Increased Litterfall in Tropical Forests Boosts the Transfer of Soil CO2 to the Atmosphere

Aboveground litter production in forests is likely to increase as a consequence of elevated atmospheric carbon dioxide (CO2) concentrations, rising temperatures, and shifting rainfall patterns. As litterfall represents a major flux of carbon from vegetation to soil, changes in litter inputs are likely to have wide-reaching consequences for soil carbon dynamics. Such disturbances to the carbon balance may be particularly important in the tropics because tropical forests store almost 30% of the global soil carbon, making them a critical component of the global carbon cycle; nevertheless, the effects of increasing aboveground litter production on belowground carbon dynamics are poorly understood. We used long-term, large-scale monthly litter removal and addition treatments in a lowland tropical forest to assess the consequences of increased litterfall on belowground CO2 production. Over the second to the fifth year of treatments, litter addition increased soil respiration more than litter removal decreased it; soil respiration was on average 20% lower in the litter removal and 43% higher in the litter addition treatment compared to the controls but litter addition did not change microbial biomass. We predicted a 9% increase in soil respiration in the litter addition plots, based on the 20% decrease in the litter removal plots and an 11% reduction due to lower fine root biomass in the litter addition plots. The 43% measured increase in soil respiration was therefore 34% higher than predicted and it is possible that this ‘extra’ CO2 was a result of priming effects, i.e. stimulation of the decomposition of older soil organic matter by the addition of fresh organic matter. Our results show that increases in aboveground litter production as a result of global change have the potential to cause considerable losses of soil carbon to the atmosphere in tropical forests

Is analysing the nitrogen use at the plant canopy level a matter of choosing the right optimization criterion?

Optimization theory in combination with canopy modeling is potentially a powerful tool for evaluating the adaptive significance of photosynthesis-related plant traits. Yet its successful application has been hampered by a lack of agreement on the appropriate optimization criterion. Here we review how models based on different types of optimization criteria have been used to analyze traits—particularly N reallocation and leaf area indices—that determine photosynthetic nitrogen-use efficiency at the canopy level. By far the most commonly used approach is static-plant simple optimization (SSO). Static-plant simple optimization makes two assumptions: (1) plant traits are considered to be optimal when they maximize whole-stand daily photosynthesis, ignoring competitive interactions between individuals; (2) it assumes static plants, ignoring canopy dynamics (production and loss of leaves, and the reallocation and uptake of nitrogen) and the respiration of nonphotosynthetic tissue. Recent studies have addressed either the former problem through the application of evolutionary game theory (EGT) or the latter by applying dynamic-plant simple optimization (DSO), and have made considerable progress in our understanding of plant photosynthetic traits. However, we argue that future model studies should focus on combining these two approaches. We also point out that field observations can fit predictions from two models based on very different optimization criteria. In order to enhance our understanding of the adaptive significance of photosynthesis-related plant traits, there is thus an urgent need for experiments that test underlying optimization criteria and competing hypotheses about underlying mechanisms of optimization

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

An overview of tissue engineering approaches for management of spinal cord injuries

Severe spinal cord injury (SCI) leads to devastating neurological deficits and disabilities, which necessitates spending a great deal of health budget for psychological and healthcare problems of these patients and their relatives. This justifies the cost of research into the new modalities for treatment of spinal cord injuries, even in developing countries. Apart from surgical management and nerve grafting, several other approaches have been adopted for management of this condition including pharmacologic and gene therapy, cell therapy, and use of different cell-free or cell-seeded bioscaffolds. In current paper, the recent developments for therapeutic delivery of stem and non-stem cells to the site of injury, and application of cell-free and cell-seeded natural and synthetic scaffolds have been reviewed

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

The phylogenetic composition and structure of soil microbial communities shifts in response to elevated carbon dioxide

http://www.nature.com/ismej/journal/v6/n2/full/ismej201199a.htmlOne of the major factors associated with global change is the ever-increasing concentration of atmospheric CO2. Although the stimulating effects of elevated CO2 (eCO2) on plant growth and primary productivity have been established, its impacts on the diversity and function of soil microbial communities are poorly understood. In this study, phylogenetic microarrays (PhyloChip) were used to comprehensively survey the richness, composition and structure of soil microbial communities in a grassland experiment subjected to two CO2 conditions (ambient, 368 p.p.m., versus elevated, 560 p.p.m.) for 10 years. The richness based on the detected number of operational taxonomic units (OTUs) significantly decreased under eCO2. PhyloChip detected 2269 OTUs derived from 45 phyla (including two from Archaea), 55 classes, 99 orders, 164 families and 190 subfamilies. Also, the signal intensity of five phyla (Crenarchaeota, Chloroflexi, OP10, OP9/JS1, Verrucomicrobia) significantly decreased at eCO2, and such significant effects of eCO2 on microbial composition were also observed at the class or lower taxonomic levels for most abundant phyla, such as Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes and Acidobacteria, suggesting a shift in microbial community composition at eCO2. Additionally, statistical analyses showed that the overall taxonomic structure of soil microbial communities was altered at eCO2. Mantel tests indicated that such changes in species richness, composition and structure of soil microbial communities were closely correlated with soil and plant properties. This study provides insights into our understanding of shifts in the richness, composition and structure of soil microbial communities under eCO2 and environmental factors shaping the microbial community structure