‘Mind, the Gap’ paper in press

I hoped it would be quicker than previous papers, but the review process of the ‘Mind, the Gap’ manuscript I worked on with John Wainwright hasn’t been particularly fast. I guess that’s just how it goes with special issues. I’ll discuss some of the topics we touch on in the paper in a future post. For now here’s the abstract – look out for the full paper on the ESPL website in the next couple of months.

Mind, the Gap in Landscape-Evolution Modelling
John Wainwright and James Millington
Earth Surface Processes and Landforms (Forthcoming)

Abstract
Despite an increasing recognition that human activity is currently the dominant force modifying geomorphic landscapes, and that this activity has been increasing through the Holocene, there has been little integrative work to evaluate human interactions with geomorphic processes. We argue that agent-based models (ABMs) are a useful tool for overcoming the limitations of existing, highly empirical approaches. In particular, they allow the integration of decision-making into process-based models and provide a heuristic way of evaluating the compatibility of knowledge gained from a wide range of sources, both within and outwith the discipline of geomorphology. The application of ABMs to geomorphology is demonstrated from two different perspectives. The SPASIMv1 (Special Protection Area SIMulator version 1) model is used to evaluate the potential impacts of land-use change – particularly in relation to wildfire and subsequent soil conditions – over a decadal timescale from the present day to the mid-21st century. It focuses on the representation of farmers with traditional versus commercial perspectives in central Spain, and highlights the importance of land-tenure structure and historical contingencies of individuals’ decision making. CYBEROSION, on the other hand, considers changes in erosion and deposition over the scale of at least centuries. It represents both wild and domesticated animals and humans as model agents, and investigates the interactions of them in the context of early agriculturalists in southern France in a prehistoric context. We evaluate the advantages and disadvantages of the ABM approach, and consider some of the major challenges. These challenges include potential process scale mis-matches, differences in perspective between investigators from different disciplines, and issues regarding model evaluation, analysis and interpretation. If the challenges can be overcome, this fully-integrated approach will provide geomorphology a means to conceptualize soundly the study of human-landscape interactions.

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

Incendio en un Paisaje Mediterráneo

Our recent paper describing and testing the Mediterranean Landscape Fire Succession Model I developed during my PhD has caught the eye of some folks in Spain. sinc (Servicio de Informacion y Noticias Cientificas), a Spanish scientific news website <a href="
http://plataformasinc.es/index.php/esl/Noticias/Un-modelo-predice-la-evolucion-del-paisaje-mediterraneo-tras-los-incendios&#8221; class=”regular”, target=”_blank”>has posted details of the paper (in Spanish) – hopefully it will generate some interest in our work and that some find it useful for their own.

Update 18th August 2009
Several other websites have picked up on the sinc summary and re-published an English version:

New Models for Ecosystems Dynamics and Restoration

Recently I’ve been working on a review of the latest contribution to The Science and Practice of Ecological Restoration book series, entitled New Models for Ecosystems Dynamics and Restoration (edited by Hobbs and Suding). Here’s an outline of what I’ve been reading and thinking about – the formal review will appear in print in Landscape Ecology sometime in the future.

The Society for Ecological Restoration defines ecological restoration as an “intentional activity that initiates or accelerates the recovery of an ecosystem with respect to its health, integrity and sustainability”. Restoration ecology is a relatively young academic field of study that addresses problems faced by land managers and other restoration practitioners. Young et al. suggest that models of succession, community assembly and state transitions are an important component of ecological restoration, and that seed and recruitment limitation, soil processes and diversity-function relationships are also important.

The ‘new’ models referenced in the title of the book are ‘threshold’ or ‘regime shift’ ecosystem models. These models are ‘new’, the editors argue, in the sense that they contrast gradual continual models and stochastic models. Gradual continuous models are described as those that assume post-disturbance ecosystem recovery follows a continuous, gradual trajectory and are associated with classical, Clementsian theory that assumes steady, uni-directional change towards some single equilibrium state. Stochastic models assume exogenous drivers dominate the behavior of ecosystems to the extent that non-equilibrium and unstable systems states are the norm. Threshold models assume there are multiple (in contrast to the Clementsian view) stable (in contrast to the stochastic view) ecosystem states and represent changes from one relatively distinct system state to another as the result of small changes in environmental (driving) conditions. Thresholds and regime shifts are important to consider in restoration ecology as there may be thresholds in system states beyond which recovery to the previous (healthy) state is not possible.

