Nematode Samplingand
Faunal Analysis
Howard FerrisDepartment of Nematology
University of California, Davis
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
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