A herbicide resistance risk assessment for weeds in wheat and barley crops in New Zealand.

We estimated the risk of selecting for herbicide resistance in 101 weed species known to occur in wheat and barley crops on farms in New Zealand. A protocol was used that accounts for both the risk that different herbicides will select for resistance and each weed's propensity to develop herbicide resistance based on the number of cases worldwide. To provide context we documented current herbicide use patterns. Most weeds (55) were low-risk, 30 were medium-risk and 16 high-risk. The top ten scored weeds were Echinochloa crus-galli, Poa annua, Lolium multiflorum, Erigeron sumatrensis, Raphanus raphanistrum, Lolium perenne, Erigeron bonariensis, Avena fatua, Avena sterilis and Digitaria sanguinalis. Seven out of ten high-risk weeds were grasses. The most used herbicides were synthetic auxins, an enolpyruvylshikimate-phosphate synthase inhibitor, acetolactate synthase (ALS) inhibitors, carotenoid biosynthesis inhibitors, and long-chain fatty acid inhibitors. ALS-inhibitors were assessed as posing the greatest risk for more species than other modes-of-action. Despite pre-emergence herbicides being known to delay resistance, New Zealand farmers only applied flufenacet and terbuthlazine with high frequency. Based on our analysis, surveys for herbicide-resistant species should focus on the high-risk species we identified. Farmer extension efforts in New Zealand should address resistance evolution in cropping weeds.

Introduction

A worldwide analysis suggests that weeds have the highest potential to cause yield losses in major crops including wheat and barley where they account for potential losses of 23% [1,2]. In response to this threat to production, farmers have come to rely on a mix of cultural and chemical control methods. Herbicidal weed control is favoured as it is cost-effective providing a three or four-fold economic return [2] and is a key element in the implementation of conservation tillage systems (including direct drilling) which reduce soil erosion [3]. However, intensive herbicide use is known to select for resistant individuals in weed populations, eroding herbicide effectiveness as these weeds escape control [4-6]. Globally farmers are addressing similar suites of weed species in any given crop, and some appear to have a greater propensity to develop resistance, with repeated convergent evolution of resistance being documented in the International Survey of Herbicide Resistant Weeds [4] and the scientific literature generally [5,6]. Over the last 40 years a total of 14 species of herbicide resistant weeds have been documented in New Zealand, with 12 instances of resistance documented in arable crops including maize, peas, oats, wheat, and barley [7]. In any given year >50% of New Zealand arable production areas are under wheat (~45000 ha) and barley (~55000 ha) rotations [8]. Other crops that may commonly be included with wheat and barley rotations are; pasture, spring-sown peas, linseed, ryegrass, clover, and oilseed rape. Production levels are high, with farmers in New Zealand obtaining world record wheat and barley yields in 2017 and 2015, respectively [9,10].

An examination of weed science publications shows that our knowledge about herbicide resistance cases has developed mostly via unsystematic detection globally. It reflects the varying effort, scientific input, and methods of detection; definitely this is the case in New Zealand [7,11]. This makes sense since farmers and herbicide companies do not necessarily report resistance cases to scientists, and even if they do, not all cases are likely to get published. What’s more, ad-hoc reporting may reflect strong biases towards a small number of the most problematic weeds. With some notable exceptions, particularly in cropping systems in Australia [12-17], systematic surveys to detect herbicide resistance cases are rare, and often focus on one or two problematic species in a given crop, for example, Alopecurus myosuroides Huds. in French wheat fields [18] or Avena fatua L. in two Canadian townships [19]. Systematic surveys may be rare because of the cost, a lack of specific pathways for reporting [11], and industry perceptions about the importance of resistance. Surveyors should ideally be open to the discovery of completely novel cases while also being aware of those that are most at risk of developing resistance.

Here we adapt a recently published risk assessment protocol [20] to identify those weeds most at risk of developing resistance in New Zealand, given their occurrence in wheat and barley fields, and their prior record of resistance in wheat and barley fields elsewhere in the world. This Moss et al. protocol [20] (henceforth the “Moss protocol”) set out to assess resistance risk as part of a pesticide authorization process in Europe, based on a European Plant Protection Organization (EPPO) protocol, originally developed in 1999 [21]. They present a quantitative risk matrix using both herbicide-risk (some herbicides pose a higher risk than others) and species-risk (some weed species are more resistance-prone than others), with an optional score modifier designed to account for agronomic management practices that may reduce the risk. We took advantage of a unique data set about herbicide use in wheat and barley fields in New Zealand to place our risk assessment into context, and construct a framework for herbicide resistance surveys and extension efforts in the New Zealand cropping industry. This risk assessment is on an industry-wide scale informed by anonymized herbicide application data from wheat and barley fields. Risks were not assessed at the scale of individual farms and fields, this requires detailed information about herbicide timing, mixtures and rotations, and their interactions with weed biology, crop rotations and other cultural practices. All the high-risk weeds identified here should be targeted in surveys designed to detect herbicide-resistant weeds.

Materials and methods

Weed list

We generated a list of potential target weeds from wheat and barley crops in New Zealand. This was primarily sourced from the Bourdôt et al. 1998 weed survey in New Zealand (Canterbury region) wheat and barley fields [22]. The Canterbury and northern Otago regions contain more than 75% of all the wheat and barley grown in New Zealand [8]. We expanded the weed species list to include species known to occur in wheat and barley fields in the wider New Zealand context. Grasses and some broadleaf genera were not identified to species by Bourdôt et al. [22], hence we took steps to address this gap and other omissions by using other literature [23,24], expert knowledge and field observations made in January (late summer) of 2019 and 2020. Species nomenclature follows the New Zealand Flora and taxonomic authorities are listed in S1 Table. [25]. Subspecies were not distinguished, and taxa were considered by us only at the species level (e.g. Avena sterilis subsp. ludoviciana (Durieu) M.Gillet & Magne was treated as Avena sterilis L.).

Ranking herbicide groups by resistance cases

We ranked Herbicide Resistance Action Committee (HRAC) legacy herbicide mode of action (MoA) groups by the number of resistance cases documented by the International Survey of Herbicide Resistant Weeds [4] to obtain an estimate of what Moss et al. called the “inherent risk” of the herbicide [20]. The Moss protocol [20] considers the inherent risk to relate to the total number of cases of resistance reported in the International Survey of Herbicide Resistant Weeds [4] for each legacy HRAC MoA [26], with risk scores of 1, 2 or 3 given for low, medium or high risk respectively. We set the threshold for high-risk at >9% of recorded cases, which captures the original high-risk categories identified in the Moss protocol, but now places group G (glyphosate) in the high category. Moss et al. used the 10% threshold for high-risk herbicides. With group A having 48 cases and group G herbicides having 47 cases we chose to place the two groups in the same risk category, with such a small difference in the numbers of cases worldwide we believe they are indistinguishable from the data. The alternative is to use the same threshold as in the Moss protocol, but this would result in group A and G being medium risk, which fails to capture the high-risk status of group A herbicides. There are different ways we can reasonably set risk thresholds, which will be discussed later. Remaining ranking thresholds were not changed: medium risk 5–9%, low risk 1–5% and very low risk <1%. Low-risk and very low risk are both scored as ‘1’.

Herbicide use

The most recent (2017–2018) data on herbicide usage trends in New Zealand were sourced from the ProductionWise® [27] platform and aggregated by active ingredient. This consisted of data entered by farmers about herbicide use in 5026 barley and 7647 wheat fields. Approximately 900 arable farmers have registered to use the platform, but anonymization was complete, with no unique identifiers for farms or fields. Farmers recorded every spray event (by herbicide product) in their fields. For example, an individual active ingredient used three times in a field is recorded three times. Products with multiple active ingredients were recorded as independent applications. Counts of herbicide use in fields were summarized by active ingredient and legacy HRAC [26] herbicide mode-of-action, from product label information. Relative rates of use by mode-of-action were quantified and characterized as very high (>20% of all application instances), high (>10%), moderate (>1%), low (~1%), extremely low (<1%) and nonexistent (0%).

