Multi-Species Call-Broadcast Improved Detection of Endangered Yuma Clapper Rail Compared to Single-Species Call-Broadcast

Nadeau, Christopher P.; Conway, Courtney J.; Piest, Linden; Burger, William P.

doi:10.1007/s13157-013-0425-x

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…Call broadcasts substantially increase detection probabilities of secretive marsh birds, which have low detection probabilities on passive surveys in the absence of call broadcast (Conway and Gibbs , Conway and Nadeau , Nadeau et al. ). Surveys were often repeated at each site within a breeding season (range = 1–23 site visits per year), and sampling conditions varied among site visits.…”

Section: Methodsmentioning

confidence: 99%

“…), and especially for surveys of secretive marsh birds like the King Rail (Conway and Gibbs , Nadeau et al. , ). In addition, our data were collected from replicated site visits during the same breeding season, which allowed estimation of King Rail occupancy while also explicitly accounting for animals present but not detected during sampling (Kéry , MacKenzie et al.…”

Section: Methodsmentioning

confidence: 99%

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Predicting species distributions: unifying model selection and scale optimization for multi‐scale occupancy models

Stevens

Conway

2019

Ecosphere

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Geographic distributions are a basic component of a species’ ecology, and predicting distributions is a fundamental task of conservation and resource management. Reliable prediction depends on identification of appropriate scales of effect for environmental data, and scale‐optimization techniques are thus desirable to identify optimal scales for predictor variables. Recent statistical developments have also advanced methods of model selection based explicitly on predictive ability, which differ from commonly used methods that regulate model structures via anticipated predictive performance. Such methods are beginning to permeate into species distribution models (SDMs), yet there remains no consensus methodology for developing optimally predictive multi‐scale SDMs when covariate data are collected over a range of scales. Thus, we compared the performance of common approaches for scale optimization and model selection in terms of their ability to produce optimally predictive multi‐scale Bayesian occupancy models for predicting a species distribution, using models of the breeding distribution for King Rails (Rallus elegans) as a case study. Our results demonstrate sizable gains in predictive performance for hierarchical occupancy models selected via their ability to predict out‐of‐sample data using the logarithmic scoring rule, as compared to models selected using information criteria (deviance information criteria [DIC] and Watanabe information criteria [WAIC]). Information criteria commonly selected individual covariates, as well as scales of effect for those covariates, with suboptimal predictive performance. Performance of models selected using the logarithmic scoring rule was also robust across the method of scale optimization, which was not true for models selected using DIC and WAIC. Thus, we demonstrate empirical benefits of study designs and statistical tools that enable covariate and scale selection based explicitly on predictive ability. Our results also imply that more careful consideration of what constitutes an optimal scale is warranted in many ecological applications, as the meaning of optimal is not independent of the technique used for scale selection.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Predicting species distributions: unifying model selection and scale optimization for multi‐scale occupancy models

Stevens

Conway

2019

Ecosphere

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“…To assess the effects of factors known to influence detection (Rush et al , Conway and Nadeau , Conway and Gibbs , Lehmicke et al , Nadeau et al ), we recorded date, start time, observer, tide stage, sky condition, wind speed, and background noise at the start of each survey. We used 7 different observers during call‐broadcast surveys.…”

Section: Methodsmentioning

confidence: 99%

“…Population monitoring program design and implementation provides the foundation for much of our understanding about status and trends of wildlife populations and responses to habitat management and restoration. A monitoring protocol should attempt to maximize detection probabilities, minimize variation in counts of focal individuals, and minimize the expenses required to acquire the information (Nadeau et al ). To be effective, monitoring efforts must be logistically feasible to implement and adhere to fiscal constraints (Neckles et al ).…”

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confidence: 99%

Survey frequency and timing affect occupancy and abundance estimates for salt marsh birds

Wiest

Shriver

2015

J Wildl Manag

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Salt marsh birds in eastern North America are high conservation priorities due to their restricted ranges, threats from sea-level rise, and an overall lack of information related to their population status or trends. We calculated estimates of detection probabilities for clapper rail (Rallus crepitans), willet (Tringa semipalmata), seaside sparrow (Ammodramus maritimus), and saltmarsh sparrow (A. caudacutus) breeding in Delaware Bay, USA. Our objectives were to model the effects of survey covariates on detection probabilities for occupancy and abundance estimates, determine how survey frequency (no. visits to a site) and survey timing (when in the season sites are sampled) affected the estimates, and how varying the number and timing of visits affected the estimates compared to the recommendations based on the North American Marsh Bird Monitoring Protocol. To make these comparisons, we defined 4 survey frequency (2, 3, 4, and 8 visits) and 3 survey timing (early, early-middle-late, and late season) scenarios. Our results are based on 480 surveys (i.e., call broadcast point counts) to 30 sampling locations located at Bombay and Prime Hook National Wildlife Refuges during the 2008 and 2009 breeding seasons. The scenario of 3 visits early in the season provided the lowest error estimates of occupancy and abundance. Distributing the survey effort across the season, our early-middle-late scenario, provided high variance estimates and should be avoided when designing monitoring programs for these tidal marsh obligate species. Ó 2015 The Wildlife Society.

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“…Second, we surveyed at 17 survey points at the reference‐restoration site in 2009 and 2010, but we only surveyed at eight of these points prior to 2009. We evaluated the effects of these differences in survey methods on our conclusions by: (1) subsampling the survey periods of all the surveys (2000–2010) so that each survey included only a 3‐minute initial passive period and a 1‐minute black rail call‐broadcast period (see Nadeau et al for more details on Methods), and (2) only including bird detections from points that were surveyed across all years. Differences in survey methods used in 2000–2008 and those used in 2009–2010 did not affect our conclusions (Fig.…”

Section: Methodsmentioning

confidence: 99%

Optimizing water depth for wetland‐dependent wildlife could increase wetland restoration success, water efficiency, and water security

Nadeau

Conway

2015

Restoration Ecology

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Securing water for wetland restoration efforts will be increasingly difficult as human populations demand more water and climate change alters the hydrologic cycle. Minimizing water use at a restoration site could help justify water use to competing users, thereby increasing future water security. Moreover, optimizing water depth for focal species will increase habitat quality and the probability that the restoration is successful. We developed and validated spatial habitat models to optimize water depth within wetland restoration projects along the lower Colorado River intended to benefit California black rails (Laterallus jamaicensis coturniculus). We observed a 358% increase in the number of black rails detected in the year after manipulating water depth to maximize the amount of predicted black rail habitat in two wetlands. The number of black rail detections in our restoration sites was similar to those at our reference site. Implementing the optimal water depth in each wetland decreased water use while simultaneously increasing habitat suitability for the focal species. Our results also provide experimental confirmation of past descriptive accounts of black rail habitat preferences and provide explicit water depth recommendations for future wetland restoration efforts for this species of conservation concern; maintain surface water depths between saturated soil and 100 mm. Efforts to optimize water depth in restored wetlands around the world would likely increase the success of wetland restorations for the focal species while simultaneously minimizing and justifying water use.

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Multi-Species Call-Broadcast Improved Detection of Endangered Yuma Clapper Rail Compared to Single-Species Call-Broadcast

Cited by 5 publications

References 15 publications

Predicting species distributions: unifying model selection and scale optimization for multi‐scale occupancy models

Predicting species distributions: unifying model selection and scale optimization for multi‐scale occupancy models

Survey frequency and timing affect occupancy and abundance estimates for salt marsh birds

Optimizing water depth for wetland‐dependent wildlife could increase wetland restoration success, water efficiency, and water security

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