Nematode Samplingand

Faunal Analysis

Howard FerrisDepartment of Nematology

University of California, Davis

hferris@ucdavis.edu

March, 2005

 Objectives of monitoring/sampling for nematodes

A. Assess risk of lossi) Determine presence or absence

a. assessment of long-term risk - perennialsb. virus-vectorsc. root crops - direct damage.d. exotic pests

ii) Determine population abundance - relative/absolutea. predict potential yield/damageb. assess rate of population change (+ or -)

iii) Determine spatial patterns.a. pattern of potential lossb. partial treatment/management

B. Faunistic studiesi) Community structure and ecosystem analysis

a. foodweb structure and functionii) Environmental impacts/quality /markers

a. effects of disturbance and contaminantsb. recovery from perturbation

iii) Collections / surveysa. faunal inventoriesb. biodiversity studies

Environmental heterogeneity

Zones andGradients:

texturestructuretemperaturewaterO2

CO2

NO3

NH4

minerals

Soil Food Webs – Environmental Effects on Structure

Separatemetacommunities?

Biological/Ecological Considerations

A. Factors Affecting Microdistributioni) Life history strategies

a. feeding/parasitismb. reproductive behaviorc. motility

ii) Food distributiona. crop spacingb. root morphology

iii) Ecological requirementsa. moistureb. temperature (magnitude and stability)c. oxygen

B. Factors Affecting Macrodistributioni) Crop history, management, field usage

a. crop sequenceb. spatial arrangement of previous crops

ii) Age of infestationa.  time to spread from a point source

iii) Edaphic conditionsa.  soil texture patterns

iv) Drainage patternsa. soil moisture levelsb. soil aeration

AlternativeSamplingDevices

Efficiency and Reliability - Optimal Sampling Methodology

A. Patterni) Organism moves to sampler

a. only over small distances in soil organisms b. to roots of bioassay plants or to CO2 attractants.

ii) Sampler moves to organisma. core sampling - aggregate samplesb. symptom assessment, e.g. gall ratings - where possible

iii) Field Stratification - based on macrodistribution parametersa. minimizes variance within each stratum b. increases confidence in estimate of mean c. allows determination of spatial pattern

B. Timingi) To maximize probability of achieving objectives

a. detect presence when populations highestb. greatest precision when lowest? - but may be many misses!

ii) To allow evaluation and management decisiona.  prior to plantingb. 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(Pi-T)

• Y=relative yield• m=minimum yield• Z=regression parameter• Pi=population level• T=tolerance level

• Based on preplant population levels – measured or predicted from overwinter survival rates

0

0.2

0.4

0.6

0.8

1

1.2

0 2 4 6 8

Ln (Pi+1)

Rel

ativ

e Y

ield

Thresholds and Expected Yield Loss

Meloidogyne incognita, J2/250 cc soil; adjusted for extraction efficiency

Expected % yield loss at different preplant nematode densities

Crop Threshold 1 2 5 10 20 50 100 200

Bell Pepper 25 0 0 0 0 0 2 5 8

Cantaloupe 4 0 0 1 3 7 17 30 46

Carrot 0 1 2 5 9 16 29 37 40

Chile Pepper 15 0 0 0 0 3 14 24 30

Cotton 22 0 0 0 0 0 6 15 27

Cowpea 52 0 0 0 0 0 0 6 8

Potato 7 0 0 0 4 15 34 47 51

Snapbean 5 0 0 0 1 3 10 18 29

Squash 0 3 5 12 23 41 74 93 100

Sugarbeet 0 0 0 1 1 2 5 8 10

Sweetpotato 0 1 2 4 8 15 30 43 51

Tomato 16 0 0 0 0 0 3 7 14

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 1 2 5 10 20 50 100 200 500

% Blemish 3 4 5 7 8 12 15 18 25

Thresholds and Expected Yield Loss

Cultivar Soil Location (T)olerance Z m

US-H9 clay Imperial 100 0.99886 0

US-H9 loam SJV/Idaho 300 0.99976 0

Heterodera schachtii, eggs/100g soil

Sugarbeets

Cultivar Soil Location Threshold 50 100 200 500 1000

US-H9 clay Imperial 100 0 0 11 37 64

US-H9 loam SJV/Idaho 300 0 0 0 5 15

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

HerbivoresBacterivoresFungivoresOmnivoresPredators

Functional Diversity of Nematodes

RhabditidaePanagrolaimidae

etc.

