Survival and growth of a high-mountain daisy transplanted outside its local range, and implications for climate-induced distribution shifts.

Field transplant experiments can improve our understanding of the effects of climate on distributions of plants versus a milieu of biotic factors which may be mediated by climate. We use a transplant experiment to test how survival and growth of a mountain-top daisy (Podolepis robusta), when planted within and outside its current local range, varies as a function of individual plant size, elevation, aspect and the presence of other vegetation. We expected a home-site advantage for the species, with highest survival and growth within the species' current elevational limits, and a decline in vital rates above (due to physiological limitations) and below (due to competition with near-neighbours) these limits. Transplant survival during the beginning of the census was high (89 %), though by the third growing season, 36 % of initial transplants were remaining. Elevation had a significant negative effect on individual mortality rates; plants growing at higher elevations had a lower estimated hazard rate and thus, higher survival relative to those planted at elevations below the current lower limit of the distribution. By contrast, we detected no significant effect of elevation on growth rates. Small vegetation gaps had no effect on growth rates, though we found a negative, but non-significant, effect on mortality rates. Aspect had a very strong impact on growth. Plants transplanted to cool aspects had a significantly lower growth rate relative to transplants growing on a warm aspect. Conversely, aspect was not a significant predictor of individual mortality rates. Restrictions on the local distribution of P. robusta appear to be governed by mortality drivers at lower elevation and by growth drivers associated with aspect. We highlight that our ability to understand the drivers of distributions in current and future climates will be limited if contextual- and individual-level plant responses remain understudied.

AusTraits, a curated plant trait database for the Australian flora.

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.

Health and economic costs of early and delayed suppression and the unmitigated spread of COVID-19: The case of Australia.

We compare the health and economic costs of early and delayed mandated suppression and the unmitigated spread of 'first-wave' COVID-19 infections in Australia in 2020. Using a fit-for-purpose SIQRM-compartment model for susceptible, infected, quarantined, recovered and mortalities on active cases, that we fitted from recorded data, a value of a statistical life year (VSLY) and an age-adjusted value of statistical life (A-VSL), we find that the economic costs of unmitigated suppression are multiples more than for early mandated suppression. We also find that using an equivalent VSLY welfare loss from fatalities to estimated GDP losses, drawn from survey data and our own estimates of the impact of suppression measures on the economy, means that for early suppression not to be the preferred strategy requires that Australia would have to incur more than 12,500-30,000 deaths, depending on the fatality rate with unmitigated spread, to the economy costs of early mandated suppression. We also find that early rather than delayed mandated suppression imposes much lower economy and health costs and conclude that in high-income countries, like Australia, a 'go early, go hard' strategy to suppress COVID-19 results in the lowest estimated public health and economy costs.

Predicting species and community responses to global change using structured expert judgement: An Australian mountain ecosystems case study.

Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which have already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we use a structured expert elicitation method (the IDEA protocol) to estimate the change in abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles are expected to decline in abundance than other species. While long-term ecological data will always be the gold standard for informing the future of biodiversity, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and a paucity of data.

Forecasting species range dynamics with process-explicit models: matching methods to applications.

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process-explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process-explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs - regulatory planning, extinction risk, climate refugia and invasive species - we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process-explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.

Effects of drought and fire on resprouting capacity of 52 temperate Australian perennial native grasses.

It remains uncertain how perennial grasses with different photosynthetic pathways respond to fire, and how this response varies with stress at the time of burning. Resprouting after fire was examined in relation to experimentally manipulated pre-fire watering frequencies. We asked the following questions: are there response differences to fire between C3 and C4 grasses? And, how does post-fire resprouting vary with pre-fire drought stress? Fifty-two perennial Australian grasses (37 genera, 13 tribes) were studied. Three watering frequencies were applied to simulate increasing drought. Pre-fire tiller number, tiller density, specific leaf area and leaf dry matter content were measured as explanatory variables to assess response. Most species (90%) and individuals (79%) resprouted following experimental burning. C4 grasses had higher probabilities of surviving fire relative to C3 grasses. Responses were not related to phylogeny or tribe. High leaf dry matter content reduced the probability of dying, but also reduced the re-emergence of tillers. Post-fire tiller number increased with increasing drought, regardless of photosynthetic type, suggesting that drought plays a role in the ability of grasses to recover after fire. This has implications for understanding the persistence of species in landscapes where fire management is practiced.

