Animal Migration Patterns Research Articles

Classifying animal migration patterns using small-shuffle surrogate and PCA evaluating short-term trends

Classifying animal migration patterns using small-shuffle surrogate and PCA evaluating short-term trends

Weather conditions at different spatial and temporal scales influence avian post‐breeding migration patterns on route

AbstractMigration plays a central role in many ecological and evolutionary processes. Global patterns of climatic variation are having a profound influence upon animal migration patterns. Even though regular counts of bird migrations at bottleneck sites can certainly offer insights into how natural populations of different species at different scales are responding to changes in weather conditions, they have not yet been widely used. By analysing a time series of regular counts, collected during autumn, of 126 species migrating during the daytime through one of the most important migratory bottlenecks in Western Europe, we found that an increase in temperature at the regional scale, as well as a decrease in precipitation level during the breeding period, may result not only in a decrease in the migration rate during autumn but also in a delay in the timing of fall migration. Furthermore, adverse weather conditions at the local scale interrupted bird migration through the bottleneck until favourable weather conditions returned. Importantly, temporal variation in the number of migratory birds followed a nonlinear pattern, something which might be partially due to the idiosyncratic responses of migratory species with different life‐history characteristics to changes in weather conditions. Our results highlight that migration is a nonlinear, multiscale and multi‐faceted process, suggesting that it will be difficult to predict the responses of idiosyncratic migratory species to the unpredictable effects of climate change.

Meta-Learning Based Classification for Moving Object Trajectories in Mobile IoT

The proliferation and ubiquity of GPS-enabled mobile Internet of Things (IoT) devices (e.g., drones and unmanned robotic devices) across many disciplines has generated substantial interest in the analysis and mining of trajectory data for enhancing public services such as air pollution monitoring and road safety. Among all trajectory analysis techniques in mobile IoT, classifying moving device trajectories is a fundamental research problem due to its importance for numerous important mobile IoT applications such as travel demand analysis and animal migration patterns. However, existing classification methods for moving object trajectories either are dynamic programming problems (such as similarity-based methods with dynamic time wrapping or Fréchet distance) with a quadratic time complexity in all cases, or need abundant labeled samples to training classification model, thus limit the scalability of these methods for given resource-constrained mobile IoT devices. In this study, we propose a deep learning-based approach for trajectory classification in mobile IoT with linear time complexity by firstly encoding a trajectory as a vector via deep representation learning, then utilizing a meta-learning based approach to learn the ability of classifying trajectory with few annotated samples. Experiments on a massive trajectory dataset show that the proposed approach outperforms state-of-the-art baselines consistently and significantly.

Air-Ice-Ocean Interactions and the Delay of Autumn Freeze-Up in the Western Arctic Ocean

Arctic sea ice is becoming a more seasonal phenomenon as a direct result of global warming. Across the Arctic, the refreezing of the ocean surface each autumn now occurs a full month later than it did just 40 years ago. In the western Arctic (Canada Basin), the delay is related to an increase in the seasonal heat stored in surface waters; cooling to the freezing point requires more heat loss to the atmosphere in autumn. In the marginal ice zone, the cooling and freezing process is mediated by ocean mixing and by the presence of remnant sea ice, which may precondition the ocean surface for refreezing. The delay in refreezing has many impacts, including increased open ocean exposure to autumn storms, additional wave energy incident to Arctic coasts, shifts in animal migration patterns, and extension of the time window for transit by commercial ships along the Northern Sea Route. This article reviews the observed trends in the western Arctic and the processes responsible for these trends, and provides brief in situ observations from the Beaufort Sea that illustrate some of these processes.

Animal Migration Patterns Extraction Based on Atrous-Gated CNN Deep Learning Model

Weather radar data can capture large-scale bird migration information, helping solve a series of migratory ecological problems. However, extracting and identifying bird information from weather radar data remains one of the challenges of radar aeroecology. In recent years, deep learning was applied to the field of radar data processing and proved to be an effective strategy. This paper describes a deep learning method for extracting biological target echoes from weather radar images. This model uses a two-stream CNN (Atrous-Gated CNN) architecture to generate fine-scale predictions by combining the key modules such as squeeze-and-excitation (SE), and atrous spatial pyramid pooling (ASPP). The SE block can enhance the attention on the feature map, while ASPP block can expand the receptive field, helping the network understand the global shape information. The experiments show that in the typical historical data of China next generation weather radar (CINRAD), the precision of the network in identifying biological targets reaches up to 99.6%. Our network can cope with complex weather conditions, realizing long-term and automated monitoring of weather radar data to extract biological target information and provide feasible technical support for bird migration research.

Telemetry reveals migratory drivers and disparate space use across seasons and age‐groups in American horseshoe crabs

AbstractIdentifying mechanisms that underpin animal migration patterns and examining variability in space use within populations is crucial for understanding population dynamics and management implications. In this study, we quantified the migration rates, seasonal changes in migratory connectivity, and residency across population demographics (age and sex) to understand the proximate cues of migration timing in American horseshoe crabs (Limulus polyphemus). Juvenile (n = 25) and adult (n = 70) horseshoe crabs were tracked with acoustic telemetry techniques for a 3‐yr period in Moriches Bay, NY. Connectivity metrics and residency probability were quantified through spatial network analysis and empirically derived Markov Chain models (EDMC), respectively. The migratory probability of adult horseshoe crabs between Moriches Bay and the Atlantic Ocean was estimated to be 41.0% (95% CI: 34.0–59.8); in contrast, only 8% (95% CI: 1.2–31.6) of juveniles migrated into the ocean. Migration timing was influenced by the interaction of photoperiod and temperature, revealing seasonal differences in migration timing and a 50% narrower range of photoperiod and temperature over which fall migrations occurred compared to spring. Sex‐specific differences in space use and connectivity within each season were largely absent; however, centralized habitats were important for maintaining connectivity across all seasons. EDMC results revealed that when standardized to the number of horseshoe crab detections on each receiver, the centrally located habitats in Moriches Bay and Inlet accounted for >50% of the total relative residency probability within most seasons, indicating these areas may be preferred by adult horseshoe crabs. Ontogenetic differences in maximum spatial extent, space use, and connectivity were observed in the bay, as juveniles exhibited lower linkages between locations (n = 4) relative to adults (n = 13) during the same temporal period. Our work highlights the application of novel quantitative approaches for addressing the movement dynamics of horseshoe crabs that can be readily applied to other taxa in the context of wildlife conservation.

‘Energising’ Nature: Rethinking the Sustainability of Renewable Energy Usage vis-à-vis Wildlife Conservation

Today the world is facing an extraordinary environmental crisis. The devastating impact of anthropogenic climate change has resulted in the rapid decline of global biodiversity. From habitat degradation to unprecedented temperature changes, the unpredictability surrounding this crisis demands incentive-based approaches to biodiversity conservation and the sustainable use of resources. In recent years, the switch to renewable energy sources has received considerable global attention. Renewable energy sources such as wind, hydro, and solar energy can effectively replace fast-depleting fossil fuels, thereby drastically reducing carbon emissions, improving air quality, and enhancing human health. Although the feasibility of producing renewable energy can vary across demographics and between the seasons, with the help of advanced technology, these sources can be utilised all year round to help cut down energy production costs in the long term. Nevertheless, as recent studies caution, a transition to renewable energy production can crucially affect weather patterns and existing habitat characteristics, resulting in critical biodiversity loss. These changes include altering species habitats, animal migration patterns, damaging croplands, and increasing human-wildlife conflict. Therefore, climate change problems, wildlife conservation, and energy production cannot be addressed in isolation. This article briefly discusses some aspects of this complex relationship between human-wildlife conflict and renewable energy production and argues in favour of a community commons-based approach to address some emerging problems.

Using satellite-derived estimates of plant phenological rhythms to predict sage-grouse nesting chronology.

