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Many animals derive benefits from roosting communally but may also face increased risk of infectious disease transmission. In spite of recent high-profile disease outbreaks in roosting animals of conservation and public health concern, we currently lack general theory for how attributes of roosting animals and their pathogens influence pathogen spread among roosts and overall population impacts on roosting species. Here we develop a model to explore how roost size and host site fidelity influence the time for a pathogen to escape from its initial roost, overall infection prevalence, and host population size, for pathogens with density- or frequency-dependent transmission and varying virulence. We find that pathogens spread rapidly to all roosts when animals are distributed among a small number of large roosts, and that roost size more strongly influences spread rate for density-dependent than frequency-dependent transmitted pathogens. However, roosting animals that exhibit high site fidelity and distribute among a large number of small roosts are buffered from population-level impacts of pathogens of both transmission modes. We discuss our results in the context of anthropogenic change that is altering aspects of roosting behavior relevant to emerging pathogen spread.

Light‐level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. Here, we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses – annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns – describing good practices and common pitfalls for each step. We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method and introduce key features of the newest open‐source analysis tools. We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open‐source analysis tools with step‐by‐step instructions and code and details our recommendations for interpreting, reporting and archiving.

Animal movement, whether for foraging, mate-seeking, predator avoidance, dispersal, or migration, is a fundamental aspect of ecology that shapes spatial abundance distributions, genetic compositions, and dynamics of populations. A variety of movement models have been used for predicting the effects of natural or human-caused landscape changes, invading species, or other disturbances on local ecology. Here we introduce the flow network—a general modeling framework for population dynamics and movement in a metapopulation representing a network of habitat sites (nodes). Based on the principles of physical transport phenomena such as fluid flow through pipes (Pouiselle’s Law) and analogously, the flow of electric current across a circuit (Ohm’s Law), the flow network provides a novel way of modeling movement, where flow rates are functions of relative node pressures and the resistance to movement between them. Flow networks offer the flexibility of incorporating abiotic and biotic conditions that affect either pressures, resistance, or both. To illustrate an application of the flow network, we present a theoretical invasion scenario. We consider the effects of spatial structure on the speed of invasion by varying the spatial regularity of node arrangement. In the context of invasion, we model management actions targeting nodes or edges, and consider the effects on speed of invasion, node occupation, and total abundance. The flow network approach offers the flexibility to incorporate spatial heterogeneity in both rates of flow and site pressures and offers an intuitive approach to connecting population dynamics and landscape features to model movement.

The mechanism by which new deltaic wetlands form is a complex suite of biological and physical processes that can modify one another. Understanding these processes and their interactions is imperative to successful coastal restoration. This study investigated the relationship between belowground plant biomass and sediment cohesion. We hypothesized that greater root densities increase shear strength, variably across plant communities, and that these communities are associated with distinct inundation regimes. A significant relationship was found between belowground biomass and surface shear strength when accounting for sediment grain size, water content, and organic matter content. Sites dominated by native graminoids or woody species had significantly higher shear strengths than unvegetated areas. However, sites dominated by Phragmites australis or forbs did not differ significantly in shear strength from the unvegetated sites. Sites dominated by Phragmites australis were also subject to significantly higher inundation rates during the previous water year than any other vegetation type. These results suggest that vegetation community differences lead to differences in shear strength that result in locally differential erosion rates, in turn modifying future geomorphology, hydrology, sedimentation, and vegetation distribution. This feedback implies that certain vegetation communities in wetland restoration projects could not only impart immediate erosion resistance to the substrate, but affect the long-term potential for land creation.

The decreasing average pH of the world's oceans, called ocean acidification, can be detrimental to marine organisms. Decreased pH causes dissolution of calcium carbonate shells, as well as changes to metabolism, behavior, growth, survival, and early development of many species; however, the impacts of lower pH on crustaceans have not been widely researched. This study investigated the effects of lower pH on the growth and survival of larval blue crabs Callinectes sapidus through laboratory experiments. Blue crab larvae live at the surface of the open ocean where the pH is decreasing with ocean acidification. A pH of 7.8 was used to mimic the average surface ocean pH predicted to be attained by 2,100 by the Intergovernmental Panel on Climate Change and was compared with a control pH of 8.2, the current average surface ocean pH. Larvae raised at the lower pH were 10% smaller and there was a 23% reduction in survival. Larval populations within an aquarium with a lower pH were more likely to exhibit ...

The 2010 Deepwater Horizon oil spill occurred during peak spawning season for many Gulf of Mexico fish and invertebrates. Early life stages of important fishery species were at risk to encounter crude oil. In this study, we investigated the effect of crude oil exposure on two life stages of the blue crab (Callinectes sapidus). We tested the effects of oil exposure on the survival and growth of larval (pelagic) and juvenile (estuarine) blue crabs as well as the effects of oil on the molt frequency of juveniles. Larval crabs exposed to crude oil showed no discernable growth or mortality differences when compared to non-exposed controls. Juvenile crabs exposed to oil also showed no differences in size but exhibited increased intermolt duration (time between molts). Our study suggests that different life-stages may respond differently when exposed to crude oil and that oil exposure negatively affects growth rate of juvenile blue crabs.

During migration, animals may experience high rates of mortality, but costs of migration could also be manifested through non-lethal carry-over effects that influence individual success in subsequent periods of the annual cycle. Using tracking data collected from light-level geolocators, we estimated total spring migration distance (from the last wintering sites to breeding sites) of tree swallows (Tachycineta bicolor) within three major North American flyways. Using path analysis, we then assessed direct and indirect effects of spring migration distance on reproductive performance of individuals of both sexes. When these data were standardized by flyway, females fledged 1.3 fewer young for every 1,017 km they traveled, whereas there was no effect of migration distance on reproductive success in males. In comparison, when these data were standardized across all individuals and not by flyway, longer migrations were associated with 0.74 more young fledged for every 1,017 km traveled by females and 0.26 more young fledged for every 1,186 km migrated by males. Our results suggest that migration distance carries over to negatively influence female reproductive success within flyways but the overall positive effect of migration distance across flyways likely reflects broader life-history differences that occur among breeding populations across the tree swallow range.

Migratory species can be visualized as occupying spatial networks with nodes representing regions and the populations that seasonally occupy them and links between seasonal subpopulations representing migratory connectivity. Connectivity is often regarded as a static property of a migratory network and visualized to evaluate the vulnerability of migratory populations to changes in specific regions. However, if the network itself is a dynamical system, its connectivity can be an output of the system that may be changed by perturbations to the network. I constructed a regulated, tripartite network population model with breeding, winter, and migration route nodes that also includes natal dispersal and in which connectivity goes to a dynamical equilibrium. I investigated how natal dispersal as well as the strength of density-dependent population regulation during breeding and non-breeding seasons affects connectivity patterns and the responses of the network population to simulated habitat loss. I found that when the population is primarily regulated by availability of habitat in only one season and natal dispersal was geographically constrained, connectivity patterns were unsymmetrical with weak (diffuse) connectivity from the non-regulating to regulating season and stronger connectivity in the other direction. Less-constrained natal dispersal always resulted in weak connectivity throughout. The overall magnitude of declines caused by habitat loss was determined by relative regulation and generally was not affected by natal dispersal although it was possible, with high natal dispersal, for loss of low-quality nodes in a non-regulating season to cause increases in network population size since the low-quality nodes were acting as an ecological trap. Although we expect that localness (i.e., the extent to which declines resulting from local winter habitat loss was concentrated in a small breeding area vs. spread across a larger area) should be predicted by connectivity, localness was in fact hugely variable and affected by both density-dependence and natal dispersal and generally quite difficult to predict from the connectivity pattern. In summary, the complexity of the system meant that visualization of a network by itself, without knowledge of the underlying processes causing connectivity patterns, often does not provide a good indication of the vulnerability of the network or individual node populations to habitat loss.

There have been an increasing number of observations of itinerancy in migratory songbirds, where individuals move among 2 or more widely separated areas during the “stationary” nonbreeding season. Knowledge of such movements and an understanding of what drives them are important for predicting how migratory populations will respond to environmental change. In this study, we investigated nonbreeding movements of the Tree Swallow (Tachycineta bicolor), an aerial insectivore that breeds across North America and spends the nonbreeding season around the Gulf of Mexico, Florida, Mexico, Central America, and the Caribbean. With year-round tracking data obtained from 133 light-level geolocators deployed at 12 breeding sites ranging from Alaska to Nova Scotia to North Carolina, we show that 44% of individuals made at least one large-scale movement (range: 301–1,744 km) within the nonbreeding range. The frequency of itinerancy decreased with longitude, such that 75% of individuals made a movement in the western portion of the nonbreeding range compared to only 31% in the east. Using the Normalized Difference Vegetation Index (NDVI) as a proxy for resource availability, we found that when individuals did move, they were more likely to move from sites where resources were deteriorating faster (a more negative change in NDVI prior to departure) than their destination sites. There was also evidence that individuals moved to destination sites with higher NDVI and temperature in the autumn, but not in the winter. Our results suggest movements of Tree Swallows during the nonbreeding season are influenced by resource availability, but because not all individuals used multiple nonbreeding sites, the density of individuals at a site and the level of competition may have also been a factor influencing nonbreeding season movements.

Latitudinal differences in timing of breeding are well documented but how such differences carry over to influence timing of events in the annual cycle of migratory birds is not well understood. We examined geographical variation in timing of events throughout the year using light-level geolocator tracking data from 133 migratory tree swallows ( Tachycineta bicolor ) originating from 12 North American breeding populations. A swallow's breeding latitude influenced timing of breeding, which then carried over to affect breeding ground departure. This resulted in subsequent effects on the arrival and departure schedules at autumn stopover locations and timing of arrival at non-breeding locations. This ‘domino effect’ between timing events was no longer apparent by the time individuals departed for spring migration. Our range-wide analysis demonstrates the lasting impact breeding latitude can have on migration schedules but also highlights how such timing relationships can reset when individuals reside at non-breeding sites for extended periods of time.

Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.Un Modelo de Redes de Panorama Poblacional para la Priorización de la Conservación de un Ave Migratoria Resumen Los animales migratorios están pasando por una declinación mundial y se requieren esfuerzos coordinados de conservación para revertir las tendencias actuales. Diseñamos un modelo novedoso de redes de panorama poblacional que combina el análisis genético con el modelado de la distribución de especies y los datos demográficos para sobreponerse a los obstáculos con la conceptualización de los factores alternativos de riesgo en las especies migratorias durante su ciclo anual completo. Aplicamos nuestro método al chipe de corona negra (Cardellina pusilla), un ave migratoria neotropical que recorre largas distancias. A pesar de la falta de datos de algunas localidades de invernación, mostramos cómo pueden usarse los resultados para ayudar a priorizar la conservación de las áreas de reproducción y de invernación. Por ejemplo, mostramos que cuando se consideraron en conjunto los resultados del modelado genético, demográfico y de redes queda claro que las recomendaciones de conservación diferirán dependiendo de si el objetivo es preservar linajes genéticos únicos o el mayor número de aves por unidad de área. Más específicamente, si el objetivo es la conservación de los linajes genéticos, entonces los recursos limitados deberían enfocarse en preservar el hábitat en la Sierra de California, la Cuenca de las Rocallosas, la costa de California (lugares en donde se reproducen los tres linajes genéticos más vulnerables) o en el oeste de México (en donde dos de los tres linajes más vulnerables pasan el invierno). Alternativamente, si el objetivo es la conservación del mayor número de individuos por unidad de área, entonces el financiamiento limitado debería aplicarse en el noroeste del Pacífico o en América Central, en donde se estima que las densidades poblacionales son las más altas. En general, nuestros resultados demostraron la utilidad de adoptar un modelo de redes basadas en la genética para la integración de datos a lo largo de escalas geográficas amplias y para informar de mejor manera la toma de decisiones de conservación para los animales migratorios.世界范围内迁徙动物的数量正在减少, 需要采取协调一致的保护措施来扭转目前的趋势。我们设计了一种新的遗传谱网络模型, 通过整合遗传分析与物种分布模型和种群统计数据, 来应对确定迁移物种在完整年周期中面临风险因素的挑战。我们将这一方法应用于一种长距离迁徙的新热带候鸟--黑头威森莺 (Cardellina pusilla)。尽管缺乏部分越冬地点数据, 我们仍展示了如何利用这些结果来确定优先保护的繁殖地和越冬地。例如, 当同时考虑遗传、种群统计和网络模型结果时, 可以明显发现, 针对不同的保护目标--保护独特的遗传谱系或确保单位面积内得到保护的鸟类数量最大化, 所得出的保护建议也不同。具体来说, 如果以保护遗传谱系为目标, 那么有限的资源应集中在保护加利福尼亚山脉、落基山盆地和加利福尼亚海岸的栖息地, 这些地区是黑头威森莺最濒危的三支遗传谱系的繁殖地, 或者集中保护墨西哥西部, 那里是三支最濒危遗传谱系中两支谱系的越冬地。然而, 如果以保护单位面积最大数量的个体为目标, 那么有限的保护资金应投向太平洋西北部或中美洲, 那里的鸟类密度估计值最高。总的来说, 我们的研究结果表明, 采用基于遗传的网络模型来整合跨越广阔地理范围的多类型数据是非常有用的, 并将更好地为迁徙动物的保护决策提供信息。【翻译: 胡怡思; 审校: 聂永刚】.

