Assessment of atmospheric heavy metal pollution in Qinghai-Tibet Plateau: Using mosses as biomonitor.

Atmospheric heavy metal (HM) pollution may pose a significant threat to the fragile ecosystem of Qinghai-Tibet Plateau (QTP). To investigate potential atmospheric HM pollution within the QTP region of China, mosses, along with other higher plants and soil, were collected from 33 sites for heavy metal measurement. The concentration ranges of Zn, Pb, Cd, and Cu in mosses were 6.07-69.9, 5.36-23.9, 0.60-1.05, and 14.4-50.5 mg·kg-1 (dry weight), respectively, significantly higher than those in other higher plants, except for Zn. The spatial distribution of relative concentrations (RCs; moss to top soil) of HMs varied considerably, indicating distinct differences in atmospheric Zn and Cu pollution levels between the northern and southern QTP. This study first reported that moderate regional atmospheric Cu pollution, primarily due to large-scale mining in recent years, had occurred, particularly in southern QTP. Pb also presented slight pollution due to anthropogenic activities. However, Cd showed almost no atmospheric pollution, while Zn concentrations were relatively high in southern QTP. Although less severe than atmospheric pollution levels in Chinese inland or coastal cities, the atmospheric pollution of Pb and Cu in QTP indicated by mosses were far more severe than global background areas, or even worse than most European cities.

Differential Investment Strategies in Leaf Economic Traits Across Climate Regions Worldwide.

The leaf economics spectrum (LES) is the leading theory of plant ecological strategies based on functional traits, which explains the trade-off between dry matter investment in leaf structure and the potential rate of resource return, revealing general patterns of leaf economic traits investment for different plant growth types, functional types, or biomes. Prior work has revealed the moderating role of different environmental factors on the LES, but whether the leaf trait bivariate relationships are shifted across climate regions or across continental scales requires further verification. Here we use the Köppen-Geiger climate classification, a very widely used and robust criterion, as a basis for classifying climate regions to explore climatic differences in leaf trait relationships. We compiled five leaf economic traits from a global dataset, including leaf dry matter content (LDMC), specific leaf area (SLA), photosynthesis per unit of leaf dry mass (Amass), leaf nitrogen concentration (Nmass), and leaf phosphorus concentration (Pmass). Moreover, we primarily used the standardized major axis (SMA) analysis to establish leaf trait bivariate relationships and to explore differences in trait relationships across climate regions as well as intercontinental differences within the same climate type. Leaf trait relationships were significantly correlated across almost all subgroups (P < 0.001). However, there was no common slope among different climate zones or climate types and the slopes of the groups fluctuated sharply up and down from the global estimates. The range of variation in the SMA slope of each leaf relationship was as follows: LDMC-SLA relationships (from -0.84 to -0.41); Amass-SLA relationships (from 0.83 to 1.97); Amass-Nmass relationships (from 1.33 to 2.25); Nmass-Pmass relationships (from 0.57 to 1.02). In addition, there was significant slope heterogeneity among continents within the Steppe climate (BS) or the Temperate humid climate (Cf). The shifts of leaf trait relationships in different climate regions provide evidence for environmentally driven differential plant investment in leaf economic traits. Understanding these differences helps to better calibrate various plant-climate models and reminds us that smaller-scale studies may need to be carefully compared with global studies.