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Agronomy Journal 94:1146-1155 (2002)
© 2002 American Society of Agronomy

POTATO

Population Dynamics and Distribution of Root Lesion Nematode (Pratylenchus penetrans) over a Three-Year Potato Crop Rotation

Gaylon D. Morgan*,a,b, Ann E. MacGuidwina, Jun Zhua and Larry K. Binninga

a Dep. of Stat., Univ. of Wisconsin, Madison, WI 53706
b Dep. of Plant Sci. and Landscape Syst., Univ. of Tennessee, 2431 Center Dr., Knoxville, TN 37996-4500

* Corresponding author (gmorgan2{at}utk.edu)

Received for publication July 16, 2001.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Population dynamics of Pratylenchus penetrans Cobb (root lesion nematode) were investigated in commercial potato (Solanum tuberosum L.) fields in the Central Sands of Wisconsin to test the hypothesis that cultural and management practices influence spatial distribution and temporal stability of nematodes over a 3-yr crop rotation. From 1998 to 2000, P. penetrans populations were investigated in fumigated and unfumigated commercial potato fields and in the subsequent rotational crops {corn (Zea mays L.) or soybean [Glycine max (L.) Merr.] and fresh market vegetables} and winter cereal cover crops. Pratylenchus penetrans populations were quantified in each field using a 0.5-ha uniform sampling grid. Traditional and geostatistical methods and interpolation maps were used to estimate the spatial distribution and temporal stability of nematode populations within each field and crop. In fumigated and unfumigated fields, the mean populations increased as the rotation progressed (potato->corn->vegetable). Population densities of P. penetrans increased more during the corn crop than potato crop. According to the Index of Dispersion, P. penetrans were aggregated (clumped) in all unfumigated fields; however, aggregation was only detectable in the fumigated fields 2 or 3 yr following soil fumigation. Geostatistical methods identified aggregation in only one field. In many cases, higher nematode populations occurred near tillage implement entry locations into each field. Nematode densities alone were not highly correlated with potato yields, corn yields, soil moisture, or soil pH but were consistently correlated with Verticillium wilt (Verticillium dahliae Kleb.) symptoms in unfumigated fields. Populations expressed more temporal stability in unfumigated fields than in fumigated fields.

Abbreviations: ID, index of dispersion • GIS, geographic information system • GPS, global positioning system


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
P RATYLENCHUS penetrans Cobb (root lesion nematode) is an economically important plant parasitic nematode in the Wisconsin Central Sands and other potato-producing regions of North America (Townshend et al., 1978). Approximately 400 different crop and weed species serve as host to P. penetrans (Mai et al., 1977). This broad host range minimizes the potential to manage these nematodes by crop rotation with nonsusceptible hosts. Currently, soil fumigation is the primary management strategy employed by commercial producers; however, soil fumigation is expensive ({approx}$380 ha-1) and has numerous environmental concerns, including acute mammalian toxicity.

Pratylenchus penetrans damage threshold densities for potato was established at 100 to 200 nematodes 100 cm-3 soil (Olthof, 1987). In addition, the nematodes interact synergistically with Verticillium dahliae (Verticillium wilt) to further reduce potato growth and yield (Bowers et al., 1996; Botseas and Rowe, 1994; MacGuidwin and Rouse, 1990; Martin et al., 1982; Rowe et al., 1985; Saeed et al., 1998). This synergistic interaction between P. penetrans and V. dahliae reduces the density of P. penetrans required to cause economic potato yield losses (Martin et al., 1982; Rowe et al., 1987; Wheeler et al., 1992). However, threshold densities for P. penetrans and V. dahliae interacting synergistically have not been sufficiently established due to complex interactions between the pathogens. The P. penetrans interaction with V. dahliae has also been reported to increase the susceptibility of V. dahliae–tolerant potato cultivars to Verticillium wilt (MacGuidwin and Rouse, 1990).

Maintaining agricultural profitability while minimizing environmental impacts is a primary focus of current agricultural research. Research aimed at solving this issue has been traditionally accomplished through small-plot and temporal research where all but the sought component received little consideration. Component research continues to play a vital role in answering specific questions related to production agriculture. However, new technologies and software, including geographic information systems (GIS), global positioning systems (GPS), and geostatistical methods, have recently allowed parameters to be measured over time on a landscape scale. These technologies promote new research methodologies, goals, and perspectives about nematode ecology and management.

