JASSS Paper Accepted

This week one of the papers I have been working on as a result of my PhD research has been accepted for publication in the Journal of Artificial Societies and Social Simulation (JASSS). The paper, written with Raúl Romero-Calcerrada, John Wainwright and George Perry, describes the agent-based model of agricultural land-use decision-making we constructed to represent SPA 56 in Madrid, Spain. We then present results from our use of the model to examine the importance of land tenure and land use on future land cover and the potential consequences for wildfire risk. The abstract is below, and I'll post again here when the paper is published and online.


An Agent-Based Model of Mediterranean Agricultural Land-Use/Cover Change for examining Wildfire Risk

James D. A. Millington, Raúl Romero-Calcerrada, John Wainwright, George L.W. Perry
(Forthcoming) Journal of Artificial Societies and Social Simulation

Abstract
Humans have a long history of activity in Mediterranean Basin landscapes. Spatial heterogeneity in these landscapes hinders our understanding about the impacts of changes in human activity on ecological processes, such as wildfire. Use of spatially-explicit models that simulate processes at fine scales should aid the investigation of spatial patterns at the broader, landscape scale. Here, we present an agent-based model of agricultural land-use decision-making to examine the importance of land tenure and land use on future land cover. The model considers two ‘types’ of land-use decision-making agent with differing perspectives; ‘commercial’ agents that are perfectly economically rational, and ‘traditional’ agents that represent part-time or ‘traditional’ farmers that manage their land because of its cultural, rather than economic, value. The structure of the model is described and results are presented for various scenarios of initial landscape configuration. Land use/cover maps produced by the model are used to examine how wildfire risk changes for each scenario. Results indicate land tenure configuration influences trajectories of land use change. However, simulations for various initial land-use configurations and compositions converge to similar states when land-tenure structure is held constant. For the scenarios considered, mean wildfire risk increases relative to the observed landscape. Increases in wildfire risk are not spatially uniform however, varying according to the composition and configuration of land use types. These unexpected spatial variations in wildfire risk highlight the advantages of using a spatially-explicit ABM/LUCC.

Creating a Genuine Science of Sustainability

Previously, I wrote about Orrin Pilkey and Linda Pilkey-Jarvis' book, Useless Arithmetic: Why Environmental Scientists Can’t Predict the Future. In a recent issue of the journal Futures, Jerome Ravetz reviews their book alongside David Waltner-Toews' The Chickens Fight Back: Pandemic Panics and Deadly Diseases That Jump From Animals to Humans. Ravetz himself points out that the subject matter and approaches of the books are rather different, but suggests that "Read together, they provide insights about what needs to be done for the creation of a genuine science of sustainability".

Ravetz (along with Silvio Funtowicz) has developed the idea of 'post-normal' science - a new approach to replace the reductionist, analytic worldview of ‘normal’ science. Post-normal science is a "systemic, synthetic and humanistic" approach, useful in cases where "facts are uncertain, values in dispute, stakes high and decisions urgent". I used some of these ideas to experiment with some alternative model assessment criteria for the socio-ecological simulation model I developed during my PhD studies. Ravetz's perspectives toward modelling, and science in general, shone through quite clearly in his review:

"On the philosophical side, the corruption of computer models can be understood as the consequence of a false metaphysics. Following on from the prophetic teachings of Galileo and Descartes, we have been taught to believe that Science is the sole and certain path to truth. And this Science is mathematical, using quantitative data and abstract reasonings. Such a science is not merely necessary for achieving genuine knowledge (an arguable position) but is also sufficient. We are all victims of the fantasy that once we have numerical data and mathematical argument (or computer programs), truth will inevitably follow. The evil consequences of this philosophy are quite familiar in neo-classical economics where partly true banalities about markets are dressed up in the language of the differential calculus to produce justifications for every sort of expropriation of the weak and vulnerable. ‘What you can’t count, doesn’t count’ sums it all up neatly. In the present case, the rule of models extends over nearly all the policy-relevant sciences, including those ostensibly devoted to the protection of the health of people and the environment.

