to assess required growing degree days (gdd) for phenological stages of four clover species in different planting dates a field experiment was conducted in 2010-11 and 2011-12 cropping seasons in seed and plant improvement institute in karaj, iran. three planting dates (14 september, 28 september and 13 october) and six clover varieties were assigned to main plots and sub-plots, respectively, a...

Accumulated growing degree-days (aGDD) are widely used to predict phenological stages of plants and insects. It has been shown in the past that the best predictive performance is obtained when aGDD are computed from hourly temperature data. As the latter are not always available, models of diurnal temperature changes are often employed to retrieve the required information from data of daily min...

Global climate change has the potential to dramatically alter multiple ecosystem processes, including herbivory. The development rates of both plants and insects are highly sensitive to temperature. Although considerable work has examined the effects of temperature on spring phenologies of plants and insects individually, few studies have examined how anticipated warming will influence their ph...

Plant phenology, a sensitive indicator of climate change, influences vegetation-atmosphere interactions by changing the carbon and water cycles from local to global scales. Camera-based phenological observations of the color changes of the vegetation canopy throughout the growing season have becomepopular in recent years. However, the linkages between camera phenological metrics and leaf bioche...

Climate change alters phenological relations between interacting species. We might expect the historical baseline, or starting-point, for such effects to be precise synchrony between the season at which a consumer most requires food and the time when its resources are most available. We synthesize evidence that synchrony was not the historical condition in two insect-plant interactions involvin...

[1] Simulations of the global water and carbon cycle are sensitive to the model representation of vegetation phenology. Current phenology models are empirical, and few predict both phenological timing and leaf state. Our previous study demonstrated how satellite data assimilation employing an Ensemble Kalman Filter yields realistic phenological model parameters for several ecosystem types. In t...