The natural spatial distribution of organism populations can be described by clumped (aggregated), uniform, or random distributions. Clumped and random distributions of species are more prevalent and depend on the availability of essential resources (Hopson and Wessells, 1990). Goodell and Ferris (1980) sampled a 7-ha alfalfa (Medicago sativa L.) field using an intensive grid system (6 by 6 m) and reported the numerous nematode species as fitting a negative binomial (aggregated) distribution. Sampling along a linear transect, Wheeler et al. (1994) reported that Meloidogyne hapla fit a negative binomial distribution in six of seven potato fields; however, P. penetrans only fit a negative binomial distribution in one of seven fields. Wallace (1991) reported spatial aggregation of numerous nematode species, including P. penetrans in an alfalfa field. However, limited research has categorized the spatial distribution of nematodes on landscapes of large-scale production potato fields and over a 3-yr crop rotation.

Despite reported aggregation of nematodes in agricultural fields, most nematicide applications and management assume a homogeneous nematode distribution. An increased understanding of nematode spatial and temporal distributions within commercial agricultural fields will add insight to P. penetrans' ecology as influenced by current management and cultural strategies. In addition, more precise cultural and management tactics may be implemented to increase profitability of commercial potato production while reducing pesticide inputs.

The natural dispersal of P. penetrans is generally considered to be short ranged, but animal movement, imported seed stock, field cultivation, and harvesting may greatly increase dispersal distances. A better understanding of P. penetrans distribution and its relationship with management strategies will lead to increased efficiency of current management strategies. Additionally, understanding P. penetrans' spatial distribution across a landscape may provide more complete information for improved regional management, modeling pest population dynamics for subsequent seasons, and site-specific management. Therefore, the objectives of this research were to determine (i) the existing spatial distribution of P. penetrans within production potato fields and rotational crops; (ii) P. penetrans spatial relationships and interactions with crop yields, V. dahliae, and field parameters; and (iii) the temporal stability of P. penetrans over a 3-yr crop rotation.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Field History
Research was conducted in cooperation with Coloma Farms near Coloma, WI, from 1998 through 2000. Four center-pivot irrigated potato fields and rotational crops were investigated. Each rotation began with long-season potato cultivars (Russet Burbank or Snowden) and was followed by two seasons of rotational crops. Research was initiated in 1998 (Season 1) on two commercial potato fields, CJ and ART, which were 46 and 53 ha, respectively. Research continued on these two fields for 1999 (second season) and 2000 (third season). In 1999, two additional 30-ha potato fields, KIR and SW, were selected for evaluation. For this article, Season 1 will always refer to the potato crop for all four fields, and rotational crops represent Season 2, 3, or both. The soils ranged from a sandy loam to loamy sand, including Plainfield sand (mixed, mesic Typic Udipsamments), Richford loamy sand (sandy, mixed, mesic Psammentic Hapudalfs), and Billet sandy loam (coarse-loamy, mixed, superactive, mesic Mollic Hapludalfs) with slopes ranging from 0 to 3.5%. Each field had similar potato-rotation cropping histories, i.e., potatoes every third year and rotational crops that included corn, soybean, and vegetables [sweet corn, pea (Pisum sativum L.), pepper (Capsicum annuum L.), or cucumber (Cucumis sativus L.)].

All management practices, including pest, soil, fertility, and irrigation, were at the farmer's discretion. The fall before the potato crop (Season 1), a fumigant biocide, metam sodium (sodium N-methyldithiocarbamate) (42%), was commercially applied (injected) into the soil at a rate of 134 kg ha-1 and was followed by a 2.5-cm irrigation application. Metam sodium was applied to one-third of the ART field (ART fumigated), one-half of the KIR field (KIR fumigated), and the entire SW field. All fields or portions of fields specified as unfumigated received a fumigant biocide application 3 yr before research initiation within each field. Spring field preparation consisted of glyphosate [isopropylamine salt of N-(phosphonomethyl) glycine] application at a rate of 1.12 kg ha-1 before spring incorporation of the cover crop and seedbed preparation. The potato crop row direction was perpendicular to the rotational crop row direction. Potato seed pieces were planted mid-April, and potato emergence occurred in mid-May. Vine desiccants were applied to the potato vines 2 to 4 wk before harvest. A fall cover crop, rye (Secale cereal L.) or wheat (Triticum aestivum L.), was planted following the incorporation of the previous crop's residue. Rotational crops were planted, managed, and harvested using standard cultural practices. Three of the four fields (ART, CJ, and KIR) were planted in corn, and the SW field was planted in soybean for the second season. Two years after the potato crop, in the third season, ART and CJ fields were planted to pepper and English pea, respectively.