Blue crabs, Callinectes sapidus Rathbun, 1896, are ubiquitous along the Atlantic and Gulf coasts of the United States. These organisms play an integral role in the ecosystems of the Gulf of Mexico (GOM), where not only are they a keystone species, but are also socioeconomically important. The survival of embryonated eggs is necessary to ensure adequate recruitment into the next generation. Because the 2010 Deepwater Horizon oil spill (DWH) occurred during the peak of the blue crab spawning season, the incident likely impacted blue crab embryos. In order to assess the effect of oil on embryonic growth and development, we collected embryonated eggs from seven different female blue crabs from the GOM throughout the spawning season and exposed them to an oil concentration of 500 ppb (the approximate concentration of oil at the surface water near the site of the Deepwater Horizon oil rig). Exposure to oil at this concentration caused a significantly larger proportion of prezoeae versus zoeae to hatch from embryonated eggs in experiments lasting longer than 4 days. Exposure to oil did not significantly affect overall survival or development rate. The prezoeal stage is a little-studied stage of blue crab development. Though it may or may not be a normal stage of development, this stage has been found to occur in suboptimal conditions and has lower survival than zoeal stages. The larger proportion of prezoeae following prolonged exposure to oil thus indicates that crude oil at concentrations likely to be experienced by crabs after the DWH spill negatively impacted the development of blue crab embryos. In addition to providing insight into the effects of the Deepwater Horizon oil spill, this study sheds light on embryonic development in blue crabs, a critical, but poorly investigated phase of this important species’ life cycle.

For seasonal migrants, non-breeding regions can play different roles in the ecology of their annual cycles: as stopover habitat, overwintering habitat, or as a combination in which some individuals stop-over and others over-winter. Such functional variations can lead to variation in occupancy dynamics and migration phenology to these different regions. In this study, we used data from archived Doppler weather surveillance radar to compare site-occupancy and movement dynamics of a migratory songbird (tree swallow Tachycineta bicolor) between two non-breeding areas: southeastern Louisiana and central peninsular Florida, USA. Specifically, in each area, we 1) quantified long-term (1996–2012) non-breeding season occupancy dynamics, 2) quantified variation in timing of autumn migration, and 3) tested which climate variables along their respective flyways were best correlated with variation in dates of arrival. Additionally, we cross-validated the dynamics from archived radar with data from eBird, a large-scale citizen science database that provides an independent measure of avian occupancy. We found strong and significant correlations between radar-estimated and eBird-estimated occupancy dynamics in both Louisiana and Florida. Long-term Louisiana occupancy dynamics conformed to our hypothesis that this region acts as a combined stopover and overwintering region whereas Florida occupancy dynamics were akin to a traditional winter region. Arrival to Louisiana during the study period was much earlier and took place over a much shorter arrival window than did arrival to Florida, which showed much more gradual arrival over the course of several months. At both sites, annual variation in mean arrival date was best explained by the amount of precipitation along the lower portions of their respective migration flyways.

