Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages

Charting the course for a Blue Economy in Peru: A Research Agenda

Ocean- and coastal-based economic activities are increasingly recognised as key drivers for supporting global economies. This move towards the “blue economy” is becoming globally widespread, with the recognition that if ocean-based activities are to be sustainable, they will need to move beyond solely extractive and exploitative endeavours, aligning more closely with marine conservation and effective marine spatial planning. In this paper we define the “blue economy” as a “platform for strategic, integrated and participatory coastal and ocean development and protection that incorporates a low carbon economy, the ecosystem approach and human well-being through advancing regional industries, services and activities”. In Peru, while the seas contribute greatly to the national economy, the full potential of the blue economy has yet to be realised. This paper presents the findings of an early career scientist workshop in Lima, Peru, in March 2016. The workshop “Advancing Green Growth in Peru” brought together researchers to identify challenges and opportunities for green growth across three Peruvian economic sectors—tourism, transport and the blue economy with this paper exploring in detail the priorities generated from the “blue economy” stream. These priorities include themes such as marine spatial planning, detailed evaluations of existing maritime industries (e.g. guano collection and fisheries), development of an effective MPA network, support for sustainable coastal tourism, and better inclusion of social science disciplines in understanding societal and political support for a Peruvian blue economy. In addition, the paper discusses the research requirements associated with these priorities. While not a comprehensive list, these priorities provide a starting point for future dialogue on a co-ordinated scientific platform supporting the blue growth agenda in Peru, and in other regions working towards a successful “blue economy”

The IIASA Energy-Multi Criteria Analysis Tool (ENE-MCA)

Researchers at the International Institute for Applied Systems Analysis (IIASA), building on work carried out within the framework of the Global Energy Assessment (GEA), have developed an interactive web-based scenario analysis tool that permits the concurrent assessment of synergies and trade-offs between multiple energy objectives at the global scale. This software, known as the IIASA Energy-Multi Criteria Analysis Policy Tool (ENE-MCA), is designed to assist national policy makers in their strategic policy planning processes. The tool extends work undertaken for the GEA and, as such, is built on the extensive set of global energy and environmental scenarios that have been generated as part of the GEA process. This document serves as an introduction to the ENE-MCA tool and as a brief manual for the typical user

Human Simulation and Sustainability : Ontological, Epistemological, and Ethical Reflections

publishedVersio

Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections

publishedVersio

Detecting and distinguishing transitions in ecological systems: model and data-driven approaches

There exists a plethora of systems that have the capacity to undergo sudden transitions that result in a significantly different state or dynamic. Consider the collapse of fisheries, outbreak of disease or transition to a 'Hothouse Earth' to name a few. The common factor among these transitions is mathematical - they are the result of crossing a bifurcation point. This thesis is concerned with the detection and description of these bifurcations from time series data, and the mechanisms that lead to these transitions. We begin in the domain of climate change, where models of the climate system are extremely sophisticated, but those that incorporate social dynamics and its two-way coupling with climate dynamics are lacking. In developing a simple socio-climate model, we show how mechanisms such as social learning, social norms, and perceived mitigation costs play a major role in climate change trajectories. These social effects can strongly determine the predicted peak global temperature anomaly, how quickly human populations respond to a changing climate, and how we can chart optimal pathways to climate change mitigation. However, we also show that if the climate model is subject to a tipping point, the climate can transition to a new state before mitigating behaviour becomes sufficiently widespread to prevent the transition. This motivates a need for early warning signals (EWS) of tipping points. Hence, in the next chapter we focus on the development of EWS in time series data that can be used to detect an upcoming bifurcation. This thesis develops two 'spectral EWS', which are derived from the power spectrum. We show that the peak in the power spectrum provides a more sensitive and conservative EWS when compared to conventional metrics, and the shape of the power spectrum, quantified using AIC weights, provides clues as to the type of approaching bifurcation. We validate these spectral EWS with empirical data from a predator-prey system. Finally we focus on EWS for population extinction, where we study the efficacy of EWS in seasonal environments. We find that conventional EWS prevail under seasonal environments, however asymmetries exist in higher-order metrics such as skewness and kurtosis that could be used to distinguish the driver of extinction. To conclude, nonlinear behaviour arising from social learning and social norms yield bifurcations that have profound impacts on future trajectories of climate change, and bifurcations can be anticipated across a wide range of systems using spectral EWS, that also provide information on the type of bifurcation. The further development of generic and system-specific EWS will play an important role in preserving healthy ecosystem functioning in the Anthropocene

Developing a sustainability science approach for water systems

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines’ different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the “characteristic management challenges” that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems