Tag: Wildfire

Posted on

Traditional Fire Knowledge in Spain

When you haven’t done something for a while it’s often best not to rush straight back in at the intensity you were at before. So here’s a nice easy blog to get me going again (not that I was blogging intensely before!).

I didn’t blog about it at the time (unsurprisingly), but back in late June 2013 I went to visit a colleague of mine in Madrid, Dr Francisco Seijo. Francisco and I met back at something I did blog about, the 2009 US-IALE conference in Snowbird. Since then we’ve been discussing how we can use the idea of coupled-human and natural systems to investigate Mediterranean landscapes.

Example of Traditional Fire Knowledge. The ‘pile-burning’ technique involves raking, piling and igniting leaves. This contrasts with ‘a manta’ broadcast burning in which leaves and ground litter are burned across larger areas. Photos by the authors of the paper.

After a brief field visit by me, an interview campaign by Francisco, collection of secondary data from other sources (aerial photography and official fire statistics) and some desk analysis, we recently published our first paper on the work. Entitled Forgetting fire: Traditional fire knowledge in two chestnut forest ecosystems of the Iberian Peninsula and its implications for European fire management policy, and published in the journal Land Use Policy, the article presents the results of our mixed-methods and interdisciplinary approach. Building on Francisco’s previous examination of ‘pre-industrial anthropogenic fire regimes’ we to to investigate differences between the fire regimes and management approaches of chestnut forest ecosystems in two municipalities in central Spain. In the paper we also discuss ideas of Traditional Ecological Knowledge (TEK), the related idea of Traditional Fire Knowledge (TFK), and discuss them in light of contemporary fire management approaches in Europe.

The full abstract is below with links to the paper. I’ll stop here now as this rate of blogging it making me quite dizzy (but hopefully I’ll be back for more soon).

—-

Seijo, Francisco, James DA Millington, Robert Gray, Verónica Sanz, Jorge Lozano, Francisco García-Serrano, Gabriel Sangüesa-Barreda, and Jesús Julio Camarero (2015) Forgetting fire: Traditional fire knowledge in two chestnut forest ecosystems of the Iberian Peninsula and its implications for European fire management policy. Land Use Policy 47 130-144. doi: 10.1016/j.landusepol.2015.03.006
[Online] [Pre-print]

Abstract

Human beings have used fire as an ecosystem management tool for thousands of years. In the context of the scientific and policy debate surrounding potential climate change adaptation and mitigation strategies, the importance of the impact of relatively recent state fire exclusion policies on fire regimes has been debated. To provide empirical evidence to this ongoing debate we examine the impacts of state fire exclusion policies in the chestnut forest ecosystems of two geographically neighbouring municipalities in central Spain, Casillas and Rozas de Puerto Real. Extending the concept of ‘Traditional Ecological Knowledge’ to include the use of fire as a management tool as ‘Traditional Fire Knowledge’ (TFK), we take a mixed-methods and interdisciplinary approach to argue that currently observed differences between the municipalities are useful for considering the characteristics of “pre-industrial anthropogenic fire regimes” and their impact on chestnut forest ecosystems. We do this by examining how responses from interviews and questionnaire surveys of local inhabitants about TFK in the past and present correspond to the current biophysical landscape state and recent fire activity (based on data from dendrochronological analysis, aerial photography and official fire statistics). We then discuss the broader implications of TFK decline for future fire management policies across Europe particularly in light of the published results of the EU sponsored FIRE PARADOX research project. In locations where TFK-based “pre-industrial anthropogenic fire regimes” still exist, ecosystem management strategies for adaptation and mitigation to climate change could be conceivably implemented at a minimal economic and political cost to the state by local communities that have both the TFK and the adequate social, economic and cultural incentives to use it.

Key words

Fire exclusion policies; traditional ecological knowledge; traditional fire knowledge; Chestnut forest ecosystems; FIRE PARADOX

 

Posted on

US-IALE 2010 Notes

The 25th US-IALE annual meeting I attended in Athens, Georgia, a couple of weeks ago was notable for the presence of so many important figures in the field of landscape ecology. Several gave interesting plenary talks and the Presidents Symposium had presentations by many of the previous US-IALE Presidents and past editors of the journal Landscape Ecology. I also attended interesting presentations and discussion in the wildfire symposium and elsewhere.

