Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US

The lack of seasonally sustained floral resources (i.e. pollen and nectar) is considered a primary global threat to pollinator health. However, the ability to predict the abundance of flowering resources for pollinators based upon climate, weather, and land cover is difficult due to insufficient monitoring over adequate spatial and temporal scales. Here we use spatiotemporally distributed honey bee hive scales that continuously measure hive weights as a standardized method to assess nectar intake. We analyze late summer colony weight gain as the response variable in a random forest regression model to determine the importance of climate, weather, and land cover on honey bee colony productivity. Our random forest model predicted resource acquisition by honey bee colonies with 71% accuracy, highlighting the detrimental effects of warm, wet regions in the Northcentral United States on nectar intake, as well as the detrimental effect of years with high growing degree day accumulation. Our model also predicted that grassy–herbaceous natural land had a positive effect on the summer nectar flow and that large areas of natural grassy–herbaceous land around apiaries can moderate the detrimental effects of warm, wet climates. These patterns characterize multi-scale ecological processes that constrain the quantity and quality of pollinator nutritional resources. That is, broad climate conditions constrain regional floral communities, while land use and weather act to further modify the quantity and quality of pollinator nutritional resources. Observing such broad-scale trends demonstrates the potential for utilizing hive scales to monitor the effects of climate change on landscape-level floral resources for pollinators. The interaction of climate and land use also present an opportunity to manage for climate-resilient landscapes that support pollinators through abundant floral resources under climate change

Design and Performance of the XENON10 Dark Matter Experiment

XENON10 is the first two-phase xenon time projection chamber (TPC) developed within the XENON dark matter search program. The TPC, with an active liquid xenon (LXe) mass of about 14 kg, was installed at the Gran Sasso underground laboratory (LNGS) in Italy, and operated for more than one year, with excellent stability and performance. Results from a dark matter search with XENON10 have been published elsewhere. In this paper, we summarize the design and performance of the detector and its subsystems, based on calibration data using sources of gamma-rays and neutrons as well as background and Monte Carlo simulations data. The results on the detector's energy threshold, energy and position resolution, and overall efficiency show a performance that exceeds design specifications, in view of the very low energy threshold achieved (<10 keVr) and the excellent energy resolution achieved by combining the ionization and scintillation signals, detected simultaneously

Drama, performance and touch in the medieval convent and beyond

In this analysis we explore the sensory performances of the performer, rather than the spectator, in medieval convent drama, particularly the tactile experiences of clothing, props, wigs, and beards worn by female performers presenting male and female characters

Calculations Predict That Carbon Tunneling Allows the Degenerate Cope Rearrangement of Semibullvalene to Occur Rapidly at Cryogenic Temperatures

Article on calculations predicting that carbon tunneling allows the degenerate cope rearrangement of semibullvalene to occur rapidly at cryogenic temperatures

