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Empirical evaluations of the ecological processes that enhance or dampen the likelihood of shifts between top-down (i.e., predator-driven) and bottom-up (i.e., resource-driven) forcing are essential to understanding the potential for cascading effects that can underpin community functioning, productivity, and stability. This suite of research used an extraordinary herbivore-outbreak in kelp forests along the central coast of California as a natural field setting to disentangle: (1) how alternations in the foraging behavior of a primary consumer drives patch state transition dynamics, (2) whether predation or resource abundance are the predominant drivers of community regulation, and (3) community-wide consequences to the formation of alternative ecosystem states. This dissertation was motived by a rapid and dramatic decline in the abundance of a sea star predator (Pycnopodia helianthoides) of sea urchins, and a decline of a primary producer (Macrocystis pyrifera, ‘kelp’) that initiated a fundamental change in purple sea urchin (Strongylocentrotus purpuratus) foraging behavior and condition, resulting in a spatial mosaic of remnant kelp forests interspersed with patches of sea urchin barrens. In Chapter 1, I demonstrate the important role of grazer behavior in mediating switching among patch states. I show that the 2014 sea urchin outbreak along the Monterey Peninsula, California, USA is explicable by a shift in sea urchin grazing behavior, not by a demographic (i.e., recruitment or survivorship) response. During this six-year study, kelp forests recovered to an area that was once an expansive sea urchin barren. I show that this remarkable recovery of kelp forests in 2019 to an area in deep water was evidenced by sea urchin movement to shallow water. These results highlight the role of grazer behavior in facilitating patch transition dynamics. In Chapter 2, I demonstrate how the behavioral response of an apex predator to changes in prey behavior and condition can dramatically alter the role and relative contribution of top-down forcing, depending on the spatial organization of ecosystem states. I show that the mosaic of adjacent alternative ecosystem states led to an increase in the number of sea otters (Enhydra lutris nereis) specializing on urchin prey, a population-level increase in urchin consumption, and an increase in sea otter survivorship. I further show that the spatial distribution of sea otter foraging effort for urchin prey was not directly linked to high prey density, but rather was predicted by energetically profitable prey patches. Finally, in Chapter 3 I examine whether the spatial mosaic of sea urchin barrens interspersed with remnant patches of kelp forest resulted in a departure of community structure from the long-standing configuration that proceeded the formation of the mosaic. I found that beginning in 2013, many sites across the study region departed from a common multivariate (“forested”) state, which had persisted for the previous six-years, and drifted into a new multivariate configuration (“urchin barrens”). Although sites trended toward a common reconfiguration, community trajectories were highly variable, and sites exhibited regional cohesion in their trajectories (Carmel, Monterey Bay). These results suggest that outbreaks of grazers associated with punctuated environmental (e.g., marine heatwaves) and biotic (loss of predators, sea urchin outbreaks) perturbations can drive apparently stable kelp forest communities to alternative potentially stable states. Collectively, the results of this dissertation highlight how patch dynamics, behavioral responses, and biotic and environmental perturbations underpin the structure and stability of ecosystems.

Spatial analysis of industrial locations is an important tool for cluster-based economic development that helps identify hot spots for attracting new businesses in a particular region. The forest product industry in North Carolina (NC) is the top employer among all manufacturing sectors, with a substantial contribution to the state economy. Using geographic information system tools, we examined the current spatial distribution of the primary and secondary forest product manufacturers (FPM) and available forest resources to identify major hot spots in NC. Additionally, by estimating count data models, this study evaluated factors influencing the location of FPMs across counties in NC. Our results suggested that primary FPMs exhibit a higher spatial dependency relative to secondary FPMs. Similarly, regression results suggested that the counties near cities with high population, hot spots of raw materials, and better county economy are more likely to host both primary and secondary FPMs in the counties of NC. The findings of this study shed light on how the clustering of forest product manufacturing firms may influence competition between FPMs, sustainable supply of raw materials, and supply-chain networks in forest-dependent rural regions.

Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n=1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n=911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r=0.13, p=0.000012, pFDR=0.000052), as did the reciprocal analysis (r=0.09, p=0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p=3.24 x 10-8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p=0.00047, pFDR=0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.

Large proportions of smokers are unsuccessful in evidence-based smoking cessation treatment and identifying prognostic predictors may inform improvements in treatment. Steep discounting of delayed rewards (delay discounting) is a robust predictor of poor smoking cessation outcome, but the underlying neural predictors have not been investigated. Forty-one treatment-seeking adult smokers completed a functional magnetic resonance imaging (fMRI) delay discounting paradigm prior to initiating a 9-week smoking cessation treatment protocol. Behavioral performance significantly predicted treatment outcomes (verified 7-day abstinence, n = 18; relapse, n = 23). Participants in the relapse group exhibited smaller area under the curve (d = 1.10) and smaller AUC was correlated with fewer days to smoking relapse (r = .56, p

While the neuroanatomical correlates of impulsivity in youths have been examined, there is little research on whether those correlates are consistent across childhood/adolescence. The current study uses data from the age 11/12 (N = 7083) visit of the Adolescent Brain Cognitive Development (ABCD) Study to investigate the replicability of the neuroanatomical correlates of impulsive personality traits identified at age 9/10. Neuroanatomy was measured using structural and diffusion magnetic resonance imaging and impulsive personality was measured using the UPPS-P Impulsive Behavior Scale. Replicability was quantified using the Open Science Foundation replication criteria, intraclass correlations, and elastic net regression modeling to make predictions across timepoints. Replicability was highly variable among traits: the neuroanatomical correlates of positive urgency showed substantial similarity between ages 9/10 and 11/12, negative urgency and sensation seeking, showed moderate similarity across ages, and (lack of) premeditation and perseverance showed substantial dissimilarity across ages. In all cases, effect sizes were small. These findings suggest that, even for studies with large samples sizes and the same participant pool, the replicability of brain-behavior correlations cannot be assumed. However, they also highlight an array of neuroanatomical structures that may be important to impulsive personality traits across development from childhood into adolescence.

We previously reported that CAP1 (Cyclase-Associated Protein 1) regulates matrix adhesion in mammalian cells through FAK (Focal Adhesion Kinase). More recently, we discovered a phosphor-regulation mechanism for CAP1 through the Ser307/Ser309 tandem site that is of critical importance for all CAP1 functions. However, molecular mechanisms underlying the CAP1 function in adhesion and its regulation remain largely unknown. Here we report that Rap1 also facilitates the CAP1 function in adhesion, and more importantly, we identify a novel signaling pathway where CAP1 mediates the cAMP signals, through the cAMP effectors Epac (Exchange proteins directly activated by cAMP) and PKA (Protein Kinase A), to activate Rap1 in stimulating matrix adhesion in colon cancer cells. Knockdown of CAP1 led to opposite adhesion phenotypes in SW480 and HCT116 colon cancer cells, with reduced matrix adhesion and reduced FAK and Rap1 activities in SW480 cells while it stimulated matrix adhesion as well as FAK and Rap1 activities in HCT116 cells. Importantly, depletion of CAP1 abolished the stimulatory effects of the cAMP activators forskolin and isoproterenol, as well as that of Epac and PKA, on matrix adhesion in both cell types. Our results consistently support a required role for CAP1 in the cAMP activation of Rap1. Identification of the key role for CAP1 in linking the major second messenger cAMP to activation of Rap1 in stimulating adhesion, which may potentially also regulate proliferation in other cell types, not only vertically extends our knowledge on CAP biology, but also carries important translational potential for targeting CAP1 in cancer therapeutics.

