Reference genome of the black rail, Laterallus jamaicensis

The black rail, Laterallus jamaicensis, is one of the most secretive and poorly understood birds in the Americas. Two of its five subspecies breed in North America: the Eastern black rail (L. j. jamaicensis), found primarily in the southern and mid-Atlantic states, and the California black rail (L. j. coturniculus), inhabiting California and Arizona, are recognized across the highly disjunct distribution. Population declines, due primarily to wetland loss and degradation, have resulted in conservation status listings for both subspecies. To help advance understanding of the phylogeography, biology, and ecology of this elusive species, we report the first reference genome assembly for the black rail, produced as part of the California Conservation Genomics Project (CCGP). We produced a de novo genome assembly using Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology with an estimated sequencing error rate of 0.182%. The assembly consists of 964 scaffolds spanning 1.39 Gb, with a contig N50 of 7.4 Mb, scaffold N50 of 21.4 Mb, largest contig of 44.8 Mb, and largest scaffold of 101.2 Mb. The assembly has a high BUSCO completeness score of 96.8% and represents the first genome assembly available for the genus Laterallus. This genome assembly can help resolve questions about the complex evolutionary history of rails, assess black rail vagility and population connectivity, estimate effective population sizes, and evaluate the potential of rails for adaptive evolution in the face of growing threats from climate change, habitat loss and fragmentation, and disease.

Stability of patch-turnover relationships under equilibrium and nonequilibrium metapopulation dynamics driven by biogeography

Two controversial tenets of metapopulation biology are whether patch quality and the surrounding matrix are more important to turnover (colonisation and extinction) than biogeography (patch area and isolation) and whether factors governing turnover during equilibrium also dominate nonequilibrium dynamics. We tested both tenets using 18 years of surveys for two secretive wetland birds, black and Virginia rails, during (1) a period of equilibrium with stable occupancy and (2) after drought and arrival of West Nile Virus (WNV), which resulted in WNV infections in rails, increased extinction and decreased colonisation probabilities modified by WNV, nonequilibrium dynamics for both species and occupancy decline for black rails. Area (primarily) and isolation (secondarily) drove turnover during both stable and unstable metapopulation dynamics, greatly exceeding the effects of patch quality and matrix conditions. Moreover, slopes between turnover and patch characteristics changed little between equilibrium and nonequilibrium, confirming the overriding influences of biogeographic factors on turnover.

A need for speed in Bayesian population models: a practical guide to marginalizing and recovering discrete latent states

Bayesian population models can be exceedingly slow due, in part, to the choice to simulate discrete latent states. Here, we discuss an alternative approach to discrete latent states, marginalization, that forms the basis of maximum likelihood population models and is much faster. Our manuscript has two goals: (1) to introduce readers unfamiliar with marginalization to the concept and provide worked examples and (2) to address topics associated with marginalization that have not been previously synthesized and are relevant to both Bayesian and maximum likelihood models. We begin by explaining marginalization using a Cormack-Jolly-Seber model. Next, we apply marginalization to multistate capture-recapture, community occupancy, and integrated population models and briefly discuss random effects, priors, and pseudo-R² . Then, we focus on recovery of discrete latent states, defining different types of conditional probabilities and showing how quantities such as population abundance or species richness can be estimated in marginalized code. Last, we show that occupancy and site-abundance models with auto-covariates can be fit with marginalized code with minimal impact on parameter estimates. Marginalized code was anywhere from five to >1,000 times faster than discrete code and differences in inferences were minimal. Discrete latent states and fully conditional approaches provide the best estimates of conditional probabilities for a given site or individual. However, estimates for parameters and derived quantities such as species richness and abundance are minimally affected by marginalization. In the case of abundance, marginalized code is both quicker and has lower bias than an N-augmentation approach. Understanding how marginalization works shrinks the divide between Bayesian and maximum likelihood approaches to population models. Some models that have only been presented in a Bayesian framework can easily be fit in maximum likelihood. On the other hand, factors such as informative priors, random effects, or pseudo-R² values may motivate a Bayesian approach in some applications. An understanding of marginalization allows users to minimize the speed that is sacrificed when switching from a maximum likelihood approach. Widespread application of marginalization in Bayesian population models will facilitate more thorough simulation studies, comparisons of alternative model structures, and faster learning.

The rescue effect and inference from isolation-extinction relationships

The rescue effect in metapopulations hypothesises that less isolated patches are unlikely to go extinct because recolonisation may occur between breeding seasons ('recolonisation rescue'), or immigrants may sufficiently bolster population size to prevent extinction altogether ('demographic rescue'). These mechanisms have rarely been demonstrated directly, and most evidence of the rescue effect is from relationships between isolation and extinction. We determined the frequency of recolonisation rescue for metapopulations of black rails (Laterallus jamaicensis) and Virginia rails (Rallus limicola) from occupancy surveys conducted during and between breeding seasons, and assessed the reliability of inferences about the occurrence of rescue drawn from isolation-extinction relationships, including autologistic isolation measures that corrected for unsurveyed patches and imperfect detection. Recolonisation rescue occurred at expected rates, but was elevated during periods of disturbance that resulted in non-equilibrium metapopulation dynamics. Inferences from extinction-isolation relationships were unreliable, particularly for autologistic measures and for the more vagile Virginia rail.