ALBERT

Description: Contrasting with birds and mammals, poikilothermic vertebrates often have homomorphic sex chromosomes, possibly resulting from high rates of sex-chromosome turnovers and/or occasional X–Y recombination. Strong support for the latter mechanism was provided by four species of European tree frogs, which inherited from a common ancestor (~5 Ma) the same pair of homomorphic sex chromosomes (linkage group 1, LG1), harboring the candidate sex-determining gene Dmrt1. Here, we test sex linkage of LG1 across six additional species of the Eurasian Hyla radiation with divergence times ranging from 6 to 40 Ma. LG1 turns out to be sex linked in six of nine resolved cases. Mapping the patterns of sex linkage to the Hyla phylogeny reveals several transitions in sex-determination systems within the last 10 My, including one switch in heterogamety. Phylogenetic trees of DNA sequences along LG1 are consistent with occasional X–Y recombination in all species where LG1 is sex linked. These patterns argue against one of the main potential causes for turnovers, namely the accumulation of deleterious mutations on nonrecombining chromosomes. Sibship analyses show that LG1 recombination is strongly reduced in males from most species investigated, including some in which it is autosomal. Intrinsically low male recombination might facilitate the evolution of male heterogamety, and the presence of important genes from the sex-determination cascade might predispose LG1 to become a sex chromosome.

Description: Mixing models are statistical tools that use biotracers to probabilistically estimate the contribution of multiple sources to a mixture. These biotracers may include contaminants, fatty acids, or stable isotopes, the latter of which are widely used in trophic ecology to estimate the mixed diet of consumers. Bayesian implementations of mixing models using stable isotopes (e.g. MixSIR, SIAR) are regularly used by ecologists for this purpose, but basic questions remain about when each is most appropriate. In this study, we describe the structural differences between common mixing model error formulations in terms of their assumptions about the predation process. We then introduce a new parameterization that unifies these mixing model error structures, as well as implicitly estimates the rate at which consumers sample from source populations (i.e. consumption rate). Using simulations and previously published mixing model datasets, we demonstrate that the new error parameterization outperforms existing models and provides an estimate of consumption. Our results suggest that the error structure introduced here will improve future mixing model estimates of animal diet. This article is protected by copyright. All rights reserved.

Description: The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish ( Anoplopoma fimbria ) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions.

Description: Seismicity was monitored beneath the Krafla central volcano, NE Iceland, between 2009 and 2012 during a period of volcanic quiescence, when most earthquakes occured within the shallow geothermal field. The highest concentration of earthquakes is located close to the rock-melt transition zone as the IDDP-1 wellbore suggests, and decays quickly at greater depths. We recorded multiple swarms of microearthquakes, which coincide often with periods of changes in geothermal field operations, and found that about one third of the total number of earthquakes are repeating events. The event size distribution, evaluated within the central caldera, indicates average crustal values with b = 0.79 ± 0.04. No significant spatial b -value contrasts are resolved within the geothermal field nor in the vicinity of the drilled melt. Besides the seismicity analysis, focal mechanisms are calculated for 342 events. Most of these short-period events have source radiation patterns consistent with double-couple (DC) mechanisms. A few events are attributed to non-shear faulting mechanisms with geothermal fluids likely playing an important role in their source processes. Diverse faulting styles are inferred from DC events, but normal faulting prevails in the central caldera. The best-fitting compressional and tensional axes of DC mechanisms are interpreted in terms of the principal stress or deformation-rate orientations across the plate boundary rift. Maximum compressive stress directions are near-vertically aligned in different study volumes, as expected in an extensional tectonic setting. Beneath the natural geothermal fields, the least compressive stress axis is found to align with the regional spreading direction. In the main geothermal field both horizontal stresses appear to have similar magnitudes causing a diversity of focal mechanisms.

Description: Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from thirteen global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES programme we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron-fertilisation experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.

