Understanding patterns and potential drivers of forest diversity in northeastern China using machine-learning algorithms

Question: Forest ecosystems are the most important
global repositories of terrestrial biodiversity. The mixed temperate forests in
northeastern China constitute one of the most biodiverse temperate regions globally
and provide nearly one-third of China’s wood supply. However, spatial patterns and potential drivers of tree species
diversity in mixed temperate forests remain poorly understood.

Location: Temperate, mixed forests of northeastern
China.

Methods: Using a large set of ground-source forest inventory
data (FIN) and geospatial covariates derived from published raster layers, we compared
different machine learning and statistical models to study spatial patterns of
tree species diversity and their underpinning drivers.

Results: The spatial distribution of tree species diversity (species richness and evenness) varied greatly across
northeastern China. Tree species
diversity varied most sensitive with climatic (annual
precipitation and annual mean temperature), topographic (elevation and slope),
and anthropogenic factors. Anthropogenic
factors affected tree species evenness
(importance value=13%) more than
tree species richness (importance value=9%). Based on these relationships, we mapped spatial patterns of tree diversity
throughout the region at a 1 km × 1 km resolution.

Conclusions: Our findings shed light on the processes behind
community assembly and biodiversity patterns, and provide a benchmark for
future assessments of forest biodiversity, as all the forested areas in China
are currently being protected from commercial harvesting under the newly
implemented China National Commercial Harvest Exclusion Policy. Our high-resolution tree species diversity maps can be
useful to landowners and land management agencies in their decision-making
processes about sustainable forest management, biodiversity conservation, and
forest restoration—a priority task outlined by the recently implemented 2050 China
National Forest Management Plan.