Influence of season and time of day on marsh bird detections

Harms, Tyler M.; Dinsmore, Stephen J.

doi:10.1676/13-150.1

Cited by 18 publications

(15 citation statements)

References 29 publications

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“…Because we detected 47% of Swamp Sparrows during evening surveys, we assumed there was no difference in detection probably between morning and evening surveys and used observations from both survey periods for our analysis. We conducted surveys at a total of 307 wetlands in both 2009 and 2010 (Table 1); 56 wetlands were surveyed four times in 2010 as part of a different study evaluating temporal variation in detection probability of marsh birds (see Harms and Dinsmore 2014) and the remaining 251 wetlands were surveyed once in either 2009 or 2010. For the 56 wetlands surveyed four times, we considered only visits that were .1 week apart for analysis to ensure independence between visits.…”

Section: Methodsmentioning

confidence: 99%

Density, Abundance, and Habitat Associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa

Harms¹,

Dinsmore²

2015

The Wilson Journal of Ornithology

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Wetlands continue to decline throughout North America and the Prairie Pothole Region, thus emphasizing the importance of understanding population trends and habitat associations of wetland species to ensure effective conservation and habitat management of those species. We estimated density and abundance and evaluated habitat associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa. We conducted standardized distance sampling surveys for Swamp Sparrows and measured habitat characteristics at 307 wetlands in two regions of Iowa in 2009 and 2010. We used Program Distance to model detection probability and estimate region-specific breeding densities of Swamp Sparrows at Iowa wetlands. We then extrapolated density estimates to the total area of wetlands in each region to obtain estimates of breeding abundance. We correlated Swamp Sparrow counts to nine habitat variables using Poisson regression in Program R. Swamp Sparrow counts were positively correlated with percent cover of cattail (Typha spp.) and water depth (cm) and negatively correlated with percent cover of woody vegetation, vegetation size (m), and wetland size (ha). We estimated breeding densities of Swamp Sparrows to be 1.488 birds/ha (95% CI = 1.308 − 1.692) in region 1 (Des Moines Lobe landform) and 0.041 birds/ha (95% CI = 0.006 − 0.275) in region 2 (remainder of the state). Our results, in comparison to those of other studies, indicate that Swamp Sparrows associate with a variety of wetland characteristics depending upon what is available. Swamp Sparrows are relatively uncommon breeders in Iowa, and our work confirms that most occur in the Des Moines Lobe landform in north-central and northwestern Iowa. Biologists and land managers should incorporate our findings on this species' habitat associations into management activities to ensure that Swamp Sparrow populations persist into the future. ABSTRACT.-Wetlands continue to decline throughout North America and the Prairie Pothole Region, thus emphasizing the importance of understanding population trends and habitat associations of wetland species to ensure effective conservation and habitat management of those species. We estimated density and abundance and evaluated habitat associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa. We conducted standardized distance sampling surveys for Swamp Sparrows and measured habitat characteristics at 307 wetlands in two regions of Iowa in 2009 and 2010. We used Program Distance to model detection probability and estimate region-specific breeding densities of Swamp Sparrows at Iowa wetlands. We then extrapolated density estimates to the total area of wetlands in each region to obtain estimates of breeding abundance. We correlated Swamp Sparrow counts to nine habitat variables using Poisson regression in Program R. Swamp Sparrow counts were positively correlated with percent cover of cattail (Typha spp.) and water depth (cm) and negatively correlated with percent cover of woody vegetation, vegetation size (m)...

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Section: Methodsmentioning

confidence: 99%

Density, Abundance, and Habitat Associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa

Harms¹,

Dinsmore²

2015

The Wilson Journal of Ornithology

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“…To reduce the number of candidate models in the co-occurrence framework, we modeled detection probability for each species using the single-season occupancy model (MacKenzie et al 2002) in Program MARK (White andBurnham 1999, Richmond et al 2010). We modeled detection probability (p) for each species as a time-varying parameter to account for seasonal differences in detection probability of our target species (Harms and Dinsmore 2014) and included the covariates temperature, wind speed, cloud cover, and observer as factors potentially influencing detection probability while keeping site occupancy probability (Ψ) constant (denoted as "."). Using Akaike's Information Criterion adjusted for small sample sizes (AIC c ; Burnham and Anderson 2002), we compared 11 candidate models for detection probability for each species.…”

