Plant-driven variation in decomposition rates improves projections of global litter stock distribution.

Plant litter stocks are critical, regionally for their role in fueling fire regimes and controlling soil fertility, and globally through their feedback to atmospheric CO₂ and climate. Here we employ two global databases linking plant functional types to decomposition rates of wood and leaf litter (Cornwell et al., 2008; Weedon et al., 2009) to improve future projections of climate and carbon cycle using an intermediate complexity Earth System model. Implementing separate wood and leaf litter decomposabilities and their temperature sensitivities for a range of plant functional types yielded a more realistic distribution of litter stocks in all present biomes with the exception of boreal forests and projects a strong increase in global litter stocks by 35 Gt C and a concomitant small decrease in atmospheric CO₂ by 3 ppm by the end of this century. Despite a relatively strong increase in litter stocks, the modified parameterization results in less elevated wildfire emissions because of a litter redistribution towards more humid regions

Causes of regional change—land cover

Anthropogenic land-cover change (ALCC) is one of the few climate forcings for which the net direction of the climate response over the last two centuries is still not known. The uncertainty is due to the often counteracting temperature responses to the many biogeophysical effects and to the biogeochemical versus biogeophysical effects. Palaeoecological studies show that the major transformation of the landscape by anthropogenic activities in the southern zone of the Baltic Sea basin occurred between 6000 and 3000/2500 cal year BP. The only modelling study of the biogeophysical effects of past ALCCs on regional climate in north-western Europe suggests that deforestation between 6000 and 200 cal year BP may have caused significant change in winter and summer temperature. There is no indication that deforestation in the Baltic Sea area since AD 1850 would have been a major cause of the recent climate warming in the region through a positive biogeochemical feedback. Several model studies suggest that boreal reforestation might not be an effective climate warming mitigation tool as it might lead to increased warming through biogeophysical processes

The history of Shtokman field development

Let's twist again! The first highly enantioselective asymmetric reaction in which a chiral reaction medium is the sole source of chirality is presented. The aza‐Baylis–Hillman reaction in an ionic liquid with a chiral anion, whose design is based on mechanistic insights, gave products with up to 84 % ee

Environmental change during MIS4 and MIS 3 opened corridors in the Horn of Africa for <i>Homo sapiens</i> expansion

Archaeological findings, numerical human dispersal models and genome analyses suggest several time windows in the past 200 kyr (thousands of years ago) when anatomically modern humans (AMH) dispersed out of Africa into the Levant and/or Arabia. From close to the key hominin site of Omo-Kibish, we provide near continuous proxy evidence for environmental changes in lake sediment cores from the Chew Bahir basin, south Ethiopia. The data show highly variable hydroclimate conditions from 116 to 66 kyr BP with rapid shifts from very wet to extreme aridity. The wet phases coincide with the timing of the North African Humid Periods during MIS5, as defined by Nile discharge records from the eastern Mediterranean. The subsequent record at Chew Bahir suggests stable regional hydrological setting between 58 and 32 kyr (MIS4 and 3), which facilitated the development of more habitable ecosystems, albeit in generally dry climatic conditions. This shift, from more to less variable hydroclimate, may help account for the timing of later dispersal events of AMH out of Africa

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Wetlands are one of the most significant natural sources of methane (CH4) to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2). Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we developed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2 and oxygen (O2) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure, results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and an intercomparison of the modelled and measured CH4 fluxes at Siikaneva, a peatland flux measurement site in Southern Finland. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that 1) the model is flexible and robust and thus suitable for different environments; 2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; 3) the sensitivity of the total CH4 emission to other input variables, LAI and WTD, is mainly mediated via the O2 concentrations that affect the CH4 production and oxidation rates; 4) with given input respiration, the peat column description does not affect significantly the simulated CH4 emissions

Intra-Campaign Changes in Voting Preferences: The Impact of Media and Party Communication

An increasing number of citizens change and adapt their party preferences during the electoral campaign. We analyze which short-term factors explain intra-campaign changes in voting preferences, focusing on the visibility and tone of news media reporting and party canvassing. Our analyses rely on an integrative data approach, linking data from media content analysis to public opinion data. This enables us to investigate the relative impact of news media reporting as well as party communication. Inherently, we overcome previously identified methodological problems in the study of communication effects on voting behavior. Our findings reveal that campaigns matter: Especially interpersonal party canvassing increases voters’ likelihood to change their voting preferences in favor of the respective party, whereas media effects are limited to quality news outlets and depend on individual voters’ party ambivalence

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for