Morphological Characterization and Phenological Modeling of <i>Jatropha platyphylla</i>(Euphorbiaceae) Muell. Arg. Genotypes

Morphological characterization and phenological modeling were carried out on genotypes of Jatropha platyphylla collected from the states of Sinaloa and Durango, Mexico. The morphological characterization evidenced the existence of monoecious plants, finding individuals with male and female flowers in the same inflorescence. Fruit with four seeds was also found. The phenological study was divided into two phases and calculated in thermal requirement (°D): Vegetative [seedtime (0), germination (24), emergence (98), cotyledons (87), second (302) and fourth (524) true leaves, end of vegetative growth (302)] and reproductive [flowering (303), fructification (342), maturation (126), defoliation and senescence (450)]. The thermal constant (2558) was similar in all eight genotypes. The phenological stages and the accumulated degree days were adjusted with a third-degree polynomial (Stage = -0.0041x3 + 0.7446x2 - 8.6808x + 6.2448) (R2 = 0.99%) stage. The development of phenological models facilitates the prediction of the flowering date for the selection of varieties with high oil and protein content.

Progress in plant phenology modeling under global climate change

Plant phenology is the study of the timing of recurrent biological events and the causes of their timing with regard to biotic and abiotic forces.Plant phenology affects the structure and function of terrestrial ecosystems and determines vegetation feedback to the climate system by altering the carbon,water and energy fluxes between the vegetation and near-surface atmosphere.Therefore,an accurate simulation of plant phenology is essential to improve our understanding of the response of ecosystems to climate change and the carbon,water and energy balance of terrestrial ecosystems.Phenological studies have developed rapidly under global change conditions,while the research of phenology modeling is largely lagged.Inaccurate phenology modeling has become the primary limiting factor for the accurate simulation of terrestrial carbon and water cycles.Understanding the mechanism of phenological response to climate change and building process-based plant phenology models are thus important frontier issues.In this review,we first summarized the drivers of plant phenology and overviewed the development of plant phenology models.Finally,we addressed the challenges in the development of plant phenology models and highlighted that coupling machine learning and Bayesian calibration into process-based models could be a potential approach to improve the accuracy of phenology simulation and prediction under future global change conditions.

Species- and Community-Scale Simulation of the Phenology of a Temperate Forest in Changbai Mountain Based on Digital Camera Images

Vegetation phenology is an important parameter in models of global vegetation and land surfaces, as the accuracy of these simulations depends strongly on the description of the canopy status. Temperate forests represent one of the major types of vegetation at mid-high latitudes in the Northern Hemisphere and act as a globally important carbon sink. Thus, a better understanding of the phenological variables of temperate forests will improve the accuracy of vegetation models and estimates of regional carbon fluxes. In this work, we explored the possibility of using digital camera images to monitor phenology at species and community scales of a temperate forest in northeastern China, and used the greenness index derived from these digital images to optimize phenological model parameters. The results show that at the species scale, the onset dates of phenological phases （Korean pine, Mongolian oak） derived from the images are close to those from field observations （error 〈 3d）. At the community scale the time series data accurately reflected the observed canopy status （A^2=0.9） simulated using the phenological model, especially in autumn. The phenological model was derived from simple meteorological data and environmental factors optimized using the greenness index. These simulations provide a powerful means of analyzing environmental factors that control the phenology of temperate forests. The results indicate that digital images can be used to obtain accurate phenologicai data and provide reference data to validate remote-sensing phenological data. In addition, we propose a new method to accurately track phenological phases in land-surface models and reduce uncertainty in spatial carbon flux simulations.

The spatiotemporal characteristics of spring phenophase changes of Fraxinus chinensis in China from 1952 to 2007

We selected widely distributed and well observed plant species Fraxinus chinensis to study the formation mechanism of geographical distribution of the plant phenophase changes and revealed their spatiotemporal dynamics in China. Based on the first leaf date （FLD） data at 12 sites derived from Chinese Phenological Observation Network （CPON） and related meteoro- logical data, we developed and validated the process-based model of FLD for Fraxinus chinensis. After reconstructing data series of FLD for Fraxinus chinensis over the study area from 1952 to 2007, we analyzed different spatiotemporal patterns of phenophase changes of this species. The results suggested that the process-based model was able to simulate the FLD accu- rately for Fraxinus chinensis on large spatial and temporal scales, because of the consideration of different budding rate re- sponded to the air temperatures during the dormancy and the quiescence in accordance with the physiological mechanism of plants. The geographical distribution of the spring phenology in temperate regions was determined by the spatial pattern of daily average air temperature. The changes of FLD for Fraxinus chinensis revealed significant phenological advances in most areas. However, it showed delayed trends in a few sites. The overall average change trend was -1 .l days/decade. This result was consistent with the advanced trend in other regions of the North Hemisphere. The changes of FLD showed a noticeable regional variation with clearer advance in the north than in the south. The FLD in northern China showed an average ad- vance as high as -2.0 days/decade （P〈0.01）. And the advance in northeastern and northwestern China was respectively -1.5 and -1.4 days/decade （P〈0.01）. Furthermore, eastern and central regions showed a minor trend, which was -1.0 days/decade （P〈0.05）. The smallest and non-significant advance appeared in southwestern and southern China.

Spatio-temporal differentiation of spring phenology in China driven by temperatures and photoperiod from 1979 to 2018

Large amounts of data accumulated in ecology and related environmental sciences arouses urgent need to explore useful patterns and information in it.Here we propose coclustering-based methods and a temperatures-photoperiod driven phenological model to explore spatio-temporal differentiation in long-term spring phenology in China.First,we created the first bloom date(FBD)dataset in China from 1979 to 2018 using the extended spring indices and China Meteorological Forcing Dataset.Then we analyzed the dataset using Bregman block average co-clustering algorithm with I-divergence(BBAC_I)and kmeans algorithm.Such analysis delineated the spatially-continuous phenoregions in China for the first time.Results showed three spatial patterns of FBD in China and their temporal dynamics for 40 years(1979–2018).More specifically,overall late spring onsets occur in 1979–1996,in which areas located in Jiangxi,northern Xinjiang and middle Inner Mongolia experienced constant changing spring onsets.Overall increasingly earlier spring onsets occur in 1997–2012,in which areas located in Fujian,Hunan and eastern Heilongjiang experienced the most variable spring onsets.Stable early spring onsets over China occur after 2012.Results also showed 15 temporal patterns of spring phenology over the study period and their spatial delineation in China.More specifically,most areas in China have the same FBD category for 40 years while northern Guizhou,Hunan and southern Hubei have the same category in 1979–1997 and then fluctuate between different categories.Finally,our results have certain directive significance on the design of existing observational sites in Chinese Phenological Network.