DOI: 10.5061/dryad.5dv41nsgz
title: Data from:Climate-specific dynamics of fall armyworm on maize: Implications for pest monitoring and management

description: Although management methods for the fall armyworm (FAW), Spodoptera
 frugiperda (Lepidoptera: Noctuidae), have been explored, monitoring and
 surveillance in newly invaded regions is problematic. This study
 investigates the population dynamics and infestation levels of the fall
 armyworm (FAW), Spodoptera frugiperda, on maize farms in Togo's
 Guinean and Sudanese climatic zones to improve pest management strategies.
 Male FAW moths were monitored using pheromone traps over 15 months, and
 larval densities and plant damage were assessed on 100 maize plants per
 farm. Results revealed higher moth captures in the Sudanese than Guinean
 climate zones (2.77 ± 0.16 vs. 2.05 ± 0.13). During the major rainy season
 (June to August), captures peaked in the Sudanese zone (5.28 ± 0.52)
 compared to the Guinean zone (3.77 ± 0.55). No significant differences
 were observed during the minor rainy season (September to November), while
 dry season (December to May) captures were higher in the Guinean zone
 (0.54 ± 0.07) than the Sudanese zone (0.24 ± 0.05).  Despite
 similar larval densities, plant damage was greater in the Guinean zone
 during the major rainy season, likely due to positive correlations between
 adult captures, larval counts, and plant damage in this region.
 Conversely, no such correlations were observed in the Sudanese zone.
 Additionally, maize stage-specific analyses in Lomé and Toaga found no
 correlations between FAW captures, larval densities, or damage. These
 findings highlight the need for climate-specific pest management
 strategies rather than uniform national approaches, supported by linear
 regression models for each region.
description: <strong>Distribution of sites and characteristics of study
 zones</strong> Over 15 months, adult FAW were
 trapped at 15 maize sites distributed across the Guinean and Sudanese
 climatic regions of Togo (Fig. 1). During the maize seasons, the sites
 were expanded to three farms per site, including an on-station experiment
 within each climatic region, or 45 farms across the country for larval
 severity data collection. The Guinean climate covers
 the three agro-ecological zones (AEZs) of southern Togo and is
 characterized by bimodal rainy seasons. The first rainy season marks the
 main maize season from April to July and the second covers the minor maize
 season from September to November. The two rainy seasons are separated by
 a short dry season of one month in August, while the main dry season lasts
 from December to March. The three AEZs of Togo's Guinean climate
 region include AEZ5 of the southern mosaic coastal savannah mixed with a
 relic forest and fallow land, AEZ4 of the western mountainous dense and
 semi-deciduous forest, and AEZ3 of the eastern Guinean woodland savannah.
 The Sudanese region includes the two AEZs of northern Togo, which has a
 wet maize growing season from June to September and a dry season from
 October to May. The two AEZs of this zone include AEZ2 of the lower north,
 characterized by a mountainous mix of dry forest to savannah, and AEZ1 of
 the upper north, characterized by a typical Sudanese savannah (Koffi et
 al. 2020a). The country is dominated by the Harmattan and Mousson winds.
 The Harmattan is a hot day and cold night wind that blows from the
 northeast to the southwest from November to April. The Mousson is a mild
 wind that blows in the opposite direction to the Harmattan from May to
 October (Amey et al. 2014). <strong>Trapping of
 male moths</strong> Pheromone-baited traps were
 used to catch male FAW moths. Standard bucket traps (green top, yellow
 funnel, white bucket; Unitraps, manufactured by International Pheromone
 Systems, Neston, UK, distributed by Great Lakes IPM, Vestaburg, MI, USA)
 were used for 15 months. Rubber septa lures composed of three <em>S.
 frugiperda</em> pheromone components of (Z)-9-tetradecenyl acetate
 (Z9-14:Ac), (Z)-11-hexadecenyl acetate (Z11-16:Ac) and (Z)-7-dodecenyl
 acetate (Z7-12:Ac) (Trécé®, Adair, OK, USA) were placed in green baskets
 at the top of the bucket traps. The trap design and lure blend used was
 the most efficient for FAW trapping in Togo and Ghana (Meagher et al.