Background People with certain underlying respiratory and cardiovascular conditions might be at an increased risk for severe illness from COVID-19. Diesel Particulate Matter (DPM) exposure may affect the pulmonary and cardiovascular systems. The study aims to assess if DPM was spatially associated with COVID-19 mortality rates across three waves of the disease and throughout 2020. Methods We tested an ordinary least squares (OLS) model, then two global models, a spatial lag model (SLM) and a spatial error model (SEM) designed to explore spatial dependence, and a geographically weighted regression (GWR) model designed to explore local associations between COVID-19 mortality rates and DPM exposure, using data from the 2018 AirToxScreen database. Results The GWR model found that associations between COVID-19 mortality rate and DPM concentrations may increase up to 77 deaths per 100,000 people in some US counties for every interquartile range (0.21 μg/m3) increase in DPM concentration. Significant positive associations between mortality rate and DPM were observed in New York, New Jersey, eastern Pennsylvania, and western Connecticut for the wave from January to May, and in southern Florida and southern Texas for June to September. The period from October to December exhibited a negative association in most parts of the US, which seems to have influenced the year-long relationship due to the large number of deaths during that wave of the disease. Conclusions Our models provided a picture in which long-term DPM exposure may have influenced COVID-19 mortality during the early stages of the disease. That influence appears to have waned over time as transmission patterns evolved.

This is the first record of a fish nidovirus isolated from a consignment of goldfish at the United Kingdom (UK) border. The full-length viral genome was 25,985 nt, sharing a 97.9% nucleotide identity with the Chinook salmon bafinivirus (CSBV) NIDO with two deletions of 537 and 480 nt on the ORF Ia protein. To assess the potential impact on UK fish species, Atlantic salmon, common carp and goldfish were exposed to the virus via an intraperitoneal (IP) injection and bath challenge. Moribundity was recorded in only 8% of IP-injected goldfish. A high viral load, &asymp, 107 of the CSBV PpIa gene, was measured in the kidney of moribund goldfish. Mild histopathological changes were observed in the kidneys of challenged carps. Ultrastructural observations in renal tubule epithelial cells of goldfish showed cylindrical tubes (&asymp, 15 nm in diameter) and tubular structures budding spherical virions (&asymp, 200 nm in diameter) with external spike-like structures. Negative staining showed both circular and bacilliform virions. Seroconversion was measured in common carp and goldfish but not in Atlantic salmon. This study reinforces the potential risk of novel and emerging pathogens being introduced to recipient countries via the international ornamental fish trade and the importance of regular full health screens at the border inspection posts to reduce this risk.

Background: Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. Methods: The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Results: Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Conclusions: Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. UPPS-P traits tended to account for relatively little variance in neuroanatomy (i.e., model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples.

The National Research Council’s Healthcare Comes Home Report encourages system engineering involvement in homecare research and development to provide medical device designers information on demands associated with homecare and the capabilities needed for non-clinical caregivers to perform successfully The objective of this study was to develop invasive therapy evaluation techniques with human factors considerations for pediatric medical devices, specifically home parenteral nutrition and home mechanical ventilation, to minimize undesirable outcomes in non-clinical settings. The method used was the case study approach to qualitative research through expert interviews, environmental observations and document review data collection methods as well as cross-case themes analysis. This discussion reviews the rated impact of human factors consideration on the safety and effectiveness outcomes of invasive therapy devices use on pediatric patients in non-clinical environment.

Techniques of optical superresolution imaging are vital for uncovering the complex dynamics of biochemistry in cellular environments. However the practical resolution for superresolution imaging is limited by the increased photon budget for superresolution, compared with conventional microscopy. For this reason it is important to determine the optimal methods for analysing all of the incoming information. Most approaches to microscopy use only the wave-like properties of light, but the particle-like nature of light provides extra information that is normally inaccessible and can be used to increase imaging resolution. Here we theoretically study the localisation of quantum emitters using higher-order quantum correlation functions to understand the resolution that is practically achievable for bio-imaging tasks. We show explicit imaging results for varying number of emitters as a function of correlation order to illustrate the necessary tradeoffs between imaging resolution and acquisition time.

