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.

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Stable water isotopes provide a means of tracing many hydrologic processes, including poorly understood dynamics like soil water interactions with the atmosphere. We present a four-year dataset of biweekly water isotope samples from eight fluxes and stores in a headwater catchment at the Hubbard Brook Experimental Forest, New Hampshire, USA. We use Dansgaard's deuterium excess (d) parameter to infer hydrologic processes that cause stable water isotope fractionation. Although we expected to observe a decrease in d from precipitation to soil water because of evaporation, instead we observed an increase, which suggests sub-canopy water vapour recycling (evapotranspiration and then re-condensation). However, the underlying mechanisms and spatial dynamics remain uncertain. The apparent recycling is most evident in the growing season; weak evidence suggests a similar process in the dormant season. Sub-canopy water recycling is a novel hydrologic process that should have implications for micro-meteorology and habitat provided by the forest sub-canopy environment.

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Aim/Purpose: Collaborative, interdisciplinary research is growing rapidly, but we still have limited and fragmented understanding of what is arguably the heart of such research—collaborative, interdisciplinary reasoning (CIR). Background: This article integrates neo-Pragmatist theories of reasoning with insights from literature on interdisciplinary research to develop a working definition of collaborative, interdisciplinary reasoning. The article then applies this definition to an empirical example to demonstrate its utility. Methodology: The empirical example is an excerpt from a Toolbox workshop transcript. The article reconstructs a cogent, inductive, interdisciplinary argument from the excerpt to show how CIR can proceed in an actual team. Contribution: The study contributes operational definitions of ‘reasoning together’ and ‘collaborative, interdisciplinary reasoning’ to existing literature. It also demonstrates empirical methods for operationalizing these definitions, with the argument reconstruction providing a brief case study in how teams reason together. Findings: 1. Collaborative, interdisciplinary reasoning is the attempted integration of disciplinary contributions to exchange, evaluate, and assert claims that enable shared understanding and eventually action in a local context. 2. Pragma-dialectic argument reconstruction with conversation analysis is a method for observing such reasoning from a transcript. 3. The example team developed a strong inductive argument to integrate their disciplinary contributions about modeling. Recommendations for Practitioners: 1. Interdisciplinary work requires agreeing with teammates about what is assertible and why. 2. To assert something together legitimately requires making a cogent, integrated argument. Recommendation for Researchers: 1. An argument is the basic unit of analysis for interdisciplinary integration. 2. To assess the argument’s cogency, it is helpful to reconstruct it using pragma-dialectic principles and conversation analysis tools. 3. To assess the argument’s interdisciplinary integration and participant roles in the integration, it is helpful to graph the flow of words as a Sankey chart from participant-disciplines to the argument conclusion. Future Research: How does this definition of CIR relate to other interdisciplinary ‘cognition’ or ‘learning’ type theories? How can practitioners and theorists tell the difference between true intersubjectivity and superficial agreeableness in these dialogues? What makes an instance of CIR ‘good’ or ‘bad’? How does collaborative, transdisciplinary reasoning differ from CIR, if at all?

In many sectors and in many respects, interdisciplinarity has made progress in recent decades, but less so when it comes to evaluating interdisciplinary work. Challenges remain, especially regarding what counts as ‘good’ interdisciplinarity. While previous reviews describe broad trends contributing to these challenges, high-level observations are less suited to: (1) pinpointing underlying sources of persistent evaluative issues, (2) capturing less frequent counterexamples and emerging trends, and (3) providing practical guidance for moving the field forward. This article presents a novel approach for excavating and analyzing assessment designs within and across a wide range of published studies. It is the first study to structure its review of interdisciplinary evaluation around the basics of evaluation theory, creating a simplified model of assessment design choices called an assessment pathway. It further stands alone as an extensive systematic review of the interdisciplinary literature uniquely placed within the context of evaluation, encompassing 20 years, 142 studies, 1,006 assessment pathways, and 19,114 data points. Results show that while interdisciplinary assessments to date excel at variation, only 12% of identified pathways contain the minimum elements required to reach an evaluative judgment. Increased attention to evaluation theory can catalyze progress and provide structure and shared language to a highly varied domain. Readers can visually explore the full dataset online and download it from Harvard’s Dataverse.