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.

Differences in response of desert plants of different ecotypes to climate warming:a case study in Minqin, Northwest China

Globally climates are warming. How do desert plants of different ecotypes respond to the climate change？ This paper studied the differing responses to climate warming shown by desert plants of different ecotypes through analyzing the phenology and meteorological data of 22 desert plant species growing in Minqin Desert Bo- tanical Garden in Northwest China during the period 1974-2009. The results indicate： （1） The temperature in the study area has risen quickly since 1974, and plants＇ growing periods became longer. The spring phenology of mesophytes advanced, and the autumn phenology of xerophytes was delayed; （2） The starting dates of spring phenophase of mesophytes and xerophytes differed significantly and both showed an advancing trend; （3） The spring phenology of mesophytes advanced by more days than that of xerophytes, whereas the autumn phenology of mesophytes was delayed by less days than that of the xerophytes; and （4） Mesophytes are more sensitive than xerophytes to rising temperature in spring and falling temperature in autumn. These findings are of value in plant management and regional introduction of different species.

Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Background:Vegetation phenology research has largely focused on temperate deciduous forests,thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions.Results:Using satellite solar-induced chlorophyll fluorescence(SIF)and MODIS enhanced vegetation index(EVI)data,we applied two methods to evaluate temporal and spatial patterns of the end of the growing season(EGS)in subtropical vegetation in China,and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation.Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods(dynamic threshold method and derivative method)was later than that derived from gross primary productivity(GPP)based on the eddy covariance technique,and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks,respectively.We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation(accounting for more than 73%and 62%of the study areas,respectively),but negatively correlated with preseason maximum temperature(accounting for more than 59%of the study areas).In addition,EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors,and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests,shrub and grassland.Conclusions:Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China.We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region.These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China,and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Garden Egg (Solanum melongena L.) Performance under Different Sources of Animal Manure as a Sustainable Alternative Fertilizer for Farmers

To ensure food security, continuous intensive farming systems with limited fallowing periods and other farming systems like crop rotation have led to poor soil health with extremely low organic matter, especially in tropical regions with high organic matter mineralization. Small-scale farmers in developing countries cannot afford intensive agricultural systems with heavy chemical inputs, which have not improved soil health. Inorganic fertilizers are harmful to the environment, so farmers should use cheap, locally available organic fertilizers like animal manure, which supports organic agricultural systems and soil health. Animal manure is used as a soil amendment to improve soil health, fertility, and crop yields, but data on how different manures affect specific crops is scarce. Poultry, cattle, and goat manure were compared to no fertilizer and mineral fertilizer on garden egg phenology, vegetative growth, and yield. Poultry manure improved garden egg vegetative growth, phenology, yield, and yield components compared to the negative control and the other treatments. Poultry manure yielded the most fruit at 0.921 kg∙ha-1, followed by cattle and goat manure at 0.709 kg∙ha-1 and 0.698 kg∙ha-1. In conclusion, poultry manure may be a better alternative to synthetic NPK with yield performance similar to garden eggs and long-term soil health benefits similar to other manure sources.

An adaptive Mealy machine model for monitoring crop status

Variation in phenological stage is the major nonlinearity in monitoring, modeling and various estimations of agricultural systems. Indices are used as a common means of evaluating agricultural monitoring data from remote sensing and terrestrial observation systems, and many of these indices have linear characteristics. The analysis of and relationships between indices are dependent on the type of plant, but they are also highly variable with respect to its phenologicat stage. For this reason, variations in the phenologica! stage affect the performance of spatiotemporal crop status monitoring. We hereby propose an adaptive event-triggered model for monitoring crop status based on remote sensing data and terrestrial observations. In the proposed model, the estimation of phenological stage is a part of predicting crop status, and spatially distributed remote sensing parameters and temporal terrestrial monitoring data are used together as inputs in a state space system model. The temporal data are segmented with respect to the phenological stage-oriented timing of the spatial data, so instead of a generalized discrete state space model, we used logical states combined with analog inputs and adaptive trigger functions, as in the case of a Mealy machine model. This provides the necessary nonlinearity for the state transi- tions. The results showed that observation parameters have considerably greater significance in crop status monitoring with respect to conventional agricultural data fusion techniques.