Short lifecycleSmall/ Mod. body sizeHigh fecunditySmall eggsDauer stagesWide amplitudeOpportunistsDisturbed conditions

AporcelaimidaeNygolaimidae

etc.

Long lifecycleLarge body sizeLow fecundityLarge eggsStress intolerantNarrow amplitudeUndisturbed conditions

Enrichment Indicators Structure Indicators

CephalobidaeAphelenchidae,

etc.

Moderate lifecycleSmall body sizeStress tolerantFeeding adaptationsPresent in all soils

Basal Fauna

Ba2

Fu2

Fu2

Ba1

Ba3

Fu3

Ca3

Ba4

Fu4

Ca4

Om4

Ba5

Fu5

Ca5

Om5

Enriched

Structured

Basal

Basalcondition

Structure index

Enr

ichm

ent i

ndex

•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)

0

50

100

0 50 100

Structure Index

Enr

ichm

ent I

ndex Prune

OrchardsYuba Co.

MojaveDesert

TomatoSystemsYolo Co.

Redwood Forest and

GrassMendocino

Co.

Trajectory Analysis of Some California Soil Systems

Carbon Pathways and Pools

Omnivory

Decomposition

Herbivory

Bacterial

Fungal

%Fungivore

%Bacterivore%Herbivore

Compromised-Not

Sustained

Fast-Ephemeral

Slow -Sustained

Characteristics of Foodweb Enrichment

FACE Site, Switzerland

0

25

50

75

100

0 25 50 75 100

%Biomass Fungivores+Bacterivores

%B

iom

as

s H

erb

ivo

res

L350/140

L350/560

L600/140

L600/560

T350/140

T350/560

T600/140

T600/560

Prune Orchards, California

0

20

40

60

80

100

0 20 40 60 80 100

%Biomass Fungivores+Bacterivores

%B

iom

as

s H

erb

ivo

res

Billiou

CSU Stony

Farmland

HeierBPS

HeierNBPS

OnstottBPS

OnstottNBPS

Stanfield

SAFS, Year 12

0

25

50

75

100

0 25 50 75 100

%Biomass Fungivores+Bacterivores

%B

iom

as

s H

erb

ivo

res

Conv/Bean

Low/Bean

Org/Bean

Conv/Corn

Low/Corn

Org/Corn

Conv/Saff

Low/Saff

Org/Saff

Conv/Tom

HI/Tom

Low/Tom

Org/Tom

Organic and Conventional Grasslands

0

25

50

75

100

0 25 50 75 100

%Biomass Fungivores+Bacterivores

%B

iom

as

s H

erb

ivo

res

Glanrhyd Org.

Glanrhyd Conv.

Goodwick Org.

Goodwick Conv.

Trawsgoed Org.

Trawsgoed Conv.

0

50

100

0 50 1000

50

100

0 50 100

Structure index

En

rich

me

nt in

de

xSampled 2000

Organically-managed for 12 years

Structure index

Sampled 2001After Deep Tillage

How Fragile is the System?

Berkelmans et al. (2003)

•Bongers, T., H. Ferris. 1999. Nematode community structure as a bioindicator in environmental monitoring. Trends Ecol. Evol. 14, 224-228.•Duncan, L. W. and H. Ferris. 1983. Effects of Meloidogyne incognita on cotton and cowpeas

in rotation. Proceedings of the Beltwide Cotton Production Research Conference: 22-26.•Ferris, H. 1984. Probability range in damage predictions as related to sampling decisions.

Journal of Nematology 16:246-251.•Ferris, H., D. A. Ball, L. W. Beem and L. A. Gudmundson. 1986. Using nematode count data

in crop management decisions. California Agriculture 40:12-14.•Ferris, H., T. Bongers, R. G. M. de Goede. 2001. A framework for soil food web diagnostics:

extension of the nematode faunal analysis concept. Appl. Soil Ecol. 18, 13-29. •Ferris, H., P. B. Goodell, M. V. McKenry. 1981. Sampling for nematodes. California Agriculture 35:13-15.•Ferris, H., M.M. Matute. 2003. Structural and functional succession in the nematode fauna of

a soil food web. Appl. Soil Ecol. 23:93-110.•Tenuta, M., H. Ferris. 2004. Relationship between nematode life-history classification and sensitivity to stressors: ionic and osmotic effects of nitrogenous solutions. J. Nematol. 36:85-94.

More information: http://plpnemweb.ucdavis.edu/nemaplex/nemaplex.htm

Some References