Abstract We know numerous abiotic factors strongly influence crop plants. Yet we often know much less about abiotic effects on closely interacting organisms including herbivorous insects. This lack of a whole-system perspective may lead to underestimating the threats from changing factors. High soil salinity is a specific example that we know threatens crop plants in many places, but we need to know much more about how other organisms are also affected. We investigated how salinity affects the soybean aphid (SBA; Aphis glycines Matsumura; Hemiptera: Aphididae) on soybean plants (Glycine max [L.] Merr.; Fabales: Fabaceae) grown across a range of saline conditions. We performed four complementary greenhouse experiments to understand different aspects of how salinity might affect SBA. We found that as salinity increased both population size and fecundity of SBA increased across electrical conductivity values ranging from 0.84 to 8.07 dS m−1. Tracking individual aphids we also found they lived longer and produced more offspring in high saline conditions compared to the control. Moreover, we found that salinity influenced aphid distribution such that when given the chance aphids accumulated more on high-salinity plants. These results suggest that SBA could become a larger problem in areas with higher salinity and that those aphids may exacerbate the negative effects of salinity for soybean production. abiotic factors, aphid, salinity, soybean Abiotic factors that alter an organism’s performance can have a much greater effect by also influencing additional interacting organisms (Tylianakis et al. 2008, Harmon and Barton 2013). For example, altering abiotic factors can often directly affect plants (e.g., Parmesan 2006), including crop plants (Olesen and Bindi 2002, Bisbis et al. 2018). Given such potential effects, we would expect that changing these abiotic factors could also alter the herbivorous pests that rely on those impacted crops. Despite this potential importance, herbivores often receive a small fraction of the attention plants receive in such areas (e.g., Jamieson et al. 2012). When we know a specific abiotic factor can be important to a crop, we should also investigate connections between that factor and the crop’s herbivorous pests. This whole-system perspective is needed for fully understanding the risks from changing abiotic factors and how to best mitigate them. One such changing abiotic factor that can impact crop plants is soil salinity. Soil salinization can be defined as any accumulation of soluble salts that may be harmful to plants (Munns 2002). High soil salinity is a substantial global issue (Butcher et al. 2016) that is predicted to increase in importance (Wang et al. 2003). These saline soils often have a negative impact on crop yield and other plant fitness characteristics (Butcher et al. 2016, Harmon and Daigh 2017). Given the strong relationship between soil salinity and plant health, it is reasonable to expect that soil salinity may also strongly affect herbivores. Soybean plants, specifically, can have a strong relationship with soil salinity (Essa 2002, Langseth 2015, Butcher 2016), but the connection between salinity and the herbivores that feed on soybean is much less clear. One recent exception showed that salinity positively affects two-spotted spider mite fecundity and population growth on soybeans (Eichele-Nelson et al. 2017). However, nothing is yet known of salinity effects on soybean aphid (SBA), the most important pest of soybeans in North America (Ragsdale et al. 2011). We do know that many other abiotic factors can strongly affect SBA performance. For example, temperature substantially influences SBA fecundity, population growth rates, and life expectancy (McCornack et al. 2004). Temperature can also interact with host plant resistance to influence SBA (Whalen and Harmon 2015). Ultraviolet radiation may also impact SBA populations, although that effect might be mediated by SBA behavior (Burdick et al. 2015). Abiotic factors in the soil can also affect SBA as soils deficient in potassium produced plants with higher SBA populations (Myers et al. 2005, Myers and Gratton 2006, Walter and DiFonzo 2007). Although research on abiotic factors often focuses on changes to population growth or demographic parameters, abiotic changes can also influence an organism’s behavior (Harmon and Barton 2013), including their movement and distribution (e.g., Whalen and Harmon 2015). This movement can cost energy and feeding time, which are especially detrimental to sedentary insects like apterous (wingless) aphids (Nelson 2007). Changes in movement behavior can also alter pests’ impact on crops through changes in pest colonization, pest spread, and