Cases of resistance by taxon and risk scoring

We assume that the best way to predict resistance in a weed species to any given herbicide (by HRAC group) is proportional to the number of documented cases of herbicide resistance in the same taxon, given the use of the same herbicide type in New Zealand. To calculate Moss’s “inherent” species-risk scores we used the global number of resistance cases from the International Survey of Herbicide Resistant Weeds [4]. Cases are defined by the International Survey of Herbicide Resistant Weeds as unique combinations of weed species and HRAC herbicide mode-of-action (species x site of action). To obtain the ‘high’, ‘medium’ and ‘low’ risk scores as used in the Moss protocol [20], we designated ≥10 cases as high risk (score = 3), < 10 as moderate (score = 2) and no cases recorded as low risk (score = 1). We assessed overall species-risk as the sum of the herbicide-risk multiplied by the “inherent” species-risk [20] combined for all relevant HRAC MoA herbicide groups, but only, but only where species had cases of resistance documented somewhere in the world. We include all cases of resistance for each weed species, rather than restricting our focus to cases from wheat and barley, because we are interested in a species propensity to develop resistance to a herbicide group. For example, the high-risk species Chenopodium album L. has more than 10 documented cases of resistance giving it a species score of 3. Then we consider the herbicide-risk scores for those herbicides where Chenopodium album has evolved resistance somewhere in the world. There were cases in two high-risk herbicide groups B and C1 (each with a herbicide score of 3), and one medium-risk group O (herbicide score of 2). The species and herbicide scores are multiplied and summed (3×3) + (3×3) + (3×2) = 24. We distinguished cases that were in herbicide groups highly-used (or not) by wheat and barley farmers in New Zealand.

The summed (cumulative) scoring method described above is not used in the European Moss protocol because its purpose was to regulate herbicide product use [20]. In contrast, we wanted to determine the risk that different herbicides will select for resistance in weed species known to occur in New Zealand’s wheat and barley fields. Ultimately we hope to inform sector stakeholders about risk, and to improve herbicide resistance detection. We adapted their protocol to score species-risk in an industry-wide assessment. Unlike Moss et al. [20] we used an explicit threshold (though arbitrary) to determine species-risk scores based on the number of cases of resistance worldwide, but we think this approach produces credible risk estimates in the light of current knowledge. We examined 101 species and ended up with 46 ‘high’ and ‘medium’ resistance risk species, many more than Moss et al (they scored an example list of only 13 high and medium risk taxa). The Moss protocol also used score modifiers that take into account resistance management practices including the use of non-chemical control measures. We did not use the score modifiers since these vary from field to field and our objective was slightly different. We acknowledge that actual risk of resistance development is determined mostly by the frequency and type of herbicide applied (selection pressure) interacting with characteristics of weed biology, distribution and abundance [5]. All graphs were created in R using the ggplot2 package [28,29].

Results

Our weed list contained 69 species from the original Bourdôt et al. article [22]. An additional 32 species were added based on field observation, expert opinion and relevant literature [23,24], resulting in a total of 101 weed species for consideration. Digitaria sanguinalis, Echinochloa crus-galli, Erigeron spp. and Raphanus raphanistrum are notable emerging weeds, so they were included. Some taxa noted by Bourdôt were resolved to species, such as Trifolium spp., which became Trifolium repens and Trifolium pratense. A full list of weed species that we considered for New Zealand wheat and barley crops is displayed with taxonomic authorities in S1 Table.

Herbicide mode-of-action risk rankings are displayed (Table 1), arranged from high risk to very low risk. This resembles the table of Moss et al., [20] with a notable exception in that group G is raised to high risk. We designated HRAC groups B, C1, A, G as high-risk (>9% of recorded cases), O, D, C2 as moderate (5–9%), E, K1, K3, N F, Z as low (1–5%) and C3, F1, H, L as very low risk (<1%).

Table 1

Herbicide mode-of-action groups ranked by resistance risk.

The number of cases of resistance from the International Survey of Herbicide Resistant Weeds [4] ranked and grouped by the legacy HRAC mode-of-action (data accessed in January 2020).

Resistance Risk	HRAC Herbicide MoA Groups		Example active ingredient	Number of resistant species worldwide	% of the worldwide total
High	B	ALS inhibitor	flumetsulam	165	32
	C1	PSII inhibitors (triazines)	atrazine	74	15
	A	ACCase inhibitors	pinoxaden	48	9
	G	EPSP synthase inhibitors	glyphosate	47	9
Medium	O	Synthetic auxin	MCPA	41	8
	D	PSI electron diverters	paraquat	32	6
	C2	PSII inhibitors (ureas and amides)	isoproturon	29	6
Low	E	PPO inhibitors	carfentrazone	13	3
	K1	Microtubule inhibitors	trifluralin	12	2
	N	Lipid inhibitors	triallate	10	2
	K3	Long-chain fatty acid inhibitors	flufenacet	7	1
	F3	Carotenoid biosynthesis (unknown target)	amitrole	6	1
	Z*	Anti-microtubule mitotic disrupter	flamprop	6	1
Very-low	C3	PSII inhibitors (nitriles)	ioxynil	4	<1
	F1	Carotenoid biosynthesis inhibitors	diflufenican	4	<1
	H	Glutamine synthase inhibitors	glufosinate	4	<1
	L	Cellulose inhibitors	dichlobenil	3	<1
	†	Other MoA	-	6	1

*Z includes subcategories Z1, Z2, Z3, Z4.

†Other includes mode-of-actions with 2 or fewer cases: F2, F4, K2, I.

Current herbicide use in New Zealand wheat and barley fields involves 75 unique active ingredients in 16 mode-of-action groups (we show the 11 most important herbicide groups in Table 2). Barley and wheat have shared patterns of herbicide usage with respect to mode-of-action (Table 2) and active-ingredients. Synthetic auxins (HRAC group O) were represented in higher proportions than any other class of herbicide (a total usage rate of 26%). ALS-inhibitors (B), PDS-inhibitors (F1) and EPSPS-inhibitors (G) were highly used herbicide groups with >10% total usage, and acetyl coenzyme-A carboxylase inhibitors (A) and photosystem-II disrupters (C) were moderately used (total <10%). EPSPS-inhibitors (G) were used in larger proportions in barley (18%) compared to wheat (12%); conversely, farmers used K3 herbicides significantly more in wheat at 12% compared to barley at 4%. Glyphosate (MoA group G) is mostly used (>95%) used to control weeds pre-sowing of the cereal crops, for termination of the previous crop or pre-establishment weed control. It is very rarely used as crop pre-harvest desiccant. The following 10 HRAC MoA groups each accounted for less than 1% of herbicide applications, N, F4, K1, I, H, F3, Z, L, F2 & K2.

Table 2

Ranked herbicide mode-of-action usage proportions.

The percentage of fields that received herbicide applications, grouped by HRAC MoA categories (data are sourced from ProductionWise®, 2017–2018).

Mode-of-action	Barley %	Wheat %	Total %
O	30	24	26
B	16	17	16
F1	14	17	16
G	18	12	14
K3	4	12	9
A	8	6	7
C1	3	5	4
C2	1	4	3
C3	2	1	1
E	2	<1	1
D	1	1	1

Individual herbicide usage ranking for each crop is displayed in Fig 1, ranked by the wheat herbicide use. The ten most used herbicides (in order) for barley were: glyphosate (HRAC group G), diflufenican (F1), fluroxypyr (O), MCPA (O), chlorsulfuron (B), pinoxaden (A), iodosulfuron (B), flufenacet (K3), mecoprop (O) and clopyralid (O). Flufenacet and terbuthylazine were the only high-use pre-emergent active-ingredient used in wheat (the latter can also be used post-emergent), both were used less in barley crops.

Fig 1

The ten most common herbicides applied in New Zealand wheat and barley fields.

The ten most used herbicides as a percentage of total application instances documented by farmers in New Zealand wheat and barley fields, here ordered by observations in wheat crops. The herbicides that were not ranked in the top ten for each crop respectively were included here for both of the crops for completeness.

Cases of resistance by species and risk scoring

The documented cases of herbicide-resistance for medium and high-risk species and all herbicide mode-of-action combinations are shown in Table 3 (a total of 46 medium and high-risk species). High-risk species were the eight grasses Avena fatua, Avena sterilis, Digitaria sanguinalis, Echinochloa crus-galli, Lolium multiflorum, Lolium perenne, Phalaris minor, Poa annua and eight broadleaf weeds Amaranthus powellii, Chenopodium album, Erigeron bonariensis, Erigeron sumatrensis, Raphanus raphanistrum, Senecio vulgaris, Solanum nigrum, Stellaria media. Considering our list of weed species known in wheat and barley in New Zealand, we can see that the number of weed species with herbicide resistance documented worldwide varies across HRAC herbicide groups B (34 species), C1 (21), G (16), O (13) and A (12) (Table 3). Poa annua, Echinochloa crus-galli, Lolium spp., Erigeron sumatrensis, Raphanus raphanistrum and Avena fatua have twenty or more recorded cases that occur in five or more unique mode-of-action groups each. We report the low risk weeds, not included in Table 3: Achillea millefolium, Agrostis capillaris, Amaranthus deflexus, Amsinckia calycina, Aphanes arvensis, Arrhenatherum elatius, Avena barbata, Barbarea intermedia, Brassica napus, Bromus hordeaceus, Calandrinia compressa, Calandrinia menziesii, Cardamine flexuosa, Cerastium glomeratum, Chenopodiastrum murale, Cirsium vulgare, Crepis capillaris, Crepis setosa, Dactylis glomerata, Elytrigia repens, Erodium cicutarium, Erodium moschatum, Festuca rubra, Fumaria bastardii, Fumaria muralis, Fumaria officinalis, Gamochaeta coarctata, Gamochaeta purpurea, Geranium molle, Leontodon saxatilis, Lepidium didymum, Lotus pedunculatus, Lysimachia arvensis, Malva neglecta, Malva parviflora, Matricaria discoidea, Oxalis debilis, Oxalis latifolia, Phalaris aquatica, Phalaris canariensis, Ranunculus repens, Sherardia arvensis, Silene vulgaris, Sisymbrium officinale, Solanum sarrachoides, Stachys arvensis, Taraxacum officinale, Trifolium pratense, Trifolium repens, Veronica arvensis, Veronica persica, Vicia hirsuta, Vicia lathyroides, Viola arvensis and Vulpia myuros. These weed species are low-risk because they had no reported instances of herbicide-resistance anywhere in the world [4].

