Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation
Abstract Modelling is widely used in ecology and its utility continues to increase as scientists, managers and policy‐makers face pressure to effectively manage ecosystems and meet conservation goals with limited resources. As the urgency to forecast ecosystem responses to global change grows, so do...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Methods in Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/2041-210X.14034 |
| _version_ | 1797767013825773568 |
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| author | Ceres Barros Yong Luo Alex M. Chubaty Ian M. S. Eddy Tatiane Micheletti Céline Boisvenue David W. Andison Steven G. Cumming Eliot J. B. McIntire |
| author_facet | Ceres Barros Yong Luo Alex M. Chubaty Ian M. S. Eddy Tatiane Micheletti Céline Boisvenue David W. Andison Steven G. Cumming Eliot J. B. McIntire |
| author_sort | Ceres Barros |
| collection | DOAJ |
| description | Abstract Modelling is widely used in ecology and its utility continues to increase as scientists, managers and policy‐makers face pressure to effectively manage ecosystems and meet conservation goals with limited resources. As the urgency to forecast ecosystem responses to global change grows, so do the number and complexity of predictive ecological models and the value of iterative prediction, both of which demand validation and cross‐model comparisons. This challenges ecologists to provide predictive models that are reusable, interoperable, transparent and able to accommodate updates to both data and algorithms. We propose a practical solution to this challenge based on the PERFICT principles (frequent Predictions and Evaluations of Reusable, Freely accessible, Interoperable models, built within Continuous workflows that are routinely Tested), using a modular and integrated framework. We present its general implementation across seven common components of ecological model applications—(i) the modelling toolkit; (ii) data acquisition and treatment; (iii) model parameterisation and calibration; (iv) obtaining predictions; (v) model validation; (vi) analysing and presenting model outputs; and (vii) testing model code—and apply it to two approaches used to predict species distributions: (1) a static statistical model, and (2) a complex spatiotemporally dynamic model. Adopting a continuous workflow enabled us to reuse our models in new study areas, update predictions with new data, and re‐parameterise with different interoperable modules using freely accessible data sources, all with minimal user input. This allowed repeating predictions and automatically evaluating their quality, while centralised inputs, parameters and outputs, facilitated ensemble forecasting and tracking uncertainty. Importantly, the integrated model validation promotes a continuous evaluation of the quality of more‐ or less‐parsimonious models, which is valuable in predictive ecological modelling. By linking all stages of an ecological modelling exercise, it is possible to overcome common challenges faced by ecological modellers, such as changing study areas, choosing between different modelling approaches, and evaluating the appropriateness of the model. This ultimately creates a more equitable and robust playing field for both modellers and end users (e.g. managers), and contributes to position predictive ecology as a central contributor to global change forecasting. |
| first_indexed | 2024-03-12T20:33:37Z |
| format | Article |
| id | doaj.art-c31285ca8f284224bc2d6370468eb961 |
| institution | Directory Open Access Journal |
| issn | 2041-210X |
| language | English |
| last_indexed | 2024-03-12T20:33:37Z |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Methods in Ecology and Evolution |
| spelling | doaj.art-c31285ca8f284224bc2d6370468eb9612023-08-01T18:55:41ZengWileyMethods in Ecology and Evolution2041-210X2023-01-0114117318810.1111/2041-210X.14034Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisationCeres Barros0Yong Luo1Alex M. Chubaty2Ian M. S. Eddy3Tatiane Micheletti4Céline Boisvenue5David W. Andison6Steven G. Cumming7Eliot J. B. McIntire8Faculty of Forestry University of British Columbia Vancouver British Columbia CanadaFaculty of Forestry University of British Columbia Vancouver British Columbia CanadaFOR‐CAST Research & Analytics Calgary Alberta CanadaCanadian Forest Service (Pacific Forestry Centre) Natural Resources Canada Victoria British Columbia CanadaFaculty of Forestry University of British Columbia Vancouver British Columbia CanadaFaculty of Forestry University of British Columbia Vancouver British Columbia CanadaBandaloop Landscape‐Ecosystem Services Ltd. Nelson British Columbia CanadaFaculté de Foresterie, de Géographie et de Géomatique, Département des Sciences du Bois et de la Forêt, Pavillon Abitibi‐Price Université Laval Québec CanadaFaculty of Forestry University of British Columbia Vancouver British Columbia CanadaAbstract Modelling is widely used in ecology and its utility continues to increase as scientists, managers and policy‐makers face pressure to effectively manage ecosystems and meet conservation goals with limited resources. As the urgency to forecast ecosystem responses to global change grows, so do the number and complexity of predictive ecological models and the value of iterative prediction, both of which demand validation and cross‐model comparisons. This challenges ecologists to provide predictive models that are reusable, interoperable, transparent and able to accommodate updates to both data and algorithms. We propose a practical solution to this challenge based on the PERFICT principles (frequent Predictions and Evaluations of Reusable, Freely accessible, Interoperable models, built within Continuous workflows that are routinely Tested), using a modular and integrated framework. We present its general implementation across seven common components of ecological model applications—(i) the modelling toolkit; (ii) data acquisition and treatment; (iii) model parameterisation and calibration; (iv) obtaining predictions; (v) model validation; (vi) analysing and presenting model outputs; and (vii) testing model code—and apply it to two approaches used to predict species distributions: (1) a static statistical model, and (2) a complex spatiotemporally dynamic model. Adopting a continuous workflow enabled us to reuse our models in new study areas, update predictions with new data, and re‐parameterise with different interoperable modules using freely accessible data sources, all with minimal user input. This allowed repeating predictions and automatically evaluating their quality, while centralised inputs, parameters and outputs, facilitated ensemble forecasting and tracking uncertainty. Importantly, the integrated model validation promotes a continuous evaluation of the quality of more‐ or less‐parsimonious models, which is valuable in predictive ecological modelling. By linking all stages of an ecological modelling exercise, it is possible to overcome common challenges faced by ecological modellers, such as changing study areas, choosing between different modelling approaches, and evaluating the appropriateness of the model. This ultimately creates a more equitable and robust playing field for both modellers and end users (e.g. managers), and contributes to position predictive ecology as a central contributor to global change forecasting.https://doi.org/10.1111/2041-210X.14034dynamic and nondynamic ecological modellingforest stand dynamicspredictive ecologyRreproducible and continuous workflowsspecies distribution models |
| spellingShingle | Ceres Barros Yong Luo Alex M. Chubaty Ian M. S. Eddy Tatiane Micheletti Céline Boisvenue David W. Andison Steven G. Cumming Eliot J. B. McIntire Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation Methods in Ecology and Evolution dynamic and nondynamic ecological modelling forest stand dynamics predictive ecology R reproducible and continuous workflows species distribution models |
| title | Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation |
| title_full | Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation |
| title_fullStr | Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation |
| title_full_unstemmed | Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation |
| title_short | Empowering ecological modellers with a PERFICT workflow: Seamlessly linking data, parameterisation, prediction, validation and visualisation |
| title_sort | empowering ecological modellers with a perfict workflow seamlessly linking data parameterisation prediction validation and visualisation |
| topic | dynamic and nondynamic ecological modelling forest stand dynamics predictive ecology R reproducible and continuous workflows species distribution models |
| url | https://doi.org/10.1111/2041-210X.14034 |
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