Response of Grassland Vegetation to Air Temperature and Precipitation in Minqin Desert Region

[ Objective] This paper aims to analyze response characteristics of desert grassland vegetation to climate change. [ Method] The responses of grassland vegetation in desert region to air temperature/precipitation changes were analyzed by phenological observations since 1974, observation data conceming vegetation samples and meteorological data during the same period. The changing trend significance was denoted by linear trend line and its regression significance. The interrelation between the two variables was indicated by correlation coefficients. Data were analyzed by the software SPSS 13.0. [Result] （1） The rising rate of annual average temperature in the Minqin desert area since 1961 was greater than both the global level and Ghina＇s level over the past century. （2） Desert plants＇ response to temperature changes were mainly displayed as the advance of spring phenology, the delay of autumn phenology and the extension of growing duration. Plants＇ main response to precipitation changes was that vegetation coverage and pure coverage were decreasing along with precipitation reducing. （3） Both the vegetation coverage and pure coverage mainly had a positive correlation with the annual precipitation. Plant density mostly had a positive correlation with the precipitation in September. （4） The impact of rising temperature on plant phenology in spring was greater than that in autumn. [ Conclusion] The effects of temperature changes on desert grassland plants were the advance of spring phenology, the delay of autumn phenology, the extension of growing season and longer plant growing period than that in other reports. The responses of desert grassland vegetation to precipitation changes were that both vegetation coverage and pure coverage were decreasing along with precipitation reducing, and plant density fluctuated along with precipitation change.

Influence of peach(Prunus persica Batsch)phenological stage on the short-term changes in oxidizable and labile pools of soil organic carbon and activities of carbon-cycle enzymes in the North-Western Himalayas

The labile organic carbon(C)and C-related enzymes are sensitive indicators capturing alterations of soil organic matter(SOM),even in a short-time scale.Although the effects of crop husbandry and land use change on these attributes have been well studied,there is no consensus about how plant phenology may impact them.This study aimed to determine the short-term effect o f six distinct phenological stages(PS-1:full bloom;PS-2:fruit set;PS-3:pit hardening;PS-4:physiological maturity;PS-5:60 d after physiological maturity;and PS-6:fall)o f peach on the changes in soil organic carbon(SOC)fractions of different oxidizability,labile C pools,and C-cycle enzyme activities in soils,for two consecutive years(2015 and 2016)in the North-Western Himalayas(NWH).Peach rhizosphere soils were sampled at the topsoil(0-15 cm)and subsoil(16-30 cm)layers,along with rhizosphere soils from adjacent perennial grasses,which served as a control.Values for most of the assessed parameters,including very labile C,labile C,microbial biomass C,permanganate oxidizable C,dissolved organic C,mineralizable C,amylase activity,and carboxymethyl-cellulase activity,were significantly(P<0.05)higher at PS-3 than at other phenological stages of peach.Conversely,a sudden decline in these soil variables was recorded at PS-5,followed by a slight buildup at PS-6,particularly in the topsoil of the peach orchard.Short-term changes in organic C fractions of different oxidizability,influenced by peach phenological stage,significantly(P<0.05)affected C management index,C pool index,and lability index.Both the C management index and lability index showed their highest values at PS-3 and their lowest values at PS-5,clearly indicating short-term accretion and depletion of SOC,in tandem with the peach phenological events.Principal component analysis suggested that a composite of soil indicators,including microbial biomass C,dissolved organic C,amylase,and invertase,could help detect short-term changes in SOC content.It is concluded that peach phenological events had a major impact on the short-term variations of the studied soil variables,which could be attributed to changes in the above-and belowground plant residues,as well as the extent of nutrients and water acquisition.