Matching Social and Ecological Systems in Complex Ocean Fisheries

This paper considers ocean fisheries as complex adaptive systems and addresses the question of how human institutions might be best matched to their structure and function. Ocean ecosystems operate at multiple scales, but the management of fisheries tends to be aimed at a single species considered at a single broad scale. The paper argues that this mismatch of ecological and management scale makes it difficult to address the fine-scale aspects of ocean ecosystems, and leads to fishing rights and strategies that tend to erode the underlying structure of populations and the system itself. A successful transition to ecosystem-based management will require institutions better able to economize on the acquisition of feedback about the impact of human activities. This is likely to be achieved by multiscale institutions whose organization mirrors the spatial organization of the ecosystem and whose communications occur through a polycentric network. Better feedback will allow the exploration of fine-scale science and the employment of fine-scale fishing restraints, better adapted to the behavior of fish and habitat. The scale and scope of individual fishing rights also needs to be congruent with the spatial structure of the ecosystem. Place-based rights can be expected to create a longer private planning horizon as well as stronger incentives for the private and public acquisition of system relevant knowledge.

An ecological systems theory approach in looking at mental health care barriers in the latino community

Tesis (Doctorado en Filosofía con Orientación en Trabajo Social y Políticas Comparadas de Bienestar Social) U.A.N.L. Facultad de Filosofía Letras y Escuela de Graduados de la Universidad de Arlington, Texas, 2008

Modelling sustainability performance to achieve absolute reductions in socio-ecological systems

As the world’s natural resources dwindle and critical levels of environmental pollution are approached, sustainability becomes a key issue for governments, organisations and individuals. With the consequences of such an issue in mind, this paper introduces a unifying approach to measure the sustainability performance of socio-economic systems based on the interplay between two key variables: essentiality of consumption and environmental impact. This measure attributes to every system a ‘fitness’ value i.e. a quantity that reflects its ability to remain resilient/healthy by avoiding ecological, social and economic collapse as it consumes the available resources. This new measure is tested on a system where there is a limited supply of resources and four basic consumption types. The analysis has theoretical implications as well as practical importance as it can help countries, organisations or even individuals, in finding better ways to measure sustainability performance.

Constructing stability landscapes to identify alternative states in coupled social-ecological agent-based models

The resilience of a social-ecological system is measured by its ability to retain core functionality when subjected to perturbation. Resilience is contextually dependent on the state of system components, the complex interactions among these components, and the timing, location, and magnitude of perturbations. The stability landscape concept provides a useful framework for considering resilience within the specified context of a particular social-ecological system but has proven difficult to operationalize. This difficulty stems largely from the complex, multidimensional nature of the systems of interest and uncertainty in system response. Agent-based models are an effective methodology for understanding how cross-scale processes within and across social and ecological domains contribute to overall system resilience. We present the results of a stylized model of agricultural land use in a small watershed that is typical of the Midwestern United States. The spatially explicit model couples land use, biophysical models, and economic drivers with an agent-based model to explore the effects of perturbations and policy adaptations on system outcomes. By applying the coupled modeling approach within the resilience and stability landscape frameworks, we (1) estimate the sensitivity of the system to context-specific perturbations, (2) determine potential outcomes of those perturbations, (3) identify possible alternative states within state space, (4) evaluate the resilience of system states, and (5) characterize changes in system-scale resilience brought on by changes in individual land use decisions.

Objectives for management of socio-ecological systems in the Great Barrier Reef region, Australia

A wide range of goals and objectives have to be taken into account in natural resources management. Defining these objectives in operational terms, including dimensions such as sustainability, productivity, and equity, is by no means easy, especially if they must capture the diversity of community and stakeholder values. This is especially true in the coastal zone where land activities affect regional marine ecosystems. In this study, the aim was firstly to identify and hierarchically organise the goals and objectives for coastal systems, as defined by local stakeholders. Two case study areas are used within the Great Barrier Reef region being Mackay and Bowen–Burdekin. Secondly, the aim was to identify similarities between the case study results and thus develop a generic set of goals to be used as a starting point in other coastal communities. Results show that overarching high-level goals have nested sub-goals that contain a set of more detailed regional objectives. The similarities in high-level environmental, governance, and socio-economic goals suggest that regionally specific objectives can be developed based on a generic set of goals. The prominence of governance objectives reflects local stakeholder perceptions that current coastal zone management is not achieving the outcomes they feel important and that there is a need for increased community engagement and co-management. More importantly, it raises the question of how to make issues relevant for the local community and entice participation in the local management of public resources to achieve sustainable environmental, social, and economic management outcomes. © 2015 Springer-Verlag Berlin Heidelberg

The decentralized social networking systems towards mobilizing actions of citizenship and solidarity against cancer

The goal of the present study is mapping the nature of possible contributions of participatory online platforms in citizen actions that may contribute in the fight against cancer and its associated consequences. These platforms are usually associated with entertainment: in that sense, we intent to test their validity in other domains such as health, as well as contribute to an expanded perception of their potential by their users. The research is based on the analysis of online solidarity networks, namely the ones residing on Facebook, Orkut and the blogosphere, that citizens have been gradually resorting to. The research is also based on the development of newer and more efficient solutions that provide the individual (directly or indirectly affected by issues of oncology) with the means to overcome feelings of impotence and fatality. In this article, we aim at summarizing the processes of usage of these decentralized, freer participatory platforms by citizens and institutions, while attempting to unravel existing hype and stigma; we also provide a first survey of the importance and the role of institutions in this kind of endeavor; lastly, we present a prototype, developed in the context of the present study, that is specifically dedicated to addressing oncology through social media. This prototype is already available online at www.talkingaboutcancer.org, however, still under development and testing. The main objective of this platform is to allow every citizen to freely build their network of contacts and information, according to their own individual and/ or collective needs and desires.

Social protection systems in vulnerable families: their importance for the public health

OBJECTIVE To analyze the effectiveness of the Chilean System of Childhood Welfare in transferring benefits to socially vulnerable families. METHODS A cross-sectional study with a sample of 132 families from the Metropolitan Region, Chile, stratified according to degree of social vulnerability, between September 2011 and January 2012. Semi-structured interviews were conducted with mothers of the studied families in public health facilities or their households. The variables studied were family structure, psychosocial risk in the family context and integrated benefits from the welfare system in families that fulfill the necessary requirements for transfer of benefits. Descriptive statistics to measure location and dispersion were calculated. A binary logistic regression, which accounts for the sample size of the study, was carried out. RESULTS The groups were homogenous regarding family size, the presence of biological father in the household, the number of relatives living in the same dwelling, income generation capacity and the rate of dependency and psychosocial risk (p ≥ 0.05). The transfer of benefits was low in all three groups of the sample (≤ 23.0%). The benefit with the best coverage in the system was the Single Family Subsidy, whose transfer was associated with the size of the family, the presence of relatives in the dwelling, the absence of the father in the household, a high rate of dependency and a high income generation capacity (p ≤ 0.10). CONCLUSIONS The effectiveness of benefit transfer was poor, especially in families that were extremely socially vulnerable. Further explanatory studies of benefit transfers to the vulnerable population, of differing intensity and duration, are required in order to reduce health disparities and inequalities.

Approximate entropy normalized measures for analyzing social neurobiological systems

When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

Interpreting change in human-nature and long term social relationships

Dissertação apresentada para obtenção do Grau de Doutor em Ciências do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Introduction to the Social Networking Systems Course

These are the Introduction slides for Comp6051 Social Networking Technologies. They outline the structure of the course, and give a (very brief) overview of the topics covered.