Extreme elevational migration spurred cryptic speciation in giant hummingbirds.

The ecoevolutionary drivers of species niche expansion or contraction are critical for biodiversity but challenging to infer. Niche expansion may be promoted by local adaptation or constrained by physiological performance trade-offs. For birds, evolutionary shifts in migratory behavior permit the broadening of the climatic niche by expansion into varied, seasonal environments. Broader niches can be short-lived if diversifying selection and geography promote speciation and niche subdivision across climatic gradients. To illuminate niche breadth dynamics, we can ask how "outlier" species defy constraints. Of the 363 hummingbird species, the giant hummingbird (Patagona gigas) has the broadest climatic niche by a large margin. To test the roles of migratory behavior, performance trade-offs, and genetic structure in maintaining its exceptional niche breadth, we studied its movements, respiratory traits, and population genomics. Satellite and light-level geolocator tracks revealed an >8,300-km loop migration over the Central Andean Plateau. This migration included a 3-wk, ~4,100-m ascent punctuated by upward bursts and pauses, resembling the acclimatization routines of human mountain climbers, and accompanied by surging blood-hemoglobin concentrations. Extreme migration was accompanied by deep genomic divergence from high-elevation resident populations, with decisive postzygotic barriers to gene flow. The two forms occur side-by-side but differ almost imperceptibly in size, plumage, and respiratory traits. The high-elevation resident taxon is the world's largest hummingbird, a previously undiscovered species that we describe and name here. The giant hummingbirds demonstrate evolutionary limits on niche breadth: when the ancestral niche expanded due to evolution (or loss) of an extreme migratory behavior, speciation followed.

Detecting turnover among complex communities using null models: a case study with sky-island haemosporidian parasites.

Turnover in species composition between sites, or beta diversity, is a critical component of species diversity that is typically influenced by geography, environment, and biotic interactions. Quantifying turnover is particularly challenging, however, in multi-host, multi-parasite assemblages where undersampling is unavoidable, resulting in inflated estimates of turnover and uncertainty about its spatial scale. We developed and implemented a framework using null models to test for community turnover in avian haemosporidian communities of three sky islands in the southwestern United States. We screened 776 birds for haemosporidian parasites from three genera (Parahaemoproteus, Plasmodium, and Leucocytozoon) by amplifying and sequencing a mitochondrial DNA barcode. We detected infections in 280 birds (36.1%), sequenced 357 infections, and found a total of 99 parasite haplotypes. When compared to communities simulated from a regional pool, we observed more unique, single-mountain haplotypes and fewer haplotypes shared among three mountain ranges than expected, indicating that haemosporidian communities differ to some degree among adjacent mountain ranges. These results were robust even after pruning datasets to include only identical sets of host species, and they were consistent for two of the three haemosporidian genera. The two more distant mountain ranges were more similar to each other than the one located centrally, suggesting that the differences we detected were due to stochastic colonization-extirpation dynamics. These results demonstrate that avian haemosporidian communities of temperate-zone forests differ on relatively fine spatial scales between adjacent sky islands. Null models are essential tools for testing the spatial scale of turnover in complex, undersampled, and poorly known systems.

Diversity, abundance, and host relationships of avian malaria and related haemosporidians in New Mexico pine forests.

Avian malaria and related haemosporidian parasites (genera Haemoproteus, Plasmodium, and Leucocytozoon) affect bird demography, species range limits, and community structure, yet they remain unsurveyed in most bird communities and populations. We conducted a community-level survey of these vector-transmitted parasites in New Mexico, USA, to describe their diversity, abundance, and host associations. We focused on the breeding-bird community in the transition zone between piñon-juniper woodland and ponderosa pine forests (elevational range: 2,150-2,460 m). We screened 186 birds representing 49 species using both standard PCR and microscopy techniques to detect infections of all three avian haemosporidian genera. We detected infections in 68 out of 186 birds (36.6%), the highest proportion of which were infected with Haemoproteus (20.9%), followed by Leucocytozoon (13.4%), then Plasmodium (8.0%). We sequenced mtDNA for 77 infections representing 43 haplotypes (25 Haemoproteus, 12 Leucocytozoon, 6 Plasmodium). When compared to all previously known haplotypes in the MalAvi and GenBank databases, 63% (27) of the haplotypes we recovered were novel. We found evidence for host specificity at the avian clade and species level, but this specificity was variable among parasite genera, in that Haemoproteus and Leucocytozoon were each restricted to three avian groups (out of six), while Plasmodium occurred in all groups except non-passerines. We found striking variation in infection rate among host species, with nearly universal infection among vireos and no infection among nuthatches. Using rarefaction and extrapolation, we estimated the total avian haemosporidian diversity to be 70 haplotypes (95% CI [43-98]); thus, we may have already sampled ∼60% of the diversity of avian haemosporidians in New Mexico pine forests. It is possible that future studies will find higher diversity in microhabitats or host species that are under-sampled or unsampled in the present study. Fortunately, this study is fully extendable via voucher specimens, frozen tissues, blood smears, parasite images, and documentation provided in open-access databases (MalAvi, GenBank, and ARCTOS).