Seasonal, not annual precipitation drives community productivity across ecosystems

Understanding drivers of aboveground net primary production (ANPP) has long been a goal of ecology. Decades of investigation have shown total annual precipitation to be an important determinant of ANPP within and across ecosystems. Recently a few studies at individual sites have shown precipitation...

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Bibliographic Details
Published inOikos Vol. 122; no. 5; pp. 727 - 738
Main Authors Robinson, Todd M. P., La Pierre, Kimberly J., Vadeboncoeur, Matthew A., Byrne, Kerry M., Thomey, Michell L., Colby, Samantha E.
Format Journal Article
LanguageEnglish
Published Oxford, UK Blackwell Publishing Ltd 01.05.2013
Blackwell Publishing
Blackwell
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Summary:Understanding drivers of aboveground net primary production (ANPP) has long been a goal of ecology. Decades of investigation have shown total annual precipitation to be an important determinant of ANPP within and across ecosystems. Recently a few studies at individual sites have shown precipitation during specific seasons of the year can more effectively predict ANPP. Here we determined whether seasonal or total precipitation better predicted ANPP across a range of terrestrial ecosystems, from deserts to forests, using long-term data from 36 plant communities. We also determined whether ANPP responses were dependent on ecosystem type or plant functional group. We found that seasonal precipitation generally explained ANPP better than total precipitation. Precipitation in multiple parts of the growing season often correlated with ANPP, but rarely interacted with each other. Surprisingly, the amount of variation explained by seasonal precipitation was not correlated with ecosystem type or plant functional group. Overall, examining seasonal precipitation can significantly improve ANPP predictions across a broad range of ecosystems and plant types, with implications for understanding current and future ANPP variation. Further work examining precipitation timing relative to species phenology may further improve our ability to predict ANPP, especially in response to climate change.
Bibliography:istex:7B7FE5F885AEE27DDBA63B88104476A1CAE0F32A
ArticleID:OIK20655
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ISSN:0030-1299
1600-0706
DOI:10.1111/j.1600-0706.2012.20655.x