Table 3

Herbicide resistance risk scores and cases for herbicide mode-of-action groups and species.

For weeds of wheat and barley in New Zealand we document the number of worldwide cases of herbicide resistance within different HRAC [26] groups. Data are sourced from the International Survey of Herbicide-Resistant Weeds [4] and concerns unique modes-of-action within reported cases of herbicide resistance. Species-risk and herbicide-risk are either low (1), medium (2), or high (3). Total cases and species per herbicide mode-of-action across worldwide cases [4] are presented at the bottom of the table.

Species	Species Risk	A	B	C1	C2	C3	D	E	F1	F2	F3	F4	G	H	L	K3	K1	N	O	Z	Groups	Total Unique Cases
Herbicide Risk		3	3	3	2	1	2	1	1	1	1	1	3	1	1	1	1	1	2	1
Amaranthus powelii	3	0	8	8	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	16
Avena fatua*	3	38	19	0	0	0	0	1	0	0	0	0	0	0	0	1	1	9	0	8	7	77
Avena sterilis	3	15	9	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	2	4	28
Brassica rapa	2	0	1	1	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	4	5
Bromus catharticus	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1
Bromus diandrus	2	1	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	3
Bromus secalinus	2	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2
Bromus sterilis	2	1	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	3
Capsella bursa-pastoris	2	0	6	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	8
Carduus nutans†	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	1
Chenopodium album†	3	0	7	41	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	3	49
Cirsium arvense	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	1	2
Critesion murinum	2	3	1	0	0	0	4	0	0	0	0	0	1	0	0	0	0	0	0	0	4	9
Convolvulus arvensis	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Digitaria sanguinalis	3	7	3	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	13
Echinochloa crus-galli	3	14	16	6	11	0	0	0	0	0	0	1	1	0	2	3	0	2	7	0	10	63
Erigeron bonariensis	3	0	1	2	0	0	6	0	0	0	0	0	13	0	0	0	0	0	0	0	4	22
Erigeron sumatrensis	3	0	7	1	0	0	9	0	0	0	0	0	10	0	0	0	0	0	1	0	5	28
Fallopia convolvulus	2	0	2	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	4
Fumaria densiflora	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	2	2
Galium aparine	2	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	2	7
Lactuca serriola	2	0	5	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	3	7
Lamium amplexicaule	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Lolium multiflorum*	3	55	37	0	0	0	2	0	0	0	1	0	27	3	0	5	0	0	0	0	7	130
Lolium perenne*	3	4	5	0	0	0	0	0	0	0	1	0	4	1	0	0	0	0	0	0	5	15
Persicaria maculosa†	2	0	1	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	5
Phalaris minor	3	9	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	13
Phalaris paradoxa	2	7	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	9
Plantago lanceolata	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	2	2
Poa annua†	3	3	10	19	0	0	2	0	0	0	1	0	7	0	0	0	7	1	4	0	9	54
Polygonum aviculare	2	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	2
Raphanus raphanistrum	3	0	9	1	0	0	0	0	3	0	0	0	1	0	0	0	0	0	6	0	5	20
Rumex acetosella	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Rumex obtusifolius	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Senecio vulgaris	3	0	2	13	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	16
Silene gallica	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Solanum americanum†	2	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2
Solanum nigrum†	3	0	0	11	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	2	14
Sonchus asper	2	0	5	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	6
Sonchus oleraceus	2	0	3	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	2	0	3	6
Spergula arvensis	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Stellaria media†	3	0	20	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	3	23
Tripleurospermum inodorum	2	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	7
Urtica urens	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Vicia sativa	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1
Vulpia bromoides	2	0	0	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	3
Total cases count		157	203	122	11	1	30	1	3	0	4	1	74	4	2	9	9	12	32	10		683
Total species count		12	34	21	1	1	9	1	1	0	4	1	16	2	1	3	3	3	13	2		127

*Species with herbicide resistance cases detected in New Zealand wheat and barley crops.

†Species with herbicide resistance cases detected in New Zealand, in other crops.

The cumulative risk scores shown in Fig 2 gives a higher score to weeds with resistance to multiple modes-of-action. Because of this, species with high overall risk scores may have relatively few cases of resistance detected overall but their score is inflated by cases of resistance to multiple HRAC modes-of-action. For example Lolium perenne (15 cases in 5 modes-of-action) has a slightly lower risk score overall compared to its congener Lolium multiflorum (130 cases in 7 modes-of-action). Chenopodium album is an example of a relatively low scoring weed that has had 49 cases of resistance documented but within only three HRAC modes-of-action (Fig 2 and Table 3). Risks can be skewed toward certain herbicide modes-of-action, or species. Weeds with the ten highest cumulative scores are Echinochloa crus-galli, Poa annua, Lolium multiflorum, Erigeron sumatrensis, Raphanus raphanistrum, Lolium perenne, Erigeron bonariensis, Avena fatua, Avena sterilis, Digitaria sanguinalis. This shows that 7 out of 10 of the high risk species are grass-weeds. Grass-weeds are over-represented in global cases of resistance.

Fig 2

Number of cases of herbicide resistance (globally) by weed species and cumulative herbicide resistance risk scores.

The Sum of Risk (cumulative risk) scores on the x-axis is the sum of the herbicide-risk × species-risk scores (from Table 3) for each HRAC herbicide mode-of-action group that had documented cases of resistance somewhere in the world. The green dashed line shows the 10 cases needed for a species to be designated high risk (score 3). We distinguished the proportion of the risk and resistance cases that matched with the high-use HRAC mode-of-action groups (A, B, C1, F1, G, K3 & O) used by wheat and barley farmers in New Zealand (light-green for risk, and grey for cases).

Discussion

We present evidence about the propensity of individual weed species to develop resistance in a curated list (S1 Table) of weed species known to occur in New Zealand wheat and barley fields [22]. The ten highest cumulative risk scores, in order Echinochloa crus-galli, Poa annua, Lolium multiflorum, Erigeron sumatrensis, Raphanus raphanistrum, Lolium perenne, Erigeron bonariensis, Avena fatua, Avena sterilis and Digitaria sanguinalis. Because some weeds with moderate-to-high risk scores are widespread, they may be more likely to develop resistance: Erigeron spp., Raphanus raphanistrum, Chenopodium album, Senecio vulgaris, Phalaris spp., Bromus diandrus, Sonchus oleraceus, Solanum nigrum and Persicaria maculosa. Species to species differences in distribution, abundance and phenology (e.g. germination timing) will mean that our risk scores do not capture field level differences in selection pressure from farmer herbicide applications in wheat in barley. As such, emerging grass weeds Echinochloa crus-galli and Digitaria sanguinalis are identified as high-risk despite their currently limited distribution. By being aware of all the weed species that are high-risk we should improve detection of resistance cases in future.

A review of the New Zealand literature shows only two reports of resistant species in wheat and barley [7,11]. This contrasts with the high numbers of resistance cases seen worldwide for these crops (77 cases in wheat, and 30 in barley) [4]. One might expect cases to be reported quickly, given that selection for rare mutations that confer resistance is infrequent but instantaneous. But surviving individuals and progeny may take a few years to increase to detectable levels (in a field) under continuous selection pressure [30]. In 2014 Avena fatua survivors in wheat and barley fields were shown to be resistant to acetyl coenzyme-A carboxylase (group A, ACCase) [31], and in 2017 ryegrasses (Lolium perenne and L. multiflorum) in wheat fields were resistant to ACCase and acetolactate synthase targeting herbicides (ALS herbicide, group B) [31,32]. A 1996 report of Stellaria media resistance to chlorsulfuron and tribenuron (group B) in an oat crop may indicate elevated risk given the shared agronomic practices between these cereal crops [33]. The resistant weeds previously detected in New Zealand cereals Lolium spp., and Avena spp. and Stellaria media, are therefore likely to continue to be observed. It seems likely that farmers are under-reporting resistance cases perhaps because alternative weed control measures can keep problems manageable. In the absence of a systematic approach, little is known about the spatial and temporal patterns of herbicide resistance development in New Zealand.

