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opencc-zeroSep 2022View details →

Forecasting climate change response in an alpine specialist songbird reveals the importance of considering novel climate

Species persistence in the face of climate change depends on both ecological and evolutionary factors. Here, we integrate ecological and whole-genome sequencing data to describe how populations of an alpine specialist, the Brown-capped Rosy-Finch (Leucosticte australis) may be impacted by climate change. We sampled 116 Brown-capped Rosy-Finches from 11 sampling locations across the breeding range. Using 429,442 genetic markers from whole-genome sequencing, we described population genetic structure and identified a subset of 436 genomic variants associated with environmental data. We modelled future climate change impacts on habitat suitability using ecological niche models (ENMs) and impacts on putative local adaptation using gradient forest models (a genetic-environment association analysis; GEA). We used the metric of niche margin index (NMI) to determine regions of forecasting uncertainty due to climate shifts to novel conditions. Population genetic structure was characterized by weak genetic differentiation, indicating potential ongoing gene flow among populations. Precipitation as snow had high importance for both habitat suitability and changes in genetic variation across the landscape. Comparing ENM and gradient forest models with future climate predicted suitable habitat contracting at high elevations and population allele frequencies across the breeding range needing to shift to keep pace with climate change. NMI revealed large portions of the breeding range shifting to novel climate conditions. Our study demonstrates that forecasting climate vulnerability from ecological and evolutionary factors reveals insights into population-level vulnerability to climate change that are obfuscated when either approach is considered independently. For the Brown-capped Rosy-Finch, our results suggest that persistence may depend on rapid adaptation to novel climate conditions in a contracted breeding range. Importantly, we demonstrate the need to characterize novel climate conditions that influence uncertainty in forecasting methods.

opencc-zeroMay 2024View details →

Data from: Anthropogenic nesting substrates increase parental fitness in a Neotropical songbird, the Pale-breasted Thrush (Turdus leucomelas)

The failure of breeding attempts is a major hindrance to bird reproduction, making nest site choice under strong selective pressure. Urbanization may offer lower risk of nest predation to certain bird species, but the impact of using anthropogenic structures as nesting sites on parental fitness is seldom studied. We studied the effect of anthropogenic substrates and brood parasitism by the Shiny Cowbird (Molothrus bonariensis) on the nest success of a Neotropical songbird, the Pale-breasted Thrush (Turdus leucomelas). We monitored 263 nesting attempts between 2017 and 2020 to estimate daily survival rate (DSR), which represents the probability of a given nest survive until the next day. DSR was modelled as a response variable in function of substrate type (plants as "natural" or human buildings as "artificial") and brood parasitism as fixed factors, using as covariates year, a linear and a quadratic seasonal trends. Additionally, we tested the effect of these same explanatory variables on the number of fledglings per nest using a generalized linear mixed-effects model. Most nests (78.7%) were placed in artificial substrates and apparent nest success (i.e. the percentage of nesting attempts that produced at least one thrush fledgling) was higher in artificial (50.2%) than in natural substrates (37.5%). DSR was higher for nests in artificial than in natural substrates regardless of cowbird parasitism, whereas the number of fledglings per nest was higher both in artificial substrates and for nests without cowbird parasitism. We highlight that nesting in buildings significantly increases parental fitness in Pale-breasted Thrushes, which may favor their settlement in cities and potentially drive the evolution of this breeding behavior in urban birds.

opencc-by-4.0Nov 2018View details →

Priority areas for boreal songbird conservation in Canada: Results for 128 scenarios based on Zonation conservation planning software

