Sampling Optimization and Crop Interface Effects on Lygus lineolaris Populations in Southeastern USA Cotton.

Seth J Dorman,Francis P F Reay-Jones,Ronald H Smith,Jeremy K Greene,Silvana Paula-Moraes,Phillip M Roberts,Sally V Taylor,Anders S Huseth,Alana L Jacobson,Sean Malone,Dominic D Reisig

doi:10.3390/insects13010088

Abstract

Simple SummaryTarnished plant bugs (Hemiptera: Miridae) are an important agricultural pest in cotton across the United States. Tarnished plant bugs reduce cotton yields and lower lint and seed quality by feeding on reproductive structures. Effective management of this pest requires timely insecticidal control when populations reach established economic thresholds. Reliable determination of the economic threshold in cotton depends on effective scouting. To evaluate the efficacy of current tarnished plant bug scouting strategies, we surveyed 120 commercial cotton fields across the southeastern USA to quantify (1) variation in tarnished plant bug populations across the production region, (2) evaluate current sampling plans for economic threshold determinations, and (3) examine landscape-scale risk factors associated with tarnished plant bug infestations in cotton. We observed the greatest variability in tarnished plant bug density at the field scale followed by within-field variation, emphasizing the importance of scouting individual fields. Additionally, we determined the sampling size needed for accurate threshold estimates for sweep net (8 sample units of 100 sweeps/sample) and drop cloth sampling (23 sampling units of 1.5 row-m/sample). Furthermore, tarnished plant bugs densities were positively related to the proportion of agriculture and double-crop winter wheat and soybeans and negatively related to contiguous cotton.Tarnished plant bug, Lygus lineolaris (Hemiptera: Miridae), is an economically damaging pest in cotton production systems across the southern United States. We systematically scouted 120 commercial cotton fields across five southeastern states during susceptible growth stages in 2019 and 2020 to investigate sampling optimization and the effect of interface crop and landscape composition on L. lineolaris abundance. Variance component analysis determined field and within-field spatial scales, compared with agricultural district and state, accounted for more variation in L. lineolaris density using sweep net and drop cloth sampling. This result highlights the importance of field-level scouting efforts. Using within-field samples, a fixed-precision sampling plan determined 8 and 23 sampling units were needed to determine L. lineolaris population estimates with 0.25 precision for sweep net (100 sweeps per unit) and drop cloth (1.5 row-m per unit) sampling, respectively. A spatial Bayesian hierarchical model was developed to determine local landscape (<0.5 km from field edges) effects on L. lineolaris in cotton. The proportion of agricultural area and double-crop wheat and soybeans were positively associated with L. lineolaris density, and fields with more contiguous cotton areas negatively predicted L. lineolaris populations. These results will improve L. lineolaris monitoring programs and treatment management decisions in southeastern USA cotton.

Highlights

The spatial heterogeneity of arthropod pest populations in crop fields is a factor that complicates accurate density estimation and the use of economic thresholds
We were surprised that state and district were not significant factors explaining variation in L. lineolaris populations, given the increases reported in North Carolina and Virginia [32], but not other states in the southeastern United States
Results of this study highlight the heterogeneity of L. lineolaris populations within and among cotton fields in the southeastern USA

Summary

Introduction

The spatial heterogeneity of arthropod pest populations in crop fields is a factor that complicates accurate density estimation and the use of economic thresholds. A wide range of biological and ecological processes influence variation in pest distribution, including dispersal ability, habitat selection, inter- and intra-species interactions, and aggregation behavior [1,2,3]. To address this challenge, estimating pest densities using systematic pest scouting has become a foundational decision support tool to anticipate economic damage in an integrated pest management (IPM) framework [4,5]. Frequency distribution models can be used to estimate the minimum sample size for accurate population estimates of arthropods [11]

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Discussion

Conclusion