A Demographic Model to Evaluate Population Declines in the Endangered Streaked Horned Lark

The Streaked Horned Lark (Eremophila alpestris strigata) is listed as endangered by the State of Washington, USA and by Canada under the Species at Risk Act and is also classified as a federal candidate for listing under the Endangered Species Act in the USA. A substantial portion of Streaked Horned Lark habitat has been lost or degraded, and range contraction has occurred in Oregon, Washington, and British Columbia. We estimate the vital rates (fecundity, adult and juvenile survival) and population growth rate (λ) for Streaked Horned Larks breeding in Washington, USA and conduct a Life-Stage Simulation Analysis (LSA) to evaluate which vital rate has the greatest influence on λ. We simulated changes in the three vital rates to examine how much they would need to be adjusted either independently or in concert to achieve a stable Streaked Horned Lark population (λ = 1). We also evaluated which fecundity component (the number of fledglings per egg laid or renesting interval) had the greatest impact on λ. The estimate of population growth suggests that Streaked Horned Larks in Washington are declining rapidly (λ = 0.62 ± 0.10) and that local breeding sites are not sustainable without immigration. The LSA results indicate that adult survival had the greatest influence on λ, followed by juvenile survival and fecundity. However, increases in vital rates led to λ = 1 only when adult survival was raised from 0.47 to 0.85, juvenile survival from 0.17 to 0.58, and fecundity from 0.91 to 3.09. Increases in breeding success and decreases in the renesting interval influenced λ similarly; however, λ did not reach 1 even when breeding success was raised to 100% or renesting intervals were reduced to 1 day. Only when all three vital rates were increased simultaneously did λ approach 1 without requiring highly unrealistic increases in each vital rate. We conclude that conservation activities need to target all or multiple vital rates to be successful. The baseline data presented here and subsequent efforts to manage Streaked Horned Larks will provide valuable information for management of other declining Horned Lark subspecies and other grassland songbirds across North America.

The spacing of orographic rainbands triggered by small-scale topography

A combination of idealized numerical simulations and analytical theory is used to investigate the spacing between convective orographic rainbands over the Coastal Range of western Oregon. The simulations, which are idealized from an observed banded precipitation event over the Coastal Range, indicate that the atmospheric response to conditionally unstable flow over the mountain ridge depends strongly on the subridge-scale topographic forcing on the windward side of the ridge. When this small-scale terrain contains only a single scale (l) of terrain variability, the band spacing is identical to l, but when a spectrum of terrain scales are simultaneously present, the band spacing ranges between 5 and 10 km, a value that is consistent with observations. Based on the simulations, an inviscid linear model is developed to provide a physical basis for understanding the scale selection of the rainbands. This analytical model, which captures the transition from lee waves upstream of the orographic cloud to moist convection within it, reveals that the spacing of orographic rainbands depends on both the projection of lee-wave energy onto the unstable cap cloud and the growth rate of unstable perturbations within the cloud. The linear model is used in tandem with numerical simulations to determine the sensitivity of the band spacing to a number of environmental and terrain-related parameters.

The triggering of orographic rainbands by small-scale topography

The triggering of convective orographic rainbands by small-scale topographic features is investigated through observations of a banded precipitation event over the Oregon Coastal Range and simulations using a cloud-resolving numerical model. A quasi-idealized simulation of the observed event reproduces the bands in the radar observations, indicating the model’s ability to capture the physics of the band-formation process. Additional idealized simulations reinforce that the bands are triggered by lee waves past small-scale topographic obstacles just upstream of the nominal leading edge of the orographic cloud. Whether a topographic obstacle in this region is able to trigger a strong rainband depends on the phase of its lee wave at cloud entry. Convective growth only occurs downstream of obstacles that give rise to lee-wave-induced displacements that create positive vertical velocity anomalies w_c and nearly zero buoyancy anomalies b_c as air parcels undergo saturation. This relationship is quantified through a simple analytic condition involving w_c, b_c, and the static stability N_m^2 of the cloud mass. Once convection is triggered, horizontal buoyancy gradients in the cross-flow direction generate circulations that align the bands parallel to the flow direction.

Discriminative pattern mining in software fault detection

We present a method to enhance fault localization for software systems based on a frequent pattern mining algorithm. Our method is based on a large set of test cases for a given set of programs in which faults can be detected. The test executions are recorded as function call trees. Based on test oracles the tests can be classified into successful and failing tests. A frequent pattern mining algorithm is used to identify frequent subtrees in successful and failing test executions. This information is used to rank functions according to their likelihood of containing a fault. The ranking suggests an order in which to examine the functions during fault analysis. We validate our approach experimentally using a subset of Siemens benchmark programs.

Observations and modeling of banded orographic convection

Radar images and numerical simulations of three shallow convective precipitation events over the Coastal Range in western Oregon are presented. In one of these events, unusually well-defined quasi-stationary banded formations produced large precipitation enhancements in favored locations, while varying degrees of band organization and lighter precipitation accumulations occurred in the other two cases. The difference between the more banded and cellular cases appeared to depend on the vertical shear within the orographic cap cloud and the susceptibility of the flow to convection upstream of the mountain. Numerical simulations showed that the rainbands, which appeared to be shear-parallel convective roll circulations that formed within the unstable orographic cap cloud, developed even over smooth mountains. However, these banded structures were better organized, more stationary, and produced greater precipitation enhancement over mountains with small-scale topographic obstacles. Low-amplitude random topographic roughness elements were found to be just as effective as more prominent subrange-scale peaks at organizing and fixing the location of the orographic rainbands.

Application of semiquantitative proteomics techniques to the Maillard reaction

Proteomic tools-in particular, mass spectrometry (MS)-have advanced significantly in recent years, and the identification of proteins within complex mixtures is now a routine procedure. Quantitative methods of analysis are less well advanced and continue to develop. These include the use of stable isotope ratio approaches, isotopically labeled peptide standards, and nonlabeling methods. This paper summarizes the use of MS as a proteomics tool to identify and semiquantify proteins and their modified forms by using examples of relevance to the Maillard reaction. Finally, some challenges for the future are presented.