King Rail Research Articles

Using Environmental DNA to Detect Radio-Tagged King Rails: Initial Validation Results and Needed Advancements

Abstract Secretive avian species can be difficult to detect. For such species, environmental DNA (eDNA) monitoring could improve our ability to estimate occupancy and population trends. There are often challenges associated with efforts to establish eDNA as an effective monitoring tool for species of conservation concern because it is difficult to hold nonmodel organisms in captivity to complete validation tests. To address this issue, we tracked four king rails Rallus elegans in Ohio, USA, in 2020 with radio telemetry to determine whether our eDNA monitoring approach could indicate king rail presence where these individuals occurred. Also, we collected eDNA near locations surveyed by human observers within potential habitat where king rail status was unknown. The eDNA surveys indicated king rail presence at one of five locations where we knew that an individual king rail had occurred within 30 h and at one of four locations where king rail presence was unknown but feasible. At these latter locations, human observers detected no king rails, although in 2022 human observers using traditional survey methods detected a king rail near the same location where our eDNA detection occurred in 2020. This study provides a preliminary, although informative, king rail eDNA monitoring methodology that we validated with radio telemetry data. We suggest ways to improve our approach to increase king rail detection rates and to add confidence in results.

King Rail (Rallus elegans) Morphometric, Nesting, Mortality, and Movement Notes from a Northern Study Area

King Rail (Rallus elegans) Morphometric, Nesting, Mortality, and Movement Notes from a Northern Study Area

King Rail (Rallus elegans) presence in the Midwestern United States is predicted by local-scale factors and avian community.

The King Rail (Rallus elegans) is a wetland dependent species of conservation concern. Our objective was to gain a better understanding of the breeding habitat associations of King Rails in the Midwestern United States and the relationship of this species to other obligate marsh birds using occupancy and MaxEnt models. To collect data pertaining to occupancy, we placed trail cameras at 50 random points in coastal wetlands in the western Lake Erie basin where calls of King Rails were continuously broadcast at night. Data pertaining to other marsh bird species were collected via call-broadcast surveys and camera surveys at each sample point. For MaxEnt modeling, we obtained presence data for King Rails and other obligate marsh birds from eBird and habitat data from GIS databases. Trail cameras and call-broadcast surveys captured 10 detections of King Rails at nine sites, an 18% naive occupancy rate. King Rail occupancy was positively related to amount of interspersion, average water depth, and percent cover of emergent vegetation at local scales within a 5-m radius. Our MaxEnt models indicated that, at a broader scale, the presence of other rail species such as the Sora (Porzana carolina) may be more important for predicting King Rail presence than other marsh birds or coarse wetland categories such as "emergent vegetation." Our results could help wetland managers to predict where King Rails occur and to adapt management plans to incorporate King Rail conservation.

First Documentation of King Rail (Rallus elegans) Reproduction in Arkansas Since 2006

First Documentation of King Rail (Rallus elegans) Reproduction in Arkansas Since 2006

A high-quality de novo genome assembly for clapper rail (Rallus crepitans).

The clapper rail (Rallus crepitans), of the family Rallidae, is a secretive marsh bird species that is adapted for high salinity habitats. They are very similar in appearance to the closely related king rail (R. elegans), but while king rails are limited primarily to freshwater marshes, clapper rails are highly adapted to tolerate salt marshes. Both species can be found in brackish marshes where they freely hybridize, but the distribution of their respective habitats precludes the formation of a continuous hybrid zone and secondary contact can occur repeatedly. This system, thus, provides unique opportunities to investigate the underlying mechanisms driving their differential salinity tolerance as well as the maintenance of the species boundary between the 2 species. To facilitate these studies, we assembled a de novo reference genome assembly for a female clapper rail. Chicago and HiC libraries were prepared as input for the Dovetail HiRise pipeline to scaffold the genome. The pipeline, however, did not recover the Z chromosome so a custom script was used to assemble the Z chromosome. We generated a near chromosome level assembly with a total length of 994.8 Mb comprising 13,226 scaffolds. The assembly had a scaffold N50 was 82.7 Mb, L50 of four, and had a BUSCO completeness score of 92%. This assembly is among the most contiguous genomes among the species in the family Rallidae. It will serve as an important tool in future studies on avian salinity tolerance, interspecific hybridization, and speciation.

