LUCI is a framework and associated computer model that uses information about topography, land cover, and soil to produce maps of ecosystem services and trade-offs. These services include flood mitigation, agricultural productivity, nitrogen/phosphorous delivery, carbon sequestration, habitat suitability/connectivity, and erosion (Table 1).
|Agricultural productivity||Evaluates the potential, currently, and optimal agricultural productivity||
Based on slope, fertility, drainage, aspect, climate
|Carbon stocks and fluxes||Calculates carbon levels at a steady state, potential to increase storage, emissions, and sequestration||
IPCC Tier 1 compatible. Based on soil, vegetation, stocking rate, fertiliser
|Erosion and sediment||Estimates soil loss from gullies and rill/inter-rill erosion||
Uses CTI and RUSLE. Based on slope, curvature, contributing area, land use, soil type, and climate
|Flood mitigation and water supply||Maps locations that are sinks for overland and surface flow, where flow may accumulate, and average flow to all points of the stream and lake network||
Topographical routing of water accounting for storage and infiltration capacity as function of soil & land use
|Habitat connectivity and suitability||Identifies suitable areas for habitat expansion and protection based on connectivity and characteristics||
Cost-distance approach: dispersal, fragmentation, connectivity; Identification of priority habitat by biophysical requirements; Measures of habitat richness, evenness, patch size etc.
|Nitrogen and Phosphorus||Maps the terrestrial load of different land cover and soil, accumulation of nutrients through the landscape, pathway to streams, and in-stream nutrient concentrations||
Export coefficients (land cover, farm type, regional fertiliser, stocking rate) combined with water and sediment delivery models
|Coast/floodplain inundation risk||Creates an indicative map of areas that could potentially be inundated by storm surge or long term rise||
Based on topography and input height of storm surge/long term rise etc: surface and groundwater impacts estimated
|Trade-offs/synergy identification||Identifies areas where management interventions may enhance or degrade multiple services||
Various layering options with categorised service maps; e.g. Boolean, conservative, weighted arithmetic, distribution plots
These ecosystem services (ES) are defined as the benefits, whether tangible or intangible, that people receive from ecosystems (MEA, 2005). It is important to manage ecosystems sustainable for the purposes of their conservation and the continued delivery of ES for human well-being. Hence, the LUCI model is a decision-support tool designed to aid stakeholders in making land management plans through exploring the effects that land cover changes will have on ES.
Among other products, LUCI produces maps showing where change can be made to improve services, or where any land cover change will degrade a service. For example, Figure 1 shows the LUCI output for flood mitigation. Based on the topography, land cover, and soil, the red areas are predicted to have high flood concentration and are therefore prime targets for mitigation interventions such as tree planting. The LUCI model can be run from field to catchment to national-scale, depending on the availability of data. One of the strengths of LUCI is that it is spatially explicit, accounting for how different types of land cover and soil are connected within the landscape, and how those combinations affect ES (Jackson et al., 2013). The trade-offs tool compares multiple services to identify areas where interventions can enhance several services (synergies) or where changes would improve one service but degrade the other (trade-offs).
Figure 1. Sample LUCI map for flood mitigation.
At a minimum, LUCI requires three things to run: a digital elevation model (DEM) to represent landscape topography, a land cover shapefile to represent different types of vegetation and management, and a soil shapefile to represent different types of soil. Ideally, the DEM would have a resolution of 5m to 10m to fully utilise LUCI’s powerful spatially-explicit modelling. Although LUCI can run with coarser datasets (30m or 90m), the results would be less detailed compared to the finer resolution maps. To enhance the accuracy and reliability of the LUCI output, optional information can be used as input: stream network, rainfall, evapotranspiration, water inputs or abstractions, etc.
Together with the land cover and soil information, LUCI generates a baseline scenario that feeds into determining the spatial distribution, supply, and opportunities of the individual ES. The land cover information can be amended or changed to explore potential future scenarios, and those results can be compared to the baseline. The comparison enables users to see how their land cover changes will affect the distribution and supply of services.
The LUCI model was initially applied in the United Kingdom, where it was used in a national-scale application in Wales to assess the effect of changes on ES and produced trade-off maps showing potential synergistic opportunities across different land cover scenarios (Emmett et al., 2017). LUCI has been used in New Zealand from farm-scale to catchment-scale to map ES and target areas for interventions, investigate the role of trees in flood mitigation, assess the response of human stakeholders to LUCI modelling and results, and identify critical source areas for nutrients. The model has also been used in the agricultural sector to inform decisions around farm management, identify mitigation opportunities, and assess inter-farm management effects at the catchment scale. However, despite being set up and applied mostly in these two temperate regions, the LUCI model has also been applied to locations within Ghana, Greece, Bulgaria, Vanuatu, and the Philippines, and is being further developed and parameterised for these and other geo-climatic regions.
LUCI is an evolving tool, and its components are in further development to continuously improve the model’s accuracy and applicability. LUCI has been applied to terrestrial ecosystems, mainly to forested or agricultural locations, and does not currently have enough detail to model urbanised areas or estuarine environments. Future work involving parameterisation of urban environments can elucidate the effect of built structures and urban anthropogenic activity on the surrounding ecosystem. Estuarine and marine environments are also crucial sources of ecosystem services, such as mangroves and coral for carbon sequestration and protection from storm surges and waves. These ecosystems are inherently linked to and affected by terrestrial ecosystems. Developing how the model connects these environments is crucial for a more holistic mountains-to-sea approach to sustainable land management.
To view more about the LUCI model, please visit our website (http://www.lucitools.org). The website also contains an extensive reference list of our previous projects, research papers, and accomplished student projects and theses.
Jackson, B., Pagella, T., Sinclair, F., Orellana, B., Henshaw, A., Reynolds, B., Mcintyre, N., Wheater, H., & Eycott, A. (2013). Polyscape: A GIS mapping framework providing efficient and spatially explicit landscape-scale valuation of multiple ecosystem services. Landscape and Urban Planning, 112, 74–88. https://doi.org/10.1016/j.landurbplan.2012.12.014
MEA. (Millennium Ecosystem Assesment). (2005). Ecosystems and human well-being. Ecosystems (Vol. 5). Island Press. https://doi.org/10.1196/annals.1439.003
Emmett B.E. and the GMEP team (2017) Glastir Monitoring & Evaluation Programme. Final Report to Welsh Government - Executive Summary (Contract reference: C147/2010/11). NERC/Centre for Ecology & Hydrology (CEH Projects: NEC04780/NEC05371/NEC05782).