How ecological feedbacks between human population and land cover influence sustainability

Abstract : It is estimated that the Earth's biocapacity is unable to meet current demands, which begs the question: is a sustainable future possible for both humans and the environment? The UN projects a human population of approximately 11 billion by the end of the 21st century; requiring additional agricultural land, greater demands for natural resources, and technological advancements. We model human population over the next century, emphasizing feedbacks between natural and agricultural resource availability and human demography. We argue that an intensive agriculture approach to feeding the growing population is ill-conceived, without considering biodiversity and ecosystem services (e.g., nutrient cycling, pollination, water purification, pest control). The productivity of agricultural land and human population dynamics are dependent on the area of natural land-generally, tipping at 5 billion ha of natural land (approximately 40% of the Earth's terrestrial area). Furthermore, our model shows that an imprudent proactive approach (i.e., focusing on agriculture and ignoring ecosystem services) limits the success of reactive measures (i.e., restoration) in the future, while the inability to react to changes and recover natural systems leads to human population decline. Author summary There exist human population projections and models of agricultural expansion or land-use change patterns. However, the ability to combine feedbacks and concepts of population growth and land-use change into a simple dynamical model is a unique feature that allows us to firstly generate realistic predictions using resource use and demographic data. Second, evaluate alternative scenarios, predict collapse and highlight opportunities for sustainability.
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Contributor : Michel Loreau <>
Submitted on : Wednesday, November 6, 2019 - 9:05:21 AM
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Kirsten Henderson, Michel Loreau. How ecological feedbacks between human population and land cover influence sustainability. PLoS Computational Biology, Public Library of Science, 2018, 14 (8), pp.e1006389. ⟨10.1371/journal.pcbi.1006389⟩. ⟨hal-02350537⟩



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