High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China
The resistance and recovery rate of forest ecosystems to droughts vary with the severity of the drought. Studies on the impacts of severe droughts on forest ecosystems have suggested that evergreen forests have higher resistance than deciduous forests. However, whether the resistance and recovery ra...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22009426 |
| _version_ | 1797990479079407616 |
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| author | Yan Lv Honglin He Xiaoli Ren Li Zhang Keyu Qin Xiaojing Wu Zhongen Niu Lili Feng Qian Xu Mengyu Zhang |
| author_facet | Yan Lv Honglin He Xiaoli Ren Li Zhang Keyu Qin Xiaojing Wu Zhongen Niu Lili Feng Qian Xu Mengyu Zhang |
| author_sort | Yan Lv |
| collection | DOAJ |
| description | The resistance and recovery rate of forest ecosystems to droughts vary with the severity of the drought. Studies on the impacts of severe droughts on forest ecosystems have suggested that evergreen forests have higher resistance than deciduous forests. However, whether the resistance and recovery rate of forest ecosystems vary under moderate droughts remained largely unknown. Here, we used the Standardized Precipitation Index to identify drought characteristics in China’s forest ecosystems from 2000 to 2018. We quantified the resistance and recovery rate to moderate droughts under different drought timings based on the Enhanced Vegetation Index. We then adopted random forest regression to evaluate the relative importance of climatic variables and species richness as drivers of resistance and recovery rate to moderate droughts. We found that China’s forest ecosystems mainly experienced moderate drought events, resulting in different resistance and recovery rate compared to severe droughts. Deciduous forests had high resistance (30.39 ± 21.32) and evergreen forests had high recovery rate (1.38 ± 1.10) due to their different response strategies under moderate droughts. The resistance and recovery rate of China’s forest ecosystems varied under different drought timings. The differences between deciduous and evergreen forests’ resistance (43.88 – 78.24 %) and recovery rate (-31.04 – −52.20 %) were remarkable in spring, autumn, and winter. In evergreen and deciduous forests, climatic variables were the main influencing factors of resistance and recovery rate to moderate droughts, similar to the leading role of climatic variables under severe droughts. Global radiation (41.06 %) and temperature (30.97 %) were the dominant factors contributing to resistance, whereas the recovery rate was primarily explained by global radiation (40.30 %) and precipitation (27.33 %). Thus, the high resistance in deciduous forests and the high recovery rate in evergreen forests under moderate droughts suggest that evergreen and deciduous forests can be mixed to improve the stability of forest ecosystems under climate change. |
| first_indexed | 2024-04-11T08:36:04Z |
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| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-11T08:36:04Z |
| publishDate | 2022-11-01 |
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| series | Ecological Indicators |
| spelling | doaj.art-edb2680a0add4b2ead2796083921bd5d2022-12-22T04:34:19ZengElsevierEcological Indicators1470-160X2022-11-01144109469High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in ChinaYan Lv0Honglin He1Xiaoli Ren2Li Zhang3Keyu Qin4Xiaojing Wu5Zhongen Niu6Lili Feng7Qian Xu8Mengyu Zhang9Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China; Corresponding authors.Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China; Corresponding authors.Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; National Ecosystem Science Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaThe resistance and recovery rate of forest ecosystems to droughts vary with the severity of the drought. Studies on the impacts of severe droughts on forest ecosystems have suggested that evergreen forests have higher resistance than deciduous forests. However, whether the resistance and recovery rate of forest ecosystems vary under moderate droughts remained largely unknown. Here, we used the Standardized Precipitation Index to identify drought characteristics in China’s forest ecosystems from 2000 to 2018. We quantified the resistance and recovery rate to moderate droughts under different drought timings based on the Enhanced Vegetation Index. We then adopted random forest regression to evaluate the relative importance of climatic variables and species richness as drivers of resistance and recovery rate to moderate droughts. We found that China’s forest ecosystems mainly experienced moderate drought events, resulting in different resistance and recovery rate compared to severe droughts. Deciduous forests had high resistance (30.39 ± 21.32) and evergreen forests had high recovery rate (1.38 ± 1.10) due to their different response strategies under moderate droughts. The resistance and recovery rate of China’s forest ecosystems varied under different drought timings. The differences between deciduous and evergreen forests’ resistance (43.88 – 78.24 %) and recovery rate (-31.04 – −52.20 %) were remarkable in spring, autumn, and winter. In evergreen and deciduous forests, climatic variables were the main influencing factors of resistance and recovery rate to moderate droughts, similar to the leading role of climatic variables under severe droughts. Global radiation (41.06 %) and temperature (30.97 %) were the dominant factors contributing to resistance, whereas the recovery rate was primarily explained by global radiation (40.30 %) and precipitation (27.33 %). Thus, the high resistance in deciduous forests and the high recovery rate in evergreen forests under moderate droughts suggest that evergreen and deciduous forests can be mixed to improve the stability of forest ecosystems under climate change.http://www.sciencedirect.com/science/article/pii/S1470160X22009426Enhanced Vegetation IndexResistance and recovery rateModerate droughtsDrought timingChina’s forest ecosystems |
| spellingShingle | Yan Lv Honglin He Xiaoli Ren Li Zhang Keyu Qin Xiaojing Wu Zhongen Niu Lili Feng Qian Xu Mengyu Zhang High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China Ecological Indicators Enhanced Vegetation Index Resistance and recovery rate Moderate droughts Drought timing China’s forest ecosystems |
| title | High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China |
| title_full | High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China |
| title_fullStr | High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China |
| title_full_unstemmed | High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China |
| title_short | High resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in China |
| title_sort | high resistance of deciduous forests and high recovery rate of evergreen forests under moderate droughts in china |
| topic | Enhanced Vegetation Index Resistance and recovery rate Moderate droughts Drought timing China’s forest ecosystems |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22009426 |
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