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Critical loads (CLs) are frequently used to quantify terrestrial ecosystem impacts from nitrogen (N) deposition using ecological responses such as the growth and mortality of tree species. Typically, CLs are reported as a single value, with uncertainty, for an indicator across a species' entire range. Mediating factors such as climate and soil conditions can influence species' sensitivity to N, but the magnitudes of these effects are rarely calculated explicitly. Here, we quantify the spatial variability and estimation error in N CLs for the growth and survival of 10 different tree species while accounting for key environmental factors that mediate species sensitivity to N (e.g., soil characteristics). We used a bootstrapped machine learning approach to determine the level of N deposition at which a 1% decrease occurs in growth rate or survival probability at forest plot locations across the United States. We found minimal differences (<5 kg N ha⁻¹ year⁻¹) when comparing a single species' CLs across climatic regimes but found considerable variability in species' local N CLs (>8.5 kg N ha⁻¹ year⁻¹) within these regimes. We also evaluated the most important factors for predicting tree growth rates and mortality and found that climate, competition, and air pollution generally have the greatest influence on growth rates and survival probability. Lastly, we developed a new probability of exceedance metric for each species and found high likelihoods of exceedance across large portions (46%) of some species' ranges. Our analysis demonstrates that machine learning approaches provide a unique capability to: (1) quantify mediating factor influences on N sensitivity of trees, (2) estimate the error in local N CL estimates, and (3) generate localized N CLs with probabilities of exceedance for tree species. 

Abstract Gene flow can affect evolutionary inference when species are undersampled. Here, we evaluate the effects of gene flow and geographic sampling on demographic inference of 2 hummingbirds that hybridize, Allen’s hummingbird (Selasphorus sasin) and rufous hummingbird (Selasphorus rufus). Using whole-genome data and extensive geographic sampling, we find widespread connectivity, with introgression far beyond the Allen’s × rufous hybrid zone, although the Z chromosome resists introgression beyond the hybrid zone. We test alternative hypotheses of speciation history of Allen’s, rufous, and Calliope (S. calliope) hummingbird and find that rufous hummingbird is the sister taxon to Allen’s hummingbird, and Calliope hummingbird is the outgroup. A model treating the 2 subspecies of Allen’s hummingbird as a single panmictic population fit observed genetic data better than models treating the subspecies as distinct populations, in contrast to morphological and behavioral differences and analyses of spatial population structure. With additional sampling, our study builds upon recent studies that came to conflicting conclusions regarding the evolutionary histories of these 2 species. Our results stress the importance of thorough geographic sampling when assessing demographic history in the presence of gene flow. 

Synopsis Animal wings produce an acoustic signature in flight. Many owls are able to suppress this noise to fly quietly relative to other birds. Instead of silent flight, certain birds have conversely evolved to produce extra sound with their wings for communication. The papers in this symposium synthesize ongoing research in “animal aeroacoustics”: the study of how animal flight produces an acoustic signature, its biological context, and possible bio-inspired engineering applications. Three papers present research on flycatchers and doves, highlighting work that continues to uncover new physical mechanisms by which bird wings can make communication sounds. Quiet flight evolves in the context of a predator–prey interaction, either to help predators such as owls hear its prey better, or to prevent the prey from hearing the approaching predator. Two papers present work on hearing in owls and insect prey. Additional papers focus on the sounds produced by wings during flight, and on the fluid mechanics of force production by flapping wings. For instance, there is evidence that birds such as nightbirds, hawks, or falcons may also have quiet flight. Bat flight appears to be quieter than bird flight, for reasons that are not fully explored. Several research avenues remain open, including the role of flapping versus gliding flight or the physical acoustic mechanisms by which flight sounds are reduced. The convergent interest of the biology and engineering communities on quiet owl flight comes at a time of nascent developments in the energy and transportation sectors, where noise and its perception are formidable obstacles. 

Abstract The metallicity and gas density dependence of interstellar depletions, the dust-to-gas (D/G), and dust-to-metal (D/M) ratios have important implications for how accurately we can trace the chemical enrichment of the universe, either by using FIR dust emission as a tracer of the ISM or by using spectroscopy of damped Ly α systems to measure chemical abundances over a wide range of redshifts. We collect and compare large samples of depletion measurements in the Milky Way (MW), Large Magellanic Cloud (LMC) ( Z = 0.5 Z ⊙ ), and Small Magellanic Cloud (SMC) ( Z = 0.2 Z ⊙ ). The relations between the depletions of different elements do not strongly vary between the three galaxies, implying that abundance ratios should trace depletions accurately down to 20% solar metallicity. From the depletions, we derive D/G and D/M. The D/G increases with density, consistent with the more efficient accretion of gas-phase metals onto dust grains in the denser ISM. For log N (H) > 21 cm −2 , the depletion of metallicity tracers (S, Zn) exceeds −0.5 dex, even at 20% solar metallicity. The gas fraction of metals increases from the MW to the LMC (factor 3) and SMC (factor 6), compensating for the reduction in total heavy element abundances and resulting in those three galaxies having the same neutral gas-phase metallicities. The D/G derived from depletions are respective factors of 2 (LMC) and 5 (SMC) higher than the D/G derived from FIR, 21 cm, and CO emission, likely due to the combined uncertainties on the dust FIR opacity and on the depletion of carbon and oxygen.