INFLUENCE OF CLIMATIC VARIABILITY

ON INTEGRATED PEST MANAGEMENT

OF Musa spp. PESTS

Luis Pérez Vicente

Instituto de Investigaciones de

Sanidad Vegetal. MINAG, Cuba.

Research Honorary Fellow

Bioversity International/RELAC

Projected warming

are expected to be :

Future projection of climatic changes

Higher on higher

lands and north

latitudes (≈2.5-3.0 ˚C)

and lower in the

south oceans and

parts of north Atlantic

ocean

Projected Patterns of Precipitations Changes

Projections of Future Climate Changes

Precipitations probably will increase in higher latitudes latitudes

Will probably decrease in most of subtropical terrestrial regions

Higher sea temperatures will lead to more

severe extreme events

0

2

4

6

8

10

12

Hurricans total Very intense hurricans

Num

ber

of h

urric

anes

Number of intense hurricanes affecting Cuba by decades

since 1801 (Pérez et al., 2000; INSMET, 2007)

Then arising questions are:

What would be the impact on

current banana pests incidence ?

Will change the relative

importance of different pests in

the crops?

Which would be the impact in

trans boundary pests movement?

Which adaptation measures

should be implemented?

Individual growth and development of

pests and vectors

Dispersal pests capacity

Effects on antagonists/ bio-regulators

Relative competitiveness (fitness)

of pathogens as results of biotic

and abiotic interactions.

Selection of more adapted species

and genotypes of pests

Higher solar radiation, C02 concentration and higher temperatures

Mesoclimate

Microclimate

Impact on defense

mechanisms

Highly complex interaction models

Higher and fast

foliar development

Dry climate will

favor virus and

vectors dispersal

Wet weather will

favor fungi and

bacteria pathogens

Crop Pest Management Practices Changes

A study case on black Sigatoka disease

in the Caribbean:

Sceneries A2 and B2 developed for

Cuba for years 2030 and 2060

Global models used in Cuba for sceneries development

(Centella, 2010; INSMET, Cuba)

ECHAM5/MPI-OM: Max Planck Institute for Meteorology,

Germany

HADCM3: Hadley Centre for Climate Prediction and

Research, Meteorological Office, United Kingdom

The Hadley Centre regional Climate Modeling System PRECIS,

Version 1.6.1 (Wilson, 2008) was used to fit the global models

data to the selected sites.

Base line developed with historical data recorded from 1962 to

1989

The future sceneries selected were (SRES/IPCC, 2000):

― A2 (more critical) and B2 (less critical )

Years 2030 and 2060.

Selected sites to determine sceneries

of climatic change (23)

Sola

Los Palacios

Güines

Artemisa

Güira/

Alquízar

Martí

Jovellanos

Colón

Iguará

Colombia

Sagua la Grande

Remedios

Juraguá

Imias

Venezuela

Baraguá

Veguitas

Mayarí/ Sagua

de Tánamo

Caney del

Sitio/ San Luis

Baracoa

Jiguaní/ Contramaestre

U. Noris

Caujerí/

San Antonio

del Sur

In 2010:

106,000 ha along the country

Total production: 670,000 t.

Development of future climatic change anomalies

for sceneries A2 and B2 in years 2030 and 2060

Anomalies obtained as average of both GCMs for every

site, sceneries and years

– Daily and monthly average of maximal (Tmax), minimal (Tmin)

and median (Tmed) temperature

– Median relative humidity (Rh)

Daily and annual rainfall

data were obtained from the HADCM3 and used as base line the

records of rainfall of every site reported by the National Institute

of Hydraulic Resources.

