a resource allocation approach to combine selection and ... · herd environments (e) are changing...

A resource allocation approach to combine selection and management

within the herd environment

Frédéric DOUHARD

Ph.D. defence

5/11/2013

A L I M E N T A T I O N

A G R I C U L T U R E

E N V I R O N N E M E N T

Supervisor: Nicolas C. FRIGGENS UMR MoSAR

Co-supervisor: Muriel TICHIT UMR SAD APT

Selection solely on production traits: SPECTACULAR PROGRESS … with simultaneously low environmental limitation

1

Context of production improvement

Herd environments (E) are changing with probably increasing variations in the future

2


The future

Herd environments (E) are changing with probably increasing variations in the future Breeding programs still select genotypes (G) in non-limiting environment to demonstrate a high level of phenotypic performance (P)

2


The future

Herd environments (E) are changing with probably increasing variations in the future Breeding programs still select genotypes (G) in non-limiting environment to demonstrate a high level of phenotypic performance (P) Risk of MISMATCH between G and E

2


The future

Mapping the problem

Between generations

Within-life

3

Population

Animal

Herd

Mapping the problem

from a nutritionist viewpoint

E

P

Between generations

Within-life

Managed environment

Performance

Nutrient partitioning

4

EFFICIENCY

Population

Animal

Herd

G

P

Between

generations Within-life

Performance

Selected genotypes

Selective breeding

5

Mapping the problem

from a geneticist viewpoint

Population

Animal

Herd

Between generations

Within-life

6

G

P

Mapping the problem

a separate focus on G and E

E

P

Population

Animal

Herd

P

E G

Between


A unifying concept

7

G

P

Mapping the problem

taking advantage of G × E

Population

Animal

Herd E

P

General objective

Describe the animal to explore

the long-term consequences

of selection × management in a herd

8

General objective

Describe the animal to explore

the long-term consequences

of selection × management in a herd

8

Selection

Nutrient partitioning

?

Management

Within-life expression Animal

Herd

General approach

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

Concepts

Theory

Experimental data

9

Outline

Resource allocation theory

The herd environment system

1. Case study

2. System approach

3. Model description

Focus

1. Management effect on within-life performance

2. Long term consequences of selection × management

Discussion

10

Outline 10



1. Case study

2. System approach


Focus



Discussion

The resource allocation

principle

Environment (E)

R

R1 R2

c (1 – c)

van Noordwijk & de Jong, 1986

Individual animal

11

Environment (E)

10

3 7


Individual animal

e.g. R = 10 c = 0.3

11


principle

Environment (E)

R

R1 R2

P1 P2

c (1 – c)


Natural fitness

Population naturally selected

Individual animal

11


principle

P1

P2

Beilhartz et al., 1993,

van der Waaij, 2004

Generation n

Rn

cn

Limiting environment

12


application

e.g. selection for P1

P1

P2

Generation n+1

Rn+1 = Rn

cn+1 > cn



van der Waaij, 2004

12


application


P1

P2


Trade-off


van der Waaij, 2004

12


application


P1

P2


Non-limiting environment

P2

Rn+1 > Rn

cn+1 = cn


van der Waaij, 2004

12


application

P1


P

E G

Between


A unifying framework

13

G

P

Mapping the problem

taking advantage of G × E

Population

Animal

Herd E

P

Outline



1. Case study

2. System approach


Focus



Discussion

Reproductive success/failure

Case study

dairy goat systems

Extended lactation control of production costs

is crucial for efficiency

mating

kidding

replacement

Culling

"Normal" yearly cycle

14


Extended lactation

high genetic merit for production

+

mating

kidding

replacement

+

Culling +

"Normal" yearly cycle

15

Case study

dairy goat systems


Extended lactation

mating

kidding

replacement

+ extended lactation

Culling

high genetic merit for production

"Normal" and "extended" cycles

extended lactation as a management compensation

16

Case study

dairy goat systems

Outline



1. Case study

2. System approach


Focus



Discussion

Whole-life (generational)

Within-life

HERD Selection

of "robust" animals

Management of extended

lactation

ANIMAL Heritable

component of allocation

Expression of allocation

priorities


approach 17


Within-life

HERD Selection

of "robust" animals


lactation

ANIMAL Heritable



priorities


18


approach


Within-life

HERD Selection

of "robust" animals


lactation

ANIMAL Heritable



priorities

Focus 1

19


approach


Within-life

HERD Selection

of "robust" animals


lactation

ANIMAL Heritable



priorities

Focus 2

20


approach

Outline



1. Case study

2. System approach


Focus



Discussion

P

E G

- Heritable traits of allocation - Performance P1, P2, P3,…

intake, body condition and size, milk,

probability of conception, probability of survival

Selection criteria W1, W2, W3, ..