Plenary Presentations
In the introductory plenary Profs. Richard Forman, Gary Barrett and Monica Turner gave their views on the origins and state of the field. Forman described his PhD work, rooted in the theory of island biogeography, in a Pine barrens landscape. He told how he suddenly realised he had been ignoring the context of his ‘islands’ and decided to look at how he might consider his study area as a landscape of patches arranged in a mosaic. He also talked about the ‘ecumenicalism of landscape ecology’ and how it is an important field for the development of interdisciplinary human-environment research.

Barrett spoke about the importance of the Allerton Park meeting in 1983 and the relationship of landscape ecology to the LTER network. He highlighted that landscape ecology is a ‘meeting point of [ecological] theory and application’ and the creation of the journal Ecological Applications (but also noted the creation 27 years earlier of the Journal of Applied Ecology).

Turner, the organiser of the very first US-IALE meeting, pointed out how similar current research themes are to those of 25 years ago. Questions still of relevance to landscape ecology include those about the relative importance of different drivers of ecological patterns and the importance of heterogeneity for driving ecosystem processes and species interactions.

Of the other plenary presentations, I found Joe Tainter’s presentation very interesting. His ‘big’ talk discussed the rise and fall of civilisations from the perspective of social and cultural complexity and Energy Return On Energy Investment (EROEI). He highlighted that sustaining complex societies requires a high EROEI and used the Roman and Byzantine Empires as examples to illustrate this. He stressed that sustainability is an active condition of problem solving – the capacity for which must itself be sustained – and questioned whether renewable energy resources (such as solar and wind power) have sufficient EROEI to allow us to do that in the future.

Presidents Symposium
In the Presidents Symposium, Jianguo Wu provided a pluralistic and hierarchical perspective of landscape ecology. Wu argued that the goal of landscape ecology should not just be about reporting on landscapes but about changing them. He also argued that the human landscape is the ‘most operational spatial scale for sustainability science’. He highlighted the formation of two new sections in the landscape ecology journal; ‘Landscape Ecology in Review’ and ‘Landscape Ecology in Practice’.

These issues were taken up later in the same session by Paul Opdam who discussed the transfer of pattern-process knowledge to society (as he wrote about with Joan Iverson Nassauer). He argued that there are three ways to do this; i) by asking questions about how our scientific knowledge is used in practice by planners, managers and stakeholders, ii) developing methods by testing them in practice, and iii) co-producing knowledge with non-scientists. He also argue that practical application of knowledge is the key methods for the ‘learning scientist’ and that research along these lines would be welcomed in the Landscape Ecology in Practice section of the journal.

Wildfire Symposium
The wildfires session contained some familiar faces. Rachel Loehman and Maureen Kennedy presented progress on their wildfire-related models and Don McKenzie outlined his efforts to take much of the recent work towards a coherent ‘theory of landscape fire’. The key elements to this theory he suggested would be energy, regulation (management) and scaling. In particular he emphasizes that we need to work hard on understanding the importance of landscape memory and the legacy of previous wildfire events on future ones.

Particularly encouraging to see was the work by Paul Hessburg and Nick Povak on self-organization and wildfire scaling in California (using data for 1950-2007). They argued that broken-stick regression is needed to represented their wildfire frequency-area data, as scale free power-law behaviour is only present across about two orders of magnitude in the medium size fires. At the lower end of the frequency-area distribution (smaller, frequent fires) they suggested bottom-up controls on the wildfire regime due to insects, stand dynamics and topography, and at the upper end of the frequency-area distribution (larger, infrequent fires) they suggested top-down controls on the wildfire regime due to climate and geology. This work examining the drivers of different wildfire regime scaling statistics certainly seems to be the way to go.

Other Discussions
My presentation seemed to go down well and I got some interesting questions. Frederik Doyon of Université du Québec en Outaouai was particularly interested in our work in the mixed hardwood-conifer forests of Michigan. Also in my session, Maria Santos presented her work comparing culture and ecology between the Mediterranean oak woodland landscapes of Portugal and California. We discussed some of the links between her work and my PhD research.

All round it was a good meeting with some interesting discussions in the various plenary session, symposia and in the pub. Here’s to another 25 years of US-IALE.

