@inproceedings{mcintire_getting_2016,
	address = {Forestry Adaptation Community of Practice, Webinar},
	title = {Getting to answers, in {SpaDES}},
	url = {https://drive.google.com/file/d/0B2ZNPaJoLI9xN2N6eFFESEl4Y00/view?usp=sharing},
	abstract = {Empirical data have a troublesome way of being both factually true, yet difficult to understand because they exist within a complex web of even more data. Worse, forecasting what the future will look like is an even greater challenge. Scientists have, for a long time, been working on these problems, often with great success. The standard venue for reporting these results has generally been peer reviewed journals. In 2016, this is not good enough: we are now at the point that policymakers must have faster access, and in a context-appropriate way, to the forecasts made by scientists.
Data collection, analysis and model building occurs over years to decades; policymaking must adapt to governments over days, weeks, months to years. This discrepancy in the speed of activity between science and policy has been widely known. But it is nevertheless a challenge to overcome. SpaDES is a new open-modeling platform that is transforming the way we build scientific models. inSpaDES is a set of new apps that run on top of SpaDES made to run on the web or on mobile platforms. The slow progression of scientific model building can happen at its pace. The faster policy and decision making can happen at their pace. Key to all this: it doesn’t matter what field of science that models are built in, SpaDES integrates across disciplines. So the answers provided by inSpaDES are cross-disciplinary and are based on whatever the latest, updated models are.
With this integrated system, we will finally ask apparently simple questions like:
* What is the forecasted probability of a spruce budworm outbreak in Chibougamau in the next 10 years?
* What are the forecasted economic costs for the forest sector in northwestern Ontario due to climate change?
Our answers will include the underlying complexity of the forests. To give the best answers to these questions, we need to be including fires, vegetation dynamics, cumulative effects, system feedbacks, economics, climate induced mortality and growth improvements and more even if they aren’t stated in the question. During this webinar, I will show the state of affairs of the SpaDES platform and the apps derived on top of it.},
	author = {McIntire, E. J. B.},
	year = {2016},
}

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The standard venue for reporting these results has generally been peer reviewed journals. In 2016, this is not good enough: we are now at the point that policymakers must have faster access, and in a context-appropriate way, to the forecasts made by scientists. Data collection, analysis and model building occurs over years to decades; policymaking must adapt to governments over days, weeks, months to years. This discrepancy in the speed of activity between science and policy has been widely known. But it is nevertheless a challenge to overcome. SpaDES is a new open-modeling platform that is transforming the way we build scientific models. inSpaDES is a set of new apps that run on top of SpaDES made to run on the web or on mobile platforms. The slow progression of scientific model building can happen at its pace. The faster policy and decision making can happen at their pace. Key to all this: it doesn’t matter what field of science that models are built in, SpaDES integrates across disciplines. So the answers provided by inSpaDES are cross-disciplinary and are based on whatever the latest, updated models are. With this integrated system, we will finally ask apparently simple questions like: * What is the forecasted probability of a spruce budworm outbreak in Chibougamau in the next 10 years? * What are the forecasted economic costs for the forest sector in northwestern Ontario due to climate change? Our answers will include the underlying complexity of the forests. To give the best answers to these questions, we need to be including fires, vegetation dynamics, cumulative effects, system feedbacks, economics, climate induced mortality and growth improvements and more even if they aren’t stated in the question. 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In 2016, this is not good enough: we are now at the point that policymakers must have faster access, and in a context-appropriate way, to the forecasts made by scientists.\nData collection, analysis and model building occurs over years to decades; policymaking must adapt to governments over days, weeks, months to years. This discrepancy in the speed of activity between science and policy has been widely known. But it is nevertheless a challenge to overcome. SpaDES is a new open-modeling platform that is transforming the way we build scientific models. inSpaDES is a set of new apps that run on top of SpaDES made to run on the web or on mobile platforms. The slow progression of scientific model building can happen at its pace. The faster policy and decision making can happen at their pace. Key to all this: it doesn’t matter what field of science that models are built in, SpaDES integrates across disciplines. 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