The plant economic spectrum (PES) predicts a suite of correlated traits in a continuum from resource conservation to rapid resource acquisition. In addition to competing for resources, plants need to cope with other environmental stresses to persist and reproduce. Yet, it is unclear how multiple strategies (i.e. traits uncorrelated with the PES) affect plant biomass allocation, hindering our ability to connect environmental gradients to ecosystem services. We examined intraspecific dimensionality of leaf and root traits in the salt marsh pioneer species Spartina anglica across salinity, redox and sand content gradients, and related them to above-ground and below-ground plant biomass—properties associated with wave attenuation and sediment stabilization in coastal marshes. Through principal component analysis, we did not find support for a single PES trait dimension (strategy), but instead identified four trait dimensions: (a) leaf economic spectrum (LES, leaf analogue of PES); (b) fine roots-rhizomes; (c) coarse roots; and (d) salt extrusion. Structural equation modelling showed a shift towards the conservative side of the LES under increasing salinity, while redox had a positive influence on the coarse roots dimension. In turn, these trait dimensions were strongly associated with above-ground and below-ground biomass (BLW biomass) allocation. These results indicate that under high salinity, plants will adopt a conservative strategy and will invest more in BLW biomass. Yet, high sediment redox would still allow plants to invest in above-ground biomass. Therefore, plants' trait-mediated biomass allocation depends on the specific combination of abiotic factors experienced at the local scale. Synthesis. Our study highlights the importance of considering multiple ecological strategies for understanding the effect of the environment on plants. Abiotic stresses can influence multiple trait strategy-dimensions, with consequences for ecosystem functioning.
Multiple trait dimensions mediate stress gradient effects on plant biomass allocation, with implications for coastal ecosystem services
De Battisti D.
;
2020
Abstract
The plant economic spectrum (PES) predicts a suite of correlated traits in a continuum from resource conservation to rapid resource acquisition. In addition to competing for resources, plants need to cope with other environmental stresses to persist and reproduce. Yet, it is unclear how multiple strategies (i.e. traits uncorrelated with the PES) affect plant biomass allocation, hindering our ability to connect environmental gradients to ecosystem services. We examined intraspecific dimensionality of leaf and root traits in the salt marsh pioneer species Spartina anglica across salinity, redox and sand content gradients, and related them to above-ground and below-ground plant biomass—properties associated with wave attenuation and sediment stabilization in coastal marshes. Through principal component analysis, we did not find support for a single PES trait dimension (strategy), but instead identified four trait dimensions: (a) leaf economic spectrum (LES, leaf analogue of PES); (b) fine roots-rhizomes; (c) coarse roots; and (d) salt extrusion. Structural equation modelling showed a shift towards the conservative side of the LES under increasing salinity, while redox had a positive influence on the coarse roots dimension. In turn, these trait dimensions were strongly associated with above-ground and below-ground biomass (BLW biomass) allocation. These results indicate that under high salinity, plants will adopt a conservative strategy and will invest more in BLW biomass. Yet, high sediment redox would still allow plants to invest in above-ground biomass. Therefore, plants' trait-mediated biomass allocation depends on the specific combination of abiotic factors experienced at the local scale. Synthesis. Our study highlights the importance of considering multiple ecological strategies for understanding the effect of the environment on plants. Abiotic stresses can influence multiple trait strategy-dimensions, with consequences for ecosystem functioning.
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