Predictors of Food Web Resistance to Environmental Change - Javier Jarillo; Jonathan F. Jupke; Tom Sinclair; Lorraine Maltby; Ralf B. Schäfer; Frederik De Laender (Ecology Letters, 2026)
Impacts of environmental change on ecosystems are seemingly highly context‐dependent and contingent on details. Here, we provide mathematical and numerical evidence that there is some generality to the resistance of food webs to species loss. To this end, we mathematically analyse simple food web models, run simulations with randomly wired food webs, develop a spatially explicit meta‐community model for realistic macroinvertebrate communities inhabiting European streams, and analyse field data. These approaches jointly support three general rules for food web resistance: (1) all else equal, predators are more vulnerable than prey, and predator diversity declines before prey diversity; (2) food webs with higher prey diversity tend to be less resistant to environmental change; and (3) food web resistance decreases with the mean taxon tolerance and reaches a maximum at an optimal ratio of predator to prey tolerance. Our findings elucidate characteristics that make food webs vulnerable, fostering more effective conservation practices.

A Lagrangian view on severe haze in Beijing: local and long-range sources of trace gases and primary and secondary aerosols - Benjamin Foreback; Petri Clusius; Metin Baykara; Alexander Mahura; Lukas Pichelstorfer; Carlton Xavier; Putian Zhou; Tom V. Kokkonen; Veli-Matti Kerminen; Yongchun Liu; Men Xia; Xin Chen; et al. (Atmospheric Environment, 2025)

Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants - Tom Sinclair; Peter Craig; Lorraine L. Maltby (Global Change Biology, 2024)
Freshwaters are highly threatened ecosystems that are vulnerable to chemical pollution and climate change. Freshwater taxa vary in their sensitivity to chemicals and changes in species composition can potentially affect the sensitivity of assemblages to chemical exposure. Here we explore the potential consequences of future climate change on the composition and sensitivity of freshwater macroinvertebrate assemblages to chemical stressors using the UK as a case study. Macroinvertebrate assemblages under end of century (2080–2100) and baseline (1980–2000) climate conditions were predicted for 608 UK sites for four climate scenarios corresponding to mean temperature changes of 1.28 to 3.78°C. Freshwater macroinvertebrate toxicity data were collated for 19 chemicals and the hierarchical species sensitivity distribution model was used to predict the sensitivity of untested taxa using relatedness within a Bayesian approach. All four future climate scenarios shifted assemblage compositions, increasing the prevalence of Mollusca, Crustacea and Oligochaeta species, and the insect taxa of Odonata, Chironomidae, and Baetidae species. Contrastingly, decreases were projected for Plecoptera, Ephemeroptera (except for Baetidae) and Coleoptera species. Shifts in taxonomic composition were associated with changes in the percentage of species at risk from chemical exposure. For the 3.78°C climate scenario, 76% of all assemblages became more sensitive to chemicals and for 18 of the 19 chemicals, the percentage of species at risk increased. Climate warming‐induced increases in sensitivity were greatest for assemblages exposed to metals and were dependent on baseline assemblage composition, which varied spatially. Climate warming is predicted to result in changes in the use, environmental exposure and toxicity of chemicals. Here we show that, even in the absence of these climate‐chemical interactions, shifts in species composition due to climate warming will increase chemical risk and that the impact of chemical pollution on freshwater macroinvertebrate biodiversity may double or quadruple by the end of the 21st century.

Grazing management for soil carbon in Australia: A review - Sarah E. McDonald; Warwick Badgery; Simon Clarendon; Susan Orgill; Katrina Sinclair; Rachelle Meyer; Dominique Bowen Butchart; Richard Eckard; David Rowlings; Peter Grace; Natalie Doran-Browne; Steven Harden; et al. (Journal of Environmental Management, 2023)

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).