 2019, Koffi et al. 2021). In each bucket, 10 g of cotton soaked in a
 diluted killing solution of an abamectin containing emamectin benzoate
 (019 g/l EC) (water/emamectin benzoate 998:2ML mixed solution), marketed
 as EMACOT 019ECTM (ANTEOR Sarl, Lomé, Togo), was suspended in the trap.
 The entire system was suspended from wooden poles obtained
 locally.  The selection of maize sites was based on the
 AEZ, with three sites within each AEZ or nine sites in the Guinean climate
 area and six in the Sudanese climate area. All sites contained three
 bucket traps attached to wooden poles initially spaced 40 meters apart and
 three meters from the main maize plots. The traps were initially placed
 0.50 m above the ground and adjusted weekly to 0.30 m in relation to the
 height of the maize plants. The killing cotton strips were replaced
 monthly, as were the pheromone lures. Caught adults were collected weekly
 and data were categorized for each month (Koffi et al. 2021). In the
 on-station trials, maize was grown in four plots of 400
 m<sup>2</sup> each, separated by three meters. Traps were set
 three weeks before the maize plants germinated.
 <strong>Population densities and infestations across
 climatic regions</strong> During three
 consecutive maize production seasons within the 15 months of adult
 trapping, data on larval density on 100 plants and infestation estimated
 from damaged plants within 100 plants were collected on the 45 maize farms
 in the two climatic regions. The selected farms included those where adult
 traps were set and two neighboring farms. Farm inspections were carried
 out monthly during June, July and August. The maize season covers June to
 August in the Guinean zone, while the maize season starts in the Sudanese
 zone from July. Inspections of each farm were conducted within the four
 quadrants of the farm corners and one in the center of the farm. Within
 each quadrant, 20 maize plants were randomly selected for counting the
 number of egg masses, larvae and damaged plants. The five quadrants and
 the selected maize plants were randomly selected during each monthly
 inspection. The data collected were recorded per farm and tabulated within
 groups of climatic regions. Comparisons were made between regions and
 correlations between parameters were assessed within each
 region. <strong>Population densities and
 infestations in on-station experiments</strong>
 Two on-station experiments were conducted in Lomé, in the Guinean
 region, and Toaga, in the Sudanese region. At each on-station site, the
 experimental plot was divided into four units of 10 m * 10 m (100
 m<sup>2</sup>), 2 m apart. The two experiments were subjected
 to the same treatments of weeding and fertilizing without any FAW control.
 Pheromone trapping was from the first day of maize germination until the
 day of harvest, and the killing cotton strips were replaced weekly.
 Pheromone lures were replaced monthly, and captured moths were collected
 weekly. The numbers of larvae, egg masses, and damaged plants or ears were
 recorded weekly on 10 randomly selected plants per experimental unit. All
 data collections took place on the same day to avoid bias. The growth of
 maize plants was divided into four phenological stages, including the
 emergence stage, which covered the first week after germination, the
 vegetative stage, which covered the second week after germination until
 the week of emergence of male flowers, the tasseling stage, which covered
 two weeks after emergence of male flowers, and the maturation stage, which
 lasted until harvest. The data collected were collated into experimental
 units, grouped into maize growth stages and then subjected to correlations
 between parameters. The maize yields were determined by the weighing of
 the total grains per plot, which were then extrapolated into hectares. The
 direct yield losses per plot were determined as the difference in grain
 weights between 10 cobs that were found to be healthy and 10 cobs that had
 been marked during the grain-forming stage and had been fed on by FAW
 larvae. <strong>Data
 Analysis</strong> The data collected were
 arranged by treatment and tabulated in Microsoft Excel version 2013. The
 raw data were subjected to the Shapiro-Wilk (1965) normality test as
 applied by Royston (1995). Normal data were compared with ANOVA and means
 separated using a Tukey test. Multi-variable data that did not pass the
 normality tests were then tested by the nonparametric Kruskal-Wallis
 one-way analysis of variance. The two variable data that passed the
 normality tests were additionally subjected to the Brown-Forsythe test of
 equal variances, then to the test of assumed equal variances
 (Student's t-test) or not assumed equal variances (Welch's
 t-test). The results of the Welch's test not assuming equal variances
 were used only when the equality of the population variances of the two
 groups was in doubt. The two variable data that failed normality tests
 were tested using a Mann-Whitney rank sum test with the U
 statistic. Pearson Product Moment Correlation was used
 to assess the relationship between different parameters. Linear regression
 models were used to establish the equations linking the independent
 variable captured adult male moths, and the dependent variables larval
 density and infestation level. The predictive ability was significant with
 a probability of <em>P</em> &lt; 0.05. All data subjected
 to regression were tested for normality (Shapiro-Wilk) and constant
 variance (Spearman Rank Correlation). Monthly and
 spatial plots were generated using simple line and scatter error bars
 under column means with standard errors. Box plots were obtained with
 medians and percentiles. The bar graphs comparing catches, larval
 densities, and infestations between the two regions or yields and yield
 losses between on-station sites were constructed using the vertical bar
 graph with error bars from the data means. All data analyses and graphs
 were performed using SigmaPlot 14.0. The data collected
 were arranged by treatment and tabulated in Microsoft Excel version 2013.
