Spatial and Population Dynamics of Patches of Wild-oats Nicola Perry and Peter Lutman IACR-Rothamsted

Background: Important grass weed Patchy distribution Patch stability unknown Wild-oats:

Experiment details Patch size 3x3 m Two sowing densities: –10 plants/m 2 and 50 plants/m 2 Ploughing, cultivations and combining in same direction each year +/- wild-oat herbicide in 2000

Experiment design SLD SHDLD SHD LDSLDHD HD = high density; LD = low density; S = sprayed arrows indicate cultivation & combining direction N 30m 12m 3m

Monitoring Panicle distribution Seed movement Patch shape Location of outliers

Panicle and seed distribution 1999 Panicles / m 2 Seeds / m 2 Direction of cultivation & combining

Panicle and seed distribution Sprayed Treatments 2000 Panicles / m 2 Seeds / m 2 Direction of cultivation & combining

Seed distribution after harvest Sprayed v Unsprayed 2000 Direction of cultivation & combining Total no. seeds/m 2 Sprayed: 17,860 Unsprayed: 139,410

Low Density Sprayed Patch 1998 (9 m 2 ) 1999 (20.3 m 2 ) 2000 (20.6 m 2 ) m harvesting & cultivation

m 1998 (9 m 2 ) 1999 (29.5 m 2 ) 2000 (41.0 m 2 ) High Density Unsprayed Patch harvesting & cultivation

Patch outline Outliers

Patch outline Outliers S S S S SSprayed plots

Conclusions Majority of seeds move 1-2 m –movement due to cultivations and plants leaning in wind Isolated plants occur up to 30 m away –movement by combine –may lead to future infestations / new patches

Conclusions Wild-oats need frequent re-mapping Patches not stable and new patches may form from isolated plants Presence of outliers make decisions on patch spraying complicated

Limitations of manually mapping weed patches Nicola Perry and Peter Lutman IACR-Rothamsted

Methods of manually mapping weed patches Visual detection (human) –mapping on a grid –ATV, tractor/sprayer, combine –walking around patches

Weed attributes which can be recorded Presence / absence Approximate levels (high / low) Weed numbers Weed vigour / ground cover

Weed attributes which can be recorded from a vehicle or using quadrats

Timing of visual assessments

Activities on Warren Field (winter wheat)

Warren Field black-grass comparison of mapping methods Correlation : 0.82 Quadrat threshold 20 plants/m 2 (Dec 99) Black-grass No Black-grass ATV (Jan 00)

Warren Field black-grass comparison of mapping methods Correlation : 0.60 Quadrat threshold 5 plants/m 2 (Dec 99) Black-grass No Black-grass ATV (Jan 00)

Warren Field black-grass comparison of mapping methods Correlation : 0.37 Quadrat threshold 20 plants/m 2 (Dec 99) Black-grass No Black-grass Tractor (June 00)

Warren Field black-grass comparison of mapping methods Correlation : 0.84 Quadrat threshold 2 plants/m 2 (Dec 99) Black-grass No Black-grass Tractor (June 00)

Warren Field wild-oats comparison of mapping methods ATV (Jan 00) Correlation : 0.74 Quadrat threshold 2 plants/m 2 (Dec 99) Wild-oats No Wild-oats

Warren Field wild-oats comparison of mapping methods Tractor (June 00) Correlation : 0.58 Quadrat threshold 2 plants/m 2 (Dec 99) Wild-oats No Wild-oats

Broad Mead black-grass comparison of mapping methods ATV (Jan 00) Correlation : 0.70 Quadrat threshold 5 plants/m 2 (Dec 99) Black-grass No Black-grass

Black-grass distribution in Cashmore Field Mapped from ATV Nov 99 Mapped from combine July 00 Mapped on foot May 00

Conclusions Limitations to manually mapping weeds Discrete quadrat sampling too time consuming for mapping on a whole-field scale Continuous visual detection from a vehicle is less accurate, & may be restricted to tramlines, but is quicker

Conclusions Need to make more progress with optimum visual detection in absence of automated detection