Setting conservation priorities for migratory networks under uncertainty

Conserving migratory species requires protecting connected habitat along the pathways they travel. Despite recent improvements in tracking animal movements, migratory connectivity remains poorly resolved at a population level for the vast majority of species, thus conservation prioritization is hampered. To address this data limitation, we developed a novel approach to spatial prioritization based on a model of potential connectivity derived from empirical data on species abundance and distance traveled between sites during migration. We applied the approach to migratory shorebirds of the East Asian‐Australasian Flyway. Conservation strategies that prioritized sites based on connectivity and abundance metrics together maintained larger populations of birds than strategies that prioritized sites based only on abundance metrics. The conservation value of a site therefore depended on both its capacity to support migratory animals and its position within the migratory pathway; the loss of crucial sites led to partial or total population collapse. We suggest that conservation approaches that prioritize sites supporting large populations of migrants should, where possible, also include data on the spatial arrangement of sites.     

Monarch butterfly migration and parasite transmission in eastern North America

Seasonal migration occurs in many animal systems and is likely to influence interactions between animals and their parasites. Here, we focus on monarch butterflies (Danaus plexippus) and a protozoan parasite (Ophryocystis elektroscirrha) to investigate how host migration affects infectious disease processes. Previous work showed that parasite prevalence was lower among migratory than nonmigratory monarch populations; two explanations for this pattern are that (1) migration allows animals to periodically escape contaminated habitats (i.e., migratory escape), and (2) long-distance migration weeds out infected animals (i.e., migratory culling). We combined field-sampling and analysis of citizen science data to examine spatiotemporal trends of parasite prevalence and evaluate evidence for these two mechanisms. Analysis of within-breeding-season variation in eastern North America showed that parasite prevalence increased from early to late in the breeding season, consistent with the hypothesis of migratory escape. Prevalence was also positively related to monarch breeding activity, as indexed by larval density. Among adult monarchs captured at different points along the east coast fall migratory flyway, parasite prevalence declined as monarchs progressed southward, consistent with the hypothesis of migratory culling. Parasite prevalence was also lower among monarchs sampled at two overwintering sites in Mexico than among monarchs sampled during the summer breeding period. Collectively, these results indicate that seasonal migration can affect parasite transmission in wild animal populations, with implications for predicting disease risks for species with threatened migrations.     

Connectivity of wood thrush breeding,wintering, and migration sites based on range‐wide tracking

Many migratory animals are experiencing rapid population declines, but migration data with the geographic scope and resolution to quantify the complex network of movements between breeding and nonbreeding regions are often lacking. Determining the most frequently used migration routes and nonbreeding regions for a species is critical for understanding population dynamics and making effective conservation decisions. We tracked the migration of individual Wood Thrushes (Hylocichla mustelina) (n = 102) from across their range with light‐level geolocators and, for the first time, quantified migration routes and wintering regions for distinct breeding populations. We identified regional and species‐level migratory connectivity networks for this declining songbird by combining our tracking results with range‐wide breeding abundance estimates and forest cover data. More than 50% of the species occupied the eastern wintering range (Honduras to Costa Rica), a region that includes only one‐third of all wintering habitat and that is undergoing intensive deforestation. We estimated that half of all Wood Thrushes in North America migrate south through Florida in fall, whereas in spring approximately 73% funnel northward through a narrow span along the central U.S. Gulf Coast (88–93°W). Identifying migratory networks is a critical step for conservation of songbirds and we demonstrated with Wood Thrushes how it can highlight conservation hotspots for regional populations and species as a whole. Conectividad de Sitios de Reproducción, Invierno y Migración del Zorzal con Base en Rastreo de Cobertura Amplia     

Integration of distance, direction and habitat into a predictive migratory movement model for blue-winged teal (Anas discors)

