Enhanced understanding of soil disturbance effects on weed seedling recruitment will help guide improved management approaches. Field experiments were conducted at 16 site-years at 10 research farms across Europe and North America to (i) quantify superficial soil disturbance (SSD) effects on Chenopodium album emergence and (ii) clarify adaptive emergence behaviour in frequently disturbed environments. Each site-year contained factorial combinations of two seed populations (local and common, with the common population studied at all site-years) and six SSD timings [0, 50, 100, 150, 200 day-degrees (d°C, base temperature 3°C) after first emergence from undisturbed soil]. Analytical units in this study were emergence flushes. Flush magnitudes (maximum weekly emergence per count flush) and flush frequencies (flushes year −1 ) were compared between disturbed and undisturbed seedbanks. One year after burial, SSD promoted seedling emergence relative to undisturbed seedbanks by increasing flush magnitude rather than increasing flush frequency. Two years after burial, SSD promoted emergence through increased flush magnitude and flush frequency. The promotional effects of SSD on emergence were strongest within 500 d°C following SSD; however, low levels of SSD-induced emergence were detected as late as 3000 d°C following SSD. Accordingly, stale seedbed practices that eliminate weed seedlings should occur within 500 d°C of disturbance, because few seedlings emerge after this time. However, implementation of stale seedbed practices will probably cause slight increases in weed population densities throughout the year. Compared with the common population, local populations exhibited reduced variance in total emergence measured within sites and across SSD treatments, suggesting that C. album adaptation to local pedo-climatic conditions involves increased consistency in SSD-induced emergence. SummaryEnhanced understanding of soil disturbance effects on weed seedling recruitment will help guide improved management approaches. Field experiments were conducted at 16 site-years at 10 research farms across Europe and North America to (i) quantify superficial soil disturbance (SSD) effects on Chenopodium album emergence and (ii) clarify adaptive emergence behaviour in frequently disturbed environments. Each site-year contained factorial combinations of two seed populations (local and common, with the common population studied at all site-years) and six SSD timings [0, 50, 100, 150, 200 day-degrees (d°C, base temperature 3°C) after first emergence from undisturbed soil]. Analytical units in this study were emergence flushes. Flush magnitudes (maximum weekly emergence per count flush) and flush frequencies (flushes year À1 ) were compared between disturbed and undisturbed seedbanks. One year after burial, SSD promoted seedling emergence relative to undisturbed seedbanks by increasing flush magnitude rather than increasing flush frequency. Two years after burial, SSD promoted emergence through increased flush magnitude and flu...

As weather patterns become more volatile and extreme, risks introduced by weather variability will become more critical to agricultural production. The availability of days suitable for field work is driven by soil temperature and moisture, both of which may be altered by climate change. We projected changes in Illinois season length, spring field workability, and summer drought risk under three different emissions scenarios (B1, A1B, and A2) down to the crop district scale. Across all scenarios, thermal time units increased in parallel with a longer frost-free season. An increase in late March and Early April field workability was consistent across scenarios, but a decline in overall April through May workable days was observed for many cases. In addition, summer drought metrics were projected to increase for most scenarios. These results highlight how the spatial and temporal variability in climate change may present unique challenges to mitigation and adaptation efforts.

Improved prediction of the days available for field work, or field working days (FWDs), is an important consideration for adapting farming systems to increased weather variability. We developed modeling approaches to estimate robust soil moisture thresholds for FWDs. We used simulated soil moisture to train the model on the same type of data that would be used for FWD forecasting (prediction). These new models were tested against previously suggested thresholds for field workability. Model 1 used historical field work and weather records from three crop research centers in a logistic regression model. A soil moisture threshold of 1.10 times the plastic limit (1.10PL) was identified. Model 2 identified statewide soil moisture and temperature thresholds by optimizing the root mean square error of the predicted number of weekly statewide FWDs across a 52‐yr data set. The resulting thresholds of either 0.88PL or 0.73FC (field capacity) and an average temperature requirement of at least 6°C yielded statistically smaller absolute errors for the state average FWDs and in eight of the nine crop reporting districts. The Model 2 thresholds also eliminated systematic overprediction present in previous thresholds. These results demonstrate that immutable theoretical thresholds for FWDs based on field‐measured soil moisture can be suboptimal for prediction at a larger spatial scale due to consistent bias.