A demo-genetic model of root-knot nematod dynamics with applications to the deployment of plant resistance

(1)

HAL Id: hal-02393318

https://hal.inria.fr/hal-02393318

Submitted on 6 Dec 2019

HAL is a multi-disciplinary open access

archive for the deposit and dissemination of

sci-entific research documents, whether they are

pub-lished or not. The documents may come from

teaching and research institutions in France or

abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est

destinée au dépôt et à la diffusion de documents

scientifiques de niveau recherche, publiés ou non,

émanant des établissements d’enseignement et de

recherche français ou étrangers, des laboratoires

publics ou privés.

A demo-genetic model of root-knot nematod dynamics

with applications to the deployment of plant resistance

Ludovic Mailleret, Samuel Nilusmas, Suzanne Touzeau, Vincent Calcagno,

Caroline Djian-Caporalino, Philippe Castagnone-Sereno

To cite this version:

Ludovic Mailleret, Samuel Nilusmas, Suzanne Touzeau, Vincent Calcagno, Caroline Djian-Caporalino,

et al.. A demo-genetic model of root-knot nematod dynamics with applications to the deployment

of plant resistance. Journée MODECO - Modélisation des Dynamiques Ecologiques, Jul 2019, Nice,

France. �hal-02393318�

(2)

Ludovic Mailleret

with S. Nilusmas, S. Touzeau, V. Calcagno, C. Caporalino, P. Castagnone

M2P2 & IPN, UMR ISA, INRA, CNRS, Universit´e Cˆote d’Azur

(3)

Introduction

Nematodes

• very small slender worms (0.1-2.5 mm)

• over 40,000 species, present in virtually any

ecosystem

• free living and parasites of animals and plants

Plant parasitic nematodes

• ∼ 4, 000 species, causing billions of dollars of crop losses each year (temperate & tropical agrosystems)

• root knot nematodes (RKN) rank first in terms of damage at the world scale

Root knot nematodes

• polyphagous (> 5, 000 host plants), distributed worlwide, but sedentary

• cause galls on roots, which alter plants development

(4)

Nematodes

ecosystem

Plant parasitic nematodes

• ∼ 4, 000 species, causing billions of dollars of crop

losses each year (temperate & tropical agrosystems)

• root knot nematodes (RKN) rank first in terms of

damage at the world scale

Root knot nematodes

• polyphagous (> 5, 000 host plants), distributed worlwide, but sedentary

(5)

Introduction

Nematodes

ecosystem

Plant parasitic nematodes

• ∼ 4, 000 species, causing billions of dollars of crop

losses each year (temperate & tropical agrosystems)

• root knot nematodes (RKN) rank first in terms of

damage at the world scale

Root knot nematodes

• polyphagous (> 5, 000 host plants), distributed

worlwide, but sedentary

• cause galls on roots, which alter plants development

(6)

Long relied on hardcore chemical use

• soil fumigation

• restricted or banned

Biological control offers limited options

Resistant plant based control

• powerful eco-friendly method

• few R-genes

• R can be broken down by virulent strains, which limits the durability of the method

Aim of this work

• understand if and how it is possible to optimize the use of resistant cultivars to control RKN in seasonal agrosystems (market gardening)

(7)

RKN control methods

Long relied on hardcore chemical use

• soil fumigation

Biological control offers limited options

Resistant plant based control

• few R-genes

• R can be broken down by virulent strains, which

limits the durability of the method

Aim of this work

• understand if and how it is possible to optimize the use of resistant cultivars to control RKN in seasonal agrosystems (market gardening)

(8)

Long relied on hardcore chemical use

• soil fumigation

Biological control offers limited options

Resistant plant based control

• few R-genes

• R can be broken down by virulent strains, which

limits the durability of the method

Aim of this work

• understand if and how it is possible to optimize

the use of resistant cultivars to control RKN in seasonal agrosystems (market gardening)

(9)

RKN Life Cycle

In the soil, near a plant root

• free living infective juveniles

• contact with the root and penetrate it

• giant cells formation

• maturate and produce eggs (clonal)

• released into the soil and hatch

At the plant root system scale

• parasites with a free-living stage

• causing an epidemic within a population of roots infec�ve juvenile Root V ascular c yli nder test

(10)

In the soil, near a plant root

At the plant root system scale

• causing an epidemic within a population of roots infec�ve juvenile migra�on V ascular c yli nder

(11)

RKN Life Cycle

In the soil, near a plant root

At the plant root system scale

• causing an epidemic within a population of roots infec�ve juvenile • • Giant cells Root migra�on V ascular c yli nder test

(12)

In the soil, near a plant root

At the plant root system scale

• causing an epidemic within a population of roots • infec�ve juvenile • • egg mass Giant cells migra�on V ascular c yli nder adult

(13)

RKN Life Cycle

In the soil, near a plant root

At the plant root system scale

• causing an epidemic within a population of roots • infec�ve juvenile • • egg mass Giant cells Root migra�on V ascular c yli nder eggs hatch adult test

(14)

In the soil, near a plant root

At the plant root system scale

• causing an epidemic within a

population of roots • infec�ve juvenile • • egg mass Giant cells migra�on V ascular c yli nder eggs hatch adult

(15)

An epidemic among a growing population

simulation p erfo rmed with op ensimro ot

Along the course of a season

• plant root system grows

• recruits new infective nematodes

Nematode infection represses plant roots

development

An unusual epidemic

• developing on a growing population

• whose growth is negatively affected by infection

• in a seasonal context

(16)

p erfo rmed with op ensimro ot

Along the course of a season

Nematode infection represses plant roots

development

An unusual epidemic

(17)

An epidemic among a growing population

simulation p erfo rmed with op ensimro ot

Along the course of a season

Nematode infection represses plant roots

development

An unusual epidemic

• in a seasonal context

(18)









˙

P = −βPH − ηP + rI

˙

H = µf (H, E , I ) − βPH

˙

E = βPH − λE

˙

• P free living nematodes

• H healthy root sites

• E maturating nematodes

(19)

Model fitting

0 5 10 15 20 25 0.03 0.16 0.8 4 20

Initial nematode density

Final nemat ode density i n roots (a) 0 0.5 1.0 1.5 0.03 0.16 0.8 4 20 42 days (prediction)

135 days (training set) 135 days (training set)

42 days (prediction) (b)

Relative root bioma

ss

data : Ehw aeti et al. 1998, 2000

Parameterization

• most parameter values were found

in literature

• some had to be estimated from

experimental data: β, f (.)

Scenarios derivation

• ± 30% parameters

• low, medium (default), high, extreme scenarios

(20)

0 5 10 15 20 25 0.03 0.16 0.8 4 20

Final nemat ode density i n roots 0 0.5 1.0 1.5 0.03 0.16 0.8 4 20 42 days (prediction)

135 days (training set) 135 days (training set)

42 days (prediction)

Relative root bioma

ss

data : Ehw aeti et al. 1998, 2000

Parameterization

• most parameter values were found

in literature

Scenarios derivation

• ± 30% parameters

(21)

Plant resistance, nematode virulence

• plants are eitherRorS

• nematode pop. structured inavirulentandvirulentphenotypes

• avirulentsdo not develop onRplants

• bothavirulentsandvirulentsdevelop onSplants

• a fraction δ ofavirulentoffspring turns intovirulent

test

R S

(22)

R S

(23)

Plant resistance, nematode virulence

• a fraction δ ofavirulentoffspring turns intovirulent

test

R S

(24)

Fitness costs of

virulence

• infectiveness: βv = (1 − wβ)βa • reproduction: rv = (1 − wr)ra R S vir avir Infec�veness Reproduc�on et al. 2007, Djian et al. 2011

(25)

Seasonal context, crop rotations, optimization

R S

�me

...

season 1 season 2 season 3

Seasonal agrosystems

• crops planted and harvested

sequentially over time

• cultivar rotations to enhance crop yield (vs. pureSand pureR)

Yield proxy

• Cumulated Healthy Root Density

CHRD = 1 n X seasons ZT 0 H(τ )d τ test

(26)

R S

�me

...

Seasonal agrosystems

• cultivar rotations to enhance crop

yield (vs. pureSand pureR)

Yield proxy

CHRD = 1 n X seasons ZT 0 H(τ )d τ

(27)

Seasonal context, crop rotations, optimization

R S

�me

...

