Ecology of Urban Bees: A Review of Current Knowledge and Directions for Future Study

Urban bee ecology is an emerging field that holds promise for advancing knowledge of bee community dynamics and promoting bee conservation. Published studies of bee communities in urban and suburban habitats are fewer than those documenting bees in agricultural and wildland settings. As land lost to urbanization is predicted to increase in coming years the necessity of studying urban bee populations is growing. We reviewed 59 publications on urban bee ecology with the following goals, to assess current knowledge, to highlight areas in need of further research, and to suggest applications of study findings to bee conservation. Methodological variation between studies was discussed in the context of data interpretation. Identified trends in urban areas included the following, negative correlation between bee species richness and urban development, cavity-nesters increase in abundance in urban habitats, and floral specialists are scarce. Future directions for studying urban bee ecology include incorporation of landscape-scale assessments, conducting manipulative experiments and actively designing urban bee habitats. We include descriptions of plant and habitat management techniques derived from our research in northern and southern California urban habitats to promote development of bee-friendly habitats

Proximal hyperspectral sensing and data analysis approaches for field-based plant phenomics

Field-based plant phenomics requires robust crop sensing platforms and data analysis tools to successfully identify cultivars that exhibit phenotypes with high agronomic and economic importance. Such efforts will lead to genetic improvements that maintain high crop yield with concomitant tolerance to environmental stresses. The objectives of this study were to investigate proximal hyperspectral sensing with a field spectroradiometer and to compare data analysis approaches for estimating four cotton phenotypes: leaf water content (Cw), specific leaf mass (Cm), leaf chlorophyll a+b content (Cab), and leaf area index (LAI). Field studies tested 25 Pima cotton cultivars grown under well-watered and water-limited conditions in central Arizona from 2010 to 2012. Several vegetation indices, including the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the physiological (or photochemical) reflectance index (PRI) were compared with partial least squares regression (PLSR) approaches to estimate the four phenotypes. Additionally, inversion of the PROSAIL plant canopy reflectance model was investigated to estimate phenotypes based on 3.68 billion PROSAIL simulations on a supercomputer. Phenotypic estimates from each approach were compared with field measurements, and hierarchical linear mixed modeling was used to identify differences in the estimates among the cultivars and water levels. The PLSR approach performed best and estimated Cw,Cm,Cab, and LAI with root mean squared errors (RMSEs) between measured and modeled values of 6.8%, 10.9%, 13.1%, and 18.5%, respectively. Using linear regression with the vegetation indices, no index estimated Cw,Cm,Cab, and LAI with RMSEs better than 9.6%, 16.9%, 14.2%, and 28.8%, respectively. PROSAIL model inversion could estimate Cab and LAI with RMSEs of about 16% and 29%, depending on the objective function. However, the RMSEs for Cw and Cm from PROSAIL model inversion were greater than 30%. Compared to PLSR, advantages to the physically-based PROSAIL model include its ability to simulate the canopy's bidirectional reflectance distribution function (BRDF) and to estimate phenotypes from canopy spectral reflectance without a training data set. All proximal hyperspectral approaches were able to identify differences in phenotypic estimates among the cultivars and irrigation regimes tested during the field studies. Improvements to these proximal hyperspectral sensing approaches could be realized with a high-throughput phenotyping platform able to rapidly collect canopy spectral reflectance data from multiple view angles

Development and application of process-based simulation models for cotton production: a review of past, present, and future directions

The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeastern United States in the 1960's and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation models, examines applications of the models since the turn of the century, and identifies opportunities for improving models and their use in cotton research and decision support. Cotton models reviewed include those specific to cotton (GOSSYM, Cotton2K, COTCO2, OZCOT, and CROPGRO-Cotton) and generic crop models that have been applied to cotton production (EPIC, WOFOST, SUCROS, GRAMI, CropSyst, and AquaCrop). Model application areas included crop water use and irrigation water management, nitrogen dynamics and fertilizer management, genetics and crop improvement, climatology, global climate change, precision agriculture, model integration with sensor data, economics, and classroom instruction. Generally, the literature demonstrated increased emphasis on cotton model development in the previous century and on cotton model application in the current century. Although efforts to develop cotton models have a 40-year history, no comparisons among cotton models were reported. Such efforts would be advisable as an initial step to evaluate current cotton simulation strategies. Increasingly, cotton simulation models are being applied by non-traditional crop modelers, who are not trained agronomists but wish to use the models for broad economic or life cycle analyses. While this trend demonstrates the growing interest in the models and their potential utility for a variety of applications, it necessitates the development of models with appropriate complexity and ease-of-use for a given application, and improved documentation and teaching materials are needed to educate potential model users. Spatial scaling issues are also increasingly prominent, as models originally developed for use at the field scale are being implemented for regional simulations over large geographic areas. Research steadily progresses toward the advanced goal of model integration with variable-rate control systems, which use real-time crop status and environmental information to spatially and temporally optimize applications of crop inputs, while also considering potential environmental impacts, resource limitations, and climate forecasts. Overall, the review demonstrates a languished effort in cotton simulation model development, but the application of existing models in a variety of research areas remains strong and continues to grow