Priority areas for boreal songbird conservation in Canada: Results for 128 scenarios based on Zonation conservation planning software Published in: Stralberg, D., A. Camfield, M. Carlson, C. Lauzon, N. K. S. Barker, A. Westwood, and F. K. A. Schmiegelow. in press. Strategies for identifying priority areas for songbird conservation in Canada's boreal forest. Avian Conservation and Ecology. Scenarios:  ----------------- #    Name 1    Representation 2    Representation + Disturbance 3    Representation + BCR Strata 4    Representation + BCR Strata + Disturbance 5    Representation + Forest Birds 6    Representation + Disturbance + Forest Birds 7    Representation + BCR Strata + Forest Birds  8    Representation + BCR Strata + Disturbance + Forest Birds 9    Representation + Conservation Status 10    Representation + Disturbance + Conservation Status 11    Representation + BCR Strata + Conservation Status 12    Representation + BCR Strata + Disturbance + Conservation Status 13    Representation + Forest Birds + Conservation Status 14    Representation + Disturbance + Forest Birds + Conservation Status 15    Representation + BCR Strata + Forest Birds  + Conservation Status 16    Representation + BCR Strata + Disturbance + Forest Birds + Conservation Status 17    Representation + Current Uncertainty 18    Representation + Current Uncertainty + Disturbance 19    Representation + Current Uncertainty + BCR Strata 20    Representation + Current Uncertainty + BCR Strata + Disturbance 21    Representation + Current Uncertainty + Forest Birds 22    Representation + Current Uncertainty + Disturbance + Forest Birds 23    Representation + Current Uncertainty + BCR Strata + Forest Birds 24    Representation + Current Uncertainty + BCR Strata + Disturbance + Forest Birds 25    Representation + Current Uncertainty + Conservation Status 26    Representation + Current Uncertainty + Disturbance + Conservation Status 27    Representation + Current Uncertainty + BCR Strata + Conservation Status 28    Representation + Current Uncertainty + BCR Strata + Disturbance + Conservation Status 29    Representation + Current Uncertainty + Forest Birds + Conservation Status 30    Representation + Current Uncertainty + Disturbance + Forest Birds + Conservation Status 31    Representation + Current Uncertainty + BCR Strata + Forest Birds + Conservation Status 32    Representation + Current Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status 33    Representation + Current/Future Uncertainty 34    Representation + Current/Future Uncertainty + Disturbance 35    Representation + Current/Future Uncertainty + BCR Strata 36    Representation + Current/Future Uncertainty + BCR Strata + Disturbance 37    Representation + Current/Future Uncertainty + Forest Birds 38    Representation + Current/Future Uncertainty + Disturbance + Forest Birds 39    Representation + Current/Future Uncertainty + BCR Strata + Forest Birds 40    Representation + Current/Future Uncertainty + BCR Strata + Disturbance + Forest Birds 41    Representation + Current/Future Uncertainty + Conservation Status 42    Representation + Current/Future Uncertainty + Disturbance + Conservation Status 43    Representation + Current/Future Uncertainty + BCR Strata + Conservation Status 44    Representation + Current/Future Uncertainty + BCR Strata + Disturbance + Conservation Status 45    Representation + Current/Future Uncertainty + Forest Birds + Conservation Status 46    Representation + Current/Future Uncertainty + Disturbance + Forest Birds + Conservation Status 47    Representation + Current/Future Uncertainty + BCR Strata + Forest Birds + Conservation Status 48    Representation + Current/Future Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status 49    Representation + Future Uncertainty 50    Representation + Future Uncertainty + Disturbance 51    Representation + Future Uncertainty + BCR Strata 52    Representation + Future Uncertainty + BCR Strata + Disturbance 53    Representation + Future Uncertainty + Forest Birds 54    Representation + Future Uncertainty + Disturbance + Forest Birds 55    Representation + Future Uncertainty + BCR Strata + Forest Birds 56    Representation + Future Uncertainty + BCR Strata + Disturbance + Forest Birds 57    Representation + Future Uncertainty + Conservation Status 58    Representation + Future Uncertainty + Disturbance + Conservation Status 59    Representation + Future Uncertainty + BCR Strata + Conservation Status 60    Representation + Future Uncertainty + BCR Strata + Disturbance + Conservation Status 61    Representation + Future Uncertainty + Forest Birds + Conservation Status 62    Representation + Future Uncertainty + Disturbance + Forest Birds + Conservation Status 63    Representation + Future Uncertainty + BCR Strata + Forest Birds + Conservation Status 64    Representation + Future Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status 65    Diversity 66    Diversity + Disturbance 67    Diversity + BCR Strata 68    Diversity + BCR Strata + Disturbance 69    Diversity + Forest Birds 70    Diversity + Disturbance + Forest Birds 71    Diversity + BCR Strata + Forest Birds  72    Diversity + BCR Strata + Disturbance + Forest Birds 73    Diversity + Conservation Status 74    Diversity + Disturbance + Conservation Status 75    Diversity + BCR Strata + Conservation Status 76    Diversity + BCR Strata + Disturbance + Conservation Status 77    Forest Birds + Conservation Status 78    Disturbance + Forest Birds + Conservation Status 79    BCR Strata + Forest Birds  + Conservation Status 80    BCR Strata + Disturbance + Forest Birds + Conservation Status 81    Diversity + Current Uncertainty 82    Diversity + Current Uncertainty + Disturbance 83    Diversity + Current Uncertainty + BCR Strata 84    Diversity + Current Uncertainty + BCR Strata + Disturbance 85    Diversity + Current Uncertainty + Forest Birds 86    Diversity + Current Uncertainty + Disturbance + Forest Birds 87    Diversity + Current Uncertainty + BCR Strata + Forest Birds 88    Diversity + Current Uncertainty + BCR Strata + Disturbance + Forest Birds 89    Diversity + Current Uncertainty + Conservation Status 90    Diversity + Current Uncertainty + Disturbance + Conservation Status 91    Diversity + Current Uncertainty + BCR Strata + Conservation Status 92    Diversity + Current Uncertainty + BCR Strata + Disturbance + Conservation Status 93    Diversity + Current Uncertainty + Forest Birds + Conservation Status 94    Diversity + Current Uncertainty + Disturbance + Forest Birds + Conservation Status 95    Diversity + Current Uncertainty + BCR Strata + Forest Birds + Conservation Status 96    Diversity + Current Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status 97    Diversity + Current/Future Uncertainty 98    Diversity + Current/Future Uncertainty + Disturbance 99    Diversity + Current/Future Uncertainty + BCR Strata 100    Diversity + Current/Future Uncertainty + BCR Strata + Disturbance 101    Diversity + Current/Future Uncertainty + Forest Birds 102    Diversity + Current/Future Uncertainty + Disturbance + Forest Birds 103    Diversity + Current/Future Uncertainty + BCR Strata + Forest Birds 104    Diversity + Current/Future Uncertainty + BCR Strata + Disturbance + Forest Birds 105    Diversity + Current/Future Uncertainty + Conservation Status 106    Diversity + Current/Future Uncertainty + Disturbance + Conservation Status 107    Diversity + Current/Future Uncertainty + BCR Strata + Conservation Status 108    Diversity + Current/Future Uncertainty + BCR Strata + Disturbance + Conservation Status 109    Diversity + Current/Future Uncertainty + Forest Birds + Conservation Status 110    Diversity + Current/Future Uncertainty + Disturbance + Forest Birds + Conservation Status 111    Diversity + Current/Future Uncertainty + BCR Strata + Forest Birds + Conservation Status 112    Diversity + Current/Future Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status 113    Diversity + Future Uncertainty 114    Diversity + Future Uncertainty + Disturbance 115    Diversity + Future Uncertainty + BCR Strata 116    Diversity + Future Uncertainty + BCR Strata + Disturbance 117    Diversity + Future Uncertainty + Forest Birds 118    Diversity + Future Uncertainty + Disturbance + Forest Birds 119    Diversity + Future Uncertainty + BCR Strata + Forest Birds 120    Diversity + Future Uncertainty + BCR Strata + Disturbance + Forest Birds 121    Diversity + Future Uncertainty + Conservation Status 122    Diversity + Future Uncertainty + Disturbance + Conservation Status 123    Diversity + Future Uncertainty + BCR Strata + Conservation Status 124    Diversity + Future Uncertainty + BCR Strata + Disturbance + Conservation Status 125    Diversity + Future Uncertainty + Forest Birds + Conservation Status 126    Diversity + Future Uncertainty + Disturbance + Forest Birds + Conservation Status 127    Diversity + Future Uncertainty + BCR Strata + Forest Birds + Conservation Status 128    Diversity + Future Uncertainty + BCR Strata + Disturbance + Forest Birds + Conservation Status Projection information ------------------- "+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs" ------------------- Projection    LAMBERT Spheroid      GRS80 Units         METERS Zunits        NO Xshift        0.0 Yshift        0.0 Parameters     49  0  0.0 /* 1st standard parallel 77  0  0.0 /* 2nd standard parallel -95  0  0.0 /* central meridian 0  0  0.0 /* latitude of projection's origin 0.0 /* false easting (meters) 0.0 /* false northing (meters)

