Dissertations / Theses on the topic 'Whole-farm'

This dissertation investigated farm management concerns faced by grain producers due to the acquisition of various precision agriculture technologies. The technologies evaluated in the three manuscripts included 1) auto-steer navigation, 2) automatic section control, and 3) autonomous machinery. Each manuscript utilized a multifaceted economic model in a whole-farm decision-making framework to determine the impact of precision agriculture technology on machinery management, production management, and risk management. This approach allowed for a thorough investigation into various precision agriculture technologies which helped address the relative dearth of economic studies of precision agriculture and farm management. Moreover, the research conducted on the above technologies provided a wide array of economic insight and information for researchers and developers to aid in the advancement of precision agriculture technologies. Such information included the risk management potential of auto-steer navigation and automatic section control, and the impact the technologies had on optimal production strategies. This dissertation was also able to provided information to guide engineers in the development of autonomous machinery by identifying critical characteristics and isolating the most influential operating machine. The inferences from this dissertation intend to be employed in an extension setting with the purpose of educating grain producers on the impacts of implementing such technologies.

Mathematical modeling in animal agriculture can be applied at various levels including at the tissue, organ, animal, farm, regional and global levels. The purposes of this research were i) to evaluate models used to estimate volatile fatty acid (VFA) and methane (CH4) production and assess their impact on regional enteric CH4 inventory, and ii) to develop a process-based, whole-farm model to estimate net farm GHG emissions. In the first study, four VFA stoichiometric models were evaluated for their prediction accuracy of rumen VFA and enteric CH4 production. Comparison of measured and model predicted values demonstrated that predictive capacity of the VFA models varied with respect to the type of VFA in rumen fluid which impacted estimated enteric CH4 production. Moving to a larger scale assessment, we examined the enteric CH4 inventory from Manitoba beef cattle (from 1990 to 2008) using two mechanistic rumen models that incorporate VFA stoichiometric models: COWPOLL and MOLLY, and two empirical models: Intergovernmental Panel on Climate Change (IPCC) Tier 2 and a nonlinear equation (Ellis). The estimated absolute enteric CH4 production varied among models (7 to 63%) indicating that estimates of GHG inventory depend on model selection. This is an important consideration if the values are to be used for management and/or policy-related decisions. Development of models at the individual farm component level (animal, soil, crop) does not accurately reflect net GHG emissions generated from the whole production system. We developed a process-based, whole-farm model (Integrated Components Model, ICM), using the existing farm component models COWPOLL, manure-DNDC and some aspects of IPCC to integrate farm components and their associated GHG emissions. Estimates of total farm GHG emissions and their relative contribution using the ICM were comparable to estimates using two other whole-farm models (Integrated Farm System Model and Holos model). Variation was observed among models both in estimating whole-farm GHG emissions and the relative contribution of the different sources in the production system. Overall, whole-farm models are required to explore management options that will mitigate GHG emissions and promote best management practices. However, for full assessment of the production system, other benefits of the system (e.g., carbon sequestration, ecosystem services), which are not part of current whole-farm models, must be considered.

I have worked on a Case-Based Reasoning (CBR) system that evaluates crop rotations for their soil erosion and risk of insect pest problems. The purpose of this system is to provide decision support for an automated whole-farm planner (CROPS). CROPS (Buick et al., 1992) generates crop rotation plans that can address some of the environmental, economic and legislative pressures facing natural resource managers. To generate and recommend a crop rotation plan CROPS requires estimates on the soil erosion risks and pesticide pollution potential of the crop rotation. In this research I have designed and prototyped a system that can assist CROPS in the process of whole-farm planning by providing information required for determining the soil erosion risks and the pesticide pollution potential of crop rotations. Inputs for the system include: a crop rotation, its tillage and residue management practices, and field conditions. Soil erosion risk is quantified using the C-value. Pest risks are likelihood of pest outbreaks that require control in a crop rotation. CBR was the chosen methodology for system implementation. In CBR, solutions to new problem situations are derived from retrieving and adapting solutions to similar problem situations experienced in the past. The system was prototyped using Esteemâ ¢, a CBR development shell, and runs on a PC under the MS. Windowsâ ¢, operating system.
Master of Science

This thesis is composed of two essays that investigate whole farm planning and crop marketing in western Kentucky. In the first essay, contracting decisions between food corn producers and a mill are analyzed to observe factors affecting the bushel amount farmers contract. Unbalanced panel data containing seven years’ worth of pricing and contract information are used with a fixed-effects model to generate parameter estimates and quantify their effect on bushels contracted. It was found that contract attributes, market condition, and relationship-specific assets had a significant effect on producers’ food corn contracting decisions. The second essay utilizes mixed-integer programming to optimize resource allocation and marketing strategy for a hypothetical farm. Post-optimal analysis is performed to determine non-binding capacities for drying and storage equipment. The model is re-run with these non-binding capacities to observe changes in net returns as well as planting, harvesting, and marketing strategies. New equipment and associated costs are identified, and the change in net returns from the base case is used as net cash flow in a net present value investment analysis. Results of the investment analysis indicate increasing drying and storage capacity is a wise investment given the scenario modeled.

The number of very small farms (<10 acres) is increasing and beginning farmers (in practice for <10 years) are more likely to run them. Very small farms are typically complex systems in which the farmer manages both production of a diverse array of crops and marketing of crops directly to consumers and their failure rate in early years is high. This work seeks to increase the likelihood of success for beginning farmers by understanding these complex systems better. We collected qualitative and quantitative data from interviews with three successful beginning farm operations in Southwest Virginia covering practical and philosophical aspects of farm production, sales and management. We mapped social, environmental and economic aspects of farming systems and studied how farmers use resources (Community Capitals) and management to enhance their system's success, developing a broader definition of success that encompasses what farmers gain from farming beyond profitability. Using these maps, we created a system dynamics model of a small farm system in STELLA including unique components such as customer attraction and retention. Through model development, we learned that these successful farmers began their operations with experience and financial resources, and employed their skills, resourcefulness and cultural and social capital to charge prices for their products that could sustain their operations financially. Using our model, current and aspiring farmers, service providers, and small farm advocates will be able to simulate real or hypothetical farm systems to better understand what establishing a successful small farm might require and how to confront potential challenges.
Master of Science

