Assessing the vulnerability of plant functional trait strategies to climate change

Aim: Our ability to understand how species may respond to changing climate conditions is hampered by a lack of high-quality data on the adaptive capacity of species. Plant functional traits are linked to many aspects of species life history and adaptation to environment, with different combinations of trait values reflecting alternate strategies for adapting to varied conditions. If the realized climate limits of species can be partially explained by plant functional trait combinations, then a new approach of using trait combinations to predict the expected climate limits of species trait combinations may offer considerable benefits. Location: Australia. Time period: Current and future. Methods: Using trait data for leaf size, seed mass and plant height for 6,747 Australian native species from 27 plant families, we model the expected climate limits of trait combinations and use future climate scenarios to estimate climate change impacts based on plant functional trait strategies. Results: Functional trait combinations were a significant predictor of species climate niche metrics with potentially meaningful relationships with two rainfall variables (R2 =.36 &.45) and three temperature variables (R2 =.21,.28,.30). Using this method, the proportion of species exposed to conditions across their range that are beyond the expected climate limits of their trait strategies will increase under climate change. Main conclusions: Our new approach, called trait strategy vulnerability, includes three new metrics. For example, the climate change vulnerability (CCV) metric identified a small but important proportion of species (4.3%) that will on average be exposed to conditions beyond their expected limits for summer temperature in the future. These potentially vulnerable species could be high priority targets for deeper assessment of adaptive capacity at the genomic or physiological level. Our methods can be applied to any suite of co-occurring plants globally

Patterns and drivers of plant diversity across Australia

Biodiversity analyses across continental extents are important in providing comprehensive information on patterns and likely drivers of diversity. For vascular plants in Australia, community-level diversity analyses have been restricted by the lack of a consistent plot-based survey dataset across the continent. To overcome these challenges, we collated and harmonised plot-based vegetation survey data from the major data sources across Australia and used them as the basis for modelling species richness (α-diversity) and community compositional dissimilarity (β-diversity), standardised to 400 m2, with the aim of mapping diversity patterns and identifying potential environmental drivers. The harmonised Australian vegetation plot (HAVPlot) dataset includes 219 552 plots, of which we used 115 083 to analyse plant diversity. Models of species richness and compositional dissimilarity both explained approximately one-third of the variation in plant diversity across Australia (D2 = 33.0% and 32.7%, respectively). The strongest environmental predictors for both aspects of diversity were a combination of temperature and precipitation, with soil texture and topographic heterogeneity also important. The fine-resolution (≈ 90 m) spatial predictions of species richness and compositional dissimilarity identify areas expected to be of particular importance for plant diversity, including south-western Australia, rainforests of eastern Australia and the Australian Alps. Arid areas of central and western Australia are predicted to support assemblages that are less speciose or unique; however, these areas are most in need of additional survey data to fill the spatial, environmental and taxonomic gaps in the HAVPlot dataset. The harmonised data and model predictions presented here provide new insight into plant diversity patterns across Australia, enabling a wide variety of future research, such as exploring changes in species abundances, linking compositional patterns to functional traits or undertaking conservation assessments for selected components of the flora

The capacity of refugia for conservation planning under climate change

Refugia – areas that may facilitate the persistence of species during large-scale, long-term climatic change – are increasingly important for conservation planning. There are many methods for identifying refugia, but the ability to quantify their potential for facilitating species persistence (ie their “capacity”) remains elusive. We propose a flexible framework for prioritizing future refugia, based on their capacity. This framework can be applied through various modeling approaches and consists of three steps: (1) definition of scope, scale, and resolution; (2) identification and quantification; and (3) prioritization for conservation. Capacity is quantified by multiple indicators, including environmental stability, microclimatic heterogeneity, size, and accessibility of the refugium. Using an integrated, semi-mechanistic modeling technique, we illustrate how this approach can be implemented to identify refugia for the plant diversity of Tasmania, Australia. The highest- capacity climate-change refugia were found primarily in cool, wet, and topographically complex environments, several of which we identify as high priorities for biodiversity conservation and management

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Effects of habitat permanence cues on larval abundance of two mosquito species

Fluctuations in mosquito populations can often be correlated with the level of rainfall in the short term, however, rainfall rarely corresponds to mosquito abundance in the long term. Here, we present results of a field based mesocosm experiment designe

Are traits measured on pot grown plants representative of those in natural communities?

Question: The quantification of functional traits in natural communities can be difficult (e.g. root traits, RGR). Can functional traits measured on pot grown plants be reliably applied to natural communities? Alternatively, can below-ground plant trait

Comment on "From Plant Traits to Plant Communities: A Statistical Mechanistic Approach to Biodiversity"

Shipley et al. (Reports, 3 November 2006, p. 812) predicted plant community composition and relative abundances with a high level of accuracy by maximizing Shannon's index of information entropy (species diversity), subject to constraints on plant trait averages. We show that the entropy maximization assumption is relatively unimportant and that the high accuracy is due largely to a statistical effect

The biogeographical attributes of the threatened flora of New South Wales

The geographic distribution, community distribution, taxonomy, and growth form of the flora listed as threatened under Schedules 1 and 2 of the New South Wales Threatened Species Conservation Act 1995 were examined. The North Coast and Central Coast Botanical Divisions have the highest number of threatened plant species, with both these divisions having significantly more threatened plant species than expected. A large disparity between the east and the west of the state was found, with the eastern divisions generally containing larger numbers and higher proportions of threatened plant species than the western divisions. Rainforest, sclerophyll forest and sclerophyll woodland communities were all found to contain large numbers of threatened plant species, with woodland containing more threatened plant species than expected. Some large families and genera contain significantly more threatened plant species than expected (e.g. Myrtaceae, Proteaceae, Grevillea and Zieria), while others contain significantly fewer (e.g. Asteraceae, Poaceae and Cyperaceae). The analysis of habit showed that fewer than expected threatened plant species were herbs. Possible explanations for the apparent distribution of threatened flora are discussed

Allocation within a generic scaling framework

Barnes and Roderick [Barnes, B., Roderick, M.L., 2004. An ecological framework linking scales across space and time based on self-thinning. Theoret. Popul. Biol. 66, 113-128] developed a generic ecological framework for scaling from individuals to ecosystems. Their approach is general and can be applied to predict above-ground, or total (above- and below-ground), dry mass. In practice, the most common situation is to measure above-ground dry mass, and apply an allometric relationship to estimate the below-ground component. In this paper we develop a general theory for incorporating the dynamics of plant partitioning into the generic framework. We consider the inclusion of allometric relationships between components (such as between roots and shoots), as well as process driven relationships, and illustrate the application of each case. Through this approach, local scale measurements and individual-based dynamic relationships pertaining to plant partitioning can be applied to an understanding of partitioning at the patch (or ecosystem) scale. Moreover, we also demonstrate that the empirically based allometric relationships have, in some circumstances, a physical explanation, providing biological meaning to empirically established allometric constants