even virus transmission (Kennedy 1976, Collinge 2000). The purpose of this study was to investigate the ecological effects of soil salinity on the SBA using manipulative experiments that demonstrate some potential consequences of changing salinity. We used sodium sulfate and magnesium sulfate, which are naturally occurring salts in agricultural fields of North Dakota (Franzen 2003), to experimentally induce a range of saline conditions in a controlled greenhouse. Our objectives were to 1) determine how soil salinity impacts SBA numbers, 2) determine more specifically how soil salinity impacts SBA demographic factors like fecundity and longevity, and 3) determine how soil salinity impacts distribution of SBA. Our goal is for this work to illustrate the multiple ways salinity can influence SBA. Materials and Methods The overall goal of our greenhouse experiments was to test different aspects of SBA performance on soybean plants grown across a range of salinity levels. We used an established methodology for all greenhouse experiments (see Eichele-Nelson et al. 2017). In brief, we hand mixed known quantities of salts to pots with a prepackaged growing medium (PRO-MIX Premier BX Mycorrhizae Pro Soil, Riviere-du-Loup, QC, Canada) in a controlled greenhouse. We lined pots with plastic to keep the salts from leaching, mixed the salts and growing medium in the bottom ¾ portion of the pot, and then planted seeds in the top ¼ portion of the pot which contained only growing medium. We established five treatments by adding different amount of those salts which resulted in measured salinity values of EC1:5 dS m−1 = 0.84, 2.37, 4.66, 6.05, and 8.07. This range of salinity treatments reflects the range of salinity values observed in production fields of the Northern Great Plains (Hadrich 2012). SBA Colony SBA used in our experiments were from an established greenhouse colony. This colony first originated in the summer of 2008 from soybean plots near Prosper, North Dakota Agricultural Experiment Station. Colonies were refreshed periodically with field collected aphids from soybean fields in the same location to maintain genetic diversity. We maintained aphids on a susceptible soybean variety (RG607RR, NDSU Research Foundation, Fargo, ND), and housed both plants and aphids in thrips proof cages (model # BD44545F dimensions 47.5 × 47.0 × 47.5, BugDorm, MegaView Science Co. Ltd, Taichung, Taiwan) with 150 × 150 nylon mesh at 21–24°C, 60–80% RH, under a photoperiod of 14:10 (L:D) h at the NDSU Agricultural Experiment Station Research Greenhouse Complex in Fargo, ND. We renewed aphid colonies once each week by removing the most heavily infested plants and replacing them with uninfested soybean plants. Small Population Experiment Our first experiment measured the change in the number of SBA while in small populations on individual plants grown in one of five different levels of soil salinity. All plants used in this experiment were planted on the same day, but differences in treatments meant that plant growth stage varied from V3 to V6 at the point when aphids were added to plants. To measure the change in these small populations, we transferred seven adult female SBA onto the leaves of each soybean plant. These aphids grew for 7 d which is approximately one full generation (McCornack et al. 2004). This time frame allows all aphid life stages to experience the differences in soil salinity and means that any observed difference in aphid numbers could be due to effects on different life stages and multiple demographic mechanisms. Once infested, we enclosed the entire plant in a tube cage which allowed aphids to move freely throughout the entire plant. Cages were made from a thin plastic sheet 10 cm in diameter and 40 cm in height with two holes covered in mesh allowing airflow but preventing escape allowing the aphids. The cage was supported in the middle with a ring of PVC pipe. Aphids remained on the soybean plant for 7 d, at which time the plant was removed and bagged so that all adult aphids and nymphs could be counted under a microscope. Each individual plant was the unit of replication, and there were 10 replications for each of the five salinity treatments. We analyzed data using a regression in JMP (SAS Institute Inc. 2010) where the total number of aphids was the dependent variable and EC1:5 measurement as the independent variable. Fecundity Experiment Herbivore fecundity is directly affected by host plant quality (Awmack and Leather 2002) and is often an important factor in creating differences aphid numbers such as those differences measured in the previous experiment. To help further explore the previous result, we performed a complementary experiment to look at a more specific