Impact of precision feeding with feed management software was assessed for whole farm nutrient balance (WFNB) and feeding management from January through December 2006. Nine treatment and six control farms were selected in four regions of the Chesapeake Bay Watershed of Virginia. Herd sizes averaged 271 and 390 lactating cows for treatment and control farms while milk yield averaged 30 and 27 kg/d per lactating cow, respectively. Crop hectares grown averaged 309 and 310 ha for treatment and control farms, respectively. Treatment farms purchased and installed feed management software (TMR Tracker, Digi-Star LLC, Fort Atkinson WI) between May and October 2006 and received more frequent feed analysis and feedback. Data were collected for calendar year 2005 and 2006 to compute WFNB using software from the University of Nebraska. On treatment farms, up to five feed samples were obtained monthly from individual feedstuffs and each total mixed ration (TMR) fed to lactating cows. Control farms submitted TMR samples every 2 mo. Standard wet chemistry analysis of samples was performed. Data stored in the software were collected monthly from each treatment farm concurrent with feed sampling. Producers from each treatment farm participated in a 24-question personal interview in December 2006 addressing installation, operation, and satisfaction with the software. Daily feeding deviation of all ingredients across treatment farms averaged 173 ± 163 kg/d. This corresponded to average daily overfeeding of CP and P of 17.6 ± 17 and 0.4 ± 0.3 kg/d, respectively. Feeding deviation did not differ between feeders. Milk production was negatively associated with kg total deviation and kg CP deviation, but positively related to P deviation. Whole farm nutrient balance did not differ between treatment and control farms. All producers indicated TMR Tracker met expectations. Change made to the feeding program due to TMR Tracker was correlated (r=0.80) with perceived improvement in ration consistency. In conclusion, producers perceived feed management software as beneficial, but WFNB was not reduced after 3 to 6 mo of using feed management software; however, the large variation in daily over or under feeding indicates potential for future reductions in WFNB through reduced feeding variability.
Master of Science

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Fundação de Amparo à Pesquisa do Estado de Minas Gerais
O mercado de trigo (Triticum aestivum L.) orgânico para produção de pão cresceu em grande magnitude na região da Nova Inglaterra, nos Estados Unidos. Este nicho de mercado representa uma alternativa de renda para os produtores de leite orgânico abastecerem este mercado através do cultivo e colheita de grãos em rotação de cultura na própria fazenda. Objetivou-se com este estudo determinar a sustentabilidade de oito sequências de rotação de cultura (três anos de rotação) durante o período de 25 anos em uma propriedade produtora de leite orgânica bem manejada. Uma fazenda média foi simulada utilizando o modelo computacional Integrated Farm System Model (versão 3.6) para avaliar o efeito da rotação de cultura no desempenho da cultura, impacto ambiental e rentabilidade. As estratégias de rotação incluíram pasto contínuo (azevém e trigo), milho (Zea mays L.) colhido cedo seguido de trigo de inverno (milho-trigo de inverno- pasto), milho seguido de trigo de primavera (milho-trigo de primavera-pasto), pasto em rotação com trigo de inverno (azevém/trigo - trigo de inverno - azevém/trigo), pasto em rotação com trigo de primavera (azevém/trigo - trigo de primavera - azevém/trigo), soja [Glycine max (L.) Merr.] em rotação por trigo de inverno (soja - trigo de inverno - azevém/trigo) e primavera (soja - trigo de primavera - azevém/trigo), milho em cultivo consecutivo (milho - milho - azevém/trigo) e soja seguida de milho (soja - milho - azevém/trigo). O trigo foi colhido em grão e comercializado a preço premium em todos os anos simulados. Em todas as simulações foram cultivados azevém e trigo (Lolium perenne / Trifolium pratense) consorciados no terceiro ano. Em geral, não houve benefício econômico e ambiental na rotação de cultura em comparação o pasto contínuo (monocultivo). Entretanto, entre as rotações de cultura, o cultivo de trigo de inverno deve ser incentivado, particularmente em rotação com a soja, para reduzir o impacto ambiental e aumentar rentabilidade da fazenda.
The market for high-quality organic bread wheat (Triticum aestivum L.) is increasing in New England. This economic niche represents one alternative income for organic dairy producers (if they include wheat in their crop rotation) to supply this market by raising wheat as a cash crop. Our objective was to determine the sustainability to eight crop rotation sequences of 3-yr rotations in a long-term (25-yr) well-managed organic dairy farm. A medium-sized organic dairy farm was simulated with the Integrated Farm System Model (IFSM, version 3.6) to evaluate crop rotation (management) effects on crop performance, environmental impacts and profitability. The cropping strategies included continuous ryegrass/red clover (continuous grass), corn (Zea mays L.) harvested early followed by winter wheat (corn-wwheat-grass), corn followed by spring wheat (corn-swheat-grass), ryegrass/red clover rotated with winter wheat (grass-wwheat-grass), ryegrass/red clover in rotation with spring wheat (grass-swheat-grass), soybean [Glycine max (L.) Merr.] rotated by both winter wheat (soybean-wwheat-grass) and spring wheat (soybean- swheat-grass), corn double cropped (corn-corn-grass) and soybean followed by corn (soybean- corn-grass). Wheat was harvested as a cash crop in all simulated years and sold at a premium price. All rotations were in long rotation with perennial ryegrass/red clover (Lolium perenne / Trifolium pratense) over the 3-yr. In general, there was no economic and environmental benefit to shifting land from continues grass-based production to specified cropping rotations. However, under crop rotation, use of winter wheat should be encouraged, particularly soybean replaced with cash crop wheat, to reduce environmental impact and improve farm profitability.

Agricultural runoff is the largest source of nitrogen and phosphorus pollution entering the Chesapeake Bay, contributing 38% of nitrogen and 45% of phosphorus (USEPA, 2010). Since agricultural runoff is the number one contributing source of nitrogen and phosphorus entering the Chesapeake Bay, action needs to be taken to reduce nitrogen and phosphorus on agriculture production facilities, such as dairy farms. The impact of feed management software on whole-farm nutrient balance was studied on 18 dairy farms located in Virginia from 2006 to 2010. Nine farms began using the TMR Tracker feed management software in 2006 and were compared to 9 control farms not using feed management software. Each of the treatment farms were visited on a monthly basis to collect ration and feed ingredient samples and feed management data. Whole-farm nutrient balance was calculated using University of Nebraska software. Herd sizes and crop hectares averaged 314 and 366 for treatment and 298 and 261 for control farms. Milk production averaged 3,226 and 2,650 tonnes per year respectively. Measures of surplus (input-output) and use efficiency (input/output) for nitrogen and phosphorus were analyzed over a four year time span and did not differ between treatment and control farms whether expressed on a per farms, cow or hectare basis. Due to the large variation in feeding accuracy within farms, the use of feed management software did not influence whole-farm nutrient balance. Sources of variation that contributed to loading errors were investigated within the feed management data. Percent load deviation increased over time from 2007 to 2009 from 0.94 ± 0.53 to 2.37 ± 0.50 percent of the actual load weight. Effects of month, day of the week and time of day on percent load deviation were not significant. There was no effect of percent load deviation on milk production. No relationship was observed between percent load deviation and whole-farm nutrient balance.
Master of Science

