Bringing Science to Management: using Simulation- and Scenario-Based Approaches to Guide Decision Making in Invasive Species Management
INTECOL 2013, London
Copyright: Rainer M Krug ([email protected])
Abstract
In science, simulation- and scenario-based approaches have been proven to be useful in understanding complex systems and their reaction to changing input parameters. This has been demonstrated for example by climate change models and scenarios which yield reproducible and transparent results. The downside of this approach is the need for substantial computing power and complexity of the tools used.
Abstract With the increasing availability of cloud computing, computing power can be re-located from the desktop to “the cloud”, and thus be made available for a wider audience. By building a simple user interface, interacting with complex simulation models in “the cloud”, simulation- and scenario-based approaches can be put at the fingertips of managers and be used to obtain reproducible and transparent results which may be used e.g. in invasive species management.
Abstract An example where this approach has be been shown to be of high value is at the interface of policy (funding priorities and levels), management (what and how much to spend where) and science (complex simulation- and scenario-based approach) by guiding the motivation for funding and the allocation of funds to removal of invasives.
Abstract The simulation model predicts the impact of different funding levels to motivate for appropriate funding, and at the same time provides a tool to develop and optimise management approaches within a particular budget scenario. These models can be designed so that they feed into other ecosystem service models, therefore allowing to quantify the impact of species invasions on different ecosystem services, dependent on budget scenarios and management practices.
Abstract With this aim in mind, we developed a model for scientific purposes (SpreadSim), which was been built for selected nature reserves in the Fynbos biome (South Africa) to simulate the spread of three different invasive alien plant groups (acacias, pines and hakeas) to
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predict the area under alien cover under different budget scenarios and
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to demonstrate the impact of different spatial prioritisation scenarios on the area under alien cover.
Abstract The model incorporates spatial and non-spatial information, fire and invasive plant spread simulation as well as costs of clearing and budgets. It is a stochastic rule based simulation model build in R, using GRASS for spatial data storage and processing as well as C++.
Abstract Simulations were run over 30 years, during which one prioritisation strategy was used, and the amount of area cleared per year was constrained by financial resources.
Abstract To date, this model has not yet been translated into a version to be used by e.g. managers. Efforts are now being made to adapt SpreadSim for use in the Drakensberg Nature Reserve (South Africa). This includes porting the model into “the cloud” and developing a simple friendly web interface so that managers can use the model to illustrate the impact of different budget scenarios, and determine the best spatial prioritisation strategy under a given budget.
Abstract In this talk, I will give an overview over the model developed for the Fynbos and discuss its adaptation for the Drakensberg as well as deployment options.
The talk is available at
The R packages are available at:
- https://github.com/rkrug/prioritization
- https://github.com/rkrug/seedGerm
- https://github.com/rkrug/fireSim
- https://github.com/rkrug/seedProd
- https://github.com/rkrug/seedDisp
- https://github.com/rkrug/logger
The final simulation will be available at: