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Removal of non-crop vegetation (e.g., forest and grassland patches) to expand crop fields is detrimental to the natural enemies of crop pests, like the ground beetle family (Coleoptera: Carabidae), that use these areas for foraging and overwintering. An argument for maintaining non-crop vegetation is its potential to support the supply of ecosystem services, like pest control, to the surrounding crop. Pest control services from non-crop areas are usually measured using the activity-density of natural enemy species, a proxy measure for predatory activity. Evidence that predators such as ground beetles are attacking pests in crops has been less frequently studied. We distributed sentinel prey (fake 'caterpillars' made to look like potential prey items) along with pitfall traps at 300 stations using a spatially and temporally replicated design across 20 field sites in Alberta, Canada. The potential for pest attacks by carabids was estimated through bite marks on the sentinels. Using generalized additive modelling, we found that non-crop vegetation positively impacts carabid predation, but activity density of carabids does not explain the relationship. Instead, the non-crop vegetation affects predation frequency, likely by promoting predatory behaviours. These findings exemplify the importance of closer indicators of ecosystem services delivery than activity-density and provide evidence of the potential that ground beetles have in supplying pest control ecosystem services within agroecosystems. • Sentinel prey used as proxy measure for biocontrol ecosystem services by carabids. • Linear increase in carabid activity-density with distance from non-crop vegetation. • Positive effect on predation activity with proximity to non-crop vegetation. • Activity-density is a poor proxy of service delivery, sentinel prey is better. [ABSTRACT FROM AUTHOR]

Remote sensing imagery has been a key data source for precision agriculture. However, high-resolution and/or hyperspectral imagery have typically been favored for their greater information content. This study aims to demonstrate the capability of medium-resolution imagery in precision agriculture by developing an example of canola yield mapping using Sentinel-2 data in central Alberta. Two simple empirical models for mapping precision canola yield are tested: one using random forest regression and a second using functional linear regression. Both take as input freely-available Sentinel-2 time series images and use these to predict precision yield gathered by a yield monitor. The models were able to predict crop yield to within 12–16% accuracy of the reference yield. These results also demonstrate that a time series of medium-resolution multispectral imagery can capture small-scale variation in crop yields. The proposed methods can be applied to other areas or cropping systems to improve understanding of crop growth at both the field-level and regional-level. [ABSTRACT FROM AUTHOR]

Canola is one of the most important cash crops in Canada, but yields can be reduced by several insect pests including Lygus spp. (Hemiptera: Miridae). Canola cultivars have been improved substantially since economic thresholds were developed for Lygus in the 1990's. Thus, the objective of this study was to integrate a large data set collected over 23 years (1999–2021) from plots and commercial fields to update economic thresholds. Regression analysis of the data from the studied years from across distinct ecoregions yielded an overall Economic Injury Level (=action threshold) around 9–23 Lygus per 10 sweeps using the current (high) canola prices. However, insecticide trials at farmer's commercial fields, showed that yield was protected from Lygus feeding by spraying a foliar insecticide at the early pod stage only when catches exceeded 30 Lygus per 10 sweeps. Further analysis of Precision Yield Data (PYD) from combine yield monitors from southern Alberta, revealed that at low abundances, under 17 Lygus per 10 sweeps, Lygus may potentially stimulate canola yield and do not require a control action, unless there are more than 30 Lygus per 10 sweeps. Developing a long term data repository for PYD across multiple sites and spatial scales in the Prairies of Canada would allow future generations of researchers to improve decision making tools such as pest action thresholds, to develop a more resilient and sustainable agriculture. [Display omitted] • From 1999 to 2021 we collected data on canola yield and Lygus bug abundance in southern Alberta from 97 farm or plot sites to validate economic injury levels (EIL). • Linear or non-linear regression models suggested an EIL similar to the historical threshold around 15 Lygus per 10 sweeps. • A detailed analysis of Lygus abundance categories from Precision Yield Data showed that Lygus reduce yield only when they surpass 30 per 10 sweeps and plants can compensate or overcompensate for Lygus feeding below this abundance. • Economic Injury Levels based on overall regression analysis (linear or not) may ignore herbivore-plant interactions that occur at distinct regions of arthropod densities. • Ideally, EIL's should be validated on farms and with large historical data sets. [ABSTRACT FROM AUTHOR]

Field boundaries can provide ecosystem services to crops by creating better abiotic conditions for crop growth, and can also act as habitat for beneficial arthropods. This suggests that crop boundaries may create an intermediate hump-shaped increase in crop yield, where negative edge effects are cancelled out by increased ecosystem services from the field boundary. However, there is little large-scale evidence showing this, largely because plot-scale crop yields are costly and time-consuming to measure. Precision yield data from combine yield monitors has huge potential in this respect, as the equipment is widespread and data is frequently recorded by growers. In this study, we used 252 field-years of yield monitor data from three common crops – wheat (Triticum aestivum), canola (Brassica napus), and peas (Pisum sativum) – recorded across Alberta, Canada, and examined how yield varied with distances from common crop boundary types. Average crop yield tended to increase with distance from crop boundaries before plateauing at about 50 m, and yield variation (SD) tended to decrease with distance. There was evidence of an intermediate increase in yield for wheat away from shelterbelts, and a weak increase in canola, but this was not seen for other crop types or boundary types. This study represents one of the first uses of precision yield data to measure ecosystem service provision at large spatial scales. • Non-cropped field boundaries can increase or stabilize crop yield. • Precision yield data can be used to assess these ecosystem services. • Yield tended to increase with distance from the boundary until about 50 m. • Shelterbelts caused an intermediate increase in wheat, but not canola or pea yields. • Canola was more sensitive to edge effects than wheat or peas. [ABSTRACT FROM AUTHOR]