Operationalizing the social-ecological systems framework to assess sustainability.

Environmental governance is more effective when the scales of ecological processes are well matched with the human institutions charged with managing human-environment interactions. The social-ecological systems (SESs) framework provides guidance on how to assess the social and ecological dimensions that contribute to sustainable resource use and management, but rarely if ever has been operationalized for multiple localities in a spatially explicit, quantitative manner. Here, we use the case of small-scale fisheries in Baja California Sur, Mexico, to identify distinct SES regions and test key aspects of coupled SESs theory. Regions that exhibit greater potential for social-ecological sustainability in one dimension do not necessarily exhibit it in others, highlighting the importance of integrative, coupled system analyses when implementing spatial planning and other ecosystem-based strategies.

Latent Space and Social Psychological Models of Diffusion

The problem of social diffusion has animated sociological thinking on topics ranging from the spread of an idea, an innovation or a disease, to the foundations of collective behavior and political polarization. While network diffusion has been a productive metaphor, the reality of diffusion processes is often muddier. Ideas and innovations diffuse differently from diseases, but, with a few exceptions, the diffusion of ideas and innovations has been modeled under the same assumptions as the diffusion of disease. In this dissertation, I develop two new diffusion models for "socially meaningful" contagions that address two of the most significant problems with current diffusion models: (1) that contagions can only spread along observed ties, and (2) that contagions do not change as they spread between people. I augment insights from these statistical and simulation models with an analysis of an empirical case of diffusion - the use of enterprise collaboration software in a large technology company. I focus the empirical study on when people abandon innovations, a crucial, and understudied aspect of the diffusion of innovations. Using timestamped posts, I analyze when people abandon software to a high degree of detail.

To address the first problem, I suggest a latent space diffusion model. Rather than treating ties as stable conduits for information, the latent space diffusion model treats ties as random draws from an underlying social space, and simulates diffusion over the social space. Theoretically, the social space model integrates both actor ties and attributes simultaneously in a single social plane, while incorporating schemas into diffusion processes gives an explicit form to the reciprocal influences that cognition and social environment have on each other. Practically, the latent space diffusion model produces statistically consistent diffusion estimates where using the network alone does not, and the diffusion with schemas model shows that introducing some cognitive processing into diffusion processes changes the rate and ultimate distribution of the spreading information. To address the second problem, I suggest a diffusion model with schemas. Rather than treating information as though it is spread without changes, the schema diffusion model allows people to modify information they receive to fit an underlying mental model of the information before they pass the information to others. Combining the latent space models with a schema notion for actors improves our models for social diffusion both theoretically and practically.

The empirical case study focuses on how the changing value of an innovation, introduced by the innovations' network externalities, influences when people abandon the innovation. In it, I find that people are least likely to abandon an innovation when other people in their neighborhood currently use the software as well. The effect is particularly pronounced for supervisors' current use and number of supervisory team members who currently use the software. This case study not only points to an important process in the diffusion of innovation, but also suggests a new approach -- computerized collaboration systems -- to collecting and analyzing data on organizational processes.

Health events and the smoking cessation of middle aged Americans.

This study investigates the effect of serious health events including new diagnoses of heart attacks, strokes, cancers, chronic lung disease, chronic heart failure, diabetes, and heart disease on future smoking status up to 6 years postevent. Data come from the Health and Retirement Study, a nationally representative longitudinal survey of Americans aged 51-61 in 1991, followed every 2 years from 1992 to 1998. Smoking status is evaluated at each of three follow-ups, (1994, 1996, and 1998) as a function of health events between each of the four waves. Acute and chronic health events are associated with much lower likelihood of smoking both in the wave immediately following the event and up to 6 years later. However, future events do not retrospectively predict past cessation. In sum, serious health events have substantial impacts on cessation rates of older smokers. Notably, these effects persist for as much as 6 years after a health event.

Dispersal and Integration in Female Chimpanzees

In chimpanzees, most females disperse from the community in which they were born to reproduce in a new community, thereby eliminating the risk of inbreeding with close kin. However, across sites, some females breed in their natal community, raising questions about the flexibility of dispersal, the costs and benefits of different strategies and the mitigation of costs associated with dispersal and integration. In this dissertation I address these questions by combining long-term behavioral data and recent field observations on maturing and young adult females in Gombe National Park with an experimental manipulation of relationship formation in captive apes in the Congo.