Partitioning mortality into growth-dependent and growth-independent hazards across 203 tropical tree species.

Tree death drives population dynamics, nutrient cycling, and evolution within plant communities. Mortality variation across species is thought to be influenced by different factors relative to variation within species. The unified model provided here separates mortality rates into growth-dependent and growth-independent hazards. This model creates the opportunity to simultaneously estimate these hazards both across and within species. Moreover, it provides the ability to examine how species traits affect growth-dependent and growth-independent hazards. We derive this unified mortality model using cross-validated Bayesian methods coupled with mortality data collected over three census intervals for 203 tropical rainforest tree species at Barro Colorado Island (BCI), Panama. We found that growth-independent mortality tended to be higher in species with lower wood density, higher light requirements, and smaller maximum diameter at breast height (dbh). Mortality due to marginal carbon budget as measured by near-zero growth rate tended to be higher in species with lower wood density and higher light demand. The total mortality variation attributable to differences among species was large relative to variation explained by these traits, emphasizing that much remains to be understood. This additive hazards model strengthens our capacity to parse and understand individual-level mortality in highly diverse tropical forests and hence to predict its consequences.

Climatic warming strengthens a positive feedback between alpine shrubs and fire.

Climate change is expected to increase fire activity and woody plant encroachment in arctic and alpine landscapes. However, the extent to which these increases interact to affect the structure, function and composition of alpine ecosystems is largely unknown. Here we use field surveys and experimental manipulations to examine how warming and fire affect recruitment, seedling growth and seedling survival in four dominant Australian alpine shrubs. We found that fire increased establishment of shrub seedlings by as much as 33-fold. Experimental warming also doubled growth rates of tall shrub seedlings and could potentially increase their survival. By contrast, warming had no effect on shrub recruitment, postfire tussock regeneration, or how tussock grass affected shrub seedling growth and survival. These findings indicate that warming, coupled with more frequent or severe fires, will likely result in an increase in the cover and abundance of evergreen shrubs. Given that shrubs are one of the most flammable components in alpine and tundra environments, warming is likely to strengthen an existing feedback between woody species abundance and fire in these ecosystems.

Modeling rates of life form cover change in burned and unburned alpine heathland subject to experimental warming.

Elevated global temperatures are expected to alter vegetation dynamics by interacting with physiological processes, biotic relationships and disturbance regimes. However, few studies have explicitly modeled the effects of these interactions on rates of vegetation change, despite such information being critical to forecasting temporal patterns in vegetation dynamics. In this study, we build and parameterize rate-change models for three dominant alpine life forms using data from a 7-year warming experiment. These models allowed us to examine how the interactions between experimental warming, the abundance of bare ground (a measure of past disturbance) and neighboring life forms (a measure of life form interaction) affect rates of cover change in alpine shrubs, graminoids and forbs. We show that experimental warming altered rates of life form cover change by reducing the negative effects of neighboring life forms and positive effects of bare ground. Furthermore, we show that our models can predict the observed direction and rate of life form cover change at burned and unburned long-term monitoring sites. Model simulations revealed that warming in unburned vegetation is expected to result in increased forb and shrub cover and decreased graminoid cover. In contrast, in burned vegetation, warming is predicted to slow post-fire regeneration in both graminoids and forbs and facilitate rapid expansion in shrub cover. These findings illustrate the applicability of modeling rates of vegetation change using experimental data. Our results also highlight the need to account for both disturbance and the abundance of other life forms when examining and forecasting vegetation dynamics under climatic change.