Numerous land surface phenology (LSP) datasets have been produced from various coarse resolution satellite data and different detection algorithms from regional to global scales. In contrast to field-observed phenological events that are defined by clearly evident organismal changes with biophysical meaning, current approaches to detecting transitions in LSP only determine the timing of variations in remotely sensed observations of surface greenness. Since activities to bridge LSP and field observations are challenging and limited, our understanding of the biophysical characteristics of LSP transitions is poor. Therefore, we set out to explore the scaling effects on LSP transitions at the nominal start of growing season (SOS) by comparing detections from coarse resolution data with those from finer resolution imagery. Specifically, using a hybrid piecewise-logistic-model-based LSP detection algorithm, we detected SOS in the agricultural core of the United States—central Iowa—at two scales: first, at a finer scale (30 m) using reflectance generated by fusing MODIS data with Landsat 8 OLI data (OLI SOS) and, second, at a coarser resolution of 500 m using Visible Infrared Imaging Radiometer Suite (VIIRS) observations. The VIIRS SOS data were compared with OLI SOS that had been aggregated using a percentile approach at various degrees of heterogeneity. The results revealed the complexities of SOS detections and the scaling effects that are latent at the coarser resolution. Specifically, OLI SOS variation defined using standard deviation (SD) was as large as 40 days within a highly spatially heterogeneous VIIRS pixel; whereas, SD could be 60% of OLI pixels within a homogeneous VIIRS pixel, but in

SummaryIn late 2018, unusual patterns of very high mortality (>50% production) were reported in intensive tilapia cage culture systems across Lake Volta in Ghana. Samples of fish and fry were collected and analysed from two affected farms between October 2018 and February 2019. Affected fish showed darkening, erratic swimming and abdominal distension with associated ascites. Histopathological observations of tissues taken from moribund fish at different farms revealed lesions indicative of viral infection. These included haematopoietic cell nuclear and cytoplasmic pleomorphism with marginalisation of chromatin and fine granulation. Transmission electron microscopy showed cells contained conspicuous virions with typical Iridovirus morphology i.e. enveloped, with icosahedral and or polyhedral geometries and with a diameter c.160 nm. PCR confirmation and DNA sequencing identified the virions as Infectious Spleen and Kidney Necrosis Virus (ISKNV). Samples of fry and older animals were all strongly positive for the presence of the virus by qPCR. All samples tested negative for TiLV and Nodavirus by qPCR. All samples collected from farms prior to the mortality event were negative for ISKNV. Follow up testing of fish and fry sampled from 5 additional sites in July 2019 showed all farms had fish that were PCR positive for ISKNV, whether there was active disease on the farm or not, demonstrating the disease was endemic to farms all over Lake Volta by that point. The results suggest that ISKNV was the cause of disease on the investigated farms and likely had a primary role in the mortality events. A common observation of coinfections with Streptococcus agalactiae and other tilapia bacterial pathogens further suggests that these may interact to cause severe pathology, particularly in larger fish. Results demonstrate that there are a range of potential threats to the sustainability of tilapia aquaculture that need to be guarded against.