Posted on

US-IALE 2010 Preparation

Next week is the Twenty-fifth Anniversary Symposium of the US chapter of the International Association of Landscape Ecology (US-IALE). I’ll be in attendance in Athens, Georgia and am currently working on my presentation, entitled Ecological-economic modeling for sustainable forest management (scheduled for Thursday 8th, 2.20pm in room T/U). In the context of our larger modelling project I’ll present work we’ve published, stuff we’re still working on, and the initial results from putting it all together.

Several symposia have been organised and I plan to be at those that consider landscape ecology and wildfires, bioenergy and land-use change, and climate change and landscape connectivity. Particularly interesting should be Don McKenzie’s presentations on ecosystem energetics and scaling laws in the wildfire symposium and Paul Opdam’s presentations on Natura 2000 and the role of landscape ecology in the climate change symposium. Two of the plenary addresses I’d like to catch are Collapse and Sustainability: Lessons from History (Joseph A Tainter) and Linking Renaissance Ecologists with Citizen Scientists to Advanced Scientific Research and Literacy (Carol Brewer).

As usual CSIS has a strong presence at US-IALE this year with seven presentations, including the insights of Jack Liu and Wu Yang into the challenges and opportunities for landscape ecology and conservation in coupled human natural research, the analysis by Andres Vina and Xiaodong Chen of the potential conservation benefits that might be offset by natural disasters, Mao-Ning Tuanmu’s work on Giant Panda habitat and the work by Pete Esselman and Dana Infante on the National Assessment of the Status of Fish Habitat. The full list of CSIS presentations is below.

It’s shaping up to be a good couple of days! I’ll try to tweet and blog some thoughts as they arise during the conference and maybe reflect on things afterwards also.

CSIS Presentations at US-IALE 2010
6th April
Are conservation benefits offset by natural disasters? — The case of the May 12, 2008 Wenchuan Earthquake. Andrés Viña, Xiaodong Chen, Wei Liu, et al.

Coupling human and natural systems: Challenges and opportunities for landscape ecologists. Jianguo Liu

The spatial framework and results of the initial National Assessment of the Status of Fish Habitat. Peter C Esselman, Dana M Infante, et al.

7th April
Effects of human-environment relationships on the spatiotemporal dynamics of giant panda habitat. Mao-Ning Tuanmu, Wei Liu, Andrés Viña, et al.

8th April
Ecological-economic modeling for sustainable forest management. James D A Millington, Michael B Walters, Megan S Matonis, et al.

Mechanisms for effective conservation in coupled human-natural systems. Wu Yang, Wei Liu, Mao-Ning Tuanmu, et al.

Patterns and drivers of reforestation: A case study in the Qinling Mountains, China. Yu Li, Andrés Viña, Jianguo Liu

Posted on

Holiday Publications!

Update January 2010: This paper is now online with doi 10.1016/j.foreco.2009.12.020.

I received some good news this morning as I prepared to head back to the UK for the holidays. The paper I started writing back in January examining the white-tailed deer distribution in our managed forest landscape (the analysis for which inspired posts on Bayesian and ensemble modelling) has been accepted for publication and is ‘In Press’! I’ve copied the abstract below.

Another piece of publications news I received a while back is that the paper I co-authored with Raul Romero-Calcerrada and others modelling socioeconomic data to understand patterns of human-caused wildfire ignition risk has now officially been published in Ecological Modelling.

Happy Holidays everyone!

Effects of local and regional landscape characteristics on wildlife distribution across managed forests (In Press) Millington, Walters, Matonis, and Liu Forest Ecology and Management

Abstract
Understanding impacts of local and regional landscape characteristics on spatial distributions of wildlife species is vital for achieving ecological and economic sustainability of forested landscapes. This understanding is important because wildlife species such as white-tailed deer (Odocoileus virginianus) have the potential to affect forest dynamics differently across space. Here, we quantify the effects of local and regional landscape characteristics on the spatial distribution of white-tailed deer, produce maps of estimated deer density using these quantified relationships, provide measures of uncertainty for these maps to aid interpretation, and show how this information can be used to guide co-management of deer and forests. Specifically, we use ordinary least squares and Bayesian regression methods to model the spatial distribution of white-tailed deer in northern hardwood stands during the winter in the managed hardwood-conifer forests of the central Upper Peninsula of Michigan, USA. Our results show that deer density is higher nearer lowland conifer stands and in areas where northern hardwood trees have small mean diameter-at-breast-height. Other factors related with deer density include mean northern hardwood basal area (negative relationship), proportion of lowland conifer forest cover (positive relationship), and mean daily snow depth (negative relationship).The modeling methods we present provide a means to identify locations in forest landscapes where wildlife and forest managers may most effectively co-ordinate their actions.