The “green wave” hypothesis posits that during spring consumers track spatial gradients in emergent vegetation and associated foraging opportunities. This idea has largely been invoked to explain animal migration patterns, yet the general phenomenon underlies trends in vertebrate reproductive chronology as well. We evaluated the utility of this hypothesis for predicting spatial variation in nest initiation of greater sage‐grouse (Centrocerus urophasianus), a species of conservation concern in western North America. We used the Normalized Difference Vegetation Index (NDVI) to map the green wave across elevation and then compiled dates and locations of >450 sage‐grouse nests from 20 study sites (2000–2014) to model nest initiation as a function of the start of the growing season (SOS), defined here as the maximum daily rate of increase in NDVI. Individual sites were drawn from three ecoregions, distributed over 4.5° latitude, and spanning 2,300 m in elevation, which captured the climatic, edaphic, and floristic diversity of sagebrush ecosystems in the southern half of current sage‐grouse range. As predicted, SOS displayed a significant, positive relationship with elevation, occurring 1.3 days later for each 100 m increase in elevation. In turn, sage‐grouse nest initiation followed SOS by 22 ± 10 days (r2 = .57), with hatch dates falling on or just prior to the peak of the growing season. By timing nesting to the green wave, sage‐grouse chicks hatched when the abundance of protein‐rich invertebrate biomass is hypothesized to be nearing a seasonal high. This adaptation likely represents a strategy for maximizing reproductive success in the arid, variable environments that define sagebrush ecosystems. Given projected changes in climate and land use, these results can be used to predict periods of relative sensitivity to habitat disturbance for sage‐grouse. Moreover, the near real‐time availability of satellite imagery offers a heretofore underutilized means of mapping the green wave, planning habitat restoration, and monitoring range conditions.

Advancing interpretation of stable isotope assignment maps: comparing and summarizing origins of known-provenance migratory bats

AbstractProbability-of-origin maps deduced from stable isotope data are important for inferring broad-scale patterns of animal migration, but few resources and tools for interpreting and validating these maps exist. For example, quantitative tools for comparing multiple probability-of-origin maps do not exist, and many existing approaches for geographic assignment of individuals have not been validated or compared with respect to precision and accuracy. To address these challenges, we created and analyzed probability-of-origin maps using stable hydrogen isotope values from known-origin individuals of three species of migratory bat. We used a metric of spatial overlap to group individuals by areas of origin without a priori knowledge of such regions. The metric of spatial similarity allowed for quantitative comparison of geographic origins and grouping of individuals with similar origins. We then compared four approaches for inferring origins (cumulative-sum, odds-ratio, quantile-only, and quantile-simulation) across a range of thresholds and probable minimum distance traveled. The accuracy of geographic origins and minimum distance traveled varied across species at most threshold values for most approaches. The cumulative-sum and quantile-simulation approaches had generally higher precision at a given level of accuracy than the odds-ratio and quantile-only approaches, and many threshold values were associated with a relatively high degree (> 300 km) of variation in minimum distance traveled. Overall, these results reinforce the importance of validating assignment techniques with known-origin individuals when possible. We present the tools discussed as part of an R package, ‘isocat’ (“Isotope Origin Clustering and Assignment Tools”).

Deep-learning-based extraction of the animal migration patterns from weather radar images

Continental coverage and year-round operation of the weather radar networks provide an unprecedented opportunity for studying large-scale airborne migration. The broad and local-scale airborne information collected by these infrastructures can answer many ecological questions. However, extracting and interpreting the biological information from such massive weather radar data remains an intractable problem. Recently, many big-data problems have been solved using the deep learning technology. In this study, the biological information in the weather radar data is identified using the advanced deep learning method. The proposed method consists of two main parts, i.e., a rendering and casting procedure and an image segmentation procedure based on a convolutional neural network. The biological data are automatically extracted by rendering and mapping, image segmentation, and result masking. By analyzing the typical radar data from single and multiple stations, we partly reveal the intensity and speed of the migration pattern. We present the first feasibility study of the extraction of local and large-scale biological phenomena from the Chinese weather radar network data.