Pancreatic cancer has the worst prognosis among major malignancies, largely due to its highly invasive property and difficulty in early detection. Mechanistic insights into cancerous transformation and especially metastatic progression are imperative for developing novel treatment strategies. The actin-regulating protein CAP1 is implicated in human cancers, while the role still remains elusive. In this study, we investigated roles for CAP1 and its phosphor-regulation in pancreatic cancer cells. No evidence supports remarkable up-regulation of CAP1 in the panel of cancer cell lines examined. However, knockdown of CAP1 in cancer cells led to enhanced stress fibers, reduced cell motility and invasion into Matrigel. Phosphorylation of CAP1 at the S308/S310 tandem regulatory site was elevated in cancer cells, consistent with hyper-activated GSK3 reported in pancreatic cancer. Inhibition of GSK3, a kinase for S310, reduced cell motility and invasion. Moreover, phosphor mutants had defects in alleviating actin stress fibers and rescuing the reduced invasiveness in the CAP1-knockdown PANC-1 cells. These results suggest a required role for transient phosphorylation for CAP1 function in controlling cancer cell invasiveness. Depletion of CAP1 also reduced FAK activity and cell adhesion, but did not cause significant alterations in ERK or cell proliferation. CAP1 likely regulates cancer cell invasiveness through effects on both actin filament turnover and cell adhesion. Finally, the growth factor PDGF induced CAP1 dephosphorylation, suggesting CAP1 may mediate extracellular signals to control cancer cell invasiveness. These findings may ultimately help develop strategies targeting CAP1 or its regulatory signals for controlling the invasive cycle of the disease.

This study is a replication of an existing large study (N = 507) on the surface-based morphometric correlates of Five-Factor Model (FFM) personality traits. The same methods were used as the original study in another large sample drawn from the same population (N = 597) with results then being aggregated from both samples (N = 1104), providing the largest investigation into the neuroanatomical correlates of FFM personality traits to date. Clusters of association between brain morphometry and each FFM trait are reported. For Neuroticism, Agreeableness, Openness, and Conscientiousness clusters of association were found in the dorsolateral prefrontal cortex for at least one morphometric index. Morphometry in various other regions was also associated with each personality trait. While some regions found in the original study were confirmed in the replication and full samples, others were not, highlighting the importance of replicating even high-quality, well-powered studies. Effect sizes were very similar in the replication and whole samples as those found in the original study. As a whole, the current results provide the strongest evidence to date on the neuroanatomical correlates of personality and highlights challenges in using this approach to understanding the neural correlates of personality.

Background: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth. Methods: Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g., demographics) and potentially modifiable (e.g., psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9-10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.Results: The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e., nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex. Conclusions: Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.

Although personality traits have been linked to internalizing and externalizing psychopathology,the extent to which these traits and psychopathological phenotypes share a commonneuroanatomical structure is unclear. To address this gap, we used structural neuroimaging andself-report data from 1104 participants in the Human Connectome Project to characterize theneuroanatomical correlates of Five Factor Model (FFM) traits. We generated neuroanatomicalprofiles (NAPs) of FFM traits and psychopathology indices based on the thickness and surfacearea of each cortical region in the Desikan atlas. We used a profile matching approach tocompare the absolute similarity of the FFM trait NAPs and psychopathology index NAPs.Evaluating the individual regions in the NAPs suggest that FFM traits show small associationswith thickness and surface area in brain regions throughout the cortex, with prefrontal regionsbeing the most strongly related to multiple personality traits. Profile matching analyses indicatedthat the NAPs derived from Neuroticism and Extraversion demonstrated large absolutesimilarities to the NAPs of internalizing psychopathology. Similarly, the NAPs of Agreeablenessand Conscientiousness showed medium to large relations with the NAPs of externalizingpsychopathology. These results suggest that similar neuroanatomical correlates underlie specificpersonality traits and symptoms of psychopathology, providing support for dimensional modelsthat incorporate personality traits into the etiology and manifestation of psychopathology.

