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Selecting plant species for practical restoration of degraded lands using a multiple‐trait approach
Author(s) -
Giannini Tereza C.,
Giulietti Ana M.,
Harley Raymond M.,
Viana Pedro L.,
Jaffe Rodolfo,
Alves Ronnie,
Pinto Carlos E.,
Mota Nara F. O.,
Caldeira Cecílio F.,
ImperatrizFonseca Vera L.,
Furtini Antonio E.,
Siqueira Jose O.
Publication year - 2017
Publication title -
austral ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.688
H-Index - 87
eISSN - 1442-9993
pISSN - 1442-9985
DOI - 10.1111/aec.12470
Subject(s) - ecosystem services , biodiversity , ecology , ecosystem , trait , restoration ecology , functional ecology , metric (unit) , environmental resource management , biology , geography , environmental science , computer science , programming language , operations management , economics
Ecological restoration is essential in rehabilitating degraded areas and safeguarding biodiversity, ecosystem services and human welfare. Using functional traits to plan restoration strategies has been suggested as they are the main ecological attributes that underlie ecosystem processes and services. However, few studies have translated ecological theory into actual restoration practices that can be easily used by different stakeholders. In this article, we applied a multiple‐trait approach to select plant species for the restoration of degraded lands inside the Brazilian Amazon Forests. We selected 10 traits encompassing ease of management, geographical distribution and interactions with animals and other ecosystem services and scored these traits using 118 native species. Then, we ranked all species according to the total number of traits that they exhibited to obtain a list of 53 highly ranked species. In addition, we employed non‐metric multidimensional scaling ( NMDS ) to assess the variation in these traits across the entire group of species. Based on the results, we selected a subset of species that maximizes functional diversity (high variability). We performed a sparse linear discriminant analysis ( SLDA ) to highlight a minimum set of traits to effectively discriminate botanical families. The final list of species and their traits highlight the importance of preserving not only the historical reference of a focused ecosystem but also its functional diversity to restore the interaction with local fauna, enrich the food chain and guarantee ecosystem services for local communities.