Incorporating physiology into species distribution models moderates the projected impact of warming on selected Mediterranean marine species

Species distribution models (SDMs) correlate species occurrences with environmental predictors, and can be used to forecast distributions under future climates. SDMs have been criticized for not explicitly including the physiological processes underlying the species response to the environment. Recently, new methods have been suggested to combine SDMs with physiological estimates of performance (physiology-SDMs). In this study, we compare SDM and physiology-SDM predictions for select marine species in the Mediterranean Sea, a region subjected to exceptionally rapid climate change. We focused on six species and created physiology-SDMs that incorporate physiological thermal performance curves from experimental data with species occurrence records. We then contrasted projections of SDMs and physiology-SDMs under future climate (year 2100) for the entire Mediterranean Sea, and particularly the ‘warm’ trailing edge in the Levant region. Across the Mediterranean, we found cross-validation model performance to be similar for regular SDMs and physiology-SDMs. However, we also show that for around half the species the physiology-SDMs substantially outperform regular SDM in the warm Levant. Moreover, for all species the uncertainty associated with the coefficients estimated from the physiology-SDMs were much lower than in the regular SDMs. Under future climate, we find that both SDMs and physiology-SDMs showed similar patterns, with species predicted to shift their distribution north-west in accordance with warming sea temperatures. However, for the physiology-SDMs predicted distributional changes are more moderate than those predicted by regular SDMs. We conclude, that while physiology-SDM predictions generally agree with the regular SDMs, incorporation of the physiological data led to less extreme range shift forecasts. The results suggest that climate-induced range shifts may be less drastic than previously predicted, and thus most species are unlikely to completely disappear with warming climate. Taken together, the findings emphasize that physiological experimental data can provide valuable supplemental information to predict range shifts of marine species.     

A comparison of diversity estimators applied to a database of host–parasite associations

Understanding the drivers of biodiversity is important for forecasting changes in the distribution of life on earth. However, most studies of biodiversity are limited by uneven sampling effort, with some regions or taxa better sampled than others. Numerous methods have been developed to account for differences in sampling effort, but most methods were developed for systematic surveys in which all study units are sampled using the same design and assemblages are sampled randomly. Databases compiled from multiple sources, such as from the literature, often violate these assumptions because they are composed of studies that vary widely in their goals and methods. Here, we compared the performance of several popular methods for estimating parasite diversity based on a large and widely used parasite database, the Global Mammal Parasite Database (GMPD). We created artificial datasets of host–parasite interactions based on the structure of the GMPD, then used these datasets to evaluate which methods best control for differential sampling effort. We evaluated the precision and bias of seven methods, including species accumulation and nonparametric diversity estimators, compared to analyzing the raw data without controlling for sampling variation. We find that nonparametric estimators, and particularly the Chao2 and second-order jackknife estimators, perform better than other methods. However, these estimators still perform poorly relative to systematic sampling, and effect sizes should be interpreted with caution because they tend to be lower than actual effect sizes. Overall, these estimators are more effective in comparative studies than for producing true estimates of diversity. We make recommendations for future sampling strategies and statistical methods that would improve estimates of global parasite diversity.     

β‐amyloid model core peptides: Effects of hydrophobes and disulfides

The mechanism by which a disordered peptide nucleates and forms amyloid is incompletely understood. A central domain of β‐amyloid (Aβ21–30) has been proposed to have intrinsic structural propensities that guide the limited formation of structure in the process of fibrillization. In order to test this hypothesis, we examine several internal fragments of Aβ, and variants of these either cyclized or with an N‐terminal Cys. While Aβ21–30 and variants were always monomeric and unstructured (circular dichroism (CD) and nuclear magnetic resonance spectroscopy (NMRS)), we found that the addition of flanking hydrophobic residues in Aβ16–34 led to formation of typical amyloid fibrils. NMR showed no long‐range nuclear overhauser effect (nOes) in Aβ21–30, Aβ16–34, or their variants, however. Serial ¹H‐¹⁵N‐heteronuclear single quantum coherence spectroscopy, ¹H‐¹H nuclear overhauser effect spectroscopy, and ¹H‐¹H total correlational spectroscopy spectra were used to follow aggregation of Aβ16–34 and Cys‐Aβ16–34 at a site‐specific level. The addition of an N‐terminal Cys residue (in Cys‐Aβ16–34) increased the rate of fibrillization which was attributable to disulfide bond formation. We propose a scheme comparing the aggregation pathways for Aβ16–34 and Cys‐Aβ16–34, according to which Cys‐Aβ16–34 dimerizes, which accelerates fibril formation. In this context, cysteine residues form a focal point that guides fibrillization, a role which, in native peptides, can be assumed by heterogeneous nucleators of aggregation.     

Sierra Nevada mountain lake microbial communities are structured by temperature,resources and geographic location

Warming, eutrophication (nutrient fertilization) and brownification (increased loading of allochthonous organic matter) are three global trends impacting lake ecosystems. However, the independent and synergistic effects of resource addition and warming on autotrophic and heterotrophic microorganisms are largely unknown. In this study, we investigate the independent and interactive effects of temperature, dissolved organic carbon (DOC, both allochthonous and autochthonous) and nitrogen (N) supply, in addition to the effect of spatial variables, on the composition, richness, and evenness of prokaryotic and eukaryotic microbial communities in lakes across elevation and N deposition gradients in the Sierra Nevada mountains of California, USA. We found that both prokaryotic and eukaryotic communities are structured by temperature, terrestrial (allochthonous) DOC and latitude. Prokaryotic communities are also influenced by total and aquatic (autochthonous) DOC, while eukaryotic communities are also structured by nitrate. Additionally, increasing N availability was associated with reduced richness of prokaryotic communities, and both lower richness and evenness of eukaryotes. We did not detect any synergistic or antagonistic effects as there were no interactions among temperature and resource variables. Together, our results suggest that (a) organic and inorganic resources, temperature, and geographic location (based on latitude and longitude) independently influence lake microbial communities; and (b) increasing N supply due to atmospheric N deposition may reduce richness of both prokaryotic and eukaryotic microbes, probably by reducing niche dimensionality. Our study provides insight into abiotic processes structuring microbial communities across environmental gradients and their potential roles in material and energy fluxes within and between ecosystems.