Marie Castellazzi

Simulation scenarios of spatio-temporal arrangement of crops at the landscape scale

The spatial and temporal arrangement of crops is a conspicuous feature of rural landscapes. It has been identified as an important factor in many environmental issues, such as the coexistence of genetically modified (GM) and non-GM crops, and the mitigation of soil erosion. This paper examines a scenario-based approach for rapid generation and screening of crop allocations that meet users constraints without requiring mechanistic modelling. LandSFACTS (Landscape Scale Functional Allocation of Crops Temporally and Spatially) is a software application specifically designed to simulate such crop arrangement scenarios, whilst ensuring both spatial and temporal coherence with regard to the initial constraints. The software uses an empirical approach to allocate crops to fields (polygons in vector format) over a sequence of years, using a stochastic process (Markov chains) and rule-based constraints. Crop rotations are represented by transition probabilities complemented by other temporal constraints such as return period or prohibited sequences. Further spatial and temporal constraints on crop arrangement can be applied through separation distances, yearly proportions, and the application of statistical tests. The software outputs a crop allocation solution with a crop for every field for every year, respecting all user-defined constraints; the range of potential solutions can then be explored through multiple model runs. Metrics based upon the difficulty of obtaining such an allocation from the initial constraints are also generated. A case study is provided to demonstrate the use of combined agronomic and environmental criteria for exploring GM crop coexistence at the landscape scale.

The interactive responses of water quality and hydrology to changes in multiple stressors, and implications for the long-term effective management of phosphorus

Soluble reactive phosphorus (SRP) plays a key role in eutrophication, a global problem decreasing habitat quality and in-stream biodiversity. Mitigation strategies are required to prevent SRP fluxes from exceeding critical levels, and must be robust in the face of potential changes in climate, land use and a myriad of other influences. To establish the longevity of these strategies it is therefore crucial to consider the sensitivity of catchments to multiple future stressors. This study evaluates how the water quality and hydrology of a major river system in the UK (the River Thames) respond to alterations in climate, land use and water resource allocations, and investigates how these changes impact the relative performance of management strategies over an 80-year period. In the River Thames, the relative contributions of SRP from diffuse and point sources vary seasonally. Diffuse sources of SRP from agriculture dominate during periods of high runoff, and point sources during low flow periods. SRP concentrations rose under any future scenario which either increased a) surface runoff or b) the area of cultivated land. Under these conditions, SRP was sourced from agriculture, and the most effective single mitigation measures were those which addressed diffuse SRP sources. Conversely, where future scenarios reduced flow e.g. during winters of reservoir construction, the significance of point source inputs increased, and mitigation measures addressing these issues became more effective. In catchments with multiple point and diffuse sources of SRP, an all-encompassing effective mitigation approach is difficult to achieve with a single strategy. In order to attain maximum efficiency, multiple strategies might therefore be employed at different times and locations, to target the variable nature of dominant SRP sources and pathways.

Scenario analysis for regional decision-making on sustainable multifunctional land uses

Abstract Land-use patterns are influenced by both top-down and bottom-up (local) factors, with their interactions varying in both space and time. This provides a major challenge to decision-making for sustainable multifunctional landscapes. A cross-scale scenario structure has been developed to integrate top-down and bottom-up context based upon the familiar IPCC Special Report on Emission Scenarios framework. Qualitative scenario storylines are converted into multiple quantified simulations of regional land-use change using a series of rules, with information translated across scales using a hierarchical land-use classification. Land-use parcels (fields) are used as key landscape reference units representing the local dimension of regional changes. Biophysical limitations on land use are represented through land capability classes (climate, soils and topography). Socio-economic factors are characterised in reference to global drivers, policy targets or local preferences. A flexible stochastic software tool (LandSFACTS) ensures spatiotemporal coherence of land-use allocation simulations consistent with scenario storylines. Scenario development is designed to be interactive, bridging ‘problem-focussed’ and ‘actor-focussed’ approaches. A case study is presented from NE Scotland, where plans to enhance multifunctionality through new woodland are evaluated against drivers of globalisation and climate change. Competing priorities, such as food security, mean that in some scenarios, a policy objective for woodland expansion to occur on farmland cannot be met. Woodland expansion would then have to occur on uncultivated upland areas. Scenario analysis has highlighted specific sensitivity to change in ‘marginal’ agricultural areas, with the varying influence of different top-down or bottom-up factors leading to divergent potential outcomes.

Changes in climate variability with reference to land quality and agriculture in Scotland

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west–east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

Visualisation techniques to support public interpretation of future climate change and land-use choices: a case study from N-E Scotland.

ABSTRACT Mitigating and adapting to climate change includes a requirement to evaluate the role of future land uses in delivering robust integrated responses that are sensitive to local landscape contexts. In practice, this emphasises the need for community engagement, planning and inclusive decision-making. Community engagement may be potentially facilitated by the use of spatially explicit quantitative scenarios of land-use change in combination with interactive visualisation. This requires a coherent framework to integrate spatial data modelling, analytical capabilities and visualisation tools in a format that will also engage diverse public audiences. These challenges were explored with a case study of virtual landscapes from N-E Scotland that was used to test preferences for scenarios of future land use. Visualisations employed texture-based rendering rather than full photo-realistic rendering to facilitate interactivity and this provided additional scope for audiences to explore multiple future scenarios compared to the present landscape. Interactive voting in a virtual landscape theatre suggested preferences for visual diversity, good stewardship and perceived naturalness that should be considered in developing planned responses to change. Further investigation of preferences was conducted using interactive 3D features located within the landscape. Study findings are reviewed against objectives for inclusive engagement in the Digital Earth agenda and used to make further recommendations on the use of scenarios and visualisation tools. In particular, technical advances in user engagement need to be developed in conjunction with emerging good practice that addresses ethical, behavioural and inclusion issues so that the content is presented in as transparent and unbiased format as possible.