Morocco Fieldtrip Recon

I spent a couple of weeks this month in Morocco, the majority of which was scouting out a route for a new physical geography fieldtrip for second year undergraduates at King’s College London. For the last several years the physical geography fieldtrip has been based on the Morocco coast at Agadir and Essaouira, visiting nearby sites. The new fieldtrip will take more of a transect approach, starting in Marrakech, traversing the High Atlas mountains and following the River Draa out to the edge of the Sahara (see map below).


As we work our way up and through the High Atlas one of the things we’ll consider is how vegetation changes and what might be driving those changes. In the picture below you can see colleagues on the trip Prof. Drake and Dr Chadwick (@DrMChad) debating (and betting on!) vegetation on the hills over-looking the town of Demnate.

For example, what are the relative influences of climate and human activity on the vegetation we see? In the picture below Prof Drake confronts one potential disturbance.

As this is a new trip and we’ll be staying in a new location each night, one of our tasks was to check the accommodation we’ll be staying in. Here hotel connoisseurs Drake and Chadwick relax in luxury in the gîte at Toufghine.

There’s some impressive geology in the High Atlas and we’ll discuss that as we go too. The scale of some of the tectonic features is illustrated by Prof Drake in the bottom right of the picture below.

We’ll also be surveying rivers, both their geomorphology and ecology. Another of our tasks therefore was to work out what we would examine and where along the various rivers in the region.

Once we get over the High Atlas and the Anti-Atlas beyond we’ll follow the River Draa all the way to the desert. The Draa is a vital life-line for people in the region, with water drawn from the river used to irrigate agriculture (including wheat).

Once the water has all been used up we reach the desert. There we’ll look for evidence of previous flows of the Draa and of climate change. Some of the dunes can be steep.

But the view from the top is usually good, especially at sunset. We’ll stay a night out in the dunes with the students to get a feel for what it might be like living in such hostile environment.

And of course there will be camels! Below, our driver negotiates a herd as we head back north to Marrakech on the final leg of our trip.

So it looks like we’re going to have a great trip with our students in December and following years! The trip will allow us to investigate how climate, geology, geomorphology, ecology and livelihoods change across space and how they have changed through time.

I’ve posted some more of my favourite pictures on Panoramio so that you can see some of the locations we’ll visit.

When is a pattern a pattern?

This week I received my copy of ‘Patterns of Land Degradation in Drylands: Understanding Self-Organised Ecogeomorphic Systems’ which I contributed to after participating at a workshop in Potsdam, Germany. It’s a well produced book and as I was flicking through it I came across one of the pieces I wrote. Rather than just leave it hidden away on pages 60 – 61 in the book I thought I’d reproduce it here. It’s less than 500 words and to the point. Just right for a blog post.

“In science, patterns are observations of any non-random structure. In ecology for example, a pattern has long been understood as the “structure which results from the distributions of organisms in, or from, their interactions with their environments” (Hutchinson 1953, p.3, also see Watt 1947, Greig-Smith 1979). However, when identifying patterns in nature, scientists more precisely mean the identification of patterns in data about nature. Important considerations for identifying patterns, therefore, are the means by which data were collected, and most importantly the scales of measurement used to collect data. In particular, two components of scale – grain and extent – are important in determining whether a pattern is identified. Grain is the resolution of measurement (i.e. the smallest unit of measurement at which objects or states can be distinguished), whereas extent is the full scope of observation or total range over which measurements are made. As examples, different spatial patterns will be detectable in maps of vegetation configuration in semi-arid areas depending on the grain and extent of the maps (e.g. compare Figures 3 and 6 in Barbier et al. 2006), and different temporal patterns will be detectable in storm hydrographs depending on the resolution and duration of measurement (e.g. compare drainage for 10 minute intervals with full 80 minute duration, and observed drainage with simulated drainage, in Figure 5 of Mueller et al. 2007). In other circumstances, observed structures may be described as being ‘scale-free’. These structures lack a characteristic length scale and have the same properties across any grain and extent of measurement (e.g. power-law distributions of vegetation patch sizes; Kéfi et al. 2007). These scale-free structures can also be considered to be patterns.