Section: Modeling Approachmentioning

confidence: 99%

Spatial scale matters when modeling avian co‐occurrence

Harms

Dinsmore

2016

Ecosphere

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The spatial scale at which competition alters the spatial distribution of a species is important to consider when evaluating competitive interactions between species. The two‐species occupancy model was developed to evaluate competitive interactions between two species while accounting for imperfect detection. However, no studies have incorporated spatial scale into such models. We developed an approach to incorporate spatial scale when evaluating species co‐occurrence using the two‐species occupancy model and tested our approach on two wetland passerines: the Yellow‐headed Blackbird (Xanthocephalus xanthocephalus) and the Marsh Wren (Cistothorus palustris). We surveyed for Yellow‐headed Blackbirds and Marsh Wrens using point counts at wetlands throughout Iowa in 2009 and 2010. We assigned observations to one of three distance bins: ≤20, ≤60, and ≤100 m and then created encounter histories for each distance bin for the two‐species occupancy model and modeled co‐occurrence as a function of habitat covariates for each distance bin. We also modeled co‐occurrence using all observations regardless of distance. We found that Yellow‐headed Blackbirds were less likely to co‐occur with Marsh Wrens at both the ≤60 and ≤100 m scales. However, using all observations, we found that Yellow‐headed Blackbirds and Marsh Wrens co‐occurred independent of one another. This result illustrated that failure to incorporate spatial scale in evaluations of species co‐occurrence could lead to incorrect inferences on co‐occurrence of different species. The two‐species co‐occurrence occupancy model is a valuable tool that allows researchers to evaluate the presence of competitive interactions between species, and incorporating spatial scale into these models provides information on how species partition resources at different spatial scales within a patch. Understanding species co‐occurrence patterns across multiple spatial scales provides valuable information that is useful for a better understanding of the mechanisms of competitive interactions between two species and aiding the restoration and management of habitat for multiple species.

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“…Despite using call‐broadcast methodology, detection probability of secretive marsh birds has been found to vary both by time of day and seasonally (Rehm and Baldassarre , Nadeau et al. , Harms and Dinsmore , Wiest and Shriver ). No one, however, has examined temporal differences in detection probability of non‐focal marsh bird species, information valuable not only to validate the marsh bird protocol for surveying non‐focal species, but also to aid managers interested in estimating population trends of marsh passerines using data collected under the marsh bird protocol or other count methods.…”

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Optimizing surveys for marsh songbirds: does timing matter?

Harms

Dinsmore

2018

J. Field Ornithol.

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Analysis of data from point counts, a common method for monitoring bird population trends, has evolved to produce estimates of various population parameters (e.g., density, abundance, and occupancy) while simultaneously estimating detection probability. An important consideration when designing studies using point counts is to maximize detection probability while minimizing variation in detection probability both within and between counts. Our objectives were to estimate detection probabilities for three marsh songbirds, including Marsh Wrens (Cistothorus palustris), Swamp Sparrows (Melospiza georgiana), and Yellow-headed Blackbirds (Xanthocephalus xanthocephalus), as a function of weather covariates and to evaluate temporal variability in detection probability of these three species. We conducted paired, unlimited radius, 10min point counts during consecutive morning and evening survey periods for our three focal species at 56 wetlands in Iowa from 20 April to 10 July 2010. Mean detection probabilities ranged from 0.272 (SE = 0.042) for Marsh Wrens to 0.365 (SE = 0.052) for Swamp Sparrows. Time of season was positively correlated with detection probability for Swamp Sparrows, but was negatively correlated with detection probability for Yellow-headed Blackbirds, suggesting that detection probability increased during the breeding season for Swamp Sparrows and was highest early in the breeding season for Yellow-headed Blackbirds. Understanding how detection probabilities of marsh songbirds vary throughout the breeding season allows targeted survey efforts that maximize detection probabilities for these species. Furthermore, consistent detection probabilities of marsh songbirds during morning and evening survey periods mean that investigators have more time to conduct surveys for these birds, allowing greater flexibility to increase spatial and temporal replication of surveys that could provide more precise estimates of desired population parameters.RESUMEN. Optimizando el muestreo de aves de pantano: es importante el tiempo en el que se hace? El an alisis de datos de puntos de conteo, un m etodo com un para el monitoreo de tendencias poblacionales en aves, ha evolucionado con el fin de producir estimados de varios par ametros poblacionales (e.g., densidad, abundancia, ocupaci on), estimando simult aneamente la probabilidad de detecci on. Una consideraci on importante en el diseño de estudios que usan puntos de conteos es maximizar la probabilidad de detecci on y minimizar la variaci on en la probabilidad de detecci on dentro y entre conteos. Nuestros objetivos fueron la estimaci on de la detecci on de probabilidad en tres especies de aves paseriformes de pantano, incluyendo Cistothorus paulstris, Melospiza georgiana y Xanthocephalus xanthocephalus como una funci on de covariables clim aticas y la evaluaci on de la variabilidad temporal en la probabilidad de detecci on de estas tres especies. Realizamos conteos pareados sin limite de radio y de 10 minutos de duraci on durante periodos de muestreo consecutivos en la ...

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Influence of season and time of day on marsh bird detections

Cited by 18 publications

References 29 publications

Density, Abundance, and Habitat Associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa

Density, Abundance, and Habitat Associations of the Inland Swamp Sparrow (Melospiza georgiana georgiana) in Iowa

Spatial scale matters when modeling avian co‐occurrence

Optimizing surveys for marsh songbirds: does timing matter?

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