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To generate realistic predictions, species distribution models require the accurate coregistration of occurrence data with environmental variables. There is a common assumption that species occurrence data are accurately georeferenced; however, this is often not the case. This study investigates whether locational uncertainty and sample size affect the performance and interpretation of fine-scale species distribution models., This study evaluated the effects of locational uncertainty across multiple sample sizes by subsampling and spatially degrading occurrence data. Distribution models were constructed for kelp ( Ecklonia radiata), across a large study site (680 km2) off the coast of southeastern Australia. Generalized additive models were used to predict distributions based on fine-resolution (2·5 m cell size) seafloor variables, generated from multibeam echosounder data sets, and occurrence data from underwater towed video. The effects of different levels of locational uncertainty in combination with sample size were evaluated by comparing model performance and predicted distributions., While locational uncertainty was observed to influence some measures of model performance, in general this was small and varied based on the accuracy metric used. However, simulated locational uncertainty caused changes in variable importance and predicted distributions at fine scales, potentially influencing model interpretation. This was most evident with small sample sizes., Results suggested that seemingly high-performing, fine-scale models can be generated from data containing locational uncertainty, although interpreting their predictions can be misleading if the predictions are interpreted at scales similar to the spatial errors. This study demonstrated the need to consider predictions across geographic space rather than performance alone. The findings are important for conservation managers as they highlight the inherent variation in predictions between equally performing distribution models, and the subsequent restrictions on ecological interpretations. [ABSTRACT FROM AUTHOR]

The critical weight range (CWR) hypothesis for Australian mammals states that extinctions and declines have been concentrated in species with body mass between 35 g and 5.5 kg. The biological basis for this hypothesis is that species of intermediate size are disproportionately impacted by introduced predators. The CWR hypothesis has received support from several statistical studies over the past decade, although the evidence is weaker or non-existent for certain groups such as mesic-zone mammals and arboreal mammals. In this study, we employ an information-theoretic model selection approach to gain further insights into the relationship between body mass and extinction risk in Australian mammals. We find evidence, consistent with the CWR hypothesis, that extinction risk peaks at intermediate body masses for marsupials, rodents and ground-dwelling species, but not for arboreal species. In contrast to previous studies, we find that the CWR describes extinction patterns in the mesic zone as well as the arid zone. In the mesic zone, there is also a weaker tendency for large species above the CWR to be more vulnerable, consistent with extinction patterns on other continents. We find that a more biological plausible Gaussian distribution consistently fits the data better than the polynomial models that have been used in previous studies. Our results justify conservation programmes targeted at species within the CWR across Australia. [ABSTRACT FROM AUTHOR]

The critical weight range hypothesis for Australian terrestrial mammals states that species in the intermediate size range 35–5500 g are particularly susceptible to extinction. In a 2001 study Cardillo and Bromham found no statistically significant evidence for this hypothesis and suggested that research should instead focus on why small species are resistant to extinction. We used a similar data set of body sizes of Australian mammals grouped by conservation classification, but we used test statistics (mean deviation above and below the median body size) that are more statistically powerful than those of Cardillo and Bromham (quartiles, maxima, and minima of body size distributions). We found strong evidence in favor of the critical weight range hypothesis: the body size distribution of threatened species was more clustered toward the median body size from above and below. This pattern was statistically significant at the continental scale and in the arid zone, but not in the mesic zone. Confusing statistical significance with evidence of no effect, as Cardillo and Bromham did, can have negative implications for conservation biology because it can result in failure to act when action is warranted or provision of incorrect advice that affects policy and planning decisions. [ABSTRACT FROM AUTHOR]

Abstract: The wedge-tailed eagle is Australia’s largest bird of prey and one of the largest eagles in the world. Aquila audax fleayi is an endemic Tasmanian subspecies isolated for 10,000years from the nominate subspecies on the Australian mainland. The Tasmanian wedge-tailed eagle is classified nationally and at a State level as endangered due to its small number of breeding pairs, low breeding success and high rate of mortality from unnatural causes. The subspecies experiences mortality throughout its range from shooting, poisoning, trapping, road accidents, electrocutions and collisions with wind turbines, aircraft, fences and overhead wires, which we term ‘un-natural mortality’. A portion of the subspecies’ range is managed for timber production, which can lead to disturbance of nest sites and the loss of nest trees. We use a model of the eagle population from the Bass District in northeast Tasmania to explore the relative importance of different sources of mortality and nesting habitat loss, and the potential for mitigating impacts associated with unnatural mortality, disturbance, nesting habitat loss and human access to forests. We create a habitat map including suitable nest sites and link it to a dynamic landscape population model based on life history traits and disturbance responses. Using the program RAMAS-Landscape, we model alternative forest management scenarios, ranging from no timber harvesting and a natural wildfire regime, to scenarios prescribing native forest harvesting and regeneration and different levels of conversion of native forest to plantation under the same natural wildfire regime. The results indicate that the Tasmanian wedge-tailed eagle is sensitive to unnatural mortality, plantation establishment and native forest harvesting. The predicted decline over the next 160years (∼65%) will most likely be driven largely by loss of current and potential future nest sites associated with harvesting activities, exacerbated by unnatural mortality in the wider landscape. Interventions that minimise unnatural mortality, reduce nest disturbance, and retain breeding habitat and nest sites may improve the prospects for the subspecies in the Bass District. If nest disturbance and unnatural mortality continue at the rates modelled here, the species appears to face a high risk of declining substantially in the region. [Copyright &y& Elsevier]

Extinctions of undiscovered species (undetected extinctions) constitute a portion of biodiversity loss that is often ignored. We compared the performance of 2 models of undetected extinctions - Tedesco and SEUX - when estimating undetected extinctions with both simulated and real-world data. We generated simulated data by considering a birth-death process in which less abundant species were more likely to go extinct. When detection rates were higher for common species, the 2 models underestimated the true number of undetected extinctions by up to 88.7%, and when detection rates were independent of abundance, the 2 models performed better; the SEUX model had an average bias of +3.1% and the Tedesco model had an average bias of -62.3%. We applied the models to 8 real-world data sets (e.g., Australian amphibians, Australian birds, North American bivalves) and found that true extinctions may be from 15% to 180% higher than observed values. For 6 of the 8 data sets, the SEUX model yielded absolute estimates that were 5.7-66.8% lower than those of the Tedesco model. We mainly attributed this difference to the SEUX model's assumption that there are no undetected extant species currently. We assessed the accuracy of the models' estimates with a logistic regression to test whether detection and extinction rates were uncorrelated across species. Rates were correlated for 3 of the 8 data sets; species discovered later had a higher probability of being extinct, suggesting that extinction numbers could be even higher for these groups. Despite caveats associated with the models, the evidence from both show biodiversity loss in these groups may be more severe than what has been documented., (© 2020 Society for Conservation Biology.)