Resource allocation theory applied to farm animal production

343 Pages·2009·1.98 MB·English

by  Wendy M 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
2 W.M. Rauw
focus on the notion that natural selection results in maximal fitness and prunes away
less-optimal life histories (Brommer, 2000).
Life histories are shaped by the interaction of extrinsic factors, i.e. environmen-
tal impacts on survival and reproduction, and intrinsic factors, i.e. trade-offs among
life-history traits and lineage-specific constrains on the expression of genetic varia-
tion (Stearns, 2000). Cole (1954) referred to the extrinsic factors when stating: ‘It is
obvious that the ability of the ancestors of existing species to replace themselves has
been sufficient to overcome all environmental exigencies which have been encoun-
tered (. . .) through physiological, morphological, and behavioural adaptations that
enable offspring to be produced and to survive in sufficient numbers to insure the
persistence of a species.’ Thus, in the absence of trade-offs, selection would drive all
life-history traits to limits imposed by design and history, i.e. the body plan and the
physiological limits posed by the phylogenetic history of the group to which the spe-
cies belongs (Stearns, 1989; Van Straalen and Roelofs, 2006). From a population
genetics point of view, given limits set by trade-offs and lineage-specific effects, sur-
vival and fertility of a species are optimized in such a way that population growth
rate is at a maximum (Van Straalen and Roelofs, 2006).
Trade-offs depict the situation where the increase of one life-history trait
imposes a cost to another, resulting in a negative correlation (Van Straalen and
Roelofs, 2006). In a population genetics context, a trade-off is generated by either
linkage disequilibrium (different loci influencing separate traits are situated closely
together on the same chromosome, preventing the genes from segregating inde-
pendently at meiosis) or pleiotropy (a single gene affects two or more different
traits); trade-offs between life-history traits are more commonly assumed to be the
result of the latter (Roff, 2007). Life-history trade-offs are often thought to be
caused by the allocation of limited resources among competing traits such as repro-
duction, somatic growth and maintenance (Leroi, 2001; Roff, 2007). Trade-offs are
extensively discussed in Chapter 3.
The idea of trade-offs resulting from energy allocation is very old and can be
traced back to Saint Hilaire and Goethe, who pronounced at about the same
time their law of compensation or balancement of growth (Darwin, 1872). As
Goethe expressed it: ‘the budget of nature is fixed; but she is free to dispose of
particular sums by any appropriation that may please her. In order to spend on
one side, she is forced to economize on the other side’ (in Stauffer, 1975). In two
volumes of Philosophie anatomique, Saint Hilaire identified the principle that all ani-
mals are formed of the same units of construction. According to his principle of
connections, these units are fixed in number and always maintain the same position
relative to each other. Since he argued that the budget of nature is fixed, he
applied the principle of balance (‘loi de balancement’) to show that if one structure
is enlarged, another one has to be reduced in order to maintain an exact equilib-
rium (Kliman, 1982; Mayr, 1983). ‘The atrophy of one organ turns to the profit of
another; and the reason why this cannot be otherwise is simple, it is because there
is not an unlimited supply of the substance required for each part’ (Geoffroy Saint
Hilaire, 1818). Darwin (1872) agreed: ‘I think this holds true to a certain extent
with our domestic productions: if nourishment flows to one part or organ in excess,
it rarely flows, at least in excess, to another part; thus it is difficult to get a cow to
give much milk and to fatten readily.’