Tangible geospatial modeling for collaborative solutions to invasive species management

Tonini, Francesco; Shoemaker, Douglas A.; Petrášová, Anna; Harmon, Brendan; Petras, Vaclav; Cobb, Richard C.; Mitášová, Helena; Meentemeyer, Ross K.

doi:10.1016/j.envsoft.2017.02.020

Cited by 13 publications

(22 citation statements)

References 36 publications

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“…Models that are inaccessible to stakeholders are likely to be overlooked; therefore, intuitive interfaces are essential for PM [7,16–18,48]. Coupling the epidemiological model with Tangible Landscape encouraged participants to collaboratively design management scenarios, visualize underlying spatial data and assess the stochastic uncertainty of results [18,35]. In our surveys, participants overwhelmingly rated the system as intuitive and easy to use (figure 3 d , e ) and we expect this was integral to promoting communication.…”

Section: Discussionmentioning

confidence: 99%

“…A majority of participants agreed, indicating that the system would facilitate collaboration (figure 3 g ). Previous work with Tangible Landscape [18] demonstrated that the platform can help users quickly grasp and communicate essential model properties. For PM to be applied in other disease systems, assessing and improving the interface will likely be of critical importance.…”

Section: Discussionmentioning

confidence: 99%

“…To simulate disease spread in Oregon, we adapted an existing modelling framework originally developed to explore disease dynamics in California [5,18,40]. These stochastic, spatially explicit simulations integrate the effects of host density and weather conditions on pathogen transmission and establishment.…”

Section: Methodsmentioning

confidence: 99%

“…These stochastic, spatially explicit simulations integrate the effects of host density and weather conditions on pathogen transmission and establishment. For a detailed model description, including key data requirements, model processes and links to source code, see electronic supplementary material, Appendix SB; [5,18,40].…”

Section: Methodsmentioning

confidence: 99%

“…The resulting model outcomes are visualized on the study area, allowing users to quickly and intuitively assess how their actions affected disease spread [18,35]. A pilot study using Tangible Landscape to evaluate SOD control measures found that users quickly learned model processes, intuitively explored management scenarios and learned from other participants, making this system ideal for PM applications [18]. For further discussion of the Tangible Landscape tool, see electronic supplementary material, Appendix SB.…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

Forecasting and control of emerging infectious forest disease through participatory modelling

Gaydos

Petrášová

Cobb

et al. 2019

Phil. Trans. R. Soc. B

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Epidemiological models are powerful tools for evaluating scenarios and visualizing patterns of disease spread, especially when comparing intervention strategies. However, the technical skill required to synthesize and operate computational models frequently renders them beyond the command of the stakeholders who are most impacted by the results. Participatory modelling (PM) strives to restructure the power relationship between modellers and the stakeholders who rely on model insights by involving these stakeholders directly in model development and application; yet, a systematic literature review indicates little adoption of these techniques in epidemiology, especially plant epidemiology. We investigate the potential for PM to integrate stakeholder and researcher knowledge, using Phytophthora ramorum and the resulting sudden oak death disease as a case study. Recent introduction of a novel strain (European 1 or EU1) in southwestern Oregon has prompted significant concern and presents an opportunity for coordinated management to minimize regional pathogen impacts. Using a PM framework, we worked with local stakeholders to develop an interactive forecasting tool for evaluating landscape-scale control strategies. We find that model co-development has great potential to empower stakeholders in the design, development and application of epidemiological models for disease control. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Forecasting and control of emerging infectious forest disease through participatory modelling

Gaydos

Petrášová

Cobb

et al. 2019

Phil. Trans. R. Soc. B

Self Cite

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Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions

Gaydos

Jones

et al. 2021

Ecological Applications

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Ecological forecasts will be best suited to inform intervention strategies if they are accessible to a diversity of decision‐makers. Researchers are developing intuitive forecasting interfaces to guide stakeholders through the development of intervention strategies and visualization of results. Yet, few studies to date have evaluated how user interface design facilitates the coordinated, cross‐boundary management required for controlling biological invasions. We used a participatory approach to develop complementary tangible and online interfaces for collaboratively forecasting biological invasions and devising control strategies. A diverse group of stakeholders evaluated both systems in the real‐world context of controlling sudden oak death, an emerging forest disease killing millions of trees in California and Oregon. Our findings suggest that while both interfaces encouraged adaptive experimentation, tangible interfaces are particularly well suited to support collaborative decision‐making. Reflecting on the strengths of both systems, we suggest workbench‐style interfaces that support simultaneous interactions and dynamic geospatial visualizations.

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Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of Parthenium hysterophorus in China

Liu,

Wei,

Zheng

et al. 2023

Ecology and Evolution

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AimAs invasive plants are often in a non‐equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas.LocationTropical monsoon rainforest and subtropical evergreen broad‐leaved forest regions in China.MethodsWe took Parthenium hysterophorus as a case study to predict its potential invasion risk using climate, terrain, and human activity variables. First, a generalized joint attribute model (GJAM) was constructed using the occurrence of P. hysterophorus and its 27 closely related species in Taiwan, given it is widely distributed in Taiwan. Based on the output correlation values, two positively correlated species (Cardiospermum halicacabum and Portulaca oleracea) and one negatively correlated species (Crassocephalum crepidioides) were selected as indicator species. Second, the distributions of P. hysterophorus and its indicator species in the study area were predicted separately using an ensemble model (EM). Third, when selecting indicator species to construct indicator SDMs, two treatments (indicator species with positive correlation only, or both positive and negative correlation) were considered. The indicator species' EM predictions were overlaid using a weighted average method, and a better indicator SDMs prediction result was selected by comparison. Finally, the EM prediction result of P. hysterophorus was used to optimize the indicator SDMs result by a maximum overlay.ResultsThe optimized indicator SDMs prediction showed an expanded range beyond the current geographic range compared to EM and the thresholds for predicting key environmental variables were wider. It also reinforced the human activities' influence on the potential distribution of P. hysterophorus.Main ConclusionsFor invasive plants with expanding ranges, information about indicator species distribution can be borrowed as a barometer for areas not currently invaded. The optimized indicator SDMs allow for more efficient potential invasion risk prediction. On this basis, invasive plants can be prevented earlier.

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Tangible geospatial modeling for collaborative solutions to invasive species management

Cited by 13 publications

References 36 publications

Forecasting and control of emerging infectious forest disease through participatory modelling

Forecasting and control of emerging infectious forest disease through participatory modelling

Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions

Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of Parthenium hysterophorus in China

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