Below-ground competition drives the self-thinning process ofStipa purpureapopulations in northern Tibet

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Abstract

Questions:

Above-ground, below-ground and individual mass–density relationships for perennial herbs were examined along a natural precipitation gradient in northern Tibet. We asked: (1) how do the self-thinning exponents respond to variation in precipitation; and (2) what mechanisms drive the observed population self-thinning?

Location:

The alpine grassland of northern Tibet.

Methods:

Forty-seven fenced sites along a precipitation gradient were established and surveyed in 2011 and 2012. Data (geographic coordinates, elevation, and vegetation information) were collected for Stipa purpurea populations at each site. Population self-thinning exponents were estimated using reduced major axis regression.

Results:

The self-thinning exponents for below-ground (−1.27, −0.47) and individual biomass (−1.26, −0.46) increased with increasing mean annual precipitation, but those for above-ground biomass decreased with precipitation (0.18, −0.25). Soil resources (moisture and nutrients) are a more important constraining factor for below-ground components than light is for above-ground components. Root competition for below-ground resources dominated in S. purpurea population self-thinning. The driving force of density regulation changed from above-ground competition to below-ground competition with increased drought stress. Our results indicate that an increased root/shoot ratio was linked to enhanced below-ground competition and weakened above-ground competition. Our study further confirmed the hypothesis that plant populations in different environments exhibit different biomass allocation patterns, which, in turn, leads to different biomass–density relationships.

Conclusions:

Our study revealed the mechanisms of population self-thinning for perennial herbs in the extreme environment of northern Tibet, where below-ground processes play a critical role in regulating population self-thinning. Our study also advances understanding of the interactions between above- and below-ground processes, providing baseline knowledge useful for local grassland management.

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