Broad‐scale patterns of the Afro‐Palaearctic landbird migration

AbstractAimKnowledge of broad‐scale biogeographical patterns of animal migration is important for understanding ecological drivers of migratory behaviours. Here, we present a flyway‐scale assessment of the spatial structure and seasonal dynamics of the Afro‐Palaearctic bird migration system and explore how phenology of the environment guides long‐distance migration.LocationEurope and Africa.Time period2009–2017.Major taxa studiedBirds.MethodsWe compiled an individual‐based dataset comprising 23 passerine and near‐passerine species of 55 European breeding populations, in which a total of 564 individuals were tracked during migration between Europe and sub‐Saharan Africa. In addition, we used remotely sensed primary productivity data (the normalized difference vegetation index) to estimate the timing of vegetation green‐up in spring and senescence in autumn across Europe. First, we described how individual breeding and non‐breeding sites and the migratory flyways link geographically. Second, we examined how the timing of migration along the two major Afro‐Palaearctic flyways is tuned with vegetation phenology at the breeding sites.ResultsWe found the longitudes of individual breeding and non‐breeding sites to be related in a strongly positive manner, whereas the latitudes of breeding and non‐breeding sites were related negatively. In autumn, migration commenced ahead of vegetation senescence, and the timing of migration was 5–7 days earlier along the Western flyway compared with the Eastern flyway. In spring, the time of arrival at breeding sites was c. 1.5 days later for each degree northwards and 6–7 days later along the Eastern compared with the Western flyway, reflecting the later spring green‐up at higher latitudes and more eastern longitudes.Main conclusionsMigration of the Afro‐Palaearctic landbirds follows a longitudinally parallel leapfrog migration pattern, whereby migrants track vegetation green‐up in spring but depart before vegetation senescence in autumn. The degree of continentality along migration routes and at the breeding sites of the birds influences the timing of migration on a broad scale.

Ecological Consequences of Animal Migration: Prey Partial Migration Affects Predator Ecology and Prey Communities

Patterns of animal migration and the ecological forces that shape them have been studied for centuries. Yet ecological impacts caused by the migration, such as altered predator–prey interactions and effects on community structure, remain poorly understood. This is to a large extent due to the scarcity of naturally replicated migration systems with negative controls, that is, ecosystems without migration. In this study, we tested whether partial migration of certain species within the overall prey community affects foraging ecology of top predators and thereby alters energy pathways in food webs. We carried out the study in independent replicated freshwater lake systems, four with and four without opportunity for prey migration. Specifically, we compared predator foraging mode in lakes where cyprinid prey fish perform seasonal partial migrations into connected streams with lakes lacking migratory opportunities for prey fish. We found clear seasonal bottom-up effects of prey migration on predators, including changes in size structure and total biomass of ingested prey, size-specific changes in littoral versus pelagic origin of diet, and a higher degree of feast-and-famine for predators in systems with migratory prey. Our analyses further showed that partially migratory prey species constitute a larger part of the prey community in systems that allow migration. Hence, prey migrations have important implications for predator foraging ecology and may cause seasonal shifts in the importance of their supporting energy pathways. We suggest that such bottom-up effects of partial migration may be a widespread phenomenon both in aquatic and in terrestrial ecosystems.

Background and the use of isoscapes in the Brazilian context: essential tool for isotope data interpretation and natural resource management

Spatial patterns of stable isotope ratios can be represented in spatial models called isoscapes, and have been widely used to track biogeochemical processes in natural and anthropic systems. Isoscapes have the potential to improve isotope dissemination and interpretation of spatial patterns, increase scientific results appropriation by non-specialists and improve natural resource management. However, the isoscape approach has not commonly been used in studies performed in the Brazilian context. Isoscapes with oxygen, hydrogen, nitrogen and carbon stable isotopes contribute in areas such as animal migration, forensics, hydrology, and studies on population, community and ecosystem level, among others. Here, we show the well-known global use and applications of isoscapes in different studies worldwide as a background to point out the potential for more Brazilian researchers to employ this approach in their studies, taking advantage of existing methods and filling spatial and methodological gaps. The incorporation of isoscapes may broaden the understanding of mechanisms and processes of major biogeochemical cycles in Brazil, assist in solving crimes, track illicit drug origins, help to detect wild animal trafficking, and increase Brazilian knowledge about the hydrological cycle and animal migration patterns in the Neotropics.

Dark side of climate change: species‐specific responses and first indications of disruption in spring altitudinal migration in myotis bats

AbstractIn the Rocky Mountain region of North America, climate change is occurring at an accelerated rate and its effects are already changing population and community organization. Although some data have been gathered on changes in latitudinal migration patterns of animals, almost nothing is known about altitudinal migrations and climate change. Myotis bats of the Rocky Mountains provide a good model for understanding these patterns because they undergo significant seasonal altitudinal movements between high‐ and low‐elevation. In order to test if climate change is affecting spring down‐slope migrations of myotis species, I compared May and June capture data gathered over the last 21 years from 31 survey sites located between 1650 m a.s.l. and 2250 m a.s.l. on the eastern slopes of the Rocky Mountains, Colorado. Although three of the Myotis species maintained stable or slightly increasing capture numbers, indicating typical down‐slope spring migrations, two species showed significant declines in spring captures at lower elevations. When climate data for May and June were tested against capture data, the apparent causative factors for these declines differed between species. Declines in the capture of fringed myotis did not closely track annual patterns of mean June temperatures across years. Instead a steady decline occurred regardless of yearly variation in temperatures. However, declining captures of long‐legged myotis showed clear synchrony with variations in mean June temperatures wherein more captures occurred in years having cooler temperatures, and notably fewer captures in years having warmer June temperatures. In addition, zero captures of long‐legged myotis occurred in five of the last six years when mean June temperatures have shown an average increase in 1.8°C over previous years. These data indicate species‐specific responses to climate warming for bats in the Colorado Rocky Mountains and that loss of spring down‐slope migrations from hibernacula may be how some species mitigate climate warming effects.

The cost of migration: spoonbills suffer higher mortality during trans-Saharan spring migrations only.

Explanations for the wide variety of seasonal migration patterns of animals all carry the assumption that migration is costly and that this cost increases with migration distance. Although in some studies, the relationships between migration distance and breeding success or annual survival are established, none has investigated whether mortality during the actual migration increases with migration distance. Here, we compared seasonal survival between Eurasian spoonbills (Platalea leucorodia leucorodia) that breed in The Netherlands and migrate different distances (ca 1000, 2000 and 4500 km) to winter in France, Iberia and Mauritania, respectively. On the basis of resightings of individually marked birds throughout the year between 2005 and 2012, we show that summer, autumn and winter survival were very high and independent of migration distance, whereas mortality during spring migration was much higher (18%) for the birds that wintered in Mauritania, compared with those flying only as far as France (5%) or Iberia (6%). As such, this study is the first to show empirical evidence for increased mortality during some long migrations, likely driven by the presence of a physical barrier (the Sahara desert) in combination with suboptimal fuelling and unfavourable weather conditions en route.

Migration confers survival benefits against avian predators for partially migratory freshwater fish

The importance of predation risk in shaping patterns of animal migration is not well studied, mostly owing to difficulties in accurately quantifying predation risk for migratory versus resident individuals. Here, we present data from an extensive field study, which shows that migration in a freshwater fish (roach, Rutilus rutilus) that commonly migrates from lakes to streams during winter confers a significant survival benefit with respect to bird (cormorant, Phalacrocorax carbo spp.) predation. We tagged over 2000 individual fish in two Scandinavian lakes over 4 years and monitored migratory behaviour using passive telemetry. Next, we calculated the predation vulnerability of fish with differing migration strategies, by recovering data from passive integrated transponder tags of fish eaten by cormorants at communal roosts close to the lakes. We show that fish can reduce their predation risk from cormorants by migrating into streams, and that probability of being preyed upon by cormorants is positively related to the time individuals spend in the lake during winter. Our data add to the growing body of evidence that highlights the importance of predation for migratory dynamics, and, to our knowledge, is one of the first studies to directly quantify a predator avoidance benefit to migrants in the field.

Departure directions, migratory timing and non-breeding distribution of the Red-backed Shrike Lanius collurio: do ring re-encounters and light-based geolocator data tell the same story?

