European emissions of isoprene and monoterpenes from the Last Glacial Maximum to present

Peer reviewe

An overview of ADSL Homed Nepenthes Honeypots In Western Australia

This paper outlines initial analysis from research in progress into ADSL homed Nepenthes honeypots. One of the Nepenthes honeypots prime objective in this research was the collection of malware for analysis and dissection. A further objective is the analysis of risks that are circulating within ISP networks in Western Australian. What differentiates Nepenthes from many traditional honeypot designs it that is has been engineered from a distributed network philosophy. The program allows distribution of results across a network of sensors and subsequent aggregation of malware statistics readily within a large network environment

The transformation of the forest steppe in the lower Danube Plain of south-eastern Europe : 6000 years of vegetation and land use dynamics

Forest steppes are dynamic ecosystems, highly susceptible to changes in climate and land use. Here we examine the Holocene history of the European forest steppe ecotone in the Lower Danube Plain to better understand its sensitivity to climate fluctuations and human impact, and the timing of its transition into a cultural forest steppe. We used multi-proxy analyses (pollen, n-alkane, coprophilous fungi, charcoal, and geochemistry) of a 6000-year sequence from Lake Oltina (SE Romania), combined with a REVEALS model of quantitative vegetation cover. We found the greatest tree cover, composed of xerothermic (Carpinus orientalis and Quercus) and temperate (Carpinus betulus, Tilia, Ulmus and Fraxinus) tree taxa between 6000 and 2500 cal yr BP. Maximum tree cover (~ 50 %) occurred between 4200 and 2500 cal yr BP at a time of wetter climatic conditions. Compared to other European forest steppe areas, the dominance of Carpinus orientalis represents the most distinct feature of the woodland's composition during that time. Forest loss was under way by 2500 yr BP (Iron Age) with REVEALS estimates indicating a fall to ~ 20 % tree cover from the mid-Holocene forest maximum linked to clearance for agriculture, while climate conditions remained wet. Biomass burning increased markedly at 2500 cal yr BP suggesting that fire was regularly used as a management tool until 1000 cal yr BP when woody vegetation became scarce. A sparse tree cover, with only weak signs of forest recovery, then became a permanent characteristic of the Lower Danube Plain, highlighting recurring anthropogenic pressure. The timing of anthropogenic ecosystem transformation here (2500 cal yr BP) was in between that in central eastern (between 3700 and 3000 cal yr BP) and eastern (after 2000 cal yr BP) Europe. Our study is the first quantitative land cover estimate at the forest steppe ecotone in south eastern Europe spanning 6000 years and provides critical empirical evidence that the present-day forest steppe/woodlands reflects the potential natural vegetation in this region under current climate conditions. This study also highlights the potential of n-alkane indices for vegetation reconstruction, particularly in dry regions where pollen is poorly preserved

Climate-vegetation modelling and fossil plant data suggest low atmospheric CO2 in the late Miocene

There is an increasing need to understand the pre-Quaternary warm climates, how climate-vegetation interactions functioned in the past, and how we can use this information to understand the present. Here we report vegetation modelling results for the Late Miocene (11-7 Ma) to study the mechanisms of vegetation dynamics and the role of different forcing factors that influence the spatial patterns of vegetation coverage. One of the key uncertainties is the atmospheric concentration of CO2 during past climates. Estimates for the last 20 million years range from 280 to 500 ppm. We simulated Late Miocene vegetation using two plausible CO2 concentrations, 280 ppm CO2 and 450 ppm CO2, with a dynamic global vegetation model (LPJ-GUESS) driven by climate input from a coupled AOGCM (Atmosphere-Ocean General Circulation Model). The simulated vegetation was compared to existing plant fossil data for the whole Northern Hemisphere. For the comparison we developed a novel approach that uses information of the relative dominance of different plant functional types (PFTs) in the palaeobotanical data to provide a quantitative estimate of the agreement between the simulated and reconstructed vegetation. Based on this quantitative assessment we find that pre-industrial CO2 levels are largely consistent with the presence of seasonal temperate forests in Europe (suggested by fossil data) and open vegetation in North America (suggested by multiple lines of evidence). This suggests that during the Late Miocene the CO2 levels have been relatively low, or that other factors that are not included in the models maintained the seasonal temperate forests and open vegetation.Peer reviewe

Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps

Sustaining ecosystem services (ES) critical to human wellbeing is hindered by many practitioners lacking access to ES models (‘the capacity gap’) or knowledge of the accuracy of available models (‘the certainty gap’), especially in the world’s poorer regions. We developed ensembles of multiple models at an unprecedented global scale for five ES of high policy relevance. Ensembles were 2-14% more accurate than individual models. Ensemble accuracy was not correlated with proxies for research capacity – indicating accuracy is distributed equitably across the globe and that countries less able to research ES suffer no accuracy penalty. By making these ES ensembles and associated accuracy estimates freely available, we provide globally consistent ES information that can support policy and decision making in regions with low data availability or low capacity for implementing complex ES models. Thus, we hope to reduce the capacity and certainty gaps impeding local to global-scale movement towards ES sustainability

The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols

The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over two decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. Here we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models

Historical (1700–2012) global multi-model estimates of the fire emissions from the Fire Modeling Intercomparison Project (FireMIP)

Fire emissions are a critical component of carbon and nutrient cycles and strongly affect climate and air quality. Dynamic global vegetation models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes in fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700–2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table based on field and laboratory studies in various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. The evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products. They can capture the high emissions over the tropical savannas and low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Before the 1850s, all models show only a weak trend in global fire emissions, which is consistent with the multi-source merged historical reconstructions used as input data for CMIP6. On the other hand, the trends are quite different among DGVMs for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land use and land cover change (LULCC). Our study provides an important dataset for further development of regional and global multi-source merged historical reconstructions, analyses of the historical changes in fire emissions and their uncertainties, and quantification of the role of fire emissions in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections

Fine-root turnover rates of European forests revisited: an analysis of data from sequential coring and ingrowth cores

Background and Aims Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values. Methods We compiled available European data and applied various turnover rate calculation methods to the resulting database. We used Decision Matrix and Maximum-Minimum formula as suggested in the literature. Results Mean turnover rates obtained by the combination of sequential coring and Decision Matrix were 0.86 yr−1 for Fagus sylvatica and 0.88 yr−1 for Picea abies when maximum biomass data were used for the calculation, and 1.11 yr−1 for both species when mean biomass data were used. Using mean biomass rather than maximum resulted in about 30 % higher values of root turnover. Using the Decision Matrix to calculate turnover rate doubled the rates when compared to the Maximum-Minimum formula. The Decision Matrix, however, makes use of more input information than the Maximum-Minimum formula. Conclusions We propose that calculations using the Decision Matrix with mean biomass give the most reliable estimates of root turnover rates in European forests and should preferentially be used in models and C reporting

The status and challenge of global fire modelling

This is the final version of the article. Available from European Geosciences Union / Copernicus Publications via the DOI in this record.The discussion paper version of this article was published in Biogeosciences Discussions on 25 January 2016 and is in ORE at http://hdl.handle.net/10871/34451Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT-6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all. For more information, contact Stijn Hantson ([email protected])