Acrogenospora terricola sp. nov., a fungal species associated with seeds of pioneer trees in the soil seed bank of a lowland forest in Panama.

As currently circumscribed, Acrogenospora (Acrogenosporaceae, Minutisphaerales, Dothideomycetes) is a genus of saprobic hyphomycetes with distinctive conidia. Although considered common and cosmopolitan, the genus is poorly represented by sequence data, and no neotropical representatives are present in public sequence databases. Consequently, Acrogenospora has been largely invisible to ecological studies that rely on sequence-based identification. As part of an effort to identify fungi collected during ecological studies, we identified strains of Acrogenospora isolated in culture from seeds in the soil seed bank of a lowland tropical forest in Panama. Here we describe Acrogenospora terricola sp. nov. based on morphological and phylogenetic analyses. We confirm that the genus has a pantropical distribution. The observation of Acrogenospora infecting seeds in a terrestrial environment contrasts with previously described species in the genus, most of which occur on decaying wood in freshwater environments. This work highlights the often hidden taxonomic value of collections derived from ecological studies of fungal communities and the ways in which rich sequence databases can shed light on the identity, distributions and diversity of cryptic microfungi.

Metabolic Pathways for S-Metolachlor Detoxification Differ Between Tolerant Corn and Multiple-Resistant Waterhemp.

Herbicide resistance in weeds can be conferred by target-site and/or non-target-site mechanisms, such as rapid metabolic detoxification. Resistance to the very-long-chain fatty acid-inhibiting herbicide, S-metolachlor, in multiple herbicide-resistant populations (CHR and SIR) of waterhemp (Amaranthus tuberculatus) is conferred by rapid metabolism compared with sensitive populations. However, enzymatic pathways for S-metolachlor metabolism in waterhemp are unknown. Enzyme assays using S-metolachlor were developed to determine the specific activities of glutathione S-transferases (GSTs) and cytochrome P450 monooxygenases (P450s) from CHR and SIR seedlings to compare with tolerant corn and sensitive waterhemp (WUS). GST activities were greater (∼2-fold) in CHR and SIR compared to WUS but much less than corn. In contrast, P450s in microsomal extracts from CHR and SIR formed O-demethylated S-metolachlor, and their NADPH-dependent specific activities were greater (>20-fold) than corn or WUS. Metabolite profiles of S-metolachlor generated via untargeted and targeted liquid chromatography-mass spectrometry from CHR and SIR differed from WUS, with greater relative abundances of O-demethylated S-metolachlor and O-demethylated S-metolachlor-glutathione conjugates formed by CHR and SIR. In summary, our results demonstrate that S-metolachlor metabolism in resistant waterhemp involves Phase I and Phase II metabolic activities acting in concert, but the initial O-demethylation reaction confers resistance.

Soilborne fungi have host affinity and host-specific effects on seed germination and survival in a lowland tropical forest.

The Janzen-Connell (JC) hypothesis provides a conceptual framework for explaining the maintenance of tree diversity in tropical forests. Its central tenet-that recruits experience high mortality near conspecifics and at high densities-assumes a degree of host specialization in interactions between plants and natural enemies. Studies confirming JC effects have focused primarily on spatial distributions of seedlings and saplings, leaving major knowledge gaps regarding the fate of seeds in soil and the specificity of the soilborne fungi that are their most important antagonists. Here we use a common garden experiment in a lowland tropical forest in Panama to show that communities of seed-infecting fungi are structured predominantly by plant species, with only minor influences of factors such as local soil type, forest characteristics, or time in soil (1-12 months). Inoculation experiments confirmed that fungi affected seed viability and germination in a host-specific manner and that effects on seed viability preceded seedling emergence. Seeds are critical components of reproduction for tropical trees, and the factors influencing their persistence, survival, and germination shape the populations of seedlings and saplings on which current perspectives regarding forest dynamics are based. Together these findings bring seed dynamics to light in the context of the JC hypothesis, implicating them directly in the processes that have emerged as critical for diversity maintenance in species-rich tropical forests.

Dormancy-defense syndromes and tradeoffs between physical and chemical defenses in seeds of pioneer species.