Master of Agribusiness
Department of Agricultural Economics
Jason Bergtold
The dramatic changes that have taken place in the production agriculture industry in the last decade have the Long Family Partnership wanting to reassess their farm land management strategy. As land owners, they feel as though they might be missing out on profit opportunity by continuing their current lease agreements as status quo. The objective of this research is to determine the optimal land management strategy for the Partnership farm that maximizes net returns for crop production, but also taking into account input costs and risk. Three scenarios were built: (1) a Base Case of the current share-crop and cash lease Agreements; (2) the possibility of farming their own irrigated farm land and continuing to cash lease land used to produce dryland wheat; and (3) deciding to farm all the irrigated and dry land farm acreage themselves. In order to do this, a whole-farm budget spreadsheet model was generated to assess alternative land management scenarios. The difference in net returns between alternative land rental scenarios were then compared and followed by a sensitivity analysis and stochastic analysis using @RISK software. The findings concluded that there was greater potential to increase net farm income while still conservatively managing risk by investing into their own farm land, as not only owners but also as operators. The stochastic and sensitivity analysis confirmed that farming their own land was more sensitive to changes in yields, prices and input expenses. However, even in consideration of the additional risk, the probability of increasing net farm income was greater for the scenarios in which they farmed their own land.

The objectives of this study were threefold: (1) to determine a suitable model for defining the farm-retail price spread for two percent and whole milk in seven cities (Atlanta, Boston, Chicago, Dallas, Hartford, Seattle, St. Louis); (2) to discover the determinants that contribute significantly to the price spreads of two percent and whole milk in seven selected cities, and (3) to calculate the elasticity of price transmission for whole and two percent milk in the seven cities. The work of Wohlgenant and Mullen in -Modeling the Farm-Retail Price Spread for Beef" was followed in order to determine a suitable model. The two specifications considered were the markup pricing model and the relative price spread model. Factors considered to affect the farm-to-retail price spread of whole and two percent milk were the retail price for whole and two percent milk, marketing costs such as fuel and labor costs, milk production, seasonality, and structural change. Monthly data were collected over a 106 month period from January 1994 through October 2002 for the selected cities in this investigation. Principal findings from the analysis are the following. The markup pricing model was determined to be the better model for both products throughout the seven cities through the examination of the Schwarz and Akaike criteria of model selection. The driving forces of the farm-to-retail price spread for whole and two percent milk in most cites were retail price and seasonality. In addition, the price spreads in the Northeast were significantly lower before and during the implementation of the Northeast Dairy Compact compared to the period corresponding to the termination of the program. The price spreads of both whole and two percent milk were highest in the third quarter and lowest in the fourth quarter. Elasticities of price transmission, measures of the sensitivity of retail prices to changes in farm prices, were higher in all regions for two percent milk compared to whole milk. The range of the elasticities of transmission for whole milk was from 0.37 (Hartford) to 2.54 (Dallas) and from 0.39 (Hartford) to 3.66 (Dallas) for two percent milk.

A decision support system for preventive integrated pest management (IPM) and nonpoint source (NPS) pollution control was designed, implemented and evaluated. The objective of the system was to generate plans at the farm level to satisfy economic and production goals while limiting risks of insect pest outbreaks, nitrate and pesticide leaching and runoff, and soil erosion. The system is composed of a constraint satisfaction planner (CROPS-LT), a modified version of CROPS (Stone, 1995), a farm-level resource management system (FLAME), an NPS module, which includes a weather generator, CLIGEN (Nicks et al. 1995), and an NPS distributed-parameter model, ANSWERS (Bouraoui, 1994), databases, a database engine and utility programs. The performance of the system was analyzed and performance enhancing features were added to increase the planner's ability to find near-optimal plans within a limited planning time. Using heuristics to sort potential crop rotations based on profit generally improved the planner's performance, as did removal of fields that were not suitable for growing target crops. Not surprisingly, the planner was best able to find plans for crops that can be grown in a variety of rotational systems. Throughout, the ability to apply environmental constraints selectively to individual fields greatly improved the planner's ability to find acceptable plans. Preventive IPM (PIPM) heuristics to control corn rootworms CRW (Diabrotica virgifera virgifera and D. barberi) were added to the planner. The model was represented and solved as a constraint satisfaction problem. Results indicated that plans obtained using PIPM heuristics had less risk of CRW damage, reduced chemical control costs, higher profit and reduced soil erosion as compared to a control plan. Linking the planner to the NPS model in a feedback control loop improved the planner's ability to reduce soil losses while preserving economic and production goals.
Ph. D.

Methods for on-farm extraction of low-concentration (minor) proteins from raw whole bovine milk directly after milking were explored. These minor proteins have high commercial value. Lactoferrin (LF) and lactoperoxidase (LP) were used as model proteins for extraction using cation exchange chromatography. Laboratory fractionations showed that milk could be processed by conventional column chromatography without excessive column backpressures if resin with large particles sizes were used and the temperature was high enough so fat in the milk was malleable; ideally the milk should be near the secretion temperature of 37oC. Processing parameters such as equilibrium and dynamic capacities were determined for SP Sepharose ™ (GE Healthcare Technologies) and Bio Rex 70 (BioRad Laboratories) resins. SP Sepharose Big Beads (SP BB) were found to be more suitable than BR 70, for raw whole milk processing due to the larger size (200 um). Design considerations showed that column chromatography was not the most practical method for on-farm processing of fresh, raw whole milk. Trials with a single-stage stirred tank showed that SP BB resin could extract up to 65% of LF (initial LF concentration of 0.5 mg/mL) with a 10-minute adsorption time. The composite non-linear (CNL) model of Rowe et al. (1999) was used to describe LF uptake by SP BB resin in raw whole milk with initial LF concentrations of 0 to 1.0 mg/mL and resin:milk volume ratios of 0.010, 0.012, 0.017 and 0.024 over 45-minute contact times. The CNL model could be used to predict LF yields if initial feed concentration, milk and resin volumes, and contact times were known. Laboratory extractions showed that processing did not significantly affect bulk milk composition (fat, protein, lactose and total solids), indicating that the milk could be used for conventional processing after the minor proteins had been extracted. Resin cleaning and regeneration studies, using a procedure similar to that recommended by the resin supplier, showed that the Sepharose resin had not degraded and there was no significant decrease in binding capacity after 50 extraction cycles. A Protein Fractionation Robot (PFR) prototype based on a single-stage stirred tank and the operating parameters obtained from the laboratory trials was designed, assembled and coupled to an Automated Milking System (AMS) to process fresh, raw whole milk from individual cows immediately after milking. The LF and LP extracted from the milk from 16 individual cows were 19.7 - 55.2% (35.6 10.2%) and 21.2 - 99.5% (87.1 12.0%) respectively. Generally, higher extraction levels were obtained at higher resin:milk ratios. The amount of LF extracted on-farm agreed within 14.1 9.8% of those predicted by the CNL model, with predicted values generally being higher. The experimental on-farm adsorption values were calculated using data of LF recovered after elution, so differences between actual and predicted values may be due to losses during post-adsorption processing. Economic feasibility studies, based on experimental data from the PFR and realistic wholesale prices for LF and LP ($400 and $150/kg respectively) showed that PFR-based processing is economically viable if the farmer is paid for the LF and LP produced as well as the bulk milk. This system would have a payback period of approximately five years and an internal rate of return of 14.5%. Further case studies determined the sensitivity of the economics to various operating parameters and value/cost assumptions, including producing recombinant human protein from transgenic bovine milk. These studies showed that the higher the value of the processed raw milk, the higher the absorptive capacity of the resin, and the higher the value of the extracted protein, the more favourable the economics. In the extreme case of producing a very high value therapeutic protein (e.g. $20 000), the payback period could be as low as 0.3 years, with an internal rate of return of 818%.

