Attic pottery in early Classical Thessaly. A case study from Achaia Phthiotis

This paper attributes a previously unnoticed Attic black-figured lekythos kept in the Archaeological Museum of Volos to the Pholos Group (ca. 470 BC) and discusses its findspot in the peripheral Thessalian district of Achaia Phthiotis. Beyond an art-historical appreciation of the hastily-drawn chariot scene on this lekythos and a discussion of stylistic parallels, which include a lekythos in Prague, it is argued that such lekythoi were socially important for their shape and small size that made them easily transportable. The assumed scarcity of Attic pottery in Thessaly can be questioned given that a considerable amount of Attic pottery from Thessalian locations is mentioned only in passing or remains unpublished in museum storage. Small late black-figured lekythoi predominate amongst Attic pottery shapes in Thessaly. The popularity of such lekythoi can become indicative of human mobility across the landscape and the consumption of imported (grave) goods by social groups other than elites.

Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community- weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.

Flooding tolerance in four 'Garrigue' landscape plants: implications for their future use in the urban landscapes of north-west Europe?

Within a changing climate, Mediterranean ‘Garrigue’ xerophytes are increasingly recommended as suitable urban landscape plants in north-west Europe, based on their capacity to tolerate high temperature and reduced water availability during summer. Such species, however, have a poor reputation for tolerating waterlogged soils; paradoxically a phenomenon that may also increase in north-west Europe due to predictions for both higher volumes of winter precipitation, and short, but intensive periods of summer rainfall. This study investigated flooding tolerance in four landscape ‘Garrigue’ species, Stachys byzantina, Cistus × hybridus, Lavandula angustifolia and Salvia officinalis. Despite evolving in a dry habitat, the four species tested proved remarkably resilient to flooding. All species survived 17 days flooding in winter, with Stachys and Lavandula also surviving equivalent flooding duration during summer. Photosynthesis and biomass production, however, were strongly inhibited by flooding although the most tolerant species, Stachys quickly restored its photosynthetic capacity on termination of flooding. Overall, survival rates were comparable to previous studies on other terrestrial (including wetland) species. Subsequent experiments using Salvia (a species we identified as ‘intermediate’ in tolerance) clearly demonstrated adaptations to waterlogging, e.g. acclimation against anoxia when pre-treated with hypoxia. Despite anecdotal information to the contrary, we found no evidence to suggest that these xerophytic species are particularly intolerant of waterlogging. Other climatic and biotic factors may restrict the viability and distribution of these species within the urban conurbations of north-west Europe, but we believe increased incidence of flooding per se should not preclude their consideration.

Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties

Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

The influence of anthropogenic landscape changes on weather in south Florida

Using identical observed meteorology for lateral boundary conditions, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida. Three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state. Over the 2-month period, there was a 9% decrease in rainfall averaged over south Florida with the 1973 landscape and an 11% decrease with the 1993 landscape, as compared with the model results when the 1900 landscape is used. The limited available observations of trends in summer rainfall over this region are consistent with these trends.

Design meetings and the coordination of expertise

The coordination of work and expertise in construction projects is often treated in terms of models or formal rules. However, much is to be gained, if we are to understand it, by examining actual coordination practices. The objective in this article is to address practices of coordination of expertise in the context of design team meetings. The focus is specifically on conversational practices between the structural engineer and the landscape architect part of the design team in a healthcare infrastructure project. The central argument is that the coordination of expertise relied on and was organised by mundane and everyday methods, and not by formal and abstract ones. This argument is drawn from ethnomethodology, a form of sociological analysis that focuses on the situated methods by which activities are produced, but shares concerns found in the literature on actual project management practices. The ethnomethodological stance, however, offers a different perspective on the significance of the empirical reality of projects and a possibility to incorporate within this literature a concern with the ordinary methodical organisation of project activities.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems

Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture.