Increased reliance on insecticide applications inCanada linked to simplified agricultural landscapes

Abstract

Intensification of agriculture and increased insecticide use have been implicated in global losses of farmland biodiversity and ecosystem services. We hypothesized that increased insecticide applications (proportion of area treated with insecticides) in Canada's expansive agricultural landscapes are due, in part, to shifts toward more simplified landscapes. To assess this relationship, we analyzed data from the Canadian Census of Agriculture spanning 20 years including five census periods (1996–2016) and across 225 census units within the four major agricultural regions of Pacific, Prairie, Central, and Atlantic Canada. Generalized mixed effects models were used to evaluate if changes in landscape simplification — defined as the proportion of farmland in crops (cereals, oilseeds, pulses and fruit/vegetables) — alongside other farming and climatic variables, influenced insecticide applications over time. Bayesian spatial–temporal models were further used to estimate the strength of the relationship with landscape simplification over time. We found that landscape simplification increased in 89% and insecticide applications increased in 70% of the Census Division spatial units during the 1996–2016 period. Nationally, significant increases in landscape simplification were observed in the two most agriculturally intensive regions of Prairie (from 55% to 63%) and Central (from 51% to 60%) Canada. For both regions, landscape simplification was a strong and significant predictor of higher insecticide applications, even after accounting for other factors such as climate, farm economics, farm size and land use practices (e.g., area in cash crops and tillage). If current trends continue, we estimated that insecticide applications will increase another 10%–20% by 2036 as a result of landscape simplification alone. To avoid increased reliance on toxic insecticides, agri‐environmental policies need to consider that losing diverse natural habitat can increase insect pest pressure and resistance with negative environmental consequences extending beyond the field.

Projected landscape-scale repercussions of global action for climate and biodiversity protection

“…In the past, the shift from low-input farming to intensive farming and concurrent landscape transitions have caused sharp species declines 35 , 79 , 80 and undermined essential NCP 2 , 4 , 8 , 9 , 13 . Promoting off-farm ecosystem management and multifunctionality within farmed landscapes therefore could not only offer decisive means for counteracting these negative trends 18 , 37 , 57 , 81 , 82 , but also reduce the use of external inputs in agricultural production, such as pesticides 83 , 84 . Increased landscape heterogeneity would also provide co-benefits for biodiversity at larger scales 20 , 37 and increase the effectiveness of protected areas (PAs).…”

Current honey bee stressor investigations and mitigation methods in the United States and Canada

“…Quinlan and colleagues ( 2023 ) found that different carbohydrate-based artificial diets had significantly influenced individual physiological markers and tended to increase survival and population size at a colony level ( Quinlan et al 2023 ). Similarly, as some agroecosystems, especially those with large monocultures, continue to rely on chemical controls of pests and pathogens, especially those with large monocultures, research investigating bee health in relation to pesticides is always at the forefront of the apicultural industry needs ( Malaj and Morrissey 2022 ). Several abiotic studies within this special issue center around pesticide exposure.…”

Advancing exposure assessment approaches to improve wildlife risk assessment

“…Recent development of climate models and access to high resolution satellite imagery (e.g., Sentinel and Landsat imagery) and freely available data processing cloud‐based analytics (e.g., Google Earth Engine; https://earthengine.google.com/) mean risk assessors can more accurately identify land use and climate stressors, predict species occurrences or distributions, and model the probability of contaminant release (Beketov & Liess, 2012). For example, macroscale GIS‐based models have been applied to predict pesticide use, runoff potential, and fate in Canada's prairie wetlands that are important wildlife habitats (Malaj et al, 2020; Malaj & Morrissey, 2022). Macroecotoxicological approaches suggest promise for predicting the effects of climate change and for addressing the issues of multiple stressors from processes that occur at local and large scales.…”