Because patterns are non-random, they have the potential to provide information. In natural science this information is usually understood as being about the processes that caused the pattern. Thus, identifying patterns is useful because they can be used to investigate processes (Levin 1992). Processes are typically assumed to act at a different scale from the patterns they produce, with patterns either emerging from processes at smaller scales (‘bottom-up’ processes) or imposed by constraints at larger scales (‘top-down’ processes). It is also important to consider the reciprocal effects of patterns on processes (Turner 1989). For example, the field of landscape ecology has placed an emphasis on the quantification of spatial pattern using pattern metrics (e.g. McGarigal 2006) and shown how the history of previous ecological processes can increase the strength and extent of spatial pattern (Peterson 2002). The ‘pattern-oriented modelling’ (POM) approach has been developed to use models to help decode the information present in patterns to better understand processes (Wiegand et al. 2003, Grimm et al. 2005). The POM approach iteratively compares empirical and model-output patterns at multiple scales and levels of organization and for multiple models to identify most appropriate models. Approaches like POM, which place pattern at the centre of scientific investigation, are vital for improving understanding about physical processes.”

References

  • Barbier N, Couteron P, Lejoly J et al (2006) Self-organized vegetation patterning as a fingerprint of climate and human impact on semi-arid ecosystems. J of Ecol 94:537-547
    Greig-Smith P (1979) Pattern in vegetation. J of Ecol 67: 755-779
  • Grimm V, Revilla E, Berger U et al. (2005) Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science 310:987-991
  • Hutchinson GE (1953) The concept of pattern in ecology. Proc of the Acad of Nat Sci of Philadelphia 105:1-12
  • Kéfi S, Rietkerk M, Alados, CL et al (2007) Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems. Nature 449:213-217
  • Levin SA (1992) The problem of pattern and scale in ecology: The Robert H. MacArthur award lecture. Ecology 73(6):1943-1967
  • McGarigal K (2006) Landscape pattern metrics. In: El-Shaarawi AH and Piegorsch WW (eds) Encyclopedia of Environmetrics. Wiley: Chichester, UK
  • Mueller EN, Wainright J, Parsons, AJ (2007) Impact of connectivity on the modeling of overland flow within semiarid shrubland environments. Water Res Res 43:W09412
  • Peterson GD (2002) Contagious disturbance, ecological memory, and the emergence of landscape pattern. Ecosystems 5:329-338
  • Turner MG (1989) Landscape ecology: The effect of pattern on process. Ann Rev of Ecol and Syst 20:171-197
  • Watt, AS (1947) Pattern and process in the plant community. J of Ecol 35:1-22
  • Wiegand T, Jeltsch F, Hanski I et al (2003) Using pattern-oriented modeling for revealing hidden information: A key for reconciling ecological theory and application. Oikos 100:209-222

Citation
Jeltsch, F., Millington, J.D.A., et al. (2014) Resilience, self-organization, complexity and pattern formation In: Mueller, E.N., Wainwright, J., Parsons, A.J. and Turnbull, L. (Eds.) Patterns of Land Degradation in Drylands. Springer, pp. 55-84.

AAG 2013

Last week I was in Los Angeles for my first ever Association of American Geographers Annual Meeting. I think I hadn’t been before because the US-IALE annual meeting is around the same time of year and attending that has made more sense in the last few years given my work on forest modelling in Michigan. As I’d heard previously, the meeting was huge – although not quite as crazy as it could have been.

Most of my participation at the meeting was related to the Land Systems Science Symposium sessions (which ran across four days) and the Agent-Based and Cellular Automata Model for Geographical Systems sessions. It was good to discuss and meet new people wrestling with similar issues to those in my own research. Unfortunately, the ABM sessions were scheduled for the last day which meant it was only late in the conference that I got to properly meet people I’d encountered online (e.g., Mike Batty, Andrew Crooks, Nick Magliocca) and others. Despite being scheduled for the last day there was a good turnout in the sessions and my presentation (below) seemed to go down well. Researchers from the group at George Mason University were most well-represented, with much of their work using the MASON modelling libraries (which I’m going to have to looking into more to continue the work initiated during my PhD).


It’s hard to concentrate on 20-minute paper sessions continuously for five days though, and I found the discussion panels and plenaries a nice relief, allowing a broader picture to develop. For example, David O’Sullivan (whom I’m currently visiting at the University of Auckland) chaired and interesting panel discussion on ABM for Land Use/Cover Change. Participants included, Chris Bone who discussed the need for better representation of model uncertainty from multiple simulation (via temporal variant-invariant analysis – coming soon in IJGIS); Dan Brown who suggested we’re missing mid-level models that are neither abstract ‘toys’ nor beholden to mimetic reproduction of specific empirical data (e.g., where are the ABM equivalents of von Thunen and Burgess type models?); and Moira Zellner who highlighted problems of using ABM for decision-making in participatory approaches (Moira’s presentation in the ABM session was great, discussing the ‘blow-up’ in her participatory modelling project when the model got too complicated and stakeholders no longer wanted to know what the model was doing under the hood).

I also really enjoyed Mike Goodchild’s Progress in Human Geography annual lecture, in which he reviewed the development of GIScience through his long career and where he thought it should go next (‘Old Debates, New Opportunities’). Goodchild argued (I think) that Geography cannot (and should not) be an experimental science in the mold of Physics, and that rather than attempting to identify laws in social (geographical) science, we should aim to find things that can be deemed to be ‘generally true’ and used as a norm for reducing uncertainty. This is possible because geography is ‘neither uniform nor unique’, but it is repeating. Furthermore, he argued it was time for GIScience to rediscover place and that a technology of place is needed to accompany the (existing) technology of space. This technology of place might use names rather than co-ordinates, hierarchies of places rather than layers of coverages, and produce sketch maps rather than planimetric maps. The substitution of names of places for co-ordinates of locations is particularly important here, as names are social constructs and so multiple (local) maps are possible (and needed) rather than a single (global) map. Goodchild exemplified this using Google Maps, which differs depending on which country you view it from (e.g., depending on what the State views as its legitimate borders). He talked about loads of other stuff, including critical GIS, but these were the points I found most intriguing.

Another way to break up the constant stream of 20-minute project summaries would have been organised fieldtrips around the LA area. However, unlike the landscape ecology conference there is no single time set aside for fieldtrips, and while there are organised trips they’re scheduled throughout the week (simultaneous with sessions). Given such a large conference I guess it would be hard to fit all the sessions into a single week if time were set aside. I didn’t make it to any of the formal fieldtrips, but with Ben Clifford (checkout his new book, The Collaborating Planner?) and Kerry Holden I did manage to find time to hit the beach for some sun. It was a long winter in the UK after all! Now I’m in Auckland it’s warm but stormy; an update about activities here to come in May.

Time(-lapse), Environment and Landscape

For the second half of this term I’m teaching the ‘Time, Environment and Landscape’ module of the First year undergraduate class ‘Geography Concepts, Skills and Methods’ at KCL.

Today was my first lecture, on ‘time’. I talked about some of the issues we need to take into consideration when we are collecting data over time, and then how that influences what we can see from the data and how we analyse them (i.e., time-series analysis). To help think through some of the considerations I used some time-lapse movies of landscapes.

I’ve been experimenting with making my own time-lapse videos after getting a remote control for my dSLR last year. In lectures the movies are useful for illustrating how our understanding of things is influenced by the frequency and duration over which we sample our data collection.

As one of the datasets we’ll be analysing in the computer practical sessions that go with the lectures on this module is the Keeling curve, at the outset of the lecture today I showed this movie of some of some Hawaiian landscapes:

Mauna Lapse: From Sea to Summit from The Upthink Lab on Vimeo.

Then, later in the lecture, to get students thinking about how sampling data ‘compresses’ time so that we can see things differently, I showed this movie of the Jorge Montt Glacier in Chile:

Jorge Montt Glacier, Chile (English) TL from Centro de Estudios Científicos on Vimeo.

