Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China

2000 ◽  
Vol 44 (2) ◽  
pp. 97-101 ◽  
Author(s):  
X. Chen ◽  
Zhongjun Tan ◽  
Mark D. Schwartz ◽  
Chengxin Xu
Keyword(s):  
Satellite Data ◽  
Growing Season ◽  
Northern China ◽  
Plant Phenology

scholarly journals Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

2018 ◽  
Vol 7 (8) ◽  
pp. 290 ◽  
Author(s):  
Jun Wang ◽  
Tiancai Zhou ◽  
Peihao Peng
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Northern China ◽  
Plant Phenology ◽  
Meadow Steppe ◽  
Typical Steppe ◽  
Alpine Steppe

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals Experimental warming differentially affects vegetative and reproductive phenology of tundra plants

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Courtney G. Collins ◽  
Sarah C. Elmendorf ◽  
Robert D. Hollister ◽  
Greg H. R. Henry ◽  
Karin Clark ◽  
...  
Keyword(s):  
Growing Season ◽  
Plant Phenology ◽  
Reproductive Phenology ◽  
Ecosystem Structure ◽  
Experimental Warming ◽  
Growing Seasons ◽  
Tundra Ecosystem ◽  
Phenological Shifts ◽  
And Function ◽  
Ecosystem Structure And Function

AbstractRapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.

scholarly journals Plant Phenology and Its Anthropogenic and Natural Influencing Factors in Densely Populated Areas During the Economic Transition Period of China

2022 ◽  
Vol 9 ◽  
Author(s):  
Peijun Ju ◽  
Wenchao Yan ◽  
Jianliang Liu ◽  
Xinwei Liu ◽  
Liangfeng Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Economic Transition ◽  
Transition Period ◽  
Growing Season ◽  
Plant Phenology ◽  
Future Research ◽  
Urban Management ◽  
Climate Factors ◽  
Natural Ecosystems ◽  
The Impact

As a sensitive, observable, and comprehensive indicator of climate change, plant phenology has become a vital topic of global change. Studies about plant phenology and its responses to climate change in natural ecosystems have drawn attention to the effects of human activities on phenology in/around urban regions. The key factors and mechanisms of phenological and human factors in the process of urbanization are still unclear. In this study, we analyzed variations in xylophyta phenology in densely populated cities during the fast urbanization period of China (from 1963 to 1988). We assessed the length of the growing season affected by the temperature and precipitation. Temperature increased the length of the growing season in most regions, while precipitation had the opposite effect. Moreover, the plant-growing season is more sensitive to preseason climate factors than to annual average climate factors. The increased population reduced the length of the growing season, while the growing GDP increased the length of the growing season in most regions (8 out of 13). By analyzing the impact of the industry ratio, we found that the correlation between the urban management of emerging cities (e.g., Chongqing, Zhejiang, and Guizhou) and the growing season is more significant, and the impact is substantial. In contrast, urban management in most areas with vigorously developed heavy industry (e.g., Heilongjiang, Liaoning, and Beijing) has a weak and insignificant effect on plant phenology. These results indicate that different urban development patterns can influence urban plant phenology. Our results provide some support and new thoughts for future research on urban plant phenology.

scholarly journals Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

2018 ◽  
Vol 10 (8) ◽  
pp. 1293 ◽  
Author(s):  
Yunpeng Luo ◽  
Tarek S. El-Madany ◽  
Gianluca Filippa ◽  
Xuanlong Ma ◽  
Bernhard Ahrens ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Plant Phenology ◽  
Mediterranean Ecosystem ◽  
Near Infrared Reflectance ◽  
Seasonally Dry ◽  
Growing Season Length ◽  
Dry Down

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

scholarly journals Characteristics of Horizontal Precipitation in Semi-Humid Forestland in Northern China

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 975
Author(s):  
Jianbo Jia ◽  
Wende Yan ◽  
Xiaoyong Chen ◽  
Wenna Liu
Keyword(s):  
Growing Season ◽  
Northern China ◽  
Formation Mechanisms ◽  
Ecological Significance ◽  
Forest Land ◽  
Mountainous Areas ◽  
Humid Climate ◽  
Climate Region ◽  
Typical Day ◽  
The One

