Potential Distribution of Fall Armyworm in Africa and Beyond, Considering Climate Change and Irrigation Patterns

doi:10.21203/rs.3.rs-196606/v1

Download PDF

Research Article

Potential Distribution of Fall Armyworm in Africa and Beyond, Considering Climate Change and Irrigation Patterns

https://doi.org/10.21203/rs.3.rs-196606/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 11 Jan, 2022

Read the published version in Scientific Reports →

You are reading this latest preprint version

The fall armyworm, Spodoptera frugiperda (FAW), first invaded Africa in 2016 and has since become established in many areas across the continent where it poses a serious threat to food and nutrition security. We re-parameterized the existing CLIMEX model to assess the FAW global invasion threat, emphasizing the risk of transient and permanent population establishment in Africa under current and predicted future climates, considering irrigation patterns. FAW can establish itself in almost all countries in eastern and central Africa and a large part of western Africa under the current climate. Climatic barriers, such as heat and dry stresses, may limit the spread of FAW to North and South Africa. Future predictions suggest that FAW invasive range will retract from both northern and southern regions towards the equator. However, a large area in eastern and central Africa is predicted to have an optimal climate for FAW persistence. These areas will serve as FAW ‘hotspots’ from where it may migrate to the north and south during winter seasons and then pose an economic threat. Our projections can be used to identify countries at risk for permanent and transient FAW-population establishment and inform timely integrated pest management interventions under present and future climate in Africa.

Entomology

Spodoptera frugiperda

climate change impacts

species distribution modeling

invasive species

CLIMEX

The fall armyworm (FAW), Spodoptera frugiperda J.E. Smith (Lepidoptera: Noctuidae), is an insect pest native to the Americas that has invaded and spread throughout sub-Saharan Africa within the last four years¹. Since its introduction, FAW has emerged as a serious threat to cereal crops' productivity, such as maize and sorghum, two of the major staple food crops of smallholder farmers, thus jeopardizing food security throughout Africa^2,3. In order to contain the FAW spread, many African countries have distributed and applied synthetic pesticides. In 2017, Zimbabwe distributed nearly 102,000 liters of pesticide valued at 1.97 million US dollars to farmers⁴. Although subsidized by governments, the use of synthetic pesticides as the sole control measure is unsustainable due to their high cost, risk of increased pesticide resistance, pest resurgence, and risk to human health and the environment⁵. Hence, there is a need to develop new, more sustainable approaches to FAW management. Alternative control measures are being considered including the use of biopesticides⁶, biological control^7–9, and agroecological practices such as intercropping with legumes, push-pull system, and diversifying the farm environment^10–12. The choice and scaling of these alternative solutions depend on accurate characterization of the potential permanent and temporal distribution of FAW across the continent as well as how FAW and the agriculture production system will respond to a changing climate. Further, such information will refine our understanding of the pest’s potential migratory behavior in Africa, and is essential for developing long-term strategies to mitigate FAW infestations in hotspots (regions where FAW is endemic) as well as transient areas where FAW may move from hotspots to occupy a region for a period of favorable climate conditions.

FAW is a polyphagous pest with a wide host range, feeding on 353 plant species, including many food crops and forages and turfgrass^13,14. The most affected crops in the Americas, the native range of FAW, are maize and sorghum¹³. FAW larvae have voracious appetites and cause severe damage to plants¹⁵. The female FAW moth lays eggs on the distal part of the maize leaf. Upon hatching the first and second instar larvae feed on that leaf, but eventually they enter the leaf whorl and feed on the unfurling leaves causing extensive defoliation. As plants mature, FAW larvae often start feeding on the ear. Finally, the larvae pupate in the soil¹⁶. Pupation lasts 8–30 days until the adults emerge¹⁷. Under ideal conditions, adult moths live up to 14 days, capable of migrating to distant new areas. In warm climate, FAW completes its entire life cycle in 3–4 weeks, but in cold climate, it takes considerably longer¹⁷. Unlike other lepidopteran pests, FAW cannot survive in areas with extended freezing temperatures. It lacks any diapause mechanisms and overwinters only in warm and moist areas¹⁴. Although its year-round distribution is restricted to tropical and subtropical regions, adult moths can migrate substantial distances into temperate regions during warm summers¹⁴ and establish transient populations which can jeopardize harvests in these regions. If left unchecked, FAW in Africa has the potential to cause an economic loss of around 13 billion US dollars per year through damage to maize, sorghum, rice, and sugarcane, alone¹⁵.

Outside of the native range in North and South America, FAW was first reported in Nigeria, São Tomé and Príncipe in early 2016¹, from where it is believed to have spread to other African countries, including Kenya, Uganda, Rwanda, Ethiopia, and Tanzania. By April 2018, FAW had invaded and spread throughout sub-Saharan Africa and Sudan¹⁸. Recently, FAW has been reported in Egypt¹⁹. The presence of FAW in North Africa substantially increases the risk of FAW invasion of Europe through migration. Beyond Africa, FAW has also invaded several countries in Asia^20–23 and Australia²⁴. The rapid spread of FAW across the world may be due to trade and weak phytosanitary regulations, but also due to migratory behavior of the pest itself^25–28.

One of the major determining factors affecting pest populations and their distribution is climate, which may either directly affect the physiology of the pest or indirectly impact parasitoids or predators, competitors, and food sources^29–31. If global temperatures increase as predicted, multivoltine migratory insects such as FAW could increase their number of generations per year³² and expand their infestation range to higher latitudes and elevations. As FAW is rapidly spreading across Africa and beyond, we urgently need information about its potential invasion and establishment threat in the present and possible future climates.

Species distribution modeling is an effective method of predicting pest invasion risk and establishment potential in the region of focus. The correlative model MaxEnt and the process-based semi-mechanistic model CLIMEX are the two most popular models used to assess the risk of FAW invasion and establishment^33–41. Using the CLIMEX model, Ramirez-Cabral et al.³⁸ assessed the possible FAW distribution changes in its native ranges under climate change scenarios. This model did not distinguish between overwintering/permanent and transient FAW populations. It predicted optimal climatic suitability in northeastern states of the USA. Later, Du Plessis et al.³⁵ reparameterized the CLIMEX model and identified the FAW potential invasion and establishment areas under the historical climate conditions broadly. However, the pest's potential distribution in Africa, the most affected continent, under future climate conditions was not predicted. Yet, the knowledge of areas of habitat suitability for transient, migrant and permanent FAW populations under climate change scenarios, including irrigation pattern is necessary to enable policymakers at the national and regional levels to develop sustainable management strategies and to identify research proirities under the present and future climates in Africa and beyond. This study aims to fill this knowledge gap.

We used CLIMEX 4.0⁴², combined with eco-physiological tolerances and global occurrence records, to assess and predict the FAW invasion and establishment risk under both historical and future climate conditions, taking also the effect of irrigation into account. In addition, we performed the sensitivity analysis to test the effect of parameter changes on the modeling outcomes and identify the parameters significantly influencing the CLIMEX results for the distribution of FAW. By mapping where transient and permanent FAW populations might potentially become established, the results from this paper can support strategic decision-making.