Seasonal agrosystems

• cultivar rotations to enhance crop

yield (vs. pureSand pureR)

Yield proxy

CHRD = 1 n X seasons ZT 0 H(τ )d τ test

(28)

Number of seasons with resistant plants Number of seasons with suscep � ble plan ts 1 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 2500 2250 1750 2000 100% R 100% S

• computation of all periodic crop _•

(29)

Optimal cultivar rotation

default scenario t Δ1 Δ2 Temporal horizon 0 10 15 20 25 3750 2500 1250 0 op�mal unconstrained op�mal periodic rota�on 100 % S

100 % R

rela�ve gain =

5 30

• R efficacy quickly drops with

temporal horizon

• optimal periodic rotationnearly

as efficient as the best strategy

• optimalR plants ratio much lower than agricultural practice (pure R)

(30)

t Δ1 Δ2 Temporal horizon 0 10 15 20 25 3750 2500 1250 0 op�mal unconstrained op�mal periodic rota�on 100 % S 100 % R rela�ve gain = 5 30 0 20 40 60 80 100 Ra � o of r esis tan t plan ts Temporal horizon 0 5 10 15 20 25 30

• R efficacy quickly drops with

temporal horizon

•

• optimalR plants ratio much lower

(31)

R characteristics: fitness costs of virulence

default scenario, 15 seasons

Castagnone et al. 2007, Djian Ca p. et al. 2011

• no advantage of rotations when

high or low fitness costs

• experimental data(Mi-tomato): >30% gain with optimal rotations

• wr and wβ have symmetrical

influence but interact negatively

R0,v= f (1 − (1 − wβ)(1 − wr)) = f (w )

(32)

Castagnone et al. 2007, Djian Cap. et al. 2011

(33)

R characteristics: fitness costs of virulence

default scenario, 15 seasons

Castagnone et al. 2007, Djian Cap. et al. 2011

• experimental data(Mi-tomato): >30% gain with optimal rotations

influence but interact negatively

R0,v= f (1 − (1 − wβ)(1 − wr)) = f (w )

(34)

0 0.5 1 0 0.5 1 0 0.5 1 0 0.5 1 0 20 40 60 rela � ve g ain w w w w

low moderate high extreme

1e-06 1e-04 1e-03 pure R

op�mal

• strong influence of disease

severity on advantage of rotations: increases with severity

• gain maximized for medium

• mild influence of virulence emergence rate on advantage of rotations: decreases with rate

(35)

Fitness cost × epidemiological scenarios

15 seasons, different virulence emergence rates

0 0.5 1 0 0.5 1 0 0.5 1 0 0.5 1 0 20 40 60 rela � ve g ain w w w w

1e-06 1e-04 1e-03 pure R

op�mal

fitness costs

• mild influence of virulence emergence rate on advantage of rotations: decreases with rate

(36)

0 0.5 1 0 0.5 1 0 0.5 1 0 0.5 1 0 20 40 60 rela � ve g ain w w w w

1e-06 1e-04 1e-03 pure R

op�mal

• mild influence of virulence

emergence rate on advantage of rotations: decreases with rate

(37)

Robustness

15 seasons, ±10% on all parameter values

0 10 20 10 30 40 50

moderate high extreme

realiz ed r ela � ve g ain

• sub-optimal rotations always outperform

pure R strategies

• benefit of optimal rotations little affected

by uncertainty on parameters

(38)

• more efficient than classical agricultural practice

• optimal periodic rotations approach best deployment performance

Fitness costs of virulence

• interact negatively

• 1 large cost + 1 small cost > 2 medium costs

Optimal rotations significantly outperform pure R

• when nematode infestation is moderate to severe

• when fitness costs are medium

• over longer time scales (not shown)

Robustness

• optimal rotation efficacy preserved despite uncertainty in model parameter estimates

(39)

Using plant Resistance against RKN

Alternating R and S cultivars

Fitness costs of virulence

Optimal rotations significantly outperform pure R

Robustness

(40)

Fitness costs of virulence

Optimal rotations significantly outperform pure R

Robustness

(41)

Using plant Resistance against RKN

Alternating R and S cultivars

Fitness costs of virulence

Optimal rotations significantly outperform pure R

Robustness

• optimal rotation efficacy preserved despite uncertainty in model

parameter estimates

(42)

(43)

Appendix: R

0,v

Season-to-season basic reproduction number of virulent nematodes

R0,v= φ exp (1 − wβ)(1 − wr) r α − 1 H0+ µT 2 β − η T

• obtained from the ˙Pv/Pv dynamics

• in the limit Pa, Pv → 0

• assuming E and I at quasi-equilibrium