Measuring yield benefits of biocontrol services in bioenergy landscapes

Background/Question/Methods

Natural enemies provide important biocontrol services by suppressing pests that reduce crop yields. Due to the expansion of bioenergy crops, agricultural landscapes in the Midwest will undergo important changes. To understand how these changes will affect ecosystem services in the region, we are studying how intensification and homogenization of the landscape affect biocontrol. Prior work by our group has determined that landscape structure affects predation rates of crop pests in two bioenergy crops. This current research aimed to a) examine biocontrol services in both bioenergy and food crops; b) quantify impact of natural enemies on yields and c) determine if biocontrol services vary with landscape composition. To accomplish these goals, we established small gardens with food (collards) and bioenergy (soybean) crops in 20 soybean fields in MI and WI along a landscape intensification gradient (i.e. from fields surrounded by a high proportion of natural and semi-natural habitats, to fields surrounded by a high proportion of annual agriculture). In each garden we conducted cage experiments where natural enemies were excluded to estimate their impact on insect pests and yields. We conducted biweekly insect counts and, at the season’s end, measured yield for both crops.  

Results/Conclusions

We found that the most abundant natural enemies were parasitoid wasps, pirate bugs, spiders, ladybugs, and lacewings. The natural enemies’ effect on green peach aphids in collards was marginally positively associated with landscape diversity and had a significant positive correlation with the proportion of small grains at a 1.5 km scale. However, chewing insects proved more important than aphids in reducing collard yields. In soybean, natural enemies suppressed soybean aphids, reducing average yield loss by 27%. However, we did not find any significant relationships between yield increase due to natural enemies and landscape variables at the 1.5 km scale. The next step in our analysis is to determine the effects of landscape variables on these measured biocontrol services at different spatial scales taking into account the spatial distribution of the different landscape components.