US-IALE 2009: Overview and Fire
Last week I was at 2009 US-IALE in Snowbird, Utah. It was a great meeting; my presentations went down well, I participated in two stimulating symposia and a statistics workshop, heard interesting presentations that spanned a range of subjects, made new friends, talked about potential collaborations and even found time at the end of the week for a spot of Spring snowboarding. There was so much going on that I'm going to devote two other blog posts to the 'Complexity in Human-Nature Interactions across Landscapes' symposium and the 'Global Land Project Symposium on Agent-Based Modeling of Land Use Effects on Ecosystem Processes and Services'.
The conference plenary, entitled 'Facilitating the Conduct of Naturally Humane and Humanely Natural Research', was given by Thomas Baerwald, Senior Science Advisor at the National Science Foundation. In-keeping with his position, Baerwald dealt with several issues related to the execution of coupled human-natural type research, from the scientific or policy questions that need to be addressed to the mechanics of putting together a research team or proposal. Broadly, his comments could be interpreted (respectively) as i) CHANS research needs to provide a better understanding of the processes underlying observed dynamics, and ii) that effective teamwork (including developing a common language between researchers from diverse backgrounds) are required in the interdisciplinary research projects his department funds. Many questions and issues raised in the plenary were later addressed in the Complexity in Human-Nature Interactions symposium.
Two areas of research caught my attention in the Fire and Landscapes session. First was the ongoing work of Don McKenzie and his PostDoc Maureen Kennedy at USFS. Don has been examining the mechanisms behind scaling laws in wildfire regimes such as those I worked on during my Masters with Bruce Malamud. In particular, Don and Maureen are trying to determine whether scaling relationships like the power-law frequency-area wildfire distribution arise from physical mechanisms or are numerical artifacts of the way data are quantified.
In his presentation Don proposed that topographic controls on fire spread are the underlying driver for more proximate mechanisms that govern the observed scaling relationships. Maureen then demonstrated how they used a raster-based neutral model for fire history to generate fire history patterns to examine this. Using the neutral model, Maureen has found the expected value of Sorensen distance (a metric for fire co-occurrence between pairs of trees) depends both on the probability two trees are both in a given fire, and on the probability a tree that is in a fire records that fire with a scar [this is important given much wildfire regime data come from paleorecords of wildfire scars]. In turn, this is related to the topographic complexity of the simulated landscape.
In conclusion, Don suggested that "the search for mechanisms behind scaling laws in landscape ecology may be fruitful only when the scope of observed phenomena is sufficiently local to be in the domain of a contagious process... Power laws and other scaling relationships at broader scales, even if not simply numerical artifacts, are likely to be phenomenological in nature rather than governed by identifiable mechanisms." Thus, Don is arguing against trying to find mechanisms driving broad-scale patterns in wildfire regimes like those Bruce Malamud, George Perry, and I found for the ecoregions of the conterminous USA. The neutral model approach is certainly appealing and provides a definitive way to test the importance of a variety of variables. We've stalled lately on following-up on our PNAS paper, but the work Don and Maureen are tackling definitely provides some food for thought.
The second area of fire research that interested came from a distinctly different background. Francisco Seijo Maceiras discussed the governance of wildfire regimes. Following-up on previous work, Francisco developed the idea that the disruption of 'Pre-Industrial Anthropogenic Fire Regimes' (PIAFRs) - and the livelihoods and lifestyles of the social groups that generated them - is an important factor in changes in wildfire regimes in recent decades. Using Spain as an example, Francisco argues that changes in understanding regarding the ecological role of wildfire in landscapes (e.g. see Perry 2002) "provides an excellent opportunity for both re-enfranchising local communities regarding fire use and improving fire management." I am no expert in the history of Spanish wildfire policy but I can certainly see potential uses of my Landscape Fire Succession Model I to examine potential consequences of a change in wildfire management strategies from top-down, state-organised management towards those favoured by local community fire practitioners.
In another session I happened to drop in on, Virginia Dale gave an interesting presentation on climate change, land-use change, and energy use. What specifically caught my attention was her discussion of the use of the net environmental benefit framework for landscape ecologists to explore the land and water resource effects climate change and different energy options might bring. Papers will be appearing with more on that soon I believe.
On the final day of the meeting I attended the bayesian statistics workshop led by Mevin Hooten from Utah State University. The introduction looked at hierarchical models and the difference between forward models (e.g. forest simulation modelling: set the parameters, run the model, look at the data produced) and inverse model (e.g. linear regression: collect the data, think about how the process works, fit the parameters). Bayesian modelling is inverse modelling that uses conditional probability: first we specify a stochastic model that explains where the data come from (i.e. a likelihood) and a stochastic model for the parameters (i.e. a prior), then we fit the model by finding the posterior distribution of the parameters give the data. That's a very simplified explanation of the approach and the workshop proceeded to get technical. What re-affirmed my determination to experiment with this approach in the future were the examples Mevin's graduate students provided: Ephraim Hanks presented his work and a tutorial on the prediction of dwarf mistletoe incidence in Black Spruce stands of Northern Minnesota using Bayesian methods, and Ryan Wilson presented his work and a tutorial that used Bayesian methods to examine uncertainty, and multi-scale clustering in core area (habitat) characterisation of a variety of mammals (hopefully forthcoming in Ecology).
