A Case of One Step Forward and Two Steps Back? An Examination of Herbicide-Resistant Weed Management Using a Simple Agroecosystem Dynamics Model

Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically.

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Publication Details

Journal
Systems
Published
2024-12-22
DOI
https://doi.org/10.3390/systems12120587
Primary Topic
Weed Control and Herbicide Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A Case of One Step Forward and Two Steps Back? An Examination of Herbicide-Resistant Weed Management Using a Simple Agroecosystem Dynamics Model

Srinadh Kodali, Chris Flores‐Lopez, Branson Kim, Lane Michna et al.
Systems
Weed Control and Herbicide Applications
article

A Case of One Step Forward and Two Steps Back? An Examination of Herbicide-Resistant Weed Management Using a Simple Agroecosystem Dynamics Model

Srinadh Kodali, Chris Flores‐Lopez, Branson Kim, Lane Michna, Benjamin L. Turner, James R. Russell, Isabelle Lobdell
article en

Abstract

Global herbicide-resistant weed populations continue rising due to selection pressures exerted by herbicides. Despite this, herbicides continue to be farmers’ preferred weed-control method due to cost and efficiency relative to physical or biological methods. However, weeds developing resistance to herbicides not only challenges crop production but also threatens ecosystem services by disrupting biodiversity, reducing soil health, and impacting water quality. Our objective was to develop a simulation model that captures the feedback between weed population dynamics, agricultural management, profitability, and farmer decision-making processes that interact in unique ways to reinforce herbicide resistance in weeds. After calibration to observed data and evaluation by subject matter experts, we tested alternative agronomic, mechanical, or intensive management strategies to evaluate their impact on weed population dynamics. Results indicated that standalone practices enhanced farm profitability in the short term but lead to substantial adverse ecological outcomes in the long term, indicated by elevated herbicide resistance (e.g., harm to non-target species, disrupting natural ecosystem functions). The most management-intensive test yielded the greatest weed control and farm profit, albeit with elevated residual resistant seed bank levels. We discuss these findings in both developed and developing-nation contexts. Future work requires greater connectivity of farm management and genetic-resistance models that currently remain disconnected mechanistically.

SystemsVol. 12(12)
South Dakota State University (US), Texas A&M University – Kingsville (US), Old Dominion University (US), Texas A&M University – Corpus Christi (US)
National Science Foundation, U.S. Department of Agriculture, Core Research for Evolutional Science and Technology
Openalex Percentile: Top 86%
Weed Control and Herbicide Applications
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