Little information is available on horizontal precipitation in forest land in semi-humid climate regions. In this study, the quantity and duration of horizontal precipitation were investigated using the high precision weighing lysimeter system in the mountainous areas of northern China during the experiment year 2011 and 2012. The purpose of this study was to better understand the formation mechanisms of horizontal precipitation in the semi-humid climate region. The results showed that hourly values of horizontal precipitation distributed between 0 and 0.1 mm, and that the one-night values distributed between 0.2 and 0.4 mm. The number of days with horizontal precipitation accounted for about 45% of the whole year. The average monthly amount of horizontal precipitation was 4.5 mm in the non-growing season, while it was a mere 1.6 mm in the growing season. The total amount of horizontal precipitation in the year was about 33 mm. Horizontal precipitation represented about 4.61% and 4.23% of the annual precipitation in 2011 and 2012. During the non-growing season, water vapor absorbed by the soil was greater than canopy and soil condensation, not only in terms of frequency, but also in the cumulated quantity. On a typical day, the canopy and soil condensation was 0.07 mm, accounting for 31.81% of total quantity of horizontal precipitation (0.22 mm). Air temperature, soil temperature and wind speed were negatively correlated with the quantity and duration of horizontal precipitation. This research could provide information for a better understanding of the ecological significance of horizontal precipitation in the semi-humid climate region in northern China.

scholarly journals Satellite-Based Observations Reveal Effects of Weather Variation on Rice Phenology

2020 ◽  
Vol 12 (9) ◽  
pp. 1522
Author(s):  
Hongfei Wang ◽  
Aniruddha Ghosh ◽  
Bruce A. Linquist ◽  
Robert J. Hijmans
Keyword(s):  
Survey Data ◽  
Ecosystem Function ◽  
Satellite Data ◽  
Growing Season ◽  
Phenological Stages ◽  
Mean Temperature ◽  
Weather Variation ◽  
Harvest Dates ◽  
Phenology Model ◽  
Rice Phenology

Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over large areas through field observations. The use of satellite remote sensing data has made phenology data collection easier, although the quality and the utility of such data to understand agro-ecosystem function have not been widely studied. Here, we evaluated satellite data-based estimates of rice phenological stages in California, USA by comparing them with survey data and with predictions by a temperature-driven phenology model. We then used the satellite data-based estimates to quantify the crop phenological response to changes in weather. We used time-series of MODIS satellite data and PhenoRice, a rule-based rice phenology detection algorithm, to determine annual planting, heading and harvest dates of paddy rice in California between 2002 and 2017. At the state level, our satellite-based estimates of rice phenology were very similar to the official survey data, particularly for planting and harvest dates (RMSE = 3.8–4.0 days). Satellite based observations were also similar to predictions by the DD10 temperature-driven phenology model. We analyzed how the timing of these phenological stages varied with concurrent temperature and precipitation over this 16-year time period. We found that planting was earlier in warm springs (−1.4 days °C−1 for mean temperature between mid-April and mid-May) and later in wet years (5.3 days 100 mm-1 for total precipitation from March to April). Higher mean temperature during the pre-heading period of the growing season advanced heading by 2.9 days °C−1 and shortened duration from planting to heading by 1.9 days °C−1. The entire growing season was reduced by 3.2 days °C−1 because of the increased temperature during the rice season. Our findings confirm that satellite data can be an effective way to estimate variations in rice phenology and can provide critical information that can be used to improve understanding of agricultural responses to weather variation.

scholarly journals The onset in spring and the end in autumn of the thermal and vegetative growing season affect calving time and reproductive success in reindeer

2019 ◽  
Vol 66 (2) ◽  
pp. 123-134 ◽  
Author(s):  
Amélie Paoli ◽  
Robert B Weladji ◽  
Øystein Holand ◽  
Jouko Kumpula
Keyword(s):  
Reproductive Success ◽  
Time Lag ◽  
Growing Season ◽  
Plant Phenology ◽  
Negative Effects ◽  
Main Hypothesis ◽  
Vegetation Growth ◽  
Growing Seasons ◽  
Finnish Lapland ◽  
Reindeer Population

Abstract A developing trophic mismatch between the peak of energy demands by reproducing animals and the peak of forage availability has caused many species’ reproductive success to decrease. The match–mismatch hypothesis (MMH) is an appealing concept that can be used to assess such fitness consequences. However, concerns have been raised on applying the MMH on capital breeders such as reindeer because the reliance on maternal capita rather than dietary income may mitigate negative effects of changing phenologies. Using a long-term dataset of reindeer calving dates recorded since 1970 in a semidomesticated reindeer population in Finnish Lapland and proxies of plant phenology; we tested the main hypothesis that the time lag between calving date and the plant phenology in autumn when females store nutrient reserves to finance reproduction would lead to consequences on reproductive success, as the time lag with spring conditions would. As predicted, the reproductive success of females of the Kutuharju reindeer population was affected by both the onset of spring green-up and vegetative senescence in autumn as calves were born heavier and with a higher first-summer survival when the onset of the vegetation growth was earlier and the end of the thermal growing season the previous year was earlier as well. Our results demonstrated that longer plant growing seasons might be detrimental to reindeer’s reproductive success if a later end is accompanied by a reduced abundance of mushrooms.

Sign in / Sign up

Export Citation Format

Share Document