Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015

Impact of sublingual nitroglycerin dosage on FFRCT assessment and coronary luminal volume-to-myocardial mass ratio.

OBJECTIVES: Fractional flow reserve computed tomography (FFRCT) depends upon nitroglycerin (NTG) inducing maximal hyperemia. However, the impact of NTG dosages on FFRCT analysis including coronary volume-to-mass ratio (V/M) is unknown. METHODS: Eighty patients with repeat coronary CT angiograms (CCTAs) with different sublingual spray NTG doses (0.4 mg and 0.8 mg) were retrospectively analyzed with 45 patients excluded. Patient and scan demographics, post-stenosis and nadir FFRCT values, coronary volume, and coronary volume-to-mass ratio (V/M) were compared at initial CCTA (0.4 mg NTG) and follow-up CCTA (0.8 mg NTG). Differences were compared by Wilcoxon signed-rank test. RESULTS: Thirty-five patients were included (time between CCTAs, 3.9 ± 1.6 years). Segment involvement score was 2.4 ± 3.3 and 2.8 ± 3.4 at initial and repeat CCTA (0.4 and 0.8 mg NTG), respectively (p = 0.004). There was similar image quality (4.1 ± 0.7 vs 4.1 ± 0.8; p = 0.51). Nadir FFRCT values did not differ in the left (0.4 mg, 0.80 ± 0.08 vs 0.8 mg, 0.80 ± 0.03; p = 0.66), right (0.4 mg, 0.90 ± 0.04 vs 0.8 mg, 0.90 ± 0.06; p = 0.25), or circumflex coronaries (0.4 mg, 0.87 ± 0.06 vs 0.8 mg, 0.88 ± 0.06; p = 0.34). Post-stenosis FFRCT values did not differ (p = 0.65). Coronary volume increased with 0.8 mg of NTG (2639 ± 753 mm3 vs 2844.8 ± 827 mm3; p = 0.009) but V/M ratio did not (p = 0.20). CONCLUSIONS: Use of 0.8 mg versus 0.4 mg of NTG in routine clinical CCTAs significantly increased coronary volume determined from FFRCT analysis but did not alter FFRCT or V/M. Further evaluation of repeat CCTAs in a more contemporaneous fashion using varied nitrate doses and disease severity is needed. KEY POINTS: • Fractional flow reserve from computed tomography (FFRCT) is a noninvasive method for evaluating the coronary arteries and relies on nitroglycerin (NTG) to induce coronary vasodilation, but the impact of different NTG dosages is unknown. • Retrospective analysis evaluated use of different NTG doses on FFRCT. • Increased NTG dose increased coronary luminal volume on FFRCTanalysis, but did not change FFRCTvalues

Hypertrophic Cardiomyopathy (HCM): New insights into Coronary artery remodelling and ischemia from FFRCT.

INTRODUCTION: Angina, myocardial ischemia, and coronary artery physiology in hypertrophic cardiomyopathy (HCM) are poorly understood. However, coronary computed tomography angiography (CCTA) with fractional flow reserve from CT (FFRCT) analysis offers a non-invasive method for evaluation of coronary artery volume to myocardial mass ratio (V/M) that may provide insight into such mechanisms. Thus, we sought to investigate changes in V/M in HCM. METHODS: A retrospective analysis was performed on 37 HCM patients and 37 controls matched for age, sex, and cardiovascular risk factors; CCTA-derived coronary artery lumen volume (V) and myocardial mass (M) were used to determine V/M. FFRCT values were calculated for the left anterior descending (LAD), left circumflex (LCx) and right coronary (RCA) arteries as well as the 3-vessel cumulative FFRCT values. RESULTS: HCM patients had significantly increased myocardial mass (176 ± 84 vs. 119 ± 27 g, p < 0.0001) and total coronary artery luminal volume (4112 ± 1139 vs. 3290 ± 924 mm3, p < 0.0001) that resulted from increases in segmented luminal volumes of both the left and right coronary artery systems. However, HCM patients had significantly decreased V/M (23.8 ± 5.9 vs. 26.5 ± 5.3 mm3/g; p = 0.026) which was further decreased when restricting V/M analysis to those HCM patients with septal hypertrophy (22.4 mm3/g, p = 0.01) that was mild-moderately predictive of HCM (AUC = 0.68). HCM patients also showed significantly lower nadir FFRCT values in the LCx (0.87 ± 0.06 vs. 0.91 ± 0.06, p = 0.02), and cumulative 3-vessel FFRCT values (2.58 ± 0.18 vs. 2.63 ± 0.14, p = 0.006). CONCLUSIONS: HCM patients demonstrate significantly greater coronary volume. Despite this, HCM patients suffer from decreased V/M. Further prospective studies evaluating the relationship between V/M, angina, and heart failure in HCM are needed

The Rural Household Multiple Indicator Survey (RHoMIS) data of 13,310 farm households in 21 countries

The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 753 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators like the Poverty Probability Index, the Household Food Insecurity Access Scale and dietary diversity. These variables are used to quantify more than 40 different aggregate indicators on farm household characteristics, welfare, productivity and economic performance. Between 2015 and the beginning of 2018, the survey instrument has been applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here cover the raw data, the indicator calculation code and the resulting indicator values, and can be used to quantify on- and off-farm pathways to food security, diverse diets and reduced poverty of rural smallholder farm households. (2019-10-31

Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases.

Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises