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Neutral weed communities: the intersection between crop productivity, biodiversity, and weed ecosystem services

Published online by Cambridge University Press:  11 May 2023

Marco Esposito*
Affiliation:
Graduate Student, Department of Agricultural Sciences, University of Naples Federico II, Portici, NA, Italy Graduate Student, Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
Anna S. Westbrook
Affiliation:
Graduate Student, Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
Albino Maggio
Affiliation:
Professor, Department of Agricultural Sciences, University of Naples Federico II, Portici, NA, Italy
Valerio Cirillo
Affiliation:
Research Scientist, Department of Agricultural Sciences, University of Naples Federico II, Portici, NA, Italy
Antonio DiTommaso*
Affiliation:
Professor, Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
*
Corresponding authors: Marco Esposito; Department of Agricultural Sciences, University of Naples Federico II, Portici (NA), Italy 80055; Email: [email protected]; and Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853; Email: [email protected], Antonio DiTommaso; Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853; Email: [email protected]
Corresponding authors: Marco Esposito; Department of Agricultural Sciences, University of Naples Federico II, Portici (NA), Italy 80055; Email: [email protected]; and Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853; Email: [email protected], Antonio DiTommaso; Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853; Email: [email protected]
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Abstract

Weeds are a fundamental component of agroecosystems and, if not appropriately managed, can cause severe crop yield losses. New perspectives on weed management are required, because current approaches, such as herbicide application or soil tillage, have significant environmental and agronomic drawbacks. We propose the concept of “neutral weed communities,” which are weed communities that coexist with crops and do not negatively affect crop yield and quality compared with weed-free conditions. Management practices that promote neutral weed communities can enable reduced use of herbicides and soil tillage while enhancing ecosystem services and biodiversity. We report scientific evidence of neutral weed communities and survey ecological explanations for why different weed communities have different effects on crop production. We also propose two weed management approaches for attaining neutral weed communities. The first approach aims to maximize weed biodiversity using traditional approaches such as cropping system diversification and integrated weed management. Higher weed biodiversity is associated with lower dominance of competitive weed species that reduce crop yield. The second approach relies on modern tools such as robots and biotechnology to manipulate the density of specific weed species. This approach can remove highly problematic species and minimize niche overlap between the weeds and crops. Given the complexity of interactions among crops, weeds, and other components of the agroecosystem, we highlight the need for multidisciplinary research to illuminate mechanisms that determine the neutrality of weed communities.

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Weed Science Society of America

Introduction

Weeds are a fundamental component of agricultural systems and may interact with crops and other organisms in several ways. Weeds can negatively impact crop production by competing with crops. When weeds are not appropriately managed, they can reduce yields of major crops by a global average of 34% (Oerke Reference Oerke2006). World food demand is rising, driven by population growth and other factors (van Dijk et al. Reference Dijk, Morley, Rau and Saghai2021). Thus, farming activities such as managing agricultural weeds play an increasingly key role in assuring food security. Given the nearly 5 billion ha of cropland and pastures worldwide (FAOSTAT 2020), it is equally important to minimize the negative environmental impacts of agricultural production. Unfortunately, current weed control strategies may be largely unsustainable. Intensive tillage and herbicide use are associated with environmental risks and herbicide resistance. Environmental risks associated with intensive tillage include soil erosion (Seitz et al. Reference Seitz, Goebes, Puerta, Pereira, Wittwer, Six, van der Heijden and Scholten2018), decreases in soil quality (Karlen et al. Reference Karlen, Cambardella, Kovar and Colvin2013), soil organic matter losses (Haddaway et al. Reference Haddaway, Hedlund, Jackson, Kätterer, Lugato, Thomsen, Jørgensen and Isberg2017), nutrient depletion (Gadermaier et al. Reference Gadermaier, Berner, Fließbach, Friedel and Mäder2012), and soil compaction (Orzech et al. Reference Orzech, Wanic and Załuski2021). Longer-term, tillage-based systems can lead to a high carbon footprint (Dachraoui and Sombrero Reference Dachraoui and Sombrero2020) and yield reductions (Kok et al. Reference Kok, Papendick and Saxton2009). Currently, 267 weed species (154 dicots and 113 monocots) have shown resistance to herbicides (Heap Reference Heap2023), and this number is growing.

Even if optimal long-term weed control could be achieved without negative externalities, it might not be desirable to remove all weeds from agricultural fields (Maxwell Reference Maxwell and Zimdahl2018). From a conservation perspective, weeds are an important component of agroecosystem biodiversity. The oversimplification of agricultural systems, associated with intensive herbicide use, has reduced the abundance and diversity of weed species (Storkey and Westbury Reference Storkey and Westbury2007 and references therein). In addition to reducing plant diversity, removing too many weeds from agricultural fields can contribute to declines in species at higher trophic levels (Bretagnolle and Gaba Reference Bretagnolle and Gaba2015; Marshall et al. Reference Marshall, Brown, Boatman, Lutman, Squire and Ward2003; Smith et al. Reference Smith, Aebischer, Ewald, Moreby, Potter and Holland2020). Fields with low biodiversity also tend to be dominated by a few highly competitive weed species that may be very difficult to control (Storkey and Neve Reference Storkey and Neve2018).

Against this background, it is necessary to identify new weed management strategies to reduce herbicide application and soil tillage while maintaining crop yield, ecosystem service provisioning, and biodiversity. These strategies should reflect knowledge about the ecological interactions between weeds and crops, which vary depending on morpho-functional traits of the weeds and crops. In this paper, we introduce the concept of “neutral weed communities.” These are communities that coexist with the crops and do not significantly reduce crop yield or quality compared with weed-free conditions. Although the term “neutral weed communities” is new, there already exists substantial evidence that not all weed communities are deleterious to crop production (Adeux et al. Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019; Brooker et al. Reference Brooker, Karley, Mitchell, Newton and Pakeman2020; Gibson et al. Reference Gibson, Young and Wood2017; Rowntree et al. Reference Rowntree, Dean, Morrison, Brooker and Price2021).

If a weed community does not cause major crop yield or quality losses, weed management actions can be reduced and some weeds conserved for ecosystem service provisioning and maintenance of biodiversity (MacLaren et al. Reference MacLaren, Bennett and Dehnen-Schmutz2019). Promoting neutral weed communities is therefore an effective method of enhancing the sustainability and long-term productivity of agricultural systems. We propose two approaches to attaining neutral weed communities. The first approach focuses on increasing weed biodiversity, whereas the second relies on selecting specific weed species for conservation or elimination. Both strategies will help shift weed community composition from undesirable to desirable weed species, which is a major aim of ecological weed management (Liebman et al. Reference Liebman, Mohler and Staver2001).

The goals of this review are:

  1. 1. to describe advantages associated with the promotion of neutral weed communities (“Benefits of Promoting Neutral Weed Communities”);

  2. 2. to provide an overview of neutral weed communities in different agricultural contexts (“Evidence of Neutral Weed Communities”);

  3. 3. to survey ecological explanations for why some weed communities are neutral with respect to crops (“Understanding the Ecology and Biology of Neutral Weed Communities”); and

  4. 4. to identify current and emerging weed management strategies to attain neutral weed communities (“How to Attain Neutral Weed Communities”)

Benefits of Promoting Neutral Weed Communities

Promoting neutral weed communities would enable farmers to reduce the frequency and intensity of weed control operations. Consequently, the economic costs and environmental drawbacks associated with weed control operations would also be reduced. In addition, weeds may have positive effects on crops or the surrounding environment. For example, weeds provide resources for beneficial arthropods (Bàrberi et al. Reference Bàrberi, Burgio, Dinelli, Moonen, Otto, Vazzana and Zanin2010; Marshall et al. Reference Marshall, Brown, Boatman, Lutman, Squire and Ward2003; Null et al. Reference Null, Hawes, Haughton, Osborne, Roy, Clark, Perry, Rothery, Bohan, Brooks, Champion, Dewar, Heard, Woiwod and Daniels2003) and birds (Gibbons et al. Reference Gibbons, Bohan, Rothery, Stuart, Haughton, Scott, Wilson, Perry, Clark, Dawson and Firbank2006; Vickery et al. Reference Vickery, Carter and Fuller2002). By providing these resources, weeds contribute to regulating ecosystem services such as crop pollination (Garibaldi et al. Reference Garibaldi, Carvalheiro, Leonhardt, Aizen, Blaauw, Isaacs, Kuhlmann, Kleijn, Klein, Kremen, Morandin, Scheper and Winfree2014; Nicholls and Altieri Reference Nicholls and Altieri2013). In addition, weed species can reduce soil erosion (Seitz et al. Reference Seitz, Goebes, Puerta, Pereira, Wittwer, Six, van der Heijden and Scholten2018) and improve soil physical properties (Arai et al. Reference Arai, Minamiya, Tsuzura, Watanabe, Yagioka and Kaneko2014). Some weeds improve soil nutrient content, such as nitrogen (Promsakha Na Sakonnakhon et al. Reference Promsakha Na Sakonnakhon, Cadisch, Toomsan, Vityakon, Limpinuntana, Jogloy and Patanothai2006), phosphorus (Ojeniyi et al. Reference Ojeniyi, Odedina and Agbede2012), potassium (Ojeniyi et al. Reference Ojeniyi, Odedina and Agbede2012), and carbon content (de Rouw et al. Reference Rouw, Soulileuth and Huon2015). Mechanisms by which weeds might increase crop yield are further discussed in the section “Facilitative Weed–Crop Interactions.”

In addition to influencing yield, weeds often affect crop quality. It is possible that some weed mixtures could improve crop profitability by increasing crop quality (Gibson et al. Reference Gibson, Young and Wood2017). In a 2-yr field experiment, Millar et al. (Reference Millar, Gibson, Young and Wood2007) studied the impact of three levels of interspecific competition on seed development and quality of soybean [Glycine max (L.) Merr.]. The seed protein content was highest under the most intense weed competition in both years, while seed yield was not affected by interspecific competition in the first year. However, greater weed competition reduced seed yield in the second year, which was much drier than the first year. Water scarcity might have made weed interference more intense, considering the water-stress resistance of dominant weed species, including cocklebur (Xanthium strumarium L.), ivyleaf morningglory (Ipomoea hederacea Jacq.), fall panicum (Panicum dichotomiflorum Michx), and common ragweed (Ambrosia artemisiifolia L.).