Precision Agriculture (PA) strives towards holistic production and environmental management. A fundamental research challenge is the continuous expansion of ideas about how PA can contribute to sustainable agriculture. Some associated pragmatic research challenges include quantification of spatio-temporal variation of crop yield; crop growth simulation modelling within a PA context and; evaluating long-term financial and environmental outcomes from site-specific crop management (SSCM). In Chapter 1 literature about managing whole farms with a mind towards sustainability was reviewed. Alternative agricultural systems and concepts including systems thinking, agro-ecology, mosaic farming and PA were investigated. With respect to environmental outcomes it was found that PA research is relatively immature. There is scope to thoroughly evaluate PA from a long-term, whole-farm environmental and financial perspective. Comparatively, the emphasis of PA research on managing spatial variability offers promising and innovative ways forward, particularly in terms of designing new farming systems. It was found that using crop growth simulation modelling in a PA context is potentially very useful. Modelling high-resolution spatial and temporal variability with current simulation models poses a number of immediate research issues. This research focused on three whole farms located in Australia that grow predominantly grains without irrigation. These study sites represent three important grain growing regions within Australia. These are northern NSW, north-east Victoria and South Australia. Note-worthy environmental and climatic differences between these regions such as rainfall timing, soil type and topographic features were outlined in Chapter 2. When considering adoption of SSCM, it is essential to understand the impact of temporal variation on the potential value of managing spatial variation. Quantifying spatiotemporal variation of crop yield serves this purpose; however, this is a conceptually and practically challenging undertaking. A small number of previous studies have found that the magnitude of temporal variation far exceeds that of spatial variation. Chapter 3 of this thesis dealt with existing and new approaches quantifying the relationship between spatial and temporal variability in crop yield. It was found that using pseudo cross variography to obtain spatial and temporal variation ‘equivalents’ is a promising approach to quantitatively comparing spatial and temporal variation. The results from this research indicate that more data in the temporal dimension is required to enable thorough analysis using this approach. This is particularly relevant when questioning the suitability of SSCM. Crop growth simulation modelling offers PA a number of benefits such as the ability to simulate a considerable volume of data in the temporal dimension. A dominant challenge recognised within the PA/modelling literature is the mismatch between the spatial resolution of point-based model output (and therefore input) and the spatial resolution of information demanded by PA. This culminates into questions about the conceptual model underpinning the simulation model and the practicality of using point-based models to simulate spatial variability. iii The ability of point-based models to simulate appropriate spatial and temporal variability of crop yield and the importance of soil available water capacity (AWC) for these simulations were investigated in Chapter 4. The results indicated that simulated spatial variation is low compared to some previously reported spatial variability of real yield data for some climate years. It was found that the structure of spatial yield variation was directly related to the structure of the AWC and interactions between AWC and climate. It is apparent that varying AWC spatially is a reasonable starting point for modelling spatial variation of crop yield. A trade-off between capturing adequate spatio-temporal variation of crop yield and the inclusion of realistically obtainable model inputs is identified. A number of practical solutions to model parameterisation for PA purposes are identified in the literature. A popular approach is to minimise the number of simulations required. Another approach that enables modelling at every desired point across a study area involves taking advantage of high-resolution yield information from a number of years to estimate site-specific soil properties with the inverse use of a crop growth simulation model. Inverse meta-modelling was undertaken in Chapter 5 to estimate AWC on 10- metre grids across each of the study farms. This proved to be an efficient approach to obtaining high-resolution AWC information at the spatial extent of whole farms. The AWC estimates proved useful for yield prediction using simple linear regression as opposed to application within a complex crop growth simulation model. The ability of point-based models to simulate spatial variation was re-visited in Chapter 6 with respect to the exclusion of lateral water movement. The addition of a topographic component into the simple point-based yield prediction models substantially improved yield predictions. The value of these additions was interpreted using coefficients of determination and comparing variograms for each of the yield prediction components. A result consistent with the preceding chapter is the importance of further validating the yield prediction models with further yield data when it becomes available. Finally, some whole-farm management scenarios using SSCM were synthesised in Chapter 7. A framework that enables evaluation of the long-term (50 years) farm outcomes soil carbon sequestration, nitrogen leaching and crop yield was established. The suitability of SSCM across whole-farms over the long term was investigated and it was found that the suitability of SSCM is confined to certain fields. This analysis also enabled identification of parts of the farms that are the least financially and environmentally viable. SSCM in conjunction with other PA management strategies is identified as a promising approach to long-term and whole-farm integrated management.