Research model and software

CLIMEX model

FAW growth and development are primarily related to climate conditions, especially temperature patterns¹⁷. The current study used CLIMEX (version 4)⁴², a semi-mechanistic niche modeling platform, to project FAW distribution in relation to climate. The model parameters that describe the species’ response to climate were overlaid onto FAW occurrence data and climate data to project the species’ potential global distribution. Briefly, the annual growth index (GI) was used to describe the potential for FAW population growth during favorable climatic conditions, while stress indices (SI: cold, wet, hot, and dry) and interaction stresses (SX: hot-dry, hot-wet, cold-dry, and cold-wet) (Table 1) were applied to describe the probability that FAW populations could survive unfavorable conditions. The Ecoclimatic index (EI) was derived from a combination of GI, SI, and SX indices to provide an overall annual index of climatic suitability on a scale of 0 to 100⁴². An EI value of 0 indicates that the location is not suitable for the long-term survival of the species, whereas an EI value of 100 indicates maximum climatic suitability comparable to conditions in incubators. EI values of more than 30 indicate the optimal climate for a species. The climatic suitability was classified into four arbitrary categories; unsuitable for EI = 0, marginal for 0 < EI ≤ 10, suitable for 10 < EI ≤ 30, and optimal for EI > 30^38,43.

ArcGIS Software

The ArcGIS software 10.6 (US Environment Systems Research Institute - ESRI, Redlands, CA, USA) was used to visualize the result obtained from the CLIMEX analysis and calculate the areas under various EI categories for the species.

Data collection

Fall armyworm occurrence data

FAW occurrence observations (n = 304) within its native range were obtained from the Global Biodiversity Information Facility (GBIF, www.gbif.org), PestWatch (www.pestwatch.psu.edu), Butterflies and Moths of North America (BAMONA, www.butterfliesandmoths.org), and literature resources (Supplementary Table S1). Real-time occurrence records (n = 1,186) in six East African countries (Burundi, Ethiopia, Kenya, Rwanda, Tanzania, and Uganda) were collected from the Community Based FAW monitoring forecasting and Early Warning (CBFAMFEW) system^44,45. The CBFAMFEW system relies on pheromone traps, field scouting and mobile applications for field data collection. Briefly, FAW pheromone traps were established in five districts in each country and, in each district, 10 villages were sampled under the coordination of two community focal persons. Thus collected FAW occurrence records were validated by national FAW focal persons and published in FAMEWS (Fall Armyworm Monitoring and Early Warning System) global platform^44,45.

The additional records of FAW occurrence were obtained from PlantVillage FAMEWS survey. PlantVillage is a public good platform that integrates AI, satellites, cloud computing, and local networks to help smallholder farmers adapt to climate changes and increased pest pressure.

Overall, a total of 13,460 FAW global distribution records with either pheromone trapping (with confirmed FAW moth) or field scouting (with confirmed FAW larvae) data were collected. To make data visualization and manipulation easier, FAW occurrence records were spatially filtered to retain a single record in each 10-arc minute grid. This resulted in 2,207 records (Africa – 1,830, Asia − 150, North America − 171 and South America − 56) used for further analysis. The distribution records used in this study are shown in Fig. 1.

Climate data

The current suitability of FAW was modeled with the CliMond historical dataset interpolated at 10-arc minute (~ 18 km) (available at https://www.climond.org)⁴⁶. This dataset consisted of long-term averages centered at 1975 for maximum and minimum temperatures, precipitation and relative humidity at 09:00 and 15:00 hours. Future climatic suitability for FAW was predicted using the 10-arc minutes gridded spatial resolution climate data for 2030, 2050, and 2080 retrieved from the CliMond (Version 2) in CLIMEX format⁴⁶. The future climate projections used in this study were based on two global climate models (GCM), CSIRO-Mk3.0 GCM developed by CSIRO Atmospheric Research, Australia⁴⁷ and MIROC-H GCM developed by Center for Climate Research, Japan. These were run with the A1B SRES (Special Report on Emission Scenarios) emission scenarios. The SRES A1B was chosen with the assumption that, in the future, the use of fossil intensive and non-fossil energy sources will be balanced. For an A1B emission scenario, the CSIRO-Mk3.0 and MIROCH-H GCMs predict a rise in temperature of 2.11 ˚C and 4.31 ˚C, respectively, by the end of 21st century^46,48. Similarly, these two GCMs predict different rainfall patterns⁴⁹.

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) released a new family of emission scenario called Representative Concentration Pathway (RCP), to replace the SRES family. This consists of four-climate change scenarios- RCP2.6, RCP4.5, RCP6 and RCP8.5. The closest similar RCP scenario to SRES A1B is RCP 6.0, which represents an intermediate emission scenario⁵⁰. The temperature increase at the end of twenty-first century for RCP6.0 scenario is projected to be 2.2˚C with a range of 1.4–3.1˚C, while for SRES A1B scenario, it is projected to be 2.8˚C with a range of 1.7-4.4⁵¹. Furthermore, the CO2 concentration by the end of the century for RCP6.0 is expected to reach 670 ppm, just below A1B (703 ppm)⁵⁰.

Irrigation data

The information on global irrigation areas was derived from the Food and Agriculture Organization of the United Nations (http://www.fao.org/aquastat/en/geospatial-information/global-maps-irrigated-areas/).

Host crops data

Geographic distribution of maize and sorghum, two major host crops of FAW, were obtained from the EarthStat database (http://www.earthstat.org/) created by Monfreda et al.⁵².

Model fitting

Using the “Compare Locations” modules in CLIMEX, the values of FAW parameters (Table 1) were determined (i) from previous studies’ findings on requirements for growth and development of FAW^53–56, and (ii) by fitting the projected distributions to the occurrence records of FAW in the world. We initially adopted parameter values from a previously conducted CLIMEX study on FAW^35,38. Then, parameter values were determined through an iterative process to fit the simulated CLIMEX results to the known distribution of FAW in the world in 2020. FAW occurrence records in North America include reports of transient/migrant populations (Supplementary Table S1). Therefore, during the model fitting process, we confirmed that the areas with migrant populations have a positive annual growth index (GI > 0) and an unsuitable eco-climatic index (i.e. EI = 0)^57,58. The process of parameter fitting was repeated until the reliability and consistency of the model predictions were established. The parameter values used in this study are listed in Table 1, and details are provided in the following sections.

Growth indices

Temperature index (TI)

The lower (DV1) and upper (DV2) optimal temperatures for FAW population growth were left unchanged at 25 ˚C and 30 ˚C, respectively³⁵. These values are supported by multiple publications^53–56. FAW reared at 25 ˚C constant temperature are less likely to emerge deformed⁵⁵, and the adult moths have the highest adult longevity and fecundity⁵³. A recent study by Du Plessis et al.¹⁷ identified 30 ˚C as the upper optimal temperature for FAW growth and development. The development rate of FAW increases linearly with increasing temperature from 18 ˚C to 30 ˚C, but declines when temperature increases above 30 ˚C¹⁷.

The limiting low temperature (DV0) was also kept the same at 12 ˚C^35,38. FAW lacks any diapause mechanisms and overwinters only in warm and humid areas; hence, FAW cannot tolerate freezing temperature¹⁴. Wood et al.⁵⁹ reported that a temperature above 10 ˚C is required for pupal eclosion. The pupae held at 10 ˚C live for 50–62 days but do not eclose^55,59.

The limiting high temperature (DV3) was set at 36 ˚C because more than 50% of FAW reared at 35˚C or above exhibit physical deformity and die within 24 hours of emergence⁵⁵.