Some authors have suggested capitalizing on the stress resistance and plasticity of weeds to realize more sustainable and diversified cropping systems. In India, Gholamhoseini et al. (Reference Gholamhoseini, AghaAlikhani, Mirlatifi and Sanavy2013) grew corn (Zea mays L.) in monoculture or mixture with an agricultural weed, redroot pigweed (Amaranthus retroflexus L.), at different nitrogen and water levels over 2 yr. They reported that the mixture used water and nitrogen inputs more efficiently and achieved higher forage yield and quality relative to the corn monoculture. This work aligns with other studies that consider the potential of arable weeds as intercrops or living mulches (Germeier Reference Germeier2000; Rowntree et al. Reference Rowntree, Dean, Morrison, Brooker and Price2021). Although the remainder of our review focuses on shaping resident weed communities rather than planting additional non-crop species, both lines of inquiry are valuable.

Evidence of Neutral Weed Communities

Not All Weed Communities Reduce Crop Yield

Weed communities can both cause severe crop yield losses (Oerke Reference Oerke2006) and provide benefits to crops and the broader environment (Blaix et al. Reference Blaix, Moonen, Dostatny, Izquierdo, Le Corff, Morrison, Von Redwitz, Schumacher and Westerman2018; Gaba et al. Reference Gaba, Cheviron, Perrot, Piutti, Gautier and Bretagnolle2020; Kleiman et al. Reference Kleiman, Koptur and Jayachandran2021; Smith et al. Reference Smith, Aebischer, Ewald, Moreby, Potter and Holland2020). A growing body of research suggests that the competitive effects of weeds on crops depends on a multitude of factors, including the functional composition of weed communities, crop traits, and environmental conditions (Bàrberi et al. Reference Bàrberi, Bocci, Carlesi, Armengot, Blanco-Moreno and Sans2018; Cirillo et al. Reference Cirillo, Masin, Maggio and Zanin2018; Gaba et al. Reference Gaba, Perronne, Fried, Gardarin, Bretagnolle, Biju-Duval, Colbach, Cordeau, Fernández-Aparicio, Gauvrit, Gibot-Leclerc, Guillemin, Moreau, Munier-Jolain, Strbik and Reboud2017; Gunton et al. Reference Gunton, Petit and Gaba2011). Under some circumstances, weed communities may provide ecosystem services without affecting crop yield and quality. In this review, we define such weed communities as neutral weed communities. In France, Adeux et al. (Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019) identified six weed communities over 3 yr of observations that included weed biomass, weed density, and winter cereal crop biomass. Two of the six communities identified did not significantly reduce grain yield compared with weed-free treatments. These two communities did not consistently have lower weed density or biomass than the communities that did reduce grain yield. The two neutral weed communities were mostly composed of Persian speedwell (Veronica persica Poir.), common chickweed [Stellaria media (L.) Vill], cutleaf geranium (Geranium dissectum L.), ivyleaf speedwell (Veronica hederifolia L.), and catchweed bedstraw (Galium aparine L.).

In Italy, Esposito et al. (Reference Esposito, Cirillo, Cozzolino, De Vita and Maggioin press) obtained similar results, identifying neutral weed communities in a field experiment with winter wheat (Triticum aestivum L.) under three different soil nutrient levels (low, optimal, and surplus). Under surplus nutrition, one detrimental community was identified. This finding suggests that high soil fertility may promote the growth of dominant weed species that capitalize on high rates of fertilization to compete aggressively with crops (Little et al. Reference Little, DiTommaso, Westbrook, Ketterings and Mohler2021). Under both low and optimal nutrient levels, one neutral weed community and one detrimental community were identified. The neutral communities did not negatively affect grain yield or quality. Corn chamomile (Anthemis arvensis L.) was the most abundant weed in neutral communities, accounting for 28% and 46% of total weed density in optimal and low nutrient treatments, respectively. The relative density of this species was higher in neutral communities than in detrimental communities. Under optimal nutrition, S. media was present only in the neutral community, while V. persica was mostly present in the neutral weed community. The annual legume California burclover (Medicago polymorpha L.) apparently contributed to the detrimental communities by accumulating a large amount of aboveground biomass and causing wheat lodging. Medicago polymorpha, which is native to the Mediterranean region and adapted to semiarid conditions (Yousfi et al. Reference Yousfi, Saïdi, Slama and Abdelly2015), may also compete with crops for water. Under optimal and low nutrition, M. polymorpha was mostly present in the detrimental communities compared with the neutral communities. Finally, Esposito et al. (Reference Esposito, Cirillo, Cozzolino, De Vita and Maggioin press) noted that the density of the neutral community was higher than the density of the detrimental weed community under optimal nutrition, suggesting that density is not always a good predictor of a weed community’s deleterious effect on crop yield.

Boström et al. (Reference Boström, Milberg and Fogelfors2003) studied the relationship between weed community composition and yield losses in spring wheat and barley (Hordeum vulgare L.; syn.: Hordeum distichum L.) in 33 field trials over 3 yr. Weeds such as scarlet pimpernel (Anagallis arvensis L.), nightflowering catchfly (Silene noctiflora L.), Euphorbia spp., field violet (Viola arvensis Murray), common lambsquarters (Chenopodium album L.), and Polygonum spp. were not associated with yield losses. In contrast, wild radish (Raphanus raphanistrum L.) and hempnettle (Galeopsis spp.) were among the most detrimental species, causing large crop yield losses.

In a 26-yr experiment in Sweden, Milberg and Hallgren (Reference Milberg and Hallgren2004) ranked weed species from the most benign to the most detrimental. Using 1,691 samples from on-farm trials, they identified benign weeds as those consistently occurring in situations with small cereal yield losses and detrimental weeds as those associated with larger yield losses. In autumn-sown cereals, benign weed species included wild buckwheat [Polygonum convolvulus L. var. convolvulus; syn.: Fallopia convolvulus (L.) Á. Löve], prostrate knotweed (Polygonum aviculare L.), false cleavers (Galium spurium L.), field forget-me-not [Myosotis arvensis (L.) Hill], S. media, and Veronica spp. Benign weed species in spring-sown cereals were P. convolvulus, Lamium spp., and wallflower mustard (Erysimum cheiranthoides L.). Detrimental weed species were scentless mayweed [Tripleurospermum inodorum (L.) Sch. Bip.] and shepherd’s purse [Capsella bursa-pastoris (L.) Medik.] in autumn-sown cereals and Galeopsis spp. and curlytop knotweed [Polygonum lapathifolium L.; syn. Persicaria lapathifolium (L.) Gray] in spring-sown cereal systems.

Similarly, in winter wheat, Jones and Smith (Reference Jones and Smith2007) grouped weeds as very desirable, desirable, and undesirable based on agronomic issues and biodiversity benefits. Out of the 18 very desirable or desirable weeds identified in this study, 6 species were also defined as benign by Milberg and Hallgren (Reference Milberg and Hallgren2004). Analogously, S. media was classified as very desirable by Jones and Smith (Reference Jones and Smith2007). This species was representative of neutral weed communities in winter wheat according to Esposito et al. (Reference Esposito, Cirillo, Cozzolino, De Vita and Maggioin press). These points of agreement between different studies suggest that certain weed species are relatively benign in several cereal-cropping systems, although any species can be harmful given the right conditions.

Much research on the relative competitiveness of different weed species and communities has been carried out in Europe. However, evidence from other world regions also exists. In an arid region of India, Bhandari and Sen (Reference Bhandari and Sen1979) showed that sowing an annual leguminous weed, Indigofera cordifolia B. Heyne ex Roth, improved growth parameters and yield in millet [Pennisetum glaucum (L.) R. Br.] and sesame (Sesamum indicum L.). Millet yield was 19.8% higher and sesame yield was 22.4% higher in plots sown with I. cordifolia, compared with weeded plots. In the same area, weeds like Arabian-primrose [Arnebia hispidissima (Lehm.) A. DC.], Spermacoce articularis L.f., and feather cockscomb (Celosia argentea L.) increased the growth parameters and yield of millet but not sesame (Sen [1978] as cited by Bhandari and Sen [Reference Bhandari and Sen1979]).

This survey reveals that much research on weed community competitiveness has focused on annual cropping systems. One reason is that annual crops account for much more harvested cropland area than perennial crops (FAOSTAT 2020). However, evidence for neutral weed communities has also emerged from perennial cropping systems. Liang and Huang (Reference Liang and Huang1994) highlighted the need to distinguish beneficial from detrimental weeds in citrus orchards. They noted that some weeds do not compete substantially with the citrus trees, instead providing economic and ecological benefits. Beneficial weeds, such as tropical ageratum (Ageratum conyzoides L.), sessile joyweed [Alternanthera sessilis (L.) R. Br. ex DC.], and many dicotyledonous weeds, often had soft tissues, shallow roots, and broad leaves. In contrast, detrimental weeds, such as goosegrass [Eleusine indica (L.) Gaertn.], cogongrass [Imperata cylindrica (L.) P. Beauv.], bermudagrass [Cynodon dactylon (L.) Pers.], large crabgrass [Digitaria sanguinalis (L.) Scop.], and many monocotyledonous weeds, had opposite characteristics. Liang and Huang (Reference Liang and Huang1994) considered A. conyzoides one of the most beneficial weeds, because it can support natural enemies of citrus pests and is suitable as a green manure. Other weeds reported to be beneficial in citrus orchards include C. argentea, alligatorweed [Alternanthera philoxeroides (Mart.) Griseb.], Chinese giant-hyssop [Agastache rugosa (Fisch. & C.A. Mey.) Kuntze], beefsteakplant [Perilla frutescens (L.) Britton], and Exallage auricularia (L.) Bremek. (Liang and Huang Reference Liang and Huang1994 and references therein).