Keywords: wildlife distribution; landscape characteristics; managed forest; ungulate herbivory; northern hardwood; lowland conifer; white-tailed deer

Posted on

Disturbance and Landscape Dynamics in a Changing World

Experimentation can be tricky for landscape ecologists, especially if we’re considering landscapes at the human scale (it’s a bit easier at the beetle scale [pdf]). The logistic constraints of studies at large spatial and temporal scales mean we frequently use models and modelling. However, every-now-and-then certain events afford us the opportunity for a ‘natural experiment’ – situations that are not controlled by an experimenter but approximate controlled experimental conditions. In her opening plenary at ESA 2009, Prof. Monica Turner used one such natural experiment – the Yellowstone fires of 1988 – as an exemple to discuss how disturbance affects landscape dynamics and ecosystem processes. Although this is a great example for landscapes with limited human activity, it is not such a useful tool for considering human-dominated landscapes.


Landsat satellite image of the Yellowstone fires on 23rd August 1988. The image is approximately 50 miles (80 km) across and shows light from the green, short-wave infrared, and near infrared bands of the spectrum. The fires glow bright pink, recently burned land is dark red, and smoke is light blue.

Before getting into the details, one of the first things Turner did was to define disturbance (drawing largely on Pickett and White) and an idea that she views as critical to landscape dynamics – the shifting mosaic steady state. The shifting mosaic steady state, as described by Borman and Likens, is a product of the processes of vegetation disturbance and succession. Although these processes mean that vegetation will change through time at individual points, when measured over a larger area the proportion of the landscape in each seral stage (of succession) remains relatively constant. Consequently, over large areas and long time intervals the landscape can be considered to be in equilibrium (but this isn’t necessarily always the case).

Other key ideas Turner emphasised were:

  • disturbance is a key component in ecosystems across many scales,

  • disturbance regimes are changing rapidly but the effects are difficult to predict,

  • disturbance and heterogeneity have reciprocal effects.

Landscape Dynamics
In contrast to what you might expect, very large disturbances generally increase landscape heterogeneity. For example, the 1988 Yellowstone fires burned 1/3 of the park in all forest types and ages but burn severity varied spatially. Turner highlighted that environmental thresholds may determine whether landscape pattern constrains fire spread. For instance, in very dry years spatial pattern will likely have less effect than years where rainfall has produced greater spatial variation in fuel conditions.

Turner and her colleagues have also found that burn severity, patch size and geographic location affected early succession in the years following the Yellowstone fires. Lodgepole pine regeneration varied enormously across the burned landscape because of the spatial variation in serotiny and burn severity. Subsequently, the size, shape and configuration of disturbed patches influenced succession trajectories. Turner also highlighted that succession is generally more predictable in small patches, when disturbances are infrequent, and when disturbance severity/intensity is low (and vice versa).

Ecosystem Processes
One of the questions landscape ecologists have been using the Yellowstone fires to examine is; do post-disturbance patterns affect ecosystem processes? Net Primary Production varies a lot with tree density (e.g., density of lodgepole pine following fire) and the post-fire patterns of tree density have produced a landscape mosaic of ecosystem process rates. For example, Kashian and colleagues found spatial legacy effects of the post-fire mosaic can last for centuries. Furthermore, this spatial variation in ecosystem process rates is greater than temporal variation and the fires produced a mosaic of different functional trajectories (a ‘functional mosaic’).

