Advertisement

Top-down suppression of arthropod herbivory in intercropped maize and organic farms evidenced from δ13C and δ15N stable isotope analyses

  • Nickson Erick OtienoEmail author
  • James Stephen Pryke
  • Mike Butler
  • Shayne Martin Jacobs
Research Article
Part of the following topical collections:
  1. Pest control

Abstract

Maize is a globally important cereal crop and a staple in sub-Saharan Africa, where it is predominantly grown by small-scale farmers. Its production, however, is undermined by numerous herbivorous arthropods, and agrochemicals used for controlling such pests are increasingly unaffordable. Farmers therefore require cheaper, effective and environmentally sustainable pest management alternatives. This study explored the hypothesis that boosting habitat heterogeneity through organic farming and intercropping enhances arthropod predator-herbivore feeding linkages that naturally suppress herbivory across non-Bt maize fields. To test this, δ13C and δ15N stable isotope analyses were conducted to establish feeding pathways from maize, legume intercrops, and marginal vegetation, through arthropod herbivores and predators across 15 small-scale maize fields in western Kenya. Farming and cropping systems’ roles in trophic linkages were also assessed. Feeding connections and plant food source contributions to arthropod consumer diets were subsequently determined using Bayesian mixing models, and predator relative efficiencies also evaluated. The results showed significantly stronger predator-herbivore trophic linkages within intercropped than monoculture fields, while farming system showed no effect. Herbivores showed stronger connections to crops than to noncrops, suggesting higher vulnerability for crops. For predators, earwigs derived most basal carbon from maize; wasps and predatory beetles, from legumes; ants, from both maize and legumes; and spiders, from both crops and noncrops. Ants and earwigs are important in maize herbivore regulation, particularly for intercropping; wasps and predatory beetles for regulating legume herbivores; and spiders for whole-field herbivore regulation. Most studies have focused on single species at single-trophic levels, but here we demonstrate, for the first time in sub-Saharan Africa, application of stable isotope analyses to characterize multitrophic feeding interactions that indicate effective agronomic practices for fostering top-down arthropod herbivore suppression in non-Bt maize fields. The results are useful in prescribing field practices with low-impact habitat management for sustainable small-scale agriculture rather than pesticide-based arthropod herbivore control.

Keywords

Ecosystem service Food-web Climate-smart agriculture Sustainable development 

Notes

Acknowledgments

We greatly thank the farmers and local County administration in Kakamega for permitting our access to the farms for sampling, and assistants Esther and Benson for their diligent work in the field. We also thank iThemba LABs Isotope Laboratory at Witswatersrand University for facilitating isotope analyses, Nairobi Museum for specimen identification support, and G. and C. Benson for the project funding.

Funding

This research was funded by private funds of Mr. and Mrs G. Benson with additional support from Stellenbosch University, and had no grant number.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