Doctor of Philosophy
Precision Agriculture (PA) strives towards holistic production and environmental management. A fundamental research challenge is the continuous expansion of ideas about how PA can contribute to sustainable agriculture. Some associated pragmatic research challenges include quantification of spatio-temporal variation of crop yield; crop growth simulation modelling within a PA context and; evaluating long-term financial and environmental outcomes from site-specific crop management (SSCM). In Chapter 1 literature about managing whole farms with a mind towards sustainability was reviewed. Alternative agricultural systems and concepts including systems thinking, agro-ecology, mosaic farming and PA were investigated. With respect to environmental outcomes it was found that PA research is relatively immature. There is scope to thoroughly evaluate PA from a long-term, whole-farm environmental and financial perspective. Comparatively, the emphasis of PA research on managing spatial variability offers promising and innovative ways forward, particularly in terms of designing new farming systems. It was found that using crop growth simulation modelling in a PA context is potentially very useful. Modelling high-resolution spatial and temporal variability with current simulation models poses a number of immediate research issues. This research focused on three whole farms located in Australia that grow predominantly grains without irrigation. These study sites represent three important grain growing regions within Australia. These are northern NSW, north-east Victoria and South Australia. Note-worthy environmental and climatic differences between these regions such as rainfall timing, soil type and topographic features were outlined in Chapter 2. When considering adoption of SSCM, it is essential to understand the impact of temporal variation on the potential value of managing spatial variation. Quantifying spatiotemporal variation of crop yield serves this purpose; however, this is a conceptually and practically challenging undertaking. A small number of previous studies have found that the magnitude of temporal variation far exceeds that of spatial variation. Chapter 3 of this thesis dealt with existing and new approaches quantifying the relationship between spatial and temporal variability in crop yield. It was found that using pseudo cross variography to obtain spatial and temporal variation ‘equivalents’ is a promising approach to quantitatively comparing spatial and temporal variation. The results from this research indicate that more data in the temporal dimension is required to enable thorough analysis using this approach. This is particularly relevant when questioning the suitability of SSCM. Crop growth simulation modelling offers PA a number of benefits such as the ability to simulate a considerable volume of data in the temporal dimension. A dominant challenge recognised within the PA/modelling literature is the mismatch between the spatial resolution of point-based model output (and therefore input) and the spatial resolution of information demanded by PA. This culminates into questions about the conceptual model underpinning the simulation model and the practicality of using point-based models to simulate spatial variability. iii The ability of point-based models to simulate appropriate spatial and temporal variability of crop yield and the importance of soil available water capacity (AWC) for these simulations were investigated in Chapter 4. The results indicated that simulated spatial variation is low compared to some previously reported spatial variability of real yield data for some climate years. It was found that the structure of spatial yield variation was directly related to the structure of the AWC and interactions between AWC and climate. It is apparent that varying AWC spatially is a reasonable starting point for modelling spatial variation of crop yield. A trade-off between capturing adequate spatio-temporal variation of crop yield and the inclusion of realistically obtainable model inputs is identified. A number of practical solutions to model parameterisation for PA purposes are identified in the literature. A popular approach is to minimise the number of simulations required. Another approach that enables modelling at every desired point across a study area involves taking advantage of high-resolution yield information from a number of years to estimate site-specific soil properties with the inverse use of a crop growth simulation model. Inverse meta-modelling was undertaken in Chapter 5 to estimate AWC on 10- metre grids across each of the study farms. This proved to be an efficient approach to obtaining high-resolution AWC information at the spatial extent of whole farms. The AWC estimates proved useful for yield prediction using simple linear regression as opposed to application within a complex crop growth simulation model. The ability of point-based models to simulate spatial variation was re-visited in Chapter 6 with respect to the exclusion of lateral water movement. The addition of a topographic component into the simple point-based yield prediction models substantially improved yield predictions. The value of these additions was interpreted using coefficients of determination and comparing variograms for each of the yield prediction components. A result consistent with the preceding chapter is the importance of further validating the yield prediction models with further yield data when it becomes available. Finally, some whole-farm management scenarios using SSCM were synthesised in Chapter 7. A framework that enables evaluation of the long-term (50 years) farm outcomes soil carbon sequestration, nitrogen leaching and crop yield was established. The suitability of SSCM across whole-farms over the long term was investigated and it was found that the suitability of SSCM is confined to certain fields. This analysis also enabled identification of parts of the farms that are the least financially and environmentally viable. SSCM in conjunction with other PA management strategies is identified as a promising approach to long-term and whole-farm integrated management.

Thesis (M.S.)--University of Kentucky, 2008.
Title from document title page (viewed on November 3, 2008). Document formatted into pages; contains: ix, 58 p. : ill. (some col.). Includes abstract and vita. Includes bibliographical references (p. 55-57).

The thesis presented consists of two essays that analyze input substitution and decision making in crop and livestock production systems. The first essay consists of a whole-farm analysis that sought to optimize feed mixes and enterprise combinations for an organic dairy operation in the Southeastern United States. This was accomplished through mathematical programming where whole-farm net returns were maximized, and total feed costs were minimized simultaneously for four milk production level cases. Additionally, the sensitivity of the system and break-even milk price were explored. Results suggest substitutability in ration components where an increase in supplemental feeds is justified by additional milk output and sales. The second essay utilizes econometric methods and hedonic modeling to explore factors that drive the price of row crop planters on the used machinery market. Factors relating to make, age, condition, planter specifications, sale type, spatial aspects, seasonality, and year of the sale were analyzed. Results suggest non-linear relationships for row number and age relative to price and interactions between variables make and age that imply varying depreciation depending on the manufacturer. An additional break-even analysis relating to pasture yields and planter purchase price was conducted to explore these primary concepts in further detail.

Calls for increased farmer involvement in research and extension programs have been numerous and well supported. One approach to integrate the collective knowledge and experience of agricultural scientists and farmers is through whole farm case studies (WFCS). An interdisciplinary team of 34 research and extension personnel at Oregon and Washington State Universities conducted WFCS of 16 vegetable and small fruit farms beginning in April 1989. The objectives of the Oregon/Washington case study project were to: (1) increase farmer involvement in research and education programs; (2) develop an interdisciplinary team to address issues of agricultural sustainability in western Oregon and Washington; (3) examine the use of the case study approach in agricultural situations; (4) prepare a guide to assist other persons interested in conducting WFCS; (5) develop a better understanding of vegetable and small fruit farming systems in the region; and, (6) identify sustainable agriculture research and education needs in western Oregon and Washington. The WFCS process proved useful in developing an interdisciplinary team, and the vast majority of team members participating in the study stated they would consider using the WFCS approach again in their work. However, the primary constraint cited by all team members was the amount of time required to conduct the study. The process of conducting WFCS in western Oregon and Washington improved communication among a wide group of people. Team members gained a better understanding of the complexity of farms and identified several areas requiring further research. Farmers stated they enjoyed participating in the case study project and discovered new information that will assist them in managing their farming systems. Farmer-developed innovations were identified that are useful to other farmers and to the research process. Included in this thesis are: (1) a guide for conducting whole farm case studies; (2) a summary of data collected from 16 farms in western Oregon and Washington participating in the WFCS, including a summary of interaction among interdisciplinary team members; and, (3) a profile of one of the farms participating in the WFCS.
Graduation date: 1994

Whole farm nutrient budgets (WFNB) enable producers to link dairy herd management with traditional field nutrient management plans. The objective of this study was to calculate WFNBs of nitrogen, phosphorus, and potassium (N, P, and K) at a commercial farm in New Brunswick and in Prince Edward Island. Reliable estimates of N fixation from alfalfa and red clover on the farms were obtained with adjustments to the Høgh-Jensen et al. (2004) dry matter conversion models. The farms had surpluses of N, P, and K. Both farms imported feed as well as nutrient inputs for crop production. Surpluses of all nutrients were typical in comparison to WFNBs of similar dairy farms; however, the nutrient use efficiencies were low. The imported manure and fertilizer used in the crop production components contributed to surpluses of N and P which could likely be reduced to improve overall farm nutrient use efficiency.

