Editing IPCC:AR6/WGII/Chapter-10 (section)

===== 10.4.2.1.4 Phenology, growth rate and productivity =====

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In East and North Asia, satellite measurements and ground-based observations in recent decades demonstrate either an increase in the length of plant growth season over sub-regions or in some territories in line with climate warming, or do not show any significant trend in other territories ( ''high confidence'' ). In recent decades in China, there has been an increasing trend in annual mean grassland net primary production (NPP), average leaf area index and lengthening of the local growing season ( [[#Piao--2015|Piao et al., 2015]] ; [[#Zhang--2017b|Zhang et al., 2017b]] ; [[#Xia--2019|Xia et al., 2019]] ). Nevertheless, phenology patterns vary across different studies, species and parts of China. In most regions of Northeast China, start date and length of land surface phenology from 2000 to 2015 had advanced by approximately 1 d yr −1 , except in the needle-leaf and cropland areas ( [[#Zhang--2017d|Zhang et al., 2017d]] ). For Inner Mongolia, it has been shown that neither the start of growing season (SOS) nor the end of growing season (EOS) presented detectable progressive patterns at the regional level in 1998–2012, except for the steppe–desert (6% of the total area) ( [[#Sha--2016|Sha et al., 2016]] ). In the Tianshan Mountains in China, the NPP of only 2 out of 12 types of vegetation increased in spring, and the NPP of only one type increased in autumn from 2000–2003 to 2012–2016 ( [[#Hao--2019|Hao et al., 2019]] ). In Republic of Korea, from 1970 to 2013, the SOS has advanced by 2.7 d per decade, and the EOS has been delayed by 1.4 d per decade ( [[#Jung--2015|Jung et al., 2015]] ). During the past decade, leaf unfolding has accelerated at a rate of 1.37 d yr −1 , and the timing of leaf fall has been delayed at a rate of 0.34 d yr −1 ( [[#Kim--2019d|Kim et al., 2019d]] ). Cherry blossoms are predicted to flower 6.3 and 11.2 d earlier after 2090 according to scenarios RCP4.5 and RCP8.5, respectively ( [[#Bae--2020|Bae et al., 2020]] ). On the Tibetan Plateau, it was found that the SOS has advanced and the EOS has been delayed over the past 30–40 years ( [[#Yang--2017|Yang et al., 2017]] ). Using normalised difference vegetation index (NDVI) datasets and ground-based Budburst data ( [[#Wang--2017c|Wang et al., 2017c]] ) found no consistent evidence that the SOS has been advancing or delaying over the Tibetan Plateau during the past two to three decades. The discrepancies among different studies in the trends of spring phenology over the Tibetan Plateau could be largely attributed to the use of different phenology retrieval methods. An uncertainty exists with the relationship between land-surface phenology and climate change estimated by satellite-derived NDVI because these indices are usually composite products of a number of days (e.g., 16 d) that could fail to capture more details. Besides, due to lack of ''in situ'' observations, the SOS and EOS at large areas cannot be easy defined ( [[#Zhang--2017d|Zhang et al., 2017d]] ).

In North Asia, in Central Siberia and south of West Siberia, the growth index of Siberian larch based on tree-ring width increased with the onset of warming and changed in antiphase with aridity in the 1980s ( [[#Kharuk--2018|Kharuk et al., 2018]] ). In Mongolia and Kazakhstan, the temperature increase over the previous decade promoted radial stem increment of the Siberian larch. However, the simultaneous influence of increased temperature, decreased precipitation and increased anthropogenic pressure resulted in widespread declines in forest productivity and reduced forest regeneration, and increased tree mortality ( [[#Dulamsuren--2013|Dulamsuren et al., 2013]] ; [[#Lkhagvadorj--2013a|Lkhagvadorj et al., 2013a]] ; [[#Lkhagvadorj--2013b|Lkhagvadorj et al., 2013b]] ; [[#Dulamsuren--2014|Dulamsuren et al., 2014]] ; [[#Khansaritoreh--2017|Khansaritoreh et al., 2017]] ). In Eastern Taimyr, growing season, the number of flowering shoots, annual increment, success of seed ripening and vegetation biomass have increased considerably in recent decades ( [[#Pospelova--2017|Pospelova et al., 2017]] ). In Vishera Nature Reserve, northern Ural Mountains, annual temperature has increased in recent decades in parallel with a summer temperature drop and an increase in summer frost numbers. As a result, trends in vegetation change are mostly unreliable ( [[#Prokosheva--2017|Prokosheva, 2017]] ).

In Asia, the date of arrival of migrant birds to nesting areas and the date of departure from winter areas are changing consistently with climate change ( ''medium confidence'' ). Time of arrival of the grey crow to the Lower Ob river region, northwest Siberia, shifted to earlier dates in the period 1970–2017, which is consistent with an increase in the daily average temperatures on the day of arrival ( [[#Ryzhanovskiy--2019b|Ryzhanovskiy, 2019b]] ). In Ilmen Nature Reserve, Urals, an earlier arrival of the majority of nesting bird species has not been observed in recent decades. This is explained by the fact that other factors, such as the weather of each spring month of particular years, population density in the previous nesting period, the seed yield of the main feeding plants and migration of wintering species from adjacent areas, determinate the long-term dynamics of bird arrival ( [[#Zakharov--2016|Zakharov, 2016]] ; [[#Zakharov--2018|Zakharov, 2018]] ). In Yokohama, Japan, observations since 1986 have revealed that the arrival of six winter bird species came later and the departure earlier than in the past, due to warmer temperatures ( [[#Kobori--2012|Kobori et al., 2012]] ; [[#Cohen--2018|Cohen et al., 2018]] ). Some papers corroborate that earlier start and later end of phenological events in Asia are associated with global warming; however, other papers do not confirm such a connection. Comparison and synthesis of results is impeded by usage of different metrics, measurement methods and models (e.g., [[#Hao--2019|Hao et al., 2019]] ). Relative contribution of climatic stress and other factors to phenology and plant growth trends are poorly understood (e.g., [[#Andreeva--2019|Andreeva et al., 2019]] ).

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