opencc-by-4.0Sep 2024View details →

Seasonal and between-population variation in heat tolerance and cooling efficiency in a Mediterranean songbird

Data collection This database contains physiological data on thermoregulation in response to heat -- heat tolerance limit (HTL), body temperature (Tb), resting metabolic rate (RMR), evaporative water loss (EWL) and evaporative cooling efficiency (EHL/MHP) -- collected during winter and summer in two populations on Great tits Parus major submitted to different thermal environments (one from a montane, more thermally stable site; and the other from a lowland, warmer and more thermally heterogeneous site) in southwestern Iberia. Physiological data were collected by using open flow through respirometry (see Material and Methods for detailed protocols).  Statistical analyses  We evaluated seasonal and between population differences to asses the degree of phenotypical flexibility in those physiological thermoregulatory traits both above and below thermoneutrlaity. See detailed analyses below:  We conducted all statistical analyses in R 4.1.2 (R Core Team, 2021). We used the segmented package (Muggeo, 2009) to determine inflection points in Tb, RMR, EWL, and EHL/MHP for each site and season. Then, the data were split based on inflection points for subsequent analyses below and above thermoneutrality (as in Whitfield et al., 2015). Linear and linear mixed-effects models were fitted to the data by using the lme4 package (Bates et al., 2015). We used the emmeans package (Lenth, 2022) to perform post-hoc pairwise contrasts between groups, and visually checked model assumptions in model residuals. First, to assess seasonal and between-population variation in heat tolerance, we fitted a linear model with HTL (please see Heat Tolerance Limits sheet on dataset) as response variable and body mass, site, season, and the site×season interaction as predictors. Then, we fitted linear models to each thermoregulatory trait (namely Tb, RMR, EWL and EHL/MHP; please see Physiological Data sheet on dataset), using a single Tair stage per individual within (Tair ~ 30 ºC) and above thermoneutral zone (Tair ~ 37 ºC) of Great tits (as inflection points of all variables were below this last Tair stage), including body mass, site, season, and the site×season interaction as predictor variables. Second, for summer measurements, we fitted linear mixed-effects models to evaluate population variation in the slopes of Tb, RMR, EWL and EHL/MHP against Tair above thermoneutrality, as we could obtain several measurements per individual above inflection points for each trait during this season. Initial models included Tair, body mass, site, and the Tair×site interaction as predictor variables, with ring as a random effect. When site emerged as a significant predictor, we additionally fitted separate population-specific models to calculate the slopes and y-intercepts of each thermoregulatory trait in response to Tair.

opencc-by-4.0Sep 2024View details →

Adult survival has a stronger role than productivity in the population dynamics of European songbirds

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Data from: Nocturnal departure timing in songbirds facing distinct migratory challenges

1. Most migratory songbirds travel between their breeding areas and wintering grounds through a series of nocturnal flights. The timing of their departures defines the potential flight duration and thus the distance covered during a migratory night. Yet, migratory songbirds show substantial variation in their nocturnal departure timing. 2. With this study we aim to assess whether the respective challenges of the migration route, namely its distance and nature, help to explain this variation. 3. At a stopover site, we caught Northern Wheatears (Oenanthe oenanthe) of two subspecies that differ in distance and nature of their onward migration route in spring, but not in autumn. We determined the start of their nocturnal migratory restlessness during short-term captivity, and radio-tracked their nocturnal departure timing after release in both migration seasons. 4. Northern Wheatears started their nocturnal migratory restlessness earlier when facing a long remaining migration distance and an extended sea barrier in spring. Individual departure directions generally affected the nocturnal departure timing with early departures being directed towards the respective migratory destination. In spring, this pattern was predominantly found in birds carrying relatively large fuel stores, but was absent in lean birds. At the same time, birds facing a short remaining migration distance and no extended sea barrier strongly reacted to relatively large fuel stores by an early start of nocturnal migratory behavior (migratory restlessness and departure timing), whereas this reaction was not found in birds facing a long remaining migration distance and sea barrier. 5. These results suggest that the basic diel schedule of birds' migratory activity is adapted to the onward migration route. Further they suggest that birds adjust their behavioral response, i.e. start of nocturnal migratory behavior, to fuel stores in relation to their impending migratory challenges. This is a substantial step in understanding variation of nocturnal departure timing and its adjustments in migratory songbirds. Further, it emphasizes the importance of interpreting birds' nocturnal migratory behavior in the respective ecological context.

