Mapping vegetation communities requires considerable investment in field data collection, analysis and interpretation. The methods for data collection and analysis can significantly affect field time and the accuracy of the classifications. We test the ability of field data subsets and data pre-treatments to reproduce an intuitively derived vegetation classification within the Australian tropical savanna biome. The data subsets include all strata, upper strata, ground strata, and tree basal area. A range of multivariate techniques were used to describe patterns in the datasets as they related to the a priori vegetation classification. We tested the degree of floristic correlation among the data subsets and the extent to which several data transformations (square root, fourth root, presence or absence) improved the level of agreement between the numerically and the intuitively derived mapping units. Our results implied high redundancy in sampling both basal area and upper strata species cover, and the ground stratum was poorly correlated with the upper stratum. Across all statistical tests, the groups derived from analysis of square root-transformed upper stratum cover data were closely aligned with the expert classification. We propose that a numerical approach using an optimal dataset will produce a meaningful classification for vegetation mapping in poorly known Australian tropical savanna.
Rare species can play important functional roles, but human‐induced changes to disturbance regimes, such as fire, can inadvertently affect these species. We examined the influence of prescribed burns on the recruitment and diversity of plant species within a temperate forest in southeastern Australia, with a focus on species that were rare prior to burning. Floristic composition was compared among plots in landscapes before and after treatment with prescribed burns differing in the extent of area burnt and season of burn (before–after, control‐impact design). Floristic surveys were conducted before burns, at the end of a decade of drought, and 3 years postburn. We quantified the effect of prescribed burns on species grouped by their frequency within the landscape before burning (common, less common, and rare) and their life‐form attributes (woody perennials, perennial herbs or geophytes, and annual herbs). Burn treatment influenced the response of rare species. In spring‐burn plots, the recruitment of rare annual herbs was promoted, differentiating this treatment from both autumn‐burn and unburnt plots. In autumn‐burn plots, richness of rare species increased across all life‐form groups, although composition remained statistically similar to control plots. Richness of rare woody perennials increased in control plots. For all other life‐form and frequency groups, the floristic composition of landscapes changed between survey years, but there was no effect of burn treatment, suggesting a likely effect of rainfall on species recruitment. A prescribed burn can increase the occurrence of rare species in a landscape, but burn characteristics can affect the promotion of different life‐form groups and thus affect functional diversity. Drought‐breaking rain likely had an overarching effect on floristic composition during our study, highlighting that weather can play a greater role in influencing recruitment and diversity in plant communities than a prescribed burn.
Understanding the distribution of plant species and vegetation communities is important for effective conservation planning and ecosystem management, but many parts of the world remain under-surveyed. The Top End of Australia’s Northern Territory is vast, remote, and sparsely populated; knowledge of the flora, in many areas, is limited to common or dominant species. Here, we describe and contrast the benefits and trade-offs between two approaches to botanical survey – vegetation sampling (assessment of structural attributes and species composition, fundamentally for mapping purposes) and hybrid floristic survey (an intensive, inventory approach considering seasonality) – as applied in each of four remote areas of the Australian wet–dry monsoonal tropics. Hybrid floristic survey effectively doubled the species richness recorded within each study area, largely due to improved detections of forbs and sedges. Species-sampling effort relationships predicted hybrid floristic survey to consistently out-perform vegetation sampling in maximum species richness and rate of species accumulation. Although vegetation sampling offers an efficient means of circumscribing vegetation communities over large areas, hybrid floristic survey improved detection of seasonal species and, potentially, those of conservation concern. Strategic, proactive investment in hybrid floristic surveys may offer improved conservation outcomes and potential efficiency dividends in biodiversity conservation planning.
Nutrient cycling is greatly influenced by dominant plants that contribute high amounts of leaf litter to soils; however, less-dominant and rare species can play keystone roles in nutrient cycling if they have unique nutrient acquisition traits and provide high-quality litter. In many parts of the world, wildfire is likely to become more frequent and intense under a changing climate. The effect this will have on plant rarity and on species with unique nutrient acquisition traits, and thus nutrient cycling, remains poorly understood. Working within an Australian box-ironbark forest, we determined if a relationship existed between species rarity and the uniqueness of their leaf nutrient profiles, and if this relationship changed after prescribed burning. We created an index of species rarity from a data set of woody perennial species abundance in areas before and after autumn or spring burns, or left unburnt. We created indices of uniqueness for the leaf nutrient profiles of 42 woody perennial species occurring in the ecosystem, based on amounts of six macronutrients and four micronutrients found in fresh and senesced leaves of each species. Five nutrient acquisition strategies (mycorrhizal, N-fixing, carnivorous, hemiparasitic and proteoid roots) were represented in the data set. There was no community-wide relationship between rarity and uniqueness of leaf nutrient profiles, and this did not change as a result of fire. However, two hemiparasitic species were relatively rare in the ecosystem studied, and differed greatly from other species due to high K and P in senesced leaves. Thus, some of the rarest species, such as hemiparasites, can be functionally unique. Understanding the functional characteristics of rare species is important so that unique functional contributors can be identified and conserved to prevent local extinction.
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