An ecological future for weed science to sustain crop production and the environment. A review

Sustainable strategies for managing weeds are critical to meeting agriculture's potential to feed the world's population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weedsat the agroecosystem levelthat, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management

Predicting Soil Organic Carbon and Total Nitrogen at the Farm Scale Using Quantitative Color Sensor Measurements

Sensor technology can be a reliable and inexpensive means of gathering soils data for soil health assessment at the farm scale. This study demonstrates the use of color system readings from the Nix ProTM color sensor (Nix Sensor Ltd., Hamilton, ON, Canada) to predict soil organic carbon (SOC) as well as total nitrogen (TN) in variable, glacial till soils at the 147 ha Cornell University Willsboro Research Farm, located in Upstate New York, USA. Regression analysis was conducted using the natural log of SOC (lnSOC) and the natural log of TN (lnTN) as dependent variables, and sample depth and color data were used as predictors for 155 air dried soil samples. Analysis was conducted for combined samples, Alfisols, and Entisols as separate sample sets and separate models were developed using depth and color variables, and color variables only. Depth and L* were significant predictors of lnSOC and lnTN for all sample sets. The color variable b* was not a significant predictor of lnSOC for any soil sample set, but it was for lnTN for all sample sets. The lnSOC prediction model for Alfisols, which included depth, had the highest R2 value (0.81, p-value < 0.001). The lnSOC model for Entisols, which contained only color variables, had the lowest R2 (0.62, p-value < 0.001). The results suggest that the Nix ProTM color sensor is an effective tool for the rapid assessment of SOC and TN content for these soils. With the accuracy and low cost of this sensor technology, it will be possible to greatly increase the spatial and temporal density of SOC and TN estimates, which is critical for soil management

Intra- and interspecific hybridization in invasive Siberian elm

Hybridization creates unique allele combinations which can facilitate the evolution of invasiveness. Frequent interspecific hybridization between the Siberian elm, Ulmus pumila, and native elm species has been detected in the Midwestern United States, Italy and Spain. However, Ulmus pumila also occurs in the western United States and Argentina, regions where no native elm species capable of hybridizing with it occurs. We examined whether inter- or intraspecific hybridization could be detected in these regions. Nuclear markers and the program STRUCTURE helped detect interspecific hybridization and determine the population genetic structure in both the native and the two non-native ranges. Chloroplast markers identified sources of introduction into these two non-native ranges. No significant interspecific hybridization was detected between U. pumila and U. rubra in the western United States or between U. pumila and U. minor in Argentina and vice versa. However, the genetic findings supported the presence of intraspecific hybridization and high levels of genetic diversity in both non-native ranges. The evidence presented for intraspecific hybridization in the current study, combined with reports of interspecific hybridization from previous studies, identifies elm as a genus where both inter- and intraspecific hybridization may occur and help maintain high levels of genetic diversity potentially associated with invasiveness

Process-based analysis of Thinopyrum intermedium phenological development highlights the importance of dual induction for reproductive growth and agronomic performance

Intermediate wheatgrass (Thinopyrum intermedium (Host) Barkworth & D.R. Dewey) is being developed for use as a new perennial grain crop through breeding and agronomic research. However, progress has been hampered by lack of understanding of environmental requirements for flowering and grain production. Therefore, we developed a phenology model for IWG adapted from the STICS soil-crop model. The model was compliant with experimental results (relative root mean square error = 0.03). The optimal vernalizing temperature was between 4 and 5°C, optimal daylength between 13 and 14h, while daylength below 11h slowed reproductive development. Vernalization requirement was found to be a constraining inductive process. Including a photoperiod limitation to the model with temperature improved its ability to predict induction at various latitudes. Therefore, timing and duration of vegetative vs. reproductive growth may differ between environments and change reproductive tiller elongation earliness, weed competitiveness, management timing, and stress conditions during phases critical to grain yield. Accurate phenology models will enable optimal field management and inform future breeding strategies. However, plasticity may lead to divergent ideotypes under various agroecosystems