Potsdam Institute for Climate Impact Research

About: Potsdam Institute for Climate Impact Research is a facility organization based out in Potsdam, Germany. It is known for research contribution in the topics: Climate change & Global warming. The organization has 1519 authors who have published 5098 publications receiving 367023 citations.

A few extreme events dominate global interannual variability in gross primary production

Abstract: Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982?2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5?Pg?C?yr?1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability.

Achievements and needs for the climate change scenario framework.

Abstract: Long-term global scenarios have underpinned research and assessment of global environmental change for four decades. Over the past ten years, the climate change research community has developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. Here we assess how well this framework is working and what challenges it faces. We synthesize insights from scenario-based literature, community discussions and recent experience in assessments, concluding that the framework has been widely adopted across research communities and is largely meeting immediate needs. However, some mixed successes and a changing policy and research landscape present key challenges, and we recommend several new directions for the development and use of this framework.

δ13C of CO2 respired in the dark in relation to δ13C of leaf metabolites: comparison between Nicotiana sylvestris and Helianthus annuus under drought

Abstract: The variations of δ13C in leaf metabolites (lipids, organic acids, starch and soluble sugars), leaf organic matter and CO2 respired in the dark from leaves of Nicotiana sylvestris and Helianthus annuus were investigated during a progressive drought. Under well-watered conditions, CO2 respired in the dark was 13C-enriched compared to sucrose by about 4‰ in N. sylvestris and by about 3‰ and 6‰ in two different sets of experiments in H. annuus plants. In a previous work on cotyledonary leaves of Phaseolus vulgaris, we observed a constant 13C-enrichment by about 6‰ in respired CO2 compared to sucrose, suggesting a constant fractionation during dark respiration, whatever the leaf age and relative water content. In contrast, the 13C-enrichment in respired CO2 increased in dehydrated N. sylvestris and decreased in dehydrated H. annuus in comparison with control plants. We conclude that (i) carbon isotope fractionation during dark respiration is a widespread phenomenon occurring in C3 plants, but that (ii) this fractionation is not constant and varies among species and (iii) it also varies with environmental conditions (water deficit in the present work) but differently among species. We also conclude that (iv) a discrimination during dark respiration processes occurred, releasing CO2 enriched in 13C compared to several major leaf reserves (carbohydrates, lipids and organic acids) and whole leaf organic matter.

Prediction of extreme floods in the eastern Central Andes based on a complex networks approach

Abstract: Extreme rainfall events in the eastern Central Andes can result in substantial economic and ecological damage, yet their prediction is difficult. Here, the authors introduce the concept of network divergence and propose a general framework for the prediction of extreme events.