Data Collection
A diamond-shaped grid system (160 by 80 m) was created in the CJ and ART fields. The average grid size was 0.5 ha, but the grid size varied because of field shapes. The grid locations were flagged and georeferenced with a Trimble differential GPS backpack unit and a Trimble data logger (Trimble Navigation, Sunnyvale, CA). The flags remained in the field throughout the entire season.

In 1999, the differential GPS backpack unit was used to relocate the 1998 sample point locations. Intermediate grid sample points were added within the grid scheme (160 by 80 m) to provide additional spatial distribution information at scales smaller than 0.5 ha. The intermediate sampling points were placed at approximately 8 and 24 m from the 0.5-ha grid sample points. Intermediate sample points were parallel to the second-season (1999) crop row direction and perpendicular to Season 1 (1998) potato crop row direction. The same grid pattern, including intermediate 8- and 24-m grid points, was also used for the KIR and SW fields in 1999 and 2000. The differential GPS unit was used to relocate the original sample point locations for all subsequent seasons in each of the fields.

Annual soil samples were taken between 17 June and 29 June to quantify P. penetrans at each georeferenced sample location. The total quantity of georeferenced sample locations in each field were as follows: CJ = 134, ART = 129, KIR = 90, and SW = 85. An intrarow composite sample (eight soil cores) was taken from a 3-m radius around each georeferenced point using a 2.0-cm-diam. soil probe to a depth of 18 cm. Soil samples were stored at 1°C until the nematode extraction process began within 13 d of sample collection. Pratylenchus penetrans from roots and soil were quantified from a 100-cm3 soil sample using the Baermann funnel technique (Jenkins, 1964) with a 48-h incubation for root fragments and centrifugation–sugar floatation process for soil. Soil inoculum assays for V. dahliae were conducted from approximately 10% of the grid sample locations to identify the presence of V. dahliae within a field (Nicot and Rouse, 1987). Verticillium wilt severity was visually assessed weekly as a percentage of plants displaying premature senescence and loss of turgor and wilting in single stems (Hooker, 1981, p. 62) within a 3-m radius around each grid sample point location.

In an attempt to determine relationships between P. penetrans and other field factors (i.e., crop, cover crop, weed, soil parameters, and field margins), the distribution of field factors was compared with the P. penetrans distribution. Soil pH and soil volumetric content measurements were chosen based on previous associations between P. penetrans and these soil factors and relative cost and rapidness of these measurements. Soil pH and soil volumetric water content were quantified during the third season (2000) for the ART and CJ fields at each georeferenced grid location. The soil pH in CaCl2 was measured using Thomas' (1996) procedures and a Corning model pH 30 probe. Soil volumetric water content was measured to a 20-cm depth following irrigation using a Campbell Scientific HydroSense soil moisture probe. The P. penetrans distribution was also compared with the soil texture present within each field according to the soil mapping units of the county USDA soil survey. Weed species and density were quantified for 9.3 m2 at each grid sample location, and a qualitative rating for cover crop density and control was recorded at each grid sample location. To identify the P. penetrans introduction into each field, the field was divided into two distinct areas using GIS software. Grid sample points within 50 m of the field edge were labeled field margins, and grid sample points greater than 50 m from the field edge were labeled internal field. Potato yields were calculated from harvesting 1.52 m from four potato rows (total of 6.8 m) adjacent to georeferenced sample points. Corn yields were calculated from a combine yield monitor for a 10-m radius area around each georeferenced point. Vegetable yields were not obtained due to harvesting complications associated with both the pea and pepper crop.

Georeference and Data Analysis
Pathfinder Office software (Sunnyvale, CA) was used to process and transfer all of the information from the Trimble data logger to the GIS software and vice versa. A differential signal from the Milwaukee, WI, Coast Guard tower provided the differential correction signal for real-time measurements. A minimum of 10 calculated locations were recorded per grid-sampling point. Position dilution of precision (PDOP) was maximized at 6.0, according to recommendations by Trimble Navigation. The accuracy for the differential GPS (Model 122) maintained an expected average submeter horizontal accuracy and 2- to 3-m vertical accuracy.