King rail (Rallus elegans) home range and microhabitat characteristics in western Lake Erie coastal marshes.

The king rail (Rallus elegans) is a secretive marsh bird that is threatened or endangered in eight of nine states and provinces in the Laurentian Great Lakes (Great Lakes) region. Available survey data suggests that this species has undergone population declines across this region and these are believed to have been driven by habitat loss and degradation. An improved understanding of the amount and type of habitat king rails require during the breeding season at sites within the Great Lakes region would inform and improve progress toward conservation goals. During 2019-2021, we caught and radio-tagged 14 king rails in northwestern Ohio and southeastern Michigan within impounded coastal wetlands of western Lake Erie. We used radio telemetry to identify breeding season (May-August) home-range characteristics and third order habitat selection within home ranges (hereafter microhabitat). For the birds whose home range stabilized (N = 10), we found a mean home-range size of 8.8 ha (±1.63 [SE]; range = 1.9 to 15.8). We generated a classification tree to determine which habitat characteristics were associated with king rail presence within home ranges in our study. We found that vegetative density within home ranges was particularly associated with king rail presence. Phragmites australis was also associated with king rail presence, despite its invasiveness and negative ecological impacts in the region, and could be selectively maintained to benefit king rails. Our results suggest that managers may be able to provide microhabitat for king rails by maintaining water depths of 6 to 17 cm and by promoting native, robust vegetation in the genera Carex and Juncus. Our findings could help inform wetland managers and conservation planners in the Great Lakes region, particularly in western Lake Erie coastal marshes, of patch sizes, water depths, plant communities, and vegetative structure preferred by king rails.

King Rail ( Rallus elegans ) response to audio playback: implications for population estimation, monitoring methodology, and trapping approach

Conspecific audio can be broadcast to improve detection probability (detectability) of secretive marsh bird species for population monitoring purposes and as a lure to more effectively trap individuals. Our primary objective was to describe King Rail (<em>Rallus elegans</em>) detectability as a function of distance and so determine if the distance sampling assumption of perfect detectability immediately adjacent to survey points was violated during call-broadcast surveys. We also described what factors affected King Rail detectability during audio broadcast surveys, and how and when this species was detected, and compared effectiveness of various King Rail call recordings used during trapping attempts. To accomplish these objectives, we experimentalized trapping efforts, radio-tagged 12 King Rails, and conducted repeated call-broadcast surveys for each radio-tagged individual in Michigan and Ohio, USA during the 2020 and 2021 breeding seasons. We found that King Rail detectability during 81 surveys was 0.39, which violates the aforementioned distance sampling assumption and necessitates a correction factor. Detectability within survey segments varied among survey periods, though overall detectability remained relatively constant, even after call-broadcast surveys in our study area typically end (post-survey period: 15 June to 10 July), which indicates that King Rail monitoring could effectively continue later than currently occurs. We found that grunt calls resulted in more captures than kek calls and that a multi-call track was most effective at trapping King Rails. Our findings could improve King Rail population estimates and increase success during trapping efforts, and may inform similar efforts for other secretive marsh birds.

Preliminary assessment of thermal imaging equipped aerial drones for secretive marsh bird detection

Rails are a highly secretive group of marshland obligate species that are difficult to consistently survey and detect. Current survey efforts utilize either call–playback or autonomous recording devices, but the low detection probabilities for rails create challenges for long-term systematic monitoring. Between 8 April and 16 May 2022, we flew a small aerial drone equipped with a thermal camera to survey for six species of rail (Black Rail ( Laterallus jamaicensis), Yellow Rail ( Coturnicops noveboracensis), Sora ( Porzana carolina), Virginia Rail ( Rallus limicola), Clapper Rail ( Rallus crepitans), and King Rail ( Rallus elegans)) along the Gulf Coast of Texas to assess the feasibility of long-term drone monitoring. We successfully conducted 33 flights at 15 m above ground level and detected rails on the first visit at 42% of known occupied points. We achieved 27 total rail detections, including 12 Black Rail/Yellow Rail detections. Of the birds detected, 81% exhibited no response to the drone’s first approach. We intend for this preliminary data to shape future survey protocol for secretive species occupying difficult to navigate terrain.