References

  1. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MH, Jada-Simon S (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol 24:127–135.  https://doi.org/10.1016/j.tree.2008.10.008 CrossRefPubMedGoogle Scholar
  2. Buckley R (1991) More aggressive ant species provide better protection for soft scale and mealybugs (Psedococcidae: Homoptera). Biotropica 23(3):282–286.  https://doi.org/10.2307/2388205 CrossRefGoogle Scholar
  3. Caut S, Angulo E, Courchamp F (2009) Variation in discrimination factors (δ15N and δ13C), effect of diet isotopic values and applications for diet reconstruction. J Appl Ecol 46:443–453.  https://doi.org/10.1111/j.1365-2664.2009.01620.x CrossRefGoogle Scholar
  4. Christensen DR, Moore BC (2009) Using stable isotopes and a multiple-source mixing model to evaluate fish dietary niches in a mesotrophic lake. Lake Reserv Manag 25(2):167–175.  https://doi.org/10.1080/07438140902905588 CrossRefGoogle Scholar
  5. Clough Y, Kruess A, Kleijn D, Tscharntke T (2005) Spider diversity in cereal fields: comparing factors at local, landscape and regional scales. J Biogeogr 32:2007–2014.  https://doi.org/10.1111/j.1365-2699.2005.01367.x CrossRefGoogle Scholar
  6. Cook SM, Khan ZR, Pickett JA (2007) The use of push-pull strategies in integrated pest management. Annu Rev Entomol 52:375–400.  https://doi.org/10.1146/annurev.ento.52.110405.091407 CrossRefPubMedGoogle Scholar
  7. Cotes B, González M, Benítez E, De Mas E, Clemente-Orta G, Campos M, Rodríguez E (2018) Spider communities and biological control in native habitats surrounding greenhouses. Insects 9:33.  https://doi.org/10.3390/insects9010033 CrossRefPubMedCentralGoogle Scholar
  8. Dib H, Jamont M, Sauphanoe B, Capowitz Y (2011) Predation potency and intra-guild interactions between generalist (Forficula auricularia) and specialist (Episyrphus balteatus) predators of the rosy apple aphid (Dysaphis plantaginea). Biol Contr 59:90–97.  https://doi.org/10.1016/j.biocontrol.2011.07.012 CrossRefGoogle Scholar
  9. Erhardt EB, Bedhart EJ (2013) A Bayesian framework for stable isotope mixing models. Environ Ecol Stat 20(3):377–397.  https://doi.org/10.1007/s10651-012-0224-1 CrossRefGoogle Scholar
  10. Food and Agriculture Organization of the United Nations (FAO) (2014) Pests and diseases management in maize, Uganda. Technologies and practices for small agricultural producers’ project. FAO, Rome. http://teca.fao.org/read/70195
  11. Gaigher R, Pryke JS, Samways MJ (2015) High parasitoid diversity in remnant natural vegetation, but limited spill-over to agricultural matrix in South African vineyard agroecosystems. Biol Conserv 186:69–74.  https://doi.org/10.1016/j.biocon.2015.03.003 CrossRefGoogle Scholar
  12. Jander G, Howe G (2008) Plant interactions with arthropod herbivores: state of the field. Plant Physiol 146(3):801–803.  https://doi.org/10.1104/pp.104.900247 CrossRefPubMedPubMedCentralGoogle Scholar
  13. Khan ZR, Pickett JA, Wadhams LJ, Muyekho F (2001) Habitat management strategies for the control of cereal stem borers and Striga weed in maize in Kenya. Insect Sci Appl 21(4):375–380.  https://doi.org/10.1017/S1742758400008481 CrossRefGoogle Scholar
  14. Kindlmann P, Yasuda S, Kajita Y, Dixon AFG (2005) Field test of the effectiveness of ladybirds in controlling aphids. 2nd Int Symp Biol Contr Arthrop. 12-16 September 2005. Davos, Switzerland, pp 441–447 https://www.bugwood.org/arthropod2005/vol2/9b.pdf Google Scholar
  15. Landis DA, Wratten SD, Gurr GM (2000) Habitat management to conserve natural enemies of arthropod pests in agriculture. Annu Rev Entomol 45:175–201.  https://doi.org/10.1146/annurev.ento.45.1.175 CrossRefPubMedGoogle Scholar
  16. Layman CA, Araujo MS, Boucek R, Hammerschlag-Peyer CM, Jud ZR, Matich P, Rosenblatt AE, Vaudo JJ, Yeager LA, Post DM, Bearhop S (2011) Applying stable isotopes to examine food – web structure: an overview of analytical tools. Biol Rev 87:545–562CrossRefGoogle Scholar