Differentially corrected GPS information was imported into the statistical software S-Plus version 4 (Mathsoft, Seattle, WA) equipped with the spatial statistical module. Data normality was evaluated using a quantile plot for P. penetrans and other parameters. A log10 data transformation was required to achieve normal data distribution. All parameters were analyzed for sample independence (spatial autocorrelation) using semivariograms. A 95% confidence interval was placed on the semivariogram points at each sample lag to aid in evaluating sample independence and determining spatial structure. A semivariogram model, including the range, sill, and nugget, were computed using weighted least squares algorithm as stated in the S-Plus spatial statistics manual (Kaluzny et al., 1997) for dependent (spatial autocorrelated) data. The best model was selected based on minimum mean squared error values.

Independent data (not spatially autocorrelated) were analyzed using traditional statistical methods. A paired t test was used to compare P. penetrans population changes over time, and a two-independent-sample t test was used to compare fumigated field parameters vs. unfumigated field parameters. Significant correlations among P. penetrans, Verticillium wilt ratings, soil moisture, soil pH, and crop yields were determined using Spearman's rank sum correlation tests (Ludwig and Reynolds, 1988).

The semivariogram model information was interpolated to create a 10 m-grid surface map using the Kriging algorithm and SSToolbox (Stillwater, OK). In spatially autocorrelated data, kriged surface maps were compared to determine the spatial distribution and temporal stability of the P. penetrans populations and other measured parameters in each field. In non-spatially autocorrelated (independent) data, inverse-distance (fourth power) interpolation maps were created and provided a visual image of the P. penetrans density and other parameters on a landscape.

An index of dispersion (ID) test (Ludwig and Reynolds, 1988) of P. penetrans was performed (P < 0.10) for each field and season to determine population distribution. The ID is a variance/mean ratio and is compared to a chi-square distribution to determine the spatial distribution (uniform, random, or aggregate) of populations. An ID value exceeding 1 indicates spatial aggregation; ID value equal to 1 indicates random distribution; and ID less than 1 indicates uniformity. The ID values may also be used as a relative comparison of degree of aggregation for similar-size data sets. Other variance/mean ratios reported in the literature were not used to analyze these data because a test for significance cannot be provided, i.e., no distribution is available for comparison. Although the ID test identifies the presence of aggregation, it does not provide information on the P. penetrans population locations, autocorrelation (independence) among samples, aggregation due to spatial structure, or population aggregate size.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Population Densities
Mean and range of P. penetrans counts were variable in each field and each year (Table 1). The initial mean populations within each of the unfumigated potato fields were below 100 nematodes 100 cm-3. Initial P. penetrans mean populations in fumigated fields were less than 3 nematodes 100 cm-3. The mean counts increased for every field, fumigated and unfumigated, throughout the sequential sampling dates, except in the ART unfumigated field where P. penetrans populations decreased (P < 0.05) between Season 1 and Season 2 (Table 2). Cultural and pest management practices and sampling methods were similar for all fields and do not explain the decrease in P. penetrans densities in the ART unfumigated field. Generally, P. penetrans counts increased over the cropping system and indicated that both corn and potato were good hosts. These results are in agreement with findings of Dickerson et al. (1964), Florini and Loria (1987), and Chen et al. (1995). The P. penetrans counts increased more between the second and third season (corn crop) than the first and second season (potato crop). This indicates the corn cropping system was more conducive to P. penetrans mean population increase than the potato cropping system, supporting findings of Dickerson et al. (1964) and contradicting those of Florini and Loria (1987). Season 1 maximum P. penetrans counts were high (>425 nematodes 100 cm-3) in each unfumigated field and were below economic thresholds of 100 to 200 nematodes 100 cm-3 (Olthof, 1987) for each of the fumigated fields (40 nematodes 100 cm-3) (Table 1). Mean P. penetrans densities were significantly lower throughout the entire rotation in the fumigated fields than the unfumigated fields (Table 3). Both rye and wheat have been demonstrated to serve as hosts for P. penetrans under greenhouse conditions (Theis et al., 1995; Townshend and Potter, 1976). However, Mai et al. (1977) reported that P. penetrans egg hatch and population growth were substantially reduced at soil temperatures below 9°C. Due to low soil temperatures typically observed in late fall, winter, and early spring in central Wisconsin, P. penetrans population increases were likely minimal on the winter cereal cover crops. Therefore, observed P. penetrans population increases resulted from reproduction on potato and corn crops.