Estimating the overall prevalence of herbicide resistance in all the major farming sectors in New Zealand could cost $1–3 million NZD depending on sampling rates [11]. An obvious concern is that detection rates for herbicide-resistant weeds will necessarily underestimate the true rate, given that surveyors may miss individual weed species, resistant plants, or seeds during farm visits [11], also they could miss cases by screening for the wrong herbicides. Surveys have been initiated for the arable sector in New Zealand’s Canterbury region where wheat and barley are important crops. They will sample about 20% of ca. 800 arable farms at an estimated cost of ca. $154,000. Given these high survey costs, it is important to take steps to improve detection rates, the high-risk species identified here should be targeted during surveys. Without this list we could be biased toward a smaller number of known problem weeds, such as Lolium spp. and Avena fatua.

The Moss protocol relies heavily on a herbicide-risk score (rank low, medium and high). We deviated from their approach slightly. This was necessary in part because the number of cases for different herbicide groups has increased since the Moss article was published. A case in point is our decision to include glyphosate as a high-risk herbicide. As recently as 2006 glyphosate was ranked as amongst the least likely to select for resistance [34], and is recognized as medium-risk by Moss. We ranked glyphosate (group G; Table 1) as high risk because worldwide the number of species showing resistance has increased to 47 cases, similar to group A (48 cases) which is universally regarded as high-risk. Group A herbicides were ranked as high-risk in the Moss protocol. Two cases of glyphosate resistance are known from New Zealand [7,11]. If we had used the 10% threshold groups, A and G would be medium risk and species scores would have changed, but the top five ranked species would have remained the same. We are aware that herbicide-risk is not just a function of the number associated cases of resistance. More complete risk assessments would ideally factor in the herbicide volumes used, years of product use, spatial extent and number of the applications, as well as the abundance of high-risk weeds in the areas treated.

Herbicide usage data in New Zealand have rarely been quantified, and only roughly via indirect sales data numbers and expert elicitation [35,36]. The ProductionWise® system is used to record the on-farm use of chemical inputs and other information. This system (and similar tools) are valuable for ensuring farmer compliance with record-keeping regulations, supporting farmer decision-making, and guiding herbicide resistance prevention efforts. It also serves to capture industry-wide behaviour regarding agrichemical use which is how we have used it in this case. Herbicide resistance risk is influenced by the other crops in the rotation, and temporal and spatial differences in weed composition. The relatively low rates of herbicide resistance detected in the New Zealand arable sector may be a consequence of mixed-crop rotation systems. It is not uncommon to include a 1–3 year pasture rotation, and a complex crop sequence, for example, winter wheat, spring-sown peas or linseed, winter wheat or barley, followed by ryegrass, and oilseed rape and back to winter wheat [37]. Cases of herbicide resistance we observe now only partly reflect current herbicide use and may, in fact, implicate historic selection by herbicides that have fallen out of favour. We think advanced record-keeping tools like ProductionWise® and related decision support systems have real potential to improve outcomes for farmers and scientists.

Within New Zealand wheat and barley fields herbicide use and risk of resistance are greatest within HRAC groups (in order) O, B, G, A and C1. Surprisingly, there have been few cases of resistance to ALS-inhibitors (B) and synthetic auxins (O) documented to date given that they have been the most commonly applied herbicides for more than 20 years [38,39]. Field observations show that broadleaf weeds are rarer in the wheat fields prior to harvest compared to grass weeds, but survivors should be tested for herbicide resistance. Group B herbicides have been implicated in a large number of resistance cases in both broadleaf and grass weeds, including 34 species known to occur in wheat and barley in NZ (Table 3). Groups F1 and K3 have a relatively low risk of developing resistance based on historical occurrences even though they are highly used in New Zealand.

Examining our herbicide use information in the context of published herbicide evolution models can provide important insights. Models based on dryland wheat systems and the weed Lolium rigidum [40] showed that resistance rate evolution was not slowed by simple herbicide rotations (i.e. annual with few herbicides). Importantly the use of soil-applied herbicides, particularly trifluralin (group K1), full-rate mixes of herbicides, and complex 8-year long rotations were shown to delay resistance evolution by years, and in some scenarios by decades [40]. There is a chance that resistance cases in soil-applied pre-emergent herbicides are under-reported compared to post-emergent ones (they are harder to test). For now, resistance evolution in those herbicides appears to be slower. Trifluralin did not feature amongst the most common herbicides in the farmer herbicide use data we obtained for 2017 and 2018 (<0.5% of field applications); the only frequently used pre-emergent herbicides were flufenacet and terbuthylazine. Farmers should be informed about the high-risk species and herbicide combinations, so as to avoid high-risk behaviors, or at least keep an eye out for problems they will select for. Farmer decision support platforms and research and extension efforts in New Zealand should emphasize mechanical and cultural control measures, the use of soil-applied pre-emergent herbicides, full-strength label-rate herbicide mixtures, crop rotation to utilize herbicides otherwise unavailable and herbicide rotations of key active ingredients to achieve maximum control and to reduce the rate at which herbicide resistance evolves in weed populations.

Conclusions

A European protocol [20], designed primarily to assist in herbicide authorization procedures, was adapted to assess the risk of herbicide resistance evolving in 101 different weed species known to occur in New Zealand wheat and barley crops. More than half the weeds weeds (55) we assessed were low-risk, 30 were medium-risk and 16 high-risk. The 10 species posing the highest resistance risk were: Echinochloa crus-galli, Poa annua, Lolium multiflorum, Erigeron sumatrensis, Raphanus raphanistrum, Lolium perenne, Erigeron bonariensis, Avena fatua, Avena sterilis and Digitaria sanguinalis. To provide important context we also report on herbicide use patterns in New Zealand wheat and barley fields. We are planning extensive surveys in New Zealand to detect new cases of herbicide resistance. The risk assessment outlined in this paper will enable us to prioritise those weeds identified as posing a high resistance risk and, consequently, make better use of available resources. The risk assessment procedure as described in this paper has the potential to be a useful tool for evaluating the risk of herbicide resistance in a wide range of different weed species in other countries too.

The full list of weed species considered in our risk assessment for herbicide resistance in New Zealand Wheat and Barley crops.

The list is derived from Bourdôt et al. [22], with additions from literature [23,24], expert knowledge and field observations made in January (late summer) of 2019 and 2020. Common name (in New Zealand) and family name are indicated. Nomenclature follows the New Zealand Flora [25].

(DOCX)

Click here for additional data file.

5 May 2020

PONE-D-20-09801

A herbicide resistance risk assessment for weeds in wheat and barley crops in New Zealand

PLOS ONE

Dear Dr Buddenhagen ,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Jun 19 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Ahmet Uludag, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments:

This is a good paper. You will see three reviewer's suggestions. Please prepare a document for me how did you proceed for every suggestion. It can help publishing faster. Good luck.

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following in the Financial Disclosure section:"All the authors worked under the Ministry of Business, Innovation and Employment [grant number C10X1806] to AgResearch Ltd.  https://www.mbie.govt.nz/science-and-technology/science-and-innovation/funding-information-and-opportunities/investment-funds/endeavour-fund/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

Thank you for stating the following in the Competing Interests section:"The authors have declared that no competing interests exist."

We note that one or more of the authors are employed by a commercial company:"AgResearch Ltd"

1.Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

Please also include the following statement within your amended Funding Statement.

“The funder provided support in the form of salaries for authors [insert relevant initials], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”

If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.

2. Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc.

Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and  there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include both an updated Funding Statement and Competing Interests Statement in your cover letter. We will change the online submission form on your behalf.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: N/A

Reviewer #3: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Because frequency and abundance of weed species in the region have not been used in the scoring, the paper provides a picture of risks due to the current use of herbicides in the region, which is informative for the farmer about the intrinsic risk of an abundant species in its own farm. However, although I agree with intrinsic high risk species as stated on line 280-285, it is pity that the overall risk for the region is not presented.

50-54: There is also an important survey on blackgrass in UK (see Hicks et al Nature Ecology & Evolution 2(3) 2018, DOI: 10.1038/s41559-018-0470-1). Probably other reports are available on surveys developed by national weed research associations in Spain, France (Columa), Italy, etc., including companies, extension service and farmers, and published in local conferences.

142: It can be assumed that weed biology is already included in the inherent species score, but abundance is a key parameter. Abundance includes effects of farming systems: if many individuals still remain in the field, then the risk of developing resistance is higher than if the population is small. A score modifier to account for variation of abundance (e.g. 1 for low density and 3 for more than a million plant/ha, or another scale) could be used. Another factor is the species frequency in the studied region, which doesn’t seem to be taken into account (is the Production Wise platform collecting main troublesome weed species?).

Fig 2: Rather the low and high use HRAC groups I expected to see also the number of cases in New Zealand. I’m not clear with the low versus high use HRAC groups.

Reviewer #2: These comments are exactly the same as in attached file which is in a more convenient format to read and possibly to respond to.

PONE-D-20-09801

A herbicide resistance risk assessment for weeds in

wheat and barley crops in New Zealand

Ngow et al

Line No (as in downloaded pdf).

Abstract: Generally fine but as likely to be most-read part I suggest a few minor changes. Do you need to say ‘wheat and barley’ or would ‘cereal’ suffice? Ditto in title.

I suggest:

15-18 ‘We estimated the risk of selecting for herbicide resistance in 100 weed species known to occur in wheat and barley crops on farms in New Zealand. A protocol was used that accounts for both the risk that different herbicides will select for resistance and each weed’s propensity to develop herbicide resistance based on the number of cases worldwide.’

24 ‘ALS-inhibitors were assessed as posing the greatest risk for more species than any other mode-of-action.

25 I prefer ‘Pre-emergence’ but that may depend on journal style.

26 ‘……. in this class commonly used by…..’ Is this better than ‘favoured’?

Somewhere I think it would be worth stressing in abstract that 7 out of the high-risk 10 are grass-weeds. If space is limiting, I think the last sentence of abstract could go or ‘farmer extension efforts’ incorporated into previous sentence.

Introduction: Good – acceptably concise and relevant. I suggest including some brief (one or two sentences) information on arable cropping in NZ and what proportion of that is accounted for by wheat and barley. Or at least to show that wheat and barley comprise a significant proportion of arable crops – you might even wish to mention that NZ currently holds world record for both barley and wheat yield/ha (I think that is correct). I would!

32 Suggest: ‘……potential losses….’ Losses of 23% don’t actually commonly occur.

41 Clarify ‘cases’. To non-specialist reader it is vague and could mean number of fields or farms – although ‘specialists’ know why that term is appropriate. I would suggest stating number of weed species instead which is 13 according to Heap website country info. That lists 19 ‘cases’ (29 April) although that duplicates some species. If it is 25 cases now (according to your reference), perhaps someone in NZ should provide Ian Heap with updated info. This is important if this paper is published. Likewise amend ‘12’ in line 42 if appropriate.

45 ‘haphazard’ is a bit unfair, although this is a valid point. I would dispute that my sampling and testing over 30 years has been ‘haphazard’! Suggest ‘unsystematic’ as a better word – I would agree with that. End sentence after ‘globally’. Then ‘It reflects…..’

50 comma needed after [9-14]. These 6 refs are all valid, but do you need them all?

53-54 Good points – one issue is that if resistance is perceived to be rare then hard to justify cost. If very widespread then why bother to do a survey? Money could be better spent. Also lack of infrastructure and personnel to conduct surveys may be as important as cost. Also, do surveys have much long-term value? Is a 20-year old survey of much value now – perhaps only as a benchmark? Perhaps money better spent on more ‘durable’ studies? Not saying that you need to consider these aspects here – perhaps in discussion as risk assessment relevant to survey priorities.

59 Suggest: ‘…….and their prior record of resistance in cereal fields elsewhere in the world.’

62-64 This is fine and a good succinct sentence, but I wonder if it is worth emphasising more that risk assessment includes not only herbicide risk but also weed species risk for non-specialist readers, as this is not particularly intuitive? So, could read: ‘They present a quantitative risk matrix using both herbicide-risk (some herbicides pose a higher risk than others) and species-risk (some weed species are more resistance-prone than others), with an optional score modifier designed to account for agronomic management practices that may reduce the risk.’

67 Change: ‘Individual field and farm scale risk is not assessed as this requires detailed information on past herbicide use, including timing etc…..’ (This covers what has been applied - surely most important factor?)

Materials and methods: Good – makes it clear what was done and why slightly different approaches to published protocol were adopted

76 Suggest: ‘Most grasses and some …..’ The wonders of Google mean that I can see, within 60 seconds, that two grass weed species were identified at species level in the paper cited…..

83 Suggest: ‘….legacy herbicide mode of action (MoA) groups……’

88-89 Suggest: ‘….legacy HRAC MoA group [24], with risk scores of 1, 2 or 3 given for low, medium or high risk respectively.’

96 Suggest: ‘…..scored as ‘1’.’ (‘One’ is a bit ambiguous).

98 Suggest: ‘Most recent….’

108-109 This is slightly confusing: ‘The most used herbicides for each crop were characterized by weighting active ingredient amounts and the number of fields they were applied to.’ It almost implies total a.i. weight was used. Not sure this sentence is needed.

110 Why taxon? Species better?

112 Suggest: ‘…..HRAC MoA group…...’ And I suggest elsewhere throughout paper.

113 Suggest: ‘….herbicide type….

114 Suggest: ‘……the global number of resistance cases….’

115 Suggest: ‘To obtain the ‘high’, ‘medium’ and ‘low’ risk scores as used in the Moss protocol [17],…..’

117-118 This sentence is slightly confusing and maybe could be improved. Is this correct? ‘We assessed overall species-risk as the sum of the herbicide-risk multiplied by the “inherent” species-risk [17] combined for all relevant HRAC MoA herbicide groups, but only…….’ (I think ‘once’ is confusing). The example you give below is useful.

120 Suggest: ’……weed species….’

135 Suggest: ‘……to determine species-risk scores based on the number of cases of resistance worldwide, but we think this……’

137 Suggest: ‘ ….45 ‘high’ and ‘medium’ resistance risk species, many more than Moss et al……….’

139 Suggest: ‘The Moss protocol also used score modifiers that take into account resistance management practices including the use of non-chemical control measures’ .

139-142 Suggest: ‘We did not use the score modifiers since these vary from field to field and our objective was slightly different. We acknowledge that actual risk of resistance development is determined mostly by the frequency and type of herbicide applied (selection pressure) interacting with characteristics of weed biology, distribution and abundance [5].’

Results: Generally good and concise. One key paragraph needs improvement to improve clarity

145 Suggest: ‘An additional 31 species were added…..’

147 Suggest: ‘ ….resulting in a total of 100 weed species for consideration.’

155 Suggest: Suggest: ‘This resembles the table of Moss et al., [17] with…’

Table 1 Use of ‘taxa’ is odd. Why not ‘species’ which is what is used on Heap’s website? Taxa is a rather more general term and I cannot see any justification for use here. Would it also be useful to make the herbicide example the most commonly used ai for the group in NZ? Or if this has been done, state in title.

171-172 Clarify if glyphosate used in-crop (for desiccation) or pre-sowing or both. Presumably both, but some comment about balance of use would be useful if only to stress that glyphosate use is very different to selective herbicides – non-specialists might assume use is primarily in GM crops, as in some other countries. Either here or earlier in M&M.

Suggest: ‘ …….in barley (18%) compared with wheat (12%); conversely, farmers………’

174 Again, ‘HRAC MoA categories’

Table 2 Suggest last 10 categories are simply summarised to save space and some statement added within table. e.g. ‘The following 10 HRAC MoA groups each accounted for less than 1% of herbicide applications, N, F4, K1, I, H, F3, Z, L, F2 & K2.’

181 I don’t really see the point of stating actual % for barley when you haven’t for wheat. Why not simply add % values to each of the bars in Fig 1. You could then say a bit about relative use of some individual herbicides in wheat and barley. Somewhere you should give some indication of relative area sown with wheat and barley – in introduction or M&M.

183 Suggest: ‘Flufenacet and terbuthylazine were the only herbicides used on a significant area pre-emergence (the latter can also be used post-emergence), both used less in barley crops.’

185 Suggest: ‘Fig 1. The ten most commonly applied herbicides in New Zealand wheat and barley fields.’

190 Why taxon? Surely ‘species’ is better?

193-194 Say eight grasses and eight broad-leafed weeds.

201 Suggest: ‘….five or more unique mode-of-action groups each’ What does>20 mean? Clarify.

202-215 This paragraph covers the key output of this paper but is confusing and really needs a thorough re-write. Expand if necessary, to clarify results. Fig 2 contains a lot of information. I did wonder how much the ‘cases’ adds to this but I can see that it is relevant. Some definition of ‘cases’ is needed, as mentioned earlier. This is tricky as not easy to explain in a few words, but if this is explained in the M&M then no need to explain again, except perhaps to say refer to M&M. Should be made clear in Figure that cases is worldwide, as might be interpreted by casual reader as in NZ.

212-215 I would make the point that 7 out of 10 are grass-weeds. Grass-weeds are over-represented in global cases of resistance. Some comment on this in discussion maybe.

