Resource Allocation Theory Applied to Farm Animal Production

344 Pages·2007·1.46 MB·English

by  W. Rauw

R A T A
ESOURCE LLOCATION HEORY PPLIED
F A P
TO ARM NIMAL RODUCTION
It is the magician’s wand,
by means of which [the agriculturist]
may summon into life
whatever form and mould he pleases
William Youatt (1872) cited in Darwin (1872)
One of the most remarkable features
in our domesticated races
is that we see in them adaptation,
not indeed to the animal’s ( . . . ) own good,
but to man’s use or fancy
Charles Darwin (1872)
R A
ESOURCE LLOCATION
T A
HEORY PPLIED TO
F A P
ARM NIMAL RODUCTION
Edited by
Wendy Mercedes Rauw
Department of Animal Biotechnology
University of Nevada-Reno
Reno, USA
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A catalogue record for this book is available from the British Library, London, UK
Library of Congress Cataloging-in-Publication Data
Resource allocation theory applied to farm animal production / edited by Wendy M.
Rauw.
p. cm.
Includes bibliographical references and index.
ISBN 978-1-84593-394-4 (alk. paper)
1. Livestock productivity--Mathematical models. 2. Resource allocation. I. Rauw,
Wendy M. II. Title.
SF140.M35R47 2008
636'.08--dc22
2008025072
ISBN: 978 1 84593 394 4
Typeset by SPi, Pondicherry, India.
Printed and bound in the UK by MPG Books Ltd, Bodmin.
The paper used for the text pages in this book is FSC certifi ed. The FSC (Forest
Stewardship Council) is an international network to promote responsible management
of the world’s forests.
Contents
Contributors vii
PART I RESOURCE ALLOCATION
1 Introduction 1
W.M. Rauw
2 Resource Allocation Patterns 22
D.S. Glazier
3 Trade-offs 44
D.S. Glazier
4 Metabolic Constraints to Resource Allocation 61
D.E. Naya and L.D. Bacigalupe
5 Homeorhesis During Heat Stress 72
R.J. Collier, S.W. Limesand, M.L. Rhoads,
R.P. Rhoads and L.H. Baumgard
PART II INPUTS AND OUTPUTS
6 Residual Feed Intake 89
R.M. Herd
7 Allocation of Resources to Maintenance 110
P.W. Knap
8 Allocation of Resources to Growth 130
C.T. Whittemore
9 Genetic Size-scaling 147
St C.S. Taylor
v
vi Contents
10 Allocation of Resources to Reproduction 169
G.B. Martin, D. Blache and I.H. Williams
11 Allocation of Resources to Immune Responses 192
I.G. Colditz
PART III CONSEQUENCES OF SELECTION FOR
INCREASED PRODUCTION EFFICIENCY
12 Selection for High Production in Pigs 210
P.W. Knap and W.M. Rauw
13 Selection for High Production in Poultry 230
P.B. Siegel, C.F. Honaker and W.M. Rauw
14 Selection for High Production in Dairy Cattle 243
R.F. Veerkamp, J.J. Windig, M.P.L. Calus, W. Ouweltjes,
Y. de Haas and B. Beerda
15 Consequences of Biological Engineering 261
for Resource Allocation and Welfare
D.M. Broom
PART IV ANIMAL BREEDING AND RESOURCE
MODELLING
16 Breeding Goals to Optimize Production Effi ciency 275
A.F. Groen
17 Robustness 288
P.W. Knap
18 Modelling of Resource Allocation Patterns 302
N.C. Friggens and E.H. van der Waaij
Index 321
Contributors
L.D. Bacigalupe, Department of Animal and Plant Sciences, University of Sheffi eld, Western
Bank, Sheffi eld S10 2TN, UK. Present address: Departamento de Zoología, Universidad
de Concepción, Casilla 160-C Concepción, Chile.
L.H. Baumgard, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721,
USA.
B. Beerda, Animal Breeding and Genomics Centre, Wageningen University and Research Centre,
8200 AB Lelystad, The Netherlands.
D. Blache, UWA Institute of Agriculture M082, The University of Western Australia, 35
Stirling Highway, Crawley, WA 6009, Australia.
D.M. Broom, Centre for Animal Welfare and Anthrozoology, Department of Veterinary
Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK.
M.P.L. Calus, Animal Breeding and Genomics Centre, Wageningen University and Research
Centre, 8200 AB Lelystad, The Netherlands.
I.G. Colditz, CSIRO Livestock Industries, FD McMaster Laboratory, Armidale, NSW 2350,
Australia.
R.J. Collier, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721,
USA.
Y. de Haas, Animal Breeding and Genomics Centre, Wageningen University and Research
Centre, 8200 AB Lelystad, The Netherlands.
N.C. Friggens, Department of Animal Health, Welfare and Nutrition, Research Centre Fou-
lum, 8830 Tjele, Denmark.
D.S. Glazier, Department of Biology, Brumbaugh Academic Center, Juniata College,
Huntingdon, PA 16652, USA.
A.F. Groen, Director Corporate Staff Education and Research, Wageningen University and
Research Center, PO Box 9101, 6700 HB Wageningen, The Netherlands.
R.M. Herd, New South Wales Department of Primary Industries, Beef Industry Centre,
Armidale, NSW 2351, Australia.
C.F. Honaker, Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, VA
24061, USA.
vii
viii Contributors
P.W. Knap, PIC International Group, 24837 Schleswig, Germany.
S.W. Limesand, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721,
USA.
G.B. Martin, UWA Institute of Agriculture M082, The University of Western Australia, 35
Stirling Highway, Crawley, WA 6009, Australia.
D.E. Naya, Center for Advanced Studies in Ecology and Biodiversity and Departamento de
Ecología, Facultad de Ciencias Biológicas, Pontifi cia Universidad Católica de Chile, CP
6513677, Santiago, Chile.
W. Ouweltjes, Animal Breeding and Genomics Centre, Wageningen University and Research
Centre, 8200 AB Lelystad, The Netherlands.
W.M. Rauw, University of Nevada-Reno Department of Animal Biotechnology, Reno, NV
89557, USA.
M.L. Rhoads, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721,
USA.
R.P. Rhoads, Department of Animal Sciences, University of Arizona, Tucson, AZ 85721,
USA.
P.B. Siegel, Department of Animal and Poultry Sciences, Virginia Tech, Blacksburg, VA
24061, USA.
St C.S. Taylor, Animal Breeding Research Organisation, Edinburgh, UK.
E.H. van der Waaij, Wageningen University, Animal Breeding and Genomics Centre, 6700
AH W ageningen, The Netherlands.
R.F. Veerkamp, Animal Breeding and Genomics Centre, Wageningen University and Research
Centre, 8200 AB Lelystad, The Netherlands.
C.T. Whittemore, University of Edinburgh, Edinburth EH9 3JG, UK.
J.J. Windig, Animal Breeding and Genomics Centre, Wageningen University and Research
Centre, 8200 AB Lelystad, The Netherlands.
I.H. Williams, UWA Institute of Agriculture M082, The University of Western Australia, 35
Stirling Highway, Crawley, WA 6009, Australia.
1
Introduction
W.M. R
AUW
University of Nevada-Reno, Department of Animal Biotechnology, Reno,
NV 89557, USA
1. Life History Theory
When Charles Darwin travelled with the H.M.S. Beagle to Tierra del Fuego and
the Falkland Islands in 1834, he observed a discrepancy between the number of
eggs of a large white Doris (a sea slug) and the abundance of the species. He real-
ized that the abundance of a species does not necessarily depend on the number
of offspring produced (Van Straalen and Roelofs, 2006). Life history theory deals
with the question of why the power of propagation differs so much between spe-
cies, and with the way an organism spreads its reproduction over its lifetime and
forms an adaptation to the environment it lives in (Brommer, 2000; Van Straalen
and Roelofs, 2006).
Darwin adopted Herbert Spencer’s (1864) term ‘survival of the fittest’ in 1866.
His concept of fitness arose from his view of the organism and the environment it lives
in. He did not actually use the term ‘fitness’, but referred to individual organisms as
being more or less ‘fit’ than other individuals: different individual members of a
species ‘fit’ into the environment to different degrees as a consequence of phenotypic
variation, and those that make the best ‘fit’ survive and reproduce their kind better
than those whose ‘fit’ is poorer (Ariew and Lewontin, 2004). In other words, fit
organisms are better represented in future generations than their relatively unfit
competitors (Stearns, 1976). Textbooks, monographs and articles show a wealth of
diversity in fitness definitions (De Jong, 1994). Or as Ariew and Lewontin (2004) state:
‘No concept in evolutionary biology has been more confusing and has produced such
a rich philosophical literature as that of fitness.’ Fitness concepts may refer to the
functioning of an organism (fitness itself is a cause of natural selection), or may consti-
tute a technical term in population biology summarizing numerical processes (fitness
is a description of natural selection; De Jong, 1994). Within the numerical fitness con-
cept, many quantities are proposed as fitness measures: life-history traits may include
lifetime reproductive success, survival, viability, fecundity, mating success and age at
maturity (Schluter et al., 1991; De Jong, 1994). Theories on the evolution of life history
©CAB International 2009. Resource Allocation Theory Applied to Farm
Animal Production (ed. W.M. Rauw) 1