Data from "Berdugo, M.; Kéfi, S.; Soliveres, S.; Maestre, F.T. Plant spatial patterns identify alternative ecosystem multifunctionality states in global drylands. Nature Ecology & Evolution 1: 0003. 2017. doi:10.1038/s41559-016-0003"
2017-01-10T12:36:56Z (GMT) by
<div>Data from the article: "Berdugo, M.; Kéfi, S.; Soliveres, S.; Maestre, F.T. Plant spatial patterns identify alternative ecosystem multifunctionality states in global drylands".</div><div><br>There are two spreadsheets with data. The spreadsheet "Data" contains the raw data at the different sampling times. The spreadsheet "Metadata" contains the associated metadata, where a description of all the variables and units can be found. All the methodological details can be found in the article.</div><div><br></div><div>Abstract:</div><div>Drylands may shift between healthy and degraded states in response to climatic changes or anthropogenic disturbances. These shifts are unannounced and difficult to reverse once they happen, thus their prompt detection is of crucial importance. The distribution of vegetation patch sizes may indicate the proximity to these shifts, but their use is hampered by the lack of large-scale studies relating them to multifunctionality (the provision of multiple ecosystem functions) and comparing them to other ecosystem attributes such as total plant cover. Here we overcome these limitations by sampling 115 dryland communities across the globe and relating their vegetation attributes (cover and patch-size distributions) to multifunctionality. This latter variable followed a bimodal distribution, which suggests contrasting multifunctionality states in global drylands. Although plant cover was most strongly related to multifunctionality, only patch-size distributions identified the bimodality found in its distribution. The uncoupling between different nutrient cycles and the loss of self-organizing biotic processes were identified as the mechanisms underlying the multifunctionality states observed. Our findings support the use of vegetation patterns as functional indicators in drylands, and pave the way for developing effective strategies to monitor desertification processes in global drylands.</div>