Sceneries A2 and B2 of temperature in 2030 and 2060

26

28

30

32

34

36

38

J F M A M J J A S O N D

Tem

per

atu

re ⁰

C

Maximal Temperature

Historical 2030 A2 2060 A2 2030 B2 2060 B2

+ 2.84

22

24

26

28

30

32

J F M A M J J A S O N D

Tem

per

atu

re ⁰

C

Median temperature

Historical 2030 A2 2060 A2 2030 B2 2060 B2

20

21

22

23

24

25

26

27

28

29

30

J F M A M J J A S O N D

Tem

per

atu

re ⁰

C

Minimal temperature

Historical 2030 A2 2060 A2 2030 B2 2060 B2

+ 2.33

+ 2.8

2030 A2 2030 B2 2060 A2 2060 B2

Rh monthly anomalies in the sceneries A2

and B2 in 2030 and 2060

-5,0

-4,5

-4,0

-3,5

-3,0

-2,5

-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Rh

(%

)

Ene Feb Mar Abr May Jun Jul Ago Set Oct Nov Dic

Annual rainfall described for sceneries A2 and B2 in

2030 and 2060 and the historical records of Institute of

Hydraulic Resources

0

500

1000

1500

2000

2500

3000M

M d

e llu

via

Historical records 2030 A2 2030 B2 2060 A2 2060 B2

Expected climatic change impact on Black Sigatoka (BS)

Temperature

BS speed of evolution

(termophysiologic method of

Livingstone) based on (Porras y

Pérez Vicente, 1998):

0

400

800

1200

1600

2000

2400

700

900

1100

1300

1500

1700

1900

2100

2300

SE

rec

ord

ed

SE calculated

n = 901

SE = 7.18 t max. + 7.19 t min.

R2 = 0.98

2. the model to calculate the

SV as function of daily

Tmax and Tmin.

0102030405060708090

100

8 12 16 20 24 28 32 36% o

f th

e m

axim

al g

row

th

Temperature ⁰C

Vf = 75.35 e-0.015( t-27.13)2; R2= 0.91

t<11 ⁰C and t>38 ⁰C, Vf = 0

1. the law of temperature on M.

fijiensis ascospore’s tube

growth using daily Tmax. and

Tmin. determined by the GCMs

and

Weekly accumulates of BLS speed of evolution according

the sceneries A2 y B2 in years 2030 and 2060 in Baraguá

site in relation with historical value of 1995

7000

8000

9000

10000

11000

12000

13000

14000

15000

16000

17000

18000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51We

ekly

accu

mu

late

s o

f sp

eed

of

evo

luti

on

Weeks

1995 2030 A2 2030 B2 2060 A2 2060 B2

Weekly threshold for BS progressions

Relationships between accumulated rainfall and speed

of evolution of BSD in banana and plantains

Expected climatic change impact on Black Sigatoka (BS)

2. Rainfall determined by HADCM3 GCM for the sites Güira de Melena

/Alquízar, Baraguá, Imías and Baracoa. Comparison of BS recurrences with

rainfall predicted with the model for A2 and B2 sceneries in 2030 and 2060

and historical in 1995

1. Rainfall accumulated for 10

and 14 days (Pérez et al., 2000 and 2006)

Independent BS state of evolution (SE)

variable after (Weeks)

(3) (4) (5)

LL14 (mm) 0.64*** 0.77*** 0.69***

DLL14 (min) 0.51** 0.75*** 0.73***

0

200

400

600

800

1000

1200

0

20

40

60

80

100

120

140

160

180

200

47 51 3 7 11 15 19 23 27 31 35 45

Sp

eed o

f evolu

tion

Rai

nfa

ll (

mm

)

WeekRainfall accumulated during 14 days SE

0

100

200

300

400

500

600

700

020406080

100120140160180200

1 6 11 16 21 26 31 36 41 46 51

Sp

eed o

f Evo

lutio

n

Rai

nfa

ll (m

m)

