Amazonian deforestation causes systematic changes in regional dry season precipitation. Some of these changes at contemporary large scales (a few hundreds of kilometers) of deforestation have been associated with a ‘dynamical mesoscale circulation’, induced by the replacement of rough forest with smooth pasture. In terms of decadal averages, this dynamical mechanism yields increased precipitation in downwind regions and decreased precipitation in upwind regions of deforested areas. Daily, seasonal, and interannual variations in this phenomenon may exist, but have not yet been identified or explained. This study uses observations and numerical simulations to develop relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions across a range of time scales. It is found that the strength of the dynamical mechanism is primarily controlled by the regional-scale thermal and dynamical conditions of the boundary layer, and not by the continental- and global-scale atmospheric state. Lifting condensation level and wind speed within the boundary layer have large and positive correlations with the strength of the dynamical mechanism. The strength of these relationships depends on time scale and is strongest over the seasonal cycle. Overall, the dynamical mechanism is found to be strongest during times when the atmosphere is relatively stable. Hence, for contemporary large scales of deforestation this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially during the dry-to-wet transition), significantly affecting the hydroclimate during this period.
Battaglia, D. J.; Boyer, M. D.; Gerhardt, S.; Mueller, D.; Myers, C. E.; Guttenfelder, W.; Menard, J. E.; Sabbagh, S. A.; Scotti, F.; Bedoya, F.; Bell, R. E.; Berkery, J. W.; Diallo, A.; Ferraro, N.; Jaworski, M. A.; Kaye, S. M.; LeBlanc, B. P.; Ono, M.; Park, J. -K.; Podesta, M.; Raman, R.; Soukhanovskii, V.
Fractures in geological formations may enable migration of environmentally relevant fluids, as in leakage of CO2 through caprocks in geologic carbon sequestration. We investigated geochemically induced alterations of fracture geometry in Indiana Limestone specimens. Experiments were the first of their kind, with periodic high-resolution imaging using X-ray computed tomography (xCT) scanning while maintaining high pore pressure (100 bar). We studied two CO2-acidified brines having the same pH (3.3) and comparable thermodynamic
disequilibrium but different equilibrated pressures of CO2 (PCO2 values of 12 and 77 bar). High-PCO2 brine has a faster calcite dissolution kinetic rate because of the accelerating effect of carbonic acid. Contrary to expectations, dissolution extents were comparable in the two experiments. However, progressive xCT
images revealed extensive channelization for high PCO2, explained by strong positive feedback between ongoing flow and reaction. The pronounced channel increasingly directed flow to a small region of the fracture, which explains why the overall dissolution was lower than expected. Despite this, flow simulations revealed large increases in permeability in the high-PCO2 experiment. This study shows that the permeability evolution of dissolving fractures will be larger for faster-reacting fluids. The overall mechanism is not because more rock dissolves, as would be commonly assumed, but because of accelerated fracture channelization.
Small changes in word choice can lead to dramatically different interpretations of narratives. How does the brain accumulate and integrate such local changes to construct unique neural representations for different stories? In this study we created two distinct narratives by changing only a few words in each sentence (e.g. “he” to “she” or “sobbing” to “laughing”) while preserving the grammatical structure across stories. We then measured changes in neural responses between the two stories. We found that the differences in neural responses between the two stories gradually increased along the hierarchy of processing timescales. For areas with short integration windows, such as early auditory cortex, the differences in neural responses between the two stories were relatively small. In contrast, in areas with the longest integration windows at the top of the hierarchy, such as the precuneus, temporal parietal junction, and medial frontal cortices, there were large differences in neural responses between stories. Furthermore, this gradual increase in neural difference between the stories was highly correlated with an area’s ability to integrate information over time. Amplification of neural differences did not occur when changes in words did not alter the interpretation of the story (e.g. “sobbing” to “crying”). Our results demonstrate how subtle differences in words are gradually accumulated and amplified along the cortical hierarchy as the brain constructs a narrative over time.
Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
Abstract:
More than 20% Amazon rainforest has been cleared in the past three decades triggering important hydroclimatic changes. Small-scale (~few kilometers) deforestation in the 1980s has caused thermally-triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared to the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing a negligible role of large-scale climate variability. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry season hydroclimate. Our study illustrates the strong scale-sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally- to a dynamically-driven hydroclimatic regime.