We badly need an effective critical philosophy of mathematical science. ... Now science has replaced religion as the foundation of our established order, and in it mathematical science reigns supreme. Systematic philosophical criticism is hard to find. (The late Imre Lakatos did pioneering work in the criticism of the dogmatism of ‘modern’ abstract mathematics but did not focus on the obscurities at the foundations of mathematical thinking.) Up to now, mathematical freethinking is mainly confined to the craftsmen, with their jokes of the ‘Murphy's Law’ sort, best expressed in the acronym GIGO (Garbage In, Garbage Out). And where criticism is absent, corruption of all sorts, both deliberate and unaware, is bound to follow. Pseudo-mathematical reasonings about the unthinkable helped to bring us to the brink of nuclear annihilation a half-century ago. The GIGO sciences of computer models may well distract us now from a sane approach to coping with the many environmental problems we now face. The Pilkeys have done us a great service in providing cogent examples of the situation, and indicating some practical ways forward."

Thus, Ravetz finds a little more value in the Useless Arithmetic book than I did. But equally, he highlights that the Pilkeys offer few, rather vague, solutions and instead turns to Waltner-Toews' book for inspiration for the future:

Pilkey's analysis of the corruptions of misconceived reductionist science shows us the depth of the problem. Waltner-Toes’ narrative about ourselves in our natural context (not always benign!) indicates the way to a solution."

Using the outbreak of avian flu as an example of how to tackle complex environmental in the 'risk society' in which we now live, Waltner-Toes:

"... makes it very plain that we will never ‘conquer’ disease. Considering just a single sort of disease, the ‘zoonoses’ (deriving from animals), he becomes a raconteur of bio-social-cultural medicine ...

What everyone learned, or should have learned, from the avian flu episode is that disease is a very complex entity. Judging from TV adverts for antiseptics, we still believe that the natural state of things is to be germ-free, and all we need to do is to find the germs and kill them. In certain limiting cases, this is a useful approximation to the truth, as in the case of infections of hospitals. But even there complexity intrudes ... "

Complexity which demands an alternative perspective that moves beyond the next stage of 'normal' science to a post-normal science (to play on Kuhn's vocabulary of paradigm shifts):

"That old simple ‘kill the germ’ theory may now be derided by medical authorities as something for the uneducated public and their media. But the practice of environmental medicine has not caught up with these new insights.

The complexity of zoonoses reflects the character of our interaction with all those myriads of other species. ... the creatures putting us at risk are not always large enough to be fenced off and kept at a safe distance. ... We can do all sorts of things to control our interactions with them, but one thing is impossible: to stamp them out, or even to kill the bad ones and keep the good ones.

Waltner-Toes is quite clear about the message, and about the sort of science that will be required, not merely for coexisting with zoonoses but also for sustainable living in general. Playing the philological game, he reminds us that the ancient Indo-European world for earth, dgghem, gave us, along with ‘humus’, all of ‘human’, ‘humane’ and ‘humble’. As he says, community by community, there is a new global vision emerging whose beauty and complexity and mystery we can now explore thanks to all our scientific tools."

This global vision is a post-normal vision. It applies to far more than just avian flu - from coastal erosion and the disposal of toxic or radioactive waste (as the Pilekys discuss for example) to climate change. This post-normal vision focuses on uncertainty, value loading, and a plurality of legitimate perspectives that demands an "extended peer community" to evaluate the knowledge generated and decisions proposed.

In all fairness, it would not be easy to devise a conventional science-based curriculum in which Waltner-Toes's insights could be effectively conveyed. For his vision of zoonoses is one of complexity, intimacy and contingency. To grasp it, one needs to have imagination, breadth of vision and humility, not qualities fostered in standard academic training. ... "

This post-normal science won't be easy and won't be learned or fostered entirely within the esoteric confines of an ivory tower. Science, with its logical rigour, is important. It is still the best game in town. But the knowledge produced by 'normal' science is provisional and its march toward truth is seemingly Sisyphean when confronted faced with the immediacy of complex contemporary environmental problems. To contribute to the production a sustainable future, a genuine science of sustainability would do well to adopt a more post-normal stance toward its subject.

