The purpose of the present study was to investigate how plant spatial patterns and insect behavior interact to influence the population dynamics of insects using the plants. The study included three phases: l) field experiments using collards (Brassica oleracea) and the crucifer insect fauna; 2) simulation models representing the population dynamics of an insect herbivore as functions of insect dispersal behavior and host plant patch size; and 3) model-field syntheses integrating model predictions and field variability estimates to choose an appropriate spatial scale for future field experiments or applications.
In field experiments on surrounding plant type, collards were planted with 1) other collards; 2) collards treated with a systemic insecticide; 3) broccoli, a related host; and 4) tomatoes, an unrelated host whose odor may repel crucifer pests. In three such experiments, eggs and larvae of the imported cabbageworm (Pieris rapae (L.)) were most abundant an collards surrounded by tomatoes. These results were contrary to those from previous experiments with other crucifer pests, but can perhaps be explained by P. rapae's preference for ovipositing on isolated host plants. In three patch size experiments, P. rapae eggs and larvae were more abundant on collards in small patches; in one of these experiments, the diamondback moth (Plutella xylostella (Linn.)) was more abundant in large patches. The results for P. rapae were consistent with previous studies showing more oviposition on plants in smaller patches and on plants at the edge of a patch.
The simulation models predicted mean level and variability of an insect herbivore population based on interactions between insect behavior and host plant patch size. Features of insect behavior modeled were: 1) an inverse relationship between distance and dispersal; 2) preferences for host vs. nonhost plants, which differ for generalist and for specialist herbivores; and 3) preference of specialists for larger areas of host plants. Aspects of plant pattern studied were size and number of host plant patches in a background of nonhost vegetation. Constant, exponential and logistic growth of insect populations in the nonhost background and in the host patches were used.
The models were designed to provide a theoretical framework for studying interactions between insect behavior and plant pattern, not to duplicate the dynamics of the field system. However, for the model-field syntheses, parameters of one model were fit to field data to establish a correspondence between expected differences in population levels predicted by the model and variability estimates obtained in the field experiments. The fitted model was used to construct a graph of differences in population levels versus patch size. Field variability estimates were used to calculate the least difference in population levels, for a given number of replicates and subsamples, that could be detected in field experiments. The least difference was compared with the differences predicted b y the fitted model to determine what patch sizes will produce significant effects of patch size on insect populations. This method was used to assess feasibility of future field experiments and to select appropriate patch sizes. The method can also be used to evaluate crop field size in agroecosystems as a component of pest management.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-7441 |
| Date | 01 May 1980 |
| Creators | Maguire, Lynn A. |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
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