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Effects of multi-resource addition on grassland plant productivity and biodiversity along a resource gradient. | LitMetric

AI Article Synopsis

Article Abstract

The change of plant biodiversity caused by resource-enhancing global changes has greatly affected grassland productivity. However, it remains unclear how multi-resource enrichment induces the effects of multifaceted biodiversity on grassland productivity under different site resource constraints. We conducted a multiple resource addition (MRA) experiment of water and nutrients at three sites located along a resource gradient in northern China. This allowed us to assess the response of aboveground net primary productivity (ANPP), species (species richness and plant density), functional (functional richness and community-weighted mean of traits) and phylogenetic (phylogenetic richness) diversity to increasing number of MRA. We used structural equation model (SEM) to examine the direct and indirect effects of MRA and multifaceted biodiversity on ANPP. The combined addition of the four resources increased ANPP at all three sites. But with increasing number of MRA, biodiversity varied at the three sites. At the high resource constraint site, species richness, plant density and leaf nitrogen concentration (LNC) increased. At the medium resource constraint site, plant height and LNC increased, leaf dry matter content (LDMC) decreased. At the low resource constraint site, species, functional and phylogenetic richness decreased, and height increased. The SEM showed that MRA increased ANPP directly at all three sites, and indirectly by increasing plant density at the high constraint site and height at the medium constraint site. Independent of MRA, ANPP was affected by height at the high resource constraint site and LNC at the low resource constraint site. Our results illustrate that multi-resource addition positively affects productivity, while affects biodiversity depending on site resource constraint. The study highlights that site resource constraint conditions need to be taken into consideration to better predict grassland structure and function, particularly under the future multifaceted global change scenarios.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2022.159367DOI Listing

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