Companion planting to attract pollinators increases the yield and quality of strawberry fruit in gardens and allotments

1. Global pollinator declines have led to concern that crop yields might fall as a result of a pollination deficit. Companion planting is a traditional practice thought to increase yield of insect pollinated crops by planting a co-flowering species next to the crop. 2. Using a combination of conventional researcher-led experiments and observational citizen scientist data, we tested the effectiveness of bee-friendly borage (Borago officinalis) as a companion plant to strawberry (Fragaria x ananassa). Insect visitors to the ‘Test’ (strawberry + borage) versus ‘Control’ (strawberry only) plants were observed, and strawberry fruit collected. Strawberries collected during the researcher-led experiment were also subject to fruit measurements and assessments of market quality. 3. Companion plants were found to significantly increase both yield and market quality of strawberries, suggesting an increase in insect pollination per plant. Test strawberries companion planted with borage produced an average of 35% more fruits, and 32% increased yield by weight. Test strawberry plants produced significantly more fruit of higher aesthetic quality when assessed by Marketing Standards for Strawberries. 4. Although there was no significant difference in the overall insect visits, when broken down by broad insect group there were significantly more flies visiting the test strawberries than controls. 5. These results could have implications for both gardeners and commercial growers. As consumers prefer a cosmetically perfect fruit, the production of fruit with increased aesthetics aids food waste reduction

Chapter 04: Ecological resilience, climate change and the Great Barrier Reef

The vulnerability assessments in this volume frequently refer to the resilience of various ecosystem elements in the face of climate change. This chapter provides an introduction to the concept of ecological resilience, and its application as part of a management response to climate change threats. As defined in the glossary, resilience refers to the capacity of a system to absorb shocks, resist dramatic changes in condition, and maintain or recover key functions and processes, without undergoing “phase shifts” to a qualitatively different state. For example, people who are physically and mentally fit and strong will have good prospect of recovery from disease, injury or trauma: they are resilient.This is Chapter 4 of Climate change and the Great Barrier Reef: a vulnerability assessment. The entire book can be found at http://hdl.handle.net/11017/13

The ecological drivers and consequences of wildlife trade

Wildlife trade is a key driver of extinction risk, affecting at least 24% of terrestrial vertebrates. The persistent removal of species can have profound impacts on species extinction risk and selection within populations. We draw together the first review of characteristics known to drive species use - identifying species with larger body sizes, greater abundance, increased rarity or certain morphological traits valued by consumers as being particularly prevalent in trade. We then review the ecological implications of this trade-driven selection, revealing direct effects of trade on natural selection and populations for traded species, which includes selection against desirable traits. Additionally, there exists a positive feedback loop between rarity and trade and depleted populations tend to have easy human access points, which can result in species being harvested to extinction and has the potential to alter source-sink dynamics. Wider cascading ecosystem repercussions from trade-induced declines include altered seed dispersal networks, trophic cascades, long-term compositional changes in plant communities, altered forest carbon stocks, and the introduction of harmful invasive species. Because it occurs across multiple scales with diverse drivers, wildlife trade requires multi-faceted conservation actions to maintain biodiversity and ecological function, including regulatory and enforcement approaches, bottom-up and community-based interventions, captive breeding or wildlife farming, and conservation translocations and trophic rewilding. We highlight three emergent research themes at the intersection of trade and community ecology: (1) functional impacts of trade; (2) altered provisioning of ecosystem services; and (3) prevalence of trade-dispersed diseases. Outside of the primary objective that exploitation is sustainable for traded species, we must urgently incorporate consideration of the broader consequences for other species and ecosystem processes when quantifying sustainability

Professionalism and the Millbank Tendency: The Political Sociology of New Labour's employees

This article analyses party employees, one of the most under-researched subjects in the study of British political parties. We draw on a blend of quantitative and qualitative data in order to shed light on the social and political profiles of Labour Party staff, and on the question of their professionalisation. The latter theme is developed through a model derived from the sociology of professions. While a relatively limited proportion of party employees conform to the pure ideal-type of professionalism, a considerably greater number manifest enough of the core characteristics of specialisation, commitment, mobility, autonomy and self-regulation to be reasonably described as 'professionals in pursuit of political outcomes'