Neutral weed communities have also been identified in other orchard types. In a 3-yr experiment in organic and conventional apple (Malus domestica Borkh.) orchards in China, Meng et al. (Reference Meng, Li, Liu, Li, Li, Wu, Yu, Guo, Cheng, Muminov, Liang and Jiang2016) demonstrated the possibility of managing pernicious weeds in the organic orchard by propagating Indian mock strawberry [Duchesnea indica (Andrews) Teschem.; syn. Potentilla indica (Andrews) Th. Wolf]. This native species was able to suppress undesirable weeds through competition, enabling good weed suppression without the use of herbicides. Despite the fast growth of P. indica and its increasing dominance in the understory ground cover of the organic orchard, apple yield was not different between the organic and conventional orchards in the last 2 yr of the study. In a comparison between organic and conventional olive (Olea europaea L.) groves in Greece, organic and conventional groves did not differ in edible olive yield or olive oil yield (Solomou and Sfougaris Reference Solomou and Sfougaris2011). Wild carrot (Daucus carota L.) and ovate goatgrass (Aegilops geniculata Roth) were the most frequently occurring herbaceous plants in 10-yr and 6-yr certified organic groves, respectively.

Caveats

Data on which weeds are most detrimental or beneficial can be used to focus weed management efforts on maximizing crop productivity and ecosystem services, rather than removing all weeds. Such data should be collected in diverse climates and cropping systems, as the identities of “detrimental” and “beneficial” weed species will vary from place to place. Several species characterized as benign by the studies discussed in this section are highly problematic in other contexts. Notably, different crops may display different degrees of competitiveness against weeds (Andrew et al. Reference Andrew, Storkey and Sparkes2015; Corre-Hellou et al. Reference Corre-Hellou, Dibet, Hauggaard-Nielsen, Crozat, Gooding, Ambus and Jensen2011; Lemerle et al. Reference Lemerle, Luckett, Lockley, Koetz and Wu2014). Consequently, neutral weed communities are more likely to occur in more competitive crops, such as wheat, barley, and corn. In addition, it is important to note that the effect of a particular weed species depends not only on climate and cropping system but also on the presence of other weed species. Species-level data cannot always substitute for community-level analysis.

Researchers and stakeholders should also adopt a multiyear perspective when considering neutral weed communities and how they should be managed. It is not advisable to modify weed management without considering how this decision will change plant community composition over time. Even if a weed community is unlikely to cause yield loss in the current year, eliminating weed control operations might allow high levels of weed seed production, increasing the soil seedbank and potentially contributing to yield loss in future years. This consideration becomes especially important when a farmer makes weed control decisions in a competitive crop, but then grows a less competitive crop in a later phase of the rotation cycle. We advocate holistic analysis of the long-term costs and benefits of weeds and management tactics.

Understanding the Ecology and Biology of Neutral Weed Communities

Coexistence between Weeds and Crops

To understand why weed communities are not always detrimental, it is useful to draw on broader theories of plant–plant coexistence. A foundational idea in ecology is the concept of competitive exclusion, that is, the idea that two or more species that occupy the same niche cannot coexist (Gause Reference Gause1934). According to this paradigm, stable coexistence of multiple species is best explained by differences in their functional traits (i.e., differences in how they respond to and affect their biotic and abiotic environments). For example, species might require different resources at different times. Even among plants, all of which require similar resources, there is substantial potential for resource partitioning to promote coexistence (Silvertown Reference Silvertown2004). Resource partitioning is one of several proposed stabilizing mechanisms of coexistence, defined as mechanisms that increase the magnitude of negative intraspecific interactions relative to negative interspecific interactions (Chesson Reference Chesson2000). In general, intraspecific interactions do tend to be more negative than interspecific interactions in plant communities, consistent with stabilizing mechanisms of coexistence (Adler et al. Reference Adler, Smull, Beard, Choi, Furniss, Kulmatiski, Meiners, Tredennick and Veblen2018). In the presence of stabilizing mechanisms of coexistence, equalizing mechanisms (i.e., mechanisms that reduce fitness differences between species) may further promote stable coexistence (Chesson Reference Chesson2000). Alternatively, equalizing mechanisms could help support models of unstable coexistence. Notably, Hubbell (Reference Hubbell2001) proposed a neutral theory in which drift, migration, and speciation are more important than stabilizing mechanisms and fitness differences. Niche-based and neutral theories are not mutually exclusive: stabilizing mechanisms and fitness differences between species do exist, but their magnitudes and effects on community assembly can vary (Adler et al. Reference Adler, HilleRisLambers and Levine2007). The uncovering of mechanisms promoting coexistence is ongoing and crucial research, especially given that such mechanisms may maintain ecosystem function as well as biodiversity (Godoy et al. Reference Godoy, Gómez-Aparicio, Matías, Pérez-Ramos and Allan2020; Turnbull et al. Reference Turnbull, Levine, Loreau and Hector2013).

In applying ecological perspectives to agricultural situations, one should remember that (1) most cropping systems are frequently disturbed and therefore best characterized as early successional habitats, and (2) the effects of weeds on crops are more frequently measured than the effects of crops on weeds. For both reasons, a report of weeds that do not appear to impact crop yield does not constitute a report of stable coexistence. Nevertheless, arguments developed to explain coexistence in natural systems can provide helpful insights into agroecological dynamics. For instance, niche complementarity (a lack of niche overlap, often reflecting different spatiotemporal resource use patterns) is a primary explanation for higher yields in some intercropping systems relative to monocultures of the component species (Brooker et al. Reference Brooker, Bennett, Cong, Daniell, George, Hallett, Hawes, Iannetta, Jones, Karley, Li, McKenzie, Pakeman, Paterson and Schöb2015). This overyielding in polyculture indicates that interspecific interference is less detrimental than intraspecific interference, implying that stabilizing mechanisms such as resource partitioning are at work. Other mechanisms, including facilitation, may also contribute to the success of intercropping systems (Brooker et al. Reference Brooker, Bennett, Cong, Daniell, George, Hallett, Hawes, Iannetta, Jones, Karley, Li, McKenzie, Pakeman, Paterson and Schöb2015).

In the context of agricultural weeds, greater niche overlap between weed species and crop species may increase weed–crop competition (Zimdahl Reference Zimdahl2004). Weeds that consume the same resources as the crop during the same time periods are typically more problematic than weeds with different requirements. More broadly, functional similarity between weeds and crops may involve shared morphological, physiological, or phenological traits (Navas Reference Navas2012). Shared traits sometimes reflect homology (common descent); therefore, understanding weed phylogeny could contribute to a better understanding of weed–crop competition (Gibson et al. Reference Gibson, Young and Wood2017). The effects of functional traits on ecological interactions between weeds and crops can be observed in the absence of weed control. However, it is also true that similarities between weeds and crops complicate efforts to develop selective weed control tactics and that weed management programs often inadvertently favor weeds that are similar to crops. This unintentional selection promotes crop mimicry in weeds. For example, early water grass [Echinochloa oryzoides (Ard.) Fritsch] closely resembles rice (Oryza sativa L.) (Barrett Reference Barrett1983).

One of the principal drivers of weed–crop competition and weed community assembly is the diversity of available resource pools. According to the resource pool diversity hypothesis, an increase in the spatiotemporal diversity of soil resource pools leads to decreased crop yield loss per unit of weed density (Smith et al. Reference Smith, Mortesen and Ryan2010). This trend occurs because diverse soil resource pools enable more resource partitioning among species. The negative relationship between resource pool diversity and crop yield loss is particularly strong when weeds and crops have different resource acquisition traits (i.e., greater capacity for niche differentiation). At the same time, resource pool diversity shapes weed community structure and may support the persistence of species that are functionally different from the crop. Overall, the resource pool diversity hypothesis predicts that practices such as crop rotation, cover cropping, use of diverse fertility amendments, and integrated weed management will reduce the dependence of crop yield on weed abundance (Smith et al. Reference Smith, Mortesen and Ryan2010). More generally, the relationship between weed abundance and yield loss is affected by environmental factors, management factors, and weed community composition (Ryan et al. Reference Ryan, Mortensen, Bastiaans, Teasdale, Mirsky, Curran, Seidel, Wilson and Hepperly2010; Swinton et al. Reference Swinton, Buhler, Forcella, Gunsolus and King1994; Wilson and Wright Reference Wilson and Wright1990).

Agricultural activities represent filters that shape the species and functional composition of weed communities (Armengot et al. Reference Armengot, Blanco-Moreno, Bàrberi, Bocci, Carlesi, Aendekerk and Sans2016; Cordeau et al. Reference Cordeau, Wayman, Ketterings, Pelzer, Sadeghpour and Ryan2021; Mhlanga et al. Reference Mhlanga, Cheesman, Maasdorp, Muoni, Mabasa, Mangosho and Thierfelder2015). Higher-strength values of these filters (intensive agriculture) are associated with reduced weed diversity and increased abundance of a few dominant weed species (Adeux et al. Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019; Storkey and Neve Reference Storkey and Neve2018). Conversely, a greater diversity of weak filters can select for more diverse and less damaging weed communities. Examples of practices to promote these more-neutral weed communities include integrated weed management, crop management diversity in space and time, and organic fertilizer application (MacLaren et al. Reference MacLaren, Storkey, Menegat, Metcalfe and Dehnen-Schmutz2020).

Recent research suggests that increased weed diversity (i.e., coexistence among many species) is associated with reduced crop yield loss. Understanding the role of weed functional diversity in maintaining ecosystem function and preventing yield loss is among the top five research priorities in weed science, according to a group of experts (Neve et al. Reference Neve, Barney, Buckley, Cousens, Graham, Jordan, Lawton-Rauh, Liebman, Mesgaran, Schut, Shaw, Storkey, Baraibar, Baucom and Chalak2018). The next subsection summarizes existing knowledge about the relationship between diversity and yield.

Increased Weed Diversity Is Associated with Reduced Crop Yield Loss

Negative relationships between weed species richness and crop yield loss have been demonstrated by several authors. Storkey and Neve (Reference Storkey and Neve2018) identified such a relationship using data from the long-term Broadbalk winter wheat experiment, which was initiated in 1843. In this experiment, weedy and weed-free plots were maintained under different fertilization regimes. Using weed species richness data from 19 yr of the experiment, the authors found a strong negative correlation between weed species richness and percentage yield loss due to weeds. This finding was used to illustrate the hypothesis that increased weed diversity is associated with reduced crop yield loss when the weed diversity reflects habitat heterogeneity. Weed species diversity in heterogenous habitats generally implies functional diversity and the presence of species that do not compete strongly against crops. This hypothesis by Storkey and Neve (Reference Storkey and Neve2018) expands on the resource pool diversity hypothesis (Smith et al. Reference Smith, Mortesen and Ryan2010) described in the previous subsection. Separately, Storkey and Neve (Reference Storkey and Neve2018) also hypothesized that weed seedbank diversity is a useful indicator of agronomic and environmental sustainability. In a different study, Brooker et al. (Reference Brooker, Karley, Mitchell, Newton and Pakeman2020) reported a positive relationship between total weed species richness and barley biomass.