Two types of threshold model are considered in New Models;

i) state-and-transition (S-T) models that represent multiple (often qualitative) stable states and the potential transitional relationships between those states (including the rates of transition), and

ii) alternative stable state (ASS) models which are a subset of S-T models and generally represent systems with fewer states and faster transitions (flips) between the alternative states.

For example, S-T models are often used to represent vegetation and land cover dynamics (as I did in the LFSM I developed to examine Mediterranean landscape dynamics), whereas ASS models are more frequently used for aquatic systems (e.g. lake ecosystems) and chemical/nutrient dynamics.

New Models focuses on use of these models in ecological restoration and provides an excellent introduction to key concepts and approaches in this field. Two of the six background chapters in this introduction address models and inference, two introduce transition theory and dynamics in lake and terrestrial ecosystems (respectively), and two discuss issues in social-ecological and rangeland systems. These background chapters are clear and concise, providing accessible and cogent introductions to the systems concepts that arise in the later case studies. The case studies present research and practical examples of threshold models in a range of ecosystems types – from arid, grassland, woodland and savanna ecosystems, though forest and wetland ecosystems, to ‘production landscapes’ (e.g. restoration following mining activities). Although the case study chapters are interesting examples of the current state of the use and practice of threshold modeling for ecological restoration, from my perspective there are certain issues that are insufficiently addressed. Notably, there is limited explicit consideration of spatial interactions or feedbacks between social and ecological systems.

For example, in their background chapter King and Whisenant highlight that many previous studies of thresholds in social-ecological systems have investigated an ecological system driven by a social system, ignoring feedbacks to the social components. Explicitly representing the links between social and ecological components in models does remain a daunting task, and many of the case studies continue in the same vein as the ‘uni-directional’ models King and Whisenant hint at (and I’ve discussed previously). The editors themselves highlight that detailed consideration of social systems is beyond the scope of the book and that such issues are addressed elsewhere (including in other volumes of the Ecological Restoration book series – Aronson et al.). However, representing human-environment feedbacks is becoming increasingly vital to ensure appropriate understanding of many environmental systems and their omission here may prove unsatisfactory to some.

A second shortcoming of the book, from the perspective of a landscape ecologist, is the general lack of consideration for spatial pattern and scaling and their influences on the processes considered in the case studies. In their background chapter on resilience theory and rangelands, Bestelmeyer et al. do highlight the importance of a landscape perspective and considering land as being a ‘state mosaic’, but only a single case study really picks up on these concepts in earnest (Cale and Willoughby). Other case studies do indirectly consider spatial feedbacks and landscape context, but explicit representation of relationships between spatial patterns and ecosystems processes is lacking.

However, these criticisms do need to be considered in light of the objectives of New Models. At the outset, the editors state that the book aims to collectively evaluate threshold modeling approaches as applied to ecological restoration – to examine when and where these models have been used, what evidence is used to derive and apply them, and how effective they are for guiding management. In their synthesis chapter the editors highlight that the models presented in the book have been used heuristically with little testing of their assumptions and ask; “Does this indicate an obvious gap between ecological theory and restoration practice?” For example, in their chapter on conceptual models for Australian wetlands, Sim et al. argue that the primary value of threshold models is to provide a conceptual framework of how ecosystems function relative to a variety of controlling variables. The editors’ suggestion is that restoration practitioners are applying models that work rather than “striving to prove particular elements” (of system function or ecological theory), and that maybe this isn’t such a bad approach given pressing environmental problems.

Potentially, this is a lesson that if landscape ecologists are to provide ecosystem managers and stewards with timely advice they may need to need to scale-back (i.e., reduce the complexity of) their modeling aims and objectives. Alternatively, we could view this situation as an opportunity for landscape ecologists to usefully contribute to advance the field of ecological restoration. Most likely it is indicative that where practical knowledge is needed quickly, simple models using established ecological theory and modelling tools are most useful. But in time, as our theoretical understanding and representation of spatial and human-environment interactions advances, these aspects will be integrated more readily into practical applications of modelling for ecological restoration.

Buy at Amazon

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.

PEST or Panacea?

Although some may say blogging is dead, the editors at Nature think it’s good to blog. The Nature editors discuss the place of blogging in scientific discourse, focusing on the reporting of results from papers in press (i.e. accepted by a journal for publication but not actually in print yet). They suggest that if the results of an article in press are reported at a conference then they are fair game for discussion and blogging. And they argue that “[m]ore researchers should engage with the blogosphere, including authors of papers in press”.