Finally, we looked at some time-lapse movies I made myself. I show the students different versions of the same video (below) to illustrate how different sampling frequencies combined with different numbers of photos (data points) changes what we can see happening.

Thames Time-Lapse 1 from James Millington on Vimeo.

You can see more time-lapse movies I’ve made in my vimeo album. Once I’ve got enough maybe I’ll try stitching them together with some music like that fancy Hawaii one!

ABM, Prezi and the New Term

I’ve not been in the office much over the last month or so, but that’s all about to change now that the new academic term has arrived!

Since I last posted, I attended and presented work at the Royal Geographical Society Annual Conference, one presentation on our managed forest landscape modelling in Michigan and one on the narrative properties of simulation modelling. Both presentations were in the environmental modelling and decision making session, but despite being the graveyard session (last of the conference!) we had some interesting questions and discussion. I tried out Prezi for my narratives presentation (brought to my attention by Tom Smith). It certainly requires a different approach than the linear style PowerPoint enforces. Whether Prezi is a more useful tool probably depends on the message you’re trying to communicate – if your story isn’t particularly linear then Prezi might be useful.

These last few days I’ve been up in Edinburgh visiting folks at the Forestry Commission’s Northern Research Station to discuss the socio-ecological modelling of potential woodland creation I’ve been working on recently. I also got to talk with Derek Robinson at the University of Edinburgh about some of these issues. Everyone seemed interested in what I’ve been doing, particularly with the ideas I’ve been bouncing around relating to the work Burton and Wilson have been doing on post-productivist farmer self-identities, how these self-identities might change, how they might influence adoption of woodland planting and how we might model that. For example, I think an agent-based simulation approach might be particularly useful for exploring what Burton and Wilson term the ‘‘temporal discordance’ in the transition towards a post-productivist agricultural regime”. And I also think there’s potential to tie it in with work like my former CSIS colleague Xiaodong Chen has been doing using agent-based approaches to model the effects of social norms on enrollment in payments for ecosystem services (such as woodland creation).

I was away on holiday for a couple of weeks after the RGS. On returning, I’ve been preparing for King’s Geography tutorials with the incoming first year undergraduates. The small groups we’ll be working will allow us to discuss and explore critical thinking and techniques about issues and questions in physical geography. Looking forward a busy autumn term!

Philosophy of Modelling and RGS 2011

I just updated the Philosophy of Modelling page on my website. It’s not anything too detailed but I was prompted to add something by my activities over the last few weeks. I’ve been working on both making progress with my ‘modelling narratives’ project and a paper I’ve started working on with John Wainwright exploring the epistemological roles agent-based simulation might play beyond mathematical and statistical modelling (expected to appear in the new-ish journal Dialogues in Human Geography).

It’s only a few weeks now until this year’s Royal Geographical Society annual meeting (31 Aug – 2 Sept). I’m making two presentations, unfortunately both in the same session! It seems my work sits squarely within ‘Environmental modelling and decision making’, as the both abstract I submitted were allocated to that session on the Friday afternoon (Skempton Building, Room 060b; last session of the week so people might be flagging!). The first presentation will deal with the ‘generative’ properties of agent-based modelling [.pdf] and what that implies for how we might study and use that modelling approach, and the second will summarise the Michigan forest modelling work we’ve completed so far. Both abstracts are below.

This also seems a good point to highlight that King’s Geography Department are hosting a drinks reception on the Thurdsay evening from 18:45 at Eastside Bar, Princes Garden, SW7 1AZ. Free drinks for the first 50 guests, so get there sharpish!

