A conceptual approach to design livestock production systems for robustness to enhance sustainability

Existing approaches to enhance sustainability of livestock production systems focus on the level of sustainability indicators. Maintaining the level of sustainability in the face of perturbations, which is robustness of sustainability, is relatively unexplored. Perturbations can be classed as noise (common in a specific system environment), shock (uncommon, either in occurrence, magnitude or duration), cycle or trend. Livestock production systems are hierarchical structures of nested systems. Lower system levels are from the biological and ecological domains (animals and micro-organisms), intermediate levels are predominantly from the technical domain (pen, barn and herd) and higher levels are from the social domain (production chain, livestock production sector). Resilience theory is the model for maintaining system features in the presence of perturbations in ecosystems and social systems. It is merely a descriptive approach, due to the low level of design and human control in these systems. Robustness theory is an equivalent model to describe and understand the maintenance of system features in biological and technical systems under perturbations. Additionally, robust design theory distinguishes concept design (choice of concept, components and materials), parameter design (optimal configuration of control factors given the concept design) and tolerance design (eliminating causes of variation) to deal with perturbations and their effect on the system. Technical systems of current livestock production systems are heavily based on tolerance design, but an interesting opportunity for new designs is to utilise the animal's intrinsic adaptation capacity and incorporate concept design and parameter design for over-all robustness. Concept design strategies for robustness include diversity and heterogeneity of components, functional redundancy and modularity. A fourth level of design, called hierarchy design, is needed to ensure that higher system levels support lower system levels of livestock production systems for optimal robustness. To enhance over-all robustness of livestock production systems for sustainability, a specific approach is needed for each system level and these approaches should be integrated and balanced.

[1]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[2]  Erica Jen,et al.  Robust design : a repertoire of biological, ecological, and engineering case studies , 2005 .

[3]  Bruce A. Francis,et al.  Feedback Control Theory , 1992 .

[4]  S. Carpenter,et al.  Catastrophic shifts in ecosystems , 2001, Nature.

[5]  E. Noordhuizen-Stassen,et al.  Undesirable side effects of selection for high production efficiency in farm animals: a review , 1998 .

[6]  R. Sellwood,et al.  Inheritance of resistance to neonatal E. coli diarrhoea in the pig: examination of the genetic system , 1977, Theoretical and Applied Genetics.

[7]  H Mollenhorst,et al.  On-farm quantification of sustainability indicators: an application to egg production systems , 2006, British poultry science.

[8]  Louise O. Fresco,et al.  Time and spatial scales in ecological sustainability , 1992 .

[9]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[10]  François Bocquier,et al.  Adaptive abilities of the females and sustainability of ruminant livestock systems. A review , 2006 .

[11]  C. S. Holling,et al.  Regime Shifts, Resilience, and Biodiversity in Ecosystem Management , 2004 .

[12]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[13]  Simon J. Oosting,et al.  Defining sustainability as a socio-cultural concept: Citizen panels visiting dairy farms in the Netherlands , 2008 .

[14]  M. Scheffer,et al.  Socioeconomic Mechanisms Preventing Optimum Use of Ecosystem Services: An Interdisciplinary Theoretical Analysis , 2000, Ecosystems.

[15]  Henry W. Altland,et al.  Engineering Methods for Robust Product Design , 1996 .

[16]  Ida Gremyr,et al.  Principles of robust design methodology , 2008, Qual. Reliab. Eng. Int..

[17]  Wolfgang Beitz,et al.  Engineering Design: A Systematic Approach , 1984 .

[18]  D. Timmermann,et al.  Intrinsic Flexibility and Robustness in Adaptive Systems: A Conceptual Framework , 2006, 2006 IEEE Mountain Workshop on Adaptive and Learning Systems.

[19]  Erica Jen,et al.  Stable or robust? What's the difference? , 2003, Complex..

[20]  S. Pimm The complexity and stability of ecosystems , 1984, Nature.

[21]  S. Levin Ecosystems and the Biosphere as Complex Adaptive Systems , 1998, Ecosystems.

[22]  J. Anderies,et al.  Robustness Trade-offs in Social-Ecological Systems , 2007 .

[23]  Simon Maxwell Farming systems research: Hitting a moving target , 1986 .

[24]  Dwight W. Read,et al.  SOME OBSERVATIONS ON RESILIENCE AND ROBUSTNESS IN HUMAN SYSTEMS , 2005, Cybern. Syst..

[25]  J. V. van Arendonk,et al.  Survival of laying hens: genetic parameters for direct and associative effects in three purebred layer lines. , 2008, Poultry science.

[26]  Elinor Ostrom,et al.  A Framework to Analyze the Robustness of Social-ecological Systems from an Institutional Perspective , 2004 .

[27]  C. S. Holling Understanding the Complexity of Economic, Ecological, and Social Systems , 2001, Ecosystems.

[28]  J. ten Napel,et al.  Utilising intrinsic robustness in agricultural production systems , 2006 .

[29]  C. S. Holling,et al.  Resilience, Adaptability and Transformability in Social–ecological Systems , 2004 .

[30]  J. Anderies,et al.  From Metaphor to Measurement: Resilience of What to What? , 2001, Ecosystems.

[31]  Piter Bijma,et al.  Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance , 2008, Genetics Selection Evolution.

[32]  C. S. Holling,et al.  Panarchy Understanding Transformations in Human and Natural Systems , 2002 .

[33]  C. S. Holling Resilience and Stability of Ecological Systems , 1973 .

[34]  J. Doyle,et al.  Reverse Engineering of Biological Complexity , 2002, Science.

[35]  H. Kitano Towards a theory of biological robustness , 2007, Molecular systems biology.