Lozanovska, I., Ferreira, M.T., Aguiar, F.C. (2018) Functional diversity assessment in riparian forests – Multiple approaches and trends: a review.Ecological Indicators, 95, 781-793. DOI:10.1016/j.ecolind.2018.08.039 (IF2017 3,983; Q1 Environmental Sciences) NON-cE3c affiliated
Measures of functional diversity are increasingly being used in ecological research to understand and predict vegetation ecosystem changes. However, there is currently no summary of how, why and where these indicators have been used in riparian forest studies around the world. The present article addresses the key concepts and their evolution across time and reviews the relevance of the use and application of functional trait-based approaches in riparian forests in the last two decades (1997–2017; 70 SCI articles). Our overview contains five sections: I. Evolution of concepts, applications, and methods; II. Functional diversity measures: application in riparian forests; III. Plant functional traits: which traits, how many and why; IV. Functional diversity responses and drivers of change; and V. Future research directions. It would appear that the advances in functional diversity frameworks in the last 20 years have led to an increase in the number of studies using riparian plant guilds and functional diversity indices, with a widespread distribution across Europe and the USA. The use of easily measurable (‘soft’) traits is more prevalent than that of ‘hard traits’ consisting of direct measurements of individual processes. Specific Leaf Area (SLA), plant height, and seed mass were the most common traits used in riparian studies. The number of traits per case study varied greatly, ranging from 1 to 36 traits (median = 6), most of which were selected with the goal of describing ecosystem processes. Among the functional diversity indices, Functional Richness was the most common metric, usually coupled with indices that incorporate trait abundances such as Functional Evenness, Functional Divergence, Functional Dispersion, Rao, and Functional Redundancy. Future research should seek to integrate ecological networks and connectivity in such a way as to produce guidance with regard to trait selection, applications to large spatial scales, and comparable frameworks (guilds, index values) across regions. Novel approaches are emerging in this field of science, seeking to improve both the connection to both prevailing ecological networks and biotic and abiotic interactions.