Combining Farmer Decision Making With Systems Models for Restoring Multi-Functional Ecohydrological Systems in Degraded Catchments

Justin Ryan (2007). Combining Farmer Decision Making With Systems Models for Restoring Multi-Functional Ecohydrological Systems in Degraded Catchments PhD Thesis, School of Geography, Planning and Architecture, The University of Queensland.

       
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Author Justin Ryan
Thesis Title Combining Farmer Decision Making With Systems Models for Restoring Multi-Functional Ecohydrological Systems in Degraded Catchments
School, Centre or Institute School of Geography, Planning and Architecture
Institution The University of Queensland
Publication date 2007-11-23
Thesis type PhD Thesis
Supervisor Ludwig, John
McAlpine, Clive A.
Subjects 300000 Agricultural, Veterinary and Environmental Sciences
Abstract/Summary In agricultural landscapes, native ecosystems are largely replaced by non-native crop and pasture species, with the extent of modification dependent on land use history and the management practices of current farmers. The result is greater complexity in some parts of the landscape, while other areas become more simplified. Of critical importance, however, is that many landscapes become ‘leaky’ due to the impaired feedback mechanisms between the types of vegetation present (i.e. land cover) and their ability to efficiently cycle water, sediment, nutrients and carbon between the lower atmosphere, vegetation, soil, and hydrological systems, causing landscapes to become ecohydrologically dysfunctional. In many mixed cropping-grazing landscapes of Australia, ecohydrologically dysfunctional landscapes exhibit declines in soil condition, water quality and quantity, rising salinity levels, higher wind speeds and temperatures, reduced rainfall, and a loss of biodiversity and production capacity. Ecohydrologically dysfunctional landscapes also are less resilient to climatic variations, which during extended dry periods, can result in water shortages with potentially dire socioeconomic consequences. This Thesis focuses on how landscape designs comprised of particular types and locations of land covers can improve and restore the ecohydrological functioning of mixed cropping-grazing landscapes. The specific aim of this Thesis is to show ‘proof of concept’ for the – development of a new modelling approach which automatically calculates the effects that land cover changes at specific locations across hillslopes have on ecohydrological systems functioning, and to use this information to delineate landscape designs that enhance water retention within the landscape while minimising sediment and nutrient export to the catchment. To support this aim, the Thesis has three major objectives: 1) develop a complex adaptive systems conceptual model of ecohydrological systems functioning within landscapes; 2) develop a participatory survey method to capture the expert knowledge of farmers in terms of preferences for a given land use and changes in these preferences during seasonal variations in rainfall; and 3) demonstrate ‘proof of concept’ that a combination of expert systems and hydrological process models can be employed to automatically delineate landscape designs which restore ecohydrological functioning within mixed cropping-grazing landscapes in sub-tropical Australia. The development of a rigorous theoretical basis of ecohydrological systems function within the landscape in terms of adaptations to environmental flux in climate and human forcings such as land cover change, was achieved by integrating the concepts of both complex adaptive systems and landscape ecology theories. The resulting framework, termed ‘Complex Adaptive Landscapes’ (CAL), derived six core tenets which described the system dynamics of a landscape: 1) a continuum of scales; 2) open systems; 3) non-linear feedback mechanisms; 4) aggregation of components; 5) self-organisation; and 6) multiple meta-stable states. The participatory survey method resulted in the development of the ‘Graphical Landscape Map Survey’ (GLAMS). This process applied three-dimensional representations of the landscape (i.e. Graphical Landscape Maps) in combination with Bayesian Belief Networks (BBNs) to capture farmer’s expert knowledge. GLAMS generated probability estimates (P) that highlighted the importance of ecohydrological functioning to farmers and the locations and change in land use through time in both average and extended dry seasons. Achievement of the last objective resulted in the ‘Landscape Ecohydrological Attenuation Configuration System (LEACS). This system utilised farmer decision rules as probability estimates (P) for a given land cover within the STELLA systems software, and then revised these P estimates depending on the magnitude of runoff from a hillslope following an intense thunderstorm event as calculated by a distributed hydrological process model (MIKE SHE). The fundamental dynamics of the LECAS model was based on iterative feedback between the outputs of water at the end of the catchment and changing the spatial locations of particular land covers within the catchment over time. Together the three objectives highlighted the following major implications for natural resource and catchment management: i) the CAL framework may be used to design both sampling and monitoring strategies in natural resource and catchment management. CAL suggested that monitoring timeframes should be decadal in time-frame, and the feedback mechanisms of landscape must be accounted for if the longer-term sustainability of human-modified landscapes is to be achieved. A basis to such complexity is likely to form around aggregated components such as native vegetation patches, and these in turn, are important for self-organisation of a desirable landscape state to be maintained through increased resilience to disturbances and climatic fluxes; ii) participatory survey methods, such as GLAMS, are an excellent means to capture farmer expert knowledge in a manner that is intuitive to the farmers. The GLAMS approach accounted for any desired set of management actions put forward by a Landcare group or catchment body, differentiated between property sizes, and incorporated landscape heterogeneity in time and space. The framework helped to prioritise the level of support for a given set of NRM actions by farmers, including where activities were best placed. The approach also aided in identifying future landscape states based on a priori conditions and farmer preferences; and iii) the LEACS model demonstrated an approach capable of providing estimates of where it would be best to locate land cover changes (e.g. tree belts) to aid in the restoration of ecohydrological functioning in the landscape. A secondary outcome for simulations which tested the effects of tree belts in specific configurations was that these designs were an effective ecohydrological restoration technique that reduced water velocities and increased infiltration across steep hillslopes in the Maronghi Creek catchment, Southeast Queensland.

 
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