Does song reflect age and viability? A comparison between two populations of the great reed warbler Acrocephalus arundinaceus

Song complexity is often regarded as a sexually selected trait that reflects the overall quality of a male. In many passerine species, old males possess larger song repertoires than younger males. This may be either because individual males improve their performance as they get older (longitudinal increase) or because poor singers have reduced viability and, hence, are underrepresented in old age classes (cross-sectional increase). We studied the age dependence of repertoire size and other song traits in a German and a Swedish great reed warbler (Acrocephalus arundinaceus) population. We found marked differences between longitudinal and cross-sectional approaches, as well as between the two study populations. In the German population, we found that syllable switching, a measure of immediate versatility and strophe length, increased with age in a cross-sectional analysis. This was not because birds improved with age (longitudinally) but because syllable switching was positively correlated with male longevity. However, in Sweden, syllable switching seemed to be unrelated to age and longevity. In the Swedish population, individual males increased their repertoire size as they got older (longitudinal increase), but this did not happen in the German population. Hence, two populations, even when belonging to the same subspecies, may differ in whether or not they show delayed song maturation.     

Optimum forage allocation through chance-constrained programming

Most resource allocation models developed to aid resource planning have been deterministic; that is, the ecosystem and economic variables are assumed to be known with certainty. It is these elements that present problems concerning risk and uncertainty involved in decision making. The objective of this study is to present a mathematical approach for optimizing resource allocation in management situations in which random events occur. This particular technique of decision analysis is chance-constrained programming. The model makes possible the investigation of risk and uncertainty associated with resource management decision making. Range decision-makers must often stock their range before they are sure of the available forage; thus, the amount of available forage is a random element with which managers must contend. The chance-constrained approach to decision making may be used when such random events occur and when it is not possible to plan exactly for future events. Two parameters are used to adjust the mean value of constraints; these are the standard deviation of the constraint value (S_bi) and the probability term which is specified by the manager (K_αi). The mean values are adjusted by the product K_αiS_bi. In the study reported here, a K_αi value of 0.57 gave results which appeared to have usefulness. The results indicate that the penalties a rancher must assume for over-estimating his carrying capacity are greater than the penalties for underestimating the carrying capacity. With the value of the standard deviation used in the example, numbers of livestock and the corresponding net revenues should be about 22% less than those indicated by average forage production. With greater variation in forage production, the reduction would be greater. By using these values, the chance-constrained approach can meaningfully incorporate random variables into a decision model.     

Estimating percentiles from composite environmental samples when all observations are nondetectable

Many environmental sampling problems involve some specified regulatory or contractual limit (RL). Often the interest is in estimating the percentile of the underlying contaminant concentration distribution corresponding to RL. The focus of this paper is on obtaining a point estimate and a lower confidence limit for that percentile when all observations are nondetectable, with the ith observation known to be less than some detection limit DLI, where DLi RL. Since composite samples are being considered, it is not unreasonable to assume an underlying normal distribution.     

Application of a coupled ecosystem-chemical equilibrium model, DayCent-Chem, to stream and soil chemistry in a Rocky Mountain watershed

Atmospheric deposition of sulfur and nitrogen species have the potential to acidify terrestrial and aquatic ecosystems, but nitrate and ammonium are also critical nutrients for plant and microbial productivity. Both the ecological response and the hydrochemical response to atmospheric deposition are of interest to regulatory and land management agencies. We developed a non-spatial biogeochemical model to simulate soil and surface water chemistry by linking the daily version of the CENTURY ecosystem model (DayCent) with a low temperature aqueous geochemical model, PHREEQC. The coupled model, DayCent-Chem, simulates the daily dynamics of plant production, soil organic matter, cation exchange, mineral weathering, elution, stream discharge, and solute concentrations in soil water and stream flow. By aerially weighting the contributions of separate bedrock/talus and tundra simulations, the model was able to replicate the measured seasonal and annual stream chemistry for most solutes for Andrews Creek in Loch Vale watershed, Rocky Mountain National Park. Simulated soil chemistry, net primary production, live biomass, and soil organic matter for forest and tundra matched well with measurements. This model is appropriate for accurately describing ecosystem and surface water chemical response to atmospheric deposition and climate change.     

Achieving forest carbon information with higher certainty: A five-part plan

International negotiations on the inclusion of land use activities into an emissions reduction system for the UN Framework Convention on Climate Change (UNFCCC) have been partially hindered by the technical challenges of measuring, reporting, and verifying greenhouse gas (GHG) emissions and the policy issues of leakage, additionality, and permanence. This paper outlines a five-part plan for estimating forest carbon stocks and emissions with the accuracy and certainty needed to support a policy for Reducing Emissions from Deforestation and forest Degradation, forest conservation, sustainable management of forests, and enhancement of forest carbon stocks (the REDD-plus framework considered at the UNFCCC COP-15) in developing countries. The plan is aimed at UNFCCC non-Annex 1 developing countries, but the principles outlined are also applicable to developed (Annex 1) countries. The parts of the plan are: (1) Expand the number of national forest carbon Measuring, Reporting, and Verification (MRV) systems with a priority on tropical developing countries; (2) Implement continuous global forest carbon assessments through the network of national systems; (3) Achieve commitments from national space agencies for the necessary satellite data; (4) Establish agreed-on standards and independent verification processes to ensure robust reporting; and (5) Enhance coordination among international and multilateral organizations.     

