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publicMay 2023View details →

Use of amino acid isotope analysis to investigate capital versus income breeding strategies in migratory avian species

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publicNov 2021View details →

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

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publicJul 2021View details →

Far Eastern Curlew and Whimbrel prefer flying low: wind support and good visibility appear only secondary factors in determining migratory flight altitude

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publicJul 2021View details →

Leveraging genomics to understand threats to migratory birds

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Fig. 3 in Movement and longitudinal distribution of a migratory fish (Salminus brasiliensis) in a small reservoir in southern Brazil

Fig. 3. Observed values of individual net displacement for Salminus brasiliensis in the Monjolinho reservoir. Each dot represents a displacement event; more than one record from the same individual may appear in the plot. a) The individual moved a large distance in a very short time, b) the individual moved a small distance in a short time, c) the individual position moved at least 20 km within 60 days and d) the individual may have moved only a small distance in a 60-day period. Note: net displacement based on large time intervals (e.g., events c and d) ignore multiple movements that may have occurred within the time interval (see main text).

Fig. 4 in Movement and longitudinal distribution of a migratory fish (Salminus brasiliensis) in a small reservoir in southern Brazil

Fig. 4. Net displacement of dourados (Salminus brasiliensis) in the Monjolinho reservoir. The numbers above the plots represent the number of individuals. The letters above the plots represent differences or similarities according to Tukey's test, which was performed after a linear mixed effect model (F= 23.57). Circles represent outlier values; the heavy horizontal line crossing the box is the median; the bottom and top of the box are the lower and upper quartiles, respectively; and the whiskers are the minimum and maximum values.

Fig. 1 in Movement and longitudinal distribution of a migratory fish (Salminus brasiliensis) in a small reservoir in southern Brazil

Fig. 1. Map of the study area in the Uruguay river basin located in southern Brazil. Stars = cities; triangles = natural barriers; squares = positions of fixed radio telemetry stations; line with dottes = duct that takes water from the Passo Fundo power house into the Monjolinho reservoir. The confluences of the Passo Fundo and Erechim rivers and of the Passo Fundo and Uruguay rivers have been flooded by the Monjolinho and Foz do Chapecó reservoirs. Dark gray represents the area that was monitored in this study.

Fig. 5. a in Movement and longitudinal distribution of a migratory fish (Salminus brasiliensis) in a small reservoir in southern Brazil

Fig. 5. a. Distance traveled by dourados (Salminus brasiliensis) from the dam in the study area. Numbers above the plots are the number of individuals. Letters above the plots represent differences or similarities according to Tukey's test, which was performed after a linear mixed effect model (F = 16.5; p<0.0001). Circles represent outlier values; the heavy horizontal line crossing the box is the median; the bottom and top of the box are the lower and upper quartiles, respectively; and the whiskers are the minimum and maximum values. b. Inflow (m³/s) and water temperature (°C) in the Monjolinho reservoir during the study period (January to December 2012). c. Rainfall (mm) in the study area, showing measurements taken between January and December 2012 and historical rainfall patterns (1961-1990).

Fig. 6 in Movement and longitudinal distribution of a migratory fish (Salminus brasiliensis) in a small reservoir in southern Brazil

Fig. 6. Line density results showing the movement patterns of dourados (Salminus brasiliensis) in the Monjolinho reservoir. Summer = January to March; Autumn = April to June; Winter = July to September; and Spring = October to December.

opencc-by-4.0Dec 2018View details →

Fig. 3 in Plasticity in the shape and growth pattern of asteriscus otolith of black prochilodus Prochilodus nigricans (Teleostei: Characiformes: Prochilodontidae) freshwater Neotropical migratory fish

Fig. 3. Cluster analysis based on the euclidean distances of the wavelet functions by shape analysis of asteriscus otoliths Prochilodus nigricans between rivers. S (Solimões); J (Japurá) and N (Negro).

opencc-by-4.0Dec 2018View details →

Fig. 2 in Plasticity in the shape and growth pattern of asteriscus otolith of black prochilodus Prochilodus nigricans (Teleostei: Characiformes: Prochilodontidae) freshwater Neotropical migratory fish

Fig. 2. Canonical variate analysis of the first 5 PC compo- nents and fish length data of the Prochilodus nigricans for all localities, with 95% confidence. Solimões (blue); Japurá (red) and Negro (green).

Fig. 6 in Age and growth of the Amazonian migratory catfish Brachyplatystoma rousseauxii in the Madeira River basin before the construction of dams

Fig. 6. Length-at age distribution and von Bertalanffy growth function (solid lines) of Brachyplatystoma rousseauxii: a. females (N = 142); b. males (N = 95); and c. females, males and unsexed individuals pooled (N = 497) in the lower / middle (Brazil) and in the upper (Bolivia and Peru) Madeira River basin. In order to improve modelling for females (a) and males (b), unsexed individuals <60 cm (black dots) were also used.

Fig. 2 in Age and growth of the Amazonian migratory catfish Brachyplatystoma rousseauxii in the Madeira River basin before the construction of dams

Fig. 2. Transverse thin sections of Brachyplatystoma rousseauxii's otoliths showing: a. one ring; b. and c. two rings; d. eight rings; e. ten rings; and f. twenty rings. The yellow line marks the rings.

