Drivers and mechanisms of tree mortality in moist tropical forests

Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO2 fertilization-induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large-scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change

Predicting risk of readmission in heart failure patients using electronic health records

This thesis research investigates the prediction of readmission risk in heart failure patients using their electronic health record (EHR) data from previous hospitalizations. We examine three primary questions. First, we study the use of attention mechanism in readmission prediction model based on long short-term memory(LSTM) networks and investigate the interpretability it offers regarding the importance of critical time during the visit in readmission prediction. Second given that, generally dataset is curated by combining data from multiple hospitals we investigate model generalization across multiple sites. Finally since in real life scenario model will be trained on past data and used to predict future readmission events, we further investigate model generalization across time. Along with those things, model performance across different endpoints will be studied

The effect of positive episodic simulation on future event predictions in non-depressed, dysphoric, and depressed individuals

Previous research demonstrates that depressed individuals have difficulties with prospection. For example, compared to non-depressed individuals, they predict negative events as more likely to happen, and positive events as less likely to happen, in their future. Recent work suggests that episodic simulation of positive events may prove a useful strategy for improving these prospective biases. The experiments within the current thesis investigated positive episodic simulation as a method of modifying predictions regarding likelihood of occurrence, perceived control, and importance for both positive and negative future events. Experiments 1 and 2 demonstrated the positive impact of a newly devised paradigm, the Future Simulation Intervention Task (F-SIT), on future event predictions in a non-depressed sample. Experiment 3 investigated the parameters under which the F-SIT modifies these predictions, by using various modifications of the paradigm. These findings suggested that both single cue words with positive instructions, and positive cue scenarios were equally effective at modifying future event predictions. Experiments 4 and 5 extended the findings to show that various versions of the F-SIT beneficially modifies predictions in both a depressed and dysphoric sample. Finally, Experiment 5 also made preliminary investigations into the mechanisms that underlie the modifications evident following the F-SIT, specifically investigating the role of affect. Findings suggested that the modification in predictions about future events that occur as a result of the F-SIT are not merely a by-product of mood improvements. Therefore, the underlying mechanisms of the prediction modification is in need of further investigation. However, overall, the findings from the current experiments suggest that training in future episodic simulation can improve future outlook and may represent a useful tool within cognitive therapeutic techniques

Murphy Scale: A Locational Equivalent Intensity Scale for Hazard Events

Empirical cross-hazard analysis and prediction of disaster vulnerability, resilience, and risk requires a common metric of hazard strengths across hazard types. In this paper, the authors propose an equivalent intensity scale for cross-hazard evaluation of hazard strengths of events for entire durations at locations. The proposed scale is called the Murphy Scale, after Professor Colleen Murphy. A systematic review and typology of hazard strength metrics is presented to facilitate the delineation of the defining dimensions of the proposed scale. An empirical methodology is introduced to derive equivalent intensities of hazard events on a Murphy Scale. Using historical data on impacts and hazard strength indicators of events from 2013 to 2017, the authors demonstrate the utility of the proposed methodology for computing the equivalent intensities for earthquakes and tropical cyclones. As part of a new area of research called hazard equivalency, the proposed Murphy Scale paves the way toward creating multi-hazard hazard maps. The proposed scale can also be leveraged to facilitate hazard communication regarding past and future local experiences of hazard events for enhancing multi-hazard preparedness, mitigation, and emergency response

Blocking and its response to climate change

Purpose of review: Atmospheric blocking events represent some of the most high-impact weather patterns in the mid-latitudes, yet they have often been a cause for concern in future climate projections. There has been low confidence in predicted future changes in blocking, despite relatively good agreement between climate models on a decline in blocking. This is due to the lack of a comprehensive theory of blocking and a pervasive underestimation of blocking occurrence by models. This paper reviews the state of knowledge regarding blocking under climate change, with the aim of providing an overview for those working in related fields. Recent Findings: Several avenues have been identified by which blocking can be improved in numerical models, though a fully reliable simulation remains elusive (at least, beyond a few days lead time). Models are therefore starting to provide some useful information on how blocking and its impacts may change in the future, although deeper understanding of the processes at play will be needed to increase confidence in model projections. There are still major uncertainties regarding the processes most important to the onset, maintenance and decay of blocking and advances in our understanding of atmospheric dynamics, for example in the role of diabatic processes, continue to inform the modelling and prediction efforts. Summary: The term ‘blocking’ covers a diverse array of synoptic patterns, and hence a bewildering range of indices has been developed to identify events. Results are hence not considered fully trustworthy until they have been found using several different methods. Examples of such robust results are the underestimation of blocking by models, and an overall decline in future occurrence, albeit with a complex regional and seasonal variation. In contrast, hemispheric trends in blocking over the recent historical period are not supported by different methods, and natural variability will likely dominate regional variations over the next few decades

Methods for anticipating governance breakdown and violent conflict

In this paper, authors Sarah Bressan, Håvard Mokleiv Nygård, and Dominic Seefeldt present the evolution and state of the art of both quantitative forecasting and scenario-based foresight methods that can be applied to help prevent governance breakdown and violent conflict in Europe’s neighbourhood. In the quantitative section, they describe the different phases of conflict forecasting in political science and outline which methodological gaps EU-LISTCO’s quantitative sub-national prediction tool will address to forecast tipping points for violent conflict and governance breakdown. The qualitative section explains EU-LISTCO’s scenario-based foresight methodology for identifying potential tipping points. After comparing both approaches, the authors discuss opportunities for methodological advancements across the boundaries of quantitative forecasting and scenario-based foresight, as well as how they can inform the design of strategic policy options

Sector CO2 and SOx emissions efficiency and investment: homogeneous vs heterogeneous estimates using the Italian NAMEA

The relationships between emissions ad economic drivers differ substantially both across countries and across sectors. In this paper I investigate cross-sector heterogeneity of emissions (CO2 and SOx) / investments relationships of Italian branches for the period 1990-2006 by using the Italian NAMEA (National Accounting Matrix including Environmental Accounts). The ‘environmental’ direction of investments in different types of capital goods is crucial in the prediction of future patterns of environmental efficiency due to the persistence of the choices regarding the features of the capital stock. Within this relationship, the role of variations in prices of energy fuels and in environmental taxes is considered to identify relevance and the direction of the technical changes induced by prices and taxes. I compare homogeneous estimates (FE) with heterogeneous estimates (SUR): homogeneity of slopes across branches is always rejected (aggregation bias). Furthermore, results differ substantially between CO2 and SOx, due to different environmental and economic features of the two types of emissions. Results show a relevant role of economic forces (investments) in explaining CO2 dynamics while SOx trends are determined to higher extent by exogenous events. The potential role of ICTs in promoting more environmental efficient production processes has not been exploited yet by Italian manufacturing sectors.NAMEA; SUR; eco-innovation; emissions efficiency