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  		Table 1. Pratylenchus penetrans population mean, range, and comparison between internal field and field margins each season.

 

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  		Table 2. Mean P. penetrans population change and temporal stability over the crop rotation sequence.

 

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  		Table 3. Mean P. penetrans comparison between unfumigated and fumigated fields.

 
A t test was used to compare P. penetrans counts at the field margins (<50 m) vs. internal field (>50 m) to assess the likelihood that P. penetrans was introduced and remained near field edges. For Season 1, P. penetrans mean counts at the field margins were not significantly different from the internal fields portions for all fields (Table 1). Comparable P. penetrans densities were observed in the internal portion and field margins of fumigated fields and indicate that the fumigation treatment did not provide total control of the nematodes or P. penetrans was reintroduced into the fields by means other than equipment.

Spatial Structure
Semivariograms were constructed from the log nematodes 100 cm-3 soil for each sample date to examine the spatial aggregation of P. penetrans populations within each field. According to variography, aggregation was apparent only in the CJ field for Season 2 and 3 but not Season 1 (Fig. 1A, 1B, and 1C) . A Gaussian model best fit the CJ P. penetrans population data for Season 2 and 3. Seasons 2 and 3 range and sill (variance) identified spatial structural changes in the P. penetrans population between the second and third seasons (Fig. 1B and 1C). The range greatly increased from 71.2 m in Season 2 to 222.2 m in Season 3. A larger range indicated an increase in P. penetrans population aggregate size and dispersal into previously uninhabited areas within the field. The sill decreased from 0.5 in the second season to 0.16 in the third season and indicated that the P. penetrans population became more uniform within the field by the third season. The nugget effect (microscale variation) also decreased between the second and third season and supports an increase in population aggregate size in the CJ field.



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  		Fig. 1. Semivariograms for P. penetrans in the unfumigated CJ field for (A) Season 1, (B) Season 2, and (C) Season 3.

 
The first-season P. penetrans populations were not spatially aggregated according to semivariograms and could not be kriged (Fig. 1A). Therefore, an inverse-distance interpolation method provided a visual interpretation of the estimated P. penetrans population spatial locations within the CJ field. Pratylenchus penetrans were associated with the eastern to southeastern portions of the CJ field and were associated with primary tillage and planting implement field entry locations (Fig. 2A) . However, the largest P. penetrans counts were not at the immediate field edges but were found sporadically in other portions of the field.



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  		Fig. 2. Pratylenchus penetrans spatial distribution in the unfumigated CJ field for (A) Season 1, (B) Season 2, and (C) Season 3. The X indicates grid sample locations, and the <- indicates implement entry locations.

 
Kriged surface interpolation maps were created from the Season 2 and 3 semivariogram models in the CJ field. In Season 2, the majority of the field remained below the management threshold level, 100 nematodes 100 cm-3 (Fig. 2B and Table 4). Larger P. penetrans populations were more dispersed into internal portions of the field and were less associated with the implement entry locations than the Season 1 populations. The highest P. penetrans counts (200–1166 nematodes 100 cm-3) occurred indiscriminately in the internal portions of the field. The population distribution was not associated with the implement direction, cropping history, cultural practices, topography, or weed species populations.


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  		Table 4. Percentage of each field infested with P. penetrans by density category.{dagger}

 
The third-season P. penetrans populations in the CJ field were aggregated on a larger scale (222.2 m) as indicated by a larger semivariogram range (Fig. 1C). Higher P. penetrans populations were primarily concentrated in the southern portion of the field (Fig. 2C). Previous cropping system [Season 1 (potato) or Season 2 (corn)] did not provide a legitimate explanation for the third-season P. penetrans population distribution because a uniform potato and corn variety, planting date, cover crop, and pest and fertility program occurred uniformly over the entire field. The only known cultural or management difference between the northern and southern portion of the field was a delayed ({approx}7 d) pre-emergence tank mix of corn herbicides {atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine) and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methlethyl)acetamide} applied to the northern portion of the field for controlling the wheat cover crop, emerged weed seedlings, and nonemerged weeds. This delayed herbicide application resulted in postponed control of the wheat cover crop in the northern portion of the field and may have negatively influenced the nematode population. In this instance, the wheat may have served as a trap crop for P. penetrans and resulted in lower P. penetrans population in the northern field portion.

