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Soil microbial communities influence plant carbon cost to acquire nutrients
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Next generation ecosystem models based on a fundamental physiological trait based approach are promising. At leaf level, Eco-Evolutionary Optimality (EEO) approaches are useful as a base for these kinds of models. The tradeoff between the cost of maintaining photosynthetic capacity and the cost of transpiration in different environments can be used effectively and modelled accurately for many different environments. The utility of EEO principles in these models is based on the link between photosynthesis and Gross Primary Production (GPP). Plant available nutrients are one of the largest constraints in ecosystem productivity so recently efforts to include this in EEO theory have been made. A crucial uncertainty in current EEO theory is how the carbon cost to acquire nutrients should be parametrized and to which extend this costs is relatively conservative or changes dynamically under different environmental conditions and between species. We hypothesize that the carbon cost to acquire nutrients increases for a plant grown in a poor soil, requiring more root system to obtain a similar amount of nutrients compared to a plant grown in a rich soil. The effect of soil microbial activity on this cost is less intuitively. Plants grown in reciprocal altruistic symbiosis with mycorrhizal fungi, for example, are known to "trade" carbon for nutrients or water, altering this carbon cost. Soil microbial pathogens can be costly from a plants perspective without any gain, but a generic representation is not yet incorporated in the optimality framework.To test this hypothesis, we conducted a greenhouse pot experiment with two plant species grown in three different nutrient treatments in sand, and compared them to plants of the same species grown in either natural soil or sterilized soil, both without additional nutrient treatment. The plant available nitrogen (N) and phosphorus (P) in the middle nutrient treatment were set to correspond closely to the available nutrients in the natural and sterilized soilsInitial results show a positive correlation between photosynthetic capacity at leaf level and total plant dry weight (DW), both increasing with increasing nutrient availability in sand. In soils however, leaf level photosynthetic capacity and total plant DW react in opposite directions when comparing natural versus sterilized soils. Total plant DW was high in sterilized soils with a relatively low leaf level photosynthetic capacity, while the opposite was found in natural soils. Elemental analyses will be used to (I) analyse carbon allocated to root systems and the correlation with whole plant nitrogen and (I) to extrapolate leaf level photosynthetic capacity to whole plant photosynthetic capacity and examine the relation between plant photsynthetic capacity and total plant DW.Investigating plant carbon allocation under varying soil environments could provide a link between the well formulated leaf level EEO theory and the more cryptic soil influences.
Title: Soil microbial communities influence plant carbon cost to acquire nutrients
Description:
Next generation ecosystem models based on a fundamental physiological trait based approach are promising.
At leaf level, Eco-Evolutionary Optimality (EEO) approaches are useful as a base for these kinds of models.
The tradeoff between the cost of maintaining photosynthetic capacity and the cost of transpiration in different environments can be used effectively and modelled accurately for many different environments.
The utility of EEO principles in these models is based on the link between photosynthesis and Gross Primary Production (GPP).
Plant available nutrients are one of the largest constraints in ecosystem productivity so recently efforts to include this in EEO theory have been made.
A crucial uncertainty in current EEO theory is how the carbon cost to acquire nutrients should be parametrized and to which extend this costs is relatively conservative or changes dynamically under different environmental conditions and between species.
We hypothesize that the carbon cost to acquire nutrients increases for a plant grown in a poor soil, requiring more root system to obtain a similar amount of nutrients compared to a plant grown in a rich soil.
The effect of soil microbial activity on this cost is less intuitively.
Plants grown in reciprocal altruistic symbiosis with mycorrhizal fungi, for example, are known to "trade" carbon for nutrients or water, altering this carbon cost.
Soil microbial pathogens can be costly from a plants perspective without any gain, but a generic representation is not yet incorporated in the optimality framework.
To test this hypothesis, we conducted a greenhouse pot experiment with two plant species grown in three different nutrient treatments in sand, and compared them to plants of the same species grown in either natural soil or sterilized soil, both without additional nutrient treatment.
The plant available nitrogen (N) and phosphorus (P) in the middle nutrient treatment were set to correspond closely to the available nutrients in the natural and sterilized soilsInitial results show a positive correlation between photosynthetic capacity at leaf level and total plant dry weight (DW), both increasing with increasing nutrient availability in sand.
In soils however, leaf level photosynthetic capacity and total plant DW react in opposite directions when comparing natural versus sterilized soils.
Total plant DW was high in sterilized soils with a relatively low leaf level photosynthetic capacity, while the opposite was found in natural soils.
Elemental analyses will be used to (I) analyse carbon allocated to root systems and the correlation with whole plant nitrogen and (I) to extrapolate leaf level photosynthetic capacity to whole plant photosynthetic capacity and examine the relation between plant photsynthetic capacity and total plant DW.
Investigating plant carbon allocation under varying soil environments could provide a link between the well formulated leaf level EEO theory and the more cryptic soil influences.
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