Thesis (M.S.)--University of Wisconsin--Madison, 1997.
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Animal agriculture plays a vital role in the provision of food for the world population; however, in the wake of global warming and greenhouse gas (GHG) emissions, the industry has been under scrutiny as one of the net emitters causing global warming. The same scrutiny applies to beef production in western Canada. The objective of this study is to evaluate the economic impact of GHG mitigation practices (GHGMP) for beef operations, and in the process identify economic and environmental sustainable scenarios. This study was an extension to a study by Beauchemin et al (2011) who studied the mitigation of GHG emissions from beef production in western Canada A beef simulation model was developed to measure the impacts of adopting GHGMPs on the profitability of a mixed farm in Vulcan County, Southern Alberta. Feed for the herd was produced on the farm, and calves were born and finished on the farm. Whole farm gross margin was used as a profitability measure of the farm over a period of 9 years, which is a full beef production cycle. Eleven GHGMPs were examined and compared to the baseline scenario. These scenarios were adopted from Beauchemin et al (2011), and included dietary modifications (change in use of forages, use of canola seed, and corn distillers grains, and improvement in quality of forage), and improvement in animal husbandry (increased weaning rates, and increased longevity of breeding stock). Simulation results showed a discounted whole farm gross margin of $11.38 per acre for the baseline scenario. Feed costs accounted for 47.1 percent of total costs of beef production. The change in whole farm gross margin per acre from implementation of different GHGMPs ranged from an increase of 4 percent to a decrease of 5 percent. Six scenarios were identified as ‘win-win’ scenarios as they improved both environment and economics of the farm. The profit of these scenarios ranged from $238.11 to $30.31 per tonne of GHG reductions expressed in carbon dioxide equivalent). The loss from the other scenarios capable of reducing GHG emissions range from $92.06 to $582.46 per tonne GHG reduced. Based on these results, it was concluded that western Canadian beef producers can adopt sustainable GHGMPs without substantial changing the structure of their operations. Scenarios that improved both the environment and the economics of the farm were: Scenario 7: use of corn distillers dried grain (CDDG) in finishing ration; Scenario 4: use of canola seed in finishing ration; Scenario 8: use of CDDG in breeding stock ration; Scenario 10: increased calve weaning rate (85% to 90%); Scenario 5: use of canola seed in breeding stock ration; and Scenario 9 : improved hay for breeding stock.