Millington RGS 2011 Abstracts

Model Histories: The generative properties of agent-based modelling
Fri 2 Sept, Session 4, Skempton Building, Room 060b
James Millington (King’s College London)
David O’Sullivan (University of Auckland, New Zealand)
George Perry (University of Auckland, New Zealand)

Novels, Kundera has suggested, are a means to explore unrealised possibilities and potential futures, to ask questions and investigate scenarios, starting from the present state of the world as we observe it – the “trap the world has become”. In this paper, we argue that agent-based simulation models (ABMs) are much like Kundera’s view of novels, having generative properties that provide a means to explore alternative possible futures (or pasts) by allowing the user to investigate the likely results of causal mechanisms given pre-existing structures and in different conditions. Despite the great uptake in the application of ABMs, many have not taken full advantage of the representational and explanatory opportunities inherent in ABMs. Many applications have relied too much on ‘statistical portraits’ of aggregated system properties at the expense of more detailed stories about individual agent context and particular pathways from initial to final conditions (via heterogeneous agent interactions). We suggest that this generative modelling approach allows the production of narratives that can be used to i) demonstrate and illustrate the significance of the mechanisms underlying emergent patterns, ii) inspire users to reflect more deeply on modelled system properties and potential futures, and iii) provide a means to reveal the model building process and the routes to discovery that lie therein. We discuss these issues in the context of, and using examples from, the increasing number of studies using ABMs to investigate human-environment interactions in geography and the environmental sciences.

Trees, Birds and Timber: Coordinating Long-term Forest Management
Fri 2 Sept, Session 4, Skempton Building, Room 060b
James Millington (King’s College London)
Megan Matonis (Colorado State University, United States)
Michael Walters (Michigan State University, United States)
Kimberly Hall (The Nature Conservancy, United States)
Edward Laurent (American Bird Conservancy, United States)
Jianguo Liu (Michigan State University, United States)

Forest structure is an important determinant of habitat use by songbirds, including species of conservation concern. In this paper, we investigate the combined long-term impacts of variable tree regeneration and timber management on stand structure, bird occupancy probabilities, and timber production in the northern hardwood forests of Michigan’s Upper Peninsula. We develop species-specific relationships between bird occupancy and forest stand structure from field data. We integrate these bird-forest structure relationships with a forest model that couples a forest-gap tree regeneration submodel developed from our field data with the US Forest Service Forest Vegetation Simulator (Ontario variant). When simulated over a century, we find that higher tree regeneration densities ensure conditions allowing larger harvests of merchantable timber, and reducing the impacts of timber harvest on bird forest-stand occupancy probability. When regeneration is poor (e.g., 25% or less of trees succeed in regenerating), timber harvest prescriptions have a greater relative influence on bird species occupancy probabilities than on the volume of merchantable timber harvested. Our results imply that forest and wildlife managers need to work together to ensure tree regeneration and prevent detrimental impacts on timber output and habitat for avian species over the long-term. Where tree regeneration is currently poor (e.g., due to deer herbivory), forest and wildlife managers should pay particularly close attention to the long-term impacts of timber harvest prescriptions on bird species.

Summer 2011 Papers

Since I last posted, THREE of the papers I’ve mentioned here previously have become available online! Here are their details, abstracts are below. Email me if you can’t get hold of them yourself.

Millington, J.D.A., Walters, M.B., Matonis, M.S., Laurent, E.J., Hall, K.R. and Liu, J. (2011) Combined long-term effects of variable tree regeneration and timber management on forest songbirds and timber production Forest Ecology and Management 262 718-729 doi: 10.1016/j.foreco.2011.05.002

Millington, J.D.A. and Perry, G.L.W. (2011) Multi-model inference in biogeography Geography Compass 5(7) 448-530 doi: 10.1111/j.1749-8198.2011.00433.x

Millington, J.D.A., Demeritt, D. and Romero-Calcerrada, R. (2011) Participatory evaluation of agent-based land use models Journal of Land Use Science 6(2-3) 195-210 doi:10.1080/1747423X.2011.558595

