The diversity bonus in pooling local knowledge about complex problems.

Recently, theoreticians have hypothesized that diverse groups, as opposed to groups that are homogeneous, may have relative merits [S. E. Page, The Diversity Bonus (2019)]-all of which lead to more success in solving complex problems. As such, understanding complex, intertwined environmental and social issues may benefit from the integration of diverse types of local expertise. However, efforts to support this hypothesis have been frequently made through laboratory-based or computational experiments, and it is unclear whether these discoveries generalize to real-world complexities. To bridge this divide, we combine an Internet-based knowledge elicitation technique with theoretical principles of collective intelligence to design an experiment with local stakeholders. Using a case of striped bass fisheries in Massachusetts, we pool the local knowledge of resource stakeholders represented by graphical cognitive maps to produce a causal model of complex social-ecological interdependencies associated with fisheries ecosystems. Blinded reviews from a scientific expert panel revealed that the models of diverse groups outranked those from homogeneous groups. Evaluation via stochastic network analysis also indicated that a diverse group more adequately modeled complex feedbacks and interdependencies than homogeneous groups. We then used our data to run Monte Carlo experiments wherein the distributions of stakeholder-driven cognitive maps were randomly reproduced and virtual groups were generated. Random experiments also predicted that knowledge diversity improves group success, which was measured by benchmarking group models against an ecosystem-based fishery management model. We also highlight that diversity must be moderated through a proper aggregation process, leading to more complex yet parsimonious models.

Local-scale dynamics and local drivers of bushmeat trade.

Bushmeat management policies are often developed outside the communities in which they are to be implemented. These policies are also routinely designed to be applied uniformly across communities with little regard for variation in social or ecological conditions. We used fuzzy-logic cognitive mapping, a form of participatory modeling, to compare the assumptions driving externally generated bushmeat management policies with perceptions of bushmeat trade dynamics collected from local community members who admitted to being recently engaged in bushmeat trading (e.g., hunters, sellers, consumers). Data were collected during 9 workshops in 4 Tanzanian villages bordering Serengeti National Park. Specifically, we evaluated 9 community-generated models for the presence of the central factors that comprise and drive the bushmeat trade and whether or not models included the same core concepts, relationships, and logical chains of reasoning on which bushmeat conservation policies are commonly based. Across local communities, there was agreement about the most central factors important to understanding the bushmeat trade (e.g., animal recruitment, low income, and scarcity of food crops). These matched policy assumptions. However, the factors perceived to drive social-ecological bushmeat trade dynamics were more diverse and varied considerably across communities (e.g., presence or absence of collaborative law enforcement, increasing human population, market demand, cultural preference). Sensitive conservation issues, such as the bushmeat trade, that require cooperation between communities and outside conservation organizations can benefit from participatory modeling approaches that make local-scale dynamics and conservation policy assumptions explicit. Further, communities' and conservation organizations' perceptions need to be aligned. This can improve success by allowing context appropriate policies to be developed, monitored, and appropriately adapted as new evidence is generated.

Knowledge gain and behavioral change in citizen-science programs.

Citizen-science programs are often touted as useful for advancing conservation literacy, scientific knowledge, and increasing scientific-reasoning skills among the public. Guidelines for collaboration among scientists and the public are lacking and the extent to which these citizen-science initiatives change behavior is relatively unstudied. Over two years, we studied 82 participants in a three-day program that included education about non-native invasive plants and collection of data on the occurrence of those plants. Volunteers were given background knowledge about invasive plant ecology and trained on a specific protocol for collecting invasive plant data. They then collected data and later gathered as a group to analyze data and discuss responsible environmental behavior with respect to invasive plants. We tested whether participants without experience in plant identification and with little knowledge of invasive plants increased their knowledge of invasive species ecology, participation increased knowledge of scientific methods, and participation affected behavior. Knowledge of invasive plants increased on average 24%, but participation was insufficient to increase understanding of how scientific research is conducted. Participants reported increased ability to recognize invasive plants and increased awareness of effects of invasive plants on the environment, but this translated into little change in behavior regarding invasive plants. Potential conflicts between scientific goals, educational goals, and the motivation of participants must be considered during program design.

Resumen: Los programas de ciencia-ciudadana a menudo son vendidos como útiles para que el público avance en sus conocimientos sobre conservación, en su conocimiento científico y en el incremento de las habilidades de razonamiento científico. No existen directrices para la colaboración entre científicos y el público y casi no se ha estudiado el grado en que estas iniciativas ciudadanos-ciencia cambian el comportamiento. Durante dos años estudiamos a 82 participantes en un programa de 3 días que incluía educación sobre plantas invasoras no nativas y la recolección de datos sobre la ocurrencia de estas plantas. A los voluntarios se les proporcionó conocimiento básico sobre la ecología de plantas invasoras y fueron entrenados en un protocolo específico para la recolección de datos de plantas invasoras. Posteriormente recolectaron datos y se reunieron para analizarlos y discutir sobre comportamiento ambiental responsable en relación con plantas invasoras. Probamos si los participantes sin experiencia en la identificación de plantas y con poco conocimiento de plantas invasoras incrementaron su conocimiento de ecología de especies invasoras, si la participación incrementó su conocimiento de métodos científicos y si la participación afectó su comportamiento. El conocimiento de plantas invasoras incrementó 24% en promedio, pero la participación no fue suficiente para incrementar el entendimiento de cómo se lleva a cabo la investigación científica. Los participantes reportaron incremento en su habilidad para reconocer plantas invasoras e incremento en la conciencia sobre el efecto de las plantas invasoras sobre el ambiente, pero esto se tradujo en pocos cambios en el comportamiento respecto a las plantas invasoras. Los potenciales conflictos entre las metas científicas, las metas educativas y la motivación de participantes deben ser considerados durante el diseño del programa.

Development of a collaborative model of low back pain: report from the 2017 NASS consensus meeting.

BACKGROUND CONTEXT: Low back pain (LBP) is a multifactorial problem with complex interactions among many biological, psychological and social factors. It is difficult to fully appreciate this complexity because the knowledge necessary to do so is distributed over many areas of expertise that span the biopsychosocial domains. PURPOSE: This study describes the collaborative modeling process, undertaken among a group of participants with diverse expertise in LBP, to build a model to enhance understanding and communicate the complexity of the LBP problem. STUDY DESIGN: The study involved generating individual models that represented participants' understanding of the LBP problem using fuzzy cognitive mapping (FCM), and 4 subsequent phases of consultation and consensus with the participants to characterize and refine the interpretation of the FCMs. METHODS: The phases consisted of: proposal of Categories for clustering of model Components; preliminary evaluation of structure, composition and focal areas of participant's FCMs; refinement of Categories and Components with consensus meeting; generation of final structure and composition of individual participant's FCMs. Descriptive statistics were applied to the structural and composition metrics of individual FCMs to aid interpretation. RESULTS: From 38 invited contributors, 29 (76%) agreed to participate. They represented 9 disciplines and 8 countries. Participants' models included 729 Components, with an average of 25 (SD = 7) per model. After the final FCM refinement process (Components from separate FCMs that used similar terms were combined, and Components from an FCM that included multiple terms were separated), there were 147 Components allocated to ten Categories. Although individual models varied in their structure and composition, a common opinion emerged that psychological factors are particularly important in the presentation of LBP. Collectively, Components allocated to the "Psychology" Category were the most central in almost half (14/29) of the individual models. CONCLUSIONS: The collaborative modeling process outlined in this paper provides a foundation upon which to build a greater understanding and to communicate the complexity of the LBP problem. The next step is to aggregate individual FCMs into a metamodel and begin disentangling the interactions among its Components. This will lead to an improved understanding of the complexity of LBP, and hopefully to improved outcomes for those suffering from this condition.

Building a Collaborative Model of Sacroiliac Joint Dysfunction and Pelvic Girdle Pain to Understand the Diverse Perspectives of Experts.

BACKGROUND: Pelvic girdle pain (PGP) and sacroiliac joint (SIJ) dysfunction/pain are considered frequent contributors to low back pain (LBP). Like other persistent pain conditions, PGP is increasingly recognized as a multifactorial problem involving biological, psychological, and social factors. Perspectives differ between experts and a diversity of treatments (with variable degrees of evidence) have been utilized. OBJECTIVE: To develop a collaborative model of PGP that represents the collective view of a group of experts. Specific goals were to analyze structure and composition of conceptual models contributed by participants, to aggregate them into a metamodel, to analyze the metamodel's composition, and to consider predicted efficacy of treatments. DESIGN: To develop a collaborative model of PGP, models were generated by invited individuals to represent their understanding of PGP using fuzzy cognitive mapping (FCM). FCMs involved proposal of components related to causes, outcomes, and treatments for pain, disability, and quality of life, and their connections. Components were classified into thematic categories. Weighting of connections was summed for components to judge their relative importance. FCMs were aggregated into a metamodel for analysis of the collective opinion it represented and to evaluate expected efficacy of treatments. RESULTS: From 21 potential contributors, 14 (67%) agreed to participate (representing six disciplines and seven countries). Participants' models included a mean (SD) of 22 (5) components each. FCMs were refined to combine similar terms, leaving 89 components in 10 categories. Biomechanical factors were the most important in individual FCMs. The collective opinion from the metamodel predicted greatest efficacy for injection, exercise therapy, and surgery for pain relief. CONCLUSIONS: The collaborative model of PGP showed a bias toward biomechanical factors. Most efficacious treatments predicted by the model have modest to no evidence from clinical trials, suggesting a mismatch between opinion and evidence. The model enables integration and communication of the collection of opinions on PGP.