Nematode Sampling and Economic Thresholds Howard Ferris Department of Entomology and Nematology University of California, Davis April, 2012

Objectives of monitoring/sampling for nematodes A. Assess risk of loss i) Determine presence or absence a. assessment of long-term risk - perennials b. virus-vectors c. root crops - direct damage. d. exotic pests ii) Determine population abundance - relative/absolute a. predict potential yield/damage b. assess rate of population change (+ or -) iii) Determine spatial patterns. a. pattern of potential loss b. partial treatment/management B. Faunistic studies i) Community structure and ecosystem analysis a. foodweb structure and function ii) Environmental impacts/quality /markers a. effects of disturbance and contaminants b. recovery from perturbation iii) Collections / surveys a. faunal inventories b. biodiversity studies

Environmental heterogeneity Zones and Gradients: texture structure temperature water O 2 CO 2 NO 3 NH 4 minerals Soil Food Webs – Environmental Effects on Structure Separate metacommunities?

Biological/Ecological Considerations A. Factors Affecting Microdistribution i) Life history strategies a. feeding/parasitism b. reproductive behavior c. motility ii) Food distribution a. crop spacing b. root morphology iii) Ecological requirements a. moisture b. temperature (magnitude and stability) c. oxygen B. Factors Affecting Macrodistribution i) Crop history, management, field usage a. crop sequence b. spatial arrangement of previous crops ii) Age of infestation a. time to spread from a point source iii) Edaphic conditions a. soil texture patterns iv) Drainage patterns a. soil moisture levels b. soil aeration

Alternative Sampling Devices

Efficiency and Reliability - Optimal Sampling Methodology A. Pattern i) Organism moves to sampler a. only over small distances in soil organisms b. to roots of bioassay plants or to CO 2 attractants. ii) Sampler moves to organism a. core sampling - aggregate samples b. symptom assessment, e.g. gall ratings - where possible iii) Field Stratification - based on macrodistribution parameters a. minimizes variance within each stratum b. increases confidence in estimate of mean c. allows determination of spatial pattern B. Timing i) To maximize probability of achieving objectives a. detect presence when populations highest b. greatest precision when lowest? - but may be many misses! ii) To allow evaluation and management decision a. prior to planting b. end of growing season, following treatment, etc.

As sample units become larger, perception of aggregated patterns: aggregated > random > uniform

Xiphinema americanum

Some of those involved…. Dan Ball Larry Duncan Pete Goodell Joe Noling Diane Alston Sally Schneider Lance Beem Nematode Thresholds and Damage Levels

Seinhorst Damage Function Y=m+(1-m)z (P i -T) Y=relative yield m=minimum yield Z=regression parameter P i =population level T=tolerance level Based on preplant population levels – measured or predicted from overwinter survival rates

That initial population at which the loss in value due to nematode damage is equal to the cost of nematode management The Economic Threshold

That initial population at which the difference in crop value with and without management is equal to the cost of the management The Economic Threshold amended

Thresholds and Expected Yield Loss Meloidogyne incognita, J2/250 cc soil; adjusted for extraction efficiency Expected % yield loss at different preplant nematode densities CropTolerance Bell Pepper Cantaloupe Carrot Chile Pepper Cotton Cowpea Potato Snapbean Squash Sugarbeet Sweetpotato Tomato

Expected Damage Meloidogyne chitwoodi; summer crop potato; Klamath Basin Fall population levels; adjusted for extraction efficiency Expected % tuber blemish at different fall nematode densities J2/250 cc % Blemish

Thresholds and Expected Yield Loss CultivarSoilLocation(T)oleranceZm US-H9clayImperial US-H9loamSJV/Idaho Heterodera schachtii, eggs/100g soil Sugarbeets CultivarSoilLocationTolerance US-H9clayImperial US-H9loamSJV/Idaho Expected % yield loss at different preplant nematode densities

Economic Threshold – Discrete Costs Model

Optimization – Continuous Costs Model

Optimized Crop Rotation Sequences

Start Rotation with Host Crop

Start Rotation with Non-host Crop

temporal avoidance

Perennial Crop Considerations

Year DD AUC LU LT NU NT Year DD AUC LU LT NU NT Year DD AUC LU LT NU NT

Noling and Ferris (1987)

References Burt, O. R. and H. Ferris Sequential decision rules for managing nematodes with crop rotations. J. Nematology 28: Ferris, H Nematode economic thresholds: derivation, requirements and theoretical considerations. J. Nematology 10: Ferris, H Density-dependent nematode seasonal multiplication and overwinter survivorship: a critical point model. J. Nematology 17: Ferris, H., T. A. Mullens and K. E. Foord Stability and characteristics of spatial description parameters for nematode populations. Journal of Nematology 22: Kim D.G. and H. Ferris Relationship between crop losses and initial population densities of Meloidogyne arenaria in winter-grown oriental melon in Korea. J. Nematology 34: Noling, J.W. and H. Ferris Nematode-degree days, a density-time model for relating epidemiology and crop losses in perennials. J. Nematology 19: Seinhorst, J.W The relationship between nematode density and damage to plants. Nematologica 11: Seinhorst, J.W The relationship between population increase and population density in plant parasitic nematodes. II. Sedentary nematodes. Nematologica 13: More information: