John Alroy's research while affiliated with Macquarie University and other places

1. Counts of species in ecological samples are of interest when they tell us about community assembly processes. Older process-based models of count distributions are either complex, widely rejected, or not able to predict high unevenness. 2. I leverage a general strategy for deriving simple one-parameter models. A distribution of abundances x on a continuous scale is predicted from a transform of a uniform distribution U; U is solved for to yield one minus a cumulative distribution function (CDF) for x; and the result is differenced and rounded to down to yield a probability mass function. The same workflow has long been used to derive the geometric series from the exponential distribution. Three variants are proposed, respectively based on the transforms /U –  = ( – U)/U where  is a constant (a scaled odds ratio); (1/U – 1)1/p where p is a constant; and [–ln(U)/]2 where –ln U is just an exponential random variate and  is a constant. 3. The distributions are all consistent with simple population dynamical models in which recruitment rates, and sometimes death rates, vary randomly amongst species and are fixed for each species. The number of recruited offspring produced during each interval by each species is Poisson-distributed, and death rates are per-capita. Population counts are equilibrial, allowing co-existence in the absence of competition. 4. Large-scale surveys of corals, fishes, butterflies, and trees are consistent with the distributions, as are local-scale inventories of trees and assorted vertebrate and insect groups. Each inventory is used to predict the counts of another one that is matched based on group representation, biogeography, and richness. Based on examining decisive differences between the resulting likelihoods, the new models routinely outperform eight different rivals. 5. Thanks to their simplicity, grounding in non-competitive equilibrial population dynamics, and predictive power, the new approaches have considerable relevance throughout ecology.

Species abundance distributions, meaning counts of individuals apportioned among species, are fundamental patterns in ecology. Numerous distribution models have been proposed, and most suffer from poor fit to data, complex formulation, excessive parameterisation, or unrealistic modelling of processes. I discuss three that meet all the basic criteria, are easily distinguished, and stem from simple and distinct population dynamics. The log series can be produced by assuming taxonomically and temporally fixed turnover rates. A model derived from scaled odds ratios assumes highly variable dynamics, and one derived from exponential variates assumes taxonomically variable but temporally fixed rates. Mathematical derivations are elementary. Maximum likelihood fits to published empirical data suggest that the two new distributions are more common in nature. Saturated models are rarely better. Ecological communities may be assembled by processes that are easily discerned, instead of being as mysterious as many have thought.

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.

Mammalian herbivores play a pivotal role in Earth System processes by affecting biogeochemical cycles and ecosystem functioning, potentially leading to significant repercussions on atmosphere–biosphere feedbacks. Global dynamic models of mammalian populations can improve our understanding of their ecological role at large scales and the consequences of their extinctions. However, such models are still lacking and mammals are poorly integrated in Earth System Science. We developed a mechanistic global model of terrestrial herbivore populations simulated with 37 functional groups defined through the analysis of eco‐physiological traits across all extant herbivores (2599 species). We coupled this model with a global vegetation model to predict herbivores' maximum potential biomass in pre‐industrial and at present‐day and to study the environmental drivers explaining the distribution of herbivore biomass. Present‐day biomass was estimated by accounting for anthropogenic activity causing habitat and range losses. We show that natural ecosystems could have sustained a potential wild herbivore wet biomass of 330 Mt (95% CI: 245–417), comprised of 193 Mt (95% CI: 177–208) by large species (body mass >1–10 kg, depending on functional group) and 138 Mt (95% CI: 68–209) by small species. We estimate that the remaining present‐day large herbivores biomass is 82 Mt (95% CI: 32–133), reduced by 57% due to anthropogenic activity; consequently, small herbivores currently dominate global herbivore biomass with 98 Mt (95% CI: 91–106, −29%). Losses vary greatly across climatic zones and functional groups, suggesting that size is not the only discriminant feature of biomass decline. Actual evapotranspiration is the most important driver of total, large and small herbivore biomass and explains 64%, 59% and 49% of its variation, respectively. Distribution of modelled and observed large herbivores' biomass suggested a high dependency on energy and water with more biomass in hot and wet areas. These results challenge the notion that large herbivore biomass peaks primarily in ecosystems with intermediate precipitation levels such as savannas. Outside Africa and the Tropics, pre‐industrial biomass hotspots occur in areas today dominated by humans; this could undermine the recovery of larger species biomass in certain areas. Our herbivore biomass estimates provide a quantitative benchmark for setting conservation and rewilding goals at large spatial scales. The herbivore model and functional classification create new opportunities to integrate mammals into Earth System Science and models. Read the free Plain Language Summary for this article on the Journal blog.

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.

The relationship between tree species diversity, measures of forest structure, and forest biomass has long been debated, with local- or continental-scale studies often finding contrasting results. Given the importance of forests as global carbon sinks, understanding the characteristics that underpin biomass accumulation is thus a critical component of mitigating climate change. Here we present a global analysis of 11,400 forest plots, sourced from scientific publications and forest inventories, to investigate the association of forest basal area (used as a proxy for biomass) with stem density and measures of tree species diversity (richness and evenness). We used generalised additive models to account for the confounding effects of climate and spatial signal and we modelled the density, climate, and diversity effects both globally and for each biogeographic region. Stem density showed a strong positive association with basal area across all biogeographic regions, while the effect of species richness varied. In the Palearctic, Nearctic, and Neotropical biogeographic regions, basal area was positively associated with species richness, although this was only detectable for lower values of basal area. In the Ethiopian and Oriental biogeographic regions there was no relationship between richness and basal area, while in the Australian biogeographic regions it was negative. The weak-to-no association between species evenness and basal area in all bioregions other than Australia suggests that the overall correlation emerges from processes operating at more local scales. Our results highlight the importance of accounting for biogeographic processes when evaluating strategies to mitigate climate change and support nature conservation.

Extinction is a new open-access journal focused on the patterns and processes underlying the loss of biodiversity. It aims to inform conservation efforts, with a broad spatial and temporal scope. Extinction biology – the scientific study of species loss – has a long history and has recently become a more interdisciplinary and integrated field. This journal offers a unique, synthetic forum in which to present cutting-edge research and discuss its implications. This includes ecological, molecular, paleontological, and social perspectives, based on empirical data, theory, and modelling, to understand extinction processes. By tackling the big challenges, the research published in Extinction will be valuable for researchers and practitioners concerned with extinction and its role in shaping the history and future of life on Earth.