Creating our Future

"The future is ours, not to predict, but to create."

- Al Gore, 16th June 2008

Hear, hear. Spoken in the context of climate change, this might be interpreted as a slight against Global Circulation Models used by scientists. Rather, I think this should be interpreted as an indication that Gore understands that we need to move past discussions about whether we can use such models to 'prove' whether climate change is actually happening, and instead act to mitigate against undesired change.

This does not mean computer simulations of earth systems become redundant however - they are still useful tools to improving our knowledge about systems that are so large (spatially) as to prevent empirical experimentation. But we do need to remember that in 'open', middle number systems (which the majority of global environmental systems are), proving the 'truth' of a model by comparing model results with empirical data is a logical fallacy. In such circumstances, a 'post-normal' approach to the use of computer simulation models and, the wider issue of climate change, would be more useful. This view is gaining recognition.

Prometheus has more detailed discussion about prediction, forecasting and decision-making of climate change.

Read the full transcript of Gore's speech, or watch the section in which he addresses climate change below.

Model Types for Ecological Modelling

Sven Erik Jørgensen introduces a recent issue of Ecological Modelling that presents selected papers from the International Conference on Ecological Modelling in Yamaguchi, Japan (28 August - 1 September 2006). The paper provides an overview of the model types available for ecological modelling, briefly highlighting the shift from a dominance of bio-geo-chemical dynamic models and population dynamics models in the 1970s toward the application of a wider spectrum of models. The emergence of new model types has come as a response to questions such as:

• How can we describe the spatial distribution which is often crucial to understand ecosystem reactions?


• How do we model middle number systems?


• How do we model hetergenous populations and databases (e.g. observations from many different ecosystems)?


• How do we model ecosystems, when our knowledge is mainly based on a number of rules/properties/propositions?

Jørgensen suggests there are at least 10 types of model currently available for modelling ecological systems (purely mathematical and statistical aside):

1. (Bio-geo-chemical and bio-energetics), dynamic models


2. Static models


3. Population dynamic models


4. Structurally dynamic models


5. Fuzzy models


6. Artificial neural networks


7. Individual-based models and cellular automata


8. Spatial models


9. Ecotoxicological models


10. Stochastic models


11. Hybrid models

Of these, my particular interest is in spatial models, individual-based models and cellular automata models (with a passing interest in population models). This is largely because of my background in geography and landscape ecology, but also because of the heterogeneity in patterns, processes and behaviour often exhibited in socio-ecological systems.

Jørgensen offers a short description of each type, before listing their advantages and disadvantages. Here are a couple with my comments in italics:

Individual-Based Models (IBMs)and Cellular Automata (CA)
First, counter to Jørgensen, I would argue that CA models should be placed with the 'spatial models' - the ability of CA to represent space for me outweighs their potential to represent (limited) heterogeneity between cells. This aside, their grouping does make sense when we consider that these models can be relatively easily combined to represent individuals' interactions across space and with a heterogeneous environment (via the CA).

Advantages

• Are able to account for individuality - agreed, especially for IBMs


• Are able to account for adaptation within the spectrum of properties - yes


• Software is available; although the choice is more limited than by bio-geo-chemical dynamic models - but excellent free modelling environments such as NetLogo make this type of modelling widely available


• Spatial distribution can be covered - yes

Disadvantages

• If many properties are considered, the models get very complex - and may require the adoption and development of new techniques to present/analyse/interpret output (e.g. POM, narratives)


• Can be used to cover the individuality of populations; but they cannot cover mass and energy transfer based on the conservation principle - I see no reason why the principle of energy and mass conservation could not be achieved by models of these types


• Require many data to calibrate and validate the models - yes, this often the case, and in some cases (again) may require new approaches and types of data to calibrate and evaluate models

Spatial Models
Advantages

• Cover spatial distribution, that is often of importance in ecology - yes, particularly Landscape Ecology, an entire discipline that has arisen since the 1970s and '80s


• The results can be presented in many informative ways, for instance GIS - GIS is a means to organise and analyse data as well as present data

Disadvantages

• Require usually a huge database, giving information about the spatial distribution - this can certainly give rise to the issue of 'model but no data' and increases the costs of performing ecological research by adding space to time. We have found that our large (~4,000 sq km) Upper Michigan study area demands high time and resources needed for data collection.