e.g. WMilk, WWeight

Resource availability (Metabolizable energy)

INPUTS:

OUTPUTS:

Selection Index = (W1 × P1) + (W2 × P2) + (W3 × P3) + …

21


model overview

Mating

Year step

OFFSPRING

PARENTS

Selection

Voluntary culls (low selection index)


herd simulation 22

Mating

Year step

OFFSPRING

Week step

PARENTS

Allocation

Selection

Resource availabilty

Involuntary culls (mortality)

22


herd simulation

Voluntary culls (low selection index)

23


animal model description

Prediction of individual performance every week:

intake, body condition, milk, body size,

probability of conception, probability of survival

R

d (1 – d)

p (1 – p)

Growth Survival

(1 – l)

(1 – g)

l

g

Body reserves


Lactation

Pregnancy

23



Deposition

l = l0 × lT × lE

Body reserves


Generational component

(heritable trait)

Within-life temporal expression

Within-life change

of expression due to E

time after parturition

e.g. Lactation

R

d (1 – d)

p (1 – p)

Growth Survival

(1 – l)

(1 – g)

l

g Lactation

Pregnancy

24



Deposition

Details of the allocation coefficients:

0 < < 1

lT

Body reserves


Genetic variation only assumed at the level

of resource allocation to

body reserves deposition (d0) and

lactation (l0)

R

d (1 – d)

p (1 – p)

Growth Survival

(1 – l)

(1 – g)

l

g Lactation

Pregnancy

25


animal model assumptions

Deposition

Simplifying assumptions:

Resource acquisition related to body size (+) and body condition (-) Probability of conception related

to level and variation of body condition (+)

Body reserves


R

d (1 – d)

p (1 – p)

Growth Survival

(1 – l)

(1 – g)

l

g Lactation

Pregnancy

26


animal model assumptions

Deposition

Fundamental assumptions:

Weight, kg

27


animal model calibration

Puillet et al., 2010

Sauvant et al., 2012

Age, weeks

year 1 year 2 year 3 year 4 year 5

27



Weight, kg

Age, weeks

model


27



Body condition score

Weight, kg

Age, weeks


27




Intake kg DM/d Weight, kg

Age, weeks


Milk kg/d

Intake kg DM/d

27




Weight, kg

Age, weeks


Milk kg/d

Intake kg DM/d

27




Weight, kg

it is possible to model a "normal " within-life profile of performance using a resource allocation approach

Age, weeks


Outline



1. Case study

2. System approach


Focus



Discussion

Management of extended lactation

experimental study

Previous studies showed a " 2nd peak " of lactation

when its length is extended for non-pregnant goats

(Linzell, 1973, Chastin et al., 2001, Salama et al., 2005)

→ What about body weight and intake?

→ Do they vary in the same way than during the peak

phase in normal lactation?

Design of an experimental study to compare "normal"

vs. "extended" lactation (n = 9) on 2 years

28

Milk kg/d

kidding kidding repro repro dry-off

2 "normal" successives lactations

29


experimental results

Time after parturition (days)

○ normal (n=9)

Milk kg/d

kidding repro

30




• extended (n=9)

1 "extended" lactation

Tchange

Milk kg/d

kidding repro

Comparison of "normal" and "extended" lactations

31


experimental results kidding Tchange

Time after parturition or Tchange (days)

○ normal (n=9)

• extended (n=9)


kidding kidding repro repro

Weightkg

32




extended lactation disrupts the opposition phase between milk and weight dynamics which normaly occurs

○ normal (n=9)

• extended (n=9)

2 main new features of extended lactation included in the model and calibrated with data from the experimental study:

1. a transient increase in resource acquisition

at about 330 days after parturition

2. almost simultaneously an increase in resource allocation expression towards body reserves deposition (d)

and towards lactation (l)

33


integration in the model

Milk kg/d

Intake kg DM/d


Weight, kg

34


integration in the model

Age, weeks

extended lactation


Outline



1. Case study

2. System approach


Focus



Discussion

E G

Selected individuals should have: High production WMilk =1 Successful reproduction WPREG =1 (pregnancy status)

Random resource availability

t

35

Consequences of selection × management

simulation study

P (Milk, Age, PREG, …)

E G


t

Giving E, animals selected over years are deemed to be robust

test of an increasing value of WAge

35


simulation study


P (Milk, Age, PREG, …)

