Spatial Dependence and Sampling of Phytoseiid Populations on Hass Avocados in Southern California.

Research on phytoseiid mites has been critical for developing an effective biocontrol strategy for suppressing Oligonchus perseae Tuttle, Baker, and Abatiello (Acari: Tetranychidae) in California avocado orchards. However, basic understanding of the spatial ecology of natural populations of phytoseiids in relation to O. perseae infestations and the validation of research-based strategies for assessing densities of these predators has been limited. To address these shortcomings, cross-sectional and longitudinal observations consisting of >3,000 phytoseiids and 500,000 O. perseae counted on 11,341 leaves were collected across 10 avocado orchards during a 10-yr period. Subsets of these data were analyzed statistically to characterize the spatial distribution of phytoseiids in avocado orchards and to evaluate the merits of developing binomial and enumerative sampling strategies for these predators. Spatial correlation of phytoseiids between trees was detected at one site, and a strong association of phytoseiids with elevated O. perseae densities was detected at four sites. Sampling simulations revealed that enumeration-based sampling performed better than binomial sampling for estimating phytoseiid densities. The ecological implications of these findings and potential for developing a custom sampling plan to estimate densities of phytoseiids inhabiting sampled trees in avocado orchards in California are discussed.

Sampling method evaluation and empirical model fitting for count data to estimate densities of Oligonychus perseae (Acari: Tetranychidae) on 'Hass' avocado leaves in southern California.

Oligonychus perseae (Acari: Tetranychidae) is an important foliar spider mite pest of 'Hass' avocados in several commercial production areas of the world. In California (USA), O. perseae densities in orchards can exceed more than 100 mites per leaf and this makes enumerative counting prohibitive for field sampling. In this study, partial enumerative mite counts along half a vein on an avocado leaf, an industry recommended practice known as the "half-vein method", was evaluated for accuracy using four data sets with a combined total of more than 485,913 motile O. perseae counted on 3849 leaves. Sampling simulations indicated that the half-vein method underestimated mite densities in a range of 15-60 %. This problem may adversely affect management of this pest in orchards and potentially compromise the results of field research requiring accurate mite density estimation. To address this limitation, four negative binomial regression models were fit to count data in an attempt to rescue the half-vein method for estimating mite densities. These models were incorporated into sampling plans and evaluated for their ability to estimate mite densities on whole leaves within 30-tree blocks of avocados. Model 3, a revised version of the original half-vein model, showed improvement in providing reliable estimates of O. perseae densities for making assessments of general leaf infestation densities across orchards in southern California. The implications of these results for customizing the revised half-vein method as a potential field sampling tool and for experimental research in avocado production in California are discussed.