TY - JOUR
T1 - Site-Specific Nutrient Data Reveal the Importance of Soils in Driving the Mycorrhizal Make-Up of Woody Vegetation Worldwide
AU - Hua, Xiaobin
AU - Lusk, Christopher H.
AU - Dickie, Ian A.
AU - Adu-Bredu, Stephen
AU - Allen, Kathryn J.
AU - Araus, Viviana
AU - Augusto, Laurent
AU - Barsukov, Pavel
AU - Bauman, David
AU - Brédoire, Félix
AU - Burslem, David F.R.P.
AU - Dalling, James W.
AU - Depauw, Leen
AU - Dexter, Kyle G.
AU - Drouet, Thomas
AU - Godlee, John L.
AU - Godoy, Roberto
AU - Gutiérrez, Rodrigo A.
AU - Muledi, Jonathan Ilunga
AU - Jacobs, Arnaud
AU - Kooyman, Robert
AU - Latorre, Claudio
AU - Angulo, Jesús López
AU - Macé, Sébastien
AU - Maes, Sybryn L.
AU - Gonçalves, Francisco Maiato Pedro
AU - Junior, Ben Hur Marimon
AU - Nicolas, Manuel
AU - Nilus, Reuben
AU - O'Brien, Michael
AU - Menor, Imma Oliveras
AU - Piper, Frida I.
AU - Read, Jennifer
AU - Reynolds, Glen
AU - Saldaña, Alfredo
AU - Marimon, Beatriz Schwantes
AU - Verheyen, Kris
AU - Westoby, Mark
AU - Wigley, Benjamin
AU - Wright, Ian J.
N1 - Funding: This work was supported by The Royal Society of New Zealand, Marsden 20-UOW-041. We thank The Royal Society of New Zealand for funding through Marsden grant 20-UOW-041 to CHL and IAD, and the referees for their constructive comments. Fifty-seven Chinese sites were provided by National Ecosystem Science Data Centre, National Science & Technology Infrastructure of China (http://www.nesdc.org.cn). Another 45 sites from five European countries were extracted from the ICP Forests database (level 1). The evaluation was based on data that was collected by partners of the official UNECE ICP Forests Network (http://icp-forests.net/contributors). Part of the data collection was co-financed by the European Commission (Data accessed on 15/06/2022). Data collection in Angola and Democratic Republic of Congo was funded by NERC grants NE/T01279X/1 and NE/P008755/1, and by National Geographic Society Grant EC-51464R-18.
We thank The Royal Society of New Zealand for funding through Marsden grant 20\u2010UOW\u2010041 to CHL and IAD, and the referees for their constructive comments. Fifty\u2010seven Chinese sites were provided by National Ecosystem Science Data Centre, National Science & Technology Infrastructure of China ( http://www.nesdc.org.cn ). Another 45 sites from five European countries were extracted from the ICP Forests database (level 1). The evaluation was based on data that was collected by partners of the official UNECE ICP Forests Network ( http://icp\u2010forests.net/contributors ). Part of the data collection was co\u2010financed by the European Commission (Data accessed on 15/06/2022). Data collection in Angola and Democratic Republic of Congo was funded by NERC grants NE/T01279X/1 and NE/P008755/1, and by National Geographic Society Grant EC\u201051464R\u201018.
PY - 2025/1
Y1 - 2025/1
N2 - Aim: Arbuscular mycorrhizas (AM) and ectomycorrhizas (ECM) have different impacts on nutrient cycling, carbon storage, community dynamics and enhancement of photosynthesis by rising CO2. Recent global analyses have concluded that patterns of AM/ECM dominance in forests worldwide are shaped by climate, with soil nutrients contributing negligible additional explanatory power. However, their reliance on nutrient data from GIS surfaces masks important local influences of parent material, topography and soil age on soil nutrient status. We asked if use of site-specific nutrient data reveals a more important role for nutrients. Time Period: Present day. Location: Global dataset comprising 703 sites, encompassing forests, savanna/woodlands, shrublands and deserts on all continents except Antarctica. Taxa Studied: Arborescent plants, including angiosperms, gymnosperms and tree ferns. Methods: Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the effects of climate variables, soil nitrogen and soil phosphorus on the proportional representation of ECM and of non-mycorrhizal species (NM) in woody vegetation. Results: GAMLSS showed a strong negative relationship of ECM representation with mean annual temperature (MAT), and a strong negative relationship with soil total nitrogen. NM representation was highest on dry sites and phosphorus-poor sites. Reanalysis showed that GIS-derived soil nutrient data had less explanatory power than site-specific nutrient data, and resulted in poorer model fits. Conclusions: Our results support the long-held belief that soil nutrients as well as climate influence the relative fitness of different mycorrhizal syndromes worldwide, and demonstrate the value of using site-specific nutrient data. Soil nutrients should be considered when predicting the impact of climate change on the mycorrhizal composition of vegetation and resulting shifts in ecosystem processes.
AB - Aim: Arbuscular mycorrhizas (AM) and ectomycorrhizas (ECM) have different impacts on nutrient cycling, carbon storage, community dynamics and enhancement of photosynthesis by rising CO2. Recent global analyses have concluded that patterns of AM/ECM dominance in forests worldwide are shaped by climate, with soil nutrients contributing negligible additional explanatory power. However, their reliance on nutrient data from GIS surfaces masks important local influences of parent material, topography and soil age on soil nutrient status. We asked if use of site-specific nutrient data reveals a more important role for nutrients. Time Period: Present day. Location: Global dataset comprising 703 sites, encompassing forests, savanna/woodlands, shrublands and deserts on all continents except Antarctica. Taxa Studied: Arborescent plants, including angiosperms, gymnosperms and tree ferns. Methods: Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the effects of climate variables, soil nitrogen and soil phosphorus on the proportional representation of ECM and of non-mycorrhizal species (NM) in woody vegetation. Results: GAMLSS showed a strong negative relationship of ECM representation with mean annual temperature (MAT), and a strong negative relationship with soil total nitrogen. NM representation was highest on dry sites and phosphorus-poor sites. Reanalysis showed that GIS-derived soil nutrient data had less explanatory power than site-specific nutrient data, and resulted in poorer model fits. Conclusions: Our results support the long-held belief that soil nutrients as well as climate influence the relative fitness of different mycorrhizal syndromes worldwide, and demonstrate the value of using site-specific nutrient data. Soil nutrients should be considered when predicting the impact of climate change on the mycorrhizal composition of vegetation and resulting shifts in ecosystem processes.
KW - aridity
KW - ectomycorrhiza
KW - non-mycorrhizal plants
KW - soil nitrogen
KW - soil phosphorus
KW - temperature
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U2 - 10.1111/geb.13936
DO - 10.1111/geb.13936
M3 - Article
AN - SCOPUS:85212066382
SN - 1466-822X
VL - 34
JO - Global Ecology and Biogeography
JF - Global Ecology and Biogeography
IS - 1
M1 - e13936
ER -