INFLUENCE OF CLIMATIC VARIABILITY ON INTEGRATED PEST...
Transcript of INFLUENCE OF CLIMATIC VARIABILITY ON INTEGRATED PEST...
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