Summary Predictive empirical models of the timing of emergence were developed for ten major weed species in maize crops. Monitoring of seedling emergence was performed over two years in two maize fields located in Central Spain and Tagus Valley in Portugal. Thermal time was used as the independent variable for predicting cumulative emergence. Different non‐linear growth curves were fitted to the data sets of cumulative percent emergence for the different species, sites and years using genetic algorithms. Based on their emergence patterns, weed species were arranged into three groups. Species with early‐season emergence (Abutilon theophrasti, Xanthium strumarium, Datura stramonium, Datura ferox, Sorghum halepense, Digitaria sanguinalis and Echinochloa crus‐galli) reached 70% emergence with less than 700 growing day degrees (GDD). Species with whole‐season emergence (Cyperus rotundus and Solanum nigrum) started early their emergence processes but the emergence continued throughout the maize life‐cycle; they required up to 1300 GDD to reach 70% emergence. The only species with late‐season emergence was Sonchus oleraceus; it required more than 1300 GDD to reach 70% emergence. The results obtained in our experiments have shown a good synchrony between the predictions obtained in different years in the same site. However, no single model was able to predict the timing of emergence in two sites with different environmental conditions, challenging the hypothesis that a single general model, based on temperature only, can be used to predict weed emergence in different geographical locations.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. SUMMARY(1) A mathematical model for simulating the population dynamics of Avena sterilis ssp. ludoviciana (Dur.) Nyman has been constructed using previously reported data. The model considers the age structure of the population of seedlings as well as the effects of density on plant survivorship and reproduction.(2) The model is used to describe the behaviour of the population in the absence of control practices and to predict the effects of various control strategies. In the absence of control, and under continuous winter cereal cropping, the population grows hyperbolically, reaching equilibrium at a density of 535 plants m-2. Annual application of herbicides with < 85% control results in moderate reductions in the equilibrium level. To obtain a negative growth of the population it is necessary to apply herbicides annually with a control level of >90%. Fallowing the land for 1 in every 2-3 years gave a practical method of containing the populations of A. sterilis. However, to eradicate this weed it was necessary to combine crop rotation with application of herbicides.(3) The effects of changing the values of the parameters on the output of the model were generally minor. The two processes most sensitive to parameter variation were dispersal and mortality of seeds after reproduction and the fecundity of the first cohort of plants. The contribution of late emerging plants to the overall dynamics of the population was rather small and could be disregarded.(4) The model was validated by comparing simulation results with those from longterm field studies. Model predictions closely matched experimental results from herbicide trials, but gave only a crude description of the population dynamics under various crop rotations.

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Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability.