Using plant, microbe, and soil fauna traits to improve the predictive power of biogeochemical models

Abstract

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.

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

“…Microbial communities are grouped into three functional types that distinguish different life-history strategies according to ecological categorizations, a technique used similarly in other models (e.g., Allison, 2012;Kaiser et al, 2015). This structure reflects fundamentally different life-history strategies according to functional-ecological frameworks such as the copiotrophy-oligotrophy continuum or Grime's competitorstress tolerator-ruderal concept (Fierer et al, 2007;Krause et al, 2014;Fierer, 2017;Ho et al, 2017;Huang et al, 2018;Fry et al, 2019;Maynard et al, 2019). The biomass of all microbial groups is regulated by growth of predators that utilize microbial pools as C and energy sources.…”

“…Including measured functional traits of plants as well as soil microorganisms and fauna in biogeochemical modeling is a promising approach to improve predictions of biogeochemical cycling in soil (Fry et al, 2019). Biogeochemical C models increasingly include metabolic and physiological traits as well as life-history strategies to account for microbial regulation of decomposition processes (Garnier et al, 2001;Ingwersen et al, 2008;Neill and Guenet, 2010;Allison, 2012;Bouskill et al, 2012;Pagel et al, 2014Pagel et al, , 2016Perveen et al, 2014;Wang et al, 2014;Le Roux et al, 2016).…”

Plant biomass, not plant economics traits, determines responses of soil CO2 efflux to precipitation in the C4 grass Panicum virgatum

“…J CO 2 is also mechanistically linked to plant size-larger plants produce more below-ground biomass (Shipley & Meziane, 2002), increasing the mass of respiring roots and litter inputs to soil C cycling. A trait-based approach to understanding the biotic controls on J CO 2 can yield insights into the links between traits and ecosystem processes (De Long et al, 2019;Fry et al, 2019). Specifically, this approach may identify covarying above-ground and below-ground traits that predict below-ground processes, but these links remain poorly understood.…”

Faculty Opinions recommendation of Robust leaf trait relationships across species under global environmental changes.

“…Recent advances have incorporated leaf trait plasticity into models for a more realistic presentation of the responses of terrestrial ecosystem to climate change 25,30 . Currently, connecting trait relationships across plants, microorganisms and animals remains a big challenge for ecology and biogeochemical modeling 63 . Our study suggests that scaling trait relationships from intra-to interspecies and even up to the community or ecosystem level 64 is an important next step to implement trait-based approaches into modeling future dynamics of the Earth system.…”