Using plant, microbe and soil fauna traits to improve the predictive power of biogeochemical models
Autor: | John E. Drake, Benjamin G. Jackson, Nil Alvarez, Sara Hortal, David W. Johnson, Richard D. Bardgett, Elizabeth M. Baggs, Jocelyn M. Lavallee, Shun Hasegawa, Mingkai Jiang, Brajesh K. Singh, Ellen L. Fry, Pete Smith, Jennifer M. Rhymes, Yolima Carrillo, Mathilde Chomel, Belinda E. Medlyn, Jonathan R. De Long, Lucía Álvarez Garrido, Ian C. Anderson, Laura Castañeda-Gómez, Marta Dondini |
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Přispěvatelé: | Terrestrial Ecology (TE), Producció Animal, Aigües Marines i Continentals |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
0106 biological sciences
Biogeochemical cycle intra- and interspecific variation Soil biology Biodiversity Climate change 010603 evolutionary biology 01 natural sciences above-belowground interactions carbon and nitrogen cycling mycorrhizae Biological sciences Ecology Evolution Behavior and Systematics biodiversity effect and response traits 2. Zero hunger Ecology 010604 marine biology & hydrobiology Ecological Modeling Plant microbe 15. Life on land climate change Work (electrical) 13. Climate action international Predictive power Environmental science community weighted means |
Zdroj: | Fry, E, De Long, J R, Garrido, L Á, Alvarez-Segura, N, Carrillo, Y, Castañeda-Gómez, L, Chomel, M, Dondini, M, Drake, J E, Hasegawa, S, Hortal, S, Jackson, B, Jiang, M, Lavallee, J M, Medlyn, B E, Rhymes, J M, Singh, B K, Smith, P, Anderson, I C, Bardgett, R D, Baggs, E & Johnson, D 2019, ' Using plant, microbe and soil fauna traits to improve the predictive power of biogeochemical models ', Methods in ecology and evolution . https://doi.org/10.1111/2041-210X.13092 Methods in Ecology and Evolution, 10(1), 146-157. John Wiley and Sons Ltd Fry, E, De Long, J, Álvarez Garrido, L, Alvarez, N, Carrillo, Y, Castañeda-Gómez, L, Chomel, M, Dondini, M, Drake, J E, Hasegawa, S, Hortal, S, Jackson, B G, Jiang, M, Lavallee, J M, Medlyn, B E, Rhymes, J, Singh, B K, Smith, P, Anderson, I C, Bardgett, R, Baggs, E M & Johnson, D 2018, ' Using plant, microbe and soil fauna traits to improve the predictive power of biogeochemical models ', Methods in Ecology and Evolution . https://doi.org/10.1111/2041-210X.13092 IRTA Pubpro. Open Digital Archive Institut de Recerca i Tecnologia Agroalimentàries (IRTA) |
ISSN: | 2041-210X |
DOI: | 10.1111/2041-210X.13092 |
Popis: | Process‐based models describing biogeochemical cycling are crucial tools to understanding long‐term nutrient dynamics, especially in the context of perturbations, such as climate and land‐use change. Such models must effectively synthesize ecological processes and properties. For example, in terrestrial ecosystems, plants are the primary source of bioavailable carbon, but turnover rates of essential nutrients are contingent on interactions between plants and soil biota. Yet, biogeochemical models have traditionally considered plant and soil communities in broad terms. The next generation of models must consider how shifts in their diversity and composition affect ecosystem processes. One promising approach to synthesize plant and soil biodiversity and their interactions into models is to consider their diversity from a functional trait perspective. Plant traits, which include heritable chemical, physical, morphological and phenological characteristics, are increasingly being used to predict ecosystem processes at a range of scales, and to interpret biodiversity–ecosystem functional relationships. There is also emerging evidence that the traits of soil microbial and faunal communities can be correlated with ecosystem functions such as decomposition, nutrient cycling, and greenhouse gas production. Here, we draw on recent advances in measuring and using traits of different biota to predict ecosystem processes, and provide a new perspective as to how biotic traits can be integrated into biogeochemical models. We first describe an explicit trait‐based model framework that operates at small scales and uses direct measurements of ecosystem properties; second, an integrated approach that operates at medium scales and includes interactions between biogeochemical cycling and soil food webs; and third, an implicit trait‐based model framework that associates soil microbial and faunal functional groups with plant functional groups, and operates at the Earth‐system level. In each of these models, we identify opportunities for inclusion of traits from all three groups to reduce model uncertainty and improve understanding of biogeochemical cycles. These model frameworks will generate improved predictive capacity of how changes in biodiversity regulate biogeochemical cycles in terrestrial ecosystems. Further, they will assist in developing a new generation of process‐based models that include plant, microbial, and faunal traits and facilitate dialogue between empirical researchers and modellers. info:eu-repo/semantics/acceptedVersion |
Databáze: | OpenAIRE |
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