Another point Turner was keen to make was that the Yellowstone fires were not the result of fire suppression as is commonly attributed, but instead they were driven by climate (particularly hot and dry conditions). Later in the presentation she used the ecosystem process examples above to argue that the Yellowstone fires were not an ecological disaster and that the ecosystem has proven resilient. However, she stressed that fire will continue to be an important disturbance and that the fire regimes is likely to change rapidly if climate does. For example, Turner highlighted the study by Westerling and colleagues that showed that increased fire activity in the western US in recent decades is a result of increasing temperatures, earlier spring snowmelt and subsequent increases in vegetation moisture deficit. If climate change projections of warming are realised, by 2100 the climate of 1988 (which was extreme) could become the norm and events like the Yellowstone fires will be much more frequent. For example, using a spatio-temporal state-space diagram (seebelow), Turner and colleagues [pdf] found that fires in Yellowstone during the 15 years previous to 1988 had relatively little impact on landscape dynamics (shown in green in the lower left of the diagram). However, the extent of the 1988 fires pushed the disturbance regime up into an area of the state-space not characteristic of a shifting-mosaic steady state (shown in red).


The spatio-temporal state-space diagram used by Turner and colleagues [pdf] to describe potential landscape disturbance dynamics. On the horizontal x-axis is the ratio of disturbance extent (area) to the landscape area and on the vertical y-axis is the ratio of disturbance interval (time) to recovery interval. Landscapes in the upper left of the diagram will appear to an observer as relatively constant in time with little disturbance impact; those in the lower right are dominated by disturbance.

Remaining Questions
Turner finished her presentation by highlighting what she sees as key questions for studying disturbance and landscape dynamics in a changing world:

  • How will disturbance interact with one another?

  • How will disturbances interact with other drivers?

  • What conditions will cause qualitative shifts in disturbance regimes (like that shown in the diagram above)?

It was comforting to hear that a leader in the field identified these points as important as many of them relate closely to what I’ve been working on thinking about. For example, the integrated ecological-economic forest modelling project I’m working on here in Michigan explicitly considers the interaction of two disturbances – human timber harvest and deer herbivory. The work I initiated during my PhD relates to the second question – how does human land use/cover change interact and drive changes in the wildfire regime of a landscape in central Spain? And recently, I reviewed a new book on threshold modelling in ecological restoration for Landscape Ecology.

Much of Turner’s presentation and discussion applied to American landscapes with limited human activity. This not surprising of course, given the context of the presentation (at the Ecological Society of America) and the location of her study areas (all in the USA). But although natural experiments like the 1988 Yellowstone fires may be useful as an analogue to understand processes and dynamics in similar systems, it is also interesting (and important) to think about how other systems potentially differ from this examplar. For example, the Yellowstone fires natural experiment has little to say about disturbance in human-dominated landscapes that are prevalent in many areas of the world (such as the Mediterranean Basin). In the future, research and models of landscape succession-disturbance dynamics will need to focus as much attention on human drivers of change as environmental drivers.

Turner concluded her plenary by emphasising that ecologists must increase their efforts to understand and anticipate the effects of changing disturbance regimes. This is important not only in the context of climate as driver of change, but also because of the influence of a growing human population.

Posted on

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.

Posted on

Environmental Modelling and Software paper In Press

It took a while (first submitted late February 2008) but the manuscript I submitted with colleagues to Environmental Modelling and Software has now been accepted for publication. The paper describes the bio-physical component of the integrated socio-ecological simulation model I developed during my PhD. I don’t envision it changing it much so the abstract is copied below. When it’s in print I’ll holler again…

Modelling Mediterranean Landscape Succession-Disturbance Dynamics: A Landscape Fire-Succession Model
James D.A. Millington, John Wainwright, George L.W. Perry, Raul Romero-Calcerrada and Bruce D. Malamud

Abstract
We present a spatially explicit Landscape Fire Succession Model (LFSM) developed to represent Mediterranean Basin landscapes and capable of integrating modules and functions that explicitly represent human activity. Plant functional types are used to represent spatial and temporal competition for resources (water and light) in a rule-based modelling framework. Vegetation dynamics are represented using a rule-based community-level modelling approach that considers multiple succession pathways and vegetation ‘climax’ states. Wildfire behaviour is represented using a cellular automata model of fire spread that accounts for land-cover flammability, slope, wind and vegetation moisture. Results show that wildfire spread parameters have the greatest influence on two aspects of the model: land cover change and the wildfire regime. Such sensitivity highlights the importance of accurately parameterising this type of grid-based model for representing landscape-level processes. We use a ‘pattern-oriented modelling’ approach in conjunction with wildfire power-law frequency-area scaling exponent beta to calibrate the model. Parameters describing the role of soil moisture on vegetation dynamics are also found to significantly influence land-cover change. Recent improvements in understanding the role of soil moisture and wildfire fuel loads at the landscape-level will drive advances in Mediterranean LFSMs.

