Crop insect pest modeling: What have we learned from past efforts?

icipe’s perspectives

Segenet KelemuDirector General

International Center of Insect Physiology and Ecology (icipe)

www.icipe.org

A centre of excellence in Africa — for research and capacity

building in insect science and its applications

An intergovernmental organization — charter signed by 13

countries worldwide

≈ 450 staff total (35 nationalities),

more than 100 MSc, PhD

students annually

Many contracted workers

An organization with a

unique history — 40+ years

old, genesis in Africa

General Facts

• Insects are everywhere; by far the most common creatures on our planet

• Without insects, our lives would be significantly different. Insects pollinate many of our fruits, flowers, vegetables and other plants

• Many insects are predatory or parasitic

• Primary or secondary decomposers

• Major role in the food web

• Interesting part of landscape and nature (e.g butterflies)

• They cause damage and transmit diseases (eg. mosquitoes, tsetse flies)

Why insects?

International Center of Insect Physiology and Ecology

icipe focuses on insect-based research for African challenges. That specific, tight focus was in recognition of the myriad of substantial challenges thatinsects and related arthropods pose for Africa and the tropics more generally.

General facts – where we work

Africa focused- currently activities

in 30 countries

Global collaborative work

International HQ in Nairobi

Several field stations across

Kenya & country offices in

Ethiopia, Uganda, Tanzania

Core-funding mainly from the Governments of Sweden, Switzerland, UK, Germany, & Kenya

Project funding from various national & international donor agencies, EU, Foundations,

UN organizations, World Bank etc.

Annual budget USD 45 million and growing

General facts -funding

Our Focus

Plant healthStaples, legumes, vegetables &

fruits, plantation crops

Animal healthTsetse, ticks, rift valley

fever and zoonotics

Human healthMalaria, dengue, yellow

fever

Environmental HealthBeneficials (bees, silk worms)

Common denominator insects/arthropods

Long term trials with maize-legume intercrops

Maize + Green gram

Maize + cowpea Maize +Desmodium

Maize + Beans

Khan et al. 2007. Crop Sci. 47:730-734; Midega et al. 2014. Field Crop Res.155: 144–152

Maize + Desmodium

Desmodium effectively inhibits striga in

upland rice

Rice monocrop Rice + Desmodium uncinatum

Pickett et al. 2010. Annual Review of Phytopathology 48:161–77

Insects for food and feed: Why consider this?

By 2050, global food production must double to

feed an estimated 9 billion population

Addressing this requires a clear sense of long-

term challenges and possibilities

Insects as food and feed have an important

role to play in assuring food security (van Huis,

2013):

Over 2000 species are consumed

Nutrition – contents are comparable to meat

and fish

Feed – cost & advantages with conversion

ratio

GHG emissions

Zoonosis

Water use efficiency

Organic waste conversionCirina forda

Inventory of African edible insects

Approximately 500 species of

insects are eaten across Africa

(More than 1/3 of the global list)

Central and Southern Africa

are hot spots of edible insects

There is still general dearth of

information on edible insects

from North Africa, parts of West

Africa and the Horn of Africa

Paradoxically, food security

situation in these countries

remain precarious

icipe’s Capacity Building Activities

African Regional Postgraduate Programme in Insect Science

(ARPPIS) – MSc and PHD Scholarships for African scholars

Dissertation Research Internship Programme (DRIP) –

Scholarships for scholars from all over the world

Post Doctoral Fellowships – short term (3 months) and long

term (2 years)

Internships opportunities hosted by different scientific

departments for 3 months

Institutional Development of Higher Education Institutions in

Africa through projects reinforcing the institutional capacity of

participating institutions

Dissemination of Insect Science Innovations through projects

promoting adaptive research and innovative grants

Products of icipe

Pests

• Smallholder farmers feed more than 2/3 of the population, but pests destroy 30-40% of what they grow.

• In Africa losses due to insects are estimated at 33 –100% more than the global average.

• The world population has doubled in the last 40 years and continues to rise.

• An adequate, reliable food supply cannot be guaranteed without sustainable management of pests, diseases and weeds.

Factors that govern insect spread and damage

o Insect pest biology

o Bio-ecological preferences

o Crop-pest interaction

o Pest-natural enemy interactions

o Invasiveness

o Climate Change

o Effectiveness of management strategies

Modeling can play a major role in understanding how these

factors either individually or collectively determine spread,

damage and overall productivity

Prostephanus truncatus

Globally invasive pest native to

South Western America

Invasive in Europe, Asia and

Africa, invaded Kenya in 1989

Highly polyphagous and an

efficient vector of tospoviruses

like tomato spotted wilt virus

65 -70% yield loss in crops such

as French bean

Highly resistant to pesticides (up

to 13 sprays on French bean per

season)

Phenology model

Temperature-driven phenology modeling for Western flower thrips

Life tables established at

temperature (15 - 35˚C)

Functions for various

factors such as

developmental time,

mortality, adult longevity,

total and relative

oviposition were

established

These functions were

utilized in Phenology

model building

Phenology model

Prediction based on Extrapolated daily maximum and minimum temperatures

Phenology model

LACTIN 1 model r (T) = epT- e [pk-(k-T)/∆] + λ Potent biopesticide commercialized in PPP

mode

Fungus efficacy and spore germination modeled

in relation to temperature

Temperature-driven prediction that the fungus is

largely going to be effective in the tropics

Phenology model

biopesticide development and commercialization: partnership with private sector

Partnership with private sector

Non-native and native distributional range of Bactrocera dorsalis

Ecological niche model

De Meyer, Ekesi, et al (2010). Bull. Ento. Res. 100: 35-48

Global prediction for B. dorsalis using GARP

White: predicted absence

Light green: low confidence in predicted presence

Green: high confidence in predicted presence

Dark green: higher confidence in predicted presence

Ecological niche model

De Meyer, Ekesi, et al (2010). Bull. Ento. Res. 100: 35-48

Ecological niche model

Role of modeling in classical biological of invasive pest

Tetranychus evansi, important

dry season pest of vegetables

Native to South America

Yield losses up to 90% on

tomato

Pesticide routine use is

harmful for natural enemies

Tetranychus evansi

Damage to tomato

Komi et al. 2006 Biological Control

Africa

South America

Role of modeling in classical biological control of invasive pests

Ecological niche model

Phytoseiulus longipes

Machine learning

MozambiqueZambia

Malawi

Taiwan

Diamondback moth

(DBM) is the most

damaging invasive

pest of crucifers

Diadegma.

semiclausum a

parasitoid of this pest

was imported from

Taiwan

Machine learning with

artificial neural

network (ANN) were

used for predicting

likelihood of

establishmentDiadegma. semiclausum

Machine learning

D. semiclausum at (t-1)

Rainfall

Relative humidity

Temperature

DBM at (t-1)

D. semiclausum at (t)

DBM at (t)

ANN for predicting likelihood of

establishment and efficacy of the

exotic parasitoid in cabbage and

kale farms in Kenya.

The developed ANN guided

the location of specific areas

for extending DBM biocontrol

D. semiclausum to Tanzania,

Uganda, Ethiopia,

Cameroon, Zambia, Malawi

and Mozambique

Machine learning

The ANN model predicted that the use of the parasitoid to manage DBM should

be compatible.

On the basis of this information, countrywide releases of D. semiclausum was

initiated in Kenya and the parasitoid has since established in various locations

The economic impact of this release is estimated as follows:

Parameters Economic impacts

Reduction in control cost 63%

Increase in yield of cabbage 4.7 t/ha

Benefit – cost ratio 28:1

This has also guided the location of specific areas for extending DBM

biocontrol to Tanzania, Uganda, Ethiopia, Cameroon, Zambia, Malawi and

Mozambique in a newly funded IFAD project

Macharia et al (2006) Crop Protection

● Is a repository for data collected on pests and diseases of crops bought into plant clinics

●There are over 720 plant clinics in 33 countries

● The KnowledgeBank also houses datasheets on many pests and diseases found globally, along with fact sheets to aid with integrated management of pests and diseases

●Can the clinic data be used to underpin model validation in pest and disease modelling?

● Could a simple alert system based on pest development times be enough to direct end users to the relevant information?

Plantwise KnowledgeBank

Knowledge Bank

●There are a wide variety of models in the literature relating to insect pests; often focus is on insect pest responses to set scenarios such as pesticides or resistant variety intervention, future climate change

●There are a few relating to pest development for maize pests found in Kenya

●Often a few key species are studied intensively and there is a wealth of information for these, but relatively little information for other species

●Much of the research for these pests was conducted outside Africa

●Those models available should be utilised for the benefit of a wide range of end users

Lessons learned

The various models tested at icipe have helped to:

Lessons learned

Comprehend and predict the dynamics between insect pests, antagonists and

the crop

Understand the impacts of biotic and abiotic factors on the interactions

between insect pests and their management strategies

Predict success of biological control and IPM efficacy

Conduct crop insect pests risk assessment

Understand and assess insect related ecosystem service such pollination

Understand, analyze and predict potential climate change impacts on crop

insect pests and provide management strategies

Future perspective

So far models are being developed in isolation - insect pest-based, crop-based or

other

There is the need to link pest model to crop model and finally integrate econometric

for measuring potential loss

Holistic approach: Apply system thinking approach by including crop and pest

into the overall agronomy and farming system

The more we study the major problems of

agronomy and farming system, the more

we come to realize that they cannot be

understood in isolation. They are systemic

problems, which means that they are

interconnected and interdependent

(Adapted from Kapra - Web of Life: A new

synthesis of mind and matter 1997)

ALFs = Agricultural Landscape farming