 The raw data were subjected to the Shapiro-Wilk (1965) normality test as
 applied by Royston (1995). Normal data were compared with ANOVA and means
 separated using a Tukey test. Multi-variable data that did not pass the
 normality tests were then tested by the nonparametric Kruskal-Wallis
 one-way analysis of variance. The two variable data that passed the
 normality tests were additionally subjected to the Brown-Forsythe test of
 equal variances, then to the test of assumed equal variances
 (Student's t-test) or not assumed equal variances (Welch's
 t-test). The results of the Welch's test not assuming equal variances
 were used only when the equality of the population variances of the two
 groups was in doubt. The two variable data that failed normality tests
 were tested using a Mann-Whitney rank sum test with the U statistic.
 Pearson Product Moment Correlation was used to assess the relationship
 between different parameters. Linear regression models were used to
 establish the equations linking the independent variable captured adult
 male moths, and the dependent variables larval density and infestation
 level. The predictive ability was significant with a probability of P
 &lt; 0.05. All data subjected to regression were tested for normality
 (Shapiro-Wilk) and constant variance (Spearman Rank Correlation). Monthly
 and spatial plots were generated using simple line and scatter error bars
 under column means with standard errors. Box plots were obtained with
 medians and percentiles. The bar graphs comparing catches, larval
 densities and infestations between the two regions or yields and yield
 losses between on-station sites were constructed using the vertical bar
 graph with error bars from the data means. All data analyses and graphs
 were performed using SigmaPlot 14.0. Figure 1. Geographical distribution
 of the trap setting localities with latitude and longitude coordinates
 within the Guinean and Sudanese climatic regions of Togo. The white dots
 mark the sites of Guinean zone and the black dots the sites of Sudanese
 zone. Numbers 1 and 15 show the on-station experiment sites of Lomé (1)
 and Toaga (15) (d-maps.com). Figure 2: Population dynamics of males of S.
 frugiperda captured with Universal moth traps baited with Trécé® lures for
 15 months across Togo (A), and within the Sudanese (B) and Guinean (C)
 climatic zones. Kruskal-Wallis One Way Analysis of Variance (P &lt;
 0.05). Figure 3: Mean numbers of pooled adults caught per trap per month
 in the Sudanese (A) and Guinea (B) climatic zones. Kruskal-Wallis One Way
 Analysis of Variance (P &lt; 0.05). Figure 4: Comparisons between the
 Guinean and Sudanese climatic regions of Togo: numbers of caught males per
 month per trap (A), collected larvae (B) and infestation levels (C) in 100
 plants per farm during the maize seasons in the. Mann-Whitney rank sum
 test with the Yates (P &lt; 0.05). Figure 5: Correlations within
 climatic zones between the trapped adults per trap per month, larval
 densities on 100 maize plants, and infestation levels of maize in the
 Guinean (A) and Sudanese climates (B). Figure 6: Correlations between the
 trapped adults per trap per week, egg masses, larval densities on 10 maize
 plants, and infestation levels during the emergence (A), vegetation (B),
 tasseling (C), and mature (D) stages of maize plants in the on-station of
 Lomé located in the Guinean climatic zone. Figure 7: Correlations between
 the trapped adults per trap per week, egg masses, larval densities on 10
 maize plants, and infestation levels during the tasseling stage of maize
 plants in the Toaga on-station trial located in the Sudanese climatic
 zone. Figure 8: Comparisons between the on-stations of Lomé in the Guinean
 zone and Toaga in the Sudanese zone: maize grain yields (A), and direct
 yield losses from FAW larval feeding on maize ears during the maturation
 (B). Table 1. Variation (mean ± SE) of male adults of FAW trapped per
