Community assembly on isolated islands: macroecology meets evolution - A. J. Rominger; K. R. Goodman; J. Y. Lim; E. E. Armstrong; L. E. Becking; G. M Bennett; M. S. Brewer; D. D. Cotoras; C. P. Ewing; J. Harte; N. D. Martinez; P. M. O'Grady; et al. (Global Ecology and Biogeography, 2016)
Aim Understanding how ecological and evolutionary processes together determine patterns of biodiversity remains a central aim in biology. Guided by ecological theory, we use data from multiple arthropod lineages across the Hawaiian archipelago to explore the interplay between ecological (population dynamics, dispersal, trophic interactions) and evolutionary (genetic structuring, adaptation, speciation, extinction) processes. Our goal is to show how communities develop from the dynamic feedbacks that operate at different temporal and spatial scales. Location The Hawaiian islands (19–22° N , 155–160° W ). Methods We synthesize genetic data from selected arthropods across the Hawaiian archipelago to determine the relative role of dispersal and in situ differentiation across the island chronosequence. From four sites on three high islands with geological ages ranging from Results From the perspective of the island chronosequence we show that species at lower trophic levels develop population genetic structure at smaller temporal and spatial scales than species at higher trophic levels. Network nestedness decreases while modularity increases with habitat age. Single‐island endemics exhibit more specialization than broadly distributed species, but both show the least specialization in communities on middle‐aged substrates. Plant–herbivore networks also show the least deviation from theoretical predictions in middle‐aged communities. Main conclusions The application of ecological theory to island chronosequences can illuminate feedbacks between ecological and evolutionary processes in community assembly. We show how patterns of population genetic structure, decreasing network nestedness, increasing network modularity and increased specialization shift from early assembly driven by immigration, to in situ diversification after > 1 Myr. Herbivore–plant communities only transiently achieve statistical steady state during assembly, presumably due to incomplete assembly from dispersal in the early stages, and the increasing influence of island ontogeny on older islands.

Unpacking Pandora’s Box: Understanding and Categorising Ecosystem Disservices for Environmental Management and Human Wellbeing - C. M. Shackleton; S. Ruwanza; G. K. Sinasson Sanni; S. Bennett; P. De Lacy; R. Modipa; N. Mtati; M. Sachikonye; G. Thondhlana (Ecosystems, 2016)

Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale - Keryn I. Paul; Stephen H. Roxburgh; Jerome Chave; Jacqueline R. England; Ayalsew Zerihun; Alison Specht; Tom Lewis; Lauren T. Bennett; Thomas G. Baker; Mark A. Adams; Dan Huxtable; Kelvin D. Montagu; et al. (Global Change Biology, 2016)
Accurate ground‐based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost‐effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above‐ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power‐law models explained 84–95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand‐based biomass from allometric models of varying levels of generalization (species‐specific, plant functional type) were validated using whole‐plot harvest data from 17 contrasting stands (range: 9–356 Mg ha −1 ). Losses in efficiency of prediction were stand ‐level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost‐effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species‐specific models is only warranted when gains in accuracy of stand‐based predictions are relatively high (e.g. high‐value monocultures).