Honey bee success predicted by landscape composition in

Foraging honey bees (Apis mellifera L.) routinely travel as far as several kilometers from their hive in the process of collecting nectar and pollen from floral patches within the surrounding landscape. Since the availability of floral resources at the landscape scale is a function of landscape composition, apiculturists have long recognized that landscape composition is a critical determinant of honey bee colony success. Nevertheless, we are aware of no published studies that present quantitative data relating colony success metrics to local landscape composition. We employed a beekeeper survey in conjunction with GIS-based landscape analysis to model colony success as a function of landscape composition in the State of Ohio, USA, a region characterized by intensive cropland, urban development, deciduous forest, and grassland. We found that colony food accumulation and wax production were positively related to cropland and negatively related to forest and grassland, a pattern that may be driven by the abundance of dandelion and clovers in agricultural areas compared to forest or mature grassland. Colony food accumulation was also negatively correlated with the ratio of urban:crop area in sites dominated by urban and agricultural land cover, which does not support the popular opinion that the urban environment is more favorable to honey bees than cropland. PrePrints Honey bees (Apis mellifera, L.) exist in large, eusocial colonies that require massive and sustained inputs of floral nectar and pollen. They meet this demand by foraging at an extremely large spatial scale and with rapid responsiveness to changes in the surrounding floral community (Visscher &amp; Seeley, 1982; Seeley, 1995). Depending on local floral availability, colonies may routinely forage over an area of more than 100 km2 (Seeley, 1995), and much larger ranges have been reported under extreme conditions (Eckert, 1931; Because honey bee foraging is a decidedly landscape-scale process, one should expect landscape composition to interact meaningfully with colony nutrition and overall colony success. While the plausibility of such a relationship is widely acknowledged (Steffan-Dewenter &amp; Kuhn, 2003; Several studies have indirectly explored the relationship between landscape and colony success by analyzing the spatial information encoded in the honey bee dance language (von Frisch, 1967). Waddington et al. (1994) found that colonies located in two suburban landscapes tended to forage over a smaller area and with a less clumped distribution than a previously studied colony located in a temperate deciduous forest (Visscher and Seeley, 1982), suggesting that suburban landscapes provide richer and more evenly distributed resource patches. Conversely, Beekman and Ratnieks (2001) observed remarkably long-distance foraging under conditions of apparently scarce local resources in a suburban landscape and highly rewarding resources in outlying seminatural heather moors. In agricultural landscapes, honey bee foraging patterns suggest that pollen sources can be scarcer and floral patches less spatially and temporally PrePrints variable in highly simplified cropping systems compared to more structurally complex habitats (Steffan-Dewenter &amp; Kuhn, 2003), while conservation management within farmlands can increase the availability of bee-attractive flora Among non-peer-reviewed sources, there is a widely circulated opinion that honey bee success is favored by urban/suburban landscapes, especially in comparison to cropland (Graham, 1992; New York Times, 2008; Wilson-Rich, 2012). These claims remain unsubstantiated but plausible given the ostensibly positive effects of suburban land use suggested by Waddington et al. (1994) and the more direct evidence supporting the favorability of suburban land use for bumble bees (Hymenoptera: Bombus, Latreille) living in predominantly agricultural areas (Goulson et al., 2002; 2010). Here, we present a quantitative study of honey bee colony success in relation to landscape composition in the State of Ohio, USA, a region characterized by a mixture of intensive cropland, deciduous forest, grassland, and urban development. Using a citizen-science survey, we investigate the relationship between colony success and the landscape as a whole, accounting for all major land cover types and also for the potential influence of hive management variables that vary between beekeepers. Then, we specifically evaluate the putative favorability of urban landscapes relative to agricultural ones using a subset of sites dominated by crop and/or urban development. Materials and Methods Survey Design. In 2012 and 2013, we used a survey-based, citizen-science approach to measure the productivity of honey bee colonies in the state of Ohio, USA. All participants were beekeepers whose hives were registered with the Ohio Department of Agriculture and who volunteered to participate in our study. Our survey was conducted with written exemption from In order to standardize the initial strength of the colonies in our study (hereafter &quot;study colonies&quot;) and minimize the influence of parasites and pathogens, we restricted our study to colonies that had been started from artificial swarms, known as &quot;package bees&quot;, in the spring of each study year. Honey bee packages are created by combining a standard quantity of worker bees (usually 1.36 kg) with a newly mated queen. The initial strength of colonies started from package bees is, therefore, less variable than that of over-wintered colonies. Moreover, because they are sold without comb or brood, they tend to have reduced parasite and pathogen loads. Data for each study colony were gathered using a two-part survey consisting of spring and fall components (hereafter &quot;spring survey&quot; and &quot;fall survey&quot;). The spring survey was made available beginning in early March, and participants were instructed to complete the survey immediately after installing their honey bee packages. In the spring survey, we gathered the geographic location of each study colony and the years of experience of each participating beekeeper (see S1 for full spring survey questionnaire). The fall survey was made available in mid-September and completed by mid-October. To complete the fall survey, each participant performed a frame-by-frame hive inspection and reported the number of frames in the study hive belonging to the following categories: (1) more than half honey/nectar, (2) more than half pollen, (3) more than half brood, (4) more than half empty wax comb, (5) more than half bare foundation (no wax comb). Participants also reported the quantity of sugar syrup that had been given to their hives as supplemental feeding, a common beekeeping practice that could be affect colony success. See S2 for full fall survey questionnaire. Survey Processing. Each beekeeper was instructed to submit data for only one study hive at one apiary site. The data quality of all surveys was carefully vetted prior to analysis, and surveys missing critical data or having irreconcilable inconsistencies were discarded. Fall surveys PrePrints reporting hives that had died since spring installation were also discarded. The final numbers of surveys included in analyses for 2012 and 2013 were 32 and 18, respectively; these were selected from a pre-processing total of 55 surveys in 2012 and 33 in 2013. From our survey data, we derived four metrics to represent colony success: net food accumulation, net wax production, adult population, and brood population. For consistency, all metrics were recorded in units of standard deep