Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States.

Journal Article (Journal Article)

The CONterminous United States (CONUS) presents a large range of climate conditions and biomes where terrestrial primary productivity and its inter-annual variability are controlled regionally by rainfall and/or temperature. Here, the response of ecosystem productivity to those climate variables was investigated across different biomes from 2010 to 2018 using three climate datasets of precipitation, air temperature or drought severity, combined with several proxies of ecosystem productivity: a remote sensing product of aboveground biomass, an net primary productivity (NPP) remote sensing product, an NPP model-based product and four gross primary productivity products. We used an asymmetry index (AI) where positive AI indicates a greater increase of ecosystem productivity in wet years compared to the decline in dry years, and negative AI indicates a greater decline of ecosystem productivity in dry years compared to the increase in wet years. We found consistent spatial patterns of AI across the CONUS for the different products, with negative asymmetries over the Great Plains and positive asymmetries over the southwestern CONUS. Shrubs and, to a lesser extent, evergreen forests show a persistent positive asymmetry, whilst (natural) grasslands appear to have transitioned from positive to negative anomalies during the last decade. The general tendency of dominant negative asymmetry response for ecosystem productivity across the CONUS appears to be influenced by the negative asymmetry of precipitation anomalies. AI was found to be a function of mean rainfall: more positive AIs were found in dry areas where plants are adapted to drought and take advantage of rainfall pulses, and more negative AIs were found in wet areas, with a threshold delineating the two regimes corresponding to a mean annual rainfall of 200-400 mm/year.

Full Text

Duke Authors

Cited Authors

  • Al-Yaari, A; Wigneron, J-P; Ciais, P; Reichstein, M; Ballantyne, A; Ogée, J; Ducharne, A; Swenson, JJ; Frappart, F; Fan, L; Wingate, L; Li, X; Hufkens, K; Knapp, AK

Published Date

  • December 2020

Published In

Volume / Issue

  • 26 / 12

Start / End Page

  • 6959 - 6973

PubMed ID

  • 32902073

Electronic International Standard Serial Number (EISSN)

  • 1365-2486

International Standard Serial Number (ISSN)

  • 1354-1013

Digital Object Identifier (DOI)

  • 10.1111/gcb.15345

Language

  • eng