Copyright 2013 Tng et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
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Ecological theory differentiates rainforest and open vegetation in many regions as functionally divergent alternative stable states with transitional (ecotonal) vegetation between the two forming transient unstable states. This transitional vegetation is of considerable significance, not only as a test case for theories of vegetation dynamics, but also because this type of vegetation is of major economic importance, and is home to a suite of species of conservation significance, including the world’s tallest flowering plants. We therefore created predictions of patterns in plant functional traits that would test the alternative stable states model of these systems. We measured functional
traits of 128 trees and shrubs across tropical and temperate rainforest – open vegetation transitions in Australia, with giant eucalypt forests situated between these vegetation types. We analysed a set of functional traits: leaf carbon isotopes, leaf area, leaf mass per area, leaf slenderness, wood density, maximum height and bark thickness, using univariate and multivariate methods. For most traits, giant eucalypt forest was similar to rainforest, while rainforest, particularly tropical rainforest, was significantly different from the open vegetation. In multivariate analyses, tropical and temperate rainforest diverged functionally, and both segregated from open vegetation. Furthermore, the giant eucalypt forests overlapped in function with their respective rainforests. The two types of giant eucalypt forests also exhibited greater overall functional similarity to each other than to any of the open vegetation types. We conclude that tropical and temperate giant eucalypt forests are ecologically and functionally convergent. The lack of clear functional
differentiation from rainforest suggests that giant eucalypt forests are unstable states within the basin of attraction of rainforest. Our results have important implications for giant eucalypt forest management.