Historically, the migration of birds has been poorly understood in comparison to other life stages during the annual cycle. The goal of our research is to present a novel approach to predict the migratory movement of birds. Using a blue-winged teal case study, our process incorporates not only constraints on habitat (temperature, precipitation, elevation, and depth to water table), but also approximates the likely bearing and distance traveled from a starting location. The method allows for movement predictions to be made from unsampled areas across large spatial scales. We used USGS’ Bird Banding Laboratory database as the source of banding and recovery locations. We used recovery locations from banding sites with multiple within-30-day recoveries were used to build core maximum entropy models. Because the core models encompass information regarding likely habitat, distance, and bearing, we used core models to project (or forecast) probability of movement from starting locations that lacked sufficient data for independent predictions. The final model for an unsampled area was based on an inverse-distance weighted averaged prediction from the three nearest core models. To illustrate this approach, three unsampled locations were selected to probabilistically predict where migratory blue-wing teals would stopover. These locations, despite having little or none data, are assumed to have populations. For the blue-winged teal case study, 104 suitable locations were identified to generate core models. These locations ranged from 20 to 228 within-30-day recoveries, and all core models had AUC scores greater than 0.80. We can infer based on model performance assessment, that our novel approach to predicting migratory movement is well-grounded and provides a reasonable approximation of migratory movement.     

A little movement orientated to the geomagnetic field makes a big difference in strong flows

Whilst a range of animals have been shown to respond behaviourally to components of the Earth’s magnetic field, evidence of the value of this sensory perception for small animals advected by strong flows (wind/ocean currents) is equivocal. We added geomagnetic directional swimming behaviour for North Atlantic loggerhead turtle hatchlings (Caretta caretta) into a high-resolution (1/4°) global general circulation ocean model to simulate 2,925-year-long hatchling trajectories comprising 355,875 locations. A little directional swimming (1–3 h per day) had a major impact on trajectories; simulated hatchlings travelled further south into warmer water. As a result, thermal elevation of hatchling metabolic rates was estimated to be between 63.3 and 114.5% after 220 days. We show that even small animals in strong flows can benefit from geomagnetic orientation and thus the potential implications of directional swimming for other taxa may be broad.     

Applying Metapopulation Theory to Conservation of Migratory Birds

Abstract: Metapopulation theory has proven useful for understanding the population structure and dynamics of many species of conservation concern. The metapopulation concept has been applied almost exclusively to nonmigratory species, however, for which subpopulation demographic independence—a requirement for a classically defined metapopulation—is explicitly related to geographic distribution and dispersal probabilities. Defining the degree of demographic independence among subpopulations of migratory animals, and thus the applicability of metapopulation theory as a conceptual framework for understanding population dynamics, is much more difficult. Unlike nonmigratory species, subpopulations of migratory animals cannot be defined as synonymous with geographic areas. Groups of migratory birds that are geographically separate at one part of the annual cycle may occur together at others, but co-occurrence in time and space does not preclude the demographic independence of subpopulations. I suggest that metapopulation theory can be applied to migratory species but that understanding the degree of subpopulation independence may require information about both spatial distribution throughout the annual cycle and behavioral mechanisms that may lead to subpopulation demographic independence. The key for applying metapopulation theory to migratory animals lies in identifying demographically independent subpopulations, even as they move during the annual cycle and potentially co-occur with other subpopulations. Using examples of migratory bird species, I demonstrate that spatial and temporal modes of subpopulation independence can interact with behavioral mechanisms to create demographically independent subpopulations, including cases in which subpopulations are not spatially distinct in some parts of the annual cycle.     

Optimism and Challenge for Science‐Based Conservation of Migratory Species in and out of U.S. National Parks

Public agencies sometimes seek outside guidance when capacity to achieve their mission is limited. Through a cooperative agreement and collaborations with the U.S. National Park Service (NPS), we developed recommendations for a conservation program for migratory species. Although NPS manages ～36 million hectares of land and water in 401 units, there is no centralized program to conserve wild animals reliant on NPS units that also migrate hundreds to thousands of kilometers beyond parks. Migrations are imperiled by habitat destruction, unsustainable harvest, climate change, and other impediments. A successful program to counter these challenges requires public support, national and international outreach, and flourishing migrant populations. We recommended two initial steps. First, in the short term, launch or build on a suite of projects for high‐profile migratory species that can serve as proof to demonstrate the centrality of NPS units to conservation at different scales. Second, over the longer term, build new capacity to conserve migratory species. Capacity building will entail increasing the limited knowledge among park staff about how and where species or populations migrate, conditions that enable migration, and identifying species’ needs and resolving them both within and beyond parks. Building capacity will also require ensuring that park superintendents and staff at all levels support conservation beyond statutory borders. Until additional diverse stakeholders and a broader American public realize what can be lost and do more to protect it and engage more with land management agencies to implement actions that facilitate conservation, long distance migrations are increasingly likely to become phenomena of the past. Optimismo y Retos para la Conservación Científicamente Basada de Especies Migratorias Dentro y Fuera de Parques Nacionales de E.U.A.     

Residency and depth movements of a coastal group of Atlantic cod (Gadus morhua L.)

Atlantic cod stocks are subdivided into geographically and biologically discrete populations; some being locally resident, others migratory. The reasons for the variation in migration pattern and the consequences it may have for population structuring is poorly understood. We studied a group of cod from the coastal waters of the Shetland Isles in the northern North Sea. During the spawning season, electronic tags that record depth and temperature over time were implanted into 133 individuals and the fish released within a few kilometres of where they were captured. Thirty-nine cod have been recaptured up to 608 days later, throughout the year and, in all but two cases, within 15 km of their release site. Geolocation methods based on temperature and bathymetry also suggested that the cod had a limited home range, remaining resident year-round in coastal waters. The cod were deeper during the winter and moved to shallower water in late spring and summer. They showed diel, fortnightly and monthly cycles in depth movement that varied much within and between individuals over the season. Residency and the individual variability in vertical movement may reflect a combination of locally complex depth strata, variable seabed substrate and the wide range of seasonally available prey resources.     

Satellite tracking reveals a dichotomy in migration strategies among juvenile loggerhead turtles in the Northwest Atlantic

Few data are available on the movements and behavior of immature Atlantic loggerhead sea turtles (Caretta caretta) from their seasonal neritic foraging grounds within the western north Atlantic. These waters provide developmental habitat for loggerheads originating from several western Atlantic nesting stocks. We examined the long-term movements of 23 immature loggerheads (16 wild-caught and seven headstart turtles) characterizing their seasonal distribution, habitat use, site fidelity, and the oceanographic conditions encountered during their migrations. We identified two movement strategies: (1) a seasonal shelf-constrained north–south migratory pattern; and (2) a year-round oceanic dispersal strategy where turtles travel in the Gulf Stream to the North Atlantic and their northern dispersal is limited by the 10–15°C isotherm. When sea surface temperatures dropped below 20°C, neritic turtles began a migration south of Cape Hatteras, North Carolina (USA) where they established fidelity to the waters between North Carolina’s Outer Banks and the western edge of the Gulf Stream along outer continental shelf. Two turtles traveled as far south as Florida. Several turtles returned to their seasonal foraging grounds during subsequent summers. Northern movements were associated with both increased sea surface temperature (>21°C) and increased primary productivity. Our results indicate strong seasonal and interannual philopatry to the waters of Virginia (summer foraging habitat) and North Carolina (winter habitat). We suggest that the waters of Virginia and North Carolina provide important seasonal habitat and serve as a seasonal migratory pathway for immature loggerhead sea turtles. North Carolina’s Cape Hatteras acts as a seasonal “migratory bottleneck” for this species; special management consideration should be given to this region. Six turtles spent time farther from the continental shelf. Three entered the Gulf Stream near Cape Hatteras, traveling in the current to the northwest Atlantic. Two of these turtles remained within an oceanic habitat from 1 to 3 years and were associated with mesoscale features and frontal systems. The ability of large benthic subadults to resume an oceanic lifestyle for extended periods indicates plasticity in habitat use and migratory strategies. Therefore, traditional life history models for loggerhead sea turtles should be reevaluated.     

