A global comparison of grassland biomass responses to CO2 and nitrogen enrichment

  1. Lookup NU author(s)
  2. Dr Peter Manning
Author(s)Lee M, Manning P, Rist J, Power SA, Marsh C
Publication type Article
JournalPhilosophical Transactions of the Royal Society Series B
Year2010
Volume365
Issue1549
Pages2047-2056
ISSN (print)0962-8452
ISSN (electronic)1471-2954
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Grassland ecosystems cover vast areas of the Earth's surface and provide many ecosystem services including carbon (C) storage, biodiversity preservation and the production of livestock forage. Predicting the future delivery of these services is difficult, because widespread changes in atmospheric CO2 concentration, climate and nitrogen (N) inputs are expected. We compiled published data from global change driver manipulation experiments and combined these with climate data to assess grassland biomass responses to CO2 and N enrichment across a range of climates. CO2 and N enrichment generally increased aboveground biomass (AGB) but effects of CO2 enrichment were weaker than those of N. The response to N was also dependent on the amount of N added and rainfall, with a greater response in high precipitation regions. No relationship between response to CO2 and climate was detected within our dataset, thus suggesting that other site characteristics, e.g. soils and plant community composition, are more important regulators of grassland responses to CO2. A statistical model of AGB response to N was used in conjunction with projected N deposition data to estimate changes to future biomass stocks. This highlighted several potential hotspots (e.g. in some regions of China and India) of grassland AGB gain. Possible benefits for C sequestration and forage production in these regions may be offset by declines in plant biodiversity caused by these biomass gains, thus necessitating careful management if ecosystem service delivery is to be maximized. An approach such as ours, in which meta-analysis is combined with global scale model outputs to make large-scale predictions, may complement the results of dynamic global vegetation models, thus allowing us to form better predictions of biosphere responses to environmental change.
PublisherThe Royal Society Publishing
URLhttp://dx.doi.org/10.1098/rstb.2010.0028
DOI10.1098/rstb.2010.0028
Actions    Link to this publication