Diversity and density patterns of large old trees in China.
Sci Total Environ
; 655: 255-262, 2019 Mar 10.
Article
en En
| MEDLINE
| ID: mdl-30471593
ABSTRACT
Large old trees are keystone ecological structures that provide vital ecosystem services to humans. However, there are few large-scale empirical studies on patterns of diversity and density of large old trees in human-dominated landscapes. We present the results of the first nationwide study in China to investigate the patterns of diversity and density of large old trees in human-dominated landscapes. We collated data on 682,730 large trees ≥100â¯years old from 198 Chinese regions to quantify tree species diversity, tree density and maximum tree age patterns. We modelled the effects of natural environmental variables (e.g. climate and topography) and anthropogenic variables (e.g. human population density and city age) on these measures. We found a low density of large old trees across study regions (0.36â¯trees/km2), and large variation in species richness among regions (ranging from 1 to 232 species). More than 95% of trees were <500â¯years old. The best fit models showed that (1) Species diversity (species richness adjusted by region size) was positively associated with mean annual rainfall and city age; (2) Density of clustered trees, which are mostly remnants of ancient woods, was negatively influenced by human population density and rural population (% of total population). In contrast, the density of scattered trees, which are mostly managed by local people, was positively correlated with mean annual rainfall and human population density. To better protect large old trees in cities and other highly-populated areas, conservation policy should protect ancient wood remnants, mitigate the effects environmental change (e.g. habitat fragmentation), minimize the negative effects of human activities (e.g. logging), and mobilize citizens to participate in conservation activities (e.g. watering trees during droughts).
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Árboles
/
Monitoreo del Ambiente
Tipo de estudio:
Prognostic_studies
Límite:
Humans
País/Región como asunto:
Asia
Idioma:
En
Revista:
Sci Total Environ
Año:
2019
Tipo del documento:
Article
País de afiliación:
China