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Botanical Sciences

On-line version ISSN 2007-4476Print version ISSN 2007-4298

Abstract

ZHANG, Huan et al. Population structure and quantitative characteristics of Tetracentron sinense (Trochodendraceae) in Leigong Mountain Nature Reserve, China. Bot. sci [online]. 2020, vol.98, n.1, pp.86-100.  Epub June 20, 2020. ISSN 2007-4476.  https://doi.org/10.17129/botsci.2178.

Background:

Knowledge of plant population structure facilitates conservation, management, and utilization of endangered plants.

Research question:

What is the current status of the natural populations of Tetracentron sinense in Leigong Mountain Nature Reserve (LMNR) and what future population development trends can be predicted?

Studied species:

Tetracentron sinense.

Study site and period of research:

T. sinense populations in LMNR in China in 2018.

Methods:

The population structure and quantity dynamics of four typical patches were studied using static life tables, survival curves, survival analyses, and time series analyses.

Results:

The age structures of the T. sinense populations were spindle-shaped, with few seedlings and saplings, and Deevey type II and III survival curves. The mortality rate (q x ) of each patch increased quickly, and then plateaued, finally increasing again. Survival rate (S x ) showed a contrary trend to q x . Trends in cumulative mortality rate (F (i) ), killing power (K x ), mortality density (f (ti) ), and hazard rate (λ (ti) ) with increasing age class were similar: increasing at a younger age, gradually stabilizing in middle age, and then increasing slightly in older age. The number of individuals in these T. sinense populations was predicted to decrease sharply in future, with younger individuals being seriously deficient. The results showed that the natural populations of T. sinense in the LMNR were relatively stable but were in an early stage of decline.

Conclusions:

The lack of younger individuals might reflect a bottleneck for regeneration of T. sinense populations, leading to a decline in population size.

Keywords : Population structure; static life table; survival analysis; time series analysis.

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