Patterns of regional lung physiology in cystic fibrosis using ventilation magnetic resonance imaging and multiple-breath washout

Hyperpolarised helium-3 (3He) ventilation magnetic resonance imaging (MRI) and multiple-breath washout (MBW) are sensitive methods for detecting lung disease in cystic fibrosis (CF). We aimed to explore their relationship across a broad range of CF disease severity and patient age, as well as assess the effect of inhaled lung volume on ventilation distribution.32 children and adults with CF underwent MBW and 3He-MRI at a lung volume of end-inspiratory tidal volume (EIVT). In addition, 28 patients performed 3He-MRI at total lung capacity. 3He-MRI scans were quantitatively analysed for ventilation defect percentage (VDP), ventilation heterogeneity index (VHI) and the number and size of individual contiguous ventilation defects. From MBW, the lung clearance index, convection-dependent ventilation heterogeneity (Scond) and convection-diffusion-dependent ventilation heterogeneity (Sacin) were calculated.VDP and VHI at EIVT strongly correlated with lung clearance index (r=0.89 and r=0.88, respectively), Sacin (r=0.84 and r=0.82, respectively) and forced expiratory volume in 1 s (FEV1) (r=-0.79 and r=-0.78, respectively). Two distinct 3He-MRI patterns were highlighted: patients with abnormal FEV1 had significantly (p<0.001) larger, but fewer, contiguous defects than those with normal FEV1, who tended to have numerous small volume defects. These two MRI patterns were delineated by a VDP of ∼10%. At total lung capacity, when compared to EIVT, VDP and VHI reduced in all subjects (p<0.001), demonstrating improved ventilation distribution and regions of volume-reversible and nonreversible ventilation abnormalities

Global hotspots of traded phylogenetic and functional diversity

Wildlife trade is a multibillion-dollar industry1 targeting a hyperdiversity of species2 and can contribute to major declines in abundance3. A key question is understanding the global hotspots of wildlife trade for phylogenetic (PD) and functional (FD) diversity, which underpin the conservation of evolutionary history4, ecological functions5 and ecosystem services benefiting humankind6. Using a global dataset of traded bird and mammal species, we identify that the highest levels of traded PD and FD are from tropical regions, where high numbers of evolutionary distinct and globally endangered species in trade occur. The standardized effect size (ses) of traded PD and FD also shows strong tropical epicentres, with additional hotspots of mammalian ses.PD in the eastern United States and ses.FD in Europe. Large-bodied, frugivorous and canopy-dwelling birds and large-bodied mammals are more likely to be traded whereas insectivorous birds and diurnally foraging mammals are less likely. Where trade drives localized extinctions3, our results suggest substantial losses of unique evolutionary lineages and functional traits, with possible cascading effects for communities and ecosystems5,7. Avoiding unsustainable exploitation and lost community integrity requires targeted conservation efforts, especially in hotspots of traded phylogenetic and functional diversity

A dual-channel deep learning approach for lung cavity estimation from hyperpolarized gas and proton MRI

