A mesic maximum in biological water use demarcates biome sensitivity to aridity shifts. Issue 12 (December 2017)

• Record Type: Journal Article
• Authors: Good, Stephen; Moore, Georgianne; Miralles, Diego
• Is Part Of: Nature ecology & evolution. Volume 1:Issue 12(2010)
• Page Start: 1883
• Page End: 1888
• Publication Date: 2017-12
• Subjects: Ecology -- Periodicals; Evolution (Biology) -- Periodicals; 577.05
• DOI: 10.1038/s41559-017-0371-8
• Languages: English
• ISSNs: 2397-334X

Abstract

Abstract Biome function is largely governed by how efficiently available resources can be used and yet for water, the ratio of direct biological resource use (transpiration, E T ) to total supply (annual precipitation, P ) at ecosystem scales remains poorly characterized. Here, we synthesize field, remote sensing and ecohydrological modelling estimates to show that the biological water use fraction (E T /P ) reaches a maximum under mesic conditions; that is, when evaporative demand (potential evapotranspiration, E P ) slightly exceeds supplied precipitation. We estimate that this mesic maximum inE T /P occurs at an aridity index (defined asE P /P ) between 1.3 and 1.9. The observed global average aridity of 1.8 falls within this range, suggesting that the biosphere is, on average, configured to transpire the largest possible fraction of global precipitation for the current climate. A unimodalE T /P distribution indicates that both dry regions subjected to increasing aridity and humid regions subjected to decreasing aridity will suffer declines in the fraction of precipitation that plants transpire for growth and metabolism. Given the uncertainties in the prediction of future biogeography, this framework provides a clear and concise determination of ecosystems' sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use. Field, remote sensing and ecohydrological modelling estimates provide a framework to determine ecosystem sensitivity to climatic shifts, as well as expected patterns in the amount of precipitation that ecosystems can effectively use.