21 resultados para integrated-process model
Resumo:
The development of northern high-latitude peatlands played an important role in the carbon (C) balance of the land biosphere since the Last Glacial Maximum (LGM). At present, carbon storage in northern peatlands is substantial and estimated to be 500 ± 100 Pg C (1 Pg C = 1015 g C). Here, we develop and apply a peatland module embedded in a dynamic global vegetation and land surface process model (LPX-Bern 1.0). The peatland module features a dynamic nitrogen cycle, a dynamic C transfer between peatland acrotelm (upper oxic layer) and catotelm (deep anoxic layer), hydrology- and temperature-dependent respiration rates, and peatland specific plant functional types. Nitrogen limitation down-regulates average modern net primary productivity over peatlands by about half. Decadal acrotelm-to-catotelm C fluxes vary between −20 and +50 g C m−2 yr−1 over the Holocene. Key model parameters are calibrated with reconstructed peat accumulation rates from peat-core data. The model reproduces the major features of the peat core data and of the observation-based modern circumpolar soil carbon distribution. Results from a set of simulations for possible evolutions of northern peat development and areal extent show that soil C stocks in modern peatlands increased by 365–550 Pg C since the LGM, of which 175–272 Pg C accumulated between 11 and 5 kyr BP. Furthermore, our simulations suggest a persistent C sequestration rate of 35–50 Pg C per 1000 yr in present-day peatlands under current climate conditions, and that this C sink could either sustain or turn towards a source by 2100 AD depending on climate trajectories as projected for different representative greenhouse gas concentration pathways.
Resumo:
Nitrous oxide (N2O) is an important greenhouse gas and ozone-depleting substance that has anthropogenic as well as natural marine and terrestrial sources. The tropospheric N2O concentrations have varied substantially in the past in concert with changing climate on glacial–interglacial and millennial timescales. It is not well understood, however, how N2O emissions from marine and terrestrial sources change in response to varying environmental conditions. The distinct isotopic compositions of marine and terrestrial N2O sources can help disentangle the relative changes in marine and terrestrial N2O emissions during past climate variations. Here we present N2O concentration and isotopic data for the last deglaciation, from 16,000 to 10,000 years before present, retrieved from air bubbles trapped in polar ice at Taylor Glacier, Antarctica. With the help of our data and a box model of the N2O cycle, we find a 30 per cent increase in total N2O emissions from the late glacial to the interglacial, with terrestrial and marine emissions contributing equally to the overall increase and generally evolving in parallel over the last deglaciation, even though there is no a priori connection between the drivers of the two sources. However, we find that terrestrial emissions dominated on centennial timescales, consistent with a state-of-the-art dynamic global vegetation and land surface process model that suggests that during the last deglaciation emission changes were strongly influenced by temperature and precipitation patterns over land surfaces. The results improve our understanding of the drivers of natural N2O emissions and are consistent with the idea that natural N2O emissions will probably increase in response to anthropogenic warming.
Resumo:
Several componential emotion theories suggest that appraisal outcomes trigger characteristic somatovisceral changes that facilitate information processing and prepare the organism for adaptive behavior. The current study tested predictions derived from Scherer's Component Process Model. Participants viewed unpleasant and pleasant pictures (intrinsic pleasantness appraisal) and were asked to concurrently perform either an arm extension or an arm flexion, leading to an increase or a decrease in picture size. Increasing pleasant stimuli and decreasing unpleasant stimuli were considered goal conducive; decreasing pleasant stimuli and increasing unpleasant stimuli were considered goal obstructive (goal conduciveness appraisal). Both appraisals were marked by several somatovisceral changes (facial electromyogram, heart rate (HR)). As predicted, the changes induced by the two appraisals showed similar patterns. Furthermore, HR results, compared with data of earlier studies, suggest that the adaptive consequences of both appraisals may be mediated by stimulus proximity.
Resumo:
In the context of a memory task, participants were presented with pictures displaying biological and cultural threat stimuli or neutral stimuli (stimulus relevance manipulation) with superimposed symbols signaling monetary gains or losses (goal conduciveness manipulation). Results for heart rate and facial electromyogram show differential efferent effects of the respective appraisal outcomes and provide first evidence for sequential processing, as postulated by Scherer's component process model of emotion. Specifically, as predicted, muscle activity over the brow and cheek regions marking the process of relevance appraisal occurred significantly earlier than facial muscle activity markers of goal conduciveness appraisal. Heart rate, in contrast, was influenced by the stimulus relevance manipulation only.
Resumo:
The phenomenon of portfolio entrepreneurship has attracted considerable scholarly attention and is particularly relevant in the family fi rm context. However, there is a lack of knowledge of the process through which portfolio entrepreneurship develops in family firms. We address this gap by analyzing four in-depth, longitudinal family firm case studies from Europe and Latin America. Using a resource-based perspective, we identify six distinct resource categories that are relevant to the portfolio entrepreneurship process. Furthermore, we reveal that their importance varies across time. Our resulting resource-based process model of portfolio entrepreneurship in family firms makes valuable contributions to both theory and practice.
Resumo:
Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.