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Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.

Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio-Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.Participatory approaches to resource management must involve those who are affected by the decisions that stem from environmental management decisions (Reed et al., 2009). Environmental resource management often requires a combination of descriptive and normative knowledges as well as local capacity for action (and inaction). Because resource users have such knowledge and capacity, local engagement is crucial in PM. However, there are imbricated layers of power between researchers and locals-often with researchers holding the balance of power due to their increased access to social goods such as money, formal education,

Abstract. Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM.

The common assumption of a uniform collimated light source used in photometric stereo results in significant error in shape recovery when real light sources are used. Practical illumination for underwater robots is more closely approximated by point light sources. It is demonstrated that an iterative approach to photometric stereo plus a sparse range map containing as little as one range data for each object in the scene, is sufficient to permit determination of the surface gradients. Simulation indicates that the method improves accuracy and is robust with respect to measurement errors in both sparse range data and attenuation length.

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While planning resource management systems in rural areas, it is important to consider criteria that are specific to the local social conditions. Such criteria might change from one region to another and are hence best identified using a participatory approach. In this work, we propose a participatory framework to identify such criteria and derive their weights. These identified criteria and their weights are used as parameters to develop a quantitative model for evaluating efficiency of each system. Such a model can serve as a support tool for stakeholders to simulate and analyze “what‐if” scenarios, evaluate alternatives, and select one which best satisfies their requirements. We use existing systems to test the model by comparing efficiencies evaluated by the model to efficiencies perceived by the stakeholders. The model is calibrated by repeating the process until statistically significant correlation is achieved between evaluated and perceived efficiencies. The novelty of the proposed framework lies in treating efficiencies perceived by the stakeholders as the ground truth since they know these systems well and are their ultimate users. The framework is successfully demonstrated using case study of rainwater harvesting (RWH) systems in an Indian village. The resulting calibrated model can be used to plan new RWH systems in this region and similar regions elsewhere. The framework can be used to plan other resource management systems in various regions.

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