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Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into ‘many-row (observation), many-column (species)‘ datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These ‘novel community datasets’ let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers using a deep neural net in a joint species distribution model. With this approach, we generate distribution maps for 76 arthropod species across a 225 km²temperate-zone forested landscape. We combine the maps to visualize the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this ‘sideways biodiversity modelling’ method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres. This article is part of the theme issue ‘Towards a toolkit for global insect biodiversity monitoring’. 

Iodine oxoacids are recognised for their significant contribution to the formation of new particles in marine and polar atmospheres. Nevertheless, to incorporate the iodine oxoacid nucleation mechanism into global simulations, it is essential to comprehend how this mechanism varies under various atmospheric conditions. In this study, we combined measurements from the CLOUD (Cosmic Leaving OUtdoor Droplets) chamber at CERN and simulations with a kinetic model to investigate the impact of temperature, ionisation, and humidity on iodine oxoacid nucleation. Our findings reveal that ion-induced particle formation rates remain largely unaffected by changes in temperature. However, neutral particle formation rates experience a significant increase when the temperature drops from +10 ^oC to −10 ^oC. Running the kinetic model with varying ionisation rates demonstrates that the particle formation rate only increases with a higher ionisation rate when the iodic acid concentration exceeds 1.5 × 10⁷ cm^sup>−3, a concentration rarely reached in pristine marine atmospheres. Consequently, our simulations suggest that, despite higher ionisation rates, the charged cluster nucleation pathway of iodic acid is unlikely to be enhanced in the upper troposphere by higher ionisation rates. Instead, the neutral nucleation channel is likely to be the dominant channel in that region. Notably, the iodine oxoacid nucleation mechanism remains unaffected by changes in relative humidity from 2% to 80%. However, under unrealistically dry conditions (below 0.008% RH at +10 ^oC), iodine oxides (I₂O₄ and I₂O₅) significantly enhance formation rates. Therefore, we conclude that iodine oxoacid nucleation is the dominant nucleation mechanism for iodine nucleation in the marine and polar boundary layer atmosphere. 

Inhomogeneities in temperature and ammonia concentrations can cause rapid growth of nanoparticles in polluted environments. 

Abstract. Extractive electrospray ionization (EESI) has been a well-knowntechnique for high-throughput online molecular characterization of chemicalreaction products and intermediates, detection of native biomolecules, invivo metabolomics, and environmental monitoring with negligible thermal andionization-induced fragmentation for over two decades. However, the EESIextraction mechanism remains uncertain. Prior studies disagree on whetherparticles between 20 and 400 nm diameter are fully extracted or if theextraction is limited to the surface layer. Here, we examined the analyteextraction mechanism by assessing the influence of particle size and coatingthickness on the detection of the molecules therein. We find that particlesare extracted fully: organics-coated NH4NO3 particles with afixed core volume (156 and 226 nm in diameter without coating) showedconstant EESI signals for NH4NO3 independent of the shell coatingthickness, while the signals of the secondary organic molecules comprisingthe shell varied proportionally to the shell volume. We also found that theEESI sensitivity exhibited a strong size dependence, with an increase insensitivity by 1–3 orders of magnitude as particle size decreasedfrom 300 to 30 nm. This dependence varied with the electrospray (ES)droplet size, the particle size and the residence time for coagulation in theEESI inlet, suggesting that the EESI sensitivity was influenced by thecoagulation coefficient between particles and ES droplets. Overall, ourresults indicate that, in the EESI, particles are fully extracted by the ESdroplets regardless of the chemical composition, when they are collected bythe ES droplets. However, their coalescence is not complete and dependsstrongly on their size. This size dependence is especially relevant whenEESI is used to probe size-varying particles as is the case in aerosolformation and growth studies with size ranges below 100 nm. 

Abstract Detecting and understanding disturbance is a challenge in ecology that has grown more critical with global environmental change and the emergence of research on social–ecological systems. We identify three areas of research need: developing a flexible framework that incorporates feedback loops between social and ecological systems, anticipating whether a disturbance will change vulnerability to other environmental drivers, and incorporating changes in system sensitivity to disturbance in the face of global changes in environmental drivers. In the present article, we review how discoveries from the US Long Term Ecological Research (LTER) Network have influenced theoretical paradigms in disturbance ecology, and we refine a framework for describing social–ecological disturbance that addresses these three challenges. By operationalizing this framework for seven LTER sites spanning distinct biomes, we show how disturbance can maintain or alter ecosystem state, drive spatial patterns at landscape scales, influence social–ecological interactions, and cause divergent outcomes depending on other environmental changes. 

Abstract Elevational and latitudinal gradients in species diversity may be mediated by biotic interactions that cause density‐dependent effects of conspecifics on survival or growth to differ from effects of heterospecifics (i.e. conspecific density dependence), but limited evidence exists to support this. We tested the hypothesis that conspecific density dependence varies with elevation using over 40 years of data on tree survival and growth from 23 old‐growth temperate forest stands across a 1,000‐m elevation gradient. We found that conspecific‐density‐dependent effects on survival of small‐to‐intermediate‐sized focal trees were negative in lower elevation, higher diversity forest stands typically characterised by warmer temperatures and greater relative humidity. Conspecific‐density‐dependent effects on survival were less negative in higher elevation stands and ridges than in lower elevation stands and valley bottoms for small‐to‐intermediate‐sized trees, but were neutral for larger trees across elevations. Conspecific‐density‐dependent effects on growth were negative across all tree size classes and elevations. These findings reveal fundamental differences in biotic interactions that may contribute to relationships between species diversity, elevation and climate.