Estimates of Avian Mortality Attributed to Vehicle Collisions in Canada

Although mortality of birds from collisions with vehicles is estimated to be in the millions in the USA, Europe, and the UK, to date, no estimates exist for Canada. To address this, we calculated an estimate of annual avian mortality attributed to vehicular collisions during the breeding and fledging season, in Canadian ecozones, by applying North American literature values for avian mortality to Canadian road networks. Because owls are particularly susceptible to collisions with vehicles, we also estimated the number of roadkilled Barn owls (Tyto alba) in its last remaining range within Canada. (This species is on the IUCN red list and is also listed federally as threatened; Committee on the Status of Endangered Wildlife in Canada 2010, International Union for the Conservation of Nature 2012). Through seven Canadian studies in existence, 80 species and 2,834 specimens have been found dead on roads representing species from 14 orders of birds. On Canadian 1 and 2-lane paved roads outside of major urban centers, the unadjusted number of bird mortalities/yr during an estimated 4-mo (122-d) breeding and fledging season for most birds in Canada was 4,650,137 on roads traversing through deciduous, coniferous, cropland, wetlands and nonagricultural landscapes with less than 10% treed area. On average, this represents 1,167 birds killed/100 km in Canada. Adjusted for scavenging, this estimate was 13,810,906 (3,462 dead birds/100 km). For barn owls, the unadjusted number of birds killed annually on 4-lane roads during the breeding and fledging season, within the species geographic range in southern British Columbia, was estimated as 244 owls and, when adjusted for scavenging and observer bias (3.6 factor), the total was 851 owls.

Avian mortalities due to transmission line collisions: a review of current estimates and field methods with an emphasis on applications to the Canadian electric network

Birds are vulnerable to collisions with human-made fixed structures. Despite ongoing development and increases in infrastructure, we have few estimates of the magnitude of collision mortality. We reviewed the existing literature on avian mortality associated with transmission lines and derived an initial estimate for Canada. Estimating mortality from collisions with power lines is challenging due to the lack of studies, especially from sites within Canada, and due to uncertainty about the magnitude of detection biases. Detection of bird collisions with transmission lines varies due to habitat type, species size, and scavenging rates. In addition, birds can be crippled by the impact and subsequently die, although crippling rates are poorly known and rarely incorporated into estimates. We used existing data to derive a range of estimates of avian mortality associated with collisions with transmission lines in Canada by incorporating detection, scavenging, and crippling biases. There are 231,966 km of transmission lines across Canada, mostly in the boreal forest. Mortality estimates ranged from 1 million to 229.5 million birds per year, depending on the bias corrections applied. We consider our most realistic estimate, taking into account variation in risk across Canada, to range from 2.5 million to 25.6 million birds killed per year. Data from multiple studies across Canada and the northern U.S. indicate that the most vulnerable bird groups are (1) waterfowl, (2) grebes, (3) shorebirds, and (4) cranes, which is consistent with other studies. Populations of several groups that are vulnerable to collisions are increasing across Canada (e.g., waterfowl, raptors), which suggests that collision mortality, at current levels, is not limiting population growth. However, there may be impacts on other declining species, such as shorebirds and some species at risk, including Alberta’s Trumpeter Swans (Cygnus buccinator) and western Canada’s endangered Whooping Cranes (Grus americana). Collisions may be more common during migration, which underscores the need to understand impacts across the annual cycle. We emphasize that these estimates are preliminary, especially considering the absence of Canadian studies.

Off-road sampling reveals a different grassland bird community than roadside sampling: implications for survey design and estimates to guide conservation

