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Aim Existing abiotic and biotic threats to plant species (e.g., disease, drought, invasive species) affect their capacity to recover post-fire. We use a new, globally applicable framework to assess the vulnerability of 26,062 Australian plant species to a suite of active threats after the 2019–2020 fires. Location Australia. Time period 2019–2020. Major species studied Plants. Methods Spatial data for existing threats and information on species-level susceptibility were combined with estimates of the extent of range burnt in southern Australia (> 22°S) to assign species against 10 criteria into vulnerability categories (high, medium, low, none, data deficient). We explore in detail results for three threats (drought, disease, feral animals), highlighting where impacts from multiple threats ranked high vulnerability may compound to reduce post-fire recovery. Results Analysis of the full suite of 10 vulnerability criteria, which encompass a broad range of threats, revealed large numbers of species vulnerable to poor post-fire recovery from one or more different hazards (high vulnerability: 1,243 species; medium vulnerability: 2,450 species). Collectively, 457 plant species that burnt extensively (> 50%) across their range are highly vulnerable to poor recovery due to exposure to pre-fire drought conditions (235 species), disease (186 species), or feral animals (97 species). Of these 457 species, 61 are vulnerable to more than one of these three threats, highlighting how a suite of interacting hazards can impact plant recovery after fire. Main conclusions While fire can renew plant populations by stimulating recruitment and resetting competitive interactions, the presence of existing threats in post-fire landscapes jeopardizes recovery. The simultaneous impact of multiple threats that impact recovery can create a suite of hazards that contribute to declines and, potentially, extinction. Our method for rapid post-fire vulnerability assessment can be applied to

The ENMTools software package was introduced in 2008 as a platform for making measurements on environmental niche models (ENMs, frequently referred to as species distribution models or SDMs), and for using those measurements in the context of newly developed Monte Carlo tests to evaluate hypotheses regarding niche evolution. Additional functionality was later added for model selection and simulation from ENMs, and the software package has been quite widely used. ENMTools was initially implemented as a Perl script, which was also compiled into an executable file for various platforms. However, the package had a number of significant limitations; it was only designed to fit models using Maxent, it relied on a specific Perl distribution to function, and its internal structure made it difficult to maintain and expand. Subsequently, the R programming language became the platform of choice for most ENM studies, making ENMTools less usable for many practitioners. Here we introduce a new R version of ENMTools that implements much of the functionality of its predecessor as well as numerous additions that simplify the construction, comparison and evaluation of niche models. These additions include new metrics for model fit, methods of measuring ENM overlap, and methods for testing evolutionary hypotheses. The new version of ENMTools is also designed to work within the expanding universe of R tools for ecological biogeography, and as such includes greatly simplified interfaces for analyses from several other R packages.

Tephritid fruit flies are among the most destructive horticultural pests posing risks to Australia’s multi-billion-dollar horticulture industry. Currently, there are 11 pest fruit fly species of economic concern in Australia. Of these, nine are native to this continent (Bactrocera aquilonis, B. bryoniae, B. halfordiae, B. jarvisi, B. kraussi, B. musae, B. neohumeralis, B. tryoni and Zeugodacus cucumis), while B. frauenfeldi and Ceratitis capitata are introduced. To varying degrees these species are costly to Australia’s horticulture through in-farm management, monitoring to demonstrate pest freedom, quarantine and trade restrictions, and crop losses. Here, we used a common species distribution model, Maxent, to assess climate suitability for these 11 species under baseline (1960–1990) and future climate scenarios for Australia. Projections indicate that the Wet Tropics is likely to be vulnerable to all 11 species until at least 2070, with the east coast of Australia also likely to remain vulnerable to multiple species. While the Cape York Peninsula and Northern Territory are projected to have suitable climate for numerous species, extrapolation to novel climates in these areas decreases confidence in model projections. The climate suitability of major horticulture areas currently in eastern Queensland, southern-central New South Wales and southern Victoria to these pests may increase as climate changes. By highlighting areas at risk of pest range expansion in the future our study may guide Australia’s horticulture industry in developing effective monitoring and management strategies.