Variography did not identify P. penetrans spatial aggregation in any of the fields, except CJ. Therefore, inverse-distance interpolation maps for the ART fumigated and unfumigated, KIR fumigated and unfumigated, and SW fumigated field were used to visually assess P. penetrans populations. Populations of P. penetrans occurred near the field edges and/or implement entry points for the majority of the fields (Fig. 2–5) . However, the highest populations were not observed exclusively at the field entry points for tillage or planting implements. Also, dispersion of the P. penetrans populations did not follow any tillage or harvest implement pattern. Over the seasons, P. penetrans populations appeared to be dispersed from the field edges to the internal field portions. Larger populations were not consistently associated with field topography, soil type, or weed aggregate locations in any field.



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  		Fig. 5. Pratylenchus penetrans spatial distribution in the fumigated (metam sodium) SW field for (A) Season 1 and (B) Season 2. The X indicates grid sample locations, and the <- indicates implement entry locations.

 


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  		Fig. 3. Pratylenchus penetrans spatial distribution in fumigated (metam sodium) and unfumigated ART field areas for (A) Season 1, (B) Season 2, and (C) Season 3. The X indicates grid sample locations, and the <- indicates implement entry locations.

 


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  		Fig. 4. Pratylenchus penetrans spatial distribution in fumigated (metam sodium) and unfumigated KIR field areas for (A) Season 1 and (B) Season 2. The X indicates grid sample locations, and the <- indicates implement entry locations.

 
An ID test was used to determine the P. penetrans distribution (aggregated, uniform, or random) for each field and season (Table 5). Previous research has used a negative binomial test to determine P. penetrans population aggregation within potato fields (Wheeler et al., 1994). The ID and negative binomial test are both a measure of the variance/mean relationship and should provide similar conclusions; however, the negative binomial test was not an appropriate procedure for the grid-sampling scheme. When spatial structure is not apparent by variography, the ID test is an alternative statistical method for detecting spatial distribution of pests; however, it provides less information about the spatial relationships and spatial structure (i.e., aggregate size or variance) within a field. According to the ID test, aggregation of P. penetrans populations could not be detected using a 0.5-ha sampling grid size until at least one season after fumigation. Populations of P. penetrans were randomly distributed the first season following the fumigation of the ART potato field but were significantly aggregated for the subsequent seasons (Table 5). In the fumigated KIR and SW fields, P. penetrans populations were randomly distributed for Seasons 1 (potato) and 2 (corn). Populations of P. penetrans were aggregated in all unfumigated fields throughout the entire rotation. The level of aggregation coincides with reported P. penetrans veriforms fitting the negative binomial distribution (k = 0.52), an indicator of aggregation, in only one of seven commercial potato fields (Wheeler et al., 1994).


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  		Table 5. Index of dispersion for P. penetrans for each season.

 
Temporal Stability
Spearman's correlation analysis of P. penetrans densities was conducted between seasons to determine the level of P. penetrans temporal stability (Table 2). Significant temporal stability occurred in each field, except the KIR fumigated field. The highest correlation was greater than 0.70 for the ART unfumigated field between Season 1 and 2, and the weakest significant correlation was 0.19 for the SW fumigated field between the first and second season. According to Spearman's correlation and inverse-distance maps, minimal P. penetrans temporal population stability occurred in the KIR and SW fumigated fields (Fig. 4 and 5). The low temporal stability found in the KIR fumigated and SW fumigated fields may have been partially a result of measurement error (processing and counting) in Season 1 because of the extremely low P. penetrans populations. MacGuidwin (1989) reported an average soil and root recovery rate of 36.0 and 26.5%, respectively, for P. scribneri on similar soil textures. Considering P. penetrans populations were not below measurement error, then the nematodes were introduced into the field between Season 1 and 2 sampling dates (e.g., by tillage, harvesting equipment, and wind). Carroll and Viglierchio (1981) reported nematode redeposition up to 5 km per erosion event when significant soil surface nematode populations were combined with dry loose soil or dry tillage operations and optimal atmospheric conditions. These authors also reported that nematode forms were more erodible than soil particles and natural lofting may occur at wind speeds exceeding 3 m s-1. Prevailing winds for this geographic region regularly exceed 3 m s-1 and likely contributed to P. penetrans dispersal into previously uninhabited field portions.