Grassland bird species continue to decline steeply across North America. Road-based surveys such as the North American Breeding Bird Survey (BBS) are often used to estimate trends and population sizes and to build species distribution models for grassland birds, although roadside survey counts may introduce bias in estimates because of differences in habitats along roadsides and in off-road surveys. We tested for differences in land cover composition and in the avian community on 21 roadside-based survey routes and in an equal number of adjacent off-road walking routes in the grasslands of southern Alberta, Canada. Off-road routes (n = 225 point counts) had more native grassland and short shrubs and less fallow land and road area than the roadside routes (n = 225 point counts). Consequently, 17 of the 39 bird species differed between the two route types in frequency of occurrence and relative abundance, measured using an indicator species analysis. Six species, including five obligate grassland species, were more prevalent at off-road sites; they included four species listed under the Canadian federal Species At Risk Act or listed by the Committee on the Status of Endangered Wildlife in Canada: Sprague’s Pipit (Anthus spragueii), Baird’s Sparrow (Ammodramus bairdii), the Chestnut-collared Longspur (Calcarius ornatus), and McCown’s Longspur (Rhynchophanes mccownii). The six species were as much as four times more abundant on off-road sites. Species more prevalent along roadside routes included common species and those typical of farmland and other human-modified habitats, e.g., the European Starling (Sturnus vulgaris), the Black-billed Magpie (Pica hudsonia), and the House Sparrow (Passer domesticus). Differences in avian community composition between roadside and off-road surveys suggest that the use of BBS data when generating population estimates or distribution models may overestimate certain common species and underestimate others of conservation concern. Our results highlight the need to develop appropriate corrections for bias in estimates derived from roadside sampling, and the need to design surveys that sample bird communities across a more representative cross-section of the landscape, both near and far from roads. 

Bird feeders and their effects on bird-window collisions at residential houses

Feeding wild birds creates an important link between homeowners and conservation. The effects of bird feeders and year-round feeding on birds have not been well studied, however, particularly in relationship to bird-window collisions. We determined effects of bird feeder presence and placement on bird-window collisions at residential homes. Paired month-long trials in which a feeder was either present or absent for one month and then removed or added for the second month were completed at 55 windows at 43 houses. In each trial, homeowners were asked to search their study window daily for evidence of a bird-window collision. During the study there were 51 collisions when there was no bird feeder and 94 when the feeder was present. The season when each trial was set up was the best individual predictor of bird-window collisions. The largest number of collisions was observed during fall migration and the lowest during the winter months. There were no collisions at 26 of the study windows. High variance was observed in the number of collisions at different houses, indicating that effects of bird feeders are context dependent. Changing the occurrence, timing, and placement of feeders can alter collision rates but is only one of many factors that influence whether a residential house is likely to have a bird window-collision or not.

An improved algorithm for generating global window brightness temperatures from multiple satellite infrared imagery

An improved algorithm for the generation of gridded window brightness temperatures is presented. The primary data source is the International Satellite Cloud Climatology Project, level B3 data, covering the period from July 1983 to the present. The algorithm rakes window brightness, temperatures from multiple satellites, both geostationary and polar orbiting, which have already been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latitude-longitude grid. The gridding uses a hierarchical scheme based on spherical kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to downweight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data are interpolated from adjacent processed images using a form of motion compensated interpolation based on the estimation of motion vectors using an hierarchical block matching scheme. Examples are shown of the various stages in the process. Also shown are examples of the usefulness of this type of data in GCM validation.

Evaluation of reanalysis rainfall estimates over Ethiopia

There is a pressing need for good rainfall data for the African continent both for humanitarian and climatological purposes. Given the sparseness of ground-based observations, one source of rainfall information is Numerical Weather Prediction (NWP) model outputs. The aim of this article is to investigate the quality of two NWP products using Ethiopia as a test case. The two products evaluated are the ERA-40 and NCEP reanalysis rainfall products. Spatial, seasonal and interannual variability of rainfall have been evaluated for Kiremt (JJAS) and Belg (FMAM) seasons at a spatial scale that reflects the local variability of the rainfall climate using a method which makes optimum use of sparse gauge validation data. We found that the spatial pattern of the rainfall climatology is captured well by both models especially for the main rainy season Kiremt. However, both models tend to overestimate the mean rainfall in the northwest, west and central regions but underestimate in the south and east. The overestimation is greater for NCEP in Belg season and greater for ERA-40 in Kiremt Season. ERA-40 captures the annual cycle over most of the country better than NCEP, but strongly exaggerates the Kiremt peak in the northwest and west. The overestimation in Kiremt appears to have been reduced since the assimilation of satellite data increased around 1990. For both models the interannual variability is less well captured than the spatial and seasonal variability. Copyright © 2008 Royal Meteorological Society

An ensemble approach to uncertainty estimation for satellite-based rainfall estimates

Condition number estimates for combined potential boundary integral operators in acoustic scattering

We study the classical combined field integral equation formulations for time-harmonic acoustic scattering by a sound soft bounded obstacle, namely the indirect formulation due to Brakhage-Werner/Leis/Panic, and the direct formulation associated with the names of Burton and Miller. We obtain lower and upper bounds on the condition numbers for these formulations, emphasising dependence on the frequency, the geometry of the scatterer, and the coupling parameter. Of independent interest we also obtain upper and lower bounds on the norms of two oscillatory integral operators, namely the classical acoustic single- and double-layer potential operators.