The growing numbers of land change models makes it difficult to select a model at the beginning of an analysis, and is often arbitrary and at the researcher’s discretion. How to select a model at the beginning of an analysis, when multiple are suitable, represents a critical research gap currently understudied, where trade-offs of choosing one model over another are often unknown. Repeatable methods are needed to conduct cross-model comparisons to understand the trade-offs among models when the same calibration and validation data are used. Several methods to assess accuracy have been proposed that emphasize quantity and allocation, while overlooking the accuracy with which a model simulates the spatial configuration (e.g., size and shape) of map categories across landscapes. We compared the quantity, allocation, and configuration accuracy of four inductive pattern-based spatial allocation land change models (SLEUTH, GEOMOD, Land Change Modeler (LCM), and FUTURES). We simulated urban development with each model using identical input data from ten counties surrounding the growing region of Charlotte, North Carolina. Maintaining the same input data, such as land cover, drivers of change, and projected quantity of change, reduces differences in model inputs and allows for focus on trade-offs in different types of model accuracy. Results suggest that these four land change models produce representations of urban development with substantial variance, where some models may better simulate quantity and allocation at the trade-off of configuration accuracy, and vice versa. Trade-offs in accuracy exist with respect to the amount, spatial allocation, and landscape configuration of each model. This comparison exercise illustrates the range of accuracies for these models, and demonstrates the need to consider all three types of accuracy when assessing land change model’s projections.

Password managers address the usability challenge of authentication, i.e., to manage the effort in creating, memorising, and entering complex passwords for an end-user. Offering features such as creating strong passwords, managing increasing number of complex passwords, and auto-filling of passwords for variable contexts, their security is as critical as the assets being protected by the passwords. Previous security risk analyses have focused primarily on cloud- and browser-based password managers, whilst the security risks of local password managers were left under-explored. Taking a systematic forensic analysis approach, this paper reports on a case study of three popular local password managers: KeePass (v2.28), Password Safe (v3.35.1) and RoboForm (v7.9.12). It revealed risks that either the master password or the content of the password database could be found unencrypted in Temp folders, Page files or Recycle bin, even after applications had been closed. As a consequence, an attacker or a malware with access to the computer on which the password managers were running may be able to steal sensitive information, even though these password managers are meant to keep the databases encrypted and protected at all times. These findings point to directions to mitigate the identified risks.

A new potentiometric oxygen sensor is proposed, based on the mixed potential of zinc in a chloride electrolyte. Variations in the sensor potential with oxygen concentration are the direct result of changes in the corrosion rate of the zinc electrode due to diffusion-limited reduction of oxygen at its surface. For static concentration measurements, the performance of the new (potentiometric) sensor is essentially equivalent to that of a traditional (amperometric) Clark sensor. For transient measurements, however, the response of the potentiometric sensor can be considerably faster than the analogous amperometric sensor, due to the sensitivity of the potentiometric method to logarithmic (rather than linear) variations in oxygen concentration.

Hydrogen is seen as the future automobile energy storage media due to its inherent cleanliness upon oxidation and its ready utilization in fuel cell applications. Its physical storage in light weight, low volume systems is a key technical requirement. In searching for ever higher gravimetric and volumetric density hydrogen storage materials and systems, it is inevitable that higher energy density materials will be studied and used. To make safe and commercially acceptable systems, it is important to understand quantitatively, the risks involved in using and handling these materials and to develop appropriate risk mitigation strategies to handle unforeseen accidental events. To evaluate these materials and systems, an IPHE sanctioned program was initiated in 2006 partnering laboratories from Europe, North America and Japan. The objective of this international program is to understanding the physical risks involved in synthesis, handling and utilization of solid state hydrogen storage materials and to develop methods to mitigate these risks. This understanding will support ultimate acceptance of commercially high density hydrogen storage system designs. An overview of the approaches to be taken to achieve this objective will be given. Initial experimental results will be presented on environmental exposure of NaAlH{sub 4}, a candidate high density hydrogen more » storage compound. The tests to be shown are based on United Nations recommendations for the transport of hazardous materials and include air and water exposure of the hydride at three hydrogen charge levels in various physical configurations. Additional tests developed by the American Society for Testing and Materials were used to quantify the dust cloud ignition characteristics of this material which may result from accidental high energy impacts and system breach. Results of these tests are shown along with necessary risk mitigation techniques used in the synthesis and fabrication of a prototype hydrogen storage system. « less