4.8 Article

Biodiversity impacts and conservation implications of urban land expansion projected to 2050

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.2117297119

关键词

urbanization; land-use change; biodiversity; conservation

资金

  1. NSF [DEB1441737]
  2. NASA [80NSSC17K0282, 80NSSC18K0435, 80NSSC19K0638]
  3. Nature Conservancy
  4. Yale Institute for Biospheric Studies
  5. E. O. Wilson Biodiversity Foundation

向作者/读者索取更多资源

Urban land expansion is a significant driver of habitat and biodiversity loss, particularly in developing tropical regions. Strategies should be implemented to minimize the impacts of urban land and strengthen global biodiversity protection.
As the global urban population is poised to grow by 2.5 billion over the next 30 y, urban land conversions are expected to be an increasingly prominent driver of habitat and biodiversity loss. Miti-gating these impacts urgently requires an improved understand-ing of where and how these biodiversity losses might occur. Here, we use a recently developed suite of land-use projections to pro-vide an assessment of projected habitat that will be lost to urban land expansion for 30,393 species of terrestrial vertebrates from 2015 to 2050 across three shared socioeconomic pathway (SSP) scenarios. We find that urban land expansion is a contributing driver of habitat loss (>= 5% of total loss) for around one-third (26 to 39%) of the species assessed. For up to 855 species (2 to 3% of those assessed), urban land is a direct driver of species imperil-ment, driving at least one-quarter of a net habitat loss of 10% or more. Urban clusters with the greatest threats to species due to projected expansion are predominantly located in the developing tropical regions of sub-Saharan Africa, South America, Mesoamer-ica, and Southeast Asia. Our results suggest that strategies for minimizing the impacts of urban land could strengthen global biodiversity protection agreements. Collaborative, global action that focuses on vulnerable species and regions may represent an efficient strategy for avoiding the impacts forecast by our analysis.

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