measure of SBA performance at a smaller temporal and spatial scale. We designed a 3-d experiment to measure SBA fecundity across plants grown in the same range of salinity conditions. In this experiment, we transferred three adult female SBA with a fine camel hair brush onto a single leaf of a soybean plant (stage V1–V3) that we grew in one of the five salinity treatments. We enclosed aphids within a clip cage (2.54 cm inside diameter model # 1458, Bioquip Products, Rancho Dominguez, CA) that was positioned to include mostly leaf but also a gap off of the leaf so SBA could move between the top and bottom sides of the leaf. Aphids were on the single leaf for 3 d. This time frame allows us to accumulate multiple days of nymph production while making sure we could differentiate the original aphids placed on the plant from offspring that had been born and growing within the cage. After 3 d, we removed the focal leaf and its stem and counted all adults and nymphs under a microscope. Individual clip cages (each on its own soybean plant) were the unit of replication, with 10 replications per treatment. We again analyzed data using a regression in JMP (SAS Institute Inc. 2010), in this case the total number of offspring laid over the entire experiment in a cage was the dependent variable and the EC1:5 measurement as the independent variable. Lifetime Experiment Both of the previous experiments provide important information about how salinity can influence SBA, but they do not necessarily tell the complete story of salinity’s impact on SBA. We performed another complementary experiment to look at the long-term (lifetime) effects of salinity on SBA. To do this, we recorded the life span and reproductive output of individual female aphids born and maintained on plants grown in different salinity conditions. For this experiment, we used the two most extreme salinity treatments: a no salts added control and the highest salinity treatment (EC1:5 dS m−1 = 8.07). We started with 15 soybean plants in each of two treatments, but three of the control plants were excluded when the focal aphid went missing. We added aphids by first infesting each plant with one adult SBA placed in a clip cage at V2–V4 growth stage. Adults had 1 d to lay nymphs, after which we removed the adult and all but one newly born aphid. This ensures that all aphids we used in the experiment were the same age. We observed the focal aphid three times each week for its entire life. During each observation we recorded whether the aphid was still alive, if the aphid had nymphs, and how many nymphs had been laid. When new offspring were found in the cage, we removed those nymphs to avoid potential crowding. We terminated the experiment after 47 d at which point all aphids had died. To determine effects of salinity in our experiment, we used analysis of variance (ANOVA) in JMP (SAS Institute Inc. 2010) with salinity treatment (high vs control) as the independent variable and total nymphs laid, longevity, length of reproductive period, or age at first reproduction as dependent variables. Each response variable was analyzed with a separate ANOVA. We also used a repeated measures analysis in JMP (SAS Institute Inc. 2010) to look at fecundity patterns through time. Our primary interest was in a potential time * treatment interaction which would indicate if differences in fecundity across the two treatments varied over the course of the aphid’s life. We show data until all aphids stopped producing offspring, but our analyses only cover the period when there was at least one aphid producing offspring in both treatments. The sphericity test was significant for our results, so we used the Huynh-Field epsilon adjusted tests. We also performed post hoc comparisons of the between-subject effects within each time period. Distribution Experiment In addition to demographic and population level differences in salinity, we wanted to investigate whether SBA had a behavioral response to plants grown in different salinity conditions. To do this, we set up an experiment in which an infested plant from the SBA colony was placed between an uninfested soybean plant grown in the highest salinity treatment (EC1:5 dS m−1 = 8.07) and an uninfested control plant grown with no added salts (EC1:5 dS m−1 = 0.84). At the end of the experiment, differences in the number of adult aphids on the high-salinity plant compared to the control plant in a given cage would indicate that salinity influenced SBA distribution via differential attraction to one plant type, repulsion from one plant type, and/or retention on one plant type. Differences in the number of juvenile SBA could be a function of juveniles moving and/or adults differentially producing nymphs on