Maingi, R.; Hu, J. S.; Sun, Z.; Tritz, K.; Zuo, G. Z.; Xu, W.; Huang, M.; Meng, X. C.; Canik, J. M.; Diallo, A.; Lunsford, R.; Mansfield, D. K.; Osborne, T. H.; Gong, X. Z.; Wang, Y. F.; Li, Y. Y.
Gan, K.; Ahn, J. -W.; Gray, T. K.; Zweben, S. J.; Fredrickson, E. D.; Scotti, F.; Maingi, R.; Park, J. -K.; Canal, G. P.; Soukhanovskii, V. A.; McLean, A. G.; Wirth, B. D.
Canal, G. P.; Ferraro, N. M.; Evans, T. E.; Osborne, T. H.; Menard, J. E.; Ahn, J. -W.; Maingi, R.; Wingen, A.; Ciro, D.; Frerichs, H.; Schmitz, O.; Soukhanovskii, V.; Waters, I.; Sabbagh, S. A.
Fredrickson, E. D.; Belova, E. V.; Battaglia, D. J.; Bell, R. E.; Crocker, N. A.; Darrow, D. S.; Diallo, A.; Gerhardt, S. P.; Gorelenkov, N. N.; LeBlanc, B. P.; Podesta, M.
Recent advances in experimental techniques have allowed the simultaneous recordings of
populations of hundreds of neurons, fostering a debate about the nature of the collective
structure of population neural activity. Much of this debate has focused on the
empirical findings of a phase transition in the parameter space of maximum entropy
models describing the measured neural probability distributions, interpreting this phase
transition to indicate a critical tuning of the neural code. Here, we instead focus on the
possibility that this is a first-order phase transition which provides evidence that the
real neural population is in a `structured', collective state. We show that this collective
state is robust to changes in stimulus ensemble and adaptive state. We find that the
pattern of pairwise correlations between neurons has a strength that is well within the
strongly correlated regime and does not require fine tuning, suggesting that this state is
generic for populations of 100+ neurons. We find a clear correspondence between the
emergence of a phase transition, and the emergence of attractor-like structure in the
inferred energy landscape. A collective state in the neural population, in which neural
activity patterns naturally form clusters, provides a consistent interpretation for our
results.
Our daily lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? In this study, participants viewed a fifty-minute audio-visual movie, then verbally described the events while undergoing functional MRI. These descriptions were completely unguided and highly detailed, lasting for up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated (movie-vs.-recall correlation) in default network, medial temporal, and high-level visual areas; moreover, individual event patterns were highly discriminable and similar between people during recollection (recall-vs.-recall similarity), suggesting the existence of spatially organized memory representations. In posterior medial cortex, medial prefrontal cortex, and angular gyrus, activity patterns during recall were more similar between people than to patterns elicited by the movie, indicating systematic reshaping of percept into memory across individuals. These results reveal striking similarity in how neural activity underlying real-life memories is organized and transformed in the brains of different people as they speak spontaneously about past events.
Does the default mode network (DMN) reconfigure to encode information about the changing environment? This question has proven difficult, because patterns of functional connectivity reflect a mixture of stimulus-induced neural processes, intrinsic neural processes and non-neuronal noise. Here we introduce inter-subject functional correlation (ISFC), which isolates stimulus-dependent inter-regional correlations between brains exposed to the same stimulus. During fMRI, we had subjects listen to a real-life auditory narrative and to temporally scrambled versions of the narrative. We used ISFC to isolate correlation patterns within the DMN that were locked to the processing of each narrative segment and specific to its meaning within the narrative context. The momentary configurations of DMN ISFC were highly replicable across groups. Moreover, DMN coupling strength predicted memory of narrative segments. Thus, ISFC opens new avenues for linking brain network dynamics to stimulus features and behaviour.