This study explores differences and consistencies between ring re-encounter and light-based geolocator data from Red-backed Shrike when used for studying three aspects of bird migration: departure direction and its relationship with longitude and latitude, non-breeding distribution, and timing of migration. Departure directions were consistent between the two methods. They indicate a funnel-shaped migration with individuals from southwest Europe taking a detour via the eastern Mediterranean rather than migrating via Gibraltar. This indicates that an original migration route has been retained after colonisation of the breeding range. Non-breeding distributions differed substantially between birds ringed and re-encountered and birds tracked by geolocators. This difference may be due to spatio-temporal heterogeneity in ring re-encounter probability and/or due to the two samples of birds belonging to different populations. The monthly average ring re-encounter location moved later southward during autumn and earlier northward during spring migration than the geolocator positions, because of an over-representation of re-encounters in the north. The results emphasise the importance of combining different sources of data when analysing migration patterns of animals that are difficult to track.

Global Weirding in British Columbia: Climate Change and the Habitat of Terrestrial Vertebrates

The authors summarize the distribution of terrestrial vertebrates of British Columbia across major habitat types and present empirical and projected effects of global weirding within two particularly vulnerable habitats—alpine and wetland. Global weirding embraces all phenomena associated with climate change: increases in average temperatures, heat waves, cold spells, floods, droughts, hurricanes, blizzards, plant and animal die-offs, population explosions, new animal migration patterns, plus dramatic regional differences. Current data suggest that many alpine species will be lost to changes in habitat wrought by climate, particularly increases in average temperatures. For many wetlands, particularly in the central and southern interior of the province, the basic issue is simple—the incoming water is decreasing and the outgoing water (evaporation) is increasing. The authors illustrate three approaches to projecting trends in wetland habitat, elaborating on the “drying index” approach, in which they have most confidence. For wetland species, they say management will struggle with the concept of a real-world triage—allocating conservation efforts where they are most likely to succeed and have the most benefit. They conclude that several conservation approaches for wetland species will face the difficulty of allocating water between needs of these species and of humans.

Tracking human travel using stable oxygen and hydrogen isotope analyses of hair and urine

The stable oxygen and hydrogen isotope compositions of organic samples are increasingly being used to investigate patterns of animal migration. Relatively few studies have applied these techniques to modern humans, despite a variety of potential forensic applications. We analyzed drinking water and food at two geographic locations, East Greenbush, New York (USA) and Fairbanks, Alaska (USA), with different delta(18)O and deltaD values for precipitation and tap water. Foods varied widely in measured delta(18)O and deltaD values, but not systematically by purchase location. We measured delta(18)O and deltaD values of scalp hair from five residents at each location. We used a mixing model to establish the proportion of oxygen and hydrogen in head hair derived from drinking water ( approximately 27% and approximately 36%, respectively). Finally, we analyzed the delta(18)O and deltaD values of facial hair and urine from a subject who traveled from Fairbanks to East Greenbush, on to the UK and back to Fairbanks. Urine delta(18)O and deltaD values responded immediately and strongly to travel-related change in drinking water, and were well described by a single-pool turnover model. Beard hair delta(18)O values tracked changes in urine delta(18)O closely, and oscillated between the values for the resident populations in both locations. In contrast, beard hair deltaD values did not track changes in urine deltaD as well, and retained a signature of the traveler's permanent residence. Our findings show that the delta(18)O and deltaD values of urine and facial hair (specifically delta(18)O) can provide a record of the geographical movements of humans.

Smithsonian climate change exhibits

Two new museum exhibits, “Arctic: A Friend Acting Strangely” and “Atmosphere: Change is in the Air” opened 15 April at the Smithsonian Institution's National Museum of Natural History in Washington, D.C., in partnership with the U.S. National Oceanic and Atmospheric Administration, NASA, and the U.S. National Science Foundation.In “Arctic: A Friend Acting Strangely,” anecdotes from indigenous polar people reveal how climate changes have affected life within the last 50 years. For example, as permafrost melts and sea ice shrinks, plant distributions and animal migration patterns are changing, severely affecting culture.