Abstract
The productivity of rainforests growing on highly weathered tropical soils is expected to be limited by phosphorus availability1. Yet, controlled fertilization experiments have been unable to demonstrate a dominant role for phosphorus in controlling tropical forest net primary productivity. Recent syntheses have demonstrated that responses to nitrogen addition are as large as to phosphorus2, and adaptations to low phosphorus availability appear to enable net primary productivity to be maintained across major soil phosphorus gradients3. Thus, the extent to which phosphorus availability limits tropical forest productivity is highly uncertain. The majority of the Amazonia, however, is characterized by soils that are more depleted in phosphorus than those in which most tropical fertilization experiments have taken place2. Thus, we established a phosphorus, nitrogen and base cation addition experiment in an old growth Amazon rainforest, with a low soil phosphorus content that is representative of approximately 60% of the Amazon basin. Here we show that net primary productivity increased exclusively with phosphorus addition. After 2 years, strong responses were observed in fine root (+29%) and canopy productivity (+19%), but not stem growth. The direct evidence of phosphorus limitation of net primary productivity suggests that phosphorus availability may restrict Amazon forest responses to CO2 fertilization4, with major implications for future carbon sequestration and forest resilience to climate change.
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Discover the latest articles, news and stories from top researchers in related subjects.Data availability
Data that support the findings of this study have been deposited in NERC Environmental Information Data Centre at https://doi.org/10.5285/b3a55011-bf46-40f5-8850-86dc8bc4c85d for root biomass, https://doi.org/10.5285/c2587e20-ba4a-4444-8ce9-ccdec15b0aa3 for tree census, https://doi.org/10.5285/c0294ec9-45d6-464c-b543-ce9ece9fd968 for litterfall production and https://doi.org/10.5285/6e70665f-b558-4949-b42a-49fbaec7e7cc for LAI. The Global Wood Density Database can be requested from https://doi.org/10.5061/dryad.234. Plot mean datasets for all response variables and AFEX plot treatment identifications are available at https://github.com/kmander7/Paper-AFEX-NPP.
Code availability
The R code used to find the best model for each variable is available in the Supplementary Material. R scripts used to generate the Supplementary Material are available at https://github.com/kmander7/Paper-AFEX-NPP.
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Acknowledgements
We thank the late Paulo Apóstolo Assunção for the botanical identification of the trees and J. Cruz, A. dos Santos and B. S. da Silva for helping in field campaigns. The authors acknowledge funding from the UK Natural Environment Research Council (NERC), grant number NE/L007223/1. This is publication 850 in the technical series of the BDFFP. C.A.Q. acknowledges the grants from Brazilian National Council for Scientific and Technological Development (CNPq) CNPq/LBA 68/2013, CNPq/MCTI/FNDCT no. 18/2021 and his productivity grant. C.A.Q., H.F.V.C., F.D.S., I.A., L.F.L., E.O.M. and S.G. acknowledge the AmazonFACE programme for financial support in cooperation with Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Institute of Amazonian Research as part of the grants CAPES-INPA/88887.154643/2017-00 and 88881.154644/2017-01. T.F.D. acknowledges funds from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grant 2015/50488-5, and the Partnership for Enhanced Engagement in Research (PEER) programme grant AID-OAA-A-11-00012. L.E.O.C.A. thanks CNPq (314416/2020-0).
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H.F.V.C., C.A.Q., I.P.H. and K.M.A. planned the study. H.F.V.C., R.D.P., A.M., M.P., J.S.R., B.B., A.L.C., S.D.C., S.T.d.S., F.A., L.S.S., G.R., R.L.d.A., A.C.S., B.T.T.P., A.C.M., L.F.L., E.O.M. and J.L.C. collected data and/or helped with project logistics. I.P.H., L.M.M., L.E.O.C.A., T.F.D., L.N., P.M. and C.A.Q. wrote the grants that funded this research. H.F.V.C., K.M.A. and I.A. organized the datasets. H.F.V.C., K.M.A., I.A. and A.M.M. conducted the statistical analyses. H.F.V.C., L.F.L., I.P.H., C.A.Q., L.M.M., S.G., I.A., K.M.A., F.D.S., T.F.D., A.L.C., P.M., R.D.P., R.L.d.A., L.E.O.C.A. and L.N. discussed the results and the structure of the paper and improved the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 Nutrient addition effects on Leaf area index.
LAI was measured over four field campaigns across treatments in a lowland forest in Central Amazon. Each panel represents mean ± 1SE LAI with (+) or without (−) the addition of specific nutrients (phosphorus addition (a); base cation addition (b); nitrogen addition (c)), based on the average LAI across the four field campaigns, n = 16 plots. No significant differences among the means were detected in linear mixed models for any of the nutrients. The dotted lines represent the mean values for the control plots (no nutrients added; n = 4 plots) for comparison purposes.
Extended Data Fig. 2 Nutrient addition effects on Leaf residence time (LRT).
Leaf residence time (yr) across treatments in a lowland forest in Central Amazon. Two separate measures of specific leaf area were used in the leaf residence time calculations based on: 1) fresh canopy leaves of common families represented across all plots sampled for a photosynthesis campaign (a-c); 2) composite leaf litter collected in the plots (d–f). Leaf residence time showed a decrease with P addition only (a, d) for both LRT estimates, with cations (b, e) and N (c, f) being shown for comparison. Means ± 1SE are presented, n = 16 plots. Linear mixed models were performed to evaluate responses in leaf residence time to added nutrients. The dotted lines represent the mean values for the control plots (no nutrients added; n = 4 plots) for comparison purposes.
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Contains supplementary information on methods, descriptive statistics, and results of linear mixed models for all response variables. Supplementary Tables 1–33.
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Cunha, H.F.V., Andersen, K.M., Lugli, L.F. et al. Direct evidence for phosphorus limitation on Amazon forest productivity. Nature 608, 558–562 (2022). https://doi.org/10.1038/s41586-022-05085-2
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DOI: https://doi.org/10.1038/s41586-022-05085-2
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