Climatic humidity mediates the strength of the species richness-biomass relationship on the Mongolian Plateau steppe.
Sci Total Environ
; 718: 137252, 2020 May 20.
Article
in En
| MEDLINE
| ID: mdl-32325613
ABSTRACT
The relationships between biodiversity and ecosystem functioning (BEF) have been extensively studied over past decades. However, the environmental factors affecting their relationships, and how their relationships vary under the influence of environmental factors, remain controversial. Studying the BEF relationships in natural/wild environments is of great significance for devising strategies in biodiversity conservation and ecosystem functioning. Using the data from 75 sites on the Mongolian Plateau steppe, we analyzed the relationship between species richness and biomass with general linear models (GLMs) and linear mixed models (LMMs), and analyzed the variation in the species richness-biomass relationships under environmental conditions by the partial least square path modeling (PLSPM). The results showed that de Martonne aridity index affected both species richness and community biomass in parallel, and that hydrothermal coupling conditions were more important direct impact factors for aboveground biomass. However, the significant species richness-biomass relationships became weaker when the effects of environmental factors (i.e. climate and soil properties) were present. Climate humidity was the most important factor in mediating the relationship between species richness and community biomass. Our research suggested that species richness-biomass relationships are weak in the natural grasslands of the Mongolian Plateau, and that this may be due to the differences in the regional-scale environment and changes in species interactions. We recommend that a more comprehensive understanding of the relationship between diversity and biomass requires further research within broader environmental gradients.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Biomass
/
Biodiversity
Type of study:
Prognostic_studies
Language:
En
Journal:
Sci Total Environ
Year:
2020
Document type:
Article
Affiliation country:
China