Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbo...

Northern Hemisphere terrestrial ecosystems have been recognized as areas with large carbon uptake capacity and sinks and are sensitive to temperature change. However, the temperature sensitivity of ecosystem carbon uptake phenology in different biomes of northern ecosystems has not been well explored. In this study, based on our previous effort in characterizing canopy photosynthesis phenology ...

The seasonal timing of lifecycle events is closely linked to individual fitness and hence, maladaptation in phenological traits may impact population dynamics. However, few studies have analysed whether and why climate change will alter selection pressures and hence possibly induce maladaptation in phenology. To fill this gap, we here use a theoretical modelling approach. In our models, the phe...

In all organisms, phenotypic variability is an evolutionary stipulation. Because the development of poikilothermic organisms depends directly on the temperature of their habitat, environmental variability is also an integral factor in models of their phenology. In this paper we present two existing phenology models, the distributed delay model and the Sharpe and DeMichele model, and develop an ...

proportionality of wheat cultivars growth patterns to the area’s agro climatic condition will improve crop production. the objective of this study was identifying the phenology of a wide range of wheat varieties in iran, as well as evaluating the relationship between phenology and drought stress tolerance under late season drought stress. in this experiment, 36 wheat genotypes were studied unde...

Investigating forest phenology prediction is a key parameter for assessing the relationship between climate and environmental changes. Traditional machine learning models are not good at capturing long-term dependencies due to problem of vanishing gradients. In contrast, Gated Recurrent Unit (GRU) can effectively address gradients allow neural network capture longer-range dependencies. this stu...

The PhD research exposed in this paper aims to develop workflows for fine scale study of climate change and its impact on agriculture using volunteered geographic information in phenology. First, a consistency checking workflow was developed to ensure the quality of volunteered observations. Next, by using novel predictors, spatio-temporal variation in plant phenology is modeled so that we can ...

Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculel...

Prediction of wheat phenology facilitates the selection of cultivars with specific adaptations to a particular environment. However, while QTL analysis for heading date can identify major genes controlling phenology, the results are limited to the environments and genotypes tested. Moreover, while ecophysiological models allow accurate predictions in new environments, they may require substanti...