Pathogen infection influences the relationship between spring and autumn phenology at the seedling and leaf level.

Seasonal life history events are often interdependent, but we know relatively little about how the relationship between different events is influenced by the abiotic and biotic environment. Such knowledge is important for predicting the immediate and evolutionary phenological response of populations to changing conditions. We manipulated germination timing and shade in a multi-factorial experiment to investigate the relationship between spring and autumn phenology in seedlings of the pedunculate oak, Quercus robur, and whether this relationship was mediated by natural colonization of leaves by specialist fungal pathogens (i.e., the oak powdery mildew complex). Each week delay in germination corresponded to about 2 days delay in autumn leaf senescence, and heavily shaded seedlings senesced 5-8 days later than seedlings in light shade or full sun. Within seedlings, leaves on primary-growth shoots senesced later than those on secondary-growth shoots in some treatments. Path analyses demonstrated that germination timing and shade affected autumn phenology both directly and indirectly via pathogen load, though the specific pattern differed among and within seedlings. Pathogen load increased with later germination and greater shade. Greater pathogen load was in turn associated with later senescence for seedlings, but with earlier senescence for individual leaves. Our findings show that relationships between seasonal events can be partly mediated by the biotic environment and suggest that these relationships may differ between the plant and leaf level. The influence of biotic interactions on phenological correlations across scales has implications for understanding phenotypic variation in phenology and for predicting how populations will respond to climatic perturbation.

Evolutionary ecology of masting: mechanisms, models, and climate change.

Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question.