Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Climate change presents unprecedented challenges for biological conservation. Agencies are increasingly looking to modeled projections of species' distributions under future climates to inform management strategies. As government scientists with a responsibility to communicate the best available science to our policy colleagues, we question whether current modeling approaches and outputs are practically useful. Here, we synthesize conceptual problems with species distribution models (SDMs) associated with interspecific interactions, dispersal, ecological equilibria and time lags, evolution, and the sampling of niche space. Although projected SDMs have undoubtedly been critical in alerting us to the magnitude of climate change impacts, we conclude that until they offer insights that are more precise than what we can derive from basic ecological theory, we question their utility in deciding how to allocate scarce funds to large-scale conservation projects.

Models that couple habitat suitability with demographic processes offer a potentially improved approach for estimating spatial distributional shifts and extinction risk under climate change. Applying such an approach to five species of Australian plants with contrasting demographic traits, we show that: (i) predicted climate‐driven changes in range area are sensitive to the underlying habitat model, regardless of whether demographic traits and their interaction with habitat patch configuration are modeled explicitly; and (ii) caution should be exercised when using predicted changes in total habitat suitability or geographic extent to infer extinction risk, because the relationship between these metrics is often weak. Measures of extinction risk, which quantify threats to population persistence, are particularly sensitive to life‐history traits, such as recruitment response to fire, which explained approximately 60% of the deviance in expected minimum abundance. Dispersal dynamics and habitat patch structure have the strongest influence on the amount of movement of the trailing and leading edge of the range margin, explaining roughly 40% of modeled structural deviance. These results underscore the need to consider direct measures of extinction risk (population declines and other measures of stochastic viability), as well as measures of change in habitat area, when assessing climate change impacts on biodiversity. Furthermore, direct estimation of extinction risk incorporates important demographic and ecosystem processes, which potentially influence species’ vulnerability to extinction due to climate change.

Summary Two main sources of data for species distribution models (SDMs) are site‐occupancy (SO) data from planned surveys, and presence‐background (PB) data from opportunistic surveys and other sources. SO surveys give high quality data about presences and absences of the species in a particular area. However, due to their high cost, they often cover a smaller area relative to PB data, and are usually not representative of the geographic range of a species. In contrast, PB data is plentiful, covers a larger area, but is less reliable due to the lack of information on species absences, and is usually characterised by biased sampling. Here we present a new approach for species distribution modelling that integrates these two data types. We have used an inhomogeneous Poisson point process as the basis for constructing an integrated SDM that fits both PB and SO data simultaneously. It is the first implementation of an Integrated SO–PB Model which uses repeated survey occupancy data and also incorporates detection probability. The Integrated Model's performance was evaluated, using simulated data and compared to approaches using PB or SO data alone. It was found to be superior, improving the predictions of species spatial distributions, even when SO data is sparse and collected in a limited area. The Integrated Model was also found effective when environmental covariates were significantly correlated. Our method was demonstrated with real SO and PB data for the Yellow‐bellied glider (Petaurus australis) in south‐eastern Australia, with the predictive performance of the Integrated Model again found to be superior. PB models are known to produce biased estimates of species occupancy or abundance. The small sample size of SO datasets often results in poor out‐of‐sample predictions. Integrated models combine data from these two sources, providing superior predictions of species abundance compared to using either data source alone. Unlike conventional SDMs which have restrictive scale‐dependence in their predictions, our Integrated Model is based on a point process model and has no such scale‐dependency. It may be used for predictions of abundance at any spatial‐scale while still maintaining the underlying relationship between abundance and area.

Movement is a trait of fundamental importance in ecosystems subject to frequent disturbances, such as fire-prone ecosystems. Despite this, the role of movement in facilitating responses to fire has received little attention. Herein, we consider how animal movement interacts with fire history to shape species distributions. We consider how fire affects movement between habitat patches of differing fire histories that occur across a range of spatial and temporal scales, from daily foraging bouts to infrequent dispersal events, and annual migrations. We review animal movements in response to the immediate and abrupt impacts of fire, and the longer-term successional changes that fires set in train. We discuss how the novel threats of altered fire regimes, landscape fragmentation, and invasive species result in suboptimal movements that drive populations downwards. We then outline the types of data needed to study animal movements in relation to fire and novel threats, to hasten the integration of movement ecology and fire ecology. We conclude by outlining a research agenda for the integration of movement ecology and fire ecology by identifying key research questions that emerge from our synthesis of animal movements in fire-prone ecosystems.

