Background: It is long known within the mathematical literature that the coefficient of determination R 2 is an inadequate measure for the goodness of fit in nonlinear models. Nevertheless, it is still frequently used within pharmacological and biochemical literature for the analysis and interpretation of nonlinear fitting to data. Results:The intensive simulation approach undermines previous observations and emphasizes the extremely low performance of R 2 as a basis for model validity and performance when applied to pharmacological/biochemical nonlinear data. In fact, with the 'true' model having up to 500 times more strength of evidence based on Akaike weights, this was only reflected in the third to fifth decimal place of R 2 . In addition, even the bias-corrected R 2 adj exhibited an extreme bias to higher parametrized models. The bias-corrected AICc and also BIC performed significantly better in this respect. Conclusion:Researchers and reviewers should be aware that R 2 is inappropriate when used for demonstrating the performance or validity of a certain nonlinear model. It should ideally be removed from scientific literature dealing with nonlinear model fitting or at least be supplemented with other methods such as AIC or BIC or used in context to other models in question. BackgroundFitting nonlinear models to data is frequently applied within all fields of pharmaceutical and biochemical assay quantification. A plethora of nonlinear models exist, and chosing the right model for the data at hand is a mixture of experience, knowledge about the underlying process and statistical interpretation of the fitting outcome. While the former are of somewhat individual nature, there is a need in quantifying the validity of a fit by some measure which discriminates a 'good' from a 'bad' fit. The most common measure is the coefficient of determination R 2 used in linear regression when conducting calibration experiments for samples to be quantified [1]. In the linear context, this measure is very intuitive as values between 0 and 1 give a quick interpretation of how much of the variance in the data is explained by the fit. Although it is known now for some time that R 2 is an

We reviewed the historical records of attacks by saltwater crocodiles (Crocodylus porosus) and the removal of problem saltwater crocodiles in the Northern Territory of Australia. Between 1977 and 2013, 5,792 problem crocodiles were removed, of which 69.04% were males and 83.01% were caught within the Darwin Crocodile Management Zone where suitable breeding habitats were hardly available. The most common size class was 150–200 cm and their mean size did not change significantly over years. This reflected the greater mobility of juvenile males as the majority of problem crocodiles, dispersing from core habitats that were occupied by dominant individuals. Eighteen fatal attacks and 45 non‐fatal attacks occurred between 1971 and 2013. The rate of crocodile attacks, particularly non‐fatal cases, increased over time. This increase was strongly related to the increasing populations of both humans and crocodiles, and the increasing proportion of larger (>180 cm) crocodiles. The management of human‐crocodile conflict (HCC) should incorporate both human (e.g., public education and safety awareness) and crocodile (e.g., population monitoring, removal of problem crocodiles) components. Crocodiles in the 300–350‐cm class were most responsible for attacks, and they should be strategically targeted as the most likely perpetrator. Approximately 60% of attacks occurred around population centers including remote communities. Problem crocodile capture and attacks both peak in the beginning (Sep–Dec) and end (Mar–Apr) of the wet season. However, fatal attacks occurred almost all year around. Attacks by crocodiles >400 cm often resulted in death of the victim (73.33%). Local and male victims were much more common than visitors and females, respectively. The most common activity of victims was swimming and wading. Despite the increasing rate of attacks over time, the Northern Territory's management program, and in particular the removal of problem crocodiles from urban areas, is considered to have reduced potential HCC. Public education about crocodile awareness and risks must be maintained. © 2014 The Wildlife Society.

Saltwater crocodile (Crocodylus porosus) populations have recovered strongly across northern Australia over the 30 years since the species was protected from hunting. However, monitoring studies show large geographical variations in abundance across the Northern Territory, Queensland and Western Australia. The Northern Territory has considerably higher densities, raising questions about constraints on recovery in the other states. We examined broad-scale environmental influences on population abundance by modelling the species–environment relationships across northern Australia. The hypothesis-based models showed strong support for the linkage to (1) the ratio of total area of favourable wetland vegetation types (Melaleuca, grass and sedge) to total catchment area, (2) a measure of rainfall seasonality, namely the ratio of total precipitation in the coldest quarter to total precipitation in the warmest quarter of a year, and (3) the mean temperature in the coldest quarter of a year. On the other hand, we were unable to show any clear negative association with landscape modification, as indicated by the extent of high-impact land uses or human population density in catchments. We conclude that geographical variations in crocodile density are mostly attributable to differences in habitat quality rather than the management regimes adopted in the respective jurisdictions.

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions.

The presence and movements of organisms both reflect and influence the distribution of ecological resources in space and time. The monitoring of animal movement by telemetry devices is being increasingly used to inform management of marine, freshwater and terrestrial ecosystems. Here, we brought together academics, and environmental managers to determine the extent of animal movement research in the Australasian region, and assess the opportunities and challenges in the sharing and reuse of these data. This working group was formed under the Australian Centre for Ecological Analysis and Synthesis (ACEAS), whose overall aim was to facilitate trans-organisational and transdisciplinary synthesis. We discovered that between 2000 and 2012 at least 501 peer-reviewed scientific papers were published that report animal location data collected by telemetry devices from within the Australasian region. Collectively, this involved the capture and electronic tagging of 12 656 animals. The majority of studies were undertaken to address specific management questions; rarely were these data used beyond their original intent. We estimate that approximately half (~500) of all animal telemetry projects undertaken remained unpublished, a similar proportion were not discoverable via online resources, and less than 8.8% of all animals tagged and tracked had their data stored in a discoverable and accessible manner. Animal telemetry data contain a wealth of information about how animals and species interact with each other and the landscapes they inhabit. These data are expensive and difficult to collect and can reduce survivorship of the tagged individuals, which implies an ethical obligation to make the data available to the scientific community. This is the first study to quantify the gap between telemetry devices placed on animals and findings/data published, and presents methods for improvement. Instigation of these strategies will enhance the cost-effectiveness of the research and maximise its impact on the management of natural resources.