To assess the risk of inbreeding for females who do and do not disperse, 129 chimpanzees were genotyped and relatedness between each dyad was calculated. Natal females were more closely related to adult community males than were immigrant females. By examining the parentage of 58 surviving offspring, I found that natal females were not more related to the sires of their offspring than were immigrant females, despite three instances of close inbreeding. The sires of all offspring were less related to the mothers than non-sires regardless of the mother’s residence status. These results suggest that chimpanzees are capable of detecting relatedness and that, even when remaining natal, females can largely avoid, though not eliminate, inbreeding.

Next, I examined whether dispersal was associated with energetic, social, physiological and/or reproductive costs by comparing immigrant (n=10) and natal (n=9) females of similar age using 2358 hours of observational data. Natal and immigrant females did not differ in any energetic metric. Immigrant females received aggression from resident females more frequently than natal females. Immigrants spent less time in social grooming and more time self-grooming than natal females. Immigrant females primarily associated with resident males, had more social partners and lacked close social allies. There was no difference in levels of fecal glucocorticoid metabolites in immigrant and natal females. Immigrant females gave birth 2.5 years later than natal females, though the survival of their first offspring did not differ. These results indicate that immigrant females in Gombe National Park do not face energetic deficits upon transfer, but they do enter a hostile social environment and have a delayed first birth.

Next, I examined whether chimpanzees use condition- and phenotype-dependent cues in making dispersal decisions. I examined the effect of social and environmental conditions present at the time females of known age matured (n=25) on the females’ dispersal decisions. Females were more likely to disperse if they had more male maternal relatives and thus, a high risk of inbreeding. Females with a high ranking mother and multiple maternal female kin tended to disperse less frequently, suggesting that a strong female kin network provides benefits to the maturing daughter. Females were also somewhat less likely to disperse when fewer unrelated males were present in the group. Habitat quality and intrasexual competition did not affect dispersal decisions. Using a larger sample of 62 females observed as adults in Gombe, I also detected an effect of phenotypic differences in personality on the female’s dispersal decisions; extraverted, agreeable and open females were less likely to disperse.

Natural observations show that apes use grooming and play as social currency, but no experimental manipulations have been carried out to measure the effects of these behaviors on relationship formation, an essential component of integration. Thirty chimpanzees and 25 bonobos were given a choice between an unfamiliar human who had recently groomed or played with them over one who did not. Both species showed a preference for the human that had interacted with them, though the effect was driven by males. These results support the idea that grooming and play act as social currency in great apes that can rapidly shape social relationships between unfamiliar individuals. Further investigation is needed to elucidate the use of social currency in female apes.

I conclude that dispersal in female chimpanzees is flexible and the balance of costs and benefits varies for each individual. Females likely take into account social cues present at maturity and their own phenotype in choosing a settlement path and are especially sensitive to the presence of maternal male kin. The primary cost associated with philopatry is inbreeding risk and the primary cost associated with dispersal is delay in the age at first birth, presumably resulting from intense social competition. Finally, apes may strategically make use of affiliative behavior in pursuing particular relationships, something that should be useful in the integration process.

Cumulative early life adversity predicts longevity in wild baboons.

In humans and other animals, harsh circumstances in early life predict morbidity and mortality in adulthood. Multiple adverse conditions are thought to be especially toxic, but this hypothesis has rarely been tested in a prospective, longitudinal framework, especially in long-lived mammals. Here we use prospective data on 196 wild female baboons to show that cumulative early adversity predicts natural adult lifespan. Females who experience ≥3 sources of early adversity die a median of 10 years earlier than females who experience ≤1 adverse circumstances (median lifespan is 18.5 years). Females who experience the most adversity are also socially isolated in adulthood, suggesting that social processes partially explain the link between early adversity and adult survival. Our results provide powerful evidence for the developmental origins of health and disease and indicate that close ties between early adversity and survival arise even in the absence of health habit and health care-related explanations.

permGPU: Using graphics processing units in RNA microarray association studies.

BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.