different salinity plants. We performed the experiment by first connecting a leaf from the high-salinity plant to a leaf from the source plant and then a leaf from the control (low salinity) plant to a different leaf from the same source plant. This allowed aphids to freely walk between plants (Whalen and Harmon 2012). We used colonies of apterous (wingless) aphids so that all movement would be through walking. Aphids had 3 d to redistribute and produce progeny after which we harvested the two experimental plants and counted aphids under the microscope. We enclosed the source plant, high-salinity plant, and control plant together in a single thrips proof mesh cage and we made all comparisons between the high-salinity plants and control plants within a given cage. We set up 20 cages that each included all three plants. We performed the experiment with all 20 cages at the same time in the same large greenhouse room where colonies were maintained. Cages were throughout the room and the orientation of each plant type was randomly assigned within each cage. To account for the fact that high-salinity plants and control plants in the same cage were not independent from each other, we used a paired t-test to look at the difference in aphids on control plants versus high-salinity plants (SAS Institute Inc. 2010). We measured both the number of adult (or late instar) aphids and the number of juvenile aphids and performed separate analyses for counts of each life stage as well as the total number of aphids. Results Small Population Experiment We found that the number of SBA at the end of the experiment was different depending on salinity treatment (Fig. 1). Specifically, the total number of SBA on a plant increased as salinity increased (r2 = 0.601, F1,48 = 72.3, P < 0.0001), with the highest salinity treatment having an average number of aphids that was 3.5 times as high as the control treatment. Fig. 1. View largeDownload slide Total number of aphids (all life stages) per plant as a function of salinity EC1:5 (dS m−1) after a 7-d greenhouse experiment. Fig. 1. View largeDownload slide Total number of aphids (all life stages) per plant as a function of salinity EC1:5 (dS m−1) after a 7-d greenhouse experiment. Fecundity Experiment Similarly, we found that SBA fecundity also increased with soil salinity (Fig. 2). Females produced more offspring as salinity increased (r2 = 0.471, F1,48 = 43.7, P < 0.0001). As in the population experiment, the average response values in the highest salinity treatment were approximately 3.5 times those found in the control treatment. Fig. 2. View largeDownload slide Number of juvenile aphids per clip cage as a function of salinity EC1:5 (dS m−1) after 3 d of nymph production. Fig. 2. View largeDownload slide Number of juvenile aphids per clip cage as a function of salinity EC1:5 (dS m−1) after 3 d of nymph production. Lifetime Experiment In this experiment, as in the other two experiments, most demographic parameters were improved in the high-salinity treatment compared to the control. This included our measurement of SBA reproduction. The total number of nymphs a SBA produced over its entire lifetime was almost twice as great for an aphid in the high-salinity treatment compared to the control treatment (average ± SE: high salinity 38.5 ± 2.55 nymphs vs control 20.0 ± 2.31 nymphs; F1,25 = 27.6, P < 0.0001). When looking at reproduction throughout the entire reproductive period of the aphids (Fig. 3), the average number of nymphs laid in the high-salinity treatment was numerically higher than in the control treatment at every time point we measured. However, how many more aphids were laid in the control compared to the high-salinity treatment varied with time as some dates, particularly at the beginning, had only minor differences and other dates had very large differences. This lead to a significant interaction between time and salinity treatment (repeated measure interaction H-F epsilon F4.5,112.9 = 2.73, P = 0.0272; time H-F epsilon F4.5,112.9 = 52.8, P < 0.0001; salinity F1,25 = 25.5, P < 0.0001; statistically significant between-subject effects [P < 0.05] for days 13, 15, 17, 20, 22, 24, and 27). Fig. 3. View largeDownload slide Average (±1 SE) aphid nymph production as a function of the aphid’s age. Aphids grown on control plants (no salts added) are shown with a solid line and closed circle. Aphids grown on plants in high-salinity soil (EC1:5 dS m−1 = 8.07) are shown with a dashed line and open circle. No nymphs were laid before the observation on day 8 or after day 36. Fig. 3. View largeDownload slide Average (±1 SE) aphid nymph production as a function of the aphid’s age. Aphids grown on control plants (no salts added) are shown with a