Pretty darn good control: when are approximate solutions better than approximate models

Existing methods for optimal control struggle to deal with the complexity commonly encountered in real-world systems, including dimensionality, process error, model bias and data heterogeneity. Instead of tackling these system complexities directly, researchers have typically sought to simplify models to fit optimal control methods. But when is the optimal solution to an approximate, stylized model better than an approximate solution to a more accurate model? While this question has largely gone unanswered owing to the difficulty of finding even approximate solutions for complex models, recent algorithmic and computational advances in deep reinforcement learning (DRL) might finally allow us to address these questions. DRL methods have to date been applied primarily in the context of games or robotic mechanics, which operate under precisely known rules. Here, we demonstrate the ability for DRL algorithms using deep neural networks to successfully approximate solutions (the "policy function" or control rule) in a non-linear three-variable model for a fishery without knowing or ever attempting to infer a model for the process itself. We find that the reinforcement learning agent discovers an effective simplification of the problem to obtain an interpretable control rule. We show that the policy obtained with DRL is both more profitable and more sustainable than any constant mortality policy -- the standard family of policies considered in fishery management.Comment: 24 pages, 14 figures. Accepted to the Bulletin of Mathematical Biolog

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

Artisanal fishing and community based resource management : a case study of Tchuma Tchato project in Mozambique.

Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1999.This study is about artisanal fishing and community based natural resources management in Chintop ward. It sets out to • develop an understanding of the fishery in the context of CBNRM; and to formulate conceptual framework for the research • evaluate how well prepared government and the Tchuma rchato project are to act as ' agent of change' in promoting CBNRM • develop an understanding of the present ways in which access is controlled; how government revenues from the fishery is generated and how it is distributed • provide informed suggestions on how to proceed in promoting the process ofCBNRM wlthin the Tchuma Tchato project. The research comprises four parts: developing a theoretical understanding and conceptual framework based on the analysis of relevant literature. Investigation of the organisational structure and capabilities of government and the Tchuma Tchato project in the context of conceptua1 model (preparedness for intervention); an analysis of the importance of the fishery to local people, regulation of access and distribution of benefits; and a critical evaluation ofthe current situation and recommendation of action to promote CBNRM. The literature analysis focused on the origins, principles and strengths and weakness of ICDP, ADMADE and CBNRM projects. It is concluded that the principles and theories that underpin CBNRM are not well understood in the three sectors involved, government, NGOs and local structures. Consequently they are not adequately prepared to implement CBNRM in the most required areas, the license system in place in Chintopo does not provide for any real regulation as well it does not control harvesting pressure. The principles and theory which underpin CBNRM are not consolidated into a user friend1y fonnat which facilitates knowledge transfer amongst practitioners. There is too much emphasis on theory and not enough on IV process and practice. Insufficient attention is devoted to team work and vertical integration. There is no strategic plan and there is no generative learning. It is evident that meaningful progress could not be made with integrating the fishery into CBNRM until the macro-issues have been addressed. Access is by license but this does not provide for any regulation. The fishery was tending towards open access. Licensing does not control harvest pressure. Consequently the current trend is toward unsustainable levels of harvest. The distribution of revenues generated by licenses and inspection fees is not distributed in a manner which provides meaningful return to the community. Consequently the recommendations made here are not specific to the fishery. The whole approach to CBNRM should be revisited before proceeding with any further expansion of the project. Comprehensive strategic analysis need to be made focusing on what was originally intended, namely building capacity for intervention. This will involve a cross sectoral team building; building a shared vision; developing real capacity; and developing a business plan which emphasizes both process and product. There should be a culture of learning so that the team learns from failures rather than fears them. Strong focus should be given on building strategic alliances among research and educational institutions and NGOs

The Roles of the Environment and Natural Resources in Economic Growth Analysis

The primary aim of this paper is pedagogical. We first present and discuss a “wiring diagram” framework in order to elucidate the general links between economic growth and "natural capital." After developing the general framework, we develop parallel frameworks applicable to several specific sectors of the economy (agriculture, forestry, and manufacturing). Two appendices provide a mathematical formulation of the economy-wide framework and a brief historical review of the role of natural resources and the environment in economic growth theory.economic growth, natural resources, sustainable development

Meeting reports: Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges, and Strategies

Understanding the complexity of human–nature interactions is central to the quest for both human well-being and global sustainability. To build an understanding of these interactions, scientists, planners, resource managers, policymakers, and communities increasingly are collaborating across wide-ranging disciplines and knowledge domains. Scientists and others are generating new integrated knowledge on top of their requisite specialized knowledge to understand complex systems in order to solve pressing environmental and social problems (e.g., Carpenter et al. 2009). One approach to this sort of integration, bringing together detailed knowledge of various disciplines (e.g., social, economic, biological, and geophysical), has become known as the study of Coupled Human and Natural Systems, or CHANS (Liu et al. 2007a, b). In 2007 a formal standing program in Dynamics of Coupled Natural and Human Systems was created by the U.S. National Science Foundation. Recently, the program supported the launch of an International Network of Research on Coupled Human and Natural Systems (CHANS-Net.org). A major kick-off event of the network was a symposium on Complexity in Human–Nature Interactions across Landscapes, which brought together leading CHANS scientists at the 2009 meeting of the U.S. Regional Association of the International Association for Landscape Ecology in Snowbird, Utah. The symposium highlighted original and innovative research emphasizing reciprocal interactions between human and natural systems at multiple spatial, temporal, and organizational scales. The presentations can be found at ‹http://chans- net.org/Symposium_2009.aspx›. The symposium was accompanied by a workshop on Challenges and Opportunities in CHANS Research. This article provides an overview of the CHANS approach, outlines the primary challenges facing the CHANS research community, and discusses potential strategies to meet these challenges, based upon the presentations and discussions among participants at the Snowbird meeting

Valuing Ecosystem Services with Fishery Rents: A Lumped-Parameter Approach to Hypoxia in the Neuse River Estuary

Valuing ecosystem services with microeconomic underpinnings presents challenges because these services typically constitute nonmarket values and contribute to human welfare indirectly through a series of ecological pathways that are dynamic, nonlinear, and difficult to quantify and link to appropriate economic spatial and temporal scales. This paper develops and demonstrates a method to value a portion of ecosystem services when a commercial fishery is dependent on the quality of estuarine habitat. Using a lumped-parameter, dynamic open access bioeconomic model that is spatially explicit and includes predator-prey interactions, this paper quantifies part of the value of improved ecosystem function in the Neuse River Estuary when nutrient pollution is reduced. Specifically, it traces the effects of nitrogen loading on the North Carolina commercial blue crab fishery by modeling the response of primary production and the subsequent impact on hypoxia (low dissolved oxygen). Hypoxia, in turn, affects blue crabs and their preferred prey. The discounted present value fishery rent increase from a 30% reduction in nitrogen loadings in the Neuse is $2.56 million, though this welfare estimate is fairly sensitive to some parameter values. Surprisingly, this number is not sensitive to initial conditions.Open access, Predator-prey, Hypoxia, Habitat-dependent fisheries

A multi-model approach to stakeholder engagement in complex environmental problems

We describe the different types of models we used as part of an effort to inform policy-making aiming at the management of the Ningaloo coast in the Gascoyne region, Western Australia. This provides an overview of how these models interact, the different roles they cover, how they fit into a full decision making process and what we learnt about the stakeholders involved in our project via their use. When modelling is explicitly used to address socio-ecological issues, the key determinant of success is whether the models, their results and recommendations are taken up by stakeholders; such uptake in turn depends on addressing stakeholders’ concerns, on engaging them in the project, on ensuring they feel ownership of the decision process at large, and that they understand and trust the modelling effort. This observation has guided our approach and has resulted in treating ‘building a model’ as the catalyst, rather than the final aim, of the process. In other words, extensive interactions in order to introduce, showcase, discuss and tune the model used for final decision making have represented both a requirement and an opportunity to ensure (i) model relevance, (ii) its acceptance, (iii) that all information available in the stakeholder team was accounted for and (iv) that stakeholders holding different levels of understanding of modelling, what it does and what it can provide to decision-making could develop an informed opinion on its use. To fulfil these roles we developed five broad classes of models: conceptual models, toy-models, singlesystem models, shuttle-models and a full-system model. In conceptual models the main drivers of a system are highlighted for subsequent representation as components of the full-system model. This usually results in a diagram summarising our understanding of how the system works. In toy-models a problem is simplified in such a way that only a handful of components are included. The purpose of these models is mostly educational: we want to understand how each component affects the problem and in order to achieve this, we temporarily renounce a satisfactory understanding of the overall problem. In single-system models we include a fairly detailed representation of a single component of the system (in our case recreational fishing and tourism); these models can be used to introduce stakeholders to modelling, provide temporary results from the study of a single activity, which will feed into the development of the final full-system model, or address sector-specific issues. In shuttle-models, we include the minimum number of processes we believe are crucial for a basic understanding of the overall problem. We know these models are still too simple for full system description, but they provide a sufficient understanding to enable us to contemplate, build and use the more complex models needed for full problem description. The term ‘shuttle’ refers to taking us from a minimum to a full description of the problem, a journey which is necessary both to developers in model definition and parameterisation and to stakeholders in the interpretation of the final full-system model results. Finally, the full-system model includes all information collected through the project and addresses all scenarios of stakeholders concern, and whose definition has been greatly eased by use of the ‘simpler’ models. As an example, a conceptual model may identify fishing and tourism as the main drivers of a region; a toymodel may describe how catches affect fish stocks; a single-system model may include the effect of gear, regulations and other processes affecting recreational fishing; a shuttle-model may include a simplified representation of the interaction between fishing, tourism, and infrastructure development on the overall health of the local ecosystem; this will gradually ‘take’ us to comprehend the ‘full’ model which may include tourism pressure, fish market values, climate effect, larger food-webs, etc