562 research outputs found
Terrestrial nitrogen feedbacks may accelerate future climate change
No full textThe effects of nitrogen (N) constraints on future terrestrial carbon (C) dynamics are investigated using the O-CN land surface model. The model's responses to elevated [CO2] and soil warming agree well with observations made in ecosystem manipulation studies. N dynamics reduce terrestrial C storage due to CO2 fertilization over the period 1860-2100 by similar to 50% (342 Pg C) mainly in mid-high latitude ecosystems, compared to a simulation not accounting for N dynamics. Conversely, N dynamics reduce projected losses of land C due to increasing temperature by 16% (49 Pg C); however, this effect is prevalent only in mid-high latitude ecosystems. Despite synergistic interactions, the balance of these opposing effects is a significant reduction in future net land C storage. Terrestrial N dynamics thereby consistently increase atmospheric [CO2] in the year 2100 with a median value of 48 (41-55) ppmv, corresponding to an additional radiative forcing of 0.29 (0.28-0.34) W m(-2). Citation: Zaehle, S., P. Friedlingstein, and A. D. Friend (2010), Terrestrial nitrogen feedbacks may accelerate future climate change, Geophys. Res. Lett., 37, L01401, doi:10.1029/2009GL041345
Effects of climate variability and extreme events on European ecosystem state and function: A CARBO-Extreme modelling study
No full textEffects of posed smiling on memory for happy and sad facial expressions
No full textThe perception and storage of facial emotional expressions constitutes an important human skill that is essential for our daily social interactions. While previous research revealed that facial feedback can influence the perception of facial emotional expressions, it is unclear whether facial feedback also plays a role in memory processes of facial emotional expressions. In the present study we investigated the impact of facial feedback on the performance in emotional visual working memory (WM). For this purpose, 37 participants underwent a classical facial feedback manipulation (FFM) (holding a pen with the teeth—inducing a smiling expression vs. holding a pen with the non-dominant hand—as a control condition) while they performed a WM task on varying intensities of happy or sad facial expressions. Results show that the smiling manipulation improved memory performance selectively for happy faces, especially for highly ambiguous facial expressions. Furthermore, we found that in addition to an overall negative bias specifically for happy faces (i.e. happy faces are remembered as more negative than they initially were), FFM induced a positivity bias when memorizing emotional facial information (i.e. faces were remembered as being more positive than they actually were). Finally, our data demonstrate that men were affected more by FFM: during induced smiling men showed a larger positive bias than women did. These data demonstrate that facial feedback not only influences our perception but also systematically alters our memory of facial emotional expressions
Identifying differences in carbohydrate dynamics of seedlings and mature trees to improve carbon allocation in models for trees and forests
No full textCarbohydrates play a central role in plant functioning because they are building blocks and energy carriers for plant metabolic processes. Because plants are sessile organisms and cannot escape stressful environments they acclimate to unfavourable conditions by strategically allocating carbohydrate resources to overcome stress and promote survival, and build reserves for later use when demand is greater than supply from photosynthesis, like after defoliation. A mechanistic understanding of how plants and, in particular, long-lived organisms like trees allocate and remobilize stored carbohydrates is still very poor. Without such an understanding, however, integration of carbon dynamics from trees to ecosystems and to the globe becomes highly uncertain, especially under ongoing climate change. Studies of carbohydrate dynamics in trees are often carried out on tree seedlings due to logistical and technical constraints and criticism has been raised whether results can be extrapolated to mature trees. Here we combine a literature review with a critical evaluation of using seedling studies on carbohydrate dynamics to infer mature tree responses that can subsequently be integrated at ecosystem level and beyond. Despite obvious differences between seedlings and mature trees with respect to carbohydrate dynamics, we propose that a combination of approaches, including seedling studies in controlled environments, measurements on mature trees in the field and ecosystem flux measurements, may provide sound estimates of carbohydrate dynamics at larger scales. We show how sensitive predictions of vegetation responses to disturbance are to changes in available reserves and argue that the implementation of more realistic representations of storage dynamics will likely improve simulations of vegetation responses to environmental stress
Terrestrial nitrogen-carbon cycle interactions at the global scale
No full textInteractions between the terrestrial nitrogen (N) and carbon (C) cycles shape the response of ecosystems to global change. However, the global distribution of nitrogen availability and its importance in global biogeochemistry and biogeochemical interactions with the climate system remain uncertain. Based on projections of a terrestrial biosphere model scaling ecological understanding of nitrogen-carbon cycle interactions to global scales, anthropogenic nitrogen additions since 1860 are estimated to have enriched the terrestrial biosphere by 1.3 Pg N, supporting the sequestration of 11.2 Pg C. Over the same time period, CO2 fertilization has increased terrestrial carbon storage by 134.0 Pg C, increasing the terrestrial nitrogen stock by 1.2 Pg N. In 2001-2010, terrestrial ecosystems sequestered an estimated total of 27 Tg N yr(-1) (1.9 Pg C yr(-1)), of which 10 Tg N yr(-1) (0.2 Pg C yr(-1)) are due to anthropogenic nitrogen deposition. Nitrogen availability already limits terrestrial carbon sequestration in the boreal and temperate zone, and will constrain future carbon sequestration in response to CO2 fertilization (regionally by up to 70% compared with an estimate without considering nitrogen-carbon interactions). This reduced terrestrial carbon uptake will probably dominate the role of the terrestrial nitrogen cycle in the climate system, as it accelerates the accumulation of anthropogenic CO2 in the atmosphere. However, increases of N2O emissions owing to anthropogenic nitrogen and climate change (at a rate of approx. 0.5 Tg N yr(-1) per 1°C degree climate warming) will add an important long-term climate forcing
The evaluation of Earth System Models: discussion summary
No full textComplex Earth system models, and their various sub-components, are not yet subject to rigorous evaluation against observations as much as they should be, despite the existence of hundreds of proposed diagnostics. A concerted process is urgently needed to make this the norm, not the exception. Earth Observation, field observations and palaeo data can be applied to contexts as diverse as wildfire, marine ecosystems, the land carbon cycle, and greenhouse gases. Model evaluation (by comparing models and benchmark data) and model weighting (defining the ‘quality’ of models on the basis of such a comparison) should be considered as separate issues. Systematic approaches to parameter optimization, such as the adjoint technique, allow structural differences between models to be identified and limitations to be addressed. Such methods are established in atmospheric tracer transport and carbon cycling; research carried out in the QUEST programme has demonstrated their applicability for climate modelling. Although it is impossible to devise a foolproof metric for the ability of models to predict the future, relevant metrics could be based on their ability to simulate the past. Furthermore, it should be possible to extend parameter optimization techniques to assimilate data from the past. There are limits to what can be achieved by benchmarking against a mean state, when it is a change in state that is of greatest interest. It is useful to benchmark individual processes rather than aggregate properties. Coupling good components does not automatically result in a good Earth System model, so for complex models, a two-stage process is needed: first, benchmarking the components in stand-alone mode, and second, using the same benchmarks in coupled mode.Complex Earth system models, and their various sub-components, are not yet subject to rigorous evaluation against observations as much as they should be, despite the existence of hundreds of proposed diagnostics. A concerted process is urgently needed to make this the norm, not the exception. Earth Observation, field observations and palaeo data can be applied to contexts as diverse as wildfire, marine ecosystems, the land carbon cycle, and greenhouse gases. Model evaluation (by comparing models and benchmark data) and model weighting (defining the ‘quality’ of models on the basis of such a comparison) should be considered as separate issues. Systematic approaches to parameter optimization, such as the adjoint technique, allow structural differences between models to be identified and limitations to be addressed. Such methods are established in atmospheric tracer transport and carbon cycling; research carried out in the QUEST programme has demonstrated their applicability for climate modelling. Although it is impossible to devise a foolproof metric for the ability of models to predict the future, relevant metrics could be based on their ability to simulate the past. Furthermore, it should be possible to extend parameter optimization techniques to assimilate data from the past. There are limits to what can be achieved by benchmarking against a mean state, when it is a change in state that is of greatest interest. It is useful to benchmark individual processes rather than aggregate properties. Coupling good components does not automatically result in a good Earth System model, so for complex models, a two-stage process is needed: first, benchmarking the components in stand-alone mode, and second, using the same benchmarks in coupled mode
Effect of height on tree hydraulic conductance incompletely compensated by xylem tapering
No full textImpact of chronic transcranial random noise stimulation (tRNS) on GABAergic and glutamatergic activity markers in the prefrontal cortex of juvenile mice
No full textTranscranial random noise stimulation (tRNS), a non-invasive neuromodulatory technique capable of altering cortical activity, has been proposed to improve the signal-to-noise ratio at the neuronal level and the sensitivity of the neurons following an inverted U-function. The aim of this study was to examine the effects of tRNS on vGLUT1 and GAD 65–67 and its safety in terms of pathological changes. For that, juvenile mice were randomly distributed in three different groups: “tRNS 1 ×” receiving tRNS at the density current used in humans (0.3 A/m2, 20 min), “tRNS 100 ×” receiving tRNS at two orders of magnitude higher (30.0 A/m2, 20 min) and “sham” (0.3 A/m2, 15 s). Nine tRNS sessions during 5 weeks were administered to the prefrontal cortex of awake animals. No detectable tissue macroscopic lesions were observed after tRNS sessions. Post-stimulation immunohistochemical analysis of GAD 65–67 and vGLUT1 immunoreactivity showed reduced GAD 65–67 immunoreactivity levels in the region directly beneath the electrode for tRNS 1 × group with no significant effects in the tRNS 100 × nor sham group. The observed results suggest an excitatory effect associated with a decrease in GABA levels in absence of major histopathological alterations providing a novel mechanistic explanation for tRNS effects
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