In the CJ field, inverse-distance and kriged maps were used to assess temporal stability (Fig. 2A–2C). Populations of P. penetrans appeared to maintain temporal stability between the first (1998), second (1999), and third (2000) seasons. Although no spatial population structure was identified for Season 1, locations with relatively high populations in Season 1 maintained relatively high populations in subsequent seasons. Aggregate size of P. penetrans populations increased as populations were dispersed to a more uniform distribution. An increase in P. penetrans–infested area demonstrates that the P. penetrans dispersal techniques and cropping system are sufficient for P. penetrans survival and dispersal to the majority of each field, 6 yr after soil fumigation.

Using interpolated maps, the level of population temporal stability was also quantified by determining the percentage of each field infested with P. penetrans at various population density categories (Table 4 and Fig. 2–5). The percentage of field in each category was calculated from the interpolated maps using SSToolbox. Five categories were selected to provide more insight into the overall population temporal stability. In the ART unfumigated field, the estimated area with P. penetrans counts between 0 and 10 nematodes 100 cm-3 increased 18-fold from Season 1 to Season 2, and the area exceeding 100 nematodes 100 cm-3 increased 8.5-fold between Seasons 2 and 3. In the ART fumigated field, greater than 74% of the field area was below 10 nematodes 100 cm-3 for Season 1 and 2; however, by the third season, only 3% of the area was below the same threshold level. In the CJ field, the percentage of field area exceeding 200 nematodes 100 cm-3 increased 20-fold over the entire 3-yr rotation. In the KIR unfumigated field, densities exceeding 100 nematodes 100 cm-3 doubled between Season 1 and 2. These results demonstrate that the P. penetrans populations increased and were more uniformly distributed at higher densities across each field landscape as time progressed.

Crop Yield Response
Total potato tuber yields and 60- to 170-g grade class were significantly higher in both fumigated fields vs. unfumigated fields (Table 6). Yields were higher for the 170- to 370-g grade class in ART fumigated than ART unfumigated field; however, the opposite results were found in the KIR field. For the largest size grade class (370–455 g), the unfumigated fields yielded higher although not significant in the ART field. Specific gravities were significantly higher in the KIR fumigated field but not the ART field.


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  		Table 6. Potato yields for unfumigated and fumigated fields.

 
Despite differences in total yield for fumigated vs. unfumigated fields, P. penetrans was only negatively correlated to potato yield in the ART fumigated and unfumigated fields (Table 7). Populations of P. penetrans were negatively correlated to 60- to 170-g tubers (-0.36) and 170- to 370-g tubers (-0.22) in the ART unfumigated field and 60- to 170-g tubers (-0.48) in the ART fumigated field. The low correlation coefficient between potato yield loss and P. penetrans populations indicates that nematode density was not the sole factor reducing potato yields on a landscape. This may be partially explained by the complex interactions between P. penetrans and V. dahliae as reported Saeed et al. (1998) where low to high P. penetrans populations in the presence of V. dahliae may provide similar potato yield loss. Corn yield was not correlated to the P. penetrans populations in either the ART fumigated, ART unfumigated, or CJ field. However, corn grain yields were negatively correlated (-0.15) to the third-season CJ field P. penetrans populations (data not shown). Dickerson et al. (1964) reported a decrease in vegetative corn growth caused by P. penetrans populations, but grain yields were not reported. Despite previous research reporting yield loss from P. penetrans alone and interacting with V. dahliae, the complexity of multiple interactions among pests and nutrients on field scale prevented a clear yield response to P. penetrans density or spatial distribution.


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  		Table 7. Spearman's correlation between P. penetrans counts and potato tuber yield.

