The interaction of temperature and sucrose concentration on foraging preferences in bumblebees

Several authors have found that flowers that are warmer than their surrounding environment have an advantage in attracting pollinators. Bumblebees will forage preferentially on warmer flowers, even if equal nutritional reward is available in cooler flowers. This raises the question of whether warmth and sucrose concentration are processed independently by bees, or whether sweetness detectors respond to higher sugar concentration as well as higher temperature. We find that bumblebees can use lower temperature as a cue to higher sucrose reward, showing that bees appear to process the two parameters strictly independently. Moreover, we demonstrate that sucrose concentration takes precedence over warmth, so that when there is a difference in sucrose concentration, bees will typically choose the sweeter feeder, even if the less sweet feeder is several degrees warmer.     

The contribution of advective fluxes to net ecosystem exchange in a high-elevation, subalpine forest

The eddy covariance technique, which is used in the determination of net ecosystem CO2 exchange (NEE), is subject to significant errors when advection that carries CO2 in the mean flow is ignored. We measured horizontal and vertical advective CO2 fluxes at the Niwot Ridge AmeriFlux site (Colorado, USA) using a measurement approach consisting of multiple towers. We observed relatively high rates of both horizontal (F(hadv)) and vertical (F(vadv)) advective fluxes at low surface friction velocities (u(*)) which were associated with downslope katabatic flows. We observed that F(hadv) was confined to a relatively thin layer (0-6 m thick) of subcanopy air that flowed beneath the eddy covariance sensors principally at night, carrying with it respired CO2 from the soil and lower parts of the canopy. The observed F(vadv) came from above the canopy and was presumably due to the convergence of drainage flows at the tower site. The magnitudes of both F(hadv) and F(vadv) were similar, of opposite sign, and increased with decreasing u(*), meaning that they most affected estimates of the total CO2 flux on calm nights with low wind speeds. The mathematical sign, temporal variation and dependence on u(*) of both F(hadv) and F(vadv) were determined by the unique terrain of the Niwot Ridge site. Therefore, the patterns we observed may not be broadly applicable to other sites. We evaluated the influence of advection on the cumulative annual and monthly estimates of the total CO2 flux (F(c)), which is often used as an estimate of NEE, over six years using the dependence of F(hadv) and F(vadv) on u(*). When the sum of F(hadv) and F(vadv) was used to correct monthly F(c), we observed values that were different from the monthly F(c) calculated using the traditional u(*)-filter correction by--16 to 20 g C x m(-2) x mo(-1); the mean percentage difference in monthly Fc for these two methods over the six-year period was 10%. When the sum of F(hadv) and F(vadv) was used to correct annual Fc, we observed a 65% difference compared to the traditional u(*)-filter approach. Thus, the errors to the local CO2 budget, when F(hadv) and F(vadv) are ignored, can become large when compounded in cumulative fashion over long time intervals. We conclude that the "micrometeorological" (using observations of F(hadv) and F(vadv)) and "biological" (using the u(*) filter and temperature vs. F(c) relationship) corrections differ on the basis of fundamental mechanistic grounds. The micrometeorological correction is based on aerodynamic mechanisms and shows no correlation to drivers of biological activity. Conversely, the biological correction is based on climatic responses of organisms and has no physical connection to aerodynamic processes. In those cases where they impose corrections of similar magnitude on the cumulative F(c) sum, the result is due to a serendipitous similarity in scale but has no clear mechanistic explanation.     

Shifting drivers and static baselines in environmental governance: challenges for improving and proving water quality outcomes

Understanding the conditions that enable or constrain success in environmental governance is crucial for developing effective interventions and adapting approaches. Efforts to achieve and assess success in environmental quality improvement are often impeded by changes in conditions that drive outcomes but lie outside the scope of intervention and monitoring. We document how long-term changes in land use, agriculture, and climate act as non-stationary, shifting drivers of change that combine to render water quality management interventions less effective and increasingly difficult to assess. Focusing on the Yahara River watershed of south-central Wisconsin, USA, we ask how baselines influence program modeling, monitoring, and evaluation, as well as adaptation in governance approach. Through historical trend, GIS, and policy and qualitative data analyses, we find that changes in long-term land use and precipitation pattern dynamics exert tremendous pressure on water quality outcomes but are not captured in snapshot baseline assessments used in management planning or evaluation. Specifically, agricultural sector change related to the intensification of milk and manure production is increasingly challenging to address through best management practices, and flashier precipitation associated with climate change makes it difficult to achieve goals and establish a causal connection between management interventions and outcomes. Analysis of shifting drivers demonstrates challenges facing environmental governance in the context of climatic and social–ecological change. We suggest that goal setting, program design, and evaluation incorporate new modes of analysis that address slowly changing and external determinants of success.     