Seeds of tropical pioneer trees have chemical and physical characteristics that determine their capacity to persist in the soil seed bank. These traits allow seeds to survive in the soil despite diverse predators and pathogens, and to germinate and recruit even decades after dispersal. Defenses in seedlings and adult plants often are described in terms of tradeoffs between chemical and physical defense, but the interplay of defensive strategies has been evaluated only rarely for seeds. Here we evaluated whether classes of seed defenses were negatively correlated across species (consistent with tradeoffs in defense strategies), or whether groups of traits formed associations across species (consistent with seed defense syndromes). Using 16 of the most common pioneer tree species in a neotropical lowland forest in Panama we investigated relationships among four physical traits (seed fracture resistance, seed coat thickness, seed permeability, and seed mass) and two chemical traits (number of phenolic compounds and phenolic peak area), and their association with seed persistence. In addition, seed toxicity was assessed with bioassays in which we evaluated the activity of seed extracts against representative fungal pathogens and a model invertebrate. We did not find univariate tradeoffs between chemical and physical defenses. Instead, we found that seed permeability - a trait that distinguishes physical dormancy from other dormancy types - was positively associated with chemical defense traits and negatively associated with physical defense traits. Using a linear discriminant analysis and a hierarchical cluster analysis we found evidence to distinguish three distinct seed defense syndromes that correspond directly with seed dormancy classes (i.e., quiescent, physical, and physiological). Our data suggest that short and long-term persistence of seeds can be achieved via two strategies: having permeable seeds that are well defended chemically, corresponding to the physiologically dormant defense syndrome; or having impermeable seeds that are well defended physically, corresponding to the physically dormant defense syndrome. In turn, transient seeds appear to have a lower degree of chemical and physical defenses, corresponding to the quiescent defense syndrome. Overall, we find that seed defense and seed dormancy are linked, suggesting that environmental pressures on seed persistence and for delayed germination can select for trait combinations defining distinct dormancy-defense syndromes.

Potential Nitrogen Losses in Relation to Spatially Distinct Soil Management History and Biochar Addition.

Soil functional zone management strategies including ridge tillage have been shown to increase in-row (IR) compared with between-row (BR) soil nitrogen (N) availability due to the development of contrasting soil properties and carbon (C) and N cycling processes. However, potential N losses may also increase for IR positions, representing an environmental tradeoff. Although biochar has putative contributions to tightening N cycles, its effect within spatially distinct management zones has not been quantified. This study evaluated the potential for biochar to reduce soil nitrous oxide (NO) emissions and leachate nitrate (NO) concentrations as influenced by changes in soil properties after 5 yr of ridge tillage in a silty clay loam soil. Soil columns for IR and BR positions were treated with and without biochar at 10 Mg ha in a 100-d laboratory incubation ( = 4 replications). Results indicate that biochar increased average daily NO emissions in IR by 30% but decreased them by 39% in BR. In both positions, biochar decreased NO concentrations in soil solution and leachate by 11 to 20% and 10 to 15%, respectively. Our findings suggest that long-term changes in soil C and N cycling processes may increase the potential for NO emissions in IR compared with BR positions. Although most biochar studies have not accounted for within-field soil variability, our results indicate that biochar may differentially affect soil NO emissions depending on spatially distinct soil management history. Findings from this laboratory study stress the need for field research evaluating spatial differences in biochar NO mitigation potential.

Increasing yield stability and input efficiencies with cost-effective mechanization in Nepal.

Nepal is at a crossroads of diminishing farm-labor and inadequate investment into farming operations that, among other factors, have stagnated domestic wheat yield. Cultural and economic constraints have hindered the widespread adoption of more expensive precision agriculture technologies like zero-till that have the capacity to improve labor and farm input efficiencies. To capture the benefits from added precision of application but with the ability to fit within the current semi-mechanized seed bed preparation and tillage system, we introduced a low-cost, chest mounted seed and fertilizer. We found that simple mechanization caused yield efficiencies to be positive and significant for nitrogen and phosphate. Seed rates using this method were positively associated with seedling density. This led to both yield and profit being more predictable for farmers. Conversely, hand-applied inputs caused a disassociation between inputs and end of season yield and therefore added a large measure of risk to their farming operations.