Posted on

Seeds and Quadtrees

The main reason I haven’t blogged much recently is because all my spare time has been taken up working on revisions to a paper submitted to Environmental Modelling and Software. Provisionally entitled ‘Modelling Mediterranean Landscape Succession-Disturbance Dynamics: A Landscape Fire-Succession Model’, the paper describes the biophysical component of the coupled human-natural systems model I started developing during my PhD studies. This biophysical component is a vegetation state-and-transition model combined with a cellular-automata to represent wildfire ignition and spread.

The reviewers of the paper wanted to see some changes to the seed dispersal mechanism in the model. Greene et al. compared three commonly used empirical seed dispersal functions and concluded that the log-normal distribution is generally the most suitable approximation to observed seed dispersal curves. However, dispersal functions using an exponential function have also been used. A good example is the LANDIS forest landscape simulation model that calculates the probability of seed fall (P) in a region between the effective (ED) and maximum (MD) seed distance from the seed source. For distances from the seed source (x) < ED, P = 0.95. For x > MD, P = 0.001. For all other distances P is calculated using the negative exponential distribution function is used as follows:
where b is a shape parameter.

Recently Syphard et al. modified LANDIS for use in the Mediterranean Type Environment of California. The two predominant pine species in our study area in the Mediterran Basin have different seed types: one (Pinus pinaster) has has wings and can fly large distances (~1km), but the other (Pinus pinea) does not. In this case a negative exponential distribution is most appropriate. However, research on the dispersal of acorns (from Quercus ilex) found that the distance distribution of acorns was best modeled by a log-normal distribution. I am currently experimenting with these two alternative seed dispersal distributions and comparing them with spatially random seed dispersal (dependent upon quantity but not locations of seed sources).

The main thing that has kept me occupied the last couple of weeks has been the implementation of these approaches in a manner that is computationally feasible. I need to run and test my model over several hundred (annual) timesteps for a landscape grid of data ~1,000,000 pixels. Keeping computation time down so that model execution does not take hundreds of hours is clearly important if sufficient model executions are to be run to ensure some form of statistical testing is possible. A brute-force iteration method was clearly not the best approach.

One of my co-authors suggested I look into the use of Quadtrees. Quadtrees are a tree data structure that are often used to partition a two dimensional space by recursively subdividing regions into quadrants (nodes). A region Quadtree partitions a region of interest into four equal quadrants. Each of these quadrants is subdivided into four subquadrants, each of which is subdivided and so on to the finest level of spatial resolution required. The University of Maryland have a nice Java applet example that helps illustrate the concept.

For our seed dispersal purposes, a region quadtree with n levels of may be used to represent an landscape of 2n × 2n pixels, where each pixel is assigned a value of 0 or 1 depending upon whether it contains a seed source of the given type or not. The distance of all landscape pixels to a seed source can then be quickly calculated using this data structure – staring at the top level we work our way down the tree querying whether each quadrant contains a pixel(s) that is a seed source. In this way, large areas of the grid can be discounted as not containing a seed source, thereby speeding the distance calculation.

Now that I have my QuadTree structure in place model execution time is much reduced and a reasonable number of model executions should be possible over the next month or so of model testing, calibration and use. My next steps are concerned with pinning down the appropriate values for ED and MD in the seed dispersal functions. This process of parameterization will take into account values previously used by similar models in similar situations (e.g. Syphard et al.) and empirical research and data on species found within our study area (e.g. Pons and Pausas). The key thing to keep in mind with these latter studies is their focus on the distribution of individual seeds from individual trees – the spatial resolution of my model is 30m (i.e. each pixel is 30m square). Some translation of values for individuals versus aggregated representation of individuals (in pixels) will likely be required. Hopefully, you’ll see the results in print early next year.

Posted on

Forest Fire Cellular Automata


One of the examples I used in class this week when talking about ‘Complex Systems’ and associated modelling approaches was the Forest Fire Cellular Automata model. I’ve produced an implementation of the model in NetLogo, complete with plots to illustrate the frequency-area scaling relationship of the resulting wildfire regime. I’ve updated the wildfire behaviour page on my website to include an applet of the NetLogo model (if that page gets changed in the future, you can view and experiment with the model here).

