presentation in the study and learning phases. The results suggested that explicit presentation of the rules is only beneficial when it is followed by practice at applying them.

Atmospheric processes and observations

The central role of the atmosphere in abrupt climate change is proposed and discussed. This discussion is given in the context of the poleward transport of energy in the climate system and of climate variability and change. A number of examples based on observational and model data are used to illustrate the ideas.

Granger causality of coupled climate processes: Ocean feedback on the North Atlantic oscillation

This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.