Crop yield loss may also be negatively associated with weed evenness or diversity indices combining richness with evenness. Yield was positively correlated with evenness and the Shannon and Simpson indices in coconut (Cocos nucifera L.) and banana (Musa × paradisiaca L.) (Cierjacks et al. Reference Cierjacks, Pommeranz, Schulz and Almeida-Cortez2016). In a long-term study (1996 to 2011), greater weed diversity was associated with a greater capacity for soybean yield increase (Ferrero et al. Reference Ferrero, Lima, Davis and Gonzalez-Andujar2017). However, greater weed diversity also interacted with cold temperatures to reduce corn yield; this result could not be fully explained (Ferrero et al. Reference Ferrero, Lima, Davis and Gonzalez-Andujar2017). Adeux et al. (Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019) reported that more diverse weed communities generally produced less weed biomass and caused lower crop yield losses. Over the gradient of weed community evenness, weed biomass decreased by 83% and crop productivity increased by 23%. It was not possible to separate the effect of reduced weed biomass from any direct effect of weed diversity on crops. However, this study did support the hypothesis that higher weed diversity is associated with lower dominance of competitive weed species that are likely to cause substantial yield loss.

Future research is needed to understand why greater weed diversity is associated with reduced dominance of highly competitive weed species. As noted earlier, this association does not necessarily reflect a causal relationship. However, it is also true that processes of weed–weed interference become more significant in diverse weed communities, sometimes limiting the growth of competitive weed species (Adeux et al. Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019; Clements et al. Reference Clements, Weise and Swanton1994; Pollnac et al. Reference Pollnac, Maxwell and Menalled2009). Real-world weed communities are multispecies assemblages in which complex interspecific interactions occur with variation in space and time. Continued study of these interactions may provide insight into the negative association between weed community diversity and weed–crop competition (Adeux et al. Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019).

Thus far, this section has focused on the competitive effects of weeds on crops. It is worth reiterating that these effects, and therefore the prevalence and composition of neutral weed communities, should be expected to vary between cropping systems and environments. In the following subsection, we turn to the topic of positive weed–crop interactions, which are similarly context specific.

Facilitative Weed–Crop Interactions

Facilitation occurs when the presence of one organism improves the survival, growth, or reproduction of another organism. Facilitative interactions among plants have been well recognized in plant ecology (Brooker et al. Reference Brooker, Maestre, Callaway, Lortie, Cavieres, Kunstler, Liancourt, Tielbörger, Travis, Anthelme, Armas, Coll, Corcket, Delzon and Forey2008; Callaway Reference Callaway2007; Hunter and Aarssen Reference Hunter and Aarssen1988). In agriculture, facilitative interactions have frequently been reported between crops grown in mixture (Brooker et al. Reference Brooker, George, Homulle, Karley, Newton, Pakeman and Schöb2021; Li et al. Reference Li, Li, Sun, Zhou, Bao, Zhang and Zhang2007; Ren et al. Reference Ren, Hu, Zhang, Sun, Tang, Yuan and Chen2014). Facilitative interactions among crops may involve numerous mechanisms, including the production of root exudates to enhance biological nitrogen fixation (Li et al. Reference Li, Li, Wu, Zhang, Li, Li, Lambers and Li2016) or mobilize nutrients (Li et al. Reference Li, Tilman, Lambers and Zhang2014) and hydraulic lift (Sekiya and Yano Reference Sekiya and Yano2004; Sekiya et al. Reference Sekiya, Araki and Yano2011). Given that these facilitative interactions can occur between different crop species, it is reasonable to assume that they might also occur between weeds and crops. Facilitative interactions between weeds and crops may also be indirect and mediated by beneficial insects or soil microbes.

Facilitative effects of weeds mediated by beneficial insects involve ecosystem services such as pollination or biological control of crop pests. The potential of weeds to promote crop pollination is an active area of research, as demonstrated by recent studies in oilseed rape (Brassica napus L.; Crochard et al. Reference Crochard, Julliard, Gaba, Bretagnolle, Baude and Fontaine2022), mango (Mangifera indica L.; Kleiman et al. Reference Kleiman, Koptur and Jayachandran2021), and sweet cherry [Prunus avium (L.) L.; Gilpin et al. Reference Gilpin, O’Brien, Kobel, Brettell, Cook and Power2022]. This topic merits further study. In contrast, the potential of weeds to promote biological control has been established for decades (Altieri and Whitcomb Reference Altieri and Whitcomb1979). For example, a study in corn showed that pests such as fall armyworm (Spodoptera frugiperda Smith & Abbot), corn leaf aphid (Rhopalosiphum maidis Fitch), and sap beetles (Colopterus spp.) were less abundant in weedy plots compared with weeded plots (Penagos et al. Reference Penagos, Magallanes, Valle, Cisneros, Martínez, Goulson, Chapman, Caballero, Cave and Williams2003). Predators of corn pests, such as the carabid Calosoma calidum Fabricius, were more abundant in weedy plots. Corn yield did not differ significantly between weedy and weed-free plots, suggesting that conservation of some weeds may be a reasonable method of enhancing biological control (Penagos et al. Reference Penagos, Magallanes, Valle, Cisneros, Martínez, Goulson, Chapman, Caballero, Cave and Williams2003). In that study, the most abundant weed species were purple nutsedge (Cyperus rotundus L.), niruri (Phyllanthus niruri L.), E. indica, and garden spurge (Euphorbia hirta L.). Similarly, Brust (Reference Brust1991) found that the activity of beneficial nematodes was higher in weedy corn plots relative to weed-free plots, whereas Patriquin et al. (Reference Patriquin, Baines, Lewis and Macdougall1988) found that black bean aphids (Aphis fabae Scopoli) were less numerous in weedy faba bean (Vicia faba L.) plots relative to weed-free plots. Moreover, no significant corn and faba bean yield reduction was reported in weedy plots compared with weed-free plots (Brust et al. Reference Brust1991; Patriquin et al. Reference Patriquin, Baines, Lewis and Macdougall1988). DiTommaso et al. (Reference DiTommaso, Averill, Hoffmann, Fuchsberg and Losey2016) reported that common milkweed (Asclepias syriaca L.) harbored aphids, which provided food for parasitoid wasps (Trichogramma spp.) and other beneficial insects that attack the eggs of insect pests such as the European corn borer (Ostrinia nubilalis Hübner). This positive effect of A. syriaca offset its negative (competitive) effect on corn. Consequently, the role of A. syriaca in promoting biological control increased the economic injury level of this weed (i.e., the minimum weed density at which weed control is worth the cost).

Soil microorganisms can play a crucial role in modulating positive plant–plant interactions (Rodríguez-Echeverría et al. Reference Rodríguez-Echeverría, Armas, Pistón, Hortal and Pugnaire2013). Weeds can be a source of beneficial soil microorganisms such as bacteria that promote crop growth (Sarathambal et al. Reference Sarathambal, Ilamurugu, Priya and Barman2014; Sorty et al. Reference Sorty, Meena, Choudhary, Bitla, Minhas and Krishnani2016; Sturz et al. Reference Sturz, Matheson, Arsenault, Kimpinski and Christie2001). In addition, some agricultural weeds are strong hosts of arbuscular mycorrhizal fungi (AMF), although many weeds are weak AMF hosts (Vatovec et al. Reference Vatovec, Jordan and Huerd2005). A meta-analysis showed that weak host weeds tend to show negative responses to AMF (Li et al. Reference Li, Li, Wu, Zhang, Li, Li, Lambers and Li2016). Even strong host weeds tend to exhibit lower plant growth responses to AMF than strong host crops under fertilized conditions (Li et al. Reference Li, Li, Wu, Zhang, Li, Li, Lambers and Li2016). These findings support the view that AMF can contribute to both crop yield and weed suppression. Additional research has suggested that the presence and appropriate management of AMF host weeds may be harnessed to promote AMF colonization of annual crops (Brito et al. Reference Brito, Carvalho and Goss2013; Feldmann and Boyle Reference Feldmann and Boyle1999). The potential for plant facilitation through mycorrhizal symbiosis might be increased when the plants involved are phylogenetically distant (Montesinos-Navarro et al. Reference Montesinos-Navarro, Valiente-Banuet and Verdú2019) and differ in their AMF assemblages (Montesinos-Navarro et al. Reference Montesinos-Navarro, Segarra-Moragues, Valiente-Banuet and Verdú2012). Therefore, a diverse weed community may be more likely to enhance AMF colonization of a crop, relative to a weed community dominated by a few aggressive species that are weak AMF hosts.

Other forms of plant facilitation may involve plant responses to signals emitted by neighbors, such as volatile organic compounds (VOCs). Signals including VOCs may trigger biochemical responses that positively or negatively affect plant performance, depending on the plant species and signal (Baluška and Mancuso Reference Baluška and Mancuso2009; Brosset and Blande Reference Brosset and Blande2022; Gagliano and Renton Reference Gagliano and Renton2013; Vivaldo et al. Reference Vivaldo, Masi, Taiti, Caldarelli and Mancuso2017). A better understanding of signaling between weeds and crops could provide further insight into why different weed communities have different effects on crop production.

This section has explored ecological mechanisms that may help explain the presence of neutral weed communities in agroecosystems. In the following section, we consider how this ecological knowledge can be applied to promote the establishment of neutral weed communities.

How to Attain Neutral Weed Communities

Here, we propose two approaches to attain neutral weed communities (Figure 1). These approaches are intended to promote sustainable weed management, enable reduced herbicide use and soil tillage, and increase biodiversity without significant crop yield losses. The first approach focuses on maximizing weed diversity, whereas the second approach focuses on selectively removing the most problematic weed species.