frames. Net food accumulation: where H = honey/nectar frames in hive at time of inspection, Hharv = honey frames harvested prior to inspection, Hadd = honey frames added to the hive prior to inspection, and P = frames of pollen in hive at time of inspection. This variable will hereafter be abbreviated Food. Net wax production: where B = brood frames in hive at time of inspection, Brm = brood frames removed prior to inspection, D = drawn but mostly empty frames in hive at time of inspection, Badd = brood frames added to the hive prior to inspection, and Dadd = drawn but mostly empty frames added to hive prior to inspection. This variable will hereafter be abbreviated Wax. Adult population (hereafter, AdultPop) was measured as the number of frames &quot;more than half covered&quot; with adult bees at time of inspection. Brood population (hereafter, BroodPop) was simply the number of &quot;mostly brood&quot; frames reported by the inspecting beekeeper. We also measured two hive management variables: years of beekeeping experience of the participating beekeeper (years) and quantity of sugar syrup fed to the study hive since its installation (syrup). Data Analysis. We first reduced the dimensionality of our landscape data using principal components analysis (PCA) based on the covariance between the variables Crop, Forest, Grassland, and Urban. This step was repeated for each spatial scale. For all scales, the first two principal components (PC 1 and PC 2) explained &gt; 96% of total variance. To evaluate the prediction that urban land cover favors honey bee success relative to agricultural land cover, we first extracted the subset of our sites for which Urban + Crop was greater than 50% of total landcover; then, we calculated the ratio of Urban : Crop for each of these sites, thus representing the relative dominance of Urban vs. Crop in sites dominated by some combination of the two. To avoid infinite or undefined results for sites having a value of zero for either Urban or Crop, a constant of 0.001 (i.e. 0.1% land cover) was added to each value. We then set up separate linear regression models for Food and Wax with the log-transformed ratio of Urban : Crop as the explanatory variable Only Food and Wax were analyzed because the results of the PCA described above indicated that only these two success metrics should be expected to respond to landscape variables. We did not use years and syrup as covariates because previous analysis showed they were not predictive of Food or Wax. Regression analysis was repeated for each spatial scale. PrePrints All analysis was performed in R statistical software (R Core Team, 2014). AICc model selection used the package AICcmodavg (Mazerolle, 2014). Results Landscape analysis. The landscapes surrounding the colonies in our survey represented a broad range of landscape composition in terms of the major land cover classes Crop, Forest, Grassland, and Urban Modeling colony success metrics by landscape principal components. Food and Wax were best modeled with PC 2 as the only explanatory variable. Almost all competing models (∆AICc &lt; 2) included PC 2 alongside other explanatory variables, further supporting the conclusion that PC 2 was the single most important predictor PrePrints Modeling colony success metrics by Urban : Crop ratio. We found a significant (p &lt; 0.05) negative relationship between Food and the log-transformed Urban : Crop ratio Discussion The negative responses of Food and Wax to PC 2 indicate that food accumulation and wax production increase with surrounding cropland and decrease with forest/grassland. This finding seems to contradict the conventional wisdom that agricultural land conversion threatens honey bee nutrition through the depauperation of floral resources relative to semi-natural environments PrePrints Interestingly, our finding that colony productivity is favored by cropland relative to forest/grassland is strikingly consistent with an anecdotal description of regional honey production in Ohio published nearly forty years ago (Goltz, 1975). In Goltz&apos; account, the areas of &quot;primary&quot; and &quot;secondary&quot; importance for honey production are in the heavily cultivated glacial plains that comprise most of the state, while the forest-dominated Appalachian Plateaus in the southeast are described as only &quot;marginally&quot; productive. The positive response of AdultPop to the management variables years and syrup is difficult to interpret. In early spring, when new colonies are very small and limited in their foraging ability, it is standard practice to supplement colony nutrition with sugar syrup. All workers produced during the period of spring build-up, though, died long before colonies were inspected in the fall, so any positive effect of the springtime management on AdultPop at time of inspection would have to be mediated by factors that allow colonies to increase reproduction later in the year. An alternative interpretation is plausible if we allow that significant feeding may have occurred later in the year. While supplemental feeding is normally concentrated in early spring, some Ohio beekeepers also feed their colonies in mid-late summer, a period of perceived dearth in natural forage. Feeding during the summer dearth period might trigger a population increase that would persist until fall inspection. Our survey did not distinguish between feeding at different times during the season. By late September and early October, when beekeepers were inspecting their colonies for the fall survey, the bees had likely already begun to reduce brood rearing in preparation for winter (Graham, 1992). This would explain the failure of both landscape and management variables in predicting BroodPop. The negative relationship observed between Food and the ratio of Urban : Crop does not support the popular opinion that urban landscapes favor honey bee success relative to agricultural landscapes. At least in Ohio, the relationship appears to be the opposite, and the fact that Food PrePrints was the only success metric to respond to Urban : Crop ratio suggests a likely mechanism. The last major nectar and pollen flow in Ohio is usually from goldenrod (Solidago spp. L.) (Morse, 1972; D. B. Sponsler, unpublished data), which blooms prolifically from late summer into fall, roughly the same period during which beekeepers in our study were conducting fall hive inspections and filling out the fall survey. At this time of year, honey bees rarely produce additional wax (Lee &amp; Winston, 1985), and brood rearing has begun to slow down in preparation for winter (Graham, 1992), so incoming food is stored rather than being invested in brood or wax production. Goldenrod occurs abundantly in uncultivated fields and conservation strips throughout agricultural landscapes, but it is relatively scarce in developed areas where vegetation is more often subject to mowing and weed control. This is consistent with the anecdotal observation of We conclude that both landscape composition and colony management contribute to the success of nascent honey bee colonies in our study region. Due to complexities not explored in this study, the prediction of colony success was partitioned such that landscape predicted food accumulation and wax production, while colony management predicted only adult worker population. We find no support for the opinion that honey bees in urban landscapes are more successful than those in cropland. To the contrary, we find that colony food accumulation responds positively to cropland relative to urban land, a pattern that we attribute to the influence of late-season floral availability, particularly goldenrod