A probabilistic approach to predicting alfalfa’s winter survival using local conditions, weather and management factors

Alfalfa (Medicago sativa L.) produce relatively high yields of high-quality forage and contributes to carbon sequestration. Still, its winter survival is often lower than that of grasses, reducing plant density and field productivity. Winterkill is influenced by environmental factors (e.g., snow cover, temperature fluctuations, hardening period) and management practices (e.g., cutting time, fertilization, drainage). To assess these factors and improve persistence, this study developed a quantitative assessment tool for Canadian forage producers. A numerical simulation framework integrated soil, weather, and field management variables to evaluate yield variability and winterkill risk. Data were collected from 225 farms across Nova Scotia, Quebec, Ontario, and Manitoba using a randomized hierarchical sampling design. Soil samples were analyzed in commercial laboratories, and stem density was measured each spring and fall over three years. Descriptive statistics linking stem characteristics with soil and topographic features, weather conditions, and management practices, including soil nutrient levels, revealed a decline in mean stem counts from 49 in spring 2021 to 37 in spring 2023. To illustrate performance, weighted scores and persistence analyses were used to define model parameters across three distinct scenarios: optimal, average, and worst-case. The risk-assessment tool offers decision support to Canadian forage growers, enhancing productivity through informed management, species selection, and soil recommendations.