Testing the scoping phase of a bottom-up planning guide designed to support Australian Indigenous rangers manage the impacts of climate change on cultural heritage sites

Since the early 1990s archaeologists have suggested archaeological and cultural heritage sites (cultural sites) will face major challenges from anthropogenic climate change. While techniques to manage such impacts are emerging, no planning tools exist for bottom-up, community-based management of the issue. This paper forms part of an overarching research project that aims to fill this gap by developing a bottom-up planning guide (the Guide). The paper tests the first of the proposed Guide’s five phases: the scoping phase. It presents the results of workshops conducted with two Australian Indigenous rangers groups. While existing studies document Indigenous peoples’ perceptions of climate change in general, none have focussed on their perceptions of impacts on cultural heritage sites. Here, Indigenous rangers related strong perceptions of particular climate change impacts on specific cultural sites in particular bio-regions. While the rangers were actively engaged with sites, they felt site management should be extended in the face of additional threats from climate change. Rangers were able to nominate a preferred methodological approach, based on a risk analysis of biophysical hazards, as well as local adaptive capacity building in the face of governance challenges. Various barriers to adaptation planning and resource limitations were identified but these were not regarded as insurmountable in terms of the current project. Testing of the scoping phase of the Guide suggested rangers had a strong organisational capacity to achieve practical adaptation results.     

Development of a low-cost air sensor package and indoor air quality monitoring in a California middle school: Detection of a distant wildfire

A low-cost air sensor package was used to monitor indoor air quality (IAQ) in a classroom at the Albany Middle School in the San Francisco Bay Area of California. A rapid increase in carbon dioxide (CO₂) was observed in the classroom as soon as it is occupied. When the classroom is unoccupied, the CO₂ levels decay slowly toward the outdoor background level. All high CO₂ concentrations observed inside the classroom, above the outdoor background, was due to exhaling of the occupants. The CO₂ concentrations generally exceed the recommended level of 1000 ppb towards the end of the school day. The exceedances and slow decay may suggest that the ventilation rate in this school is not sufficient. The particulate level in the classroom was low until a distant wildfire advected large amount of particulate matter to the San Francisco Bay Area. Very high (10–15 times compared to the background) particle numbers (per m³ of particles with diameter >0.3 µm) were observed in the classroom during the wildfire. These particles were relatively small (0.3–1.0 µm) and the filters (MERV 8) of the ventilation system were unable to filter them out. Therefore, the measurements made by low-cost particle counters can inform the school administrators of adverse IAQ during future wildfire (or other combustion) events. The particle number was independent of the occupation before and during the wildfire suggesting that all observed particles were infiltrated into the classroom from outside. Consistent with previous studies, no appreciable increase in the local ambient CO₂ background was observed during this distant wildfire event.

Implications: Low-cost air sensors are effective in monitoring indoor air quality in classrooms. The CO₂ levels in classrooms are mainly generated indoors due to exhalation of occupants. Concentration of CO₂ generally exceed the recommended level of 1000 ppb towards the end of the school day. In contrast, the particulate matter mostly comes from outdoors and small particles penetrate though the filters normally used at schools. Distant wildfires do not increase the local CO₂ background appreciably, but significantly increase the particulate matter concentrations both indoors and outdoors. Further investigations are needed to assure that ventilation rates in classrooms are sufficiently health protective.     

Temporal trends in polychlorinated dibenzo-p-dioxins and dibenzofurans, dioxin-like PCBs, and polybrominated diphenyl ethers in Niagara river suspended sediments

