Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018
The fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysiological parameter of terrestrial ecosystems. However, due to a lack of data with adequate spatial resolution and in long enough time series, there have been limitations in exploring the spatiotemporal changes of ve...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/15/3707 |
| _version_ | 1797586127548317696 |
|---|---|
| author | Yuxin Zhang Junbang Wang Alan E. Watson |
| author_facet | Yuxin Zhang Junbang Wang Alan E. Watson |
| author_sort | Yuxin Zhang |
| collection | DOAJ |
| description | The fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysiological parameter of terrestrial ecosystems. However, due to a lack of data with adequate spatial resolution and in long enough time series, there have been limitations in exploring the spatiotemporal changes of vegetation and response to climate change. In this study, a 1 km spatial resolution and 8-day period length dataset (FPAR<sub>ANN</sub>) was developed covering the years 1980 to 2018 and evaluated on spatiotemporal change consistency by validating with Gross Primary Production (GPP) observations from the Chinese Flux Observation and Research Network (ChinaFLUX), and comparison with other FPAR products. FPAR<sub>ANN</sub> provided a comparable performance in capturing seasonal change observed through GPP, according to the coefficient of determination (<i>R</i><sup>2</sup>): 0.50, 0.51, 0.70 and 0.74 averaged for all sites, forest sites, grassland sites and cropland flux sites, respectively. The new data had more spatial similarity to the MODIS FPAR product (FPAR<sub>MCD15A2</sub>) with a greater <i>R</i><sup>2</sup> (0.77) and a lower RMSE (0.12) than other products. With a newly developed dataset, combined with FPAR<sub>ANN</sub> (1980–2003) and FPAR<sub>MCD15A2</sub> (2004–2018), an overall increasing trend in FPAR was found for over 81% of the vegetated area of China from 1980 to 2018. FPAR increased more rapidly for over 83.7% of the area in the 2010s, and at a slower pace for over 62.1% of the area in the early 2000s, which was attributed to a decadal shifting of climate change. This study implies the new dataset is useful in quantifying vegetation changes and would be an important data source for future study of the carbon cycle, soil erosion, or evapotranspiration, with great application potential. |
| first_indexed | 2024-03-11T00:18:52Z |
| format | Article |
| id | doaj.art-e8794d2cff1b4ac68128f6542b2267bf |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T00:18:52Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e8794d2cff1b4ac68128f6542b2267bf2023-11-18T23:29:45ZengMDPI AGRemote Sensing2072-42922023-07-011515370710.3390/rs15153707Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018Yuxin Zhang0Junbang Wang1Alan E. Watson2National Ecosystem Science Data Center, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaNational Ecosystem Science Data Center, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaUSDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59801, USAThe fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysiological parameter of terrestrial ecosystems. However, due to a lack of data with adequate spatial resolution and in long enough time series, there have been limitations in exploring the spatiotemporal changes of vegetation and response to climate change. In this study, a 1 km spatial resolution and 8-day period length dataset (FPAR<sub>ANN</sub>) was developed covering the years 1980 to 2018 and evaluated on spatiotemporal change consistency by validating with Gross Primary Production (GPP) observations from the Chinese Flux Observation and Research Network (ChinaFLUX), and comparison with other FPAR products. FPAR<sub>ANN</sub> provided a comparable performance in capturing seasonal change observed through GPP, according to the coefficient of determination (<i>R</i><sup>2</sup>): 0.50, 0.51, 0.70 and 0.74 averaged for all sites, forest sites, grassland sites and cropland flux sites, respectively. The new data had more spatial similarity to the MODIS FPAR product (FPAR<sub>MCD15A2</sub>) with a greater <i>R</i><sup>2</sup> (0.77) and a lower RMSE (0.12) than other products. With a newly developed dataset, combined with FPAR<sub>ANN</sub> (1980–2003) and FPAR<sub>MCD15A2</sub> (2004–2018), an overall increasing trend in FPAR was found for over 81% of the vegetated area of China from 1980 to 2018. FPAR increased more rapidly for over 83.7% of the area in the 2010s, and at a slower pace for over 62.1% of the area in the early 2000s, which was attributed to a decadal shifting of climate change. This study implies the new dataset is useful in quantifying vegetation changes and would be an important data source for future study of the carbon cycle, soil erosion, or evapotranspiration, with great application potential.https://www.mdpi.com/2072-4292/15/15/3707FPARartificial neural networkinterannual trendclimate changeterrestrial ecosystems |
| spellingShingle | Yuxin Zhang Junbang Wang Alan E. Watson Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 Remote Sensing FPAR artificial neural network interannual trend climate change terrestrial ecosystems |
| title | Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 |
| title_full | Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 |
| title_fullStr | Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 |
| title_full_unstemmed | Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 |
| title_short | Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018 |
| title_sort | rapid vegetation growth due to shifts in climate from slow to sustained warming over terrestrial ecosystems in china from 1980 to 2018 |
| topic | FPAR artificial neural network interannual trend climate change terrestrial ecosystems |
| url | https://www.mdpi.com/2072-4292/15/15/3707 |
| work_keys_str_mv | AT yuxinzhang rapidvegetationgrowthduetoshiftsinclimatefromslowtosustainedwarmingoverterrestrialecosystemsinchinafrom1980to2018 AT junbangwang rapidvegetationgrowthduetoshiftsinclimatefromslowtosustainedwarmingoverterrestrialecosystemsinchinafrom1980to2018 AT alanewatson rapidvegetationgrowthduetoshiftsinclimatefromslowtosustainedwarmingoverterrestrialecosystemsinchinafrom1980to2018 |