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Emerging opportunities and challenges in phenology: a review

Tang, Jianwu; Körner, Christian; Muraoka, Hiroyuki; Piao, Shilong; Shen, Miaogen; Thackeray, Stephen J.; Yang, Xi. 2016 Emerging opportunities and challenges in phenology: a review. Ecosphere, 7 (8), e01436. 17, pp. https://doi.org/10.1002/ecs2.1436

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Abstract/Summary

Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long-term monitoring data across multiple spatial scales are needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar induced fluorescence, to assess our capability to address the importance of these scale-dependent drivers. Then we review phenology models as an important component of earth system modeling. We find that the lack of species-level knowledge and observation data lead to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for “big data” collection for plant phenology, we envision a breakthrough in process-based phenology modeling.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1002/ecs2.1436
CEH Sections/Science Areas: Parr
ISSN: 2150-8925
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: cameras, greenness, ILTER, international LTER, modelling, phenology, scale
NORA Subject Terms: Ecology and Environment
Date made live: 02 Sep 2016 14:45 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/513751

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