 
Verticillium Wilt Symptoms
Visual ratings for Verticillium wilt symptoms were not reported for the KIR fumigated or unfumigated fields because a separate foliar fungicide research project was ongoing within this field. Spearman's correlation test was used to determine if a relationship existed between P. penetrans and Verticillium wilt symptoms. In the ART unfumigated and CJ unfumigated fields, Verticillium wilt ratings were correlated to P. penetrans counts for all rating dates (data not shown). Verticillium wilt ratings and P. penetrans counts in ART fumigated were not correlated for the 5 or 11 August rating dates but were correlated to the last rating date, 18 August. Wilt symptoms were not present in the SW fumigated field until 30 August and were not correlated with P. penetrans populations (data not shown). This lack of correlation in the SW field may be the result of misidentification of natural late-season crop senescence vs. Verticillium wilt symptoms and very low P. penetrans densities within this field.

Field Characteristics
Soil pH and volumetric water content were only measured during the third season and were compared to the third-season P. penetrans counts in the fumigated and unfumigated ART field and the CJ unfumigated field. No consistent correlations existed between the soil pH, soil mapping units, or weed populations and P. penetrans counts; however, the volumetric water content and P. penetrans counts were correlated (data not shown) (Morgan, 2001). Inconsistencies in the relationship between P. penetrans populations and soil characteristics (pH, soil texture, etc.) were similar to results reported by Florini et al. (1987) and Wallace (1991). The inability to correlate abiotic factors suggests that P. penetrans populations may be capable of inhabiting diverse soil and plant environments.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Temporal and spatial distribution of P. penetrans populations over an entire potato crop rotation sequence (3 yr) had not been previously quantified. Results from this research demonstrated the spatial distribution of P. penetrans was associated with farm machinery entry locations and suggest farm machinery may contribute to P. penetrans dispersal and reintroduction into fields. If farm machinery was responsible for P. penetrans interfield dispersal, removal of soil and plant debris from farm implements would reduce P. penetrans dispersal from infested fields to noninfested fields. Once P. penetrans was present within a field, mean populations generally increased each season and became dispersed over the majority of each field. Both potato and corn crops served as sufficient hosts for P. penetrans and contributed to mean population increases. However, potato and corn yield losses were not consistently correlated to P. penetrans densities.

Spatial aggregation was detected in unfumigated fields; however, the ability to detect aggregation in fumigated fields was limited by the grid sample size, and P. penetrans aggregation was not observable until two or three seasons following soil fumigation. The P. penetrans distributions were generally temporally stable between seasons. Spatial aggregation and temporal stability indicate that opportunities exist for site-specific management of P. penetrans in potato fields, especially near equipment entry locations into the field. Thus, potential for reducing pesticide use may be accomplished while maintaining economical crop production. However, more economical processing methods are needed to provide the information necessary to accurately estimate spatial distribution of P. penetrans.

One method with potential to increase the feasibility and accuracy of quantifying P. penetrans population distribution in agricultural fields is the use of co-kriging methods. The conceptual basis for co-kriging is to identify a parameter (x) strongly associated with P. penetrans population distribution and use parameter x to assist in accurately identifying the spatial distribution of the P. penetrans population. Assuming parameter x is more feasible to quantify, it can be intensively sampled, and fewer P. penetrans samples can be taken to create an accurate spatial distribution map. Adoption of site-specific management has the potential to increase the production efficacy and reduce soil fumigant inputs.

The use of geostatistics (variography) can be beneficial in developing scouting protocols for soil and pests, including P. penetrans in agricultural fields. For example, the semivariogram describes the distance at which observations are dependent or independent. Depending on the sampling goals, samples should be taken at distances exceeding the range to accurately determine population density. If the goal is to predict the P. penetrans density at unsampled locations in the field, the samples should be taken at a distance below the range. The dependent samples may then be used to create kriged maps for site-specific management, modify current management strategies, and provide further understanding of population dynamics (biology and/or ecology) of P. penetrans. Semivariograms and kriged interpolation maps can also quantify the direction of the P. penetrans population dispersion and population aggregate size fluctuations over time. However, the ability to detect the intricate details or population dispersion and aggregate size changes may require a more intensive grid-sampling method than that used in this research.


   ACKNOWLEDGMENTS
 
This research was funded by a USDA-CSREES Hatch Project from the Wisconsin Agricultural Experiment Station. The authors thank Steve, Andy, and Mike Diercks of Coloma Farms for their cooperation in this research and extend our appreciation to Aimee Reid-Rice for aiding in quantification and processing of the Pratylenchus penetrans samples.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 





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