Week

Rainfall accumulated during 14 days SE

El Guayas, Ecuador, 1998ECV La Cuba, Baraguá Cuba,

1995

Weekly threshold for BS progressions

Sceneries

Number of BLS recurrences of stage of

evolution/year according accumulated rainfall

during 10 days

BaraguáAlquízar/ Güira

de MelenaImías Baracoa

1995 16 17 - -

A2 2030 9 11 13 10

B2 2030 5 11 9 10

A2 2060 7 11 8 11

B2 2060 8 9 9 12

Table 1. Expected recurrences of BS state of evolution

according the rainfall accumulated 14 days

described for the A2 and B2 sceneries in 2030 and

2060 and historical in 1995

In high altitude/latitude banana production areas:

Temperature will be suitable for potential BSD spread and

development at least in some periods of the year

Severity will depend on rainfall, duration of leaf wetness

(during favorable temperature periods) and management

practices

Key activities:

1. Area wide application of management practices

2. Use of resistant cultivars whenever accepted.

3. Cultural practices to foster growing, plant natural resistance, fruit quality and made environment

adverse to disease: (nutrition, sanitation, under canopy irrigation; drainage improving)

4. Weekly monitoring of: a) rate of leaves emergence, disease evolution speed, functional leaves, at

flowering and at 13 weeks after flowering; b) temperature rainfall and relative humidity.

5. Fungicide in oil mixtures applications. Rotation of fungicides belonging to different chemical

families and action mechanisms.

6. Monitoring of M. fijiensis populations sensitivity to main systemic fungicides

7. Improving application technology to get better deposit and coverage of fungicides on leaves.

INTEGRATED BSD MANAGEMENT

Effect of temperature on the growth of Fusarium oxysporum

f. sp. cubense (Foc) colonies (Batlle and Pérez, 2003)

Banana growing temperature range

Current Foc distribution in the world

Fusarium wilt spread and management

Fusarium wilt are world widely distributed

Foc growth are able in the range of temperature that banana

Cavendish banana behave susceptible under low

temperature stress to subtropical race 4 (race 1??)

Foc TR4 has been found in tropical areas but also spread to

subtropical temperate areas as Taiwan and Pakistan

Dispersal to new areas are closely related to infecting

planting material movement.

Key activities to prevent spread and damages:

1. Prevention and quarantine at countries borders

2. Adoption of in farm biosafety best practices of prevention of exotic diseases

3. Use of healthy planting material from free areas or trusted certified sources

4. Capacity building in disease recognition and contention procedures

5. Use of resistant varieties whenever available

6. Improving of soil antagonism capacity and use of crop rotation.

Virus transmitted by aphids in Musa: distribution

BBrMV. Davao, Filipinas

BBTV. Davao, Filipinas

Aphis gossypiiMyzus persicae

Ropalosiphum maidis

Pentalonia nigronervosa

Banana aphid Pentalonia nigronervosaAdapted from Robson et al. (2007). Biology of P. nigronervosa on banana.

Environmental Entomology 36 (1): 46-52

Survival rate

Nymphs/female

Survival rate

Nymphs/female

Survival rate

Nymphs/femalePopulation growth at:

20⁰C

25⁰C

30⁰C

The higher temperature will probable

reduce the rates of growth, survival

and reproduction.

Su

rviv

al r

ate

(lx)

Nym

ph

s/female/d

ay (mx)

Days

Nu

mb

er o

f ap

hid

s

Week

20⁰C

25⁰C

30⁰C

Pseudoccocus elisae

Planococcus citri

eggs

Pseudococcids (mealybugs) in bananaBanana streak virus (BSV)

Planococcus citri (vector BSV)

Planococcus figus (vector BSV)

Dysmiccocus brevipes (vector BSV)

Planococcus minor (vector BSV)

Dysmicoccus alazon

Pseudococcus adonidum

Pseudococcus comstocki

Pseudoccocus elisae

Dysmicoccus bispinosus

Saccarichocus sacchari

Meyer et al., 2002; Gonzalez et al., (2002); Javer, (2014)

Feeding damages

Planoccocus citriAdapted from: Goldasteh el al., (2009)

Arch. Biol. Sci., Belgrade, 61 (2), 329-336, 2009

74,71

45,03

45,8

29,73

18,61

22,1723,66

28,96

52,67

53,5

26,69

18,77

22,16

21,09 22,23

0

10

20

30

40

50

60

70

80

15 18 20 23 25 28 30 32

Cycle

du

rati

on

in

days

Temperature ⁰C

Females Males

Aphid transmitted viruses

Dispersal to new areas are closely

related to infecting planting

material movement (all virus).