Methoden zur genomischen Vorhersage basierend auf Genotypinformationen von Single Nucleotide Polymorphism (SNP)-Arrays mit unterschiedlicher Markeranzahl sind mittlerweile in vielen Zuchtprogrammen für Nutztiere fest implementiert. Mit der zunehmenden Verfügbarkeit von vollständigen Genomsequenzdaten, die auch kausale Mutationen enthalten, werden mehr und mehr Studien veröffentlicht, bei denen genomische Vorhersagen beruhend auf Sequenzdaten durchgeführt werden. Das Hauptziel dieser Arbeit war zu untersuchen, inwieweit SNP-Array-Daten mit statistischen Verfahren bis zum Sequenzlevel ergänzt werden können (sogenanntes „Imputing“) (Kapitel 2) und ob die genomische Vorhersage mit imputeten Sequenzdaten und zusätzlicher Information über die genetische Architektur eines Merkmals verbessert werden kann (Kapitel 3). Um die Genauigkeit der genomischen Vorhersage besser verstehen und eine neue Methode zur Approximation dieser Genauigkeit ableiten zu können, wurde außerdem eine Simulationsstudie durchgeführt, die den Grad der Überschätzung der Genauigkeit der genomischen Vorhersage verschiedener bereits bekannter Ansätze überprüfte (Kapitel 4). Der technische Fortschritt im letzten Jahrzehnt hat es ermöglicht, in relativ kurzer Zeit Millionen von DNA-Abschnitten zu sequenzieren. Mehrere auf unterschiedlichen Algorithmen basierende Software-Programme zur Auffindung von Sequenzvarianten (sogenanntes „Variant Calling“) haben sich etabliert und es möglich gemacht, SNPs in den vollständigen Genomsequenzdaten zu detektieren detektieren. Oft werden nur wenige Individuen einer Population vollständig sequenziert und die Genotypen der anderen Individuen, die mit einem SNP-Array an einer Teilmenge dieser SNPs typisiert wurden, imputet. In Kapitel 2 wurden deshalb anhand von 50 vollständig sequenzierten Weiß- und Braunleger-Individuen die mit drei unterschiedlichen Variant-Calling-Programmen (GATK, freebayes and SAMtools) detektierten Genomvarianten verglichen und die Qualität der Genotypen überprüft. Auf den untersuchten Chromosomen 3,6 und 26 wurden 1.741.573 SNPs von allen drei Variant Callers detektiert was 71,6% (81,6%, 88,0%) der Anzahl der von GATK (SAMtools, freebayes) detektierten Varianten entspricht. Die Kenngröße der Konkordanz der Genotypen („genotype concordance“), die durch den Anteil der Individuen definiert ist, deren Array-basierte Genotypen mit den Sequenz-basierten Genotypen an allen auch auf dem Array vorhandenen SNPs übereinstimmt, betrug 0,98 mit GATK, 0,98 mit SAMtools und 0,97 mit freebayes (Werte gemittelt über SNPs auf den untersuchten Chromosomen). Des Weiteren wiesen bei Nutzung von GATK (SAMtools, freebayes) 90% (88 %, 75%) der Varianten hohe Werte (>0.9) anderer Qualitätsmaße (non-reference sensitivity, non-reference genotype concordance und precision) auf. Die Leistung aller untersuchten Variant-Calling-Programme war im Allgemeinen sehr gut, besonders die von GATK und SAMtools. In dieser Studie wurde außerdem in einem Datensatz von ungefähr 1000 Individuen aus 6 Generationen die Güte des Imputings von einem hochdichten SNP-Array zum Sequenzlevel untersucht. Die Güte des Imputings wurde mit Hilfe der Korrelationen zwischen imputeten und wahren Genotypen pro SNP oder pro Individuum und der Anzahl an Mendelschen Konflikten bei Vater-Nachkommen-Paaren beschrieben. Drei unterschiedliche Imputing-Programme (Minimac, FImpute und IMPUTE2) wurden in unterschiedlichen Szenarien validiert. Bei allen Imputing-Programmen betrug die Korrelation zwischen wahren und imputeten Genotypen bei 1000 Array-SNPs, die zufällig ausgewählt und deren Genotypen im Imputing-Prozess als unbekannt angenommen wurden, durchschnittlich mehr als 0.95 sowie mehr als 0.85 bei einer Leave-One-Out-Kreuzvalidierung, die mit den sequenzierten Individuen durchgeführt wurde. Hinsichtlich der Genotypenkorrelation zeigten Minimac und IMPUTE2 etwas bessere Ergebnisse als FImpute. Dies galt besonders für SNPs mit niedriger Frequenz des selteneren Allels. FImpute wies jedoch die kleinste Anzahl von Mendelschen Konflikten in verfügbaren Vater-Nachkommen-Paaren auf. Die Korrelation zwischen wahren und imputeten Genotypen blieb auf hohem Niveau, auch wenn die Individuen, deren Genotypen imputet wurden, einige Generationen jünger waren als die sequenzierten Individuen. Zusammenfassend zeigte in dieser Studie GATK die beste Leistung unter den getesteten Variant-Calling-Programmen, während Minimac sich unter den untersuchten Imputing-Programmen als das beste erwies. Aufbauend auf den Ergebnissen aus Kapitel 2 wurden in Kapitel 3 Studien zur genomischen Vorhersage mit imputeten Sequenzdaten durchgeführt. Daten von 892 Individuen aus 6 Generationen einer kommerziellen Braunlegerlinie standen hierfür zur Verfügung. Diese Tiere waren alle mit einem hochdichten SNP-Array genotypisiert. Unter der Nutzung der Daten von 25 vollständig sequenzierten Individuen wurden jene Tiere ausgehend von den Array-Genotypen bis zum Sequenzlevel hin imputet. Das Imputing wurde mit Minimac3 durchgeführt, das bereits haplotypisierte Daten (in dieser Studie mit Beagle4 erzeugt) als Input benötigt. Die Genauigkeit der genomischen Vorhersage wurde durch die Korrelation zwischen de-regressierten konventionellen Zuchtwerten und direkt genomischen Zuchtwerten für die Merkmale Bruchfestigkeit, Futteraufnahme und Legerate gemessen. Neben dem Vergleich der Genauigkeit der auf SNP-Array-Daten und Sequenzdaten basierenden genomischen Vorhersage wurde in dieser Studie auch untersucht, wie sich die Verwendung verschiedener genomischer Verwandtschaftsmatrizen, die die genetische Architektur berücksichtigen, auf die Vorhersagegenauigkeit auswirkt. Hierbei wurden neben dem Basisszenario mit gleichgewichteten SNPs auch Szenarien mit Gewichtungsfaktoren, nämlich den -(〖log〗_10 P)-Werten eines t-Tests basierend auf einer genomweiten Assoziationsstudie und den quadrierten geschätzten SNP-Effekten aus einem Random Regression-BLUP-Modell, sowie die Methode BLUP|GA („best linear unbiased prediction given genetic architecture“) überprüft. Das Szenario GBLUP mit gleichgewichteten SNPs wurde sowohl mit einer Verwandtschaftsmatrix aus allen verfügbaren SNPs oder nur derer in Genregionen, jeweils ausgehend von der Grundmenge aller imputeten SNPs in der Sequenz oder der Array-SNPs, getestet. Gemittelt über alle untersuchten Merkmale war die Vorhersagegenauigkeit mit SNPs aus Genregionen, die aus den imputeten Sequenzdaten extrahiert wurden, mit 0,366 ± 0,075 am höchsten. Den zweithöchsten Wert erreichte die genomische Vorhersage mit SNPs aus Genregionen, die im SNP-Array erhalten sind (0,361 ± 0,072). Weder die Verwendung gewichteter genomischer Verwandtschaftsmatrizen noch die Anwendung von BLUP|GA führten im Vergleich zum normalen GBLUP-Ansatz zu höheren Vorhersagegenauigkeiten. Diese Beobachtung war unabhängig davon, ob SNP-Array- oder imputete Sequenzdaten verwendet wurden. Die Ergebnisse dieser Studie zeigten, dass kaum oder kein Zusatznutzen durch die Verwendung von imputeten Sequenzdaten generiert werden kann. Eine Erhöhung der Vorhersagegenauigkeit konnte jedoch erreicht werden, wenn die Verwandschaftsmatrix nur aus den SNPs in Genregionen gebildet wurde, die aus den Sequenzdaten extrahiert wurden. Die Auswahl der Selektionskandidaten erfolgt in genomischen Selektionsprogrammen mit Hilfe der geschätzten genomischen Zuchtwerte (GBVs). Die Genauigkeit des GBV ist hierbei ein relevanter Parameter, weil sie die Stabilität der geschätzten Zuchtwerte beschreibt und zeigen kann, wie sich der GBV verändern kann, wenn mehr Informationen verfügbar werden. Des Weiteren ist sie einer der entscheidenden Faktoren beim erwarteten Zuchtfortschritt (auch als so genannte „Züchtergleichung“ beschrieben). Diese Genauigkeit der genomischen Vorhersage ist jedoch in realen Daten schwer zu quantifizieren, da die wahren Zuchtwerte (TBV) nicht verfügbar sind. In früheren Studien wurden mehrere Methoden vorgeschlagen, die es ermöglichen, die Genauigkeit von GBV durch Populations- und Merkmalsparameter (z.B. effektive Populationsgröße, Sicherheit der verwendeten Quasi-Phänotypen, Anzahl der unabhängigen Chromosomen-Segmente) zu approximieren. Weiterhin kann die Genauigkeit bei Verwendung von gemischten Modellen mit Hilfe der Varianz des Vorhersagefehlers abgeleitet werden. In der Praxis wiesen die meisten dieser Ansätze eine Überschätzung der Genauigkeit der Vorhersage auf. Deshalb wurden in Kapitel 4 mehrere methodische Ansätze aus früheren Arbeiten in simulierten Daten mit unterschiedlichen Parametern, mit Hilfe derer verschiedene Tierzuchtprogramme (neben einem Basisszenario ein Rinder- und ein Schweinezuchtschema) abgebildet wurden, überprüft und die Höhe der Überschätzung gemessen. Außerdem wurde in diesem Kapitel eine neue und leicht rechenbare Methode zur Approximation der Genauigkeit vorgestellt Die Ergebnisse des Vergleichs der methodischen Ansätze in Kapitel 4 zeigten, dass die Genauigkeit der GBV durch den neuen Ansatz besser vorhergesagt werden kann. Der vorgestellte Ansatz besitzt immer noch einen unbekannten Parameter, für den jedoch eine Approximation möglich ist, wenn in einem geeigneten Datensatz Ergebnisse von Zuchtwertschätzungen zu zwei verschiedenen Zeitpunkten vorliegen. Zusammenfassend kann gesagt werden, dass diese neue Methode die Approximation der Genauigkeit des GBV in vielen Fällen verbessert.

