Mummies and masquerades: English and Caribbean connections

The composite mumming play script that the Ecclesfield-based Victorian children's author Juliana Horatia Ewing published in 1884 found its way to St. Kitts and Nevis in the Caribbean, where it was it was taken up enthusiastically by the black population as one of its Christmas Sports. The Mummies continue to act (and dance) to this day. Economic migrants took the Christmas Sports in turn to the Dominican Republic, in particular around the town of San Pedro de Macoris, where the performers recently gained a UNESCO Cultural Heritage Award. This paper derives from a presentation based around two videos, presented here as story boards. Millington introduces Ewing's play, and footage of the St Kitts Mummies and the Bull Play filmed by Joan McMurray. James continues the story by introducing footage of the related tradition from the Dominican Republic called the Wild Indians in English and Los Guloyas (the Goliaths) in Spanish

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

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. The 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 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. 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 agent-based model of land use/cover change.Land Use/Cover Change, Land Tenure, Wildfire, Mediterranean-Type Ecosystem, Agriculture, Spatial Heterogeneity

Assessing the quality of land system models: moving from valibration to evaludation

Reviews suggest that evaluation of land system models is largely inadequate, with undue reliance on a vague concept of validation. Efforts to improve and standardise evaluation practices have so far had limited effect. In this article we examine the issues surrounding land system model evaluation and consider the relevance of the TRACE framework for environmental model documentation. In doing so, we discuss the application of a comprehensive range of evaluation procedures to existing models, and the value of each specific procedure. We develop a tiered checklist for going beyond what seems to be a common practice of ‘valibration’ (the repeated variation of model parameter values to achieve agreement with data) to achieving ‘evaludation’ (the rigorous, broad-based assessment of model quality and validity). We propose the Land Use Change – TRACE (LUC-TRACE) model evaludation protocol and argue that engagement with a comprehensive protocol of this kind (even if not this particular one) is valuable in ensuring that land system model results are interpreted appropriately. We also suggest that the main benefit of such formalised structures is to assist the process of critical thinking about model utility, and that the variety of legitimate modelling approaches precludes universal tests of whether a model is ‘valid’. Evaludation is therefore a detailed and subjective process requiring the sustained intellectual engagement of model developers and users

Local winter deer density: Effects of forest structure and snow in a managed forest landscape

*Background/Questions/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 will 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. 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 mean hardwood tree diameter-at-breast-height is low. Multiple regression models including these factors explain 22% of variance in deer density and have up to a 65% chance of correctly ranking a site’s deer density (relative to other sites within our study area). We use model ensembles to produce maps of estimated deer density (and associated uncertainty) for a subset of our study area and show how managers might use these maps to aid co-management of deer and forest regeneration. Our results highlight the importance of local and regional factors (forest cover-type pattern, stand structure, climate) on winter white-tailed deer density in managed hardwood-conifer forests. Use of these results, and the simulation model being developed, 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.
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