Moisture index (MI)

Not much is known about the relationship between soil moisture and the FAW lifecycle, so we adopted the species parameters from previous studies^35,38, with some assumptions. The lower soil moisture threshold (SM0) was kept the same at 0.15 to allow FAW invasion in semi-arid areas in Africa. Silvain & Ti-A-Hing⁶⁰ reported higher FAW populations (both adult moths and larvae) during rainy seasons than in the dry seasons. At any time, the larval population is affected by the amount of rainfall that was experienced three weeks earlier⁶⁰. Although a heavy downpour reduces adult emergence by trapping moths in their pupation tunnel⁶¹, FAW larvae can tolerate substantial waterlogging conditions³⁵. Therefore, the upper soil moisture threshold (SM3) was set to 2. Reducing the value of SM3 from 2.5 to 2 had no effect on defining the potential range of FAW. The lower (SM1) and upper (SM2) limits for optimal growth were left unchanged at 0.8 and 1.5, respectively³⁵. The upper optimal soil moisture (SM2) value allows the persistence of FAW in tropical areas that experience high rainfall, such as Central America. Here, the SM value 0 indicates no soil moisture; SM 0.5 indicates soil moisture is 50% of soil water holding capacity, and SM > 1 indicates a run-off situation.

Stress indices (SI)

CLIMEX mainly uses four stress indices (SI: heat, cold, wet, and dry) to determine the species' geographical distribution. Species population growth occurs between the temperature parameters DV0 and DV3, and moisture parameters SM0 and SM3 (Table 1). Values outside of this range result in negative population growth.

Cold Stress (CS)

The cold stress temperature threshold (TTCS) and cold stress accumulation rate (THCS) was decreased to 8ºC and − 0.005, respectively, to fit the FAW distribution in the Reo Grande valley Texas (overwintering site in North America), Mediterranean coast in North Africa and the Yunnan province (first FAW-invaded province) in China.

Heat Stress (HS)

The heat stress temperature threshold (TTHS) for HS was kept the same at 39ºC to allow pest development in western African countries³⁵. Heat stress accumulation rate (THHS) was set to 0.0025 week^− 1 to allow the pest development in Nile river basins in Egypt and irrigated areas in Yemen and Pakistan.

Dry Stress (DS)

Dry stress indices were the same as those of the existing model of Du Plessis et al. ³⁵. Soil moisture dry stress threshold (SMDS) was set to the same value as SM0, i.e. 0.15, and dry stress rate (HDS) was set to 0.005.

Wet Stress (WS)

Soil moisture threshold for wet stress (SMWS) was set at the same value as SM3 in our model. The wet stress accumulation rate (HWS) was increased to 0.01 week^− 1to exclude extremely wet areas from being suitable. This change does not limit the FAW persistence in areas with known FAW distribution but reduces the modeled risk in extremely wet areas.

Effective Degree-Days (PDD)

In CLIMEX, the PDD parameter indicates the degree-day above the minimum base temperature (DV0) necessary for species to complete one generation. Hogg et al.⁶² estimated PDD for FAW at 346.2 degree-days with base temperature of 13.8˚C while Du Plessis et al.¹⁷ calculated PDD value of 390 degree-days with base temperature 12.57˚C. In the current study, the base temperature was set at 12˚C. To get the same number of generations per year, PDD value was increased to 400-degree days.

Table 1. CLIMEX parameter values used for modeling the distribution and invasion risk of FAW (Spodoptera frugiperda)

	Parameters			Ramirez-Cabral et al. 2017	Du Plessis et al, 2018	Current study
	Temperature
	DV0	Lower temperature threshold (˚C)		12	12	12
	DV1	Lower optimal temperature (˚C)		22	25	25
	DV2	Upper optimal temperature (˚C)		27	30	30
	DV3	Upper temperature threshold (˚C)		34	39	36
	Soil Moisture
	SM0	Lower soil moisture threshold		0.1	0.15	0.15
	SM1	Lower optimal soil moisture		0.7	0.8	0.8
	SM2	Upper optimal soil moisture		0.9	1.5	1.5
	SM3	Upper soil moisture threshold		1.5	2.5	2.0
	Cold stress
	TTCS	Cold stress temperature threshold (˚C)		8	12	8
	THCS	Cold stress accumulation rate (week^-1)		-0.00001	0.001	-0.005
	Heat stress
	TTHS	Heat stress temperature threshold (˚C)		38	39	39
	THHS	Heat stress accumulation rate (week^-1)		0.001	0.005	0.0025
	Dry stress
	SMDS		Soil moisture dry stress threshold	0.1	0.1	0.1
	HDS		Dry stress accumulation rate (week^-1)	-0.001	-0.005	-0.005
	Wet stress
	SMWS		Soil moisture wet stress threshold	1.5	2.5	2
	HWS		Wet stress accumulation rate (week^-1)	0.001	0.002	0.01
Threshold Annual Heat sum
PDD			Minimum degree day sum needed to complete a generation	559	600		400
Irrigation (mm day^-1)				No	2.5		2.5

Changes made to the Du Plessis et al.³⁵ parameter values are given in bold.

Irrigation

FAW was reported in dry areas in North Africa, Pakistan and Yemen. These areas did not fall within the climatic suitable areas projected under natural rainfall conditions. These dry area records might reflect FAW populations able to persist only when irrigation is applied to sustain the crop. To simulate the effect of irrigation in FAW distribution, two irrigation scenarios were taking into account. First, the CLIMEX model for FAW was run using 2.5mm day^− 1 as top-up irrigation throughout the year (Irrigation scenario I) to capture the risk posed by FAW in areas where cropping should be sustained by irrigation. Second, a composite FAW-risk map was developed by combining the natural rainfall and irrigation scenario I results; EI from irrigation scenario I was mapped in areas under irrigation reported by Siebert et al.¹⁷ and EI for natural rainfall scenario was mapped elsewhere.

Parameter sensitivity and model uncertainty analysis

CLIMEX model is a robust tool to assess the risk of pest invasion and establishment, but it includes several sources of uncertainty that need to be communicated to risk assessors and decision makers. The CLIMEX Version 4 has the parameter sensitivity and model uncertainty analysis tool available to evaluate the model. The sensitivity analysis identifies the degree to which each species parameter affects the projected areas of climatic suitability. Whereas uncertainty analysis reflects the ability of the model to accurately predict the climatic suitability for a species. For the parameter sensitivity and uncertainty analysis, the default model parameters were run using the historic climate (CM10 1975H V1.2) under the natural rainfall scenario. Both parameter sensitivity and model uncertainty analysis were run for the entire world.

FAW global potential geographical distribution under current climate

The potential projected global geographical distribution of FAW, ignoring the distribution of crop hosts and non-climatic barriers, corresponded well with the known present distribution of this species. The result shows that most of the world's tropical and subtropical climates are climatically suitable for year-round FAW establishment (with EI > 30) (Fig. 2). This area increases substantially when looking at seasonal FAW population growth (with GI > 0): our model predicts that areas with humid-continental and Mediterranean climates have the potential to support FAW population growth during sometime of the year (Supplementary Fig. S1).

The model predicted a significance difference in the potential distribution of FAW between irrigation scenario-I and the natural rainfall scenario, especially in North Africa, Middle East and Australia (Fig. 2). Many parts of North Africa and the Middle East become climatically suitable for FAW population establishment, when irrigation is available in these areas.

Native range

Potential FAW distribution in the Americas, native range, is consistent with its known geographical range. The model confirmed that FAW over-wintering locations in the Americas are climatically suitable (with EI > 30) for the persistence of the FAW populations (Fig. 2). Furthermore, our model predicted the expansion of the FAW geographical range to the eastern parts of North America with humid-continental and humid-subtropical climates during favorable seasons (with GI > 0, EI = 0) (Fig. 2 and Supplementary Fig. S1). In South America, the entire continent, except the Andes region and southern-most tip, has an optimal climate for FAW establishments.

Non-native range

Almost all areas in Africa, the non-native range, with known presence records were projected to be climatically suitable (with EI > 30) for FAW population persistence under natural rainfall conditions (Fig. 2a). A few occurrence records in North Africa did not fall into the region predicted as suitable by the model. However, irrigation is used to sustain agriculture in those areas⁶³. All of these locations become suitable when the irrigation scenario II is included in the model (Fig. 2c). About 27% of Africa's total area is predicted to have an optimal climate, nearly incubator-like conditions, for FAW population establishment, under irrigation scenario II (Fig. 2c). In eastern and central Africa, all countries except Somalia, Eritrea and Chad were predicted to have medium to optimal climatic suitability for FAW population establishment and are under high risk. In western Africa, Guinea, Sierra Leone, Liberia, Cote d'Ivoire, Ghana, Togo, Benin, Nigeria, Sao Tome and Principe were also predicted to potentially support year-round FAW populations. North African countries with tropical and subtropical desert climates were projected to be most unsuitable, with only irrigated areas and areas along the Mediterranean coast projected to have marginally suitable climates for FAW persistence. Heat and dry stresses would limit population establishment and growth in North African countries under the current climate (Fig. 3). Similarly, the Indian Ocean coast in South Africa is the only area in southern Africa that has an optimal environment for FAW persistence. Other parts in this region were not predicted to support FAW population establishment due to dry and cold stress (Fig. 3b & d). However, availability of irrigation would render these dry areas suitable for FAW invasion and population growth (Fig. 2b).

Although Europe has an unsuitable climate for FAW year-round establishment (Fig. 2), a few areas with humid-continental and Mediterranean climates are potentially suitable to support migrant FAW populations (with GI > 10) for a few generations per year (Supplementary Fig. S1). The risk of FAW invasion in Europe has become increasingly possible considering that FAW presence has recently been reported for Egypt and Mauritania. Furthermore, since extensive areas of host crop plants are readily available in southern Mediterranean Europe (Supplementary Fig. S1d), these areas have potential to support transient populations under the current climate. Small regions of southern Italy, Spain, and Portugal have moderately suitable to marginal climates for FAW year-round establishment, and these areas could be expected to be invaded first, as FAW has already reached the Nile Valley in Sudan, Egypt, and Mauritania. Yet, low winter temperatures in the majority of Europe would limit population growth and establishment under the current climate (Fig. 3b).

FAW invasion has been confirmed in many countries in Asia in early 2018^20–23. There is a considerable chance that FAW will extend beyond its current range in Asia. Based on historical climate data, South East Asian and South Asian countries have optimal climate conditions for FAW population establishment (Fig. 2). In addition, areas in southeast China with a humid subtropical climate are also optimal for FAW population establishment. When weather is favorable, FAW could migrate seasonally to maize-growing areas with unsuitable/ marginal climates for seasonal population establishment (Supplementary Fig. S1).

A large part of Australia is unsuitable for FAW persistence because it has a tropical and subtropical desert climate. However, areas with tropical wet/dry climate are projected to range from moderate to optimally suitable for FAW persistence (Fig. 2), and regions with humid-subtropical climate are moderately suitable and have the potential to support migrant FAW populations only (Supplementary Fig. S1).

FAW projection under future climate conditions

The predicted FAW distributions in Africa under CSIRO-Mk3.0 and MIROC-H GCMs using the A1B scenario for 2030, 2050, and 2080 are shown in Fig. 4. The future scenarios project the gradual loss of climatically suitable areas for FAW population establishment and persistence in Africa. Although both GCMs project similar trends, the reduction in climatic suitability was more widespread under CSIRO-Mk3.0 than under MIROC-H GCM (Table 2, Fig. 4, and Supplementary Fig. S3).

For 2030, both CSIRO-Mk3.0 and MIROC-H GCMs predicted a reduction of approximately 2% in areas with optimal climatic suitability, with a shift from optimal to medium/marginal suitability. All currently suitable countries in West Africa were predicted to gradually retract from the optimal range for FAW by 2030, and many countries lose it by 2080 due to heat and dry stress (Figs. 4 & 5). Areas of optimal suitability are also predicted to decrease in countries, such as South Sudan and Mozambique. For the remaining countries with current climatic suitability, the predicted changes in climate for the next 10 years would not affect their FAW suitability. Some areas in Angola, Zambia, Zimbabwe, and Tanzania currently classified medium suitable category increased to optimal in the warmer future climates.

The modeled projections of climatic suitability for 2050 under the two GCMs indicated slight differences. The predicted decrease in area with optimal suitability was higher under the CSIRO-Mk model (5.5%) than predictions under the MIROC-H model (3.7%). While all the currently suitable countries (except Angola, Zambia, and Zimbabwe) lose optimal to medium suitability, the reduction is significant in Eastern and West African countries (Supplementary Fig. S3). There would be no or very little change in the suitability of areas in Central African countries, such as Cameroon, Equatorial Guinea, Gabon, Congo, and the Democratic Republic of Congo. In Eastern Africa, Uganda, Rwanda, and Burundi are the only countries with optimally suitable climates throughout the countries by 2050 under both GCMs.

The projections under both GCMs show a reduction in climatic suitability, changing from optimal to marginal by 2080, for African countries south of the Sahara and north of the Kalahari Desert. The CSIRO-Mk3.0 model predicted larger decreases in areas of optimal suitability, with a 10% reduction, compared with only a 4% reduction under MIROC-H. Under both models, nine countries –Senegal, Mali, Niger, Sierra Leone, Burkina Faso, Chad, Togo, Benin and South Sudan – showing current optimal to medium climatic suitability, will no longer support or marginally support FAW year-round persistence by 2080. The region where the suitability would be least affected by predicted climate changes under the MIROC-H model is central Africa, except Chad and the Central African Republic.

Table 2. Areas subject to projected eco-climate suitability for FAW (Spodoptera frugiperda) persistence under current and future projected climates.

	EI under current climate scenario		Percentage change in areas under future projected climate from the current climate
	Total area (10^6 Km2)	Percentage	CSIRO-Mk3.0			MIROC-H
	Total area (10^6 Km2)	Percentage	2030	2050	2080	2030	2050	2080
Optimal	8.9	26.8	-2.4	-5.5	-11.6	-1.8	-3.7	-7.2
Suitable	5.5	16.4	-0.8	-1	0.3	0.2	-0.2	-0.8
Marginal	4.7	14	1.7	2.2	1.3	1	2.3	3.7
Unsuitable	14.3	42.8	1.5	4.4	10	0.6	1.6	4.3

Note: The percentage values for future projected climate are the percentage change in these areas under future projected climate from the current climate.

Under the climate change scenario, the current potential range of FAW is expected to decrease mainly due to heat and dry stress in Africa (Fig. 5). Hot and dry summers will create stressful conditions that prevent FAW from completing its life cycle and persisting year-round in areas that are now suitable for year-round persistence. However, there is still a chance that FAW escapes the heat and dry stress during hot summers by migrating to Central and Eastern Africa and reinvading the marginal/unsuitable areas during the warm winter season in each year.

