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- W4353035377 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> Precipitation events are becoming more intense around the world, changing the way water moves through soils and plants. Plants that have, or create, roots that absorb more water under these conditions are likely to become more abundant (e.g., shrub encroachment). Yet, it remains difficult to predict species responses to climate change because we typically do not know where active roots are located or how much water they absorb. Here, we used water tracer injections in a field experiment to describe forb, grass, and shrub root distributions under low and high precipitation intensity treatments. To estimate how much water different active rooting distributions can absorb over time, we used a soil water flow model, and we compared our estimates of water uptake to aboveground plant growth. In low precipitation intensity plots, deep shrub roots were estimated to absorb the most water (93 mm yr<sup>−1</sup>) and shrubs had the greatest aboveground cover (27 %). Grass root distributions were estimated to absorb an intermediate amount of water (80 mm yr<sup>−1</sup>) and grasses had intermediate aboveground cover (18 %). Forb root distributions were estimated to absorb the least water (79 mm yr<sup>−1</sup>) and had the least aboveground cover (12 % cover). In high precipitation intensity plots, shrub and forb roots moved in ways that increased their water uptake relative to grasses, predicting the increased aboveground growth of shrubs and forbs in these plots. In short, water uptake caused by different rooting distributions predicted plant aboveground cover. Our results suggest that detailed descriptions of active plant root distributions can predict plant growth responses to climate change in arid and semi-arid ecosystems." @default.
- W4353035377 created "2023-03-23" @default.
- W4353035377 date "2023-03-22" @default.
- W4353035377 modified "2023-10-17" @default.
- W4353035377 title "Reply on RC1" @default.
- W4353035377 doi "https://doi.org/10.5194/bg-2023-13-cc1" @default.
- W4353035377 hasPublicationYear "2023" @default.
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