An affinity-effect relationship for microbial communities in plant-soil feedback loops.

Feedback loops involving soil microorganisms can regulate plant populations. Here, we hypothesize that microorganisms are most likely to play a role in plant-soil feedback loops when they possess an affinity for a particular plant and the capacity to consistently affect the growth of that plant for good or ill. We characterized microbial communities using whole-community DNA fingerprinting from multiple "home-and-away" experiments involving giant ragweed (Ambrosia trifida L.) and common sunflower (Helianthus annuus L.), and we looked for affinity-effect relationships in these microbial communities. Using canonical ordination and partial least squares regression, we developed indices expressing each microorganism's affinity for ragweed or sunflower and its putative effect on plant biomass, and we used linear regression to analyze the relationship between microbial affinity and effect. Significant linear affinity-effect relationships were found in 75 % of cases. Affinity-effect relationships were stronger for ragweed than for sunflower, and ragweed affinity-effect relationships showed consistent potential for negative feedback loops. The ragweed feedback relationships indicated the potential involvement of multiple microbial taxa, resulting in strong, consistent affinity-effect relationships in spite of large-scale microbial variability between trials. In contrast, sunflower plant-soil feedback may involve just a few key players, making it more sensitive to underlying microbial variation. We propose that affinity-effect relationship can be used to determine key microbial players in plant-soil feedback against a low "signal-to-noise" background of complex microbial datasets.

U.S. cereal rye winter cover crop growth database.

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001-2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha-1, a median of 2,458 kg ha-1, and a standard deviation of 3,163 kg ha-1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata.

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.

Evolutionary limits ameliorate the negative impact of an invasive plant.

Invasive species can quickly transform biological communities due to their high abundance and strong impacts on native species, in part because they can be released from the ecological forces that limit native populations. However, little is known about the long-term dynamics of invasions; do invaders maintain their dominant status over long time spans, or do new ecological and evolutionary forces eventually develop to limit their populations? Alliaria petiolata is a Eurasian species that aggressively invades North American forest understories, in part due to the production of toxic phytochemicals. Here we document a marked decline in its phytotoxin production and a consequent decline in their impact on three native species, across a 50+ year chronosequence of Alliaria petiolata invasion. Genetic evidence suggests that these patterns result from natural selection for decreased phytotoxin production rather than founder effects during introduction and spread. These patterns are consistent with the finding of slowing A. petiolata population growth and rebounding native species abundance across a separate chronosequence in Illinois, U.S. These results suggest that this invader is developing evolutionary limits in its introduced range and highlight the importance of understanding the long-term processes that shape species invasions and their impacts.

Perspective: Scientific rigor or ritual? Statistical significance in pest management science.

P values, binary hypothesis tests, and statistical significance are too often overused or used incorrectly in pest management reports. These statistical results are not the point of an analysis, they are just a by-product that can sometimes be informative. The point of the analysis is always a biological interpretation of the data focusing on whether something new has been learned and then quantifying what was learned in terms of biological effects or supported hypotheses. The term 'statistical significance' should be retired if only because of the common misunderstanding that it implies biological relevance; these terms are not equivalent. © 2021 Society of Chemical Industry.

Consequences of parameterization and structure of applied demographic models: a comment on Pardini et al. (2009).

Correcting the problems in the model of A. petiolata presented in Pardini et al. (2009) changes its dynamics and thus the management recommendations. As with any model, our revised model's-management predictions are conditional on model parameterization. Thus, managers should carefully consider at what spatial scales it is appropriate to infer management recommendations given the data used to build the model (e.g., is a management plan developed from a population in Missouri equally relevant to populations in Georgia, Maine, and Oregon?). In agreement with PDCK's conclusions, we found their A. petiolata study population to exhibit complex dynamics (two-point cycling) at lower efficacies of either rosette or adult management, and stable equilibria at higher management efficacies. This could have important implications for A. petiolata management techniques such as biological control if the biocontrol agents' population dynamics are dependent on A. petiolata density. While the predictions generated in our reanalysis represent an improvement over the original model, they should be tempered by the limited scope of the data used to parameterize the model. Running the model through previously published parameter ranges results in qualitatively different dynamics than those predicted in PDCK. Because of the tremendous spatiotemporal variability in A. petiolata demographic rates and the species' large geographical range, more general management recommendations will only arise from a larger set of demographic data that has greater coverage in space and time. Our revision of the model of Pardini et al. (2009) should therefore be considered as a subset of many possible models of A. petiolata population dynamics.