Those countries that lie along the equator will likely support the long-term persistence of FAW populations and experience a stable risk throughout the year (Fig. 4). These areas include parts of Ethiopia, Kenya, Uganda, Rwanda, Burundi, Tanzania, Zimbabwe, Zambia, Angola, Democratic Republic of Congo, Republic of Congo, Gabon, Equatorial Guinea, and Madagascar. These areas could also serve as FAW hot spots from where FAW migrate each year to re-infest a succession of cropping areas in other regions with marginal/suitable growth index (GI > 0) but unsuitable eco-climatic index (i.e. EI = 0) (Supplementary Fig. S2).

Parameter sensitivity and model uncertainty

The potential distribution of FAW modeled using the recent CLIMEX model is highly sensitive to change in cold stress temperature threshold (TTCS) and limiting low moisture (SM0), with 1 and 0.8% impact, respectively (Supplementary Table 2). Other parameters have less than 0.5% sensitivity to the predicted potential range, suggesting that TTCS and SM0 were the fundamental parameters for fitting the model simulation into the actual distribution.

The model uncertainty analysis indicates that there is a greater degree of geographical uncertainty about the ability of FAW to persist in drier areas (e.g. Sub-saharan Africa, Australia and the Middle East) than colder areas (e.g. USA and Mexico, Southern China) (Fig. 6).

The global geographical distribution of FAW projected with CLIMEX model closely matched the current distribution of FAW. The model set out to predict areas where FAW populations could establish themselves permanently; that is, their presence is year-round with multiple generations. Based on the CLIMEX projections under present climate conditions, the world’s tropical and subtropical climates are suitable for the year-round establishment of FAW, whereas temperate climates are at risk of seasonal invasions. In Africa, a large part of east, west and central Africa (i.e. 57.2% of the total area) is currently suitable for FAW population establishment. In the future, areas of climatic suitability for FAW establishment are expected to gradually decrease over time mainly due to heat and dry stress. However, FAW may still survive and become established in significant areas in Africa (i.e. 47.2% and 53% of the total area under the CSIRO-Mk3.0 and MIROC-H GCMs, respectively) by the end of 2080. If certain conditions are met, these established persistent populations, could, in turn, serve as a source of seasonal invasions and migrate into less favorable climatic regions. Therefore, it is likely that FAW will establish permanent populations and cause substantial damage and economic losses to certain crops production every year in Africa unless FAW population can be effectively managed.

Our CLIMEX model projects that, under the current climate, there is an increased risk of global FAW invasion and establishment. Outside of its native range in North and South America, the current climatic conditions in many parts of Africa, South and South-East Asia, southeastern parts of China, the north coast of Australia, and a few pockets in Europe are favorable for FAW invasion and establishment. Until 2016, FAW was confined to areas with a subtropical wet/dry climate in the Americas. After invading Africa in 2016, FAW has spread rapidly throughout vast regions of Africa that have a climate similar to its native range. By 2020, FAW has further spread to the Middle East, South Asia, South East Asia, and Australia^18,24. While FAW has not yet invaded Europe, our model identifies several pockets in Europe that are climatically suitable for FAW invasion, suggesting that FAW has not reached its full potential range and its range is still expanding.

The model suggests that extreme temperatures, cold winters and hot summers, as well as limited soil moisture, are the most critical factors constraining the survival of FAW. Currently, cold stress limits FAW’s potential to permanently establish in northern North America, southern parts of South America, the northern part of Asia, and Europe. Presently, the permanent establishment of FAW in these regions is not possible because FAW does not diapause¹⁴. However, if global temperature increases as predicted, some areas currently classified as climatically unsuitable may become suitable for FAW invasion and establishment in the future. Expansion towards the north has already been reported for several invasive insect species under climate change^64,65.

Similarly, dry stress limits FAW’s establishment in North African countries, the Middle East, and a large part of Australia. In the future, these areas are predicted to experience a reduction in total annual rainfall and would not be expected to support FAW populations. However, irrigated crop fields in these areas could support seasonal FAW populations during warm winters.

In Africa, central, eastern, and western African countries with sub-tropical wet/dry climates offer optimal conditions for FAW population establishment and are under high risk. These areas could serve as overwintering areas and sources of seasonal invasions to other parts of Africa, in the same way, that southern Florida, Texas, and Mexico serve in North America²⁸. The predicted FAW overwintering areas in the present study are consistent with those in previous studies^35,26. Further, the projected climatic suitability for FAW also closely matches the predicted distribution of maize, its preferred host under current and future climates (see Ramirez-Cabral et al.⁴³ for global distribution maps of Zea mays), which further enhances the probability of FAW to invade and even establish persistent populations in the areas projected by our model.

In Africa, the northern part of FAW's current distribution is currently limited by extreme heat and dry stress. The permanent establishment of FAW in this region is unlikely, as FAW cannot tolerate extreme heat^53–55. However, microclimates near maize growing areas in the Nile River basins and irrigated zones could provide channels of suitable habitat⁶⁶ and support the establishment of FAW permanent populations. In addition, a small portion of the Mediterranean coast in North Africa is suitable for FAW persistence but has not yet been invaded. The arrival of FAW in those areas by its means is unlikely because FAW has to migrate across the Sahara and face these harsh desert conditions. Yet, since FAW has already invaded the humid irrigated zones of Aswan Governorate in South Egypt¹⁹, we should not rule out the possibility of seasonal invasion of the north through natural migration. Migrant FAW moths could use maize fields along the Nile River basins as ‘stepping-stones’ before finding a suitable location along the North African coast. The flight biology of FAW in North America suggests that it can complete such a long-distance migration²⁸. The establishment of significant populations along the North African coast and the Nile River basin will increase the threat to North Africa and Europe through seasonal migration⁶⁷. The risk posed by migrant FAW populations north of the Sahara should not be ignored, since a similar scenario occurs in North America where the climate also does not support FAW establishment, yet crops are still devastated by seasonal invasions of FAW²⁸.

Furthermore, several pest species have crossed unfavorable geographic barriers by ‘piggybacking’ on human transit routes. Therefore, intra-continental travel and trade increase the risk of FAW introduction to the North African coast and Europe^26,27. Rwomushana et al.⁴ reported several interceptions of FAW in consignments from Africa. Therefore, to prevent travel-assisted introduction of the FAW in these places, close monitoring of the FAW invasion and activity in North Africa as well as adopting strict phytosanitary measures are and will continue to be necessary. In addition, pest species, including FAW, can move long distances aided by meteorological phenomena such as storm fronts⁶⁸. While the present study did not consider it, an analysis of synoptic and mesoscale wind and storm patterns may be useful, especially since these patterns are predicted to change over time.

The climate around the globe is changing, and the distribution of areas climatically favorable to FAW persistence will change accordingly. Our results suggest that under future climate scenarios, the projected distribution of FAW in Africa will contract in both northern and southern regions towards the equator. These findings are in line with the results of a previous study, which also predicted a decrease in climatically suitable areas in the Americas under the climate change scenario³⁸. These range contraction predictions are similar to those made for its preferred host, Z. mays⁴³. The predicted decrease in suitable climate in the northern and southern range in Africa is due to a significant increase in heat and dry stress caused by increased temperatures. During hot and dry summers, FAW pupae do not generally hatch, and if hatched, their ability to fly and search for mating partners is compromised^55,56. Similarly, exposure to high temperatures for extended periods also significantly reduces fecundity and increases mortality in FAW⁵³, leading to population decline in formerly suitable areas. However, these areas could be re-infested every year from migrant populations, accordingly resulting in potential damage.