  17. Norton L, Johnson P, Joys A, Stuart R, Feber R, Manley WD, Fuller RJ (2009) Consequences of organic and non-organic farming practices for field, farm and landscape complexity. Agric Ecosyst Environ 129:221–227.  https://doi.org/10.1016/j.agee.2008.09.002 CrossRefGoogle Scholar
  18. Ostrom PH, Colunga-Garcia M, Gaze SH (1997) Establishing pathways of energy flow for insect predators using stable isotope ratios: field and laboratory evidence. Oecologia 109:108–113.  https://doi.org/10.1007/s004420050064 CrossRefGoogle Scholar
  19. Phillips DL, Newsome SD, Greg JW (2005) Combining sources in stable isotope mixing models: alternative methods. Oecologia 144:520–527.  https://doi.org/10.1007/s00442-004-1816-8 CrossRefPubMedGoogle Scholar
  20. Pinol J, Espadaler X, Canellas N, Perez (2009) Effects of concurrent exclusion of ants and earwigs on aphid abundance in an organic citrus grove. BioContr 54(4):515–527CrossRefGoogle Scholar
  21. Post DM (2002) Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology 83(3):703–718.  https://doi.org/10.1890/0012-9658(2002)083[0703:USITET]2.0.CO;2 CrossRefGoogle Scholar
  22. R Core Team (2017) R: A language and environment for statistical computing. R foundation for statistical computing, ViennaGoogle Scholar
  23. Schmidt MH, Soschewitz I, Thies C, Tscharntke T, Nentwig W (2005) Spiders in space: how landscape-wide movement of generalist predators influences local density, species richness, and biocontrol. 2nd Int. Symp Biol Contr Arthrop. September 12-16, 2005. Davos, Switzerland, pp 448–452 https://pdfs.semanticscholar.org/ce8a/de5e7b5baebb5bed5c49c780747aff9c70f1.pdf Google Scholar
  24. Sekamatte BM, Ogenga-Latigo M, Russell-Smith A (2003) Effects of maize-legume intercrops on termite damage to maize, activity of predatory ants and maize yields in Uganda. Crop Prot 22(1):87–93.  https://doi.org/10.1016/S0261-2194(02)00115-1 CrossRefGoogle Scholar
  25. Spence KO, Rosenheim JA (2005) Isotopic enrichment in herbivorous insects: a comparative field-based study of variation. Oecologia 146(1):89–97.  https://doi.org/10.1007/s00442-005-0170-9 CrossRefPubMedGoogle Scholar
  26. Thomson LJ, Macfadyen S, Hoffmann AA (2012) Predicting effects of climate change on agricultural pest natural enemies. Biol Control 52:296–306.  https://doi.org/10.1016/j.biocontrol.2009.01.022 CrossRefGoogle Scholar
  27. Tilman D, Knops J, Wedin D, Ritchie M, Siemann E (1997) Influence of functional diversity and composition on ecosystem processes. Science 277:1300–1302.  https://doi.org/10.1126/science.277.5330.1300 CrossRefGoogle Scholar
  28. Tixier P, Dagneau D, Mollot G, Vinatier F, Duyck PF (2012) Weeds mediate the level of intra-guild predation in arthropod food webs. J Appl Entomol 137(9):702–710.  https://doi.org/10.1111/jen.12060 CrossRefGoogle Scholar
  29. Winqvist C, Bengtsson J, Aavik T, Berendse F, Clement LW, Eggers S, Fischer C, Flohre A, Geiger F, Liira J, Pärt T, Thies C, Tscharntke T, Weisser WW, Bommarco R (2011) Mixed effects of organic farming and landscape complexity on farmland biodiversity and biological control potential across Europe. J Appl Ecol 48(3):570–579.  https://doi.org/10.1111/j.1365-2664.2010.01950.x CrossRefGoogle Scholar
  30. Wolts JM, Isaacs R, Landis DA (2012) Landscape structure and habitat management differentially influence insect natural enemies in an agricultural landscape. Agric Ecosyst Environ 152:40–49.  https://doi.org/10.1016/j.agee.2012.02.008 CrossRefGoogle Scholar

Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Conservation Ecology and EntomologyStellenbosch UniversityStellenboschSouth Africa
  2. 2.National Museums of KenyaNairobiKenya
  3. 3.iThemba LABS Isotope LaboratoryUniversity of WitwatersrandJohannesburgSouth Africa

Personalised recommendations