Discussion: The paper would benefit from a more concise discussion with improved, more logical structure. Content is OK but lacking in focus and a bit rambling. I suggest reducing it to about 60% max of current length by heavily reducing some paragraphs or omitting altogether. The focus should be on the lessons and implications from what you have presented in the paper. Some of Discussion, while valid, reduces the impact of the paper rather than enhances it.

226-235 Better if this is later in Discussion.

236-261 Reduce this paragraph very substantially. Some of this could be in introduction.

There appear to be some contradictions quoted: ‘77 cases in wheat and 30 cases in barley [4].’ ‘ A review of the New Zealand literature shows only two reports of resistant species in wheat and barley [7,8].’ ‘Cases’ is confusing as different, I think, to previous use of term.

262-287 Suggest this starts the Discussion as seems more logical.

288-306 Again lacks focus. Glyphosate comments relevant. But to make some suggestion but then say ‘Estimations of these other factors can be made, but are likely to be inaccurate.’ Is a case of ‘shooting yourself in the foot.’ Ditto ‘Using Beckie’s as our herbicide-risk ranking would produce different risk-scores.’ Omit.

Other paragraphs – consider what content really adds to paper and what can be omitted.

One aspect that seems missing, is some idea of the crop rotations used on NZ farms and the impact this might have. This focus in this paper is on wheat and barley but the frequency of growing these crops and consequent herbicide use will surely impact on the resistance risk? How commonly is arable cropping rotated with grass? Are all-arable farms common compared with mixed farms? This may explain why herbicide resistance is relatively uncommon in NZ. Also relevant to risk at individual field level which lends itself nicely to comments about where you should set priorities for resistance monitoring, management and farmer KT. No need to go into great detail, but is relevant.

Conclusions: Generally fine but suggest the following.

343-346 Suggest: ‘A European protocol [17], designed primarily to assist in herbicide authorization procedures, was adapted to assess the risk of herbicide resistance evolving in 100 different weed species known to occur in New Zealand wheat and barley crops. More than half the weeds (55) we assessed were low-risk, 29 were medium-risk and 16 high-risk. The 10 species posing the highest resistance risk were: etc etc’

349-351 Final two sentences could usefully be a bit ‘punchier’. ’Suggest: ‘We are planning extensive surveys in New Zealand to detect new cases of herbicide resistance. The risk assessment outlined in this paper will enable us to prioritise those weeds identified as posing a high resistance risk and, consequently, make better use of available resources. The risk assessment procedure as described in this paper has the potential to be a very useful tool for evaluating the risk of herbicide resistance in a wide range of different weed species in other countries too’.

Reviewer #3: Reviewer (YASEEN KHALIL):

Thanks for allowing me to review the manuscript entitle “A herbicide resistance risk assessment for weeds in wheat and barley crops in New Zealand”. This is a very well written and informative manuscript. Authors have carried out a systematic study to determine the quantitative risk matrix using ranked herbicide-risk and species-risk with optional score modifier designed to account for agronomic management practices that may reduce the risk. The researchers took advantage of a unique data set about herbicide use in wheat and barley fields in New Zealand to place their risk assessment into context, and construct a framework for herbicide resistance surveys and extension efforts in the New Zealand cropping industry. This study would be provided a very good message for the growers about the herbicide resistance risk assessment on the industry-wide scale, but not on the field and farm scale. I am in favor of publishing this manuscript to the PLOS ONE Journal. I have very few comments.

GENERAL COMMENTS:

The manuscript represents a review article instead of research article, as it is been mentioned in the manuscript draft, in an important area of herbicide research and was conducted with reasonable methods. In addition, the manuscript is written well, with areas for improvement in several instances.

Keywords should be main words that are not included in the title and the abstract.

The abstract is well structured. I suggest mentioning the scientific name of the weeds including the name of classifiers for the first time.

The introduction and methodology of the experiments seem to be satisfactory. However, in the methods section, the authors need to explain how they did the statistical analyses and data presentation.

SPECIFIC COMMENTS:

L20-22 Add the classifiers to the scientific names. Alternatively, you may add the classifiers to the scientific names in the Materials and methods section and after that no need for it to be mentioned.

L20-22 Add hyphen “herbicide-resistant”

L45 Add the “it reflects the varying”

L52 Add the classifier to the scientific name “Alopecurus myosuroides ”.

L20-22 Add hyphen “farm-scale”

L74-76 What about the other 25% of the wheat and barley production regions in New Zealand. I would prefer to stick to the mentioned region and not extrapolate to the whole country of New Zealand.

L78 It will be very useful to mention the regions of the studies conducted by the mentioned researcher’s literature [21, 22].

L79 It is recommended to follow the journal guidelines in this regards instead (Species nomenclature).

L91-92 What is the logic and the rationale behind this decision? Worldwide, Group A herbicides are the most vulnerable group in terms of weed resistance evolving

L122 Add the classifier to the scientific name “Chenopodium album”.

L140 Add the “that the actual”

L142 Add comma “distribution, and abundance”

L147 Add of “total of 100 weeds”

L150 I would recommend adding the S1 Table to the text instead of having it as a supporting file.

L152 I would recommend adding the S2 Table to the text instead of having it as a supporting file.

L179 Add the “ranked by the wheat”

L203 Add comma “modes-of-action, and”

L234 Add comma “Without this list, we”

L234 replace are with a “As a result”

L240 Add comma “cases in wheat, and”

L246 Add s “indicates elevated”

L247 Add comma “surprising when”

L256 delete “Clearly”

L275, 281, 284 Add hyphens to “spring-sown cereals”, “on-field”, “high-risk”

L289“because of the number”

L290 have instead of has “groups have increased”

L296“because of worldwide”

L308 Surprisingly, there have

L324 Add commas “may, in fact, implicate”

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Dr Stephen Moss

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Reviewers comments on PONE-D-20-09801 29April20.docx

Click here for additional data file.

Submitted filename: PONE-D-20-09801_reviewer (YK).docx

Click here for additional data file.

18 May 2020

Reviewer #1:

Because frequency and abundance of weed species in the region have not been used in the scoring, the paper provides a picture of risks due to the current use of herbicides in the re-gion, which is informative for the farmer about the intrinsic risk of an abundant species in its own farm. However, although I agree with intrinsic high risk species as stated on line 280-285, it is pity that the overall risk for the region is not presented.

The regional risk is assessed! We use a published account of weeds, as well as ex-pert knowledge to identify problem weeds in wheat and barley. The risk assess-ment considers the propensity of those weeds to develop resistance. It uses the most important factors, the crop specific region wide weed flora and region wide data about herbicide use. The selection pressure comes from the herbicides used and so captures the most important dimensions of the regional risk.

L50-54 There is also an important survey on blackgrass in UK (see Hicks et al Nature Ecology & Evolution 2(3) 2018, DOI: 10.1038/s41559-018-0470-1). Probably other reports are availa-ble on surveys developed by national weed research associations in Spain, France (Columa), Italy, etc., including companies, extension service and farmers, and published in local con-ferences.

That is another example of the “focus on one or two problematic species in a given crop” issue we highlight, and therefore does not need to be added.

L142 It can be assumed that weed biology is already included in the inherent species score, but abundance is a key parameter. Abundance includes effects of farming systems: if many individuals still remain in the field, then the risk of developing resistance is higher than if the population is small. A score modifier to account for variation of abundance (e.g. 1 for low density and 3 for more than a million plant/ha, or another scale) could be used. Another factor is the species frequency in the studied region, which doesn’t seem to be taken into account (is the Production Wise platform collecting main troublesome weed species?).

While that is true, regional abundance and density data do not exist to be able to implement that. We acknowledge that distribution, abundance and phenology are important #(L272). ProductionWise does not gather any information on weeds. Be-cause we identified high-risk species and herbicides the data are useful as a region-al assessment. Farmers and experts can now interpret the observed weed abun-dance with an eye to the likely risk of resistance.

Fig 2 Rather the low and high use HRAC groups I expected to see also the number of cases in New Zealand. I’m not clear with the low versus high use HRAC groups.

We emphasize high use herbicides in our studied regions, because that selection pressure drives the evolution of resistance. We mention in the introduction that in New Zealand, there are only 12 instances of herbicide resistance in arable crops #(L41-43) and in the discussion delve further into New Zealand HR weeds (L238-244). The high and low usage herbicide groups come from ProductionWise data, which can be found on Table 2. The basis of deciding which groups are ‘high use in New Zealand’ is on L106-108. Cases of resistance have been indicated on Table 3.

Reviewer #2 Dr Stephen Moss:

Abstract: Generally fine but as likely to be most-read part I suggest a few minor changes. Do you need to say ‘wheat and barley’ or would ‘cereal’ suffice? Ditto in title.