Fig. 7.a. Relationship between fish standard length and otolith radius for Brachyplatystoma rousseauxii below 80 in Age and growth of the Amazonian migratory catfish Brachyplatystoma rousseauxii in the Madeira River basin before the construction of dams

Fig. 7.a. Relationship between fish standard length and otolith radius for Brachyplatystoma rousseauxii below 80 cm (black circles, black line: y = 0.031x + 0.209, r² = 0.805, P <0.001) and above 80 cm (white triangles, broken line: y = 0.034x – 0.223, r² = 0.328, P <0.001); and b. relationship between fish age and otolith radius for B. rousseauxii below 80 cm (black circles, black line: y = 0.887ln(x) + 1.567, r² = 0.879, P <0.001) and above 80 cm (white triangles, broken line: y = 0.209ln(x) + 2.055, r² = 0.822, P <0.001), both in Madeira River basin.

Fig. 1 in Age and growth of the Amazonian migratory catfish Brachyplatystoma rousseauxii in the Madeira River basin before the construction of dams

Fig. 1. Map of the sampling sites of Brachyplatystoma rousseauxii in the Madeira River basin. 1- Puerto Maldonado, 2- Rurrenabaque, 3-Puerto Villarroel, 4-Surpresa, 5- Cachuela Esperanza, 6-Iata/Vila Murtinho, 7-São Sebastião, 8-São Carlos, 9- Calama and 10- Humaitá.

Fig. 3 in Age and growth of the Amazonian migratory catfish Brachyplatystoma rousseauxii in the Madeira River basin before the construction of dams

Fig. 3. Mean and standard deviation (SD) of each growth ring radius in otoliths of Brachyplatystoma rousseauxii from the Madeira River basin.

opencc-zeroMay 2020View details →

Data from: Developing a Stopover-CORT hypothesis: corticosterone predicts body composition and refueling rate in Gray Catbirds during migratory stopover

Migratory flight is energetically challenging, requiring alternating phases of fuel catabolism and fuel accumulation, accompanied by dramatic changes in body composition and behavior. Baseline corticosterone (CORT; the primary glucocorticoid in birds) is thought to underlie transitions between fuel catabolism during flight, fuel deposition during stopover, and the initiation of migratory flight. However, studies of CORT on stopover physiology and behavior remain disparate efforts, lacking the cohesion of a general hypothesis. Here we develop a Stopover-CORT hypothesis formalizing the relationships among CORT, body condition, and refueling rate in migratory birds. First we expect body mass to increase with triglycerides (TRIG) as birds refuel. Second, based on a synthesis of previous literature, we predict a U-shaped CORT curve over the course of stopover, postulating that elevated CORT at arrival is reactive, responding to poor body condition, while CORT elevation before departure is preparative, driving changes in behavior and body condition. We tested these predictions in Gray Catbirds (Dumetella carolinensis) following a trans-Gulf flight during spring migration. We found baseline CORT was negatively correlated with body condition and TRIG, corresponding with our predictions for arriving and refueling—but not departing—birds. It is possible catbirds undergo regional habitat translocations rather than complete the entire stopover phase at our study site. We propose the Stopover-CORT hypothesis as a useful predictive framework for future studies of the mechanistic basis of stopover physiology. By studying the regulation of stopover refueling and departure, we may better understand physiological limitations to overall migration rate and improve assessments of habitat quality for refueling birds.

opencc-zeroAug 2020View details →

Data from: To migrate or not: drivers of over-summering in a long-distance migratory shorebird

The phenomenon of over-summering in southern non-breeding areas by boreal-breeding birds is particularly prevalent among shorebirds. Despite its frequency, it is understudied compared with most other aspects of shorebird ecology. Our aim was to expand knowledge of this subject through a study of Red Knots Calidris canutus rufa over-summering at a site in Argentina during the austral winter. We measured the proportion of one-year-old and adult over-summerers and evaluated the roles of flight-feather condition and physiological status (through leukocite profile, physiological stress index, and presence of blood parasites) as triggers for over-summering. We also explore sex-ratio, the evolution of body mass and extent of breeding plumage within each age-class. Over-summerers were 57% yearlings and 43% adults, 46% females and 54% males. Almost all yearlings exhibited incomplete molt of primary feathers and some were in active primary molt. This suggests that the condition of flight-feathers and the timing of molt are likely to be important factors selecting for deferred migration during the first year of life. Other factors, not associated with flight-feather molt, seem to trigger over-summering in adults, which had completed flight feather molt but had low fat loads and/or incomplete alternate plumage. We found no evidence of a weakened immune system, high loads of blood parasites, or high stress levels that can explain this poor migratory conditioning and therefore over-summering. Our data indicates that our adult age-class comprises both young individuals postponing first breeding until they are at least two years old and sexually mature individuals with prior reproductive experience skipping a breeding opportunity. Breeding propensity and age at first breeding are both poorly known, but key demographic parameters that determine population growth. This study suggests that potentially they can be estimated from mark-recapture at non-breeding areas and this warrants further study.

opencc-zeroAug 2020View details →

Data (D2H values) from: Generational shift in the migratory common noctule bat: first-year males lead the way to hibernacula at higher latitudes

Supplementary_Table_3_D2H values noctules_Kravchenko et al The dataset contains stable hydrogen values (D2H) (column "sample_value") in fur keratin of 413 common noctule bats (Nyctalus noctula) from Kharkiv (Ukraine). Samples were collected in winter colonies over 12 years (2004-2015). Each row is one individual. Column "sample_ID" is an ID of an individual. Columns "lat" and "long" are coordinates of Kharkiv city (sampling site). Column "sex" is sex of individuals. Column "age1" shows the age of individuals: ad - adult individuals, sad -subadult individuals (younger than one year). Column "Status" assign origin status of individuals to either 0 - regional or 1 - migratory. Column "Year3" represents the year of sample collection in a format of time in the past from the first year of the collection (-11) till the last year of the collection (0). Column "Year" is the year of sample collection.