Development of a Welfare-Cost-Output Feedback Framework for Intensive Livestock Systems

Thesis Abstract

There is a critical need to integrate welfare, economic costs, and production outputs within intensive livestock systems to guide ethically informed and economically viable decision making under rapidly changing market and regulatory conditions. The study aims to develop a Welfare-Cost-Output Feedback Framework (WCOFF) that models dynamic interactions among animal welfare indicators, production economics, and management costs to optimize overall system performance. Specific objectives are (1) to identify and validate a core set of welfare indicators (behavioral, physiological, and health metrics) that are predictive of production efficiency; (2) to quantify direct and indirect costs associated with welfare-related interventions and their impact on output metrics such as feed conversion ratio, daily weight gain, and carcass yield; (3) to formulate a systems-based feedback mechanism linking welfare status to production decisions and cost structures; (4) to test the framework across diverse species (broiler chickens, lactating dairy cattle, and finishing pigs) and housing conditions (battery, free-range, and enriched environments); and (5) to develop decision-support tools for farmers and policymakers grounded in the framework. The methodology adopts a mixed-methods, explanatory sequential design conducted in three phases. Phase I entails a cross-sectional survey of 60 commercial poultry houses, 40 dairy herds, and 40 pig pens across three regions to establish baseline welfare, cost, and output parameters. Phase II employs longitudinal data collection over 12 months in a stratified sample of 20 broiler houses, 15 dairy herds, and 15 pig farms, capturing welfare indicators (behavioral observations using instantaneous scan sampling, corticosterone metabolites, incidence of routine illnesses, and injury/lameness scores), production metrics (feed intake, weight gain, milk yield, carcass quality), and economic data (variable costs, labor hours, veterinary expenses). Data collection instruments include validated welfare assessment protocols, electronic feeding and weight-tracking systems, farm financial records, and semistructured interviews with farm managers. Phase III focuses on model development and validation. A hierarchical Bayesian network model is specified to capture causal relationships and feedback loops among welfare status, costs, and outputs, supported by structural equation modeling to test direct and indirect effects. Regression analyses (multivariate and mixed-effects) will quantify associations between welfare indicators and production efficiency, while ANOVA will evaluate differences across species and housing types. Theoretical grounding draws on Pig Welfare Theory and the Cost–Benefit of Welfare framework, augmented by the Systems Thinking and Feedback Control Theory to justify the dynamic, closed-loop structure of the framework. The analysis will be performed using R and Mplus, with sensitivity analyses conducted to assess robustness to missing data and measurement error. Expected findings include (a) robust welfare indicators that significantly predict production efficiency and cost trajectories; (b) quantification of trade-offs between welfare-enhancing practices and marginal increases in operating costs, offset by gains in performance and product quality; (c) evidence of time-lag effects in welfare improvements on production outputs, necessitating anticipatory management adjustments; (d) a validated modular framework adaptable to multiple species and housing systems, with species-specific parameter estimates and thresholds for decision support. The study contributes to knowledge by operationalizing a dynamic, integrative model that couples animal welfare with economic feasibility and production outcomes, advancing measurement of welfare in economic terms and enabling proactive decision-making in intensive systems. It provides a transferable theoretical construct—the Welfare-Cost-Output Feedback Framework—for researchers and practitioners, along with a suite of empirically calibrated indicators, a Bayesian network model, and a user-friendly decision-support prototype for on-farm application. Conclusions are expected to underscore that welfare improvements can be designed as economically rational investments when embedded within a structured feedback framework that explicitly accounts for lagged effects and system-level interdependencies. Recommendations include policy guidance on welfare-related incentives, development of standardized reporting for welfare-cost-output metrics, and scaling of the framework to other production contexts such as aquaculture and alternative protein systems.