solid line and closed circle. Aphids grown on plants in high-salinity soil (EC1:5 dS m−1 = 8.07) are shown with a dashed line and open circle. No nymphs were laid before the observation on day 8 or after day 36. Salinity also affected aphid longevity. Aphids in the high-salinity treatment lived more than 50% longer than aphids in the control treatment (average ± SE: high salinity 34.0 ± 2.13 d vs control 21.7 ± 1.70 d; F1,25 = 19.0, P = 0.0002). This difference in longevity was primarily during the reproductive period of the aphid’s life. The total number of days aphids laid nymphs in the high-salinity treatment was almost double the duration compared to aphids in the control (average ± SE: high salinity 18.1 ± 1.34 vs control 9.67 ± 1.08; F1,25 = 22.1, P < 0.0001). There was not a difference in the aphid’s age when we first observed a nymph in the cage (average ± SE: high salinity 8.40 ± 0.363 vs control 8.83 ± 0.167; F1,25 = 1.00, P = 0.327). However, salinity may have impacted juvenile development at a smaller magnitude then we could measure with our periods of observation. Distribution Experiment In this experiment, we found that aphid numbers were higher on high-salinity plants compared to control plants. After 3 d, the average number of aphids was almost five times higher on the high-salinity plant in a cage as compared to the control plant in the same cage (average ± SE: high salinity 586.8 ± 102.2 vs control 123 ± 24.4; t19 = 4.35, P = 0.0035). When looking at these same results broken down to individual plants within each cage (Fig. 4), there were almost always more aphids on the high-salinity plant compared to the low-salinity plant in the same cage. This difference in total aphid distribution was primarily driven by a fivefold difference in the number of juvenile aphids (average ± SE: high salinity 500.1 ± 87.5 vs control 111 ± 23.1; t19 = 4.22, P = 0.0005) which may have preferentially moved to the high-salinity plants or been born there at a greater rate (as seen in previous experiments). However, adult aphids were also found much more on the high-salinity plant compared to the control (average ± SE: high salinity 88.0 ± 22.4 vs control 11.9 ± 2.42; t19 = 3.40, P = 0.0031). This difference in adults should only be due to differential movement since the experiment was not long enough for aphids to lay nymphs on the experimental plants that grew to adults. Fig. 4. View largeDownload slide Distribution of aphids (adults plus juveniles) on high-salinity plants compared to low-salinity plants. Each circle represents the results from a given cage. The circle’s position on the x-axis shows the number of aphids that were on the high-salinity plant and the position on the y-axis shows the number of aphids on the low-salinity plant in the same cage. The dotted line is the 1:1 line where the number of aphids on each plant would be equal. Circles to the left of that line had relatively more aphids on the low-salinity plant in that cage and the circles to the right of that line had relatively more aphids on the high-salinity plant in that cage. Fig. 4. View largeDownload slide Distribution of aphids (adults plus juveniles) on high-salinity plants compared to low-salinity plants. Each circle represents the results from a given cage. The circle’s position on the x-axis shows the number of aphids that were on the high-salinity plant and the position on the y-axis shows the number of aphids on the low-salinity plant in the same cage. The dotted line is the 1:1 line where the number of aphids on each plant would be equal. Circles to the left of that line had relatively more aphids on the low-salinity plant in that cage and the circles to the right of that line had relatively more aphids on the high-salinity plant in that cage. Discussion Salinity had a consistently positive effect on SBA. Their population increased with salinity as measured by the number of aphids found on plants grown across a range of saline soils. Such differences in the number of aphids could have been caused by a number of different demographic changes; therefore, we performed complementary experiments to help explore different possible effects of salinity. Our second experiment showed that SBA fecundity over 3 d increased with salinity. Our third experiment expanded this result to show that SBA produced more offspring throughout their entire lives and that SBA lived longer on host plants grown in saline conditions compared to SBA reared on nonsaline plants. All of these factors could help lead to changes in the total number of aphids on plants grown in higher salinity. Moreover, our fourth experiment determined that SBA differentially distributed in response to salinity. Although the few experiments