• Calibration and validation are difficult and time-consuming - maybe more so than non-spatial models, but probably not as much as some individual-based models


• A very complex model is usually needed to give a proper description of the spatial patterns - not necessarily. A model should be only as complex as the patterns and processes it seeks to examine and the inclusion of space does not imply patterns or processes any more complex than a system with less variables or interactions that is non-spatial.

This isn't a bad review of the types of ecological modelling being done. However, more incisive and useful insight could have been made with respect to landscape ecology and those models that are now beginning to attempt to account for human activity in ecological systems. [And it definitely could have been better written.] Maybe I'll stop criticising sometime and write one myself eh?

Aldo Leopold Legacy Center - The 'Greenest Building in the US'

One of the fieldtrips we took during the US-IALE conference in Madison was to Aldo Leopold's shack and the Aldo Leopold Legacy Center. Aldo Leopold is considered by many to be the 'father' of wildlife management. His significant and lasting mark is his book, A Sand County Almanac. I'll look at the book in later post, but here I'll talk briefly about what we saw on our excursion from Madison.

After graduating from the Yale Forest School in 1909, Aldo Leopold spent time working in Arizona and New Mexico before moving to Madison, Wisconsin, in 1924. In 1933 he published the first wildlife management textbook and accepted a new chair in game management at the University of Wisconsin - a first for both the university and the nation.



In 1935, Leopold and his family initiated their own ecological restoration experiment on a washed-out sand farm of 120 acres along the Wisconsin River near Baraboo, Wisconsin. Planting thousands of pine trees, restoring prairies, and documenting the ensuing changes in the flora and fauna informed and inspired Leopold. Many of his writings in the initial parts of A Sand County Almanac - the history of the local region as told through the rings of an oak tree, evening shows of sky dancing woodcock, fishing the Alder Fork, hunting ruffled-grouse in smoky gold tamarack - were penned in 'the shack' (above) on his farm which we stopped by at on a wet, grey day after visiting The Aldo Leopold Legacy Center (below).



In sharp contrast to 'the shack' the Legacy Center feels solid and dry. But consistent with the Land Ethic message of the writing that was done in the old dilapidated building, the new building 'sustains the health, wildness, and productivity of the land, locally and globally'. The Legacy Center has received Platinum Leadership in Energy and Environment Design (LEED) Certification from the U.S. Green Building Council and is currently the 'greenest building in the U.S.'.

The Legacy Center is an example of how we can use energy more efficiently and construct building with a limited impact on our environment. Through energy efficiency, renewable energy, the Legacy Center is the first carbon neutral building certified by LEED — annual operations account for no net gain in carbon dioxide emissions.

The Legacy Center is also a net zero energy building, using 70 percent less energy than a building built just to code and meeting all of its energy needs on site using tools like a roof-mounted solar array and a 'thermal flux zone' to reduce heat flow between interior rooms and the outdoors. Many of the structural columns, beams, and trusses, as well as interior panelling and finish work, are from the pine trees Leopold planted himself on his farm between 1935-1948.

This really is a building that embodies Leopold's Land Ethic - both conceptually through the principles used when designing the building, and physically by using material from Leopold's own ecological restoration experiment. The Legacy Center contains the offices of the Leopold Foundation, has a small shop and 'museum' about Leopold, and can be hired for meetings. The building itself is what is really the attraction - and hopeully there will be more like this appearing more frequently elsewhere. Unless you're passing by or really want to make a pilgrimage to gain an insight into the area where Leopold's vision unfolded, there's really no need to go out of your way to visit. Take a virtual tour instead to save energy and carbon and make the building even greener.