What mechanisms support our ability to estimate durations on the order of minutes? Behavioral studies in humans have shown that changes in contextual features lead to overestimation of past durations. Based on evidence that the medial temporal lobes and prefrontal cortex represent contextual features, we related the degree of fMRI pattern change in these regions with people's subsequent duration estimates. After listening to a radio story in the scanner, participants were asked how much time had elapsed between pairs of clips from the story. Our ROI analysis found that the neural pattern distance between two clips at encoding was correlated with duration estimates in the right entorhinal cortex and right pars orbitalis. Moreover, a whole-brain searchlight analysis revealed a cluster spanning the right anterior temporal lobe. Our findings provide convergent support for the hypothesis that retrospective time judgments are driven by 'drift' in contextual representations supported by these regions.
Maingi, R.; Canik, J. M.; Bell, R. E.; Boyle, D. P.; Diallo, A.; Kaita, R.; Kaye, S. M.; LeBlanc, B. P.; Sabbagh, S. A.; Scotti, F.; Soukhanovskii, V. A.
Kramer, G. J.; Bortolon, A.; Ferraro, N. M.; Spong, D. A.; Crocker, N. A.; Darrow, D. S.; Fredrickson, E. D.; Kubota, S.; Park, J.-K.; Podesta, M.; Heidbrink, W. W.
This dataset contains all the model output used to generate the figures and data reported in the article "Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone". The data was generated during spring 2015 using the a modified version of the Ecosystem Demography model version 2, provided as a supplement accompanying the article. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
It is well known that formation of new episodic memories depends on hippocampus, but in real-life settings (e.g., conversation), hippocampal amnesics can utilize information from several minutes earlier. What neural systems outside hippocampus might support this minutes-long retention? In this study, subjects viewed an audiovisual movie continuously for 25 min; another group viewed the movie in 2 parts separated by a 1-day delay. Understanding Part 2 depended on retrieving information from Part 1, and thus hippocampus was required in the day-delay condition. But is hippocampus equally recruited to access the same information from minutes earlier? We show that accessing memories from a few minutes prior elicited less interaction between hippocampus and default mode network (DMN) cortical regions than accessing day-old memories of identical events, suggesting that recent information was available with less reliance on hippocampal retrieval. Moreover, the 2 groups evinced
reliable but distinct DMN activity timecourses, reflecting differences in information carried in these regions when Part 1 was recent versus distant. The timecourses converged after 4 min, suggesting a time frame over which the continuous-viewing group may have relied less on hippocampal retrieval. We propose that cortical default mode regions can intrinsically retain real-life episodic information for several minutes.
Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
Abstract:
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.
This dataset contains all the data, model and MATLAB codes used to generate the figures and data reported in the article (DOI: 10.1002/2014JD022278). The data was generated during September 2013 and February 2014 using the Ocean-Land-Atmosphere Model also provided with this package. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
Complete dataset of pore water chemical parameters measured at the Marsh Resource Meadowlands Mitigation Bank, a tidal marsh within the New Jersey Meadowlands, from March 2011 to April 2012. Analytes measured include dissolved methane, sulfate, dissolved organic carbon, temperature, salinity, and pH. Measurements were conducted using porewater dialysis samplers, and water was sampled from the surface to a depth of 60 cm.
The Magnetospheric Multiscale (MMS) mission has given us unprecedented access to high cadence particle and field data of magnetic reconnection at Earth's magnetopause. MMS first passed very near an X-line on 16 October 2015, the Burch event, and has since observed multiple X-line crossings. Subsequent 3D particle-in-cell (PIC) modeling efforts of and comparison with the Burch event have revealed a host of novel physical insights concerning magnetic reconnection, turbulence induced particle mixing, and secondary instabilities. In this study, we employ the Gkeyll simulation framework to study the Burch event with different classes of extended, multi-fluid magnetohydrodynamics (MHD), including models that incorporate important kinetic effects, such as the electron pressure tensor, with physics-based closure relations designed to capture linear Landau damping. Such fluid modeling approaches are able to capture different levels of kinetic physics in global simulations and are generally less costly than fully kinetic PIC. We focus on the additional physics one can capture with increasing levels of fluid closure refinement via comparison with MMS data and existing PIC simulations. In particular, we find that the ten-moment model well captures the agyrotropic structure of the pressure tensor in the vicinity of the X-line and the magnitude of anisotropic electron heating observed in MMS and PIC simulations. However, the ten-moment model has difficulty resolving the lower hybrid drift instability, which has been observed to plays a fundamental role in heating and mixing electrons in the current layer.