A Bayesian mixture model for missing data in marine mammal growth analysis

Much of what is known about bottle nose dolphin (Tursiops truncatus) anatomy and physiology is based on necropsies from stranding events. Measurements of total body length, total body mass, and age are used to estimate growth. It is more feasible to retrieve and transport smaller animals for total body mass measurement than larger animals, introducing a systematic bias in sampling. Adverse weather events, volunteer availability, and other unforeseen circumstances also contribute to incomplete measurement. We have developed a Bayesian mixture model to describe growth in detected stranded animals using data from both those that are fully measured and those not fully measured. Our approach uses a shared random effect to link the missingness mechanism (i.e. full/partial measurement) to distinct growth curves in the fully and partially measured populations, thereby enabling drawing of strength for estimation. We use simulation to compare our model to complete case analysis and two common multiple imputation methods according to model mean square error. Results indicate that our mixture model provides better fit both when the two populations are present and when they are not. The feasibility and utility of our new method is demonstrated by application to South Carolina strandings data.     

A general approach to the analysis of habitat selection

The investigation of animal habitat selection aims at the detection of selective usage of habitat types and the identification of covariates influencing their selection. The results not only allow for a better understanding of the habitat selection process but are also intended to help improve the conservation of animals. Usually, habitat selection by larger animals is assessed by radio-tracking or visual observation studies, where the chosen habitat is determined for some animals at a set of specific points in time. Hence the resulting data often have the following structure: a categorical variable indicating the habitat type selected by an animal at a specific point in time is repeatedly observed and will be explained by covariates. These may either describe properties of the habitat types currently available and/or properties of the animal. In this paper, we present a general approach to the analysis of such data in a categorical regression setup. The proposed model generalizes and improves upon several of the approaches previously discussed in the literature. In particular, it accounts for changing habitat availability due to the movement of animals within the observation area. It incorporates both habitat- and animal-specific covariates, and includes individual-specific random effects to account for correlations introduced by the repeated measurements on single animals. Furthermore, the assumption that the effects are linear can be dropped by including the effects in nonparametric manner based on a penalized spline approach. The methodology is implemented in a freely available software package. We demonstrate the general applicability and the potential of the proposed approach in two case studies: The analysis of a songbird community in South-America and a study on brown bears in Central Europe.     

Persistence of Different-sized Populations: An Empirical Assessment of Rapid Extinctions in Bighorn Sheep

Abstract: Theory and simulation models suggest that small populations are more susceptible to extinction than large populations, yet assessment of this idea has been hampered by lack of an empirical base. I address the problem by asking how long different-sized populations persist and present demographic and weather data spanning up to 70 years for 122 bighorn sheep ( Ovis canadensis ) populations in southwestern North America Analyses reveal that: (1) 100 percent of the populations with fewer than 50 individuals went extinct within 50 years; (2) populations with greater than 100 individuals persisted for up to 70 years; and (3) the rapid loss of populations was not likely to be caused by food shortages, severe weather, predation, or interspecific competition These data suggest that population size is a marker of persistence trajectories and they indicate that local extinction cannot be overcome because 50 individuals, even in the short term, are not a minimum viable population size for bighorn sheep.     

Fitting probability models to population dynamics data

Methods for modeling population dynamics in probability using the generalized point process approach are developed. The life history of these populations is such that seasonal reproduction occurs during a short time. Several models are developed and analyzed. Data about two species: colonial spiders (Stegodyphus dumicola) and a migratory bird (wood thrush, Hylocichla mustelina) are used to estimate model parameters with appropriate log maximum likelihood functions. For the spiders, the model is fitted to provide evolutionary feasible colony size based on maximum likelihood estimates of fecundity and survival data. For the migratory bird species, a maximum likelihood estimates are derived for the fecundity and survival rates of young and adult birds and immigration rate. The presented approach allows computation of quantities of interest such as probability of extinction and average time to extinction.     