I wish I had more papers in the in press pile. Unfortunately I’ve got more in the under review pile (see my previous post), but at least I’m adding to it. Earlier this week David Demeritt, Sarah Dyer and I submitted a manuscript to Transactions of the Institute of British Geographers. The paper discusses public engagement in science and technology and examines some of the practical challenges such a collaboration entails. One of the examples we use is the work I did during my PhD examining the communication of my model results with local stakeholders. It’s only just submitted so I’ll just post the abstract for now. As we get further along the review process toward the in press stage (with this and other papers) I’ll return to see if we can spark some debate.

David Demeritt, Sarah Dyer and James Millington
PEST or Panacea? Science, Democracy, and the Promise of Public Participation
Submitted Abstract
This paper explores what is entailed by the emerging UK consensus on the need for increased public engagement in science and technology, or PEST as we call it. Common to otherwise incompatible instrumental and de-ontological arguments for PEST is an associated claim that increased public engagement will also somehow make for ‘better’ science and science-based policy. We distinguish two different ways in which PEST might make such a substantive contribution, which we term ‘normative steering’ and ‘epistemic checking’. Achieving those different aims involves engaging with different publics in different ways to different ends. Accordingly, we review a number of recent experiments in PEST to assess the practical challenges in delivering on its various substantive promises. The paper concludes with some wider reflections on whether public engagement in science is actually the best way of resolving the democratic dilemmas to which PEST is addressed.

Publishing in Geography

Got a Geography paper you want to publish? You would do well to read the RGS guide to publishing in Geography. In fact, it’s got some good tips for anyone wanting to learn more about publishing in academia. And if you really aren’t bothered about academia or publishing you should still check it out because it has one of the nicest online document readers I’ve seen in a while.

Reading the RGS guide gave me the idea that maybe I should write up my blog on David Demeritt’s TIBG Boundary Crossing piece for submission as a commentary. So I’ve been reading and thinking about that and will hopefully have something submitted in February. I’ve also been asked to help re-write the Human Decision-Making chapter of Wainwright and Mulligan’s Environmental Modelling ready for its second edition. I’ll be working on that throughout 2009.

Other things I’ve been working on recently are the spatial deer density modelling manuscript (in draft) and the Deer browse/mesic conifer planting experiment (also in draft). I’ve nearly compled the revisions for the paper on my Landscape Fire Succession Model and should be able to return it to EMS soon. The Mind, the Gap paper still isn’t back from the reviewers, and who knows when I’ll ever get round to looking at the narratives paper again.

Not this weekend that’s for sure – Saturday is paper revisions and then on Sunday we’re heading north to our Michigan UP study area to meet with the timber companies (Plum Creek and American Forest Management) that have helped us with our fieldwork over the last two summers. Between the meetings we’ll drive through the study area and maybe jump out at one or two of our sites to take a look at them in the winter snow. I’ve been up there during Spring, Summer and Autumn, so this trip will check off my final season. I’ll take my camera and hopefully have a few pictures to post here next week.

Winter White-Tailed Deer Density Paper

First week back in CSIS after the holiday and I got cracking with the winter white-tailed deer density paper we’re working. Understanding the winter spatial distribution of deer are important for the wider simulation modelling project we’re working on as the model needs to be able to estimate deer densities at each model timestep. We need to do this so that we might represent the impacts of deer on tree regeneration following timber harvest in the simulation model. The work the paper will present is using data from several sources:

  1. data we collected this summer regarding forest stand composition and structure,
  2. similar data kindly shared with us by the Michigan DNR,
  3. estimates of deer density derived from deer pellet counts we also made this year,
  4. other environmental data such as snow depth data from SNODAS.

Here’s my first stab at the opening paragraph (which will no doubt change before publication):

Spatial distributions of wildlife species in forest landscapes are known to be influenced by forest-cover composition and pattern. The influence of forest stand structure on the spatial distribution of wildlife is less well understood. However, understanding the spatial distribution of herbivorous ungulate species that modify vegetation regeneration dynamics is vital for forest managers entrusted with the goal of ensuring both ecological and economic sustainability of their forests. Feedbacks between timber harvest, landscape pattern, stand structure, and herbivore population density may lead to spatial variation in tree regeneration success. In this paper we explore how forest stand structure and landscape pattern, and their interactions with other environmental factors, can be used to predict and understand the winter spatial distribution of white-tailed deer (Odocoileus virginianus) during in the managed forests of the central Upper Peninsula (U.P.) of Michigan, USA.

I’ll update the status of the paper here periodically.