Spatial variation and mechanisms of leaf water content in grassland plants at the biome scale: evidence from three comparative transects.

Sci Rep

Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing, 100101, China.

Published: April 2021


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Leaf water content (LWC) has important physiological and ecological significance for plant growth. However, it is still unclear how LWC varies over large spatial scale and with plant adaptation strategies. Here, we measured the LWC of 1365 grassland plants, along three comparative precipitation transects from meadow to desert on the Mongolia Plateau (MP), Loess Plateau, and Tibetan Plateau, respectively, to explore its spatial variation and the underlying mechanisms that determine this variation. The LWC data were normally distributed with an average value of 0.66 g g. LWC was not significantly different among the three plateaus, but it differed significantly among different plant life forms. Spatially, LWC in the three plateaus all decreased and then increased from meadow to desert grassland along a precipitation gradient. Unexpectedly, climate and genetic evolution only explained a small proportion of the spatial variation of LWC in all plateaus, and LWC was only weakly correlated with precipitation in the water-limited MP. Overall, the lasso variation in LWC with precipitation in all plateaus represented an underlying trade-off between structural investment and water income in plants, for better survival in various environments. In brief, plants should invest less to thrive in a humid environment (meadow), increase more investment to keep a relatively stable LWC in a drying environment, and have high investment to hold higher LWC in a dry environment (desert). Combined, these results indicate that LWC should be an important variable in future studies of large-scale trait variations.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084930PMC
http://dx.doi.org/10.1038/s41598-021-88678-7DOI Listing

Publication Analysis

Top Keywords

spatial variation
12
lwc
12
variation lwc
12
leaf water
8
water content
8
grassland plants
8
three comparative
8
meadow desert
8
lwc three
8
three plateaus
8

Similar Publications

Introduction: Pedestrian safety has become a critical concern with the rising global population of older adults. Older pedestrians face higher crash risks due to age-related physical limitations, yet road infrastructure often fails to address their specific needs. Most studies treat older adults as a single group, overlooking variations in mobility and behavior.

View Article and Find Full Text PDF

Flood pulses reshape phytoplankton richness through aggregation, density, and species abundance distribution across floodplains.

Sci Total Environ

September 2025

Programa de Pós-graduação em Ecologia de Ambientes Aquáticos Continentais (PEA/DBI), Universidade Estadual de Maringá, Maringá, Brazil; Núcleo de Pesquisas em Limnologia, Ictiologia e Aquicultura (NUPELIA)/PEA/CCB, Universidade Estadual de Maringá (UEM), Maringá, Brazil.

The flood pulse is a key driver of species distribution and richness in floodplains, yet the underlying components of its effect on species richness remain incompletely understood. We examined how three key components, namely species spatial aggregation, density, and species abundance distribution (SAD), explain seasonal variation in phytoplankton richness across multiple spatial scales. Our study encompassed 66 lakes from four Brazilian floodplains spanning approximately 2300 km across a subcontinental scale, comparing high- and low-water seasons in 2011-2012, including one dammed floodplain.

View Article and Find Full Text PDF

Spatiotemporal characteristics, drivers, sources, and health risks of nitrate and sulfate in groundwater on the Chinese Loess Plateau.

Water Res

September 2025

Key Laboratory of Groundwater Remediation of Hebei Province and China Geological Survey, Shijiazhuang, 050061, China; The Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geosciences, Shijiazhuang, 050061, China.

Groundwater nitrate (NO) and sulfate (SO) pollution in semi-arid regions has attracted widespread attention. However, unveiling the dynamics and sources of NO and SO in regional groundwater is challenging because of complex anthropogenic activities and hydrogeological conditions. This study combined physicochemistry and multiple stable isotopes (δH-HO, δO-HO, δN-NO, δO-NO, δS-SO, and δO-SO) to explore the spatiotemporal patterns, driving factors, sources, and potential health hazards of NO and SO in groundwater on the Loess Plateau, China.

View Article and Find Full Text PDF

Small glaciers situated in high mountainous areas are experiencing notable declines, characterized by unprecedented rates of ice loss in recent years. This study investigates the recent changes in surface elevation and mass loss occurring between 2010 and 2023 within the Alamkouh Glacier over three subperiods, one of the biggest glaciers in Iran and the Middle East. These assessments are derived from a combination of high-resolution LiDAR data in 2010 (with a spatial resolution of 20 cm) and multi-temporal surveys conducted using unmanned aerial vehicles (UAVs) in 2018, 2020, and 2023 (with spatial resolutions varied from 10 to 20 cm).

View Article and Find Full Text PDF

Spatial Difference-in-Differences with Bayesian Disease Mapping Models.

Epidemiology

September 2025

School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.

Bayesian disease-mapping models are widely used in small-area epidemiology to account for spatial correlation and stabilize estimates through spatial smoothing. In contrast, difference-in-differences (DID) methods-commonly used to estimate treatment effects from observational panel data-typically ignore spatial dependence. This paper integrates disease mapping models into an imputation-based DID framework to address spatially structured residual variation and improve precision in small-area evaluations.

View Article and Find Full Text PDF