Archived suspended sediment samples collected over the period 1980-2002 at Niagara-on-the-Lake in the Niagara river were analyzed to assess temporal trends in contaminants associated with historical industrial activities in the watershed (PCDDs/PCDFs, DLPCBs), compared to more modern industrial chemicals (PBDEs). The temporal trends for PCDDs/PCDFs and DLPCBs were generally similar, and showed a general trend toward decreasing concentrations, which was presumably due to implementation of control measures in the Niagara river watershed, including the remediation of hazardous waste facilities. The temporal trend in PBDEs contrasted with those of PCDDs/PCDFs and DLPCBs. Prior to 1988, PBDEs (sum of 16 congeners including deca-BDE) were generally detected at low-ppb concentrations, but showed a trend toward increasing concentrations over the period 1980-1988. After 1988, PBDE concentrations in the Niagara river showed a more rapidly increasing trend to a maximum of approximately 35 ng/g in 1995, with deca-BDE as the predominant congener detected. Samples collected over the period February 2003 to March 2004 at the head and mouth of the Niagara river were also analyzed for PBDEs; in all cases PBDE concentrations were higher at the mouth of the river at the outflow to Lake Ontario, indicating the Niagara river watershed is a source of PBDE contamination to Lake Ontario. However, PBDE concentrations in suspended sediments of the Niagara river were comparable to, or lower than, concentrations in bottom sediments in other industrialized/urbanized areas of the world. Based on these comparisons of global PBDE bottom sediment concentrations, the Niagara river watershed does not appear to be a significant local source of PBDEs to Lake Ontario, and concentrations in suspended sediments appear to be indicative of general PBDE contamination from a contamination of local, regional, and continental sources.     

Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization

Speciated particulate matter (PM)2.5 data collected as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) program in Phoenix, AZ, from April 2001 through October 2003 were analyzed using the multivariate receptor model, positive matrix factorization (PMF). Over 250 samples and 24 species were used, including the organic carbon and elemental carbon analytical temperature fractions from the thermal optical reflectance method. A two-step approach was used. First, the species excluding the carbon fractions were used, and initially eight factors were identified; non-soil potassium was calculated and included to better refine the burning factor. Next, the mass associated with the burning factor was removed, and the data set rerun with the carbon fractions. Results were very similar (i.e., within a few percent), but this step enabled a separation of the mobile factor into gasoline and diesel vehicle emissions. The identified factors were burning (on average 2% of the mass), secondary transport (7%), regional power generation (13%), dust (25%), nitrate (9%), industrial As/Pb/Se (2%), Cu/Ni/V (7%), diesel (9%), and general mobile (26%). The overall contribution from mobile sources also increased, as some mass (OC and nitrate) from the nitrate and regional power generation factors were apportioned with the mobile factors. This approach allowed better apportionment of carbon as well as total mass. Additionally, the use of multiple supporting analyses, including air mass trajectories, activity trends, and emission inventory information, helped increase confidence in factor identification.     

The impact of technology characteristics and job control on worker mental health

Recent research suggests that the occurrence of operational problems in advanced manufacturing technology (AMT) places stressful demands on operators. Applying Karasek's demand–control model, we predict that two properties of operational problems, namely technological uncertainty and abstractness, interact with timing and method control to predict operator strain. The results failed to confirm ordinal effects for timing or method control, but showed a dis-ordinal (crossover) interaction for timing control. While these findings provide little support for the demand–control model, they suggest that two new processes, namely ‘traction–distraction’ and ‘passivity–challenge’, are critical to understanding the nature of the relationship between operational problems and operator strain in AMT systems. We describe these processes and examine the implications for future research. © 1997 John Wiley & Sons, Ltd.     

Use of activated Chromolaena odorata biomass for the removal of crystal violet from aqueous solution: kinetic,equilibrium, and thermodynamic study

Environmental Science and Pollution Research - In the present study, biomass from the Chromolaena odorata plant’s stem was activated using sulfuric acid to adsorb crystal violet (CV) dye. The...     

SNOTEL,the Soil Climate Analysis Network,and water supply forecasting at the Natural Resources Conservation Service: Past,present, and future

The Snow Survey and Water Supply Forecasting (SSWSF) Program and the Soil Climate Analysis Network (SCAN) of the United States Department of Agriculture's Natural Resources Conservation Service (NRCS) generate key observational and predictive information for water managers. Examples include mountain climate and snow monitoring through manual snow surveys and the SNOw TELemetry (SNOTEL) and SNOtel LITE networks, in situ soil moisture data acquisition through the SCAN and SNOTEL networks, and water supply forecasting using river runoff prediction models. The SSWSF Program has advanced continuously over the decades and is a major source of valuable water management information across the western United States, and the SCAN network supports agricultural and other water users nationwide. Product users and their management goals are diverse, and use-cases range from guiding crop selection to seasonal flood risk assessment, drought monitoring and prediction, avalanche and fire prediction, hydropower optimization, tracking climate variability and change, environmental management, satisfying international treaty and domestic legal requirements, and more. Priorities going forward are to continue innovating to enhance the accuracy and completeness of the observational and model-generated data products these programs deliver, including expanded synergies with the remote sensing community and uptake of artificial intelligence while maintaining long-term operational reliability and consistency at scale.