P

E G


Configuration: Selection during 40 years Herd size = 500

t

Selection Index = (WMilk × Milk) + (WPREG × PREG) + (WAge × Age)

Giving E, animals selected over years are deemed to be robust

test of an increasing value of WAge

35


simulation study


- allocation traits (d0, l0) - performance (Milk, Age, PREG)

36


results: herd rates

Time of selection, years

Survival rate, %

Selection for age:

Survival rate, %

36


results: herd rates


Survival improvement associated with increasing proportion of extended lactation

Extended lactation proportion, %

Selection for age:

Survival rate, %

37


results: herd rates


Extended lactation proportion, %

Low proportion

Selection for age:

Survival improvement associated with increasing proportion of extended lactation

Milk, kg/d Body condition score

37


results: average P

Selection for age:

Time of selection, years Time of selection, years

High proportion of extended lactation non-linear effects on milk and condition selection responses

37


results: average P

Milk, kg/d Body condition score

Selection for age:

Time of selection, years Time of selection, years

38


results: resource allocation

Type I II III

Extended lactation (%) low

Allocation to deposition (d0) –

Allocation to lactation (l0) +

Selection for age:

39


results: allocation type I

39


results: allocation type I

size and survival –

milk +

body condition –



Type I II III

Extended lactation (%) low low

Allocation to deposition (d0) – +

Allocation to lactation (l0) + –

Body condition –

Milk +

Survival –

Selection for age:

40


results: allocation type II

size and survival =

milk =

body condition =



Type I II III

Extended lactation (%) low low high

Allocation to deposition (d0) – + –

Allocation to lactation (l0) + – +

Body condition – =

Milk + =

Survival – =

Selection for age:

41


results: allocation type III

size and survival +

body condition –

41


results: allocation type III

size and survival +

body condition –

milk +

intake +



Type I II III

Extended lactation (%) low low high

Allocation to deposition (d0) – + –

Allocation to lactation (l0) + – +

Body condition – = –

Milk + = +

Survival – = +

Selection for age:

42


overall result: trade-off

Milk, kg/d

Survival rate, %

Selection for age:

Type II

Type I

Extended lactation

low

Trade-off

confirms Beilhartz et al., 1993, van der Waaij, 2004

Type II

Type I

Type III

Type III reveals a win-win situation

43


overall result: trade-off

Milk, kg/d

Survival rate, %

Selection for age:

Extended lactation

low high

in lines with suggestion of Kolver et al., 2009

Outline



1. Case study

2. System approach


Focus



Discussion

General approach

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

Experimental data

44

Concepts

Theory

Concepts

Theory

General approach

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

Experimental data

44

1 - A resource allocation model calibrated on within-life profile

General approach

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

Experimental data

2 –Extended lactation affects resource acquisition

and allocation within-life

44

Concepts

Theory


Concepts

Theory

General approach

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

Experimental data

3 - Selection and Management of extended lactation interact and offer

opportunities for a win-win situation

44

2 –Extended lactation affects resource acquisition

and allocation within-life


Discussion

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

45

Discussion

biological insights

Win-win situation demonstrates a synergy between selection and management effects

The relationship between competing traits is manageable

46

Win-win situation demonstrates a synergy between selection and management effects

Not a single road to production improvement

exploit innate biological capacities to deal

with variable resource provision

The relationship between competing traits is manageable

46

Discussion

biological insights

Discussion

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

47

48

G × E not a result per se but

a multi-level process that involves the farm manager Only a proof-of-principle ….

Discussion

framework

G × E not a result per se but

a multi-level process that involves the farm manager Only a proof-of-principle …. Limitations: G: crude selection index, random mating, closed herd E: ‘narrow’ nutrition, crude intake, simplified reproduction management Evaluation of the resource allocation hierarchy

48

Discussion

framework

Discussion

MODEL

DESCRIBE

DESIGN

EXPLAIN

EXPLORE

49

Discussion

perspectives

Towards a generic animal model → Estimation of the genetic parameters of the generational component of allocation

50

Towards a generic animal model → Estimation of the genetic parameters of the generational component of allocation Towards taking advantage of G × E → Role of the manager in the herd environment

50

Discussion

perspectives

Conclusion 51

Challenging context opens a bright future for production improvement, if we focus on

INTERACTIONS

Resource acquisition – Resource allocation

Selection – Management

AND SYNERGY OF METHODS

Modelling – Experimentation

Animal

Herd

Thank you for your attention

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