Future efficacy of pre-emergence herbicides in corn (Zea mays) is threatened by more variable weather.

BACKGROUND: By 2050, weather is expected to become more variable with a shift towards higher temperatures and more erratic rainfall throughout the U.S. Corn Belt. The effects of this predicted weather change on pre-emergence (PRE) herbicide efficacy have been inadequately explored. Using an extensive database, spanning 252 unique weather environments, the efficacy of atrazine, acetochlor, S-metolachlor, and mesotrione, applied PRE alone and in combinations, was modeled on common weed species in corn (Zea mays L.). RESULTS: Adequate rainfall to dissolve the herbicide into soil water solution so that it could be absorbed by developing weed seedlings within the first 15 days after PRE application was essential for effective weed control. Across three annual weed species, the probability of effective control increased as rainfall increased and was maximized when rainfall was 10 cm or more. When rainfall was less than 10 cm, increasing soil temperatures had either a positive or negative effect on the probability of effective control, depending on the herbicide(s) and weed species. Herbicide combinations required less rainfall to maximize the probability of effective control and had higher odds of successfully controlling weeds compared with the herbicides applied individually. CONCLUSIONS: Results of this study highlight the importance of rainfall following PRE herbicide application. As rainfall becomes more variable in future, the efficacy of common PRE herbicides will likely decline. However, utilizing combinations of PRE herbicides along with additional cultural, mechanical, biological, and chemical weed control methods will create a more sustainable integrated weed management system and help U.S. corn production adapt to more extreme weather. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Metabolic resistance to S-metolachlor in two waterhemp (Amaranthus tuberculatus) populations from Illinois, USA.

BACKGROUND: Two waterhemp (Amaranthus tuberculatus) populations from Illinois demonstrating multiple-resistance to acetolactate synthase (ALS)-, 4-hydroxyphenylpyruvate dioxygenase, and photosystem II (PSII)-inhibiting herbicides (designated CHR and SIR) also displayed reduced sensitivity to very-long-chain fatty acid-inhibiting herbicides, including S-metolachlor. We hypothesized that a physiological mechanism, such as enhanced metabolism, could be responsible for the reduced efficacy of S-metolachlor. RESULTS: Metabolism experiments indicated that resistant populations degraded S-metolachlor more rapidly than sensitive populations and equally as rapidly as corn 2-24 h after treatment (HAT). Resistant waterhemp and corn metabolized 90% (DT90 ) of absorbed S-metolachlor in less than 3.2 h whereas DT90 values for sensitive waterhemp exceeded 6 h. The glutathione S-transferase inhibitor 4-chloro-7-nitrobenzofurazon and cytochrome P450-inhibitor malathion decreased the amount of S-metolachlor metabolized in resistant waterhemp at 4 HAT but not in sensitive waterhemp or corn, and altered the abundance of certain metabolites in resistant waterhemp. CONCLUSION: Results from this research demonstrate that resistance to S-metolachlor in these waterhemp populations is due to enhanced herbicide metabolism relative to sensitive populations. In addition, our results indicate that resistant waterhemp might utilize metabolic pathway(s) more intricate than either sensitive waterhemp or corn based on their metabolite profiles. © 2020 Society of Chemical Industry.

An ecological perspective on managing weeds during the great selection for herbicide resistance.

More than 70 years after modern agriculture declared a 'war on weeds', they continue to thrive and suppress crop yields. Viewing weeds as an enemy that can be defeated if only a powerful enough technology can be deployed is a losing proposition. The latest evidence for the inadequacy of this approach, rampant evolution of multiple herbicide-resistant weed genotypes and dwindling options for chemical control in many production systems, should be seen as an urgent message to all those concerned with the science and practice of weed management: we need another way of thinking about the weed resistance issue. Fortunately, the theoretical and practical foundation of this alternative approach, ecological weed management, has been in development for decades. Here, we use Barry Commoner's laws of ecology as a conceptual frame for a review of some of the fundamental concepts of ecological weed management. © 2018 Society of Chemical Industry.

