Effects of ambient noise on detectability and localization of avian songs and tones by observers in grasslands

A stochastic simulation model for assessing the masking effects of road noise for wildlife, outdoor recreation, and bioacoustic monitoring

Traffic noise is one of the leading causes of reductions in animal abundances near roads. Acoustic masking of conspecific signals and adventitious cues is one mechanism that likely causes animals to abandon loud areas. However, masking effects can be difficult to document in situ and the effects of infrequent noise events may be impractical to study. Here, we present the Soundscapes model, a stochastic individual-based model that dynamically models the listening areas of animals searching for acoustic resources (“searchers"). The model also studies the masking effects of noise for human detections of the searchers. The model is set in a landscape adjacent to a road. Noise produced by vehicles traveling on that road is represented by calibrated spectra that vary with speed. Noise propagation is implemented using ISO-9613 procedures. We present demonstration simulations that quantify declines in searcher efficiency and human detection of searchers at relatively low traffic volumes, fewer than 50 vehicles per hour. Traffic noise is pervasive, and the Soundscapes model offers an extensible tool to study the effects of noise on bioacoustics monitoring, point-count surveys, the restorative value of natural soundscapes, and auditory performance in an ecological context.

Detection Rate of Bird Species and What It Depends on: Tips for Field Surveys

Bird counting inevitably suffers from imperfect detection, which varies across species, habitats, period of the day, and seasons. Although various modeling techniques have recently been developed to account for this phenomenon, the biological basis of natural variation in detection remains insufficiently known. This study examined the bird species’ detection rate throughout the day, considering their body mass and diet type, concerning the environment and weather characteristics. Species detection rates were significantly affected by the number of individuals of that species but were unrelated to body mass. Overall, species with the highest detection rate were Corn bunting, Blackbird, European robin, House sparrow and Common chiffchaff. Granivores-insectivores and insectivores showed significant differences in detection rates throughout the day among habitats, with higher detection rates in grasslands during the afternoon. Insectivores showed higher detection rates in farmland during midday (warmest time of the day). Granivores, omnivores and scavengers did not show changes in detection rates in different day periods. Such patterns in daily detection rates were significant even when considering abundance and total species richness in each community. Finally, cloudiness was unrelated to the overall detection rate of birds, while temperature and wind affected detection rates in some guilds. Our findings provide some advice for choosing a suitable ornithological sampling method by considering the avian communities composition in combination with the type of environment, the diet of bird species, and the period of the day.

Direct Mercury Detection in Landfill Leachate Using a Novel AuNP-Biopolymer Carbon Screen-Printed Electrode Sensor

A novel Au nanoparticle (AuNP)-biopolymer coated carbon screen-printed electrode (SPE) sensor was developed through the co-electrodeposition of Au and chitosan for mercury (Hg) ion detection. This new sensor showed successful Hg2+ detection in landfill leachate using square wave anodic stripping voltammetry (SWASV) with an optimized condition: a deposition potential of -0.6 V, deposition time of 200 s, amplitude of 25 mV, frequency of 60 Hz, and square wave step voltage of 4 mV. A noticeable peak was observed at +0.58 V associated with the stripping current of the Hg ion. The sensor exhibited a good sensitivity of ~0.09 μA/μg (~0.02 μA/nM) and a linear response over the concentration range of 10 to 100 ppb (50-500 nM). The limit of detection (LOD) was 1.69 ppb, which is significantly lower than the safety limit defined by the United States Environmental Protection Agency (USEPA). The sensor had an excellent selective response to Hg2+ in landfill leachate against other interfering cations (e.g., Zn2+, Pb2+, Cd2+, and Cu2+). Fifteen successive measurements with a stable peak current and a lower relative standard deviation (RSD = 5.1%) were recorded continuously using the AuNP-biopolymer-coated carbon SPE sensor, which showed excellent stability, sensitivity and reproducibility and consistent performance in detecting the Hg2+ ion. It also exhibited a good reliability and performance in measuring heavy metals in landfill leachate.

A Novel Bismuth-Chitosan Nanocomposite Sensor for Simultaneous Detection of Pb(II), Cd(II) and Zn(II) in Wastewater

A novel bismuth (Bi)-biopolymer (chitosan) nanocomposite screen-printed carbon electrode was developed using a Bi and chitosan co-electrodepositing technique for detecting multiple heavy metal ions. The developed sensor was fabricated with environmentally benign materials and processes. In real wastewater, heavy metal detection was evaluated by the developed sensor using square wave anodic stripping voltammetry (SWASV). The nanocomposite sensor showed the detection limit of 0.1 ppb Zn²⁺, 0.1 ppb Cd²⁺ and 0.2 ppb Pb²⁺ in stock solutions. The improved sensitivity of the Bi-chitosan nanocomposite sensor over previously reported Bi nanocomposite sensors was attributed to the role of chitosan. When used for real wastewater samples collected from a mining site and soil leachate, similar detection limit values with 0.4 ppb Cd²⁺ and 0.3 ppb Pb²⁺ were obtained with relative standard deviations (RSD) ranging from 1.3% to 5.6% (n = 8). Temperature changes (4 and 23 °C) showed no significant impact on sensor performance. Although Zn²⁺ in stock solutions was well measured by the sensor, the interference observed while detecting Zn²⁺ in the presence of Cu²⁺ was possibly due to the presence of Cu-Zn intermetallic species in mining wastewater. Overall, the developed sensor has the capability of monitoring multiple heavy metals in contaminated water samples without the need for complicated sample preparation or transportation of samples to a laboratory.