Our model predicted a high risk of the permanent establishment of FAW in Africa. The year-round availability of host plants and warm and moist winters is optimal for FAW populations' long-term persistence in Africa. Although hot summer temperatures are likely to exclude the FAW from the warm habitat in humid-tropics in Africa, the overwintering populations in sub-tropical wet/dry climate areas could re-infest these areas every year during favorable seasons. Records of FAW occurrence in hotter and dryer areas than those in its native regions suggest that FAW is extremely heat-tolerant, more so than we thought in the past. Since there are no detailed studies on FAW biology and ecology in Africa, we used temperature-dependent life history data from the studies conducted in the Americas during the 1960s-1990s to predict infestation areas with suitable climatic conditions. However, FAW may have adapted and become more heat tolerant than previously reported. Therefore, any change in the insect's ability to survive in extreme climate conditions (in this case, tolerance to dry and heat stress) would expand the predicted range of distribution. Hence, further studies are necessary to assess FAW's biological and ecological adaptation to the African continent.

The geographic distribution of FAW is determined by biotic interactions, abiotic factors, and its active or passive movementv⁶⁹. This study focuses on abiotic factors for temperature-dependent life history events to map climatically suitable areas for FAW because abiotic factors such as climatic variables are considered prime factors affecting species distribution at the continental and global scales. At these large scales, the results from the bioclimatic models alone are sufficient to suggest which regions are at high risk pest invasion and establishment under future climates⁷⁰. Consequently, we examined the influence of climate change only on FAW's range of invasion and establishment.

Biotic factors should be incorporated in the bioclimatic model results to provide a more refined understanding of the species distribution under changing climates⁶⁹. FAW requires a suitable place to live and complete its lifecycle over several generations. FAW also requires an adequate supply of host plants in synchrony with its lifecycle, without which it cannot persist in that environment. Furthermore, FAW's interactions with other species, such as natural enemies and competitors in a particular region, affect species distribution. Unfortunately, at this point combining all these factors in the bioclimatic model would increase the complexity and is not currently possible^69–70.

The projected distribution of the FAW in Africa has indicated that FAW will severely impact agriculture over the next several decades. Insect pest management will be more challenging in a changing climate since climatic factors affect the timing of pest infestation, host preference, the efficacy of chemical and biological measures of control, and their utilization within integrated pest management strategies⁷¹. In this case, modeling/predicting habitat suitability for the pest under current and future climatic conditions provides robust tools and recommendations across multiple stakeholder levels and geographical scales. The current study will guide farmers, extension agents, researchers, policymakers, and public and private sectors to develop risk assessment protocols and climate-smart pest management strategies to prevent/reduce the economic loss due to FAW.

The FAW poses a considerable threat to farmers worldwide, and the establishment of its occurrence is crucial in enhancing preparedness, particularly selecting appropriate pest management control. Since FAW performance and survival is limited by temperature and humidity, we constructed a model that predicts areas suitable for FAW occurrence under current and future climate conditions. Two fundamentally different scenarios have to be considered: areas, where FAW persist year-round with multiple generations per year, and areas where seasonal invasions starting from persistent populations, can occur. Under current climatic conditions, FAW has not yet reached all areas where it could potentially establish year-round populations, and therefore also not all areas that it can occasionally or seasonally invade. Under predicted global temperature increases, the optimal areas for FAW persistence will shrink and, with them, the areas of seasonal invasions. Our model does not consider the multitudes of biotic interactions. However, it appears that at least the distribution of maize, FAW’s preferred host plant, follows a similar pattern, which means that under future climatic conditions successful cultivation of maize will require successful management of FAW populations.

Acknowledgements

We thank FAO and PlantVillage, which made the data used in this paper freely available, and Armen R. Kemanian for providing suggestions on the model run. We are grateful to the Graduate School and International Agriculture and Development (INTAD) program at Pennsylvania State University, PA, USA, for providing financial support to conduct this study. The authors express their gratitude to farmers, extension agents and all technical staff members involved in the data collection in the different countries. USAID/OFDA contributed to the national capacity that enabled the data to be generated. We also gratefully acknowledge the financial support for the core research agenda of ICIPE by UK Aid from the UK Government; the Swedish International Development Cooperation Agency (SIDA); the Swiss Agency for Development and Cooperation (SDC); and the Government of Kenya.

Author Contributions:

B. P. T.: Conceptualization, Methodology, Spatial data analysis, Modeling, Writing original draft, Review & editing. S. N.: Conceptualization, Methodology, Writing, and Review & editing. E. K.: Spatial Data Analysis and Maps development. E. M. A-R: Methodology, Data Analysis, Modeling, Review & editing. I. S-A: Writing, Review & editing. M.W: Spatial Data Analysis, Review & editing. H. E. Z. T: Spatial Data Analysis, Modeling, and Review & editing. S. E.: Review, Resource mobilization. D.P.H.: Methodology, Review & Editing. E. G. R.:Conceptualization, Supervision, and Review & Editing. S. S.: Conceptualization, Methodology, Resource Mobilization, and Review & Editing