Limited fitness costs of herbicide-resistance traits in Amaranthus tuberculatus facilitate resistance evolution.

BACKGROUND: The fitness cost of herbicide resistance (HR) in the absence of herbicide selection plays a key role in HR evolution. Quantifying the fitness cost of resistance, however, is challenging, and there exists a knowledge gap in this area. A synthetic (artificially generated) Amaranthus tuberculatus population segregating for five types of HR was subjected to competitive growth conditions in the absence of herbicide selection for six generations. Fitness costs were quantified by using a combination of phenotyping and genotyping to monitor HR frequency changes over generations. RESULTS: In the absence of herbicide selection, a significant fitness cost was observed for resistance to acetolactate synthase-inhibiting herbicides, but not for resistances to atrazine (non-target-site resistance mechanism), protoporphyrinogen oxidase inhibitors, 4-hydroxyphenylpryuvate dioxygenase inhibitors or glyphosate. Glyphosate resistance was conferred by multiple mechanisms in the synthetic population, and further analysis revealed that one mechanism, amplification of the 5-enolypyruvylshikimate-3-phosphate synthase gene, did decrease in frequency. CONCLUSION: Our results indicate that herbicide-resistance mitigation strategies (e.g. herbicide rotation) that rely on the existence of fitness costs in the absence of herbicide selection likely will be largely ineffective in many cases. © 2017 Society of Chemical Industry.

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits.

Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized.

Confronting herbicide resistance with cooperative management.

BACKGROUND: Resistance of pathogens and pests to antibiotics and pesticides worldwide is rapidly reaching critical levels. The common-pool-resource nature of this problem (i.e. whereby the susceptibility to treatment of target organisms is a shared resource) has been largely overlooked. Using herbicide-resistant weeds as a model system, we developed a discrete-time landscape-scale simulation to investigate how aggregating herbicide management strategies at different spatial scales from individual farms to larger cooperative structures affects the evolution of glyphosate resistance in common waterhemp (Amaranthus tuberculatus). RESULTS: Our findings indicate that high-efficacy herbicide management strategies practiced at the farm scale are insufficient to slow resistance evolution in A. tuberculatus. When best practices were aggregated at large spatial scales, resistance evolution was hindered; conversely, when poor management practices were aggregated, resistance was exacerbated. Tank mixture-based strategies were more effective than rotation-based strategies in most circumstances, while applying glyphosate alone resulted in the poorest outcomes. CONCLUSIONS: Our findings highlight the importance of landscape-scale cooperative management for confronting common-pool-resource resistance problems in weeds and other analogous systems. © 2018 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A regionally-adapted implementation of conservation agriculture delivers rapid improvements to soil properties associated with crop yield stability.

Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.

Opportunities and challenges for harvest weed seed control in global cropping systems.

The opportunity to target weed seeds during grain harvest was established many decades ago following the introduction of mechanical harvesting and the recognition of high weed-seed retention levels at crop maturity; however, this opportunity remained largely neglected until more recently. The introduction and adoption of harvest weed seed control (HWSC) systems in Australia has been in response to widespread occurrence of herbicide-resistant weed populations. With diminishing herbicide resources and the need to maintain highly productive reduced tillage and stubble-retention practices, growers began to develop systems that targeted weed seeds during crop harvest. Research and development efforts over the past two decades have established the efficacy of HWSC systems in Australian cropping systems, where widespread adoption is now occurring. With similarly dramatic herbicide resistance issues now present across many of the world's cropping regions, it is timely for HWSC systems to be considered for inclusion in weed-management programs in these areas. This review describes HWSC systems and establishing the potential for this approach to weed control in several cropping regions. As observed in Australia, the inclusion of HWSC systems can reduce weed populations substantially reducing the potential for weed adaptation and resistance evolution. © 2017 Society of Chemical Industry.