Water acquisition, sharing and redistribution by roots: applications to agroforestry systems

摘要

Aims In the face of problems caused by 'intensive agriculture' dominated by large areas of monocultures, mixed intercropping mimicking natural ecosystems has been reported to constitute a viable solution to increase and stabilize productivity. When designing such systems, root niche separation was thought to be a prerequisite to optimize production. Methods This paper reviews the beneficial and adverse effects of trees and crops on water acquisition and redistribution in agroforestry ecosystems using the concepts of competition and facilitation between plants in link with root functional traits. Results The results of the review showed that the reality was more complex leading agroforestry practitioners to adopt management practices to induce a separation in root activities thus avoid competition, particularly for water. Water uptake by plant roots is triggered by the water potential difference between the soil and the atmosphere when leaf stomata are open and depends largely on the root exploration capacity of the plant. Thus, root water uptake dynamics are strongly related to root-length densities and root surface areas. In addition, plants with deep roots are able to lift up or redistribute water to the upper layers through a process known as hydraulic lift, potentially acting as "bioirrigators" to adjacent plants. The redistributed water could be of importance not only in regulating plant water status, e.g. by enhancing transpiration, but also in increasing the survival and growth of associated crops in mixed systems. Conclusions Even though some more work is still needed to assess the volume of water transferred to neighbors, hydraulic lift could constitute an ecological viable mechanism to buffer against droughts and ensure productivity in regions with erratic rainfall. Giving the difficulty in measuring the above-mentioned aspects in the field, modeling of some of the most relevant parameters to quantify them might inform the design of future empirical studies.