Description: Based on hierarchical multi‐species models applied to avian mist‐netting data from six sites along a montane elevation gradient in a large protected area, we show advancement of avian breeding phenology (mean first capture date of juvenile birds) and increase in productivity (probability of capturing a juvenile bird) over 25 years with variable but declining snowfall and increasing spring temperatures. Breeding phenology depended on elevation and tracked climatic conditions. Productivity was higher in relatively warm springs, while productivity–elevation responses were variable among species; species with higher productivity at higher elevations tended to be species with recent range retractions. Abstract Climate variation has been linked to historical and predicted future distributions and dynamics of wildlife populations. However, demographic mechanisms underlying these changes remain poorly understood. Here, we assessed variation and trends in climate (annual snowfall and spring temperature anomalies) and avian demographic variables from mist‐netting data (breeding phenology and productivity) at six sites along an elevation gradient spanning the montane zone of Yosemite National Park between 1993 and 2017. We implemented multi‐species hierarchical models to relate demographic responses to elevation and climate covariates. Annual variation in climate and avian demographic variables was high. Snowfall declined (10 mm/year at the highest site, 2 mm at the lowest site), while spring temperature increased (0.045°C/year) over the study period. Breeding phenology (mean first capture date of juvenile birds) advanced by 0.2 day/year (5 days); and productivity (probability of capturing a juvenile bird) increased by 0.8%/year. Breeding phenology was 12 days earlier at the lowest compared to highest site, 18 days earlier in years with lowest compared to highest snowfall anomalies, and 6 d earlier in relatively warm springs (after controlling for snowfall effects). Productivity was positively related to elevation. However, elevation–productivity responses varied among species; species with higher productivity at higher compared to lower elevations tended to be species with documented range retractions during the past century. Productivity tended to be negatively related to snowfall and was positively related to spring temperature. Overall, our results suggest that birds have tracked the variable climatic conditions in this system and have benefited from a trend toward warmer, drier springs. However, we caution that continued warming and multi‐year drought or extreme weather years may alter these relationships in the future. Multi‐species demographic modeling, such as implemented here, can provide an important tool for guiding conservation of species assemblages under global change.

Description: Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia ( NH x ( sw )), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here, we compare [ NH x ( sw )] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [ NH x ( sw )] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NH x within observed ranges. The resulting global ocean emissions is 2.5 TgN a −1 , much lower than current literature values(7–23 TgN a −1 ), including the widely used GEIA inventory (8 TgN a −1 ). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NH x over most of the ocean in the Northern hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a −1 , comparable in magnitude to other natural sources from open fires and soils.

Description: Future projections of potential ocean ecosystem stressors, such as acidification, warming, deoxygenation and changes in ocean productivity, are uncertain due to incomplete understanding of fundamental processes, internal climate variability, and divergent carbon emissions scenarios. This complicates climate change impact assessments. We evaluate the relative importance of these uncertainty sources in projections of potential stressors as a function of projection lead-time and spatial scale. Internally generated climate variability is the dominant source of uncertainty in mid-to-low latitudes and in most coastal Large Marine Ecosystems over the next few decades, suggesting irreducible uncertainty inherent in these short projections. Uncertainty in projections of century-scale global sea surface temperature (SST), global thermocline oxygen, and regional surface pH is dominated by scenario uncertainty, highlighting the critical importance of policy decisions on carbon emissions. In contrast, uncertainty in century-scale projections of net primary productivity (NPP), low oxygen waters, and Southern Ocean SST is dominated by model uncertainty, underscoring the importance of overcoming deficiencies in scientific understanding and improved process representation in Earth system models are critical for making more robust projections of these potential stressors. We also show that changes in the combined potential stressors emerge from the noise in 39% (34 – 44%) of the ocean by 2016-2035 relative to the 1986-2005 reference period and in 54% (50 – 60%) of the ocean by 2076-2095 following a high carbon emissions scenario. Projected large changes in surface pH and SST can be reduced substantially and rapidly with aggressive carbon emission mitigation, but only marginally for oxygen. The regional importance of model uncertainty and internal variability underscores the need for expanded and improved multi-model and large initial condition ensemble projections with Earth system models for evaluating regional marine resource impacts.