Communicating complex ecological models to non-scientist end users

Cartwright, Samantha J.; Bowgen, Katharine M.; Collop, Catherine; Hyder, Kieran; Nabe‐Nielsen, Jacob; Stafford, Richard; Stillman, Richard A.; Thorpe, Robert; Sibly, Richard M.

doi:10.1016/j.ecolmodel.2016.07.012

Cited by 61 publications

(71 citation statements)

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“…Specifically, the likely synergistic and antagonistic effects of management measures and concurrent changes in prevailing climatic conditions should be investigated at each assessment cycle of the MSFD. Sources of uncertainty (measurement error, uncertainty in pressure-state relationships, model uncertainty) must be considered and communicated during indicator assessments and model studies (Cartwright et al, 2016). Utilizing modeling support as a routine in the assessment cycle would ultimately improve long term planning for the marine environment.…”

Section: Discussionmentioning

confidence: 99%

Uses of Innovative Modeling Tools within the Implementation of the Marine Strategy Framework Directive

et al. 2016

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In Europe and around the world, the approach to management of the marine environment has developed from the management of single issues (e.g., species and/or pressures) toward holistic Ecosystem Based Management (EBM) that includes aims to maintain biological diversity and protect ecosystem functioning. Within the European Union, this approach is implemented through the Marine Strategy Framework Directive (MSFD, 2008/56/EC). Integrated Ecosystem Assessment is required by the Directive in order to assess Good Environmental Status (GES). Ecological modeling has a key role to play within the implementation of the MSFD, as demonstrated here by case studies covering a range of spatial scales and a selection of anthropogenic threats. Modeling studies have a strong role to play in embedding data collected at limited points within a larger spatial and temporal scale, thus enabling assessments of pelagic and seabed habitat. Furthermore, integrative studies using food web and ecosystem models are able to investigate changes in food web functioning and biological diversity in response to changes in the environment and human pressures. Modeling should be used to: support the development and selection of specific indicators; set reference points to assess state and the achievement of GES; inform adaptive monitoring programs and trial management scenarios. The modus operandi proposed shows how ecological modeling could support the decision making process leading to appropriate management measures and inform new policy.

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Section: Discussionmentioning

confidence: 99%

Uses of Innovative Modeling Tools within the Implementation of the Marine Strategy Framework Directive

et al. 2016

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“…This will increase the likelihood that: (a) the model is representative of the existing knowledge; (b) knowledge gaps are identified; and, (c) unforeseen relationships are accounted for properly. Lack of clarity about the units and meaning of the model parameters can lead to ambiguity or unintended consequences, and can potentially hinder acceptance by end-users (Cairney, Oliver, & Wellstead, 2016;Cartwright et al, 2016;Conroy & Peterson, 2013). Rather, it refers to specifying a model that accommodates all of the information assumed to influence the modeled processes while remaining sufficiently simple to address its conservation management purpose efficiently (i.e., "parsimony").…”

Section: Model Specificationmentioning

confidence: 99%

“…Propagating the uncertainty in parameters estimated from a statistical model that will be used in a simulation model is seamless when the outputs of the statistical model are distributions of values (Wade, 2002). The main shortcoming of this recommendation is that output distributions can be difficult to communicate to conservation managers (Cartwright et al, 2016;Hoffrage, Lindsey, Hertwig, & Gigerenzer, 2000;Parrott, 2017). Moreover, distributions are a core component of conservation decision-making techniques such as costeffectiveness analyses and stochastic dominance (Canessa, Ewen, West, McCarthy, & Walshe, 2016;Carwardine et al, 2012;Groves & Game, 2016).…”

Section: Model Inference and Usementioning

confidence: 99%

A concise guide to developing and using quantitative models in conservation management

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Anderson

et al. 2019

Conservation Science and Practice

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Quantitative models are powerful tools for informing conservation management and decision-making. As applied modeling is increasingly used to address conservation problems, guidelines are required to clarify the scope of modeling applications and to facilitate the impact and acceptance of models by practitioners. We identify three key roles for quantitative models in conservation management: (a) to assess the extent of a conservation problem; (b) to provide insights into the dynamics of complex social and ecological systems; and, (c) to evaluate the efficacy of proposed conservation interventions. We describe 10 recommendations to facilitate the acceptance of quantitative models in conservation management, providing a basis for good practice to guide their development and evaluation in conservation applications. We structure these recommendations within four established phases of model construction, enabling their integration within existing workflows: (a) design (two recommendations); (b) specification (two); (c) evaluation (one); and (d) inference (five). Quantitative modeling can support effective conservation management provided that both managers and modelers understand and agree on the place for models in conservation. Our concise review and recommendations will assist conservation managers and modelers to collaborate in the development of quantitative models that are fit-for-purpose, and to trust and use these models appropriately while understanding key drivers of uncertainty. K E Y W O R D Sapplied conservation, ecological models, prediction, projection, simulation model, statistical model, uncertainty GLOSSARY Conservation management: activities conducted with the primary aim of conserving species and systems to achieve maintenance or restoration of biodiversity features. Correlative or correlational model: a model representing noncausative associations between two or more variables.Differential equation: Mathematical equation that relates a function with one or more of its derivatives (i.e., the instantaneous rate of change of a function). For example, an expression for the rate of change (in space or time) of a population. Estimation: using data to approximate, with some degree of uncertainty, the parameter values of a model. Gene drive: a synthetic, self-replicating genetic element that can propagate one or more focal genes through a population.

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“…The availability of products and decision making timescales are often at odds with model development (Hyder et al, 2015a;Queirós et al, 2016). Communicating the outcomes and limitations of complex models to stakeholders is one of the main challenges when it comes to uptake and should be dealt with as part of the model building process (Cartwright et al, 2016).…”

Section: Optimizing Marine Monitoring Modeling In Current Monitoring mentioning

confidence: 99%

A Review of the Tools Used for Marine Monitoring in the UK: Combining Historic and Contemporary Methods with Modeling and Socioeconomics to Fulfill Legislative Needs and Scientific Ambitions

et al. 2017

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Marine environmental monitoring is undertaken to provide evidence that environmental management targets are being met. Moreover, monitoring also provides context to marine science and over the last century has allowed development of a critical scientific understanding of the marine environment and the impacts that humans are having on it. The seas around the UK are currently monitored by targeted, impact-driven, programmes (e.g., fishery or pollution based monitoring) often using traditional techniques, many of which have not changed significantly since the early 1900s. The advent of a new wave of automated technology, in combination with changing political and economic circumstances, means that there is currently a strong drive to move toward a more refined, efficient, and effective way of monitoring. We describe the policy and scientific rationale for monitoring our seas, alongside a comprehensive description of the types of equipment and methodology currently used and the technologies that are likely to be used in the future. We contextualize the way new technologies and methodologies may impact monitoring and discuss how whole ecosystems models can give an integrated, comprehensive approach to impact assessment. Furthermore, we discuss how an understanding of the value of each data point is crucial to assess the true costs and benefits to society of a marine monitoring programme.

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Communicating complex ecological models to non-scientist end users

Cited by 61 publications

References 50 publications

Uses of Innovative Modeling Tools within the Implementation of the Marine Strategy Framework Directive

Uses of Innovative Modeling Tools within the Implementation of the Marine Strategy Framework Directive

A concise guide to developing and using quantitative models in conservation management

A Review of the Tools Used for Marine Monitoring in the UK: Combining Historic and Contemporary Methods with Modeling and Socioeconomics to Fulfill Legislative Needs and Scientific Ambitions

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