Communicating complex ecological models to non-scientist end users
Authors: Cartwright, S.J., Bowgen, K.M., Collop, C., Hyder, K., Nabe-Nielsen, J., Stafford, R., Stillman, R.A., Thorpe, R.B. and Sibly, R.M.
Journal: Ecological Modelling
Volume: 338
Pages: 51-59
ISSN: 0304-3800
DOI: 10.1016/j.ecolmodel.2016.07.012
Abstract:© 2016Complex computer models are used to predict how ecological systems respond to changing environmental conditions or management actions. Communicating these complex models to non-scientists is challenging, but necessary, because decision-makers and other end users need to understand, accept, and use the models and their predictions. Despite the importance of communicating effectively with end users, there is little guidance available as to how this may be achieved. Here, we review the challenges typically encountered by modellers attempting to communicate complex models and their outputs to managers and other non-scientist end users. We discuss the implications of failing to communicate effectively in each case. We then suggest a general approach for communicating with non-scientist end users. We detail the specific elements to be communicated using the example of individual-based models, which are widely used in ecology. We demonstrate that despite their complexity, individual-based models have characteristics that can facilitate communication with non-scientists. The approach we propose is based on our experiences and methods used in other fields, but which until now have not been synthesised or made broadly available to ecologists. Our aim is to facilitate the process of communicating with end users of complex models and encourage more modellers to engage in it by providing a structured approach to the communication process. We argue that developing measures of the effectiveness of communication with end users will help increase the impact of complex models in ecology.
https://eprints.bournemouth.ac.uk/24492/
Source: Scopus
Communicating complex ecological models to non-scientist end users
Authors: Cartwright, S.J., Bowgen, K.M., Collop, C., Hyder, K., Nabe-Nielsen, J., Stafford, R., Stillman, R.A., Thorpe, R.B. and Sibly, R.M.
Journal: Ecological Modelling
Volume: 338
Pages: 51-59
ISSN: 0304-3800
DOI: 10.1016/j.ecolmodel.2016.07.012
Abstract:Complex computer models are used to predict how ecological systems respond to changing environmental conditions or management actions. Communicating these complex models to non-scientists is challenging, but necessary, because decision-makers and other end users need to understand, accept, and use the models and their predictions. Despite the importance of communicating effectively with end users, there is little guidance available as to how this may be achieved. Here, we review the challenges typically encountered by modellers attempting to communicate complex models and their outputs to managers and other non-scientist end users. We discuss the implications of failing to communicate effectively in each case. We then suggest a general approach for communicating with non-scientist end users. We detail the specific elements to be communicated using the example of individual-based models, which are widely used in ecology. We demonstrate that despite their complexity, individual-based models have characteristics that can facilitate communication with non-scientists. The approach we propose is based on our experiences and methods used in other fields, but which until now have not been synthesised or made broadly available to ecologists. Our aim is to facilitate the process of communicating with end users of complex models and encourage more modellers to engage in it by providing a structured approach to the communication process. We argue that developing measures of the effectiveness of communication with end users will help increase the impact of complex models in ecology.
https://eprints.bournemouth.ac.uk/24492/
Source: Scopus
Communicating complex ecological models to non-scientist end users
Authors: Cartwright, S.J., Bowgen, K.M., Collop, C., Hyder, K., Nabe-Nielsen, J., Stafford, R., Stillman, R.A., Thorpe, R.B. and Sibly, R.M.
Journal: ECOLOGICAL MODELLING
Volume: 338
Pages: 51-59
eISSN: 1872-7026
ISSN: 0304-3800
DOI: 10.1016/j.ecolmodel.2016.07.012
https://eprints.bournemouth.ac.uk/24492/
Source: Web of Science (Lite)
Communicating complex ecological models to non-scientist end users
Authors: Cartwright, S.J., Bowgen, K.M., Collop, C.M., Hyde, K., Nabe-Nielsen, J., Stafford, R., Stillman, R., Thorpe, R.B. and Sibley, R.M.
Journal: Ecological Modelling
Volume: 338
Pages: 51-59
ISSN: 1872-7026
Abstract:Complex computer models are used to predict how ecological systems respond to changing environ- mental conditions or management actions. Communicating these complex models to non-scientists is challenging, but necessary, because decision-makers and other end users need to understand, accept, and use the models and their predictions. Despite the importance of communicating effectively with end users, there is little guidance available as to how this may be achieved. Here, we review the challenges typically encountered by modellers attempting to communicate complex models and their outputs to managers and other non-scientist end users. We discuss the implications of failing to communicate effec- tively in each case. We then suggest a general approach for communicating with non-scientist end users. We detail the specific elements to be communicated using the example of individual-based models, which are widely used in ecology. We demonstrate that despite their complexity, individual-based models have characteristics that can facilitate communication with non-scientists. The approach we propose is based on our experiences and methods used in other fields, but which until now have not been synthesised or made broadly available to ecologists. Our aim is to facilitate the process of communicating with end users of complex models and encourage more modellers to engage in it by providing a structured approach to the communication process. We argue that developing measures of the effectiveness of communication with end users will help increase the impact of complex models in ecology.
https://eprints.bournemouth.ac.uk/24492/
Source: Manual
Communicating complex ecological models to non-scientist end users
Authors: Cartwright, S.J., Bowgen, K., Collop, C., Hyde, K., Nabe-Nielsen, J., Stafford, R., Stillman, R.A., Thorpe, R.B. and Sibley, R.M.
Journal: Ecological Modelling
Volume: 338
Pages: 51-59
ISSN: 1872-7026
Abstract:Complex computer models are used to predict how ecological systems respond to changing environ- mental conditions or management actions. Communicating these complex models to non-scientists is challenging, but necessary, because decision-makers and other end users need to understand, accept, and use the models and their predictions. Despite the importance of communicating effectively with end users, there is little guidance available as to how this may be achieved. Here, we review the challenges typically encountered by modellers attempting to communicate complex models and their outputs to managers and other non-scientist end users. We discuss the implications of failing to communicate effec- tively in each case. We then suggest a general approach for communicating with non-scientist end users. We detail the specific elements to be communicated using the example of individual-based models, which are widely used in ecology. We demonstrate that despite their complexity, individual-based models have characteristics that can facilitate communication with non-scientists. The approach we propose is based on our experiences and methods used in other fields, but which until now have not been synthesised or made broadly available to ecologists. Our aim is to facilitate the process of communicating with end users of complex models and encourage more modellers to engage in it by providing a structured approach to the communication process. We argue that developing measures of the effectiveness of communication with end users will help increase the impact of complex models in ecology.
https://eprints.bournemouth.ac.uk/24492/
Source: BURO EPrints