Optimality principles explaining divergent responses of alpine vegetation to environmental change

Recent increases in vegetation greenness over much of the world reflect increasing CO₂ globally and warming in cold areas. However, the strength of the response to both CO₂ and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (F_max) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year⁻¹ in drier regions and a browning of 0.12 ± 0.08% year⁻¹ in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in F_max with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year⁻¹) and browning (0.07 ± 0.06% year⁻¹). We also predicted the observed reduced sensitivities of F_max to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces F_max in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO₂ stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.     

Emetic material associated with Fusarium species in cereal grains and artificial media

Substances which cause emesis in pigeons were extracted from corn (Zea mays) artificially inoculated with Fusarium graminearum and from liquid culture medium inoculated with F. moniliforme, F. roseum, F. poae, F. culmorum, and F. nivale. Emetic preparations were obtained also from infected wheat (Triticum aestivum L. em. Thell), (Hordeum vulgare L. em. Lam), and durum (Triticum durum Desf). Partial purification resulted from chromatography with columns of cellulose and DEAE cellulose and with thin layers of silica gel. Two active materials were obtained from liquid culture of F. moniliforme but only one from infected cereals. Emetic preparations from F. moniliforme and infected cereals contained a polypeptide as a minor component. Ultraviolet and infrared spectrums, elemental analyses, refractive indices, and amino acid composition of the emetic from corn and one of the emeties from liquid culture of F. moniliforme were similar but not identical. Attempts to crystalline these emetics and to characterize them were unsuccessful.     

Statistical uncertainty in forest composition estimates obtained from fossil pollen spectra via the R-value model

Estimates of past forest composition obtained from Late Quaternary pollen spectra via a calibration of modern pollen spectra in terms of species abundances are subject to various sources of error, whose combined effect requires statistical analysis. Two statistical procedures, the maximum likelihood method and an approach using series expansions, are used to estimate standard deviations associated with forest composition estimates obtained via the R-value method of calibration. The two approaches yield similar values. The series expansion method also allows one to allocate pollen counting effort between fossil and modern samples in such a way as to maximize the precision of the final estimates. M.B. Davis's original controversial estimates of early Holocene forest composition in Vermont, U.S.A., are shown to have been vitiated by statistical errors. The optimum allocation procedure here suggests increasing the relative effort put into the modern count. This change would have improved but not rescued the estimates; omission of Larix, however, led to a substantial reduction in the errors. Exceptionally poor pollen producers such as Larix should generally be excluded from quantitative calibration; the remaining taxa should be calibrated on the basis of large samples of pollen, the modern pollen being collected preferably from a network of surface sampling sites.     

Global leaf-trait mapping based on optimality theory

Aim

Leaf traits are central to plant function, and key variables in ecosystem models. However recently published global trait maps, made by applying statistical or machine-learning techniques to large compilations of trait and environmental data, differ substantially from one another. This paper aims to demonstrate the potential of an alternative approach, based on eco-evolutionary optimality theory, to yield predictions of spatio-temporal patterns in leaf traits that can be independently evaluated.

Innovation

Global patterns of community-mean specific leaf area (SLA) and photosynthetic capacity (V_cmax) are predicted from climate via existing optimality models. Then leaf nitrogen per unit area (N_area) and mass (N_mass) are inferred using their (previously derived) empirical relationships to SLA and V_cmax. Trait data are thus reserved for testing model predictions across sites. Temporal trends can also be predicted, as consequences of environmental change, and compared to those inferred from leaf-level measurements and/or remote-sensing methods, which are an increasingly important source of information on spatio-temporal variation in plant traits.

Main conclusions

Model predictions evaluated against site-mean trait data from > 2,000 sites in the Plant Trait database yielded R² = 73% for SLA, 38% for N_mass and 28% for N_area. Declining species-level N_mass, and increasing community-level SLA, have both been recently reported and were both correctly predicted. Leaf-trait mapping via optimality theory holds promise for macroecological applications, including an improved understanding of community leaf-trait responses to environmental change.     

Thymic function and T cell parameters in a natural human experimental model of seasonal infectious diseases and nutritional burden

Background  

The study exploits a natural human experimental model of subsistence farmers experiencing chronic and seasonally modified food shortages and infectious burden. Two seasons existed, one of increased deprivation and infections (Jul-Dec), another of abundance and low infections (Jan-Jun); referred to as the hungry/high infection and harvest/low infection seasons respectively. Prior analysis showed a 10-fold excess in infectious disease associated mortality in young adults born in the hungry/high infection versus harvest/low infection season, and reduced thymic output and T cell counts in infancy. Here we report findings on the role of early life stressors as contributors to the onset of T cell immunological defects in later life.     

Genetic structure in the species-pair Silene vulgaris and S. uniflora (Caryophyllaceae) on the Baltic island of Öland

Allozyme data were used to assess the genetic structure between 37 sympatric populations of the species-pair Stlene vulgaris and S uniflora ssp petraea, and to infer levels of intra- and interspecific gene flow in the two species Silene vulgaris is a geographically widespread weed of disturbed habitats whereas S uniflora ssp petraea is endemic to the Baltic islands of Oland and Gotland On Oland, Silene vulgaris forms extensive linear populations along roads while S uniflora ssp petraea occurs in sparse and spatially-separated populations in open limestone habitats Despite the differences in population size and structure between the two species, both species show extremely low levels of between-population differentiation Between-site differences account for <2% of the total allozyme diversity within Oland in S vulgaris, and < 1% in S uniflora ssp petraea Indirect estimates of gene flow are high for both species (Nm = 11 and 27, respectively) There is no relationship between genetic distance and geographic distance within either species, and the lack of genetic structure is consistent with the pollination biology of the species - both of which are predominantly moth-pollinated The two species hybridize in intermediate habitats, and the geographic distribution of species-characteristic alleles indicates a potential for spatially extensive interspecific gene flow Nevertheless, there are significant differences in allele frequencies between the two species and multivariate analyses show no overlap between populations of the two species The species are ecologically separated by their different habitat preferences and by differences in their flowering phenology There is no evidence that the endemic S uniflora ssp petraea is threatened by genetic contamination or assimilation by the widespread weed, S vulgaris