Figure 1. Schematic representation of the principal aims and ecological effects of two approaches proposed to increase the neutrality of weed communities. The first approach can be pursued by applying traditional management strategies (Adeux et al. Reference Adeux, Vieren, Carlesi, Bàrberi, Munier-Jolain and Cordeau2019). The second approach may be facilitated by emerging technologies.

As described previously, weed species diversity is frequently associated with functional diversity and reduced crop yield loss. The main mechanism underlying reduced crop yield loss is a reduction in the dominance of highly competitive weed species that consume the resources crops require. Weed diversity can be enhanced through management practices that increase environmental heterogeneity and the potential for niche complementarity between weeds and crops (Navas Reference Navas2012; Smith et al. Reference Smith, Mortesen and Ryan2010; Storkey and Neve Reference Storkey and Neve2018). Practices aimed at increasing crop diversity, such as crop mixtures, crop rotation, and cover cropping, are valuable tools to increase weed biodiversity and reduce yield loss (Palmer and Maurer Reference Palmer and Maurer1997; Smith et al. Reference Smith, Mortesen and Ryan2010). Other strategies include diversifying residue management programs and fertility sources to support weeds with different resource use profiles (Smith et al. Reference Smith, Mortesen and Ryan2010). In the context of weed management, integrated programs combining diverse tactics result in higher weed diversity and better long-term outcomes, compared with less diverse programs that are heavily reliant on one or two tactics (Clements et al. Reference Clements, Weise and Swanton1994; Cordeau et al. Reference Cordeau, Adeux and Deytieux2020; Liebman Reference Liebman and Zimdahl2018; Liebman and Gallandt Reference Liebman, Gallandt and Jackson1997). The capacity of a management system to simultaneously promote weed biodiversity and crop yield may vary with crop identity, environmental conditions, and the weed species present in an area (Mézière et al. Reference Mézière, Petit, Granger, Biju-Duval and Colbach2015). Further research is needed to develop systems that promote diverse and neutral weed communities in each context. In addition, research is needed to develop strategies for managing aggressive weed species that impede efforts to increase weed community diversity (Armengot et al. Reference Armengot, José-María, Chamorro and Sans2017). These species may require specific control measures, that is, the application of our second approach.

Species-specific weed management (Figure 1) can be accomplished in several ways. Humans are often capable of identifying and removing troublesome weed species by hand. However, hand weeding is laborious and expensive (Tiwari et al. Reference Tiwari, Sindel, Smart, Coleman, Fyfe, Lawlor, Vo and Kristiansen2022). Emerging technologies provide more efficient methods of removing specific weed species, such as competitive species that show substantial niche overlap with the crop. We suggest that these technologies can be used to establish weed communities “shaped” according to the ecology of each cropping system, drastically reducing weed–crop interference.

Some approaches to species-specific weed management involve sensor-equipped field robots or drones (Zhang et al. Reference Zhang, Miao, Li, He and Sun2022; Figure 2). The sensors measure features such as weed shape, size, color, texture, and spectral reflectance, then artificial intelligence can be used to identify weed species based on these features (Bawden et al. Reference Bawden, Kulk, Russell, McCool, English, Dayoub, Lehnert and Perez2017; Pantazi et al. Reference Pantazi, Moshou and Bravo2016; Peteinatos et al. Reference Peteinatos, Reichel, Karouta, Andújar and Gerhards2020; Wang et al. Reference Wang, Yao and Nguyen2022). Accurate weed identification represents a major challenge, as individuals of the same weed species can frequently appear different. Other issues include the difficulty of identifying young seedlings and variable light availability (Zhang et al. Reference Zhang, Miao, Li, He and Sun2022). Despite these challenges, classification accuracy is improving with the emergence of new machine learning and deep learning strategies, combined with the creation of large training image sets (Zhang et al. Reference Zhang, Miao, Li, He and Sun2022). For example, Olsen et al. (Reference Olsen, Konovalov, Philippa, Ridd, Wood, Johns, Banks, Girgenti, Kenny, Whinney, Calvert, Azghadi and White2019) used numerous labeled images of eight Australian weed species and deep learning to achieve a greater than 95% classification accuracy. Du et al. (Reference Du, Zhang, Tsang and Jawed2022) used approximately 10,000 images of flax (Linum usitatissimum L.) and associated weeds to develop convolutional neural network models, one of which achieved 90% classification accuracy when deployed in a flax field.

Figure 2. Using drones and weeder robots to promote neutral weed communities. (A) Weed community manipulation with (1) drones and (2) weeder robots capable of recognizing and removing specific weed species. (B) Crop coexistence with a neutral weed community. Modified from Esposito et al. (Reference Esposito, Crimaldi, Cirillo, Sarghini and Maggio2021).

Once identified, weeds that require control can be mechanically or chemically removed. Detection and removal of the targeted weed species may both be performed by a single terrestrial unit (Zhang et al. Reference Zhang, Miao, Li, He and Sun2022). Alternatively, some authors have suggested combining aerial drones with terrestrial robots. In this scenario, unmanned aerial vehicles fly over a crop field and take aerial images, which are analyzed by an off-site system that sends information about the locations of problematic weeds to terrestrial robots that perform weed removal (Esposito et al. Reference Esposito, Crimaldi, Cirillo, Sarghini and Maggio2021; Figure 2). Buddha et al. (Reference Buddha, Nelson, Zermas and Papanikolopoulos2019) developed an image-analysis procedure that identified three corn weed species with 93.8% accuracy from RGB images taken from a high altitude (24.4 m). The weed locations and identifications would be sent to a robotic sprayer. Similarly, in sugar beet (Beta vulgaris L.), Lottes et al. (Reference Lottes, Khanna, Pfeifer, Siegwart and Stachniss2017) identified two weed species with 85% precision from aerial images. Such promising results should encourage further research, which will increase the ability of robotic tools to selectively remove specific weed species without causing collateral damage (i.e., damage to beneficial weeds or crops).

New biotechnologies also show promise for selective weed management. In particular, RNA interference (RNAi) enables the silencing of specific gene targets. Agricultural research on RNAi is largely focused on controlling insect pests (Kunte et al. Reference Kunte, McGraw, Bell, Held and Avila2020; Mamta and Rajam Reference Mamta and Rajam2017). However, RNAi might also allow the control of troublesome weed species without affecting desirable plants or other organisms (Mezzetti et al. Reference Mezzetti, Smagghe, Arpaia, Christiaens, Dietz-Pfeilstetter, Jones, Kostov, Sabbadini, Opsahl-Sorteberg, Ventura, Taning and Sweet2020). To achieve this selectivity, small interfering RNA molecules would need to silence gene sequences that are important in the target species but not present in desirable species. Further research is needed to develop this technology and determine what level of selectivity is possible.

Conclusion

In this paper, we have provided scientific evidence of neutral weed communities in different cropping systems. We have also explored ecological mechanisms that help explain why different weed communities have different effects on crops. We emphasize that a weed community that is neutral in one cropping system and environment may be detrimental in other contexts. More studies are needed to understand the interactions between neutral weed communities and crops and to identify neutral weed communities in diverse cropping systems and environments. Further research is needed on neutral weed communities in the context of crop rotation, as a weed community that is neutral in one rotation phase could be detrimental in the next phase. Whenever possible, research on these questions should occur over long timeframes and assess indirect and positive interactions between weeds and crops as well as direct negative interactions such as competition.

We proposed two weed management approaches to attain neutral weed communities. The first approach seeks to maximize weed biodiversity and can be pursued with existing ecological weed management practices. The second approach seeks to selectively manage specific weed species. Advanced tools such as weeding robots may increase the feasibility of this second approach. Using these approaches to promote neutral communities could contribute to decreased weed control costs, enhanced ecosystem services, and increased biodiversity without reducing crop productivity.

Acknowledgments

We thank current and former members of the DiTommaso Cornell Weed Ecology and Management Laboratory and Maggio Laboratory at the University of Naples Federico II for engaging discussions and feedback on this work. We thank David Clements and Richard Smith for providing valuable suggestions for improving the article. This research received no specific grant from any funding agency or the commercial or not-for-profit sectors. No competing interests have been declared.

