Models for an Ecosystem Approach to Fisheries

This document is one outcome from a workshop held in Gizo in October 2010 attended by 82 representatives from government, NGO's private sector, and communities. The target audience for the document is primarily organizations planning to work with coastal communities of Solomon Islands to implement Community-Based Resource Management (CBRM). It is however also envisaged that the document will serve as a reference for communities to better understand what to expect from their partners and also for donors, to be informed about agreed approaches amongst Solomon Islands stakeholders. This document does not attempt to summarize all the outcomes of the workshop; rather it focuses on the Solomon Islands Coral Triangle Initiative (CTI) National Plan of Action (NPoA): Theme 1: Support and implementation of CBRM and specifically, the scaling up of CBRM in Solomon Islands. Most of the principles given in this document are derived from experiences in coastal communities and ecosystems as, until relatively recently, these have received most attention in Solomon Islands resource management. It is recognized however that the majority of these principles will be applicable to both coastal and terrestrial initiatives. This document synthesizes information provided by stakeholders at the October 2010 workshop and covers some basic principles of engagement and implementation that have been learned over more than twenty years of activities by the stakeholder partners in Solomon Islands. The document updates and expands on a summary of guiding principles for CBRM which was originally prepared by the Solomon Islands Locally Managed Marine Area Network (SILMMA) in 2007

Modeling Complex Systems

Abstract Empirical observations suggest that linear dynamics are not an adequate representa- tion of ecological systems and that a realistic representation would require adoption of complex nonlinear dynamical systems with characteristics encountered in complex adaptive systems (CAS). Adequate modelling should include and combine, among others, strategic interactions among economic agents, nonconvexities induced by non-linear feedbacks, separate spatial and temporal scales and modeling of spatiotempo-ral dynamics, and allowance of alternative time scales. Ignoring these characteristics might obscure very important features that we observe in reality such as bifurcations and irreversibilities or hysteresis. As a consequence, the design of policies that do not take CAS characteristics into account might lead to erroneous results and undesirable states of managed economic-ecological systems.Complex adaptive systems, differential games, spatiotemporal dynamics, fast-slow variables.

Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability

The integrated - environmental, economic and social - analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behaviour. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. A vast body of literature on agent-based modelling (ABM) shows its potential to couple social and environmental models, to incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few publications which concretely apply this methodology to the study of climate change related issues. The analysis of the state of the art reported in this paper supports the idea that today ABM is an appropriate methodology for the bottom-up exploration of climate policies, especially because it can take into account adaptive behaviour and heterogeneity of the system's components.Review, Agent-Based Modelling, Socio-Ecosystems, Climate Change, Adaptation, Complexity.

Accounting for changes in biodiversity and ecosystem services from a business perspective

Biodiversity refers to the dynamics of interactions between organisms in changing environments. Within the context of accelerating biodiversity loss worldwide, firms are under increasing pressures from stakeholders to develop appropriate tools to account for the nature and consequences of their actions, inclusive of their influences on ecosystem services used by other agents. This paper presents a two-pronged approach towards accounting for changes in biodiversity and ecosystem services from a business perspective. First, we seek to analyze how Environmental Management Accounting (EMA) may be used by firms to identify and account for the interactions between their activities and biodiversity and ecosystem services (BES). To that end, we use dairy farming as a case study and propose general recommendations regarding accounting for changes in biodiversity and ecosystem services from a management accounting perspective. Secondly, after discussing the corporate reporting implications of the main environmental accounting approaches, we propose the underlying principles and structural components of a Biodiversity Accountability Framework (BAF) which would combine both financial and BES data sets; hence, suggesting the need for changes in business accounting and reporting standards. Because this would imply significant changes in business information systems and corporate rating practices, we also underline the importance of making the associated technological, organizational and institutional innovations financially viable. The BAF should be designed as an information base, coconstructed with stakeholders, for setting up and managing new modes of regulation combining tools for mitigating BES loss and remunerating BES supply.Accounting, business, biodiversity, ecosystem services, indicators, management accounting, financial accounting, reporting, corporate social responsibility, standards, biodiversity accountability framework.

Scientific instruments for climate change adaptation: estimating and optimizing the efficiency of ecosystem service provision

Adaptation to the consequences of climate change can depend on efficient use of ecosystem services (ES), i.e. a better use of natural services through management of the way in which they are delivered to society. While much discussion focuses on reducing consumption and increasing production of services, a lack of scientific instruments has so far prevented other mechanisms to improve ecosystem services efficiency from being addressed systematically as an adaptation strategy. This paper describes new methodologies for assessing ecosystem services and quantifying their values to humans, highlighting the role of ecosystem service flow analysis in optimizing the efficiency of ES provision.Ecosystem services, flow analysis, Bayesian modeling, spatial analysis, Environmental Economics and Policy, Q01, Q54, Q55, Q57,

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating autonomy, environmental interactions, communication and cooperation, reactivity and proactivity, reasoning and learning capabilities. Their decisions maximize both task-specific marginal utility for their actions and joint, weighted marginal utility for their time-stepping. Agent behavior is achieved by personalizing a dynamic utility-based knowledge base through sequential GIS filtering, probability-distributed weighting, joint probability Bayesian correlational weighting, and goal-based distributional properties, applied to socio-economic and behavioral criteria. First-order logics, heuristics and appropriation of time-step sequences employed, provide a simulation-able environment, capable of re-generating space-time evolution of the agents.Environmental Economics and Policy,

Resilience in rural common-pool resource management systems: towards enhancing landscape amenities using a multi-agent approach

Rural areas are continuously subject to changing circumstances, varying from changes in ecosystem conditions to socio-economic changes like food- and financial crises. Within Europe, the Common Agricultural Policy (CAP) reform is driver as well for change of rural common pool resources (CPR). Rural CPRs are defined as rural social-ecological systems which provide landscapes with high agricultural, ecological and cultural-historical values. The conservation of these systems is treated as the enhancement of these values through the protection of rare plant species. Analyzing resilience of rural CPRs offers a framework to emphasize dynamics and interdependencies across time, space and between social, economic and ecological domains. This paper provides insight into the effects of CAP reforms on rural CPRs and its resilience, through the use of a multi-agent simulation approach. The advantage of such a multi-agent approach is that it allows to capture interactions of heterogeneous agents in a landscape that provides space for both agriculture and rare plant species. The simulation model is applied for Winterswijk, which is a rural region in eastern part of the Netherlands. This CPR is characterized by a small scale landscape with high biodiversity. Transferring insights from resilience thinking to rural development strategies would lead to a focus on the factors that build the ability of the rural area to respond to policy changes. The strength of multi-agent models is illustrated and their potential for the analysis of different policy options and implications in rural areas is shown