performed in agroecosystems with salinity have failed to show a consistent effect across herbivores (reviewed in Harmon and Daigh 2017), this set of experiments showed similar results to those with two-spotted spider mites (Eichele-Nelson et al. 2017). In that study, fecundity and numbers of two-spotted spider mite increased as salinity increased for soybean plants. While it is only two examples, it is worth beginning to speculate whether herbivores on soybeans might have a consistent response to salinity. No such generality thus far exists for all aphids. Some previous studies found results similar to ours in that salinity had positive effects on aphids (Braun and Fluckiger 1984, Spencer and Port 1988, Polack et al. 2011). However, a controlled experiment from one of those studies also found no effect of salinity (Spencer and Port 1988), and yet another study showed a general negative impact of salinity on aphids that varied somewhat dependent with plant (Araya et al. 1991). While still a relatively small sample size, these results could indicate that salinity effects in plant–aphid systems depend more on the particular species of plant or aphid. While previous studies of salinity measured demographic and population level effects, movement and distribution are also important to consider when studying herbivore–plant interactions, especially with crop pests. Movement can impact individual fitness, population dynamics, and species distribution (Bowler and Benton 2005). This is especially true when plant quality motivates herbivore movement and gives the insect a chance to increase their fitness by finding a more suitable host (as in Whalen and Harmon 2012). While we did not directly observe individuals moving in our experiment, we know that the adults in our experiment must have come from the original source plant. Thus, there was something about the higher salinity plant that either attracted the aphid to the high-salinity plant or decreased their willingness to leave that plant and find a different host. This behavior could have important implications for population growth and infestation within soybean fields. In agricultural fields, soil salinity can have a patchy distribution, with areas of high salinity located near areas of low salinity. Given the differences we found in both fitness and movement, saline areas within a field could become hot spots where SBA populations increase at a much greater rate than other areas. Such areas would have consequences for scouting efforts while also potentially providing ‘source’ areas where aphid populations grow quickly and spread to the rest of the field. Thus, salinity could be an important factor in determining the risk of SBA being a problem in a given field. Since salinity can also decrease crop yield (Butcher et al. 2016), our results indicate that salinity can negatively impact crops in multiple ways and therefore may help encourage producers to manage their salinity issues. Pests like SBA are, however, potentially influenced by additional factors that would need to be considered in relation to salinity. For example, many studies have been performed on natural enemies and SBA densities (e.g., Donaldson et al. 2007). While we do not yet know what impacts salinity has on the natural enemies of these herbivores, the results from our experiments could suggest important implications. For example, in one optimistic scenario, SBA first aggregate and grow in high-salinity areas of a field, which might cause natural enemies that respond to high densities to be drawn into these spots, reproduce, and then spread throughout the area. Another possible benefit may be from SBA in saline areas living longer which could potentially increase parasitoid populations by giving aphid parasitoids more time to find aphids and complete their development (e.g., Ballman et al. 2012). Our study demonstrates that salinity can have positive effects on SBA across a range of different aphid characteristics. This study furthers the knowledge of how terrestrial herbivores respond to soil salinity while demonstrating the multiple ways we can see herbivores respond to changing abiotic variables that alter their host plant. Investigating this type of knock-on effect helps us understand how abiotic changes affect the whole system. It is not just the central host plant that changes, but also all the other organisms that depend on that plant. This approach helps develop richer and more meaningful predictions of how changing abiotic factors ultimately affect ecosystem services. 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Environmental Entomology – Oxford University Press
Published: Aug 1, 2018
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