Data from: Early development of vocal interaction rules in a duetting songbird

Exchange of vocal signals is an important aspect of animal communication. Although birdsong is the premier model for understanding vocal development, the development of vocal interaction rules in birds and possible parallels to humans have been little studied. Many tropical songbirds engage in complex engage in vocal interactions in the form of duets between mated pairs. In some species duets show precise temporal coordination and follow rules (duet codes) governing which song type one bird uses to reply to each of the song types of its mate. We determined whether these duetting rules are acquired during early development in canebrake wrens. Results show that juveniles acquire a duet code by singing with a mated pair of adults and that juveniles gradually increase their fidelity to the code over time. Additionally, we found that juveniles exhibit poorer temporal coordination than adults and improve their coordination as time progresses. Human turn-taking, an analogous rule to temporal coordination, is learned during early development. We report that the ontogeny of vocal interaction rules in songbirds is analogous to that of human conversation rules.

Data from: Fuel for the pace of life: baseline blood glucose concentration coevolves with life history traits in songbirds

1. It has been proposed that life histories have coevolved with a suite of physiological and behavioural adaptations, termed pace-of-life syndromes (POLS). Here, we hypothesise that basal concentration of blood glucose (G0), a major source of energy circulating in vertebrate blood, may constitute a key component of POLS. 2. To test this hypothesis, we measured G0 in 30 passerine species and tested its covariation with body mass and other life history traits. Importantly, body mass is a major life history determinant and, when its effect is controlled for, there may be no single fast-slow life history continuum in birds comprising both fecundity and lifespan. Hence, we used individual life history traits, rather than principal component analysis, to characterise life history variation in our analysis. 3. In support of G0 life history coevolution, we found G0 to be negatively correlated with body mass and positively with reproductive investment in a single clutch across 30 passerine species. Higher G0 in females suggests that the energy demands of clutch production and incubation may be an important selection force driving coevolution of G0 with reproductive output. 4. In contrast, G0 was not associated with maximum lifespan, suggesting that high G0 may not constrain evolution of longevity. This implies that long-lived species can evolve physiological adaptations preventing harmful effects of high glucose concentrations, known to cause pathologies and accelerate ageing. 5. In addition, G0, but not basal metabolic rate (BMR), was negatively correlated with migration distance, attesting to evolutionary changes in energy metabolism in long distance migrants. Our results further suggest that the links between body mass, reproduction and G0 are not mediated by BMR and that G0 is associated with fast-slow life history variation more closely than available BMR data. 6. A species life history is determined to a great extent by body mass. When this effect is controlled for, only those traits related to reproduction (but not lifespan) constitute the principal axis of life history variation in birds. Hence, the coevolution of G0 with body mass and reproductive output evidenced in our study indicates that G0 constitutes an important physiological component of POLS.

opencc-zeroAug 2019View details →

Data from: Selection on VPS13A linked to migration in a songbird

Animal migration demands an interconnected suite of adaptations for individuals to navigate over long distances. This trait complex is crucial for small birds whose migratory behaviors—such as directionality—are more likely innate, rather than being learned as in many longer-lived birds. Identifying causal genes has been a central goal of migration ecology, and this endeavor has been furthered by genome-scale comparisons. However, even the most successful studies of migration genetics have achieved low resolution associations, identifying large chromosomal regions that encompass hundreds of genes, one or more of which might be causal. Here we leverage the genomic similarity among golden-winged (Vermivora chrysoptera) and blue-winged warblers (V. cyanoptera) to identify a single gene—Vacuolar Protein Sorting 13A (VPS13A)—that is associated with distinct differences in migration to Central American (CA) or South American (SA) wintering areas. We find reduced sequence variation in this gene-region for SA wintering birds, and show this is the likely result of natural selection on this locus. In humans, variants of VPS13A are linked to the neurodegenerative disorder chorea-acanthocytosis. This new association provides one of the strongest gene-level associations with avian migration differences.

Data from: A mimicked bacterial infection prolongs stopover duration in songbirds – but more pronounced in short- than long-distance migrants

1) Migration usually consists of intermittent travel and stopovers, the latter being crucially important for individuals to recover and refuel to successfully complete migration. Quantifying how sickness behaviours influence stopovers is crucial for our understanding of migration ecology and how diseases spread. However, little is known about infections in songbirds, which constitute the majority of avian migrants. 2) We experimentally immune-challenged autumn migrating passerines (both short- and long-distance migrating species) with a simulated bacterial infection. Using an automated radio-telemetry system in the stopover area, we subsequently quantified stopover duration, 'bush-level' activity patterns (0.1-30m) and landscape movements (30-6000m). 3) We show that compared to controls, immune-challenged birds prolonged their stopover duration by on average 1.2 days in long-distance and 2.9 days in short-distance migrants, respectively (100 – 126 % longer than controls, respectively). During the prolonged stopover, the immune-challenged birds kept a high 'bush-level' activity (which was unexpected) but reduced their local movements, independent of migration strategy. Baseline immune function, but not blood parasite infections prior to the immune challenge, had a prolonging effect on stopover duration, particularly in long-distance migrants. 4) We conclude that a mimicked bacterial infection does not cause lethargy, per se, but restricts landscape movements and prolongs stopover duration, and that this behavioural response also depends on the status of baseline immunity and migration strategy. This adds a new level to the understanding of how acute inflammation affect migration behaviour and hence the ecology and evolution of migration. Accounting for these effects of bacterial infections will also enable us to fine-tune and apply optimal migration theory. Finally it will help us predicting how migrating animals may respond to increased pathogen pressure by global change.

Data from: Phenological mismatch drives selection on elevation, but not on slope, of breeding time plasticity in a wild songbird

Phenotypic plasticity is an important mechanism for populations to respond to fluctuating environments, yet may be insufficient to adapt to a directionally changing environment. To study whether plasticity can evolve under current climate change, we quantified selection and genetic variation in both the elevation (RNE) and slope (RNS) of the breeding time reaction norm in a long-term (1973–2016) study population of great tits (Parus major). The optimal RNE (the caterpillar biomass peak date regressed against the temperature used as cue by great tits) changed over time, whereas the optimal RNS did not. Concordantly, we found strong directional selection on RNE, but not RNS, of egg-laying date in the second third of the study period; this selection subsequently waned, potentially due to increased between-year variability in optimal laying dates. We found individual and additive genetic variation in RNE but, contrary to previous studies on our population, not in RNS. The predicted and observed evolutionary change in RNE were, however, marginal, due to low heritability and the sex limitation of laying date. We conclude that adaptation to climate change can only occur via micro-evolution of RNE, but this will necessarily be slow and potentially hampered by increased variability in phenotypic optima.

opencc-zeroDec 2016View details →

Data from: Subspecies delineation amid phenotypic, geographic, and genetic discordance in a songbird

Understanding the processes that drive divergence within and among species is a long-standing goal in evolutionary biology. Traditional approaches to assessing differentiation rely on phenotypes to identify intra- and interspecific variation, but many species express subtle morphological gradients in which boundaries among forms are unclear. This intraspecific variation may be driven by differential adaptation to local conditions and may thereby reflect the evolutionary potential within a species. Here, we combine genetic and morphological data to evaluate intraspecific variation within the Nelson's (Ammodramus nelsoni) and saltmarsh (A. caudacutus) sparrow complex, a group with populations that span considerable geographic distributions and a habitat gradient. We evaluated genetic structure among and within five putative subspecies of A. nelsoni and A. caudacutus using a reduced-representation sequencing approach to generate a panel of 1,929 SNPs among 69 individuals. Although we detected morphological differences among some groups, individuals sorted along a continuous phenotypic gradient. In contrast, the genetic data identified three distinct clusters corresponding to populations that inhabit coastal salt marsh, interior freshwater marsh, and coastal brackish-water marsh habitats. These patterns support the current species-level recognition but do not match the subspecies-level taxonomy within each species– a finding which may have important conservation implications. We identified loci exhibiting patterns of elevated divergence among and within these species, indicating a role for local selective pressures in driving patterns of differentiation across the complex. We conclude that this evidence for adaptive variation among subspecies warrants the consideration of evolutionary potential and genetic novelty when identifying conservation units for this group.