Great Meadows National Wildlife Refuge, Massachusetts, USA: A Wetland of Distinction

Great Meadows National Wildlife Refuge in eastern Massachusetts has been recognized as a Wetland of Distinction by the Society of Wetland Scientists. It provides essential habitat for migratory birds as well as for resident wildlife including state endangered birds: least bittern (Ixobrychus exilis), pied-billed grebe (Podilymbus podiceps), upland sandpiper (Bartramia longicauda), American bittern (Botaurus lentiginosus), and two state threatened species grasshopper sparrow (Ammodramus savannarum) and king rail (Rallus elegans). Great Meadows also harbors the largest genetically distinct populations of threatened Blanding’s turtle (Emydoidea blandingii) in the Northeast. The refuge also provides outdoor recreation opportunities (hunting, fishing, and nature observation) and a place for environmental education.

King Rail (Rallus elegans) response to audio playback: implications for population estimation, monitoring methodology, and trapping approach

King Rail (Rallus elegans) response to audio playback: implications for population estimation, monitoring methodology, and trapping approach

Trends in Rail Migration Arrival and Departure Times Using Long-Term Citizen Science Data from Mississippi, USA

Little is known of rail migration ecology, consequently limiting efforts to effectively conserve rail populations. Therefore, we investigated changes in the migratory arrival/departure dates for Virginia Rails (Rallus limicola), King Rails (Rallus elegans) and Sora (Porzana carolina) north of Ocean Springs, Mississippi. Using citizen science data collected over the last 25 years, we inspected summarized data for patterns of primary arrival and departure windows indicated by first or last observations of each species at the lagoons, respectively, alongside 10th/90th quantiles that controlled for outliers (i.e., early arrivals, late departures). Regression models found no differences in spring migration departures for any species. In fall migration we found a difference only in Virginia Rail arrivals, which became later over time. King Rail arrived in autumn first in mid-September (September 22nd) followed by Sora (October 5th) and Virginia Rails (October 21st). In spring migration, Virginia Rails departed first (March 19th), then King Rails (March 24th), and Sora (April 20th). Trends for King Rails may have been skewed by some individuals having non-migratory behavior. Despite limitations, citizen science efforts were useful for an initial investigation of rail migration ecology, and future applications could be used to identify and assess factors affecting migration timing (e.g., climate change, habitat availability, weather shifts).

King Rail (Rallus elegans) Home Range and Microhabitat Characteristics in the Great Lakes Region

King Rail (Rallus elegans) Home Range and Microhabitat Characteristics in the Great Lakes Region

King Rail (Rallus elegans) Microhabitat and Home Range Characteristics in the Great Lakes Region

King Rail (Rallus elegans) Microhabitat and Home Range Characteristics in the Great Lakes Region

Secretive marsh bird habitat relationships at mid‐continent spring migration stopover sites