Millington, J.D.A. et al. (2011) Combined long-term effects of variable tree regeneration and timber management on forest songbirds and timber production Forest Ecology and Management 262 718-729
Abstract
The structure of forest stands is an important determinant of habitat use by songbirds, including species of conservation concern. In this paper, we investigate the combined long-term impacts of variable tree regeneration and timber management on stand structure, songbird occupancy probabilities, and timber production in northern hardwood forests. We develop species-specific relationships between bird species occupancy and forest stand structure for canopy-dependent black-throated green warbler (Dendroica virens), eastern wood-pewee (Contopus virens), least flycatcher (Empidonax minimus) and rose-breasted grosbeak (Pheucticus ludovicianus) from field data collected in northern hardwood forests of Michigan’s Upper Peninsula. We integrate these bird-forest structure relationships with a forest simulation model that couples a forest-gap tree regeneration submodel developed from our field data with the US Forest Service Forest Vegetation Simulator (Ontario variant). Our bird occupancy models are better than null models for all species, and indicate species-specific responses to management-related forest structure variables. When simulated over a century, higher overall tree regeneration densities and greater proportions of commercially high value, deer browse-preferred, canopy tree Acer saccharum (sugar maple) than low-value, browse-avoided subcanopy tree Ostrya virginiana (ironwood) ensure conditions allowing larger harvests of merchantable timber and had greater impacts on bird occupancy probability change. Compared to full regeneration, no regeneration over 100 years reduces merchantable timber volumes by up to 25% and drives differences in bird occupancy probability change of up to 30%. We also find that harvest prescriptions can be tailored to affect both timber removal volumes and bird occupancy probability simultaneously, but only when regeneration is adequate. When regeneration is poor (e.g., 25% or less of trees succeed in regenerating), timber harvest prescriptions have a greater relative influence on bird species occupancy probabilities than on the volume of merchantable timber harvested. However, regeneration density and composition, particularly the density of Acer saccharum regenerating, have the greatest long-term effects on canopy bird occupancy probability. Our results imply that forest and wildlife managers need to work together to ensure tree regeneration density and composition are adequate for both timber production and the maintenance of habitat for avian species over the long-term. Where tree regeneration is currently poor (e.g., due to deer herbivory), forest and wildlife managers should pay particularly close attention to the long-term impacts of timber harvest prescriptions on bird species.

Millington, J.D.A. and Perry, G.L.W. (2011) Multi-model inference in biogeography Geography Compass 5(7) 448-530
Abstract
Multi-model inference (MMI) aims to contribute to the production of scientific knowledge by simultaneously comparing the evidence data provide for multiple hypotheses, each represented as a model. With roots in the method of ‘multiple working hypotheses’, MMI techniques have been advocated as an alternative to null-hypothesis significance testing. In this paper, we review two complementary MMI techniques – model selection and model averaging – and highlight examples of their use by biogeographers. Model selection provides a means to simultaneously compare multiple models to evaluate how well each is supported by data, and potentially to identify the best supported model(s). When model selection indicates no clear ‘best’ model, model averaging is useful to account for parameter uncertainty. Both techniques can be implemented in information-theoretic and Bayesian frameworks and we outline the debate about interpretations of the different approaches. We summarise recommendations for avoiding philosophical and methodological pitfalls, and suggest when each technique is best used. We advocate a pragmatic approach to MMI, one that emphasises the ‘thoughtful, science-based, a priori’ modelling that others have argued is vital to ensure valid scientific inference.

Millington et al. (2011) Participatory evaluation of agent-based land use models Journal of Land Use Science 6(2-3) 195-210
Abstract
A key issue facing contemporary agent-based land-use models (ABLUMs) is model evaluation. In this article, we outline some of the epistemological problems facing the evaluation of ABLUMs, including the definition of boundaries for modelling open systems. In light of these issues and given the characteristics of ABLUMs, participatory model evaluation by local stakeholders may be a preferable avenue to pursue. We present a case study of participatory model evaluation for an agent-based model designed to examine the impacts of land-use/cover change on wildfire regimes for a region of Spain. Although model output was endorsed by interviewees as credible, several alterations to model structure were suggested. Of broader interest, we found that some interviewees conflated model structure with scenario boundary conditions. If an interactive participatory modelling approach is not possible, an emphasis on ensuring that stakeholders understand the distinction between model structure and scenario boundary conditions will be particularly important.