opencc-zeroJul 2021View details →

Data from: Early origin of sweet perception in the songbird radiation

Early events in the evolutionary history of a clade can shape the sensory systems of descendant lineages. Although the avian ancestor may not have had a sweet receptor, the widespread incidence of nectar-feeding birds suggests multiple acquisitions of sugar detection. In this study, we identify a single early sensory shift of the umami receptor (the T1R1-T1R3 heterodimer) that conferred sweet-sensing abilities in songbirds, a large radiation containing nearly half of all living birds. We demonstrate sugar responses across species with diverse diets, uncover critical sites underlying carbohydrate detection, and identify the molecular basis of sensory convergence between songbirds and nectar-specialist hummingbirds. This early shift shaped the sensory biology of an entire radiation, emphasizing the role of contingency and providing an example of the genetic basis of convergence in avian evolution.

opencc-zeroAug 2022View details →

Presence, precipitation, and temperature data used to estimate eastern forest songbird historical distributions using climatic niche modeling

Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest-grassland ecotone in the south-central United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad-scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest-breeding passerines from 30-year average climate conditions from 1980 to 2010. During this time the southern Great Plains experienced an unprecedented wet period without periodic multi-year droughts that characterized the region's long-term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952–1958 and 1966–1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest-grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980–2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966–1972 range limit projections. Periods of lower precipitation in the forest-grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.

opencc-zeroAug 2021View details →

Poor quality monitoring data underestimate the impact of Australia's megafires on a critically endangered songbird

Aim: Catastrophic events such as south-eastern Australia's 2019/20 megafires are predicted to increase in frequency and severity under climate change. Rapid, well-informed conservation prioritisation will become increasingly crucial for minimising biodiversity losses resulting from megafires. However, such assessments are susceptible to bias, because the quality of monitoring data underpinning knowledge of species' distributions is highly variable and they fail to account for differences in life-history traits such as aggregative breeding. We aimed to assess how impact estimates of the 2019/20 megafires on the critically endangered regent honeyeater Anthochaera phrygia varied according to the quality of available input data and assessment methodology. Innovation: Using Google Earth Engine Burnt Area Mapping, we estimated the impact of the megafires on the regent honeyeater using six monitoring datasets that differ in quality and temporal span. These datasets are representative of the variable quality of monitoring data available for assessing fire impact on 326 other threatened species; most are poorly monitored and few have standardised, species-specific monitoring programs. We found that assessments based on Area of Occupancy (AOO), Extent of Occurrence (EOO) and public sightings underestimated the fire impact relative to recent, targeted monitoring datasets; a MaxEnt model, sightings from a national monitoring program and nest locations since 2015. Using an impact threshold of 30% of habitat burned, regent honeyeaters would not meet this criteria using estimates derived from EOO, AOO or public sightings, but would exceed the cut-off based on estimates derived from the targeted monitoring data that account for population density. Main conclusions: To ensure that conservation prioritisation has the greatest capacity to minimise biodiversity losses, we highlight the need to improve targeted, threatened species monitoring. We demonstrate the importance of using recent, standardised monitoring data to estimate accurately the impact of major ecological disturbances, particularly for declining, nomadic species undergoing range contractions.

