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Alternative food improves the combined effect of an omnivore and a predator on biological pest control. A case study in avocado orchards

Published online by Cambridge University Press:  08 December 2008

J.J. González-Fernández
Affiliation:
E.E. La Mayora, CSIC,29750 Algarrobo-Costa, Málaga, Spain
F. de la Peña
Affiliation:
E.E. La Mayora, CSIC,29750 Algarrobo-Costa, Málaga, Spain
J.I. Hormaza
Affiliation:
E.E. La Mayora, CSIC,29750 Algarrobo-Costa, Málaga, Spain
J.R. Boyero
Affiliation:
IFAPA, Centro de Churriana, Cortijo de la Cruz, s/n, 29140 Churriana, Málaga, Spain
J.M. Vela
Affiliation:
IFAPA, Centro de Churriana, Cortijo de la Cruz, s/n, 29140 Churriana, Málaga, Spain
E. Wong
Affiliation:
IFAPA, Centro de Churriana, Cortijo de la Cruz, s/n, 29140 Churriana, Málaga, Spain
M.M. Trigo
Affiliation:
Departamento Biología Vegetal, Universidad de Málaga, Campus de Teatinos, 29080 Málaga, Spain
M. Montserrat*
Affiliation:
E.E. La Mayora, CSIC,29750 Algarrobo-Costa, Málaga, Spain
*
*Author for correspondence Fax: +34 952552677 E-mail: mmontserrat@eelm.csic.es
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Abstract

Ecological communities used in biological pest control are usually represented as three-trophic level food chains with top-down control. However, at least two factors complicate this simple way of characterizing agricultural communities. First, agro-ecosystems are composed of several interacting species forming complicated food webs. Second, the structure of agricultural communities may vary in time. Efficient pest management approaches need to integrate these two factors to generate better predictions for pest control. In this work, we identified the food web components of an avocado agro-ecosystem, and unravelled patterns of co-occurrence and interactions between these components through field and laboratory experiments. This allowed us to predict community changes that would improve the performance of the naturally occurring predators and to test these predictions in field population experiments. Field surveys revealed that the food-web structure and species composition of the avocado community changed in time. In spring, the community was characterized by a linear food chain of Euseius stipulatus, an omnivorous mite, feeding on pollen. In the summer, E. stipulatus and a predatory mite, Neoseiulus californicus, shared a herbivorous mite prey. Laboratory experiments confirmed these trophic interactions and revealed that N. californicus can feed inside the prey nests, whereas E. stipulatus cannot, which may further reduce competition among predators. Finally, we artificially increased the coexistence of the two communities via addition of the non-herbivore food source (pollen) for the omnivore. This led to an increase in predator numbers and reduced populations of the herbivore. Therefore, the presence of pollen is expected to improve pest control in this system.

Information

Type
Research Paper
Copyright
Copyright © 2008 Cambridge University Press
Figure 0

Fig. 1. Experimental avocado orchard with intercropped maize plants. Thin lines represent laneways. Thick black lines are the laneways with maize. Grey circles are the trees chosen for sampling. Small black circles represent the wooden sticks for pollen deposition measures.

Figure 1

Fig. 2. Population dynamics (mean±SE) of the persea mite Olygonichus perseae (grey triangles), the phytoseiid mites (▪) and pollen abundance (○) in an avocado orchard during 2006.

Figure 2

Table 1. (a) Phytoseiid mite species and abundance in the two peaks of the dynamics of population (i.e. weeks 23 and 40). (b) Pollen species and abundances in the weeks of maximum density (weeks 20–23).(a)

Figure 3

Fig. 3. Predation rates (mean±SE) of E. stipulatus and N. californicus when they were offered (a) eggs of O. perseae laid by females inside the nest (□, eaten;, alive), and (b) females of the persea mite.

Figure 4

Fig. 4. Population dynamics (mean±SE) of the persea mite, phytoseiid mites, and number of necrotic spots in trees next to laneways with maize plants (○) or in laneways without maize plants (•). In the left graphs, only trees next to laneways with maize are considered and sides within the same trees are represented. Graphs on the right compare trees next to laneways with maize with trees next to laneways without maize.

Figure 5

Table 2. Repeated measures ANOVA for each of the three variables measured (i.e. # nest per UML2, # spots per UML2 and # phytoseiid per leaf) when only trees from the plot with maize were considered (within trees analysis) and laneway side (with or without maize) was used as independent variable and when trees next to laneways with or without maize were compared (between trees analysis).

Figure 6

Fig. 5. Maize pollen deposition (number of grains/cm2/day) on microscope slides located next to laneways with maize plants (upper panels) and next to laneways without maize plants (lower panels). Different numbers in legends correspond to different trees, and W and E stands for West and East, respectively. Cm, closest to maize. Exact location of the wooden sticks can be seen in fig. 1 (□, 2W; , 2E, Cm; □, 3W, Cm; , 3E; □, 1W; , 1E; □, 4W; , 4E).

Figure 7

Fig. 6. Natural community modules present in an avocado agro-ecosystem of south-eastern Spain during (a) spring and (b) summer, and (c) community module artificially created to control the pest O. perseae. White and grey drawings of phytoseiids correspond to E. stipulatus and N. californicus, respectively. Solid arrows indicate trophic interactions, dotted arrows indicate indirect predator-plant positive interactions (trophic cascade) and dashed arrows indicate indirect predator-predator (competition) or indirect plant-plant (apparent competition) negative interactions. The strength of the lines indicates the interaction strength. The question mark in (b) indicates that predation of E. stipulatus on N. californicus in the field, although potentially possible, it has not been measured either in this work or elsewhere.

Figure 8

Appendix 1. Two-factor nested MANOVAs with ‘tree’ and ‘side tree’ as factors, ‘side tree’ nested to ‘tree’, and each of the variables considered (i.e. # nests per UML2, # spots per UML2, and # phytoseiids per leaf) at each of the four dates used as dependent variables. This additional statistical analysis is provided to account for possible dependence of data in the ‘within tree’ analysis provided in the text. The analysis shows that trees differed in the number of nests and spots per UML. Yet, those variables differed depending on the side of the tree as well. The number of phytoseiid mites per leaf was also different depending on the side of trees.