A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence–absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS‐INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM‐GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

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The Fitzroy River delivers large amounts of nutrients and fine sediments to Keppel Bay (contiguous with the Great Barrier Reef Lagoon) during intermittent flow events. This study explores sources, forms and transformations of nutrients in Keppel Bay, and develops a functional process zonation that integrates seabed geochemistry and water column nutrient characteristics which are controlled by suspended sediment. The water column and seabed properties were investigated over two dry seasons, with supplementary core incubations taken to measure carbon decomposition rates and nutrient fluxes. Keppel Bay can be divided into three zones, the: zone of maximum resuspension (ZMR); coastal transitional zone (CTZ); and blue water zone (BWZ). Mineralisation of predominantly terrestrial organic matter occurs in the ZMR where nutrient uptake by phytoplankton is light limited. The CTZ and BWZ had higher light penetration and phytoplankton growth was likely limited by N and P, respectively. The identified zones conform to the bathymetry and hydrodynamic characteristics of the bay, allowing for the development of an integrated conceptual model accounting for the benthic and pelagic biogeochemical processes. Recognition of these different zones shows that considerable variation in benthic and water column properties is possible within a small system with the bathymetric and hydrodynamic characteristics of the fluidized bed reactor.

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