Posted on

Regional partitioning for wildfire regime characterization

Fighting wildfires is a strategic operation. In fire-prone areas of the world, such as California and the Mediterranean Basin, it is important that managers allocate and position fire trucks, water bombers and human fire-fighters in locations that minimize the response time to reach new fires. Not only is this important to reduce risk to human lives and livelihoods, the financial demands of fighting a prolonged campaign against multiple fires demands that resources be used as economically as possible.

Characterizing the wildfire regime of an area (the frequency, timing and magnitude of all fires) can be very useful for this sort of planning. If an area burns more frequently, or with greater intensity, on average, fire-fighting resources might be better placed in or near these areas. The relationship between the frequency of fires and the area they burn is one the characteristics that is particularly interesting from this perspective.

As I’ve written about previously with colleagues, although it is well accepted that the frequency-area distribution of wildfires is ‘heavy-tailed’ (i.e. there are many, many more small fires than large fires), the exact nature of this distribution is still debated. One of the distributions that is frequently used is the power-law distribution. Along with my former advisors Bruce Malamud and George Perry, I examined how this characteristic of the wildfire regime, the power-law frequency-area distribution, varied for different regions across the continental USA (see Malamud et al. 2005). Starting with previously defined ‘ecoregions’ (area with characterized by similar vegetation, climate and topography) we mapped how the frequency-area relationship varied in space, finding a systematic change from east to west across the country.

More recently, Paolo Fiorucci and colleagues (Fiorucci et al. 2008) have taken a slightly different approach. Rather than starting with pre-defined spatial regions and calculating the frequency-area distribution of all the fires in each region, they have devised a method that splits a large area into smaller regions based on the wildfire data for the entire area. Thus, they use the data to define the spatial differentiation of regions with similar wildfire regime characteristics a posteriori rather than imposing the spatial differentiation a priori.

Fiorucci and his colleagues apply their method to a dataset of 6,201 fires (each with an area greater than 0.01 sq km) that burned between 1987 and 2004 in the Liguria region of Italy (5400 sq km). They show that estimates of a measure of the wildfire frequency-area relationship (in this case the power-law distribution) of a given area varies significantly depending on how regions within that area are partitioned spatially. Furthermore, they found differences in spatial patterns of the frequency-area relationship between climatic seasons.

Using both a priori (the approach of Malamud et al. 2005) and a posteriori (the approach of Fiorucci et al. 2008) spatial delineation of wildfire regime areas, whilst simultaneously considering patterns in the processes believed to be driving wildfire regimes (such as climate, vegetation and topography), will lead to better understanding of wildfire regimes. That is, future research in this area will be well advised to look at the problem of wildfire regime characterization from both perspectives – data-driven and process-driven. The approach developed by Fiorucci et al. also provide much promise for a more rigorous, data-driven, approach to make decisions about the allocation and positioning of wildfire fire-fighting resources.

Citation and Abstract
Fiorucci, P., F. Gaetani, and R. Minciardi (2008) Regional partitioning for wildfire regime characterization, Journal of Geophysical Research, 113, F02013
doi:10.1029/2007JF000771

Wildfire regime characterization is an important issue for wildfire managers especially in densely populated areas where fires threaten communities and property. The ability to partition a region by articulating differences in timing, frequency, and intensity of the phenomena among different zones allows wildfire managers to allocate and position resources in order to minimize wildfire risk. Here we investigate “wildfire regimes” in areas where the ecoregions are difficult to identify because of their variability and human impact. Several studies have asserted that wildfire frequency-area relationships follow a power law distribution. However, this power law distribution, or any heavy-tailed distribution, may represent a set of wildfires over a certain region only because of the data aggregation process. We present an aggregation procedure for the selection of homogeneous zones for wildfire characterization and test the procedure using a case study in Liguria on the northwest coast of Italy. The results show that the estimation of the power law parameters provides significantly different results depending on the way the area is partitioned into its various components. These finds also show that it is possible to discriminate between different wildfire regimes characterizing different zones. The proposed procedure has significant implications for the identification of ecoregion variability, putting it in a more mathematical basis.