Footnotes

Associate Editor: William Vencill, University of Georgia

References

Adeux, G, Vieren, E, Carlesi, S, Bàrberi, P, Munier-Jolain, N, Cordeau, S (2019) Mitigating crop yield losses through weed diversity. Nat Sustain 2:10181026 CrossRefGoogle Scholar
Adler, PB, HilleRisLambers, J, Levine, JM (2007) A niche for neutrality. Ecol Lett 10:95104 CrossRefGoogle ScholarPubMed
Adler, PB, Smull, D, Beard, KH, Choi, RT, Furniss, T, Kulmatiski, A, Meiners, JM, Tredennick, AT, Veblen, KE (2018) Competition and coexistence in plant communities: intraspecific competition is stronger than interspecific competition. Ecol Lett 21:13191329 CrossRefGoogle ScholarPubMed
Altieri, MA, Whitcomb, WH (1979) The potential use of weeds in the manipulation of beneficial insects. HortScience 14:1218 CrossRefGoogle Scholar
Andrew, IKS, Storkey, J, Sparkes, DLA (2015) A review of the potential for competitive cereal cultivars as a tool in integrated weed management. Weed Res 55:239248 CrossRefGoogle ScholarPubMed
Arai, M, Minamiya, Y, Tsuzura, H, Watanabe, Y, Yagioka, A, Kaneko, N (2014) Changes in water stable aggregate and soil carbon accumulation in a no-tillage with weed mulch management site after conversion from conventional management practices. Geoderma 221–222:5060 CrossRefGoogle Scholar
Armengot, L, Blanco-Moreno, J M, Bàrberi, P, Bocci, G, Carlesi, S, Aendekerk, R, Sans, FX (2016) Tillage as a driver of change in weed communities: a functional perspective. Agric Ecosyst Environ 222:276285 CrossRefGoogle Scholar
Armengot, L, José-María, L, Chamorro, L, Sans, FX (2017) Avena sterilis and Lolium rigidum infestations hamper the recovery of diverse arable weed communities. Weed Res 57:278286 CrossRefGoogle Scholar
Bawden, O, Kulk, J, Russell, R, McCool, C, English, A, Dayoub, F, Lehnert, C, Perez, T (2017) Robot for weed species plant-specific management. Journal of Field Robotics 34:11791199 CrossRefGoogle Scholar
Baluška, F, Mancuso, S (2009) Plant neurobiology: from sensory biology, via plant communication, to social plant behavior. Cogn Process 10:37 CrossRefGoogle ScholarPubMed
Bàrberi, P, Bocci, G, Carlesi, S, Armengot, L, Blanco-Moreno, JM, Sans, FX (2018) Linking species traits to agroecosystem services: a functional analysis of weed communities. Weed Res 58:7688 CrossRefGoogle Scholar
Bàrberi, P, Burgio, G, Dinelli, G, Moonen, AC, Otto, S, Vazzana, C, Zanin, G (2010) Functional biodiversity in the agricultural landscape: relationships between weeds and arthropod fauna. Weed Res 50:388401 CrossRefGoogle Scholar
Barrett, SH (1983) Crop mimicry in weeds. Economic Botany 37:255282 CrossRefGoogle Scholar
Bhandari, DC, Sen, DN (1979) Agro-ecosystem analysis of the Indian arid zone I. Indigofera cordifolia heyne ex roth. as a weed. Agro-Ecosystems 5:257262 10.1016/0304-3746(79)90005-2CrossRefGoogle Scholar
Blaix, C, Moonen, AC, Dostatny, DF, Izquierdo, J, Le Corff, J, Morrison, J, Von Redwitz, C, Schumacher, M, Westerman, PR (2018) Quantification of regulating ecosystem services provided by weeds in annual cropping systems using a systematic map approach. Weed Res 58:151164 CrossRefGoogle Scholar
Boström, U, Milberg, P, Fogelfors, H (2003) Yield loss in spring-sown cereals related to the weed flora in the spring. Weed Sci 51:418424 CrossRefGoogle Scholar
Bretagnolle, V, Gaba, S (2015) Weeds for bees? A review. Agron Sustain Dev 35:891909 CrossRefGoogle Scholar
Brito, I, Carvalho, M, Goss, MJ (2013) Soil and weed management for enhancing arbuscular mycorrhiza colonization of wheat. Soil Use Manage 29:540546 CrossRefGoogle Scholar
Brooker, RW, Bennett, AE, Cong, W-F, Daniell, TJ, George, TS, Hallett, PD, Hawes, C, Iannetta, PPM, Jones, HG, Karley, AJ, Li, L, McKenzie, BM, Pakeman, RJ, Paterson, E, Schöb, C, et al. (2015) Improving intercropping: a synthesis of research in agronomy, plant physiology and ecology. New Phytol 206:107117 CrossRefGoogle ScholarPubMed
Brooker, RW, George, TS, Homulle, Z, Karley, AJ, Newton, AC, Pakeman, RJ, Schöb, C (2021) Facilitation and biodiversity–ecosystem function relationships in crop production systems and their role in sustainable farming. J Ecol 109:20542067 CrossRefGoogle Scholar
Brooker, RW, Karley, AJ, Mitchell, C, Newton, AC, Pakeman, RJ (2020) Do we need weeds? The place of non-crop plants in arable systems. Pages 149–154 in Dundee Conference, Crop Production in Northern Britain. Dundee, UK: Association for Crop Protection in Northern BritainGoogle Scholar
Brooker, RW, Maestre, FT, Callaway, RM, Lortie, CL, Cavieres, LA, Kunstler, G, Liancourt, P, Tielbörger, K, Travis, JMJ, Anthelme, F, Armas, C, Coll, L, Corcket, E, Delzon, S, Forey, E, et al. (2008) Facilitation in plant communities: the past, the present, and the future. J Ecol 96:1834 Google Scholar
Brosset, A, Blande, JD (2022) Volatile-mediated plant–plant interactions: volatile organic compounds as modulators of receiver plant defence, growth, and reproduction. J Exp Bot 73:511528 CrossRefGoogle ScholarPubMed
Brust, GE (1991) Augmentation of an endemic entomogenous nematode by agroecosystem manipulation for the control of a soil pest. Agric Ecosyst Environ 36:175184 CrossRefGoogle Scholar
Buddha, K, Nelson, HJ, Zermas, D, Papanikolopoulos, N (2019) Weed detection and classification in high altitude aerial images for robot-based precision agriculture. Pages 280–285 in 27th Mediterranean Conference on Control and Automation (MED). New York: IEEECrossRefGoogle Scholar
Callaway, RM (2007) Positive Interactions and Interdependence in Plant Communities. Dordrecht, Netherlands: Springer. 418 pGoogle Scholar
Chesson, P (2000) Mechanisms of maintenance of species diversity. Annu Rev Ecol Syst 31:343366 CrossRefGoogle Scholar
Cierjacks, A, Pommeranz, M, Schulz, K, Almeida-Cortez, J (2016) Is crop yield related to weed species diversity and biomass in coconut and banana fields of northeastern Brazil? Agric Ecosyst Environ 220:175183 CrossRefGoogle Scholar
Cirillo, V, Masin, R, Maggio, A, Zanin, G (2018) Crop-weed interactions in saline environments. Eur J Agron 99:5161 CrossRefGoogle Scholar
Clements, DR, Weise, SF, Swanton, CJ (1994) Integrated weed management and weed species diversity. Phytoprotection 75:118 CrossRefGoogle Scholar
Cordeau, S, Adeux, G, Deytieux, V (2020) Diversity is the key for successful agroecological weed management. Indian J Weed Sci 52:204210 Google Scholar
Cordeau, S, Wayman, S, Ketterings, QM, Pelzer, C J, Sadeghpour, A, Ryan, MR (2021) Long-term soil nutrient management affects taxonomic and functional weed community composition and structure. Front Agron 3:636179 CrossRefGoogle Scholar
Corre-Hellou, G, Dibet, A, Hauggaard-Nielsen, H, Crozat, Y, Gooding, M, Ambus, P, Jensen, E S (2011) The competitive ability of pea–barley intercrops against weeds and the interactions with crop productivity and soil N availability. Field Crops Res 122:264272 CrossRefGoogle Scholar
Crochard, L, Julliard, R, Gaba, S, Bretagnolle, V, Baude, M, Fontaine, C (2022) Weeds from non-flowering crops as potential contributors to oilseed rape pollination. Agric Ecosyst Environ 336:108026 CrossRefGoogle Scholar
Dachraoui, M, Sombrero, A (2020) Effect of tillage systems and different rates of nitrogen fertilisation on the carbon footprint of irrigated maize in a semiarid area of Castile and Leon, Spain. Soil Tillage Res 196:104472 CrossRefGoogle Scholar
Dijk, M van, Morley, T, Rau, ML, Saghai, Y (2021) A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050. Nat Food 2:494501 CrossRefGoogle ScholarPubMed
DiTommaso, A, Averill, KM, Hoffmann, MP, Fuchsberg, JR, Losey, JE (2016) Integrating insect, resistance, and floral resource management in weed control decision-making. Weed Sci 64:743756 CrossRefGoogle Scholar
Du, Y, Zhang, G, Tsang, D, Jawed, MK (2022) Deep-CNN based robotic multi-class under-canopy weed control in precision farming. Pages 2237–2279 in 2022 IEEE International Conference on Robotics and Automation (ICRA). Philadelphia, PA: Institute of Electrical and Electronics EngineersCrossRefGoogle Scholar
Esposito, M, Cirillo, V, Cozzolino, E, De Vita, P, Maggio, A (in press) Soil nutrition management may preserve non-detrimental weed communities in rainfed winter wheat (T. aestivum). Agr Ecosyst Environ. doi: 10.1016/j.agee.2023.108596 CrossRefGoogle Scholar
Esposito, M, Crimaldi, M, Cirillo, V, Sarghini, F, Maggio, A (2021) Drone and sensor technology for sustainable weed management: a review. Chem Biol Technol Agric 8:18 CrossRefGoogle Scholar
Feldmann, F, Boyle, C (1999) Weed-mediated stability of arbuscular mycorrhizal effectiveness in maize monocultures. Angew Bot 73:15 Google Scholar
Ferrero, R, Lima, M, Davis, AS, Gonzalez-Andujar, JL (2017) Weed diversity affects soybean and maize yield in a long term experiment in Michigan, USA. Front Plant Sci 8:236 CrossRefGoogle Scholar
Gaba, S, Cheviron, N, Perrot, T, Piutti, S, Gautier, J-L, Bretagnolle, V (2020) Weeds enhance multifunctionality in arable lands in South-West of France. Front Sustain Food Syst 4:71 CrossRefGoogle Scholar