Background Hyperpolarized gas MRI can quantify regional lung ventilation via biomarkers, including the ventilation defect percentage (VDP). VDP is computed from segmentations derived from spatially co-registered functional hyperpolarized gas and structural proton (1H)-MRI. Although acquired at similar lung inflation levels, they are frequently misaligned, requiring a lung cavity estimation (LCE). Recently, single-channel, mono-modal deep learning (DL)-based methods have shown promise for pulmonary image segmentation problems. Multichannel, multimodal approaches may outperform single-channel alternatives. Purpose We hypothesized that a DL-based dual-channel approach, leveraging both 1H-MRI and Xenon-129-MRI (129Xe-MRI), can generate LCEs more accurately than single-channel alternatives. Study Type Retrospective. Population A total of 480 corresponding 1H-MRI and 129Xe-MRI scans from 26 healthy participants (median age [range]: 11 [8–71]; 50% females) and 289 patients with pulmonary pathologies (median age [range]: 47 [6–83]; 51% females) were split into training (422 scans [88%]; 257 participants [82%]) and testing (58 scans [12%]; 58 participants [18%]) sets. Field Strength/Sequence 1.5-T, three-dimensional (3D) spoiled gradient-recalled 1H-MRI and 3D steady-state free-precession 129Xe-MRI. Assessment We developed a multimodal DL approach, integrating 129Xe-MRI and 1H-MRI, in a dual-channel convolutional neural network. We compared this approach to single-channel alternatives using manually edited LCEs as a benchmark. We further assessed a fully automatic DL-based framework to calculate VDPs and compared it to manually generated VDPs. Statistical Tests Friedman tests with post hoc Bonferroni correction for multiple comparisons compared single-channel and dual-channel DL approaches using Dice similarity coefficient (DSC), average boundary Hausdorff distance (average HD), and relative error (XOR) metrics. Bland–Altman analysis and paired t-tests compared manual and DL-generated VDPs. A P value < 0.05 was considered statistically significant. Results The dual-channel approach significantly outperformed single-channel approaches, achieving a median (range) DSC, average HD, and XOR of 0.967 (0.867–0.978), 1.68 mm (37.0–0.778), and 0.066 (0.246–0.045), respectively. DL-generated VDPs were statistically indistinguishable from manually generated VDPs (P = 0.710). Data Conclusion Our dual-channel approach generated LCEs, which could be integrated with ventilated lung segmentations to produce biomarkers such as the VDP without manual intervention. Evidence Level 4. Technical Efficacy Stage 1

Functional imaging in asthma and COPD: design of the NOVELTY ADPro substudy

The NOVEL observational longiTudinal studY (NOVELTY; ClinicalTrials.gov identifier: NCT02760329) is a global, prospective, observational study of ∼12 000 patients with a diagnosis of asthma and/or chronic obstructive pulmonary disease (COPD). Here we describe the design of the Advanced Diagnostic Profiling (ADPro) substudy of NOVELTY being conducted in a subset of ∼180 patients recruited from two primary care sites in York, UK. ADPro is employing a combination of novel functional imaging and physiological and metabolic modalities to explore structural and functional changes in the lungs, and their association with different phenotypes and endotypes. Patients participating in the ADPro substudy will attend two visits at the University of Sheffield, UK, 12±2 months apart, at which they will undergo imaging and physiological lung function testing. The primary endpoints are the distributions of whole lung functional and morphological measurements assessed with Xenon-129 magnetic resonance imaging, including ventilation, gas transfer and airway microstructural indices. Physiological assessments of pulmonary function include spirometry, bronchodilator reversibility, static lung volumes via body plethysmography, transfer factor of the lung for carbon monoxide, multiple-breath nitrogen washout and airway oscillometry. Fractional exhaled nitric oxide will be measured as a marker of Type-2 airways inflammation. Regional and global assessment of lung function using these techniques will enable more precise phenotyping of patients with physician-assigned asthma and/or COPD. These techniques will be assessed for their sensitivity to markers of early disease progression

PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation

Functional lung imaging modalities such as hyperpolarized gas MRI ventilation enable visualization and quantification of regional lung ventilation; however, these techniques require specialized equipment and exogenous contrast, limiting clinical adoption. Physiologically-informed techniques to map proton (1H)-MRI ventilation have been proposed. These approaches have demonstrated moderate correlation with hyperpolarized gas MRI. Recently, deep learning (DL) has been used for image synthesis applications, including functional lung image synthesis. Here, we propose a 3D multi-channel convolutional neural network that employs physiologically-informed ventilation mapping and multi-inflation structural 1H-MRI to synthesize 3D ventilation surrogates (PhysVENeT). The dataset comprised paired inspiratory and expiratory 1H-MRI scans and corresponding hyperpolarized gas MRI scans from 170 participants with various pulmonary pathologies. We performed fivefold cross-validation on 150 of these participants and used 20 participants with a previously unseen pathology (post COVID-19) for external validation. Synthetic ventilation surrogates were evaluated using voxel-wise correlation and structural similarity metrics; the proposed PhysVENeT framework significantly outperformed conventional 1H-MRI ventilation mapping and other DL approaches which did not utilize structural imaging and ventilation mapping. PhysVENeT can accurately reflect ventilation defects and exhibits minimal overfitting on external validation data compared to DL approaches that do not integrate physiologically-informed mapping