Goergen, G., Kumar, P. L., Sankung, S. B., Togola, A. & Tamò, M. First report of outbreaks of the fall armyworm Spodoptera frugiperda (J E Smith) (Lepidoptera, Noctuidae), a new alien invasive pest in West and Central Africa.PLoS ONE11, (2016).
Devi, S. Fall armyworm threatens food security in southern Africa. The Lancet. 391, 727 (2018).
FAO. FAWRisk-Map 1.1. FAW food insecurity risk, http://www.fao.org/emergencies/resources/maps/detail/en/c/1110178/ (2018).
Rwomushana, I. et al. Fall armyworm: impacts and implications for Africa. Evidence note update. (Center for Agriculture and Bioscience International-CABI, 2018).
Togola, A. et al. Measurement of pesticide residues from chemical control of the invasive Spodoptera frugiperda (Lepidoptera: Noctuidae) in a maize experimental field in Mokwa, Nigeria. Int. J. Environ. Res. Public Health. 15, 849–860 (2018).
Akutse, K. S. et al. Ovicidal effects of entomopathogenic fungal isolates on the invasive Fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae). J. Appl. Entomol. 143, 626–634 (2019).
Laminou, S. A., Ba, M. N., Karimoune, L., Doumma, A. & Muniappan, R. Parasitism of Locally Recruited Egg Parasitoids of the Fall Armyworm in Africa. Insects. 11, 430–443 (2020).
Sisay, B. et al. First report of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), natural enemies from Africa. J. Appl. Entomol. 142, 800–804 (2018).
Sisay, B. et al. Fall Armyworm, Spodoptera frugiperda, Infestations in East Africa: Assessment of Damage and Parasitism. Insects. 10, 195–205 (2019).
Hailu, G., Niassy, S., Zeyaur, K. R., Ochatum, N. & Subramanian, S. Maize-legume intercropping and push-pull for management of fall armyworm, stemborers, and striga in Uganda. Agron. J. 110, 2513–2522 (2018).
Harrison, R. D. et al. Agro-ecological options for fall armyworm (Spodoptera frugiperda JE Smith) management: Providing low-cost, smallholder friendly solutions to an invasive pest. J. Environ. Manage. 243, 318–330 (2019).
Midega, C. A. O., Pittchar, J. O., Pickett, J. A., Hailu, G. W. & Khan, Z. R. A climate-adapted push-pull system effectively controls fall armyworm, Spodoptera frugiperda (J E Smith), in maize in East Africa. Crop Prot. 105, 10–15 (2018).
Montezano, D. G. et al. Host Plants of Spodoptera frugiperda (Lepidoptera: Noctuidae) in the Americas. Afr. Entomol. 26, 286–300 (2018).
Sparks, A. N. A review of the biology of the fall armyworm. Fla. Entomol. 62, 82–87 (1979).
Abrahams, P. et al. Fall armyworm: impacts and implications for Africa. Evidence note (2) (Center for Agriculture and Bioscience International-CABI, Sept 2017).
van Huis, A. Integrated pest management in the small farmer’s maize crop in Nicaragua [Doctoral dissertation]. (Wageningen University & Research, Wageningen, Netherland, 1981).
Du Plessis, H., Schlemmer, M. L. & Van den Berg, J. The effect of temperature on the development of Spodoptera frugiperda (Lepidoptera: Noctuidae). Insects. 11, 228–239 (2020).
FAO. Map of areas affected by fall armyworm. http://www.fao.org/emergencies/resources/maps/detail/en/c/902959/ (2020).
IPPC. Reporting fall armyworm (Spodoptera frugiperda) in Egypt. IPPC official pest report no. EGY-01/1. FAO Rome, Italy. https://www.ippc.int/ (2019)
Bhusal, K. & Bhattarai, K. A review on fall armyworm (Spodoptera frugiperda) and its possible management options in Nepal. J. Entomol. Zool. Stud. 7, 1289–1292 (2019).
Navasero, M. V. et al. Detection of fall armyworm Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) using larval morphological characters, and observations on its current local distribution in the Philippines. Philipp. Entomol. 33, 171–184 (2019).
Sharanabasappa, D. et al. First report of the Fall armyworm, Spodoptera frugiperda (J E Smith)(Lepidoptera: Noctuidae), an alien invasive pest on maize in India. Pest Management in Horticultural Ecosystems. 24, 23–29 (2018).
Xiao-xu, S. et al. Case study on the first immigration of fall armyworm Spodoptera frugiperda invading into China. J. Integr. Agric. 18, 2–10 (2019).
IPPC. on mainland Australia. IPPC official pest report no. AUS-97/2 (FAO Rome, Italy, 2020). Detections of fall armyworm (Spodoptera frugiperda)https://www.ippc.int/
Cock, M. J. W., Beseh, P. K., Buddie, A. G., Cafá, G. & Crozier, J. Molecular methods to detect Spodoptera frugiperda in Ghana, and implications for monitoring the spread of invasive species in developing countries. Sci Rep. 7, 4103 (2017).
Early, R., González-Moreno, P., Murphy, S. T. & Day, R. Forecasting the global extent of invasion of the cereal pest Spodoptera frugiperda, the fall armyworm. NeoBiota. 40, 25–50 (2018).
Faulkner, K. T., Hurley, B. P., Robertson, M. P., Rouget, M. & Wilson, J. R. U. The balance of trade in alien species between South Africa and the rest of Africa. Bothalia - African Biodiversity & Conservation. 47, 1–16 (2017).
Westbrook, J. K., Nagoshi, R. N., Meagher, R. L., Fleischer, S. J. & Jairam, S. Modeling seasonal migration of fall armyworm moths. Int. J. Biometeorol. 60, 255–267 (2016).
Bale, J. S. et al. Herbivory in global climate change research: Direct effects of rising temperature on insect herbivores. Glob. Change Biol. 8, 1–16 (2002).
Cannon, R. J. C. The implications of predicted climate change for insect pests in the UK, with emphasis on non-indigenous species. Glob. Change Biol. 4, 785–796 (1998).
Chidawanyika, F., Mudavanhu, P. & Nyamukondiwa, C. Biologically based methods for pest management in agriculture under changing climates: challenges and future Directions. Insects. 3, 1171–1189 (2012).
Ramírez-Cabral, N., Medina-García, G. & Kumar, L. Increase of the number of broods of Fall Armyworm (Spodoptera frugiperda) as an indicator of global warming. Revista Chapingo Serie Zonas Áridas. 19, 1–16 (2020).
Baloch, M. N., Fan, J., Haseeb, M. & Zhang, R. Mapping potential distribution of Spodoptera frugiperda (Lepidoptera: Noctuidae) in Central Asia. Insects. 11, 1–10 (2020).
Cokola, M. C. et al. Bioclimatic zonation and potential distribution of Spodoptera frugiperda (Lepidoptera: Noctuidae) in South Kivu Province, DR Congo. BMC Ecol. 20, 1–13 (2020).
Du Plessis, H., Van Den Berg, J., Ota, N. & Kriticos, D. J. Pest Geography (CSIRO-InSTePP, Canberra, June, 2018). Spodoptera frugiperda (Fall Armyworm)
Fan, J. et al. Potential distribution and niche differentiation of Spodoptera frugiperda in Africa. Insects. 11, 1–10 (2020).
Huang, Y. et al. Overwintering Distribution of Fall Armyworm (Spodoptera frugiperda) in Yunnan, China, and Influencing Environmental Factors. Insects. 11, 805 (2020).
Ramirez-Cabral, N. Y. Z., Kumar, L. & Shabani, F. Future climate scenarios project a decrease in the risk of fall armyworm outbreaks. J. Agri. Sci. 155, 1219–1238 (2017).
Wang, R. et al. Potential distribution of Spodoptera frugiperda (J.E. Smith) in China and the major factors influencing distribution. Glob. Ecol. Conserv. 21, e00865 (2020).
Wu, Q. L. et al. Estimation of the potential infestation area of newly-invaded fall armyworm Spodoptera frugiperda in the Yangtze River Valley of China. Insects 10(2019).
Zacarias, D. A. Global bioclimatic suitability for the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), and potential co-occurrence with major host crops under climate change scenarios. Clim. Change. 161, 555–566 (2020).
Kriticos, D. J. et al. CLIMEX Version 4: Exploring the Effects of Climate on Plants, Animals and Diseases (CSIRO, Canberra, 2015).
Ramirez-Cabral, N. Y. Z., Kumar, L. & Shabani, F. Global alterations in areas of suitability for maize production from climate change and using a mechanistic species distribution model (CLIMEX). Sci. Rep. 7, 5910–5923 (2017).
FAO. Fall armyworm. http://www.fao.org/fall-armyworm/en/ (2020).
FAO. FAO raising awareness and providing capacity development on monitoring and early warning tools for the Fall Armyworm in Africa. http://www.fao.org/food-chain-crisis/how-we-work/plant-protection/fallarmyworm/faw-doc/en/ (2018).
Kriticos, D. J. et al. CliMond: Global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol. Evol. 3, 53–64 (2012).
Gordon, H. B. et al. The CSIRO Mk3 Climate system model. CSIRO Atmospheric Research Technical paper. 60, 1–130 (2002).
Hennessy, K. J. et al. Global climate change projections. in Climate change in Australia - Technical Report 2007 (eds. Pearce, K. B.)36–48 (CSIRO Marine and Atmospheric Research, Melbourne, Australia, 2007).
Chiew, F. H. S., Kirono, D. G. C., Kent, D. & Vaze, J. Assessment of rainfall simulations from global climate models and implications for climate change impact on runoff studies.3907–3914(18th World IMACS / MODSIM Congress Australia, 2009).
Hayhoe, K. et al. Climate models, scenarios, and projections. in Climate Science Special Report: Fourth National Climate Assessment (eds. Wuebbles, D.J. et al.). Volume I,133–160(U.S. Global Change Research Program, Washington, DC, USA, 2017).
IPCC (Intergovernmental Panel on Climate Change). Climate change 2014: synthesis report-contribution of working groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC, Geneva, 2014).
Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem. Cycles. 22, 1–19 (2008).
Barfield, C. S. & Ashley, T. R. Effects of Corn Phenology and Temperature on the Life Cycle of the Fall Armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae). Fla. Entomol. 70, 110–116 (1987).
Busato, G. R. et al. Thermal requirements and estimate of the number of generations of biotypes “corn” and “rice” of Spodoptera frugiperda. Pesquisa Agropecuária Brasileira. 40, 329–335 (2005).
Simmons, A. M. Effects of constant and fluctuating temperatures and humidities on the survival of Spodoptera frugiperda pupae (Lepidoptera: Noctuidae). Fla. Entomol. 76, 333–340 (1993).
Valdez-Torres, J. B., Soto-Landeros, F. & Osuna-Enciso, T. & Báez-Sañudo, M. A. Phenological prediction models for white corn (Zea mays L.) and fall armyworm (Spodoptera frugiperda J.E. Smith). Agrociencia. 46, 399–410 (2012).
Kriticos, D. J. et al. The Potential Distribution of Invading Helicoverpa armigera in North America: Is It Just a Matter of Time? PLoS ONE. 10, e0119618 (2015).
Vera, M. T., Rodriguez, R., Segura, D. F., Cladera, J. L. & Sutherst, R. W. Potential geographical distribution of the mediterranean fruit fly, Ceratitis capitata (Diptera: Tephritidae), with emphasis on Argentina and Australia. Environ. Entomol. 31, 1009–1022 (2002).
Wood, J. R., Poe, S. L. & Leppla, N. C. Winter survival of fall armyworm pupae in Florida. Environ. Entomol. 8, 249–252 (1979).
Silvain, J. F. & Ti-A-Hing, J. Prediction of larval infestation in pasture grasses by Spodoptera frugiperda (Lepidoptera: Noctuidae) from Estimates of Adult Abundance. Fla. Entomol. 68, 686–691 (1985).
Sims, S. R. Influence of soil yype and rainfall on pupal survival and adult emergence of the fall armyworm (Lepidoptera: Noctuidae) in Southern Florida. J. Entomol. Sci. 43, 373–380 (2008).
Hogg, D. B., Pitre, H. N. & Anderson, R. E. Assessment of Early-Season Phenology of the Fall Armyworm (Lepidoptera: Noctuidae) in Mississippi. Environ. Entomol. 11, 705–710 (1982).
Siebert, S., Henrich, V., Frenken, K. & Burke, J. Global Map of Irrigation Areas version 5. (Rheinische Friedrich-Wilhelms-University (Food and Agriculture Organization of the United Nations, Rome, Italy,, Bonn, Germany /, 2013).
Musolin, D. L. Insects in a warmer world: ecological, physiological and life-history responses of true bugs (Heteroptera) to climate change. Glob. Change Biol. 13, 1565–1585 (2007).
Svobodová, E. et al. Determination of areas with the most significant shift in persistence of pests in Europe under climate change. Pest Manag. Sci. 70, 708–715 (2014).
Varner, J. & Dearing, M. D. The importance of biologically relevant microclimates in habitat suitability assessments. PLoS ONE. 9, e104648 (2014).
Jeger, M. et al. Pest risk assessment of Spodoptera frugiperda for the European Union. EFSA J. 16, 1–120 (2018).
Nagoshi, R. N., Meagher, R. L. & Hay-Roe, M. Inferring the annual migration patterns of fall armyworm (Lepidoptera: Noctuidae) in the United States from mitochondrial haplotypes. Ecol Evol. 2, 1458–1467 (2012).
Soberón, J. Niche and area of distribution modeling: a population ecology perspective. Ecography. 33, 159–167 (2010).
Pearson, R. G. & Dawson, T. P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob. Ecol. Biogeogr. 12, 361–371 (2003).
Andrew, N. R. & Hill, S. J. Effect of Climate Change on Insect Pest Management. in Environmental Pest Management: Challenges for Agronomists; Ecologists, Economists and Policymakers (eds. Coll, M. & Wajnberg, E.) 197–223 (John Wiley & Sons Ltd 2017).

