Affecting soil microenvironments due to differences in soil porosity, bulk density and soil surface conditions. Thus, minimum tillage provides less moisture conservation than no tillage and plants under this tillage system would need additional moisture provided by Publications Using Abomle LY294002 climate factors, especially in a semi-arid climate. It is interesting to note that the predictive Neratinib Abmole Chemical Proteomics Reveals Ferrochelatase as a Common Off-target of Kinase Inhibitors capacity of model 23 was similar whether or not it included NAO. Our results indicated that D. sophia presented low sensitivity to local climate effects, such as precipitation and temperature. These results are surprising because local climate factors are considered to be determinant in weed emergence. This is especially true in Mediterranean climates, where water availability is the most important environmental constraint, due to the combination of high summer temperatures and low rainfall. In contrast to the environmental independence of models of D. sophia population dynamics, the pure endogenous model for V. hederifolia per capita growth rates explained less than 49% of the variability in both the no-tillage and minimum tillage systems. Population dynamics of V. hederifolia seemed to be driven mainly by climate factors. Large-scale and local scale exogenous factors had a different role in the growth rates of this species. Under no tillage the main driving force was the local weather. Regarding the minimum tillage system, NAO seemed to have the main role. It was noticeable that the importance of NAO was higher in the minimum tillage system for both species. However, the best predictions are from the model including winter temperature and rainfall fitted to the minimum tillage system and used to predict no-tillage data. In contrast, models fitted to the no-tillage system did not predict the data from minimum tillage system very well. One potential explanation for this pattern is that no-tillage system appears to be more influenced by exogenous variables. Therefore the parameter values from models fitted on data from this system can have more source of unknown variation. Two different patterns emerge from our results. On the one hand, exogenous factors seem to mainly influence the population dynamics of V. hederifolia, in agreement with the general view in weed science. On the other hand, endogenous factors seem to be the main driver of the population dynamics of D. sophia. The use of this approach, discerning between the roleof exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and controlling invasive weedy species. This approach signifies a radical change relative to most approaches currently used to guide weed management.