Data for: Modelling the surprising recolonisation of an understudied aquatic mammal in a highly urbanised area: Fortune favored the Smooth-coated otter in Singapore
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https://datadryad.org/dataset/doi:10.5061/dryad.j3tx95xm6
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资源简介:
Ever-growing human activities present an active and continuing threat to
many species throughout the world. Nevertheless, concerted conservation
efforts in some regions have balanced these threats and allowed endangered
species to recolonise former parts of their original ranges and reverse
their decline. This is notably the case of the smooth-coated otter
(Lutrogale perspicillata). In 1998, individuals returned to Singapore
after more than a 20-year absence. In 2017, 79 otters were counted
throughout the heavily urbanized city. Despite this comeback, the future
of the species in Singapore is unclear. By collating information on the
species’ life history traits, we implemented a spatially explicit
individual-based model. The model demonstrated that successful
establishment of Singapore's population from the initial immigrants
was highly uncertain. In 43% of cases, stochastic extinction occurred.
From the 9% of model replicates that closely reproduced the observed
colonisation history, projections showed that the population would reach
close to 200 individuals in 50 years. This study successfully demonstrates
the use of individual-based modelling to simulate the inherently
stochastic recolonisation dynamics of an endangered species and predict
its longer-term future. We discuss emerging issues that may arise from
increasing negative interactions between otters and humans and the general
challenges associated with rewilding highly urbanized environments. We
stress the importance of long-term monitoring surveys and education
campaigns to mitigate human-wildlife conflicts. With species and natural
habitats increasingly threatened by our ever-growing human expansion,
understanding the factors that allow human-dominated landscapes to be
compatible with biodiversity is of the utmost importance.
提供机构:
Dryad
创建时间:
2023-08-31



