Nematode Sampling and Faunal Analysis Howard Ferris Department of Nematology University of California, Davis March, 2005

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

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

Thresholds and Expected Yield Loss Meloidogyne incognita, J2/250 cc soil; adjusted for extraction efficiency Expected % yield loss at different preplant nematode densities CropThreshold 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 CultivarSoilLocationThreshold US-H9clayImperial US-H9loamSJV/Idaho Expected % yield loss at different preplant nematode densities

Soil Food Webs - Function Decomposition of organic matter Cycling of minerals and nutrients Reservoirs of minerals and nutrients Redistribution of minerals and nutrients Sequestration of carbon Degradation of pollutants, pesticides Modification of soil structure Community self-regulation Biological regulation of pest species

Soil Food Web Structure - the need for indicators

The Nematode Fauna as a Soil Food Web Indicator Herbivores Bacterivores Fungivores Omnivores Predators

Functional Diversity of Nematodes

Rhabditidae Panagrolaimidae etc.  Short lifecycle  Small/ Mod. body size  High fecundity  Small eggs  Dauer stages  Wide amplitude  Opportunists  Disturbed conditions Aporcelaimidae Nygolaimidae etc.  Long lifecycle  Large body size  Low fecundity  Large eggs  Stress intolerant  Narrow amplitude  Undisturbed conditions Enrichment Indicators Structure Indicators Cephalobidae Aphelenchidae, etc.  Moderate lifecycle  Small body size  Stress tolerant  Feeding adaptations  Present in all soils Basal Fauna

Ba 2 Fu 2 Ba 1 Ba 3 Fu 3 Ca 3 Ba 4 Fu 4 Ca 4 Om 4 Ba 5 Fu 5 Ca 5 Om 5 Enriched Structured Basal condition Structure index Enrichment index Disturbed N-enriched Low C:N Bacterial Conducive Maturing N-enriched Low C:N Bacterial Regulated Matured Fertile Mod. C:N Bact./Fungal Suppressive Degraded Depleted High C:N Fungal Conducive Testable Hypotheses of Food Web Structure and Function Ferris et al. (2001)

Structure Index Enrichment Index Prune Orchards Yuba Co. Mojave Desert Tomato Systems Yolo Co. Redwood Forest and Grass Mendocino Co. Trajectory Analysis of Some California Soil Systems

Carbon Pathways and Pools Omnivory Decomposition Herbivory Bacterial Fungal

Structure index Enrichment index Sampled 2000 Organically-managed for 12 years Structure index Sampled 2001 After Deep Tillage How Fragile is the System? Berkelmans et al. (2003)

Bongers, T., H. Ferris Nematode community structure as a bioindicator in environmental monitoring. Trends Ecol. Evol. 14, Duncan, L. W. and H. Ferris Effects of Meloidogyne incognita on cotton and cowpeas in rotation. Proceedings of the Beltwide Cotton Production Research Conference: Ferris, H Probability range in damage predictions as related to sampling decisions. Journal of Nematology 16: Ferris, H., D. A. Ball, L. W. Beem and L. A. Gudmundson Using nematode count data in crop management decisions. California Agriculture 40: Ferris, H., T. Bongers, R. G. M. de Goede A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Appl. Soil Ecol. 18, Ferris, H., P. B. Goodell, M. V. McKenry Sampling for nematodes. California Agriculture 35: Ferris, H., M.M. Matute Structural and functional succession in the nematode fauna of a soil food web. Appl. Soil Ecol. 23: Tenuta, M., H. Ferris Relationship between nematode life-history classification and sensitivity to stressors: ionic and osmotic effects of nitrogenous solutions. J. Nematol. 36: More information: Some References