Gaba, S, Perronne, R, Fried, G, Gardarin, A, Bretagnolle, F, Biju-Duval, L, Colbach, N, Cordeau, S, Fernández-Aparicio, M, Gauvrit, C, Gibot-Leclerc, S, Guillemin, J-P, Moreau, D, Munier-Jolain, N, Strbik, F, Reboud, X (2017) Response and effect traits of arable weeds in agro-ecosystems: a review of current knowledge. Weed Res 57:123147 CrossRefGoogle Scholar
Gadermaier, F, Berner, A, Fließbach, A, Friedel, JK, Mäder, P (2012) Impact of reduced tillage on soil organic carbon and nutrient budgets under organic farming. Renew Agric Food Syst 27:6880 CrossRefGoogle Scholar
Gagliano, M, Renton, M (2013) Love thy neighbour: facilitation through an alternative signalling modality in plants. BMC Ecol 13:16 CrossRefGoogle ScholarPubMed
Garibaldi, LA, Carvalheiro, LG, Leonhardt, SD, Aizen, MA, Blaauw, BR, Isaacs, R, Kuhlmann, M, Kleijn, D, Klein, AM, Kremen, C, Morandin, L, Scheper, J, Winfree, R (2014) From research to action: enhancing crop yield through wild pollinators. Front Ecol Environ 12:439447 CrossRefGoogle Scholar
Gause, GF (1934) The Struggle for Existence. Maryland: The Williams and Wilkins Company. 167 pCrossRefGoogle ScholarPubMed
Germeier, CU (2000) Wide row spacing and living mulch: new strategies for producing high protein grains in organic cereal production. Biol Agric Hortic 18:127139 CrossRefGoogle Scholar
Gholamhoseini, M, AghaAlikhani, M, Mirlatifi, SM, Sanavy, SAMM (2013) Weeds—friend or foe? Increasing forage yield and decreasing nitrate leaching on a corn forage farm infested by redroot pigweed. Agric Ecosyst Environ 179:151162 CrossRefGoogle Scholar
Gibbons, DW, Bohan, DA, Rothery, P, Stuart, RC, Haughton, AJ, Scott, RJ, Wilson, JD, Perry, JN, Clark, SJ, Dawson, RJG, Firbank, LG (2006) Weed seed resources for birds in fields with contrasting conventional and genetically modified herbicide-tolerant crops. Proc R Soc B Biol Sci 273:19211928 CrossRefGoogle ScholarPubMed
Gibson, DJ, Young, BG, Wood, AJ (2017) Can weeds enhance profitability? Integrating ecological concepts to address crop-weed competition and yield quality. J Ecol 105:900904 CrossRefGoogle Scholar
Gilpin, AM, O’Brien, C, Kobel, C, Brettell, LE, Cook, JM, Power, SA (2022) Co-flowering plants support diverse pollinator populations and facilitate pollinator visitation to sweet cherry crops. Basic Appl Ecol 63:3648 CrossRefGoogle Scholar
Godoy, O, Gómez-Aparicio, L, Matías, L, Pérez-Ramos, IM, Allan, E (2020) An excess of niche differences maximizes ecosystem functioning. Nat Commun 11:4180 CrossRefGoogle ScholarPubMed
Gunton, RM, Petit, S, Gaba, S (2011) Functional traits relating arable weed communities to crop characteristics. J Veg Sci 22:541550 CrossRefGoogle Scholar
Haddaway, NR, Hedlund, K, Jackson, LE, Kätterer, T, Lugato, E, Thomsen, IK, Jørgensen, HB, Isberg, P-E (2017) How does tillage intensity affect soil organic carbon? A systematic review. Environ Evidence 6:30 Google Scholar
Heap, I (2023) The International Herbicide-Resistant Weed Database. www.weedscience.org Accessed: January 9, 2023Google Scholar
Hubbell, SP (2001) A Unified Neutral Theory of Biodiversity and Biogeography. Princeton, NJ: Princeton University Press. 392 pGoogle Scholar
Hunter, AF, Aarssen, LW (1988) Plants helping plants. Bioscience 38:3440 CrossRefGoogle Scholar
Jones, NE, Smith, BM (2007) Effects of selective herbicide treatment, row width and spring cultivation on weed and arthropod communities in winter wheat. Asp Appl Biol 81:3946 Google Scholar
Karlen, DL, Cambardella, CA, Kovar, JL, Colvin, TS (2013) Soil quality response to long-term tillage and crop rotation practices. Soil Tillage Res 133:5464 CrossRefGoogle Scholar
Kleiman, BM, Koptur, S, Jayachandran, K (2021) Beneficial interactions of weeds and pollinators to improve crop production. J Res Weed Sci 4:151164 Google Scholar
Kok, H, Papendick, RI, Saxton, KE (2009) STEEP: impact of long-term conservation farming research and education in Pacific Northwest wheatlands. J Soil Water Conserv 64:253264 CrossRefGoogle Scholar
Kunte, N, McGraw, E, Bell, S, Held, D, Avila, LA (2020) Prospects, challenges and current status of RNAi through insect feeding. Pest Manage Sci 76:2641 CrossRefGoogle ScholarPubMed
Lemerle, D, Luckett, DJ, Lockley, P, Koetz, E, Wu, H (2014) Competitive ability of Australian canola (Brassica napus) genotypes for weed management. Crop Pasture Sci 65:13001310 CrossRefGoogle Scholar
Li, B, Li, YY, Wu, HM, Zhang, FF, Li, CJ, Li, XX, Lambers, H, Li, L (2016) Root exudates drive interspecific facilitation by enhancing nodulation and N2 fixation. Proc Natl Acad Sci USA 113:64966501 CrossRefGoogle ScholarPubMed
Li, L, Li, SM, Sun, JH, Zhou, LL, Bao, XG, Zhang, HG, Zhang, F-S (2007) Diversity enhances agricultural productivity via rhizosphere phosphorus facilitation on phosphorus-deficient soils. Proc Natl Acad Sci USA 104:1119211196 CrossRefGoogle ScholarPubMed
Li, L, Tilman, D, Lambers, H, Zhang, F-S (2014) Plant diversity and overyielding: insights from belowground facilitation of intercropping in agriculture. New Phytol 203:6369 CrossRefGoogle ScholarPubMed
Liang, W, Huang, M (1994) Influence of citrus orchard ground cover plants on arthropod communities in China: a review. Agric Ecosyst Environ 50:2937 CrossRefGoogle Scholar
Liebman, M (2018) Cultural techniques to manage weeds. Pages 203225 in Zimdahl, L, ed. Integrated Weed Management for Sustainable Agriculture. Cambridge: Burleigh Dodds Science Google Scholar
Liebman, M, Gallandt, ER (1997) Many little hammers: ecological management of crop-weed interactions. Pages 290330 in Jackson, LE, ed. Ecology in Agriculture. San Diego, CA; London, UK: Academic Press Google Scholar
Liebman, M, Mohler, C, Staver, C, eds (2001) Ecological management of agricultural weeds. Cambridge: Cambridge University Press. 532 pCrossRefGoogle Scholar
Little, NG, DiTommaso, A, Westbrook, AS, Ketterings, QM, Mohler, CL (2021) Effects of fertility amendments on weed growth and weed–crop competition: a review. Weed Sci 69:132146 CrossRefGoogle Scholar
Lottes, P, Khanna, R, Pfeifer, J, Siegwart, R, Stachniss, C (2017) UAV-based crop and weed classification for smart farming. Pages 30243031 in IEEE International Conference on Robotics and Automation (ICRA), Singapore, SG. New York: IEEECrossRefGoogle Scholar
MacLaren, C, Bennett, J, Dehnen-Schmutz, K (2019) Management practices influence the competitive potential of weed communities and their value to biodiversity in South African vineyards. Weed Res 59:93106 CrossRefGoogle Scholar
MacLaren, C, Storkey, J, Menegat, A, Metcalfe, H, Dehnen-Schmutz, K (2020) An ecological future for weed science to sustain crop production and the environment. A review. Agron Sustain Dev 40:129 CrossRefGoogle Scholar
Mamta, B, Rajam, M V (2017) RNAi technology: a new platform for crop pest control. Physiol Mol Biol Plants 23:487501 CrossRefGoogle ScholarPubMed
Marshall, EJP, Brown, VK, Boatman, ND, Lutman, PJW, Squire, GR, Ward, LK (2003) The role of weeds in supporting biological diversity within crop fields. Weed Res 43:7789 CrossRefGoogle Scholar
Maxwell, B (2018) Weed-plant interactions. Pages 2942 in Zimdahl, RL, ed. Integrated Weed Management for Sustainable Agriculture. Cambridge: Burleigh Dodds ScienceGoogle Scholar
Meng, J, Li, L, Liu, H, Li, Y, Li, C, Wu, G, Yu, X, Guo, L, Cheng, D, Muminov, MA, Liang, X, Jiang, G (2016) Biodiversity management of organic orchard enhances both ecological and economic profitability. PeerJ 4:e2137 CrossRefGoogle ScholarPubMed
Mézière, D, Petit, S, Granger, S, Biju-Duval, L,Colbach, N (2015) Developing a set of simulation-based indicators to assess harmfulness and contribution to biodiversity of weed communities in cropping systems. Ecol Indic 48:157170 CrossRefGoogle Scholar
Mezzetti, B, Smagghe, G, Arpaia, S, Christiaens, O, Dietz-Pfeilstetter, A, Jones, H, Kostov, K, Sabbadini, S, Opsahl-Sorteberg, H-G, Ventura, V, Taning, CNT, Sweet, J (2020) RNAi: what is its position in agriculture? J Pest Sci 93:11251130 CrossRefGoogle Scholar
Mhlanga, B, Cheesman, S, Maasdorp, B, Muoni, T, Mabasa, S, Mangosho, E, Thierfelder, C (2015) Weed community responses to rotations with cover crops in maize-based conservation agriculture systems of Zimbabwe. Crop Prot. 69:18 CrossRefGoogle Scholar
Milberg, P, Hallgren, E (2004) Yield loss due to weeds in cereals and its large-scale variability in Sweden. Field Crops Res 86:199209 CrossRefGoogle Scholar
Millar, K, Gibson, DJ, Young, BG, Wood, AJ (2007) Impact of interspecific competition on seed development and quality of five soybean cultivars. Aust J Exp Agric 47:14551459 CrossRefGoogle Scholar
Montesinos-Navarro, A, Segarra-Moragues, JG, Valiente-Banuet, A, Verdú, M (2012) Plant facilitation occurs between species differing in their associated arbuscular mycorrhizal fungi. New Phytol 196:835844 CrossRefGoogle ScholarPubMed
Montesinos-Navarro, A, Valiente-Banuet, A, Verdú, M (2019) Plant facilitation through mycorrhizal symbiosis is stronger between distantly related plant species. New Phytol 224:928935 CrossRefGoogle ScholarPubMed
Navas, M-L (2012) Trait-based approaches to unravelling the assembly of weed communities and their impact on agro-ecosystem functioning. Weed Res 52:479488 CrossRefGoogle Scholar