No competing interests reported.

SuplementaryTableS1FAWnativerange.xlsx
Supplementary Table 1. FAW occurrence records from the Americas, the native range of FAW.
Supplementary Table 2. CLIMEX parameter sensitivity values for Spodoptera frugiperda (FAW) parameters listed in Table 1, as applied to the CM10 1975H V1.2 global dataset under a natural rainfall scenario.
Supplementrymaterials.docx
Supplementary Fig. S1. . The area with potential suitability for FAW population growth under historic climate using CLIMEX. FAW annual growth index (GI) under (a) natural rainfall condition, (b) irrigation scenario I, and (c) irrigation scenario II. (d) Global distribution of maize and sorghum, two major host crops of FAW.
Supplementary Fig. S2. The areas with potential suitability for FAW seasonal population growth based on current and predicted future climates (2030, 2050 and 2080) under CSIRO-Mk3.0 (top) and MIROC-H (bottom), considering irrigation scenario II.
Supplementary Fig. S3. Impact of climate change on climatic suitability area (EI) for FAW population persistence. White indicates no change, red indicates an increase, and blue indicates decrease in EI values under the future projected climate from the current climate. Depth of color indicates the degree of changes in EI value.

Download PDF

Journal Publication

published 11 Jan, 2022

Read the published version in Scientific Reports →

Editorial decision: Major revision
03 Jun, 2021
Reviews received at journal
31 May, 2021
Reviewers agreed at journal
21 May, 2021
Reviewers agreed at journal
29 Mar, 2021
Reviews received at journal
23 Mar, 2021
Reviewers agreed at journal
11 Mar, 2021
Reviewers invited by journal
19 Feb, 2021
Editor assigned by journal
10 Feb, 2021
Editor invited by journal
02 Feb, 2021
Submission checks completed at journal
02 Feb, 2021
First submitted to journal
01 Feb, 2021

You are reading this latest preprint version

Potential Distribution of Fall Armyworm in Africa and Beyond, Considering Climate Change and Irrigation Patterns

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Methods

Research model and software

CLIMEX model

ArcGIS Software

Data collection

Fall armyworm occurrence data

Climate data

Irrigation data

Host crops data

Model fitting

Growth indices

Temperature index (TI)

Moisture index (MI)

Stress indices (SI)

Cold Stress (CS)

Heat Stress (HS)

Dry Stress (DS)

Wet Stress (WS)

Effective Degree-Days (PDD)

Irrigation

Parameter sensitivity and model uncertainty analysis

Results

FAW global potential geographical distribution under current climate

Native range

Non-native range

FAW projection under future climate conditions

Parameter sensitivity and model uncertainty

Discussion

Conclusion

Declarations

Acknowledgements

Author Contributions:

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1