Even without my notes on the comments on the 'Complexity in Human-Nature Interactions across Landscapes' symposium and the 'Global Land Project Symposium on Agent-Based Modeling of Land Use Effects on Ecosystem Processes and Services' this has turned into a long blog post. There really was a lot on at the US-IALE this year. I hope to post on those symposia very soon.
The conference plenary, entitled 'Facilitating the Conduct of Naturally Humane and Humanely Natural Research', was given by Thomas Baerwald, Senior Science Advisor at the National Science Foundation. In-keeping with his position, Baerwald dealt with several issues related to the execution of coupled human-natural type research, from the scientific or policy questions that need to be addressed to the mechanics of putting together a research team or proposal. Broadly, his comments could be interpreted (respectively) as i) CHANS research needs to provide a better understanding of the processes underlying observed dynamics, and ii) that effective teamwork (including developing a common language between researchers from diverse backgrounds) are required in the interdisciplinary research projects his department funds. Many questions and issues raised in the plenary were later addressed in the Complexity in Human-Nature Interactions symposium.
Two areas of research caught my attention in the Fire and Landscapes session. First was the ongoing work of Don McKenzie and his PostDoc Maureen Kennedy at USFS. Don has been examining the mechanisms behind scaling laws in wildfire regimes such as those I worked on during my Masters with Bruce Malamud. In particular, Don and Maureen are trying to determine whether scaling relationships like the power-law frequency-area wildfire distribution arise from physical mechanisms or are numerical artifacts of the way data are quantified.
In his presentation Don proposed that topographic controls on fire spread are the underlying driver for more proximate mechanisms that govern the observed scaling relationships. Maureen then demonstrated how they used a raster-based neutral model for fire history to generate fire history patterns to examine this. Using the neutral model, Maureen has found the expected value of Sorensen distance (a metric for fire co-occurrence between pairs of trees) depends both on the probability two trees are both in a given fire, and on the probability a tree that is in a fire records that fire with a scar [this is important given much wildfire regime data come from paleorecords of wildfire scars]. In turn, this is related to the topographic complexity of the simulated landscape.
In conclusion, Don suggested that "the search for mechanisms behind scaling laws in landscape ecology may be fruitful only when the scope of observed phenomena is sufficiently local to be in the domain of a contagious process... Power laws and other scaling relationships at broader scales, even if not simply numerical artifacts, are likely to be phenomenological in nature rather than governed by identifiable mechanisms." Thus, Don is arguing against trying to find mechanisms driving broad-scale patterns in wildfire regimes like those Bruce Malamud, George Perry, and I found for the ecoregions of the conterminous USA. The neutral model approach is certainly appealing and provides a definitive way to test the importance of a variety of variables. We've stalled lately on following-up on our PNAS paper, but the work Don and Maureen are tackling definitely provides some food for thought.
The second area of fire research that interested came from a distinctly different background. Francisco Seijo Maceiras discussed the governance of wildfire regimes. Following-up on previous work, Francisco developed the idea that the disruption of 'Pre-Industrial Anthropogenic Fire Regimes' (PIAFRs) - and the livelihoods and lifestyles of the social groups that generated them - is an important factor in changes in wildfire regimes in recent decades. Using Spain as an example, Francisco argues that changes in understanding regarding the ecological role of wildfire in landscapes (e.g. see Perry 2002) "provides an excellent opportunity for both re-enfranchising local communities regarding fire use and improving fire management." I am no expert in the history of Spanish wildfire policy but I can certainly see potential uses of my Landscape Fire Succession Model I to examine potential consequences of a change in wildfire management strategies from top-down, state-organised management towards those favoured by local community fire practitioners.
In another session I happened to drop in on, Virginia Dale gave an interesting presentation on climate change, land-use change, and energy use. What specifically caught my attention was her discussion of the use of the net environmental benefit framework for landscape ecologists to explore the land and water resource effects climate change and different energy options might bring. Papers will be appearing with more on that soon I believe.
On the final day of the meeting I attended the bayesian statistics workshop led by Mevin Hooten from Utah State University. The introduction looked at hierarchical models and the difference between forward models (e.g. forest simulation modelling: set the parameters, run the model, look at the data produced) and inverse model (e.g. linear regression: collect the data, think about how the process works, fit the parameters). Bayesian modelling is inverse modelling that uses conditional probability: first we specify a stochastic model that explains where the data come from (i.e. a likelihood) and a stochastic model for the parameters (i.e. a prior), then we fit the model by finding the posterior distribution of the parameters give the data. That's a very simplified explanation of the approach and the workshop proceeded to get technical. What re-affirmed my determination to experiment with this approach in the future were the examples Mevin's graduate students provided: Ephraim Hanks presented his work and a tutorial on the prediction of dwarf mistletoe incidence in Black Spruce stands of Northern Minnesota using Bayesian methods, and Ryan Wilson presented his work and a tutorial that used Bayesian methods to examine uncertainty, and multi-scale clustering in core area (habitat) characterisation of a variety of mammals (hopefully forthcoming in Ecology).
Even without my notes on the comments on the 'Complexity in Human-Nature Interactions across Landscapes' symposium and the 'Global Land Project Symposium on Agent-Based Modeling of Land Use Effects on Ecosystem Processes and Services' this has turned into a long blog post. There really was a lot on at the US-IALE this year. I hope to post on those symposia very soon.
This work by James D.A. Millington is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License.
posted by James at Wednesday, April 22, 2009
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