We think wheat and barley is a more accurate statement for our case since the herbicide data focuses on that. Wheat and barley is more widely grown than oats, and depending on the reader, corn would also be consid-ered to be a cereal…

I suggest:

15-18 ‘We estimated the risk of selecting for herbicide resistance in 100 weed species known to occur in wheat and barley crops on farms in New Zealand. A protocol was used that accounts for both the risk that different herbicides will select for resistance and each weed’s propensity to develop herbicide resistance based on the number of cases worldwide.’ Done

24 ‘ALS-inhibitors were assessed as posing the greatest risk for more species than any other mode-of-action. Done

25 I prefer ‘Pre-emergence’ but that may depend on journal style. Done

26 ‘……. in this class commonly used by…..’ Is this better than ‘favoured’? Done

Somewhere I think it would be worth stressing in abstract that 7 out of the high-risk 10 are grass-weeds. If space is limiting, I think the last sentence of abstract could go or ‘farmer extension efforts’ incorporated into previous sentence. Done

Introduction: Good – acceptably concise and relevant. I suggest including some brief (one or two sentences) information on arable cropping in NZ and what proportion of that is accounted for by wheat and barley. Or at least to show that wheat and barley comprise a significant proportion of arable crops – you might even wish to mention that NZ currently holds world record for both barley and wheat yield/ha (I think that is correct). I would! Done

32 Suggest: ‘……potential losses….’ Losses of 23% don’t actually commonly occur. Done

41 Clarify ‘cases’. To non-specialist reader it is vague and could mean number of fields or farms – although ‘specialists’ know why that term is appropriate. I would suggest stating number of weed species instead which is 13 according to Heap website country info. That lists 19 ‘cases’ (29 April) although that dupli-cates some species. If it is 25 cases now (according to your reference), perhaps someone in NZ should provide Ian Heap with updated info. This is important if this paper is published. Likewise amend ‘12’ in line 42 if appropriate. Done re-worded to reflect species numbers in New Zealand, and documented instances of resistance, to distinguish from the usage of cases in the Heap database.

45 ‘haphazard’ is a bit unfair, although this is a valid point. I would dispute that my sampling and testing over 30 years has been ‘haphazard’! Suggest ‘unsystemat-ic’ as a better word – I would agree with that. End sentence after ‘globally’. Then ‘It reflects…..’ Done

50 comma needed after [9-14]. These 6 refs are all valid, but do you need them all? They are valid, focus on systematic efforts to detect any and all weed re-sistant cases. Also, they could be hard to find for other researchers working on a similar project. Leaving as is.

53-54 Good points – one issue is that if resistance is perceived to be rare then hard to justify cost. If very widespread then why bother to do a survey? Money could be better spent. Also lack of infrastructure and personnel to conduct surveys may be as important as cost. Also, do surveys have much long-term value? Is a 20-year old survey of much value now – perhaps only as a benchmark? Perhaps money better spent on more ‘durable’ studies? Not saying that you need to con-sider these aspects here – perhaps in discussion as risk assessment relevant to survey priorities. Good points thanks for the insightful commentary.

59 Suggest: ‘…….and their prior record of resistance in cereal fields elsewhere in the world.’ We specifically looked at wheat and barley. It’s an important dis-tinction.

62-64 This is fine and a good succinct sentence, but I wonder if it is worth emphasising more that risk assessment includes not only herbicide risk but also weed species risk for non-specialist readers, as this is not particularly intuitive? So, could read: ‘They present a quantitative risk matrix using both herbicide-risk (some herbicides pose a higher risk than others) and species-risk (some weed species are more resistance-prone than others), with an optional score modifier de-signed to account for agronomic management practices that may reduce the risk.’ Done

67 Change: ‘Individual field and farm scale risk is not assessed as this requires de-tailed information on past herbicide use, including timing etc…..’ (This covers what has been applied - surely most important factor?) We changed the para-graph to emphasize importance of our herbicide application data set: “. This risk assessment is on an industry-wide scale informed by anonymized herbicide application data from wheat and barley fields. Risks were not assessed at the scale of individual farms and fields, this requires detailed information about herbicide timing, mixtures and rotations, and their interactions with weed bi-ology, crop rotations and other cultural practices. All the high-risk weeds iden-tified here should be targeted in surveys designed to detect herbicide-resistant weeds.

Materials and methods: Good – makes it clear what was done and why slightly differ-ent approaches to published protocol were adopted

76 Suggest: ‘Most grasses and some …..’ The wonders of Google mean that I can see, within 60 seconds, that two grass weed species were identified at species level in the paper cited….. Done

83 Suggest: ‘….legacy herbicide mode of action (MoA) groups……’ Done

88-89 Suggest: ‘….legacy HRAC MoA group [24], with risk scores of 1, 2 or 3 given for low, medium or high risk respectively.’ Done

96 Suggest: ‘…..scored as ‘1’.’ (‘One’ is a bit ambiguous). Done

98 Suggest: ‘Most recent….’ Done but, “The most recent…”

108-109 This is slightly confusing: ‘The most used herbicides for each crop were charac-terized by weighting active ingredient amounts and the number of fields they were applied to.’ It almost implies total a.i. weight was used. Not sure this sen-tence is needed. Deleted the sentence.

110 Why taxon? Species better? Changed to species.

112 Suggest: ‘…..HRAC MoA group…...’ And I suggest elsewhere throughout paper. Done

113 Suggest: ‘….herbicide type…. Done

114 Suggest: ‘……the global number of resistance cases….’ Done

115 Suggest: ‘To obtain the ‘high’, ‘medium’ and ‘low’ risk scores as used in the Moss protocol [17],…..’ Done

117-118 This sentence is slightly confusing and maybe could be improved. Is this correct? ‘We assessed overall species-risk as the sum of the herbicide-risk multiplied by the “inherent” species-risk [17] combined for all relevant HRAC MoA herbicide groups, but only…….’ (I think ‘once’ is confusing). The example you give below is useful. Done

120 Suggest: ’……weed species….’ Done

135 Suggest: ‘……to determine species-risk scores based on the number of cases of resistance worldwide, but we think this……’ Done

137 Suggest: ‘ ….45 ‘high’ and ‘medium’ resistance risk species, many more than Moss et al……….’ Done

139 Suggest: ‘The Moss protocol also used score modifiers that take into account re-sistance management practices including the use of non-chemical control measures’ . Done

139-142 Suggest: ‘We did not use the score modifiers since these vary from field to field and our objective was slightly different. We acknowledge that actual risk of re-sistance development is determined mostly by the frequency and type of herbi-cide applied (selection pressure) interacting with characteristics of weed biolo-gy, distribution and abundance [5].’ Done

Results: Generally good and concise. One key paragraph needs improvement to im-prove clarity

145 Suggest: ‘An additional 31 species were added…..’ Done

147 Suggest: ‘ ….resulting in a total of 100 weed species for consideration.’ Done

155 Suggest: Suggest: ‘This resembles the table of Moss et al., [17] with…’ Done

Table 1 Use of ‘taxa’ is odd. Why not ‘species’ which is what is used on Heap’s website? Taxa is a rather more general term and I cannot see any justification for use here. Would it also be useful to make the herbicide example the most common-ly used ai for the group in NZ? Or if this has been done, state in title. Done

171-172 Clarify if glyphosate used in-crop (for desiccation) or pre-sowing or both. Pre-sumably both, but some comment about balance of use would be useful if only to stress that glyphosate use is very different to selective herbicides – non-specialists might assume use is primarily in GM crops, as in some other coun-tries. Either here or earlier in M&M. Done “Glyphosate (MoA group G) is most-ly used (>95%) used pre-sowing of the cereal crops, for termination of the pre-vious crop or pre-establishment weed control. It is very rarely used as crop pre-harvest desiccant.”

Suggest: ‘ …….in barley (18%) compared with wheat (12%); conversely, farm-ers………’ Done

174 Again, ‘HRAC MoA categories’ Done

Table 2 Suggest last 10 categories are simply summarised to save space and some statement added within table. e.g. ‘The following 10 HRAC MoA groups each ac-counted for less than 1% of herbicide applications, N, F4, K1, I, H, F3, Z, L, F2 & K2.’ Done

181 I don’t really see the point of stating actual % for barley when you haven’t for wheat. Why not simply add % values to each of the bars in Fig 1. You could then say a bit about relative use of some individual herbicides in wheat and barley. Somewhere you should give some indication of relative area sown with wheat and barley – in introduction or M&M. We added the percent values to the graph and clarified a comment about relative use under Table 2. The areas sown for wheat and barley are now in the introduction.

183 Suggest: ‘Flufenacet and terbuthylazine were the only herbicides used on a sig-nificant area pre-emergence (the latter can also be used post-emergence), both used less in barley crops.’