The pattern of breathing during a hyperthermia-induced hyperventilation varies across different species. Thermal tachypnea is a first phase panting response adopted during hyperthermia when tidal volume is minimized and the frequency of breathing is maximized. Blood-gas tensions and pH are maintained during this hyperventilation, and the associated heat loss helps the animal regulate its body temperature. A second pattern of breathing adopted in hyperthermia is thermal hyperpnea; this response is the focus of this review. This form of hyperventilation is evident after an increase in core temperature and it is apparent in humans. Increases of tidal volume as well as frequency of breathing are evident during this response that results in a respiratory alkalosis. The cause of thermal hyperpnea is not resolved; evidence of the potential mechanisms underlying this response support that modulators of the response act in either a multiplicative or additive manner with body temperatures. The details of the designs and methodologies of the studies supporting or refuting these two views are discussed. A physiological rationale for thermal hyperpnea is presented in which it is suggested this response serves a heat-loss role and contributes to selective brain cooling in hyperthermic humans. Ongoing research in this area is focused on resolving the mechanisms underlying thermal hyperpnea and its contribution to cranial thermoregulation. The direct application of this research is for the care of febrile and hyperthermic patients.

Humans have higher ventilation when they are hyperthermic but it is not known whether core temperature thresholds for ventilation exist, nor has a physiological rationale been presented for this response. To examine this question, ventilation was studied in relation to core temperatures in humans rendered hyperthermic in a warm bath. Seven subjects [mean (SE), 23.3 (1.4) years] wearing only shorts and a thick felt hat with ear flaps were immersed to the neck in a bath at 41 (0.5) degrees C for 25 min. Tympanic (Tty), esophageal (Tes), thigh skin and forehead skin temperatures, heart rate, inspired minute ventilation (V1 at body temperature and pressure, saturated), ventilation frequency and oxygen consumption (VO2 at standard temperature and pressure, dry) were recorded at 30-s intervals. At immersion V1 briefly increased to 18.6 (3.0) l.min-1, returned to about the pre-immersion value, and significantly increased to 19.3 (3.0) l.min-1 by the end of immersion. VO2 increased significantly from the pre-immersion value of 0.27 l.min-1 to 0.67 l.min-1 by the first 0.5 min of immersion, but then returned to its pre-immersion value. Tty increased to 38.7 (0.2) degrees C and Tes increased to 39.0 (0.2) degrees C by the end of immersion. Core temperature thresholds for increases in V1 were evident at 38.1 degrees C when expressed against Tty and at 38.5 degrees C when expressed against Tes. The results indicated that during body warming core temperature thresholds for V1 are reached and subsequently a hyperpnea was evident, despite VO2 remaining at a resting value.(ABSTRACT TRUNCATED AT 250 WORDS)

Aim To quantify the impact of the 2019–2020 megafires on Australian plant diversity by assessing burnt area across 26,062 species ranges and the effects of fire history on recovery potential. Further, to exemplify a strategic approach to prioritizing plant species affected by fire for recovery actions and conservation planning at a national scale. Location Australia. Methods We combine data on geographic range, fire extent, response traits and fire history to assess the proportion of species ranges burnt in both the 2019–2020 fires and the past. Results Across Australia, suitable habitat for 69% of all plant species was burnt (17,197 species) by the 2019–2020 fires and herbarium specimens confirm the presence of 9,092 of these species across the fire extent since 1950. Burnt ranges include those of 587 plants listed as threatened under national legislation (44% of Australia's threatened plants). A total of 3,998 of the 17,197 fire‐affected species are known to resprout after fire, but at least 2,928 must complete their entire life cycle—from germinant to reproducing adult—prior to subsequent fires, as they are killed by fire. Data on previous fires show that, for 257 species, the historical intervals between fire events across their range are likely too short to allow regeneration. For a further 411 species, future fires during recovery will increase extinction risk as current populations are dominated by immature individuals. Main conclusion Many Australian plant species have strategies to persist under certain fire regimes, and will recover given time, suitable conditions and low exposure to threats. However, short fire intervals both before and after the 2019–2020 fire season pose a serious risk to the recovery of at least 595 species. Persistent knowledge gaps about species fire response and post‐fire population persistence threaten the effective long‐term management of Australian vegetation in an increasingly pyric world.