The invasive spread of exotic plants in native vegetation can pose serious threats to native faunal assemblages. This is of particular concern for reptiles and amphibians because they form a significant component of the world's vertebrate fauna, play a pivotal role in ecosystem functioning and are often neglected in biodiversity research. A framework to predict how exotic plant invasion will affect reptile and amphibian assemblages is imperative for conservation, management and the identification of research priorities. Here, we present a new predictive framework that integrates three mechanistic models. These models are based on exotic plant invasion altering: (1) habitat structure; (2) herbivory and predator-prey interactions; (3) the reproductive success of reptile and amphibian species and assemblages. We present a series of testable predictions from these models that arise from the interplay over time among three exotic plant traits (growth form, area of coverage, taxonomic distinctiveness) and six traits of reptiles and amphibians (body size, lifespan, home range size, habitat specialisation, diet, reproductive strategy). A literature review provided robust empirical evidence of exotic plant impacts on reptiles and amphibians from each of the three model mechanisms. Evidence relating to the role of body size and diet was less clear-cut, indicating the need for further research. The literature provided limited empirical support for many of the other model predictions. This was not, however, because findings contradicted our model predictions but because research in this area is sparse. In particular, the small number of studies specifically examining the effects of exotic plants on amphibians highlights the pressing need for quantitative research in this area. There is enormous scope for detailed empirical investigation of interactions between exotic plants and reptile and amphibian species and assemblages. The framework presented here and further testing of predictions will provide a basis for informing and prioritising environmental management and exotic plant control efforts.

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The value of plant ecological datasets with hundreds or thousands of species is principally determined by the taxonomic accuracy of their plant names. However, combining existing lists of species to assemble a harmonized dataset that is clean of taxonomic errors can be a difficult task for non-taxonomists. Here, we describe the range of taxonomic difficulties likely to be encountered during dataset assembly and present an easy-to-use taxonomic cleaning protocol aimed at assisting researchers not familiar with the finer details of taxonomic cleaning. The protocol produces a final dataset (FD) linked to a companion dataset (CD), providing clear details of the path from existing lists to the FD taken by each cleaned taxon. Taxa are checked off against ten categories in the CD that succinctly summarize all taxonomic modifications required. Two older, publicly-available lists of naturalized Asteraceae in Australia were merged into a harmonized dataset as a case study to quantify the impacts of ignoring the critical process of taxonomic cleaning in invasion ecology. Our FD of naturalized Asteraceae contained 257 species and infra-species. Without implementation of the full cleaning protocol, the dataset would have contained 328 taxa, a 28% overestimate of taxon richness by 71 taxa. Our naturalized Asteraceae CD described the exclusion of 88 names due to nomenclatural issues (e.g. synonymy), the inclusion of 26 updated currently accepted names and four taxa newly naturalized since the production of the source datasets, and the exclusion of 13 taxa that were either found not to be in Australia or were in fact doubtfully naturalized. This study also supports the notion that automated processes alone will not be enough to ensure taxonomically clean datasets, and that manual scrutiny of data is essential. In the long term, this will best be supported by increased investment in taxonomy and botany in university curricula. NeoBiotaBrad R. Murray et al. / NeoBiota 34: 1-20 (2017) 2

With recent and predicted increases in the frequency and intensity of wildfires, there is a pressing need for mitigation strategies to reduce the impacts of wildfires on human lives, infrastructure and biodiversity. One strategy involves the use of low-flammability plants to build green firebreaks at the wildland–urban interface. It is common, however, to encounter uncertainty in a diverse range of stakeholders about the concept of flammability as it applies to plants, which may impede efforts to identify suitable low-flammability plant species. Here, we provide an approach to identify low-flammability plant species that integrates three fundamental and relatively easy-to-measure plant-flammability attributes – ignitibility, sustainability and combustibility – in a way that removes confusion about the concept of plant flammability. These three intrinsic flammability attributes relate to each other such that an ideal low-flammability species is one that is slow to ignite, sustains burning for a short period of time and combusts with low intensity. Consideration is then given to secondary attributes of plants critical to the selection of low-flammability plants, including attributes that influence the volume of fuel available for fires and the vertical and horizontal spread of fires. More work is urgently needed across the world to identify low-flammability plant species using standardised measurement protocols, and our integrated approach provides a transparent way to ensure we are selecting the right species, for the right location, in green firebreaks.

Summary During recent work examining the effects of Bitou Bush (Chrysanthemoides monilifera ssp. rotundata) invasion on native reptile assemblages in coastal heathland vegetation in Eastern Australia, unplanned spot‐spraying of glyphosate occurred at some of our experimental sites invaded by Bitou Bush. We used this unexpected herbicide application as an opportunity to provide a preliminary assessment of the short‐term impacts on reptiles of glyphosate spot‐spraying of Bitou Bush. Using an M‐BARCI design, we compared reptile assemblages among uninvaded (reference) sites, invaded (control) sites and invaded and sprayed (impact) sites before and after spraying. We found no significant short‐term (7 – 10 months) differences in reptile abundance, species richness or assemblage composition among invaded, uninvaded and sprayed sites before and after glyphosate application. We cautiously interpret our results to generate a preliminary finding that spot‐spraying of Bitou Bush with glyphosate appears not to have a deleterious effect on reptile assemblages at seven and ten months following herbicide application. While we would not recommend basing management decisions on the outcomes of our study alone, we suggest that our findings can be used to assist in the development of strategic analyses of glyphosate impacts on native flora and fauna.

In calibration tasks students assess exemplar texts using criteria against which their own work will be assessed. Typically these tasks are used in the context of training for peer assessment. Little research has been conducted on the benefits of calibration tasks, such as benchmarking, as learning opportunities in their own right. This paper examines a dataset from a long-running benchmarking task (~500 students per semester, for four semesters). We investigate the relationship of benchmarking performance to other student outcomes, including ability to self-assess accurately. We show that students who complete the benchmarking perform better, that there is a relationship between benchmarking performance and self-assessment performance, and that students appreciate the support for learning that benchmarking tasks provide. We discuss implications for teaching and learning flagging the potential of calibration tasks as an under-explored tool.

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Environmental databases play an essential role in the management of land and communities, including mapping and monitoring environmental hazards over time (i.e., abandoned mines). Over the last century, mines have closed for many reasons, but there has been no comprehensive database of the locations of closed and abandoned mine sites kept for many regions of the world. As such, the locations of many mines have been lost from public knowledge, with no way for managers to assess the risks of land and water contamination, as well as subsidence. To address this knowledge gap, we present an integrated framework for identifying abandoned mine sites using a combination of satellite imagery, historical records, geographic evidence, and local knowledge. We tested this framework within the Newcastle, Illawarra, and Lithgow regions of NSW, Australia. We identified 61 abandoned coal mines which are currently unaccounted for in mine registries, with 56% of all mines in the Newcastle region being unmarked (N = 32), 36% in the Illawarra region (N = 22), and 20% in the Lithgow region (N = 7). These findings demonstrate that our framework has promising utility in identifying historic and unmarked environmental hazards in both national and international contexts.