Neve, P, Barney, JN, Buckley, Y, Cousens, RD, Graham, S, Jordan, NR, Lawton-Rauh, A, Liebman, M, Mesgaran, MB, Schut, M, Shaw, J, Storkey, J, Baraibar, B, Baucom, RS, Chalak, M, et al. (2018) Reviewing research priorities in weed ecology, evolution and management: a horizon scan. Weed Res 58:250258 CrossRefGoogle ScholarPubMed
Nicholls, CI, Altieri, MA (2013) Plant biodiversity enhances bees and other insect pollinators in agroecosystems. A review. Agron Sustain Dev 33:257274 CrossRefGoogle Scholar
Null, N, Hawes, C, Haughton, AJ, Osborne, JL, Roy, DB, Clark, SJ, Perry, JN, Rothery, P, Bohan, DA, Brooks, DR, Champion, GT, Dewar, AM, Heard, MS, Woiwod, IP, Daniels, RE, et al. (2003) Responses of plants and invertebrate trophic groups to contrasting herbicide regimes in the Farm Scale Evaluations of genetically modified herbicide–tolerant crops. Philos Trans R Soc Lond B Biol Sci 358:18991913 Google Scholar
Oerke, EC (2006) Crop losses to pests. J Agric Sci 144:3143 CrossRefGoogle Scholar
Ojeniyi, S, Odedina, S, Agbede, T (2012) Soil productivity improving attributes of mexican sunflower (Tithoniadiversifolia) and siam weed (Chromolaena odorata). Emir J Food Agric 24:243247 Google Scholar
Olsen, A, Konovalov, DA, Philippa, B, Ridd, P, Wood, JC, Johns, J, Banks, W, Girgenti, B, Kenny, O, Whinney, J, Calvert, B, Azghadi, MR, White, RD (2019) DeepWeeds: a multiclass weed species image dataset for deep learning. Sci Rep 9:2058 CrossRefGoogle ScholarPubMed
Orzech, K, Wanic, M, Załuski, D (2021) The effects of soil compaction and different tillage systems on the bulk density and moisture content of soil and the yields of winter oilseed rape and cereals. Agriculture 11:666 CrossRefGoogle Scholar
Palmer, MW, Maurer, TA (1997) Does diversity beget diversity? A case study of crops and weeds. J Veg Sci 8:235240 CrossRefGoogle Scholar
Pantazi, X-E, Moshou, D, Bravo, C (2016) Active learning system for weed species recognition based on hyperspectral sensing. Biosyst Eng 146:193202 CrossRefGoogle Scholar
Patriquin, DG, Baines, D, Lewis, J, Macdougall, A (1988) Aphid infestation of fababeans on an organic farm in relation to weeds, intercrops and added nitrogen. Agric Ecosyst Environ 20:279288 CrossRefGoogle Scholar
Penagos, DI, Magallanes, R, Valle, J, Cisneros, J, Martínez, AM, Goulson, D, Chapman, JW, Caballero, P, Cave, RD, Williams, T (2003) Effect of weeds on insect pests of maize and their natural enemies in Southern Mexico. Int J Pest Manag 49:155161 CrossRefGoogle Scholar
Peteinatos, GG, Reichel, P, Karouta, J, Andújar, D, Gerhards, R (2020) Weed identification in maize, sunflower, and potatoes with the aid of convolutional neural networks. Remote Sens 12:4185 CrossRefGoogle Scholar
Pollnac, FW, Maxwell, BD, Menalled, FD (2009) Weed community characteristics and crop performance: a neighbourhood approach. Weed Res 49:242250 CrossRefGoogle Scholar
Promsakha Na Sakonnakhon, S, Cadisch, G, Toomsan, B, Vityakon, P, Limpinuntana, V, Jogloy, S, Patanothai, A (2006) Weeds—friend or foe? The role of weed composition on stover nutrient recycling efficiency. Field Crops Res 97:238247 CrossRefGoogle Scholar
Ren, W, Hu, L, Zhang, J, Sun, C, Tang, J, Yuan, Y, Chen, X (2014) Can positive interactions between cultivated species help to sustain modern agriculture? Front Ecol Environ 12:507514 CrossRefGoogle Scholar
Rodríguez-Echeverría, S, Armas, C, Pistón, N, Hortal, S, Pugnaire, FI (2013) A role for below-ground biota in plant–plant facilitation. J Ecol 101:14201428 CrossRefGoogle Scholar
Rouw, A de, Soulileuth, B, Huon, S (2015) Stable carbon isotope ratios in soil and vegetation shift with cultivation practices (northern Laos). Agric Ecosyst Environ 200:161168 CrossRefGoogle Scholar
Rowntree, JK, Dean, C, Morrison, F, Brooker, RW, Price, EAC (2021) Arable wildflowers have potential as living mulches for sustainable agriculture. Plant Ecol Divers 14:93104 CrossRefGoogle Scholar
Ryan, MR, Mortensen, DA, Bastiaans, L, Teasdale, JR, Mirsky, SB, Curran, WS, Seidel, R, Wilson, DO, Hepperly, PR (2010). Elucidating the apparent maize tolerance to weed competition in long-term organically managed systems. Weed Res 50:2536 CrossRefGoogle Scholar
Sarathambal, C, Ilamurugu, K, Priya, LS, Barman, KK (2014) A review on weeds as source of novel plant growth promoting microbes for crop improvement. J Appl Nat Sci 6:880886 CrossRefGoogle Scholar
Seitz, S, Goebes, P, Puerta, VL, Pereira, EIP, Wittwer, R, Six, J, van der Heijden, MGA, Scholten, T (2018) Conservation tillage and organic farming reduce soil erosion. Agron Sustain Dev 39:4 CrossRefGoogle Scholar
Sekiya, N, Araki, H, Yano, K (2011) Applying hydraulic lift in an agroecosystem: forage plants with shoots removed supply water to neighboring vegetable crops. Plant Soil 341:3950 CrossRefGoogle Scholar
Sekiya, N, Yano, K (2004) Do pigeon pea and sesbania supply groundwater to intercropped maize through hydraulic lift?—Hydrogen stable isotope investigation of xylem waters. Field Crops Res 86:167173 CrossRefGoogle Scholar
Silvertown, J (2004) Plant coexistence and the niche. Trends Ecol Evol 19:605611 CrossRefGoogle Scholar
Smith, BM, Aebischer, NJ, Ewald, J, Moreby, S, Potter, C, Holland, JM (2020) The potential of arable weeds to reverse invertebrate declines and associated ecosystem services in cereal crops. Front Sustain Food Syst 3:118 CrossRefGoogle Scholar
Smith, RG, Mortesen, DA, Ryan, MR (2010) A new hypothesis for the functional role of diversity in mediating resource pools and weed–crop competition in agroecosystems. Weed Res 50:3748 CrossRefGoogle Scholar
Solomou, A, Sfougaris, A (2011) Comparing conventional and organic olive groves in central Greece: plant and bird diversity and abundance. Renew Agric Food Syst 26:297316 CrossRefGoogle Scholar
Sorty, AM, Meena, KK, Choudhary, K, Bitla, UM, Minhas, PS, Krishnani, KK (2016) Effect of plant growth promoting bacteria associated with halophytic weed (Psoralea corylifolia L) on germination and seedling growth of wheat under saline conditions. Appl Biochem Biotechnol 180:872882 CrossRefGoogle Scholar
Storkey, J, Neve, P (2018) What good is weed diversity? Weed Res 58:239243 CrossRefGoogle ScholarPubMed
Storkey, J, Westbury, DB (2007) Managing arable weeds for biodiversity. Pest Manage Sci 63:517523 CrossRefGoogle ScholarPubMed
Sturz, AV, Matheson, BG, Arsenault, W, Kimpinski, J, Christie, BR (2001) Weeds as a source of plant growth promoting rhizobacteria in agricultural soils. Can J Microbiol 47:10131024 CrossRefGoogle ScholarPubMed
Swinton, SM, Buhler, DD, Forcella, F, Gunsolus, JL, King, RP (1994). Estimation of crop yield loss due to interference by multiple weed species. Weed Science 42:103109 CrossRefGoogle Scholar
Tiwari, S, Sindel, BM, Smart, N, Coleman, MJ, Fyfe, C, Lawlor, C, Vo, B, Kristiansen, P (2022) Hand weeding tools in vegetable production systems: an agronomic, ergonomic and economic evaluation. Int J Agric Sustainability 20:659674 CrossRefGoogle Scholar
Turnbull, LA, Levine, JM, Loreau, M, Hector, A (2013) Coexistence, niches and biodiversity effects on ecosystem functioning. Ecol Lett 16:116127 CrossRefGoogle ScholarPubMed
Vatovec, C, Jordan, N, Huerd, S (2005) Responsiveness of certain agronomic weed species to arbuscular mycorrhizal fungi. Renew Agric Food Syst 20:181189 CrossRefGoogle Scholar
Vickery, J, Carter, N, Fuller, RJ (2002) The potential value of managed cereal field margins as foraging habitats for farmland birds in the UK. Agric Ecosyst Environ 89:4152 CrossRefGoogle Scholar
Vivaldo, G, Masi, E, Taiti, C, Caldarelli, G, Mancuso, S (2017) The network of plants volatile organic compounds. Sci Rep 7:11050 CrossRefGoogle Scholar
Wang, J, Yao, X, Nguyen, BK (2022) Identification and localisation of multiple weeds in grassland for removal operation. Pages 290–299 in Fourteenth International Conference on Digital Image Processing (ICDIP 2022), Wuhan, China: SPIECrossRefGoogle Scholar
Wilson, BJ, Wright, KJ (1990) Predicting the growth and competitive effects of annual weeds in wheat. Weed Res 30:201211 CrossRefGoogle Scholar
Yousfi, N, Saïdi, I, Slama, I, Abdelly, C (2015) Phenology, leaf gas exchange, growth and seed yield in Medicago polymorpha L. populations affected by water deficit and subsequent recovery. Flora: Morphol Distrib Funct Ecol Plants 214:5060 CrossRefGoogle Scholar
Zhang, W, Miao, Z, Li, N, He, C, Sun, T (2022) Review of current robotic approaches for precision weed management. Curr Robot Rep 3:139151 CrossRefGoogle ScholarPubMed
Zimdahl, RL (2004) Weed-crop competition: a review. 2nd ed. Iowa: Blackwell Publishing Professional. 220 pCrossRefGoogle Scholar
Figure 0

Figure 1. Schematic representation of the principal aims and ecological effects of two approaches proposed to increase the neutrality of weed communities. The first approach can be pursued by applying traditional management strategies (Adeux et al. 2019). The second approach may be facilitated by emerging technologies.

Figure 1

Figure 2. Using drones and weeder robots to promote neutral weed communities. (A) Weed community manipulation with (1) drones and (2) weeder robots capable of recognizing and removing specific weed species. (B) Crop coexistence with a neutral weed community. Modified from Esposito et al. (2021).