ESA 2009 Abstract

February 2009 seems to be the month of abstracts. Here's another we just submitted to the 94th Ecological Society of America Annual Meeting, the theme of which is Ecological Knowledge and a Global Sustainable Society.

Local winter white-tailed deer density: Effects of forest cover pattern, stand structure, and snow in a managed forest landscape
James D. A. Millington, Michael B. Walters, Megan S. Matonis and Jianguo Liu
Michigan State University

Background/Question/Methods
White-tailed deer (Odocoileus virginianus) are a ‘keystone herbivore’ with the potential to cause tree regeneration failure and greatly affect vegetation dynamics, stand structure and ecological function of forests across eastern North America. In northern mixed conifer-hardwood forests, local winter-time deer populations are dependent on habitat characterized by patterns of forest cover that provide shelter from snow and cold temperatures (lowland conifer stands) in close proximity to winter food (deciduous hardwood stands). Stand structure may also influence winter spatial deer distribution. Consequently, modification of forest cover patterns and stand structure by timber harvesting may affect local spatial deer distributions, with potential ecological and economic consequences. Here, we ask if forest cover pattern and stand structure, and their interactions with snow depth, can explain winter deer density in the managed forests of the central Upper Peninsula of Michigan, USA. For each local winter deer density estimate (from fecal pellet counts) we calculate stand-level characteristics for surrounding ‘landscapes of influence’ of radius 200 m and 380 m. For these data, and modeled snow depth estimates, we use multivariate techniques to produce predictive models and to identify the most important factors driving local deer densities across our 400,000 ha study area.

Results/Conclusions
Distance to the nearest conifer stand consistently explains the most variance in univariate regression models. Deer densities are highest near lowland conifer stands in areas where the proportion of hardwood forest-cover is high but the mean tree diameter-at-breast-height is low. Multiple regression models including these factors explain up to 38% of variance in deer density and have up to a 68% chance of correctly ranking a site’s deer density (relative to other sites within our study area). We are unable to conclusively show that snow depth has a significant impact on winter deer density, but our data suggest that more detailed investigation into the combined effect of distance to lowland conifer and snow depth may prove fruitful. Our results quantify clear effects of stand structure and forest cover composition on the winter spatial distribution of white-tailed deer. We briefly discuss how these results can be used in an ecological-economic simulation model of a managed forest for tree regeneration risk assessment. Use of these results, and the simulation model, will help identify management practices that can decrease deer impacts and ensure the ecological and economic sustainability of forests in which deer browse is proving problematic for tree regeneration.

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.

US-IALE 2009: Abstracts

The two abstracts I submitted to US-IALE 2009 have been accepted for (oral) presentation at the meeting. I'll be presenting both on the work I've been doing here at CSIS and from my PhD. I've copied the initial abstracts below (these may change slightly) and I'll post a full list of what everyone in CSIS is up to at the conference nearer the time. See you in Snowbird!


Modeling Interactions of Human and Natural Disturbances in a Managed Forest Landscape

James D.A. Millington, Michael B. Walters, Megan S. Matonis, Frank Lupi, Susan Chen, Kimberly R. Hall, Edward J. Laurent, Jianguo (Jack) Liu

As is often the case for coupled human and natural systems, the interactions between human and natural forest disturbances have the potential to produce complex system behavior. Spatially-explicit ecological-economic modeling provides a useful tool to investigate these phenomena in an integrated manner, revealing patterns and processes not observable by investigating the social and natural components separately. We present the development and initial results from such a model that examines the complex interactions among timber harvest, white-tailed deer browse and vegetation dynamics in a managed forest landscape in Michigan’s Upper Peninsula. This landscape has been experiencing low tree regeneration due to overabundant white-tailed deer, and changes in habitat for songbirds of conservation concern due to deer impacts and timber harvesting.

The multi-scale model uses input data on deer population, forest stand structure, tree regeneration, forest cover, habitat type and land ownership data collected at plot, stand, and landscape levels. Vegetation establishment, regeneration and growth are simulated using the USFS Forest Vegetation Simulator (FVS). Deer browse impacts are represented in FVS and parameterized by data we have collected on deer density and forest gap regeneration. As is common for many studies, our stand-level data for model initialization are incomplete across the 4,000 km2 study area. We show how we impute our stand-level data across the remainder of the study area using auxiliary variables including topography and remotely-sensed land cover.

Results show that distance to nearest lowland conifer stand, mean stand tree diameter-at-breast-height and the proportion of hardwood species in the surrounding local area are statistically significant predictors of deer density across the landscape (p < 0.01). These variables alone explain 40% of variance in deer density. Our initial model simulation results indicate complex spatial interactions between deer densities, stand structure and timber values across the managed forest landscape.


Investigating the Interaction of Land Use/Cover Change and Wildfire using Agent-Based Modelling
(Global Land Project symposium on agent-based modelling of land use effects on ecosystem processes and services)

James D.A. Millington, John Wainwright, Raul Romero-Calcerrada, George L.W. Perry and David Demeritt

Humans have a long history of activity in Mediterranean Basin landscapes. Spatial heterogeneity in these landscapes hinders understanding about the impacts of changes in human activity on ecological processes, such as wildfire. We present an Agent-Based Model (ABM) of agricultural land-use decision-making. This model is integrated with a spatially-explicit, state-and-transition Landscape Fire-Succession Model (LFSM) to investigate the relative importance of anthropic and ecological drivers of the wildfire regime.

The ABM 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 farmers that manage their land because of its cultural, rather than economic, value. Results from the ABM indicate that 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.

The LFSM uses plant functional types to represent spatial and temporal competition for resources (predominantly water and light) in a rule-based modelling framework. Wildfire behaviour is represented using a cellular-automata approach. Results from the integrated ABM-LFSM indicate that fires ignited by human causes burned greater areas of shrubland than would be expected at random, and modelled lightning fires burned greater areas of forest land-cover types than would be expected at random.

We conclude by discussing our efforts to achieve a form of ‘stakeholder model validation’. This evaluation process involved taking the model and its results back for examination by the agricultural actors and decision-makers that aided our model conceptualization. We put this discussion in the context of recent calls for increased engagement between science and the public, highlighting some of the problems we encountered with this form of model evaluation.