Modeling and inference of animal movement using artificial neural networks

Movement of animals in relation to objects in their environment is important in many areas of ecology and wildlife conservation. Tools for analysis of movement data, however, still remain rather limited. In previous work, we developed nonlinear regression models for movement in relation to a single landscape feature. Here we greatly expand these previous models by using artificial neural networks. The new models add substantial flexibility and capabilities, including the ability to incorporate multiple factors and covariates. We devise a likelihood-based model fitting procedure that utilizes genetic algorithms and demonstrate the approach with movement data for red diamond rattlesnakes. The proposed methodology can be useful for global positioning system tracking data that are becoming more common in studies of animal movement behavior.     

Song sharing in two populations of song sparrows (Melospiza melodia)

Sharing song types with immediate neighbors is widespread in birds with song repertoires, and sharing songs may confer a selective advantage in some cases. Levels of song sharing vary between different geographical populations of several bird species, and ecological differences often correlate with differences in singing behavior; in particular, males in migratory subspecies often share fewer songs than males in resident subspecies. The song sparrow (Melospiza melodia) appears to fit this pattern: resident song sparrows in western North America generally share 20–40% of their repertoire (of about eight songs) with each neighbor, while migratory subspecies from eastern North America often share 10% or less. We compared song sharing in two populations within a single subspecies of song sparrow (M. m. morphna) in Washington State. These populations, separated by only 120 km, nonetheless differ in migratory tendencies and several other ecological and life history variables. We recorded complete song repertoires from 11 male song sparrows in a high-elevation, migrating population at Gold Creek in west-central Washington, and compared them to two samples (n = 15 and n = 36) from a coastal, resident population at Discovery Park, Seattle, Washington. Despite major differences in habitat, population density, and migratory tendencies, song sharing among Gold Creek males was as high as that among Discovery Park males. In both populations, sharing was highest between immediate neighbors, and declined with distance. We conclude that at the within-subspecies level, neither migration nor population density affect song sharing in song sparrows, a song repertoire species. Received: 26 November 1998 / Received in revised form: 1 May 1999 / Accepted: 29 May 1999     

Population structure of short-beaked common dolphins (<Emphasis Type="Italic">Delphinus delphis</Emphasis>) in the North Atlantic Ocean as revealed by mitochondrial and nuclear genetic markers

The understanding of population structure and gene flow of marine pelagic species is paramount to monitoring, management and conservation studies. Such studies are often hampered by the potentially high dispersal behavior of the species, the lack of obvious geographical barriers in the marine environment and the scarce sample availability. Short-beaked common dolphins (Delphinus delphis) are widespread in coastal and open-ocean habitats of the North Atlantic Ocean, nevertheless population structure and migratory patterns are poorly understood. Furthermore, concern has been raised about the status of the species because large numbers of dolphins have been taken incidentally in several fisheries throughout the North Atlantic in the past decades. In the present study, a large number of individual samples were obtained from seasonal and spatial aggregations of common dolphins from western (wNA) and eastern North Atlantic (eNA) regions, mostly using opportunistic sampling (i.e. from incidental entanglement in fishing gear or beach-cast carcasses). Genetic variability was investigated using nuclear (14 microsatellite loci) and mitochondrial (360 bp of the control region) genetic markers. Levels of genetic diversity were relatively high in all sampled areas and no evidence of recent reduction of effective population size (i.e. bottleneck) was detected at the nuclear loci. Significant population structure was detected between the two main regions (wNA and eNA) where it appeared to be more pronounced at mitochondrial (F _ST = 0.018, P < 0.001) than nuclear markers (F _ST = 0.005, P < 0.05), indicating the presence of at least two genetically distinct populations of common dolphins in the North Atlantic Ocean. In contrast, no significant genetic structure was detected between temporal aggregations of dolphins from within the same region, suggesting possible seasonal movement patterns at a regional scale. The observed levels of genetic differentiation between classes of markers are discussed here as a possible consequence of migratory patterns or recent population subdivision. An erratum to this article can be found at     

Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: observed trends and contributing factors

The Cropland Data Layers (CDL) are high-resolution geo-referenced data products made available by the U.S. Department of Agriculture. However, the CDL lacks in its ability to be employed as a tool to identify the impact of the gradually evolving drivers of land use change, e.g., climate change, due to its limited historical depth. We implement a robust, phenology-based satellite image classification algorithm to identify historical cropland allocation in eastern South Dakota and North Dakota predating the initial CDL by 13 and 22 years, respectively. Five major land covers, i.e., corn, soybeans, wheat, alfalfa and grass (including native grass, hay and pasture) are identified using archived Landsat-5 surface reflectance data, while achieving CDL-like accuracy. The long-term rate of grassland loss during 1985–2011 is found to be significantly lower (26,781 hectares or 1.5% annually) relative to the near-term rate of grassland loss during 2006-’11 (84,545 hectares or 5.2% annually). We find similar discrepancy in regional corn expansion rates. Our value-added raster data provide opportunities for improved identification of land use drivers, whereas relying solely on the CDL’s restricted historical extent may lead to biased land use change estimates and misguide policy.     

Use of Land Facets to Plan for Climate Change: Conserving the Arenas,Not the Actors

Abstract: Even under the most optimistic scenarios, during the next century human‐caused climate change will threaten many wild populations and species. The most useful conservation response is to enlarge and link protected areas to support range shifts by plants and animals. To prioritize land for reserves and linkages, some scientists attempt to chain together four highly uncertain models (emission scenarios, global air–ocean circulation, regional circulation, and biotic response). This approach has high risk of error propagation and compounding and produces outputs at a coarser scale than conservation decisions. Instead, we advocate identifying land facets—recurring landscape units with uniform topographic and soil attributes—and designing reserves and linkages for diversity and interspersion of these units. This coarse‐filter approach would conserve the arenas of biological activity, rather than the temporary occupants of those arenas. Integrative, context‐sensitive variables, such as insolation and topographic wetness, are useful for defining land facets. Classification procedures such as k‐means or fuzzy clustering are a good way to define land facets because they can analyze millions of pixels and are insensitive to case order. In regions lacking useful soil maps, river systems or riparian plants can indicate important facets. Conservation planners should set higher representation targets for rare and distinctive facets. High interspersion of land facets can promote ecological processes, evolutionary interaction, and range shift. Relevant studies suggest land‐facet diversity is a good surrogate for today's biodiversity, but fails to conserve some species. To minimize such failures, a reserve design based on land facets should complement, rather than replace, other approaches. Designs based on land facets are not biased toward data‐rich areas and can be applied where no maps of land cover exist.     

A Graph-Theory Framework for Evaluating Landscape Connectivity and Conservation Planning

Abstract:  Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A).^. We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.     

Range-wide effects of breeding- and nonbreeding-season climate on the abundance of a Neotropical migrant songbird

Geographic variation in the population dynamics of a species can result from regional variability in climate and how it affects reproduction and survival. Identifying such effects for migratory birds requires the integration of population models with knowledge of migratory connectivity between breeding and nonbreeding areas. We used Bayesian hierarchical models with 26 years of Breeding Bird Survey data (1982-2007) to investigate the impacts of breeding- and nonbreeding-season climate on abundance of American Redstarts (Setophaga ruticilla) across the species range. We focused on 15 populations defined by Bird Conservation Regions, and we included variation across routes and observers as well as temporal trends and climate effects. American Redstart populations that breed in eastern North America showed increased abundance following winters with higher plant productivity in the Caribbean where they are expected to overwinter. In contrast, western breeding populations showed little response to conditions in their expected wintering areas in west Mexico, perhaps reflecting lower migratory connectivity or differential effects of winter rainfall on individuals across the species range. Unlike the case with winter climate, we found few effects of temperature prior to arrival in spring (March-April) or during the nesting period (May-June) on abundance the following year. Eight populations showed significant changes in abundance, with the steepest declines in the Atlantic Northern Forest (-3.4%/yr) and the greatest increases in the Prairie Hardwood Transition (4%/yr). This study emphasizes how the effects of climate on populations of migratory birds are context dependent and can vary depending on geographic location and the period of the annual cycle. Such knowledge is essential for predicting regional variation in how populations of a species might vary in their response to climate change.