 month per trap during the major rainy, minor rainy and dry season in the
 five AEZs of Togo. Table 2. Pearson correlations between fall armyworm
 variables sampled at the Lomé Experiment Station in the Guinean climatic
 zone in Togo. Table 3. Pearson correlations between fall armyworm
 variables sampled at the Toaga Experiment Station in the Sudanese climatic
 zone in Togo. Table 4: Linear regression of the independent variables
 larval density (larv) and plant infestation (inf) to predicting number of
 adult male fall armyworm captured in pheromone-baited traps during maize
 season in the field (all stages) and plant phenological stages at
 on-stations in Guinean zone (A) and Sudanese zone (B) in Togo
description: # Climate-specific dynamics of fall armyworm on maize: Implications for
 pest monitoring and management Dataset DOI:
 [10.5061/dryad.5dv41nsgz](10.5061/dryad.5dv41nsgz) ## Description of the
 data and file structure ### Files and variables #### File:
 Koffi\_et\_al.\_DATA\_New\.xlsx **Description:**  Adults: Number of
 trapped adults of FAW in the two climatic zones of Togo during the 15
 months (Fig. 2a, Table 1 Sudan: Number of trapped adults, larvae on 100
 plants, and infestations of FAW in the Sudanese climatic zones of Togo
 during the 15 months (Fig. 2b, Fig. 3a, Fig. 4abc, Fig 5a, Table 4ac
 Guinea: Number of trapped adults, larvae on 100 plants, and infestations
 of FAW in the Guinean climatic zones of Togo during the 15 months (Fig.
 2c, Fig. 3b, Fig. 4abc, Fig 5b, Table 4ab Toaga: Number of trapped adults,
 larvae on 10 plants, and infestations of FAW in the on-station of Toaga
 (Fig. 7, Table 3, Table 4c) Lome: Number of trapped adults, larvae on 10
 plants, and infestations of FAW in the on-station of Lome (Fig. 6 abcd,
 Table 2, Table 4b) Yields: Yields and yield losses (t/ha) of maize grains
 at on-station experiments of Toaga and Lome (SEAL) (Fig. 8) The data
 collected were arranged by treatment and tabulated in Microsoft Excel
 version 2013. The raw data were subjected to the Shapiro-Wilk (1965)
 normality test as applied by Royston (1995). Normal data were compared
 with ANOVA and means separated using a Tukey test. Multi-variable data
 that did not pass the normality tests were then tested by the
 nonparametric Kruskal-Wallis one-way analysis of variance. The two
 variable data that passed the normality tests were additionally subjected
 to the Brown-Forsythe test of equal variances, then to the test of assumed
 equal variances (Student's t-test) or not assumed equal variances
 (Welch's t-test). The results of the Welch's test not assuming
 equal variances were used only when the equality of the population
 variances of the two groups was in doubt. The two variable data that
 failed normality tests were tested using a Mann-Whitney rank sum test with
 the U statistic. Pearson Product Moment Correlation was used to assess the
 relationship between different parameters. Linear regression models were
 used to establish the equations linking the independent variable captured
 adult male moths, and the dependent variables larval density and
 infestation level. The predictive ability was significant with a
 probability of *P* &lt; 0.05. All data subjected to regression were tested
 for normality (Shapiro-Wilk) and constant variance (Spearman Rank
 Correlation). Monthly and spatial plots were generated using simple line
 and scatter error bars under column means with standard errors. Box plots
 were obtained with medians and percentiles. The bar graphs comparing
 catches, larval densities and infestations between the two regions or
 yields and yield losses between on-station sites were constructed using
 the vertical bar graph with error bars from the data means. All data
 analyses and graphs were performed using SigmaPlot 14.0. Empty cells
 represent values were not determined. ## Access information Other publicly
 accessible locations of the data: * none Data was derived from the
 following sources: * None