It is well known that forest fragmentation reduces fecundity in several avian species, including wood thrush, Hylocichla mustelina, a migratory songbird that has been declining for several decades. However, I found that landscape-scale density in wood thrush was lower and population declines steeper in higher quality, less-fragmented landscapes (an inverse buffer effect) than in poor quality landscapes. These patterns suggest that wood thrush was not limited by availability of breeding habitat but that declines were primarily driven by non-breeding season events. A two-season model predicts that if this hypothesis is correct, breeding population trends will be negatively related to the strength of density dependence (b’) in the breeding season. To test this, a site-dependence model was used to construct fecundity-density curves and showed that landscape fragmentation affected the shape of density dependence. In good quality landscapes, the onset of strong density dependence was much more abrupt than in poorer quality landscapes and the realized strength of density dependence, b’, was lower in good quality landscapes. Population trends were negatively associated with b’, providing support for the non-breeding limitation hypothesis. The combination of the negative associations of trends with b’ and b’ with landscape quality explain the inverse buffer effect.

In their 2015 Current Biology paper, Streby et al. [1] reported that Golden-winged Warblers (Vermivora chrysoptera), which had just migrated to their breeding location in eastern Tennessee, performed a facultative and up to “>1,500 km roundtrip” to the Gulf of Mexico to avoid a severe tornadic storm. From light-level geolocator data, wherein geographical locations are estimated via the timing of sunrise and sunset, Streby et al. [1] concluded that the warblers had evacuated their breeding area approximately 24 hours before the storm and returned about five days later. The authors presented this finding as evidence that migratory birds avoid severe storms by temporarily moving long-distances. However, the tracking method employed by Streby et al. [1] is prone to considerable error and uncertainty. Here, we argue that this interpretation of the data oversteps the limits of the used tracking technique. By calculating the expected geographical error range for the tracked birds, we demonstrate that the hypothesized movements fell well within the geolocators’ inherent error range for this species and that such deviations in latitude occur frequently even if individuals remain stationary.

Many migratory species are in decline and understanding these declines is challenging because individuals occupy widely divergent and geographically distant habitats during a single year and therefore populations across the range are interconnected in complex ways. Network modeling has been used to show, theoretically, that shifts in migratory connectivity patterns can occur in response to habitat or climate changes and that habitat loss in one region can affect sub-populations in regions that are not directly connected. Here, we use a network model, parameterized by integrating long-term monitoring data with direct tracking of -100 individuals, to explain population trends in the rapidly declining Wood Thrush (Hylocichla mustelina) and to predict future trends. Our model suggests that species-level declines in Wood Thrush are driven primarily by tropical deforestation in Central America but that protection of breeding habitat in some regions is necessary to prevent shifts in migratory connectivity and to sustain populations in all breeding regions. The model illustrates how shifts in migratory connectivity may lead to unexpected population declines in key regions. We highlight current knowledge gaps that make modeling full life-cycle population demographics in migratory species challenging but also demonstrate that modeling can inform conservation while these gaps are being filled.

Despite benefits of using light-sensitive geolocators to track animal movements and describe patterns of migratory connectivity, concerns have been raised about negative effects of these devices, particularly in small species of aerial insectivore. Geolocators may act as handicaps that increase energetic expenditure, which could explain reported effects of geolocators on survival. We tested this ‘Energetic Expenditure Hypothesis’ in 12 populations of tree swallows ( Tachycineta bicolor ) and barn swallows ( Hirundo rustica ) from North America and Europe, using measurements of corticosterone from feathers (CORT f ) grown after deployment of geolocators as a measure of physiology relevant to energetics. Contrary to predictions, neither among- (both species) nor within-individual (tree swallows only) levels of CORT f differed with respect to instrumentation. Thus, to the extent that CORT f reflects energetic expenditure, geolocators apparently were not a strong handicap for birds that returned post-deployment. While this physiological evidence suggests that information about migration obtained from returning geolocator-equipped swallows is unbiased with regard to levels of stress, we cannot discount the possibility that corticosterone played a role in reported effects of geolocators on survival in birds, and suggest that future studies relate corticosterone to antecedent factors, such as reproductive history, and to downstream fitness costs.