The analysis of macroecological patterns has necessitated the use of large, composite datasets recording local-scale species occurrences distributed across the globe. These datasets, however, have various spatial and temporal biases. They have rarely been compared to data collected in the field across large spatial gradients. In this paper we use two datasets built from online repositories plus a standardised field collection to reconstruct macroecological patterns for marine bivalves along the eastern coastline of Australia – spanning over 20° of latitude. We test the strength of the latitudinal diversity gradient using four diversity measures and identify a biogeographical boundary. The field collection demonstrates a strong latitudinal gradient, but mixed support was found in the composite datasets. Worse, adding observation-based records to the composite dataset obscured the latitudinal gradient. The biogeographic boundary was consistently found, and the location mirrored two previously published bioregionalisations. Although broad patterns seen in the field can be uncovered from composite macroecological datasets, care both in dataset construction and choice of methods is needed to ensure robust results.

A document by Benjamin Carter. Click on the document to view its contents.

Latitudinal diversity gradients are among the most studied macroecological phenomena. However, they tend to be described using large composite datasets that often show taxonomic and geographic sampling bias. Here we describe a latitudinal gradient in marine bivalves along the eastern coastline of Australia, spanning 2,667km of coastline and 20° of latitude. We utilise a large, structured field dataset (5,552 individuals) in conjunction with a routine macroecological dataset downloaded from the Ocean Biogeographic Information System (OBIS - 36,226 specimens). Diversity is estimated using a series of analytical methods to account for undersampling, and biogeographic gradients in taxonomic composition are quantified and compared to existing biogeographical schemes. A strong latitudinal gradient is present in both datasets. However, the strength of the gradient depends on the dataset and analytical method used. The inclusion of observational data in the macroecological dataset obscures any latitudinal pattern. The documented biogeographic gradients are consistent with global and regional reconstructions. However, we find evidence for a strong transition zone between two clusters. Although latitudinal gradients inferred from large macroecological datasets such as OBIS can match those inferred from field data, care should be taken when curating downloaded data as small changes in protocol can generate very different results. By contrast, even modest regional field datasets can readily reconstruct latitudinal patterns.

Calculating spatial ranges of species and individuals is a crucial problem throughout ecology. However, sample size biases can be strong, and defining range boundaries can be difficult. These hurdles can be overcome by calculating areas without calculating boundaries. The first step is to algorithmically define a graph that connects the spatial points where observations have been made. The routine generates a small number of short edges that form a pattern resembling a mosaic. The edge lengths are summed, squared, divided by the edge count, and multiplied by a known constant to obtain a total area estimate for the shape. This non-parametric mosaic area method can work with irregular outlines and clumped point distributions. It is more accurate than convex hull, kernel density, and hypervolume estimation according to simulation analyses. Mosaic area calculations can be used in areas ranging all the way from conservation biology to morphometrics.