Semi‐Natural Habitats Buffer the Effects of Crop Diversification on Arthropod Pest Control Services in Agricultural Landscapes - Thomas Perrot; Léa Beaumelle; Eva Thomine; Yann Tricault; Nicolas Desneux; Matthias Albrecht; Péter Batáry; Felix Bianchi; Klaus Birkhofer; Aliette Bosem Baillod; Rebecca Chaplin‐Kramer; Anne‐Marie Cortesero; et al. (Ecology Letters, 2026)
Crop diversification is a promising strategy to strengthen pest control services in agricultural landscapes. Diversifying crops may limit pests through host crop dilution or by enhancing top‐down control by their enemies. However, crop diversification may also benefit generalist pests through higher resource continuity. Using a large‐scale dataset encompassing 742 landscapes across 13 countries, we assessed the impact of landscape‐scale crop diversity on the abundance of natural enemies, the potential for biological control, and insect pest abundance. Crop diversification did not increase the overall abundance of natural enemies or the potential for biological pest control. Instead, crop diversity primarily favoured the abundance of specialist natural enemies and pests in highly simplified landscapes, an effect that was reduced in landscapes with high proportions of semi‐natural habitats. Lastly, low proportions of host crops in the landscape were associated with higher abundances of natural enemies. Taken together, our results indicate that crop diversification is not a ‘one size fits all’ strategy to control agricultural pests, and that other landscape characteristics, such as high amounts of semi‐natural habitats, must be considered to enhance biological pest control services.

Movement and Habitat Use by Invasive Blue Catfish Ictalurus furcatus (Valenciennes 1840) in a Tidal Freshwater River (Maryland, USA) - Joseph W. Love; Branson D. Williams; Tim Groves; Ross Williams; Mary Groves (Estuaries and Coasts, 2025)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Subduction accretion, thermal overprinting, and exhumation of high-pressure/low-temperature metasedimentary rocks of the south-central brooks range - Tim M. O’Brien; M. Grove (International Geology Review, 2022)

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).

Calibration and Uncertainty Analysis of a Carbon Accounting Model to Stem Wood Density and Partitioning of Biomass for Eucalyptus globulus and Pinus Radiata - Keryn Paul; Phil Polglase; Peter Snowdon; Tivi Theiveyanathan; John Raison; Tim Grove; Stan Rance (New Forests, 2006)