A Young Scientist's Guide To Gainful Employment

A recent article that ranked #1 on the Bulletin of the Ecological Society of America's Top Ten was led by Anita Morzillo, a former student in Fisheries and Wildlife at MSU. The article, entitled 'A Young Scientist's Guide To Gainful Employment: Recent Graduates' Experiences And Successful Strategies' is based on a workshop supported by the NASA-MSU Professional Enhancement Award Program and has some wise words for any junior researcher starting out on their academic career. It's written with ecologists and biologists in mind but much of the advice is likely to apply to other fields.

The paper is organized into four areas:

1. Self promotion. What can I do prior to and during the job hunt?
   
2. Personal considerations. How will both my professional and personal lives affect which jobs I should apply for?
   
3. The application process. What should I expect when applying?
   
4. Keeping it all in perspective. What if my application is rejected?
   

Section 1 considers publications, the importance of experiences beyond research, the 'elevator speech', getting your name recognised, and your network or personal connections. Section 2 discussed the necessity (or otherwise) of PhD and post-doctoral experience, issues around the geographic location of jobs, balancing professional and personal life, and issues regarding the careers of 'significant others'. Section 3 then addresses the job application process from learning about the process before applying to phone and on-site interviews. The final section reflects on extraneous situations such as competing against 'superstar' applicants for positions and the need for perseverance in certain circumstances.

The paper concludes:

"Since we all are responsible for taking the initiative to forge our career path, our goal was to share our perspectives on and experiences with several broad themes involved in a job search. Do not hesitate to start thinking about the job hunt early in your career as a graduate student. Each position that you consider will offer unique opportunities to build your resume or curriculum vitae, and will present personal and professional trade-offs. Take time to think about and proactively discuss both professional and personal factors, but also keep in mind that you control only so much of the process. Good luck!"

Shapefiles in Google Earth

Last week I put together a presentation about our Michigan UP Ecological-Economic Modeling project for our funding body. I thought it would be useful to demonstrate the location of our study area in Google Earth, so I set about learning how to import ESRI shapefiles into Google Earth. I discovered it's really easy.

My first stop in working this out was 'Free Geography Tools' and their series of posts about exporting shapefiles to Google Earth. From their list of free programs, first I tried Shp2KML by Jacob Reimers. Unfortunately this program resulted in some security conflicts with our network so I couldn't use it. Next I tried a second program, also called shp2kml, from Zonum Solutions and that worked a treat. Zonum have several other Google Earth tools that I'll have to try out sometime.

You can download the kml file it produced for the boundary of our study area here (right click, 'save as' or whatever). If you have Google Earth installed you can then just double click that file (once downloaded) and Google Earth will take you right there. When I first created the link above, I hoped that when you clicked on it the file would open automatically in Google Earth - it didn't. But after a little playing I found that kmz files will open automatically in Google Earth. kmz files are simply zipped (compressed) kml files - I used WinRar to zip the kml file and then changed the file suffix from zip to kmz. Click here - the study area file will open automatically in Google Earth (from Firefox at least - see note below). Sweet.

I also exported shapefiles for DNR and private industrial stand boundaries which match up nicely with spatial patterns of vegetation observed in the landscape. Obviously, I can't post these shapefiles online, but you can see evidence of land ownership boundaries in our study area right here. The light green rectangular area is non-DNR land and has been clear cut. The surrounding area is managed by the DNR (possibly selective timber harvest) - the resulting land cover from different management approaches is stark. These are the sorts of patterns and issues we will be able to examine using our ecological-economic landscape model.

[Note - When posting the presentation to our web server I also learned about MS Internet Explorer .png issues. They say they've fixed them, but there still seem to be some problems - try viewing this page in both IE and Firefox and note the difference (hover your cursor over the words at the bottom). Viewing the presentation pages in Firefox means the links to the .kmz files are active - they are not in IE. The issue arose becasue I used OpenOffice Impress to convert my MS PowerPoint file to html files.]

