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Community environment analysis of giant panda and red panda in Wolong Nature Reserve, China
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In order to understand the community environment of giant panda and red
panda, so as to increase the understanding of their ecological evolution
and facilitate conservation and management. In our study, spatial data
monitored by infrared camera from 2017 to 2018 in Wolong, China was used
to analyze the spatial association network of terrestrial animals. The
results show that a total of 35 terrestrial species is recorded, of
which 20 species formed a spatial network including giant panda and red
panda. In the network, giant panda and red panda are directly related,
and 9 other species have direct spatial associations with them. Further
analysis show that: (1) Giant panda and red panda already ate bamboo at
the early stage of community evolution. Bamboo eating helps them blend
into the community and coexist. (2) Giant panda had moderate niche
separation with most of the species that have directly spatial
associations, the same to red panda. There is a commensalism
relationship between giant panda and red panda: red panda may create
suitable habitat for giant panda to some extent, which is beneficial to
the survival of giant panda. (3) In the existing community, giant panda
has no natural enemies, and has a mutually beneficial relationship with
golden snub-nosed monkey. (4) In the community, red panda has predator:
the yellow-throated marten. Yellow-throated marten not only preys on red
panda, but also may have evolved a unknown counter-anti-predatory
strategy to attract red panda, that can improve the chances of meeting
and preying. The red panda also moderately creates suitable habitat for
golden snub-nosed monkey, which is conducive to the survival of golden
snub-nosed monkey. (5) In the community, commensalism, mutualism, and
counter anti-predation strategies of predators enhanced inter-specific
associations significant. Compared with giant panda, red panda has more
interspecific associations and transfers more energy.
Title: Community environment analysis of giant panda and red panda in Wolong Nature Reserve, China
Description:
In order to understand the community environment of giant panda and red
panda, so as to increase the understanding of their ecological evolution
and facilitate conservation and management.
In our study, spatial data
monitored by infrared camera from 2017 to 2018 in Wolong, China was used
to analyze the spatial association network of terrestrial animals.
The
results show that a total of 35 terrestrial species is recorded, of
which 20 species formed a spatial network including giant panda and red
panda.
In the network, giant panda and red panda are directly related,
and 9 other species have direct spatial associations with them.
Further
analysis show that: (1) Giant panda and red panda already ate bamboo at
the early stage of community evolution.
Bamboo eating helps them blend
into the community and coexist.
(2) Giant panda had moderate niche
separation with most of the species that have directly spatial
associations, the same to red panda.
There is a commensalism
relationship between giant panda and red panda: red panda may create
suitable habitat for giant panda to some extent, which is beneficial to
the survival of giant panda.
(3) In the existing community, giant panda
has no natural enemies, and has a mutually beneficial relationship with
golden snub-nosed monkey.
(4) In the community, red panda has predator:
the yellow-throated marten.
Yellow-throated marten not only preys on red
panda, but also may have evolved a unknown counter-anti-predatory
strategy to attract red panda, that can improve the chances of meeting
and preying.
The red panda also moderately creates suitable habitat for
golden snub-nosed monkey, which is conducive to the survival of golden
snub-nosed monkey.
(5) In the community, commensalism, mutualism, and
counter anti-predation strategies of predators enhanced inter-specific
associations significant.
Compared with giant panda, red panda has more
interspecific associations and transfers more energy.
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