Advances in farming technology, and the variety of modern agricultural practices, have the potential to reduce, maintain or improve biodiversity in an agricultural landscape. Environmentally sensitive farming systems are becoming more important on a local level, as climate change, declining biodiversity and habitat fragmentation impact the environment at a landscape scale. Invertebrates are important components of an agricultural landscape, playing numerous roles including pest control, plant protection, pollination, and carbon cycling. They are also an important food source for many reptiles, birds, mammals and other insects, making them a key component of the food chain. Ants in particular are useful tools in biodiversity monitoring as they are abundant in both disturbed and intact habitats, and their many functional groups help to illustrate their community structure at a given point in time. For these reasons, they can be used to demonstrate the short and long term impacts of land management in various environments, including rehabilitated mine sites, fire affected regions, and agricultural landscapes. Conducted on working farms, this study looked specifically at insect in the agricultural landscape, using 10 sheep pastures which have been restored with eucalypt plantings. Looking at species richness, relative abundance, and community structure, this study assessed the ant and beetle communities in these plantings and compares these to pasture control sites and nearby remnant woodland patch control sites. The influences of elevation, ground cover, soil clay, patch size, and age of planting were tested using regression analyses. It was found that leaf litter cover and weediness have a significant influence on invertebrate recolonisation of a restoration planting. Elevation was negatively correlated for all ant activity, whilst the age of the planting was positively correlated with ant abundance and species richness. This study shows that ants can be useful monitoring tools in agricultural landscapes, and specifically useful when assessing the effectiveness of on-farm restoration plantings. It also provides a better understanding of the influence of environmental variables on a restoration planting, which in turn can help inform land management decisions.

The increasing demand for aquaculture products globally is leading to greater demand for coastal marine farm space, intensification within existing aquaculture areas, and conversion of production to high value species, especially finfish. Among the many environmental interactions that arise with finfish aquaculture development, one of the most dramatic impacts is local-scale organic enrichment of the benthic ecosystem due to deposition of fish faeces and uneaten feed. A benthic impact is typically evident as severe organic enrichment beneath finfish cages (e.g. species-poor, near-azoic conditions), with a gradient of decreasing enrichment extending to background conditions across scales of tens to hundreds of metres distant from cages. The overall hypothesis of this thesis was that seabed organic enrichment (degradation and recovery) can be accurately and quantitatively determined using biological and physicochemical variables that can be applied across geographic regions and contrasting environments. This was accompanied by an objective to refine knowledge of processes underpinning benthic enrichment, and to develop or refine tools for the prediction, monitoring and management of enrichment effects associated with fish aquaculture. The thesis comprises six sequential, related chapters that address: site- and region-specific ecological characterisation of benthic communities and the development on a new environmental indicator variable; comparisons of existing biological indicators and indices in different hydrodynamic regimes; application and validation of a depositional model for predicting effects under very different environmental conditions; and a detailed analysis of long-term and medium-term recovery from highly enriched states, and consideration of re-impact rates and implications for farm management strategies. The analyses are based on both targeted recent studies as well as longer-term monitoring undertaken at six salmon farms situated in the Marlborough Sounds, New Zealand; four of which are situated in low flow environments, and two are situated in high flow (dispersive) environments. Characterising the differences associated with the sites’ dispersive properties is a theme that runs throughout this study. Chapter 2 used best professional judgement methods to develop a quantitative benthic enrichment index termed ‘enrichment stage’, which unifies information from biological and physico-chemical variables. The resulting seven stage bounded continuous variable was used to assign enrichment tolerance groups to benthic taxa using quantile regression splines. A number of key indicator taxa were discriminated along the enrichment gradient, including several that were responsive to low-level changes in enrichment stage (ES), but not necessarily organic matter (%OM), and 10 taxa for which ecological understanding was previously limited. In Chapter 3, the gradient was also used to evaluate the performance of five benthic indicators and ten biotic indices for defining organic enrichment under different flow regimes. A subset of variables was recommended comprising: two biotic indices, total abundance, and a geochemical variable. A subsequent but related study in Chapter 4 revealed pronounced flowrelated differences in the magnitude and spatial extent of benthic enrichment. Total macrofaunal abundances at high-flow sites were nearly an order of magnitude greater than at comparable low flow sites, representing a significant benthic biomass, and occurred in conjunction with moderate-to-high species richness and the absence of appreciable organic accumulation. The atypical ecological conditions associated with high-flow sites were attributed to i) minimal accumulation of fine sediments, ii) maintenance of aerobic conditions in near-surface sediments, and iii) an abundant food supply. Chapter 5 explored the relationship between predicted depositional flux (using DEPOMOD) and enrichment stage, calculated using the methods developed in the previous chapters (1 to 3). Observed impacts at farms with contrasting flow regimes were examined to evaluate the role of modelled resuspension dynamics in determining impacts. When resuspension was included in the model, net particle export was predicted at the most dispersive sites. However, significant seabed effects were observed, suggesting that although the model outputs were theoretically plausible they were inconsistent with the observational data. When the model was run without resuspension the results were consistent with the field survey data. This retrospective validation suggested that approximately twice the flux was needed to induce an effect level at the dispersive sites equivalent to that at the nondispersive sites. Flux estimates are provided for detectable enrichment and highly enriched states. This study shows that the association between current flow, sediment resuspension and ecological impacts is more complex than presently encapsulated within DEPOMOD and emphasises the need for validation of such models, particularly at dispersive sites. The final two data chapters (Chapters 6 and 7) examine the spatial and temporal recovery processes that take place following a highly enriched state. Chapter 6 provides a comprehensive analysis of a long-term (8 year) dataset in relation to a variety of proposed recovery and remediation definitions. Many challenges associated with quantifying the endpoint of ‘recovery’ were identified. The concept of dynamic and spatial equilibria proved to be valid in this situation, and alternate state theories may apply. In combination with visualisation of plotted data, statistical tests for parallelism in temporal trajectories of cage and reference sites proved to be an effective method for characterising recovery, but the method was highly sensitive to window time-length. Simple, univariate indicators of enrichment tended to be less sensitive, and indicate recovery earlier, than more complex multivariate indicators. Recovery was assessed to be complete after approximately five years, but there was some evidence of on-going instability in the composition of the macrofauna, which was partly attributed to spatial and temporal processes and patterning in the macrobenthos. The last data chapter (Chapter 7) examined shorter-term recovery and re-impact patterns and revealed some interesting successional patterns in time and space, especially between %OM, TFS and abundances of opportunistic taxa. The discussion brings together findings from the targeted and long-term studies to reveal alternate oscillations between sediment chemistry and biological response, which have temporally distinct signals. It is proposed that the large oscillations that occur in the early stages of recovery represent the extreme end of the environmental instability that occurs as a result of a severe perturbation (in this case, cessation of extreme enrichment) that abates through time as recovery ensues. This integrated study has a number of important implications for the management of organic enrichment in general but is especially pertinent for fish farming. In particular, recommendations are made regarding the i) adequacy of chemical and biological benthic indicators and their performance in typical non-dispersive and atypical dispersive sites; ii) use and applicability of depositional models in the same environments with emphasis on the role of resuspension, and iii) timing and approach for reintroduction of impacts, with respect to monitoring and management of rotational fallowing strategies to ensure on-going sustainability.