AbstractDespite several secretive marsh bird (SMB) species being listed as critically imperiled throughout the mid‐continent of North America, limited information on SMB distribution and habitat use within primary migratory corridors results in uncertainty on contributions of wetlands in mid‐latitude states toward their annual cycle needs. Our objectives were to quantify temporal patterns of SMB wetland occupancy during spring migration at a mid‐latitude state and evaluate the relationships between SMB colonization probability and water‐level management practices, and the resulting habitat conditions during spring migration. We conducted a 2‐year, dynamic occupancy study (2013–2014) that included 6 rounds of repeated call‐back surveys to detect the presence of 5 SMB species (i.e., Virginia rail [Rallus limicola], sora [Porzana carolina], king rail [R. elegans], least bittern [Ixobrychus exilis], and American bittern [Botaurus lentiginosus]) during spring (Apr–Jun) on 107 wetlands across 8 conservation areas and 4 national wildlife refuges throughout Missouri, USA. We detected sora most frequently, followed by least bittern, American bittern, Virginia rail, and king rail. Coefficient estimates indicated colonization probability for all species was positively associated with emergent vegetation cover and negatively associated with amount of open water. Open water was the only variable in the best supported model explaining American bittern site colonization, to which they were negatively associated. Virginia rail colonization had a strong positive association with vegetation height, whereas least bittern and sora site colonization were influenced positively by water depth and agriculture, respectively. Based on the habitat associations within and among SMB species identified in this study, wetland managers can tailor management strategies to optimize spring migration habitat for single‐ or multi‐species objectives.

Interclutch variability in egg characteristics in two species of rail: Is maternal identity encoded in eggshell patterns?

Maternal signatures are present in the eggs of some birds, but quantifying interclutch variability within populations remains challenging. Maternal assignment of eggs with distinctive appearances could be used to non-invasively identify renesting females, including hens returning among years, as well as to identify cases of conspecific brood parasitism. We explored whether King Rail (Rallus elegans) eggs with shared maternity could be matched based on eggshell pattern. We used NaturePatternMatch (NPM) software to match egg images taken in the field in conjunction with spatial and temporal data on nests. Since we had only a small number of marked breeders, we analyzed similar clutch images from a study of Eurasian Common Moorhens (Gallinula chloropus chloropus) with color-banded breeders for which parentage at many nests had been verified genetically to validate the method. We ran 66 King Rail clutches (n = 338 eggs) and 58 Common Moorhen clutches (n = 364 eggs) through NPM. We performed non-metric multidimensional scaling and permutational analysis of variance using the best egg match output from NPM. We also explored whether eggs could be grouped by clutch using a combination of egg dimensions and pattern data derived from NPM using linear discriminant analyses. We then scrutinized specific matches returned by NPM for King Rail eggs to determine whether multiple matches between the same clutches might reveal maternity among nests and inform our understanding of female laying behavior. To do this, we ran separate NPM analyses for clutches photographed over several years from two spatially distant parts of the site. With these narrower datasets, we were able to identify four instances where hens likely returned to breed among years, four likely cases of conspecific brood parasitism, and a within-season re-nesting attempt. Thus, the matching output was helpful in identifying congruent egg patterns among clutches when used in conjunction with spatial and temporal data, revealing previously unrecognized site fidelity, within-season movements, and reproductive interference by breeding females. Egg pattern data in combination with nest mapping can be used to inform our understanding of female reproductive effort, success, and longevity in King Rails. These methods may also be applied to other secretive birds and species of conservation concern.

Automated auditory detection of a rare, secretive marsh bird with infrequent and acoustically indistinct vocalizations

Autonomous recording units (ARUs) provide a non‐invasive and efficient method for acoustic detection of elusive species across large temporal and spatial scales. However, species with indistinct vocalization structures can be a considerable challenge for automated signal recognizers. We investigated the performance of ARUs and signal recognizers in identifying the broadband, short‐syllable, pulsed calls of a secretive, threatened marsh bird, the King Rail Rallus elegans. Other sympatric species in the same habitat also have repetitive calls within the same frequency range that can be difficult to distinguish. Following serial ARU deployments at specified sites in known breeding habitat, we conducted standardized callback surveys and nest searches to provide an independent measure of breeder density. To analyse recordings, we developed a signal recognizer based on user‐input training files to detect two common call types, kek and grunt. Detections that remained following manual review of recognizer output revealed a previously undescribed seasonal decline and crepuscular diel pattern in calling rate. The rate of the grunt call also predicted density. These patterns emerged despite the recognizer's low precision and high false‐positive rate, which were largely due to misclassification of other species' calls, although ambient noise and effective detection radius also limited the detectability of King Rail calls. We demonstrate that with informed ARU scheduling, improved ability to manipulate user‐specified parameters within signal detection software, and attention to quality control, even the simplest call structures can be located consistently in a diverse acoustic landscape. Our behavioural findings will inform improvements to auditory surveys and to management of King Rails across their range.

Migration Chronology and Wintering Locations of King Rails (Rallus elegans) Captured in the Upper Midwest

King Rails (Rallus elegans) are a secretive marshbird often separated for management purposes into resident and migratory populations. The objective of this research was to gain a better understanding of where Midwest King Rails migrate and winter. Satellite transmitters were placed on nine King Rails captured in Ohio (USA). Autumn migration data was available for four individuals and spring migration data for two individuals. Autumn migration was completed in ≤ 5 days. During autumn migration, three individuals migrated from Ohio to the Gulf Coast, and one individual migrated from Pennsylvania to the southern Atlantic coast. Spring migration lasted longer and had more stopovers than autumn migration. During spring, one individual migrated from Louisiana to Indiana, and one individual migrated from Georgia to Louisiana, indicating likely immigration and emigration between coastal resident and Midwest King Rail populations. Departure dates from the breeding range varied from 30 August to 20 October and spring arrival date to the Upper Midwest was 20 April. All four of the individuals monitored were exposed to potential harvest while on the wintering range. We recommend continued satellite marking of the migratory population across their breeding range to improve understanding of the annual lifecycle of King Rail.

Vocal Repertoire of the King Rail (Rallus elegans)

Auditory callback is the standard method for monitoring rails and other secretive marsh birds that live in concealing habitats. Due to recent population declines, monitoring the King Rail (Rallus elegans) has become a conservation priority. Analysis of field recordings (n = 542 calls or notes) and behavioral observations were combined to provide an account of the structure and function of the King Rail's vocal repertoire, which included 10 different vocalizations. King Rails produced an array of pulsed sounds by altering frequency, note length, pulse rate, and amplitude of each call. The most commonly heard call, the grunt (61 calls recorded; 37 individuals), had multiple functions including mate communication, duetting, and interaction with neighbors in a ‘roll call’ context. The kek (208 calls; 46 individuals) was the primary mate advertisement call. Most of King Rail's calls, including alarms (165 notes; 7 individuals), screeches (47 calls; 7 individuals), churrs (43 calls; 10 individuals), and the poorly documented boom (5 calls; 5 individuals), were used and sometimes combined in defense and distress situations. Although previously described as a signal of receptivity by females, the kek-burr may also be used in the context of defense. This synthesis is intended to assist researchers and managers in interpreting behavioral observations and improving effectiveness of audio lures for detecting or trapping King Rails.

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

AbstractGeographic 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.

Quantitative acoustic differentiation of cryptic species illustrated with King and Clapper rails.

Reliable species identification is vital for survey and monitoring programs. Recently, the development of digital technology for recording and analyzing vocalizations has assisted in acoustic surveying for cryptic, rare, or elusive species. However, the quantitative tools that exist for species differentiation are still being refined. Using vocalizations recorded in the course of ecological studies of a King Rail (Rallus elegans) and a Clapper Rail (Rallus crepitans) population, we assessed the accuracy and effectiveness of three parametric (logistic regression, discriminant function analysis, quadratic discriminant function analysis) and six nonparametric (support vector machine, CART, Random Forest, k‐nearest neighbor, weighted k‐nearest neighbor, and neural networks) statistical classification methods for differentiating these species by their kek mating call. We identified 480 kek notes of each species and quantitatively characterized them with five standardized acoustic parameters. Overall, nonparametric classification methods outperformed parametric classification methods for species differentiation (nonparametric tools were between 57% and 81% accurate, parametric tools were between 57% and 60% accurate). Of the nine classification methods, Random Forest was the most accurate and precise, resulting in 81.1% correct classification of kek notes to species. This suggests that the mating calls of these sister species are likely difficult for human observers to tell apart. However, it also implies that appropriate statistical tools may allow reasonable species‐level classification accuracy of recorded calls and provide an alternative to species classification where other capture‐ or genotype‐based survey techniques are not possible.