Does time of season influence bird species number determined from point-count data? A capture-recapture approach

Selmi, Slaheddine; Boulinier, Thierry

doi:10.1648/0273-8570-74.4.349

Cited by 39 publications

(41 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar to changes in vocalization frequency throughout a day, singing rate may vary across the breeding season (Selmi and Boulinier 2003). There were lower counts in overall species richness and abundance and almost all of the common species during surveys conducted in early June (11 June; forest-edge ARU 1 week earlier) than those from later in June (18-20 June; forestedge ARU BBS).…”

Section: Discussionmentioning

confidence: 88%

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

Mahon¹,

Haché²,

Sólymos³

et al. 2017

ACE

View full text Add to dashboard Cite

ABSTRACT. The North American Breeding Bird Survey (BBS) is one of the longest annual avian surveys and has the greatest spatiotemporally extensive coverage in the Western Hemisphere. Although this important survey provides trend estimates for more than 400 species, it has limited coverage in the boreal forest and biases in representation and detectability that complicate inference. Thus, there is a need to evaluate the potential of new technologies and analytical approaches to increase coverage and improve monitoring efficiency. We documented variation in counts between BBS surveys (hereafter "human BBS") and different on-road and forest-edge surveys using autonomous recording units (ARUs) from 3 routes in the Northwest Territories, Canada. Specifically, we quantified percent differences (i.e., bias in counts) in species richness, abundance indices of birds, and species-specific variation in counts between human BBS and ARU-based surveys conducted on-road and at the forest edge at different dates and times of day. We also generated on-road effective detection radius (EDR) estimates for 15 species and tested for species-specific differences in EDR to explain bias in counts between on-road and forest-edge ARU surveys. Overall, species richness and abundance indices in human BBS surveys were higher than forest-edge ARU surveys conducted simultaneously and when similar forest-edge ARU surveys were conducted at sunset and a week earlier in June. However, there was no difference when comparing values from human BBS with on-road ARU BBS and forest-edge ARU surveys conducted at sunrise. Extracting the maximum count per species from 4 types of 3-minute forest-edge surveys increased counts by 62% and 64% for species richness and abundance indices, respectively, relative to human BBS, but the importance of this bias differed considerably among the 10 most common species in the study area. Our results suggest that false-negative bias in species detection could be corrected with appropriate methods, and ARUs deployed at the forest edge near BBS stops could be used to increase data quality of on-road surveys. When combined with appropriate correction factors to adjust for surveys done at the forest edge, ARUs could also be used to increase the geographic coverage of boreal surveys by allowing inexperienced volunteers to collect BBS data along winter or secondary roads in remote locations. Avantages

show abstract

Section: Discussionmentioning

confidence: 88%

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

Mahon¹,

Haché²,

Sólymos³

et al. 2017

ACE

View full text Add to dashboard Cite

show abstract

“…We also collected data on four survey-specific covariates for use in occupancy modeling (developing best-fit regression models to assess habitat characteristics that influence the occurrence of birds at sites): sample day (days from May 17), time of day (minutes from 06:00 h), estimated percent cloud cover, and air temperature ( • C) at the time of the point count (Ralph and Scott, 1981;Selmi and Boulinier, 2003). We used these survey covariates to model detection probability, or the probability of detecting a species when it is actually present during a single visit (MacKenzie et al, 2002).…”

Section: Bird Surveysmentioning

confidence: 99%

Wetlands as habitat in urbanizing landscapes: Patterns of bird abundance and occupancy

McKinney

Raposa

Cournoyer

2011

Landscape and Urban Planning

View full text Add to dashboard Cite

“…Counts based on point-count surveys are considered an index of the actual population present at a given site because some portion of the population is not present on the breeding grounds during the time of the survey (i.e., probability of presence), is present but does not signal its presence during a survey (i.e., availability bias), or signals but is not detected by the surveyor (i.e., perceptibility bias) (Rosenstock et al 2002;Elphick 2008;Nichols et al 2009). This ''imperfect detection'' may not affect the interpretation of results as long as the ratio of detection and counts are unbiased or relatively constant (Johnson 2008), but several studies have shown that detection probability often varies by observers (Diefenbach et al 2003;Alldredge et al 2007;Simons et al 2007;Reidy et al 2014), by habitat (Pacifici et al 2008;Amundson et al 2014), with weather conditions Amundson et al 2014), and through time (Selmi and Boulinier 2003;Diefenbach et al 2007). Further, if detection probability differs between habitats but is not accounted for, differences in detection may be misattributed to species habitat associations (Amundson et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Landscape and local effects on occupancy and densities of an endangered wood-warbler in an urbanizing landscape

et al. 2015

View full text Add to dashboard Cite

Context Golden-cheeked warblers (Setophaga chrysoparia), an endangered wood-warbler, breed exclusively in woodlands co-dominated by Ashe juniper (Juniperus ashei) in central Texas. Their breeding range is becoming increasingly urbanized and habitat loss and fragmentation are a main threat to the species' viability.Objectives We investigated the effects of remotely sensed local habitat and landscape attributes on point occupancy and density of warblers in an urban preserve and produced a spatially explicit density map for the preserve using model-supported relationships. Methods We conducted 1507 point-count surveys during spring 2011-2014 across Balcones Canyonlands Preserve (BCP) to evaluate warbler habitat associations and predict density of males. We used hierarchical Bayesian models to estimate multiple components of detection probability and evaluate covariate effects on detection probability, point occupancy, and density. Results Point occupancy was positively related to landscape forest cover and local canopy cover; mean occupancy was 0.83. Density was influenced more by local than landscape factors. Density increased with greater amounts of juniper and mixed forest and decreased with more open edge. There was a weak negative relationship between density and landscape urban land cover. Conclusions Landscape composition and habitat structure were important determinants of warbler occupancy and density, and the large intact patches of juniper and mixed forest on BCP ([2100 ha) supported a high density of warblers. Increasing urbanization and fragmentation in the surrounding landscape will likely result in lower breeding density due to loss of juniper and mixed forest and increasing urban land cover and edge.

show abstract

Does time of season influence bird species number determined from point-count data? A capture-recapture approach

Cited by 39 publications

References 15 publications

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

Wetlands as habitat in urbanizing landscapes: Patterns of bird abundance and occupancy

Landscape and local effects on occupancy and densities of an endangered wood-warbler in an urbanizing landscape

Contact Info

Product

Resources

About