EFFECTS OF CLIMATE CHANGE ON HYDROLOGY AND WATER RESOURCES IN THE COLUMBIA RIVER BASIN1

ABSTRACT: As part of the National Assessment of Climate Change, the implications of future climate predictions derived from four global climate models (GCMs) were used to evaluate possible future changes to Pacific Northwest climate, the surface water response of the Columbia River basin, and the ability of the Columbia River reservoir system to meet regional water resources objectives. Two representative GCM simulations from the Hadley Centre (HC) and Max Planck Institute (MPI) were selected from a group of GCM simulations made available via the National Assessment for climate change. From these simulations, quasi-stationary, decadal mean temperature and precipitation changes were used to perturb historical records of precipitation and temperature data to create inferred conditions for 2025, 2045, and 2095. These perturbed records, which represent future climate in the experiments, were used to drive a macro-scale hydrology model of the Columbia River at 1/8 degree resolution. The altered streamflows simulated for each scenario were, in turn, used to drive a reservoir model, from which the ability of the system to meet water resources objectives was determined relative to a simulated hydrologic base case (current climate). Although the two GCM simulations showed somewhat different seasonal patterns for temperature change, in general the simulations show reasonably consistent basin average increases in temperature of about 1.8–2.1°C for 2025, and about 2.3–2.9°C for 2045. The HC simulations predict an annual average temperature increase of about 4.5°C for 2095. Changes in basin averaged winter precipitation range from -1 percent to + 20 percent for the HC and MPI scenarios, and summer precipitation is also variously affected. These changes in climate result in significant increases in winter runoff volumes due to increased winter precipitation and warmer winter temperatures, with resulting reductions in snowpack. Average March 1 basin average snow water equivalents are 75 to 85 percent of the base case for 2025, and 55 to 65 percent of the base case by 2045. By 2045 the reduced snowpack and earlier snow melt, coupled with higher evapotranspiration in early summer, would lead to earlier spring peak flows and reduced runoff volumes from April-September ranging from about 75 percent to 90 percent of the base case. Annual runoff volumes range from 85 percent to 110 percent of the base case in the simulations for 2045. These changes in streamflow create increased competition for water during the spring, summer, and early fall between non-firm energy production, irrigation, instream flow, and recreation. Flood control effectiveness is moderately reduced for most of the scenarios examined, and desirable navigation conditions on the Snake are generally enhanced or unchanged. Current levels of winter-dominated firm energy production are only significantly impacted for the MPI 2045 simulations.     

Mineralogical variables that control the antibacterial effectiveness of a natural clay deposit

As antibiotic-resistant bacterial strains emerge and pose increased global health risks, new antibacterial agents are needed as alternatives to conventional antimicrobials. Naturally occurring antibacterial clays have been identified which are effective in killing antibiotic-resistant bacteria. This study examines a hydrothermally formed antibacterial clay deposit near Crater Lake, OR (USA). Our hypothesis is that antibacterial clays buffer pH and Eh conditions to dissolve unstable mineral phases containing transition metals (primarily Fe²⁺), while smectite interlayers serve as reservoirs for time release of bactericidal components. Model pathogens (Escherichia coli ATCC 25922 and Staphylococcus epidermidis ATCC 14990) were incubated with clays from different alteration zones of the hydrothermal deposit. In vitro antibacterial susceptibility testing showed that reduced mineral zones were bactericidal, while more oxidized zones had variable antibacterial effect. TEM images showed no indication of cell lysis. Cytoplasmic condensation and cell wall accumulations of <100 nm particles were seen within both bacterial populations. Electron energy loss analysis indicates precipitation of intracellular Fe³⁺-oxide nanoparticles (<10 nm) in E. coli after 24 h. Clay minerals and pyrite buffer aqueous solutions to pH 2.5–3.1, Eh > 630 mV and contain elevated level (mM) of soluble Fe (Fe²⁺ and Fe³⁺) and Al³⁺. Our interpretation is that rapid uptake of Fe²⁺ impairs bacterial metabolism by flooding the cell with excess Fe²⁺ and overwhelming iron storage proteins. As the intracellular Fe²⁺ oxidizes, it produces reactive oxygen species that damage biomolecules and precipitates Fe-oxides. The ability of antibacterial clays to buffer pH and Eh in chronic non-healing wounds to conditions of healthy skin appears key to their healing potential and viability as an alternative to conventional antibiotics.