Columbia University Press Sale

Columbia University Press currently has a sale on. They have savings of up to 80% on more than 1,000 titles from several fields of study. I was particularly interested in their books in the Environmental Studies and Ecology section and purchased several:

• Foundation Papers in Landscape Ecology Edited by John Wiens, Michael R. Moss, Monica G. Turner, and David Mladenoff
  
• Understanding Environmental Policy Steven Cohen
  
• Environment, Power, and Society for the Twenty-first Century: The Hierarchy of Energy Howard T. Odum
  
• The Wealth of Nature: How Mainstream Economics Has Failed the Environment Robert L. Nadeau
  

Previously on this blog I reviewed another book they have on sale, Useless Arithmetic: Why Environmental Scientists Can't Predict the Future by Orrin H. Pilkey and Linda Pilkey-Jarvis.

When I get round to reading this new batch I'll review some of these also (at first glance the Wiens et al. book looks particularly useful for any Landscape Ecologist - student, teacher or researcher). You've got up until May 31st to order yours.

Bristol, UK. Whence I came.

Amazingly it's just over a year since I arrived in Michigan and started my postdoc at MSU. Time flies when you're having fun, eh? Well, the first few months didn't fly so fast... but it's been fairly well shooting by recently. That's not to say I don't miss home everynowandthen. Especially when I see videos like this about my hometown:


[From University of Bristol and DestinationBristol]

But I do remember Bristol - it's not that sunny ALL the time. ;)

Michigan UP Seedling Experiment

I've been back from our study area in Michigan's Upper Peninsula for over a week so it's about time I posted something about what we were doing up there.

One of the main issues we will study with our integrated ecological-economic landscape model is the impact of whitetail deer (Odocoileus virginianus) herbivory on tree regeneration following cutting. Last November we spent a week planting 2 year-old seedlings in Northern Hardwood forest gaps created by selective timber harvest (like the one in the photo below).



Our plan was to return this spring to examine the impacts of deer browse on these seedlings. In particular, we wanted to examine how herbivory varies across space due to changes in deer population densities (in turn driven by factors such as snow depth).

To this end we selected almost 40 forest sites that would hopefully capture some spatial variation in snowfall and that had recently been selectively harvested. At each site we selected 10 gaps produced by timber harvest in which to plant our seedlings.

In each gap we planted six trees of each of three species: White Spruce (Picea glauca), White Pine (Pinus strobus) and Eastern Hemlock (Tsuga canadensis). We chose these coniferous species as these are examples of the mesic confer species the Michigan DNR are trying to restore across our study area, and because we expected a range of herbivory across these species.

At each site we would also undertake deer pellet counts in the spring to estimate the number of deer in the vicinity of the site during the winter (during which time the browse we were measuring would have occurred).

On returning to the study sites a couple of weeks ago we set about looking for the trees we had planted to measure herbivory and count deer pellets. In some cases, finding the trees we planted was easier said than done. We tried to get our field crews to plant the trees in straight lines with equal spacing between each tree. In general, this was done well but on occasion the line could only be described as crooked at best. Micro-topography, fallen tree trunks and limbs, and slash from previous cutting all contributed to hamper the planned planting system. However, we did pretty well and found well over 90% of the trees.

We haven't begun analyzing our data as yet, but some anecdotal observations stand out. First, the deer preferentially browsed Hemlock over the other species, often removing virtually all non-woody biomass as shown by the 'before and after' examples below (NB - these photographs are not of the same tree and this is not a true before/after comparison).





In some cases, the deer not only removed all non-woody biomass but also pulled the tree out of the ground (as shown below).



In contrast, White Pine was browsed to a much lesser extent and White Spruce was virtually untouched (as shown below).





Having a species that was unaffected by deer (i.e. spruce) often made our job of finding the other trees much easier. Finding heavily browsed Hemlock that no longer had any green vegetation was often tricky against a background of forest floor litter.

The next step now is to start looking at this variation in browse through a more quantitative lens. Then we can start examining how browse and deer densities vary across space and how these variables are related to one another and other factors (such as snow depth and distance to conifer stands).

All-in-all the two weeks of work went pretty well. There were some issues with water-logged roads (due to snow melt) meaning we couldn't get to one or two of the sites we planted at, but generally the weather was pretty good (it only rained heavily one day). I'll write more once we have done more analysis and stop here with a shot I took at sunrise as I left for home.