An Interdisciplinary Insight Into the Human Dimension in Fisheries Models. A Systematic Literature Review in a European Union Context

Abstract

Fisheries are complex adaptive social-ecological systems (SES) that consist of interlinked human and ecosystems. They have mainly been studied by the natural sciences and focused on the ecosystem. However, rising concerns about sustainability and increasing complexity of societal challenges often require an understanding of fisheries in a SES context. For this purpose, the study of the human system should be expanded within fisheries science. Models are currently the most common method used in the field and these need to include the human dimension, alongside the ecosystem, when addressing fisheries systems as SES. The human dimension is an umbrella term for the complex web of human processes and it is captured by disciplines from the social sciences and the humanities. Consequently, capturing and synthesizing the variety of disciplines involved in the human dimension, and integrating them into fisheries models, requires an interdisciplinary approach. This study attempts to assess the presence of the human dimension in fisheries models applied to a European Union context and to evaluate interdisciplinarity within modeled human dimension aspects through a systematic review and qualitative analysis. Within 31 modeling publications, 20 different human dimension aspects could be identified within the categories of social phenomena, social processes, and individual attributes. Most of the human dimension aspects were modeled in an interdisciplinary manner in mathematical, statistical, simulation, or conceptual models. Yet, predominantly through the use of economic and environmental variables. We conclude that there is potential for the expansion of the human dimension and interdisciplinarity in fisheries models. To reach this potential, one should consider early involvement of all relevant disciplines in the formulation of theories, identification of data, and in the model development. We provide recommendations for interdisciplinary model development, communication, and documentation to increase our understanding of fisheries as SES.

Where the Ecological Gaps Remain, a Modelers' Perspective

“…Examples include how human exploitation can influence evolutionary processes on ecologically relevant timeframes (Audzijonyte et al, 2013) and how changing social-ecological conditions need to be accounted for to understand and manage regional resilience of terrestrial protected areas (Cumming et al, 2015). This has helped drive the desire to share ideas from other research fields, to help close some of these gaps-for example bringing together ecologists, economists and others to capture iterative interactions between human actions and natural system responses in fisheries (e.g., Weber et al, 2019), catchments (e.g., Voinov et al, 1999) and agricultural landscapes (e.g., Münier et al, 2004;Crepin and Lindahl, 2009).…”

Behavioural diversity in fishing—Towards a next generation of fishery models

“…We envision the next generation of fishery models to account for and enhance our understanding of the importance of the dynamics (and diversity) of human behaviour for the development and management of sustainable fisheries (Weber et al., 2019). These new models will be built on knowledge of human behavioural as well as biological and ecological complexities that is available from across the sciences.…”

“…Fisheries research and management benefits from a diversity of models that allow for studying and assessing fisheries (Nielsen et al., 2018; Weber et al., 2019). This diversity of model types is ultimately needed to advance the development of next‐generation social–ecological fishery models.…”

Navigating Complexities: Agent-Based Modeling to Support Research, Governance, and Management in Small-Scale Fisheries

“…ABMs are, however, also able to represent interactions beyond a local SSF with other distal interactions such as global market dynamics or climate change. This may be helpful in the process of integrating knowledge from different stakeholders, experts, and researchers (Weber et al, 2019).…”

“…This is different from standard fisheries models, which typically aim at predicting future states of a fishery by modeling variables at the macro-level (e.g., fleet behavior, fishing effort, market demand) as characteristic of the whole fleet (Quinn, 2003;van Putten et al, 2012;Nielsen et al, 2018). Even though standard fishery models are powerful, they are often not adequately flexible or sensitive to the microlevel complexities of SSF (Weber et al, 2019), nor able to fully represent the social dimension in fisheries (Fulton et al, 2011;van Putten et al, 2012;Burgess et al, 2018).…”