Phenolic compounds in young developing kiwifruit in relation to light exposure: Implications for fruit calcium accumulation

The interaction between light availability and the biosynthesis of phenolic compounds in fruit of kiwifruit (Actinidia deliciosa var. deliciosa, C.F. Liang et A. R. Ferguson) was investigated. Fruits were exposed either to natural light or were artificially shaded while growing on mature vines and were analysed weekly during the first 11 weeks of development. Phenols were identified and quantified by using High Performance Liquid Chromatography (HPLC). Results showed that the predominant phenolic compounds were hydroxycinnamic acids (HCAs), flavonols and the flavan 3-ol epicatechin. Calcium (Ca2+), the main mineral nutrient involved in fruit quality was also determined. Light significantly increased the accumulation of both phenols and Ca2+ into the fruit. This work expands the list of known phenolics in kiwifruit and provides a possible explanation for the seasonal pattern of Ca2+ import into the fruit. Results on light–phenol interaction being apparently beneficial for fruit Ca2+ accumulation, suggest that accurate canopy management could enhance fruit quality

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults

Backgroun

Pregnancy-Associated Hypertension in Glucose-Intolerant Pregnancy and Subsequent Metabolic Syndrome

To evaluate whether pregnancy-associated hypertension (preeclampsia or gestational hypertension), among women with varying degrees of glucose intolerance during pregnancy is associated with maternal metabolic syndrome 5-10 years later

The DEHVILS Survey Overview and Initial Data Release: High-Quality Near-Infrared Type Ia Supernova Light Curves at Low Redshift

While the sample of optical Type Ia Supernova (SN Ia) light curves (LCs) usable for cosmological parameter measurements surpasses 2000, the sample of published, cosmologically viable near-infrared (NIR) SN Ia LCs, which have been shown to be good "standard candles," is still $\lesssim$ 200. Here, we present high-quality NIR LCs for 83 SNe Ia ranging from $0.002 < z < 0.09$ as a part of the Dark Energy, H$_0$, and peculiar Velocities using Infrared Light from Supernovae (DEHVILS) survey. Observations are taken using UKIRT's WFCAM, where the median depth of the images is 20.7, 20.1, and 19.3 mag (Vega) for $Y$, $J$, and $H$-bands, respectively. The median number of epochs per SN Ia is 18 for all three bands ($YJH$) combined and 6 for each band individually. We fit 47 SN Ia LCs that pass strict quality cuts using three LC models, SALT3, SNooPy, and BayeSN and find scatter on the Hubble diagram to be comparable to or better than scatter from optical-only fits in the literature. Fitting NIR-only LCs, we obtain standard deviations ranging from 0.128-0.135 mag. Additionally, we present a refined calibration method for transforming 2MASS magnitudes to WFCAM magnitudes using HST CALSPEC stars that results in a 0.03 mag shift in the WFCAM $Y$-band magnitudes.Comment: 24 pages, 9 figures. Accepted by MNRA

The architecture of a probation office: a reflection of policy and an impact on practice

This article illustrates how the physicality of a probation office can be considered both integral to, and representative of, several important changes in the probation service’s recent history through analysis of research conducted in a probation office. I suggest that the relationship between the ‘protected’ zone of the office and the ‘unprotected’ zone of the waiting area and interview rooms is similar to Goffman’s ‘frontstage’ and ‘backstage’ and expand on his theory of social action by describing how the architecture of probation represents and potentially perpetuates the rise of risk, punishment and managerialism in probation. The article then moves onto the exterior and location of the office to look at how these represent probation’s move away from the communities it serves as well as inadvertently increasing the amount of punishment certain offenders receive. This has significant consequences if the policy of probation moves towards modes of practice which no longer prioritise standardisation and punishment over professional judgment and the importance of the offender-officer relationship and the article concludes by looking to some examples of more inclusive forms of office design and architecture