opencc-zeroOct 2021View details →

Bayesian N-mixture and occupancy modeling code for songbirds

The proliferation of energy rights-of-way (pipelines and powerlines; ROWs) in the central Appalachian region has prompted wildlife management agencies to consider ways to use these features to manage and conserve at-risk songbird species. However, little empirical evidence exists regarding best management strategies to enhance habitat surrounding ROWs for the songbird community during stopover or breeding periods. We used a before-after-control-impact design to study cut-back border (linear tree cuttings along abrupt forest edges) harvest width (15 m, 30 m, and 45 m wide into the forest) and harvest intensity (14 m2/ha and 4.5 m2/ha basal area retention) prescriptions along ROWs and assessed their effects on mature forest and young forest songbird species and avian guilds (forest gap habitat, forest interior habitat, young forest habitat, and species of regional conservation priority) up to two years after treatment throughout West Virginia. Species richness during the spring stopover period initially decreased at one-year post-treatment but returned to pre-treatment levels by two-year post-treatment. Breeding season responses to cut-back border treatments varied across harvest width, harvest intensity, and time, but all responses of focal species abundance and guild richness were neutral or positive. Cut-back border harvest intensity had a stronger influence (i.e., more positive responses) than harvest width on breeding focal species abundances and guild richness. For harvest intensity, the more intense, 4.5 m2/ha retention treatment had a stronger influence (i.e., more positive responses) than the less intense, 14 m2/ha retention treatment. For harvest width, the narrowest treatment (15-m wide) had the strongest influence (i.e., more positive responses) of all width treatments, followed by the widest (45-m wide treatment) with the least influence from the 30-m wide treatment. Abundances and richness increased from pre-treatment to two-year post-treatment across all species and guilds that exhibited a response. These results suggest that cut-back borders increase breeding season habitat suitability along ROWs for the mature forest and young forest songbird community as well as for species of regional conservation priority in the short-term. These findings can aid development of management guidelines for the forest songbird community along abrupt forest edges of man-made habitat features in forest-dominated landscapes.

opennotspecifiedDec 2012View details →

FIGURE 2 in Haemoproteus nucleocondensus n. sp. (Haemosporida, Haemoproteidae) from a Eurasian songbird, the Great Reed Warbler Acrocephalus arundinaceus

FIGURE 2. Bayesian phylogeny of 24 mitochondrial cytochrome b lineages of Haemoproteus spp. and 4 lineages of Plasmodium spp. One lineage of Leucocytozoon is used as outgroup. Codes of lineages and GenBank accession numbers (in parentheses) are given after parasite species names, with the name of new species in bold. Names of parasites with microgametocytes possessing condensed nuclei morphologically similar to the new species are underlined. Posterior probability values>70 are indicated near the nodes.Vertical bars A and B indicate haemoproteid species belonging to the subgenera Haemoproteus and Parahaemoproteus, respectively.

opennotspecifiedDec 2012View details →

FIGURE 1 in Haemoproteus nucleocondensus n. sp. (Haemosporida, Haemoproteidae) from a Eurasian songbird, the Great Reed Warbler Acrocephalus arundinaceus

FIGURE 1. Gametocytes of Haemoproteus nucleocondensus sp. nov. (a-l) from the blood of Great Reed Warbler, Acrocephalus arundinaceus and Haemoproteus payevskyi (m-t) from the blood of Reed Warbler, Acrocephalus scirpaceus: a, b, i, m, q—young gametocytes; c–h, n–p—macrogametocytes; j–l, r–t—microgametocytes. Long arrows—nuclei of parasites; short arrows—unfilled spaces between gametocyte and envelope of infected erythrocyte; arrow head—pigment granules. Giemsa-stained thin blood films. Bar = 10 µm.

opencc-zeroNov 2022View details →

Simulated infection alters the behavior of pair bonded songbirds and their healthy neighbors

While infection and perceived infection risk can influence social and reproductive behavior in several taxa, relatively little is known about how infection specifically affects pair bond behaviors. Some pair bond maintenance behaviors may be costly to maintain during infection, and infection could promote avoidance behaviors within an established pair. Many species exhibiting pair bonds are part of larger social groups, and behavioral shifts in established pairs can result in altered extra-pair contact rates that could also shape disease transmission. Using captive zebra finches (Taeniopygia guttata), we examined how an immune challenge with lipopolysaccharide (LPS) influences activity, social behavior, and pair bond maintenance behaviors in established pairs and their healthy neighbors. We observed shifts in individual and pair maintenance behaviors in both immune-challenged pairs and healthy pairs exposed to a social cue of infection (sick conspecifics). Specifically, LPS-challenged birds decreased activity and social interaction attempts relative to control birds, consistent with LPS-induced sickness behavior. LPS-challenged birds also increased the frequency of clumping (perching together in bodily contact) between individuals within a pair. Healthy birds exposed to immune-challenged conspecifics decreased flight activity and increased self-preening, behaviors which could function to limit infection risk. Exploring how both infection and the perceived risk of infection shape behaviors within and among paired individuals will increase our understanding of the role of social behaviors in shaping disease dynamics.