Relative importance of CMV vector

aphid species probably will

change in tropics.

In subtropics, P. nigronervosa

most probably will still being the

most important vector

Key activities to prevent spread and damages:

1. Prevention and quarantine

2. Adoption of farm biosafety best practices of prevention of exotic diseases

3. Use of healthy planting material from free areas or trusted sources

4. Capacity building in disease recognition and contention procedures

5. Efficient sanitation, weed management as well as aphid control in the case of virus

host associated crops

6. Latency and procedures for eradication is a key factor in success of BBTV

management

Mealybugs transmitted BSV

Recent studies carried out

show the relative low

importance of mealybugs on

BSV spread (CABARE

project)

The most important factor is

the plant multiplication

procedure and use of

infected planting material

(adapted from Cubillas, 2011)

TemperatureRainfall

Week/2005

Tem

per

atu

re

(⁰C

)

Rai

nfa

ll (m

m/w

eek)

Nu

mb

er o

f re

ject

ed b

un

ches

Pentalonia nigronervosa

Pseudoccocus elisae

Fruit rejection by month with relationship to

climatic conditions in Costa Rica.

Flower thrip Frankliniella parvula)

Red spot thrip Chaetanaphothrips spp.

(Frankliniella parvula)

Chaetanaphothrips orchidii

Chaetanaphothrips signipennis

Mealybugs, aphids and thrips fruit pests Insect presence and fruit damages are a cosmetic issue, but supermarkets

manage “ZERO tolerance” of both.

Research on red rust banana thrips: abandoned after introduction of bunch

bags, impregnated with insecticide

Temperature increasing, dry weather and reduced pesticides and oil

uses will favor aphids, mealybugs and thrip spreading and presence as

well as damages in fruits.

Can become threats to organic banana production

Key activities to prevent pest spread and damages:

1. In the field

1.1 Early elimination of flowers and bunch bagging

1.2 Elimination of fruit and flowers residue on the ground to avoid pest reservoirs

1.3 Elimination of weeds and other plant hosts

1.4 Capacity building in monitoring pests, predators, parasitoids and

entomopathogens recognition and uses

1.5 Use of approved insecticides in bags and pseudostem (spinosad ?).

2. In the boxing plant:

2.1. Bunches washing with water at high pressure

2.2. Inspection and sanitation of infested fruits

Mites

Mite populations increase during the driest months of the year with warm weather

and low Rh.

Heavy rains depress populations and long draught periods are conducive to strong

attacks specially in young plants

Strong winds contribute to mite distribution

Even when there are predators, prohibitions of oil treatments will conduce to higher

incidence of this pests.

Some remarks

The future sceneries of climatic changes describing temperature

rising, lower Rh and less rainfall in tropics and more suitable

conditions for banana growing in subtropics will lead to changes

in pests behavior to take into account in pest managing strategies

The assumptions of the climatic changes effect on plant pests are

speculative due to the difficulties to validate models for future and

which effect would have on a particular pest

Uncertainness in the predictions are high and the best adaptation

change is monitoring changes and to retain innovation capacity

The foreseen sceneries of climatic changes should be included in

risk analysis of trans boundary pests

Climatic conditions described should be considered in future

research on banana pest biology and simulation studies.

Studies of banana pest behavior in areas of similar climes

(homoclimes) will help to gain future pest managing changes.

¡Thanks!

“Hacer pronósticos es muy difícil especialmente

cuando concierne al futuro”

Mark Twain