Estimating surface CO2 fluxes from space-borne dry air mole fraction observations using an Ensemble Kalman filter

We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Inconsistencies between satellite estimates of longwave cloud forcing and dynamical fields from reanalyses

The greenhouse effect of cloud may be quantified as the difference between outgoing longwave radiation (OLR) and its clear-sky component (OLRc). Clear-sky measurements from satellite preferentially sample drier, more stable conditions relative to the monthly-mean state. The resulting observational bias is evident when OLRc is stratified by vertical motion; differences to climate model OLRc of 15 Wm−2 occur over warm regions of strong ascent. Using data from the ECMWF 40-year reanalysis, an estimate of cloud longwave radiative effect is made which is directly comparable with standard climate model diagnostics. The impact of this methodology on the cancellation of cloud longwave and shortwave radiative forcing in the tropics is estimated.

Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

Correlating Bayesian date estimates with climatic events and domestication using a bovine case study

The tribe Bovini contains a number of commercially and culturally important species, such as cattle. Understanding their evolutionary time scale is important for distinguishing between post-glacial and domestication-associated population expansions, but estimates of bovine divergence times have been hindered by a lack of reliable calibration points. We present a Bayesian phylogenetic analysis of 481 mitochondrial D-loop sequences, including 228 radiocarbon-dated ancient DNA sequences, using a multi-demographic coalescent model. By employing the radiocarbon dates as internal calibrations, we co-estimate the bovine phylogeny and divergence times in a relaxed-clock framework. The analysis yields evidence for significant population expansions in both taurine and zebu cattle, European aurochs and yak clades. The divergence age estimates support domestication-associated expansion times (less than 12 kyr) for the major haplogroups of cattle. We compare the molecular and palaeontological estimates for the Bison-Bos divergence.

The diurnal course of soil moisture as measured by various dielectric sensors: Effects of soil temperature and the implications for evaporation estimates

Soil moisture content, theta, of a bare and vegetated UK gravelly sandy loam soil (in situ and repacked in small lysimeters) was measured using various dielectric instruments (single-sensor ThetaProbes, multi-sensor Profile Probes, and Aquaflex Sensors), at depths ranging between 0.03 and I m, during the summers of 2001 (in situ soil) and 2002 (mini-lysimeters). Half-hourly values of evaporation, E, were calculated from diurnal changes in total soil profile water content, using the soil water balance equation. For the bare soil field, Profile Probes and ML2x ThetaProbes indicated a diurnal course of theta that did not concur with typical soil physical observations: surface layer soil moisture content increased from early morning until about midday, after which theta declined, generally until the early evening. The unexpected course of theta was positively correlated to soil temperature, T-s, also at deeper depths. Aquaflex and ML1 ThetaProbe (older models) outputs, however, reflected common observations: 0 increased slightly during the night (capillary rise) and decreased from the morning until late afternoon (as a result of evaporation). For the vegetated plot, the spurious diurnal theta fluctuations were less obvious, because canopy shading resulted in lower amplitudes of T-s. The unrealistic theta profiles measured for the bare and vegetated field sites caused diurnal estimates of E to attain downward daytime and upward night-time values. In the mini-lysimeters, at medium to high moisture contents, theta values measured by (ML2x) ThetaProbes followed a relatively realistic course, and predictions of E from diurnal changes in vertically integrated theta generally compared well with lysimeter estimates of E. However, time courses of theta and E became comparable to those observed for the field plots when the soil in the lysimeters reached relatively low values of theta. Attempts to correct measured theta for fluctuations in T, revealed that no generally applicable formula could be derived. (c) 2005 Elsevier B.V. All rights reserved.