It is a challenge to scale‐up from simplified proxies to ecosystem functioning since the inherent complexity of natural ecosystems hinders such an approach. One way to address this complexity is to track ecosystem processes through the lens of plant functional traits. Elevational gradients with diverse biotic and abiotic conditions offer ideal settings for inferring functional trait responses to environmental gradients globally. However, most studies have focused on differences in mean trait values among species, and little is known on how intraspecific traits vary along wide elevational gradients and how this variability reflects ecosystem productivity. We measured functional traits of the sub‐shrub Koenigia mollis (Basionym: Polygonum molle; a widespread species) in 11 populations along a wide elevational gradient (1515–4216 m) considering from subtropical forest to alpine treeline in the central Himalayas. After measuring different traits (plant height, specific leaf area, leaf area, length of flowering branches, leaf carbon isotope (δ13C), leaf carbon and leaf nitrogen concentrations), we investigated drivers on changes of these traits and also characterized their relationships with elevation, climate and ecosystem productivity. All trait values decreased with increasing elevation, except for δ13C that increased upwards. Likewise, most traits showed strong positive relationships with potential evapotranspiration, while δ13C exhibited a negative relationship. In this context, elevation‐dependent water–energy dynamics is the primary driver of trait variations. Furthermore, six key traits (plant height, length of flowering branch, specific leaf area, leaf carbon, leaf nitrogen and leaf δ13C) explained 90.45% of the variance in ecosystem productivity. Our study evidences how elevation‐dependent climate variations affect ecosystem processes and functions. Intraspecific variability in leaf functional traits is strongly driven by changes in water–energy dynamics, and reflects changes in ecosystem productivity over elevation. K. mollis, with one of the widest elevational gradients known to date, could be a model species to infer functional trait responses to environmental gradients globally. As inferred from K. mollis, the water–energy dynamics can be a hydrothermal variable to understand the formation of vegetation boundaries, such as alpine treeline. This study sheds new insight on how plants modify their basic ecological strategies to cope with changing environments. Read the free Plain Language Summary for this article on the Journal blog.

The Himalayan region has already witnessed profound climate changes detectable in the cryosphere and the hydrological cycle, already resulting in drastic socio-economic impacts. We developed a 619-yea-long tree-ring-width chronology from the central Nepal Himalaya, spanning the period 1399–2017 CE. However, due to low replication of the early part of the chronology, only the section after 1600 CE was used for climate reconstruction. Proxy climate relationships indicate that temperature conditions during spring (March–May) are the main forcing factor for tree growth of Tsuga dumosa at the study site. We developed a robust climate reconstruction model and reconstructed spring temperatures for the period 1600–2017 CE. Our reconstruction showed cooler conditions during 1658–1681 CE, 1705–1722 CE, 1753–1773 CE, 1796–1874 CE, 1900–1936 CE, and 1973 CE. Periods with comparably warmer conditions occurred in 1600–1625 CE, 1633–1657 CE, 1682–1704 CE, 1740–1752 CE, 1779–1795 CE, 1936–1945 CE, 1956–1972 CE, and at the beginning of the 21st century. Tropical volcanic eruptions showed only a sporadic impact on the reconstructed temperature. Also, no consistent temperature trend was evident since 1600 CE. Our temperature reconstruction showed positive teleconnections with March–May averaged gridded temperature data for far west Nepal and adjacent areas in Northwest India and on the Southwest Tibetan plateau. We found spectral periodicities of 2.75–4 and 40–65 years frequencies in our temperature reconstruction, indicating that past climate variability in central Nepal might have been influenced by large-scale climate modes, like the Atlantic Multi-decadal Oscillation, the North Atlantic Oscillation, and the El Niño-Southern Oscillation.

Forest biomass is an important component of terrestrial carbon pools.However, how climate, biodiversity, and structural attributes co-determine spatiotemporal variation in forest biomass remains not well known. We aimed to shed light on these drivers of forest biomass by measuring diversity and structural attributes of tree species in 400-m 2 plots located every 100 m along a 4200-m elevational gradient in the eastern Himalayas. We applied structural equation models to test how climate, species richness, structural attributes, and their interactions influence forest biomass. Importantly, species richness was a stronger driver of biomass than environmental and structural attributes such as annual air temperature or stem density. Integrating the availability of energy and the demand for water, potential evapotranspiration was more strongly correlated with biomass than water availability, likely due to the strong influence of the Indian summer monsoon. Thus, interactions between climate and tree community composition ultimately control how much carbon is stored in woody biomass across bioclimatic gradients. This fundamental understanding will support predictive efforts of the forest carbon sink in this

No abstract

Studying the past glacier fluctuations during the Little Ice Age (LIA) is crucial for interpretation of climate-induced glacier changes. Thickness, flux and length changes are particularly vital, as they are the sequential changes on the glacier with changes in mass balance. In the past, the studies regarding long-term glacier fluctuations were particularly based on moraine dating in the southeastern Tibetan Plateau. However, arrays of glacier changes for each time step were not well understood. Based on the dominant role of warming temperature in glacier retreat, we hypothesized that during LIA, low temperature could have mediated the glacier fluctuation compared to precipitation. To test this hypothesis, we used three-stage linear model and simulated thickness, flux and length of the Midui glacier since 1385 CE. Our results showed that the glacier advanced during the LIA (1550-1780 CE) was controlled by temperature rather than precipitation. The simulated changes were more comparable with moraine records when both the climatic factors were considered as forcing. In the light of these findings, we concluded that the three-stage linear model was important tool to emulate the past climate driven glacier fluctuations in the southeastern Tibetan Plateau. This study may help to advance our understanding of variation in glacier behavior under ongoing warming climate.