185 Suggest: ‘Fig 1. The ten most commonly applied herbicides in New Zealand wheat and barley fields.’ Done

190 Why taxon? Surely ‘species’ is better? Done

193-194 Say eight grasses and eight broad-leafed weeds. Done

201 Suggest: ‘….five or more unique mode-of-action groups each’ What does>20 mean? Clarify. Done

202-215 This paragraph covers the key output of this paper but is confusing and really needs a thorough re-write. Expand if necessary, to clarify results. Fig 2 contains a lot of information. I did wonder how much the ‘cases’ adds to this but I can see that it is relevant. Some definition of ‘cases’ is needed, as mentioned earlier. This is tricky as not easy to explain in a few words, but if this is explained in the M&M then no need to explain again, except perhaps to say refer to M&M. Should be made clear in Figure that cases is worldwide, as might be interpreted by casual reader as in NZ. Done Figure 2 clearly mentions global cases. Also added the following to the methods: “Cases are defined by the International Sur-vey of Herbicide Resistant Weeds as unique combinations of weed species and HRAC herbicide mode-of-action (species x site of action).”

212-215 I would make the point that 7 out of 10 are grass-weeds. Grass-weeds are over-represented in global cases of resistance. Some comment on this in discussion maybe. Done

Discussion: The paper would benefit from a more concise discussion with improved, more logical structure. Content is OK but lacking in focus and a bit ram-bling. I suggest reducing it to about 60% max of current length by heavily reducing some paragraphs or omitting altogether. The focus should be on the lessons and implications from what you have presented in the paper. Some of Discussion, while valid, reduces the impact of the paper rather than enhances it.

226-235 Better if this is later in Discussion. Done

236-261 Reduce this paragraph very substantially. Some of this could be in introduction.

There appear to be some contradictions quoted: ‘77 cases in wheat and 30 cases in barley [4].’ ‘ A review of the New Zealand literature shows only two reports of resistant species in wheat and barley [7,8].’ ‘Cases’ is confusing as different, I think, to previous use of term. Done

262-287 Suggest this starts the Discussion as seems more logical. Done

288-306 Again lacks focus. Glyphosate comments relevant. But to make some sugges-tion but then say ‘Estimations of these other factors can be made, but are likely to be inaccurate.’ Is a case of ‘shooting yourself in the foot.’ Ditto ‘Using Beck-ie’s as our herbicide-risk ranking would produce different risk-scores.’ Omit. Several sentences deleted and reworded to avoid “shooting ourselves in the foot” but keeping the main ideas as a reasonable caveat around interpretation of our results.

Other paragraphs – consider what content really adds to paper and what can be omitted.

One aspect that seems missing, is some idea of the crop rotations used on NZ farms and the impact this might have. This focus in this paper is on wheat and barley but the frequency of growing these crops and consequent herbicide use will surely impact on the resistance risk? How commonly is arable cropping ro-tated with grass? Are all-arable farms common compared with mixed farms? This may explain why herbicide resistance is relatively uncommon in NZ. Also relevant to risk at individual field level which lends itself nicely to comments about where you should set priorities for resistance monitoring, management and farmer KT. No need to go into great detail, but is relevant. We have includ-ed some text about rotations.

Conclusions: Generally fine but suggest the following.

343-346 Suggest: ‘A European protocol [17], designed primarily to assist in herbicide authorization procedures, was adapted to assess the risk of herbicide re-sistance evolving in 100 different weed species known to occur in New Zealand wheat and barley crops. More than half the weeds (55) we assessed were low-risk, 29 were medium-risk and 16 high-risk. The 10 species posing the highest resistance risk were: etc etc’ Done

349-351 Final two sentences could usefully be a bit ‘punchier’. ’Suggest: ‘We are plan-ning extensive surveys in New Zealand to detect new cases of herbicide re-sistance. The risk assessment outlined in this paper will enable us to prioritise those weeds identified as posing a high resistance risk and, consequently, make better use of available resources. The risk assessment procedure as described in this paper has the potential to be a very useful tool for evaluating the risk of herbicide resistance in a wide range of different weed species in other coun-tries too’. Done

Reviewer #3 (YASEEN KHALIL):

The introduction and methodology of the experiments seem to be satisfactory.

However, in the methods section, the authors need to explain how they did the statistical analyses and data presentation.

We do not carry out any statistical tests. All our data is descriptive, and are visual-ized using graphs . We added a sentence to the last line of the methods section about the graphs.

SPECIFIC COMMENTS:

L20-22 Add the classifiers to the scientific names. Alternatively, you may add the classifiers to the scientific names in the Materials and methods section and after that no need for it to be mentioned.

We think the reviewer is referring to the specific binomial author authorities. We examined other abstracts in PLOS ONE and do not see the these being used for ab-stracts unless it is specifically about a taxonomic treatment.

L20-22 Add hyphen “herbicide-resistant” Done but line 27

L45 Add the “it reflects the varying” Done

L52 Add the classifier to the scientific name “Alopecurus myosuroides ”. Done and also for Avena fatua

L20-22 Add hyphen “farm-scale” We added this at line 68 though which was the first men-tion

L74-76 What about the other 25% of the wheat and barley production regions in New Zea-land. I would prefer to stick to the mentioned region and not extrapolate to the whole coun-try of New Zealand.

We intend the weed list to capture our best estimate of the weeds known to occur in wheat and barley fields in New Zealand. We added a new sentence to explain: We expanded the weed species list to include species known to occur in wheat and barley fields in the wider New Zealand context.

L78 It will be very useful to mention the regions of the studies conducted by the mentioned researcher’s literature [21, 22].

We disagree. We checked the regions studied in those articles and knowing them adds lit-tle insight. Also, only a few species were added from these.

L79 It is recommended to follow the journal guidelines in this regards instead (Species no-menclature). Taxonomic authorities added at first mention.

L91-92 What is the logic and the rationale behind this decision? Worldwide, Group A herbi-cides are the most vulnerable group in terms of weed resistance evolving

We do classify Group A herbicides as high risk. We include a bit more detail here and consider the issues in the discussion. It now reads: With group A having 48 cas-es and group G herbicides having 47 cases we chose to place the two groups in the same risk category, with a difference in the numbers of cases of just worldwide we believe they are indistinguishable from the data. The alternative is to use the same threshold as in the Moss protocol, but this would result in group A and G being me-dium risk, which fails to capture the high-risk status of group A herbicides.

L122 Add the classifier to the scientific name “Chenopodium album”. Done

L140 Add the “that the actual” Done

L142 Add comma “distribution, and abundance” Done

L147 Add of “total of 100 weeds” Done, but it is now 101 weeds.

L150 I would recommend adding the S1 Table to the text instead of having it as a supporting file. Done

L152 I would recommend adding the S2 Table to the text instead of having it as a supporting file. Done We think this one should stay where it is because of its length.

L179 Add the “ranked by the wheat” Done

L203 Add comma “modes-of-action, and” Done

L234 Add comma “Without this list, we” Done

L234 replace are with a “As a result” Done

L240 Add comma “cases in wheat, and” Done

L246 Add s “indicates elevated” Not done. “may indicate” is correct

L247 Add comma “surprising when” Not done. Comma is correct

L256 delete “Clearly” Done

L275, 281, 284 Add hyphens to “spring-sown cereals” Done, “on-field” Not done the acting on field experience” refers to experience gained in the field, “high-risk” Done

L289“because of the number” Not done. This makes sense “This was necessary in part be-cause the number of cases for different herbicide groups has increased since the Moss arti-cle was published.”

L290 have instead of has “groups have increased” Not done. This makes sense “This was necessary in part because the number of cases for different herbicide groups has increased since the Moss article was published.”

L296“because of worldwide” Not done, it makes sense the way it is.

L308 Surprisingly, there have Done

L324 Add commas “may, in fact, implicate” Done

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

3 Jun 2020

A herbicide resistance risk assessment for weeds in wheat and barley crops in New Zealand

PONE-D-20-09801R1

Dear Dr. Chris Evan Buddenhagen,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements and edits suggested by academic editor..

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ahmet Uludag, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

I went through all over the document. I have some suggestions mostly editorial. I also read it with eye of a person who is not a native speaker of English. Two points I would like to mention here as well as on attached, PONE-D-20-09801_R1 AUl. Tables and figures has extra informations in titles. Most of them have been shown on attached document. You have the most of information in the text. There is no need repeat them again header fo the table or figure. Please check all of them not only I have mentioned. Some information iunder table can be moved to text, please see the attachment. The first paragraph of discussion is real conclusive paragraph. It should be moved to conclusion.

Reviewers' comments:

Submitted filename: PONE-D-20-09801_R1 AUl.pdf

Click here for additional data file.

16 Jun 2020

PONE-D-20-09801R1

A herbicide resistance risk assessment for weeds in wheat and barley crops in New Zealand

Dear Dr. Buddenhagen:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ahmet Uludag

Academic Editor

PLOS ONE