Noisy anthropogenic infrastructure interferes with alarm responses in Savannah sparrows (Passerculus sandwichensis)

Many birds rely on anti-predator communication to protect their nests; however, anthropogenic noise from industrial activities such as oil and gas development may disrupt acoustic communication. Here, we conducted acoustic playback experiments to determine whether Savannah sparrows (Passerculus sandwichensis) responded to conspecific alarm calls by delaying feeding visits, and whether this response was impaired by noise-producing natural gas compressor stations, generator- or grid-powered screw pump oil wells, and noise amplitude. We played alarm calls, and, as a control, western meadowlark songs, to Savannah sparrows as they approached their nests to feed their nestlings, and measured feeding latency. The greatest impacts on behaviour were detected at the noisiest treatment, compressor stations; feeding latency was shortened here compared with control sites, which may expose nests to greater predation risk. As noise amplitudes increased, Savannah sparrows took longer to feed following meadowlark playbacks, perhaps because noise interfered with interpretation of acoustic cues. The effects of compressor stations on anti-predator behaviour may be best explained by the distracting effects of anthropogenic noise, while increases in feeding latency following meadowlark playbacks may be explained by a heightened response threshold caused by acoustic masking. Industrial infrastructure can influence the reproductive success of wildlife through its impact on perception and interpretation of conspecific signals, but these effects are complex.

Conventional oil and natural gas infrastructure increases brown-headed cowbird (Molothrus ater) relative abundance and parasitism in mixed-grass prairie

The rapid expansion of oil and natural gas development across the Northern Great Plains has contributed to habitat fragmentation, which may facilitate brood parasitism of ground-nesting grassland songbird nests by brown-headed cowbirds (Molothrus ater), an obligate brood parasite, through the introduction of perches and anthropogenic edges. We tested this hypothesis by measuring brown-headed cowbird relative abundance and brood parasitism rates of Savannah sparrow (Passerculus sandwichensis) nests in relation to the presence of infrastructure features and proximity to potential perches and edge habitat. The presence of oil and natural gas infrastructure increased brown-headed cowbird relative abundance by a magnitude of four times, which resulted in four times greater brood parasitism rates at infrastructure sites. While the presence of infrastructure and the proximity to roads were influential in predicting brood parasitism rates, the proximity of perch sites was not. This suggests that brood parasitism associated with oil and natural gas infrastructure may result in additional pressures that reduce productivity of this declining grassland songbird.

Conventional oil and natural gas infrastructure increases brown-headed cowbird (Molothrus ater) relative abundance and parasitism in mixed-grass prairie

The rapid expansion of oil and natural gas development across the Northern Great Plains has contributed to habitat fragmentation, which may facilitate brood parasitism of ground-nesting grassland songbird nests by brown-headed cowbirds (Molothrus ater), an obligate brood parasite, through the introduction of perches and anthropogenic edges. We tested this hypothesis by measuring brown-headed cowbird relative abundance and brood parasitism rates of Savannah sparrow (Passerculus sandwichensis) nests in relation to the presence of infrastructure features and proximity to potential perches and edge habitat. The presence of oil and natural gas infrastructure increased brown-headed cowbird relative abundance by a magnitude of four times, which resulted in four times greater brood parasitism rates at infrastructure sites. While the presence of infrastructure and the proximity to roads were influential in predicting brood parasitism rates, the proximity of perch sites was not. This suggests that brood parasitism associated with oil and natural gas infrastructure may result in additional pressures that reduce productivity of this declining grassland songbird.

Effects of shallow natural gas well structures and associated roads on grassland songbird reproductive success in Alberta, Canada

Grassland songbird populations across North America have experienced dramatic population declines due to habitat loss and degradation. In Canada, energy development continues to fragment and disturb prairie habitat, but effects of oil and gas development on reproductive success of songbirds in North American mixed-grass prairies remains largely unknown. From 2010–2012, in southeastern Alberta, Canada, we monitored 257 nests of two ground-nesting grassland songbird species, Savannah sparrow (Passerculus sandwichensis) and chestnut-collared longspur (Calcarius ornatus). Nest locations varied with proximity to and density of conventional shallow gas well structures and associated roads in forty-two 258-ha mixed-grass prairie sites. We estimated the probabilities of nest success and clutch size relative to gas well structures and roads. There was little effect of distance to or density of gas well structure on nest success; however, Savannah sparrow experienced lower nest success near roads. Clutch sizes were lower near gas well structures and cattle water sources. Minimizing habitat disturbance surrounding gas well structures, and reducing abundance of roads and trails, would help minimize impacts on reproductive success for some grassland songbirds.