Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

In this study we examined ecosystem respiration (R_ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R_ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R_ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R_ECO. The maximum seasonal leaf area index (LAI_MAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T_ref=15 °C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r²=0.52, P<0.001, n=104) even within each PFT. Besides LAI_MAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N_depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI_MAX) which performed well in predicting the spatio‐temporal variability of R_ECO, explaining >70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.     

Density‐dependent polyphenism and geographic variation in size among two populations of lubber grasshoppers (Romalea microptera)

1. Density‐dependent phase polyphenism occurs when changes in density during the juvenile stages result in a developmental shift from one phenotype to another. Density‐dependent phase polyphenism is common among locusts (Orthoptera: Acrididae). 2. Previously, we demonstrated a longitudinal geographic cline in adult body size (western populations = small adults; eastern populations = large adults) in the eastern lubber grasshopper (Romalea microptera) in south Florida. As lubbers are confamilial with locusts, we hypothesised that the longitudinal size cline was partly due to density‐dependent phase polyphenism. 3. We tested the effect of density, population, and density×population interaction on life‐history traits (pronotum length, mass, cumulative development time, growth rate) of, and proportion surviving to, each of the five instars and the adult stage in a 2 × 3 factorial laboratory experiment with two lubber populations, each reared from hatchling to adult at three different densities. 4. The effect of density on life history and survival was independent of the effects of population on life history and survival. Higher densities led to larger adult sizes (pronotum, mass) and lower survivorship. The western population had smaller adult masses, fewer cumulative days to the adult stage, and higher survivorship than the eastern population. 5. Our data suggest that lubber grasshoppers exhibit density‐dependent phase polyphenism initiated by the physical presence of conspecifics. However, the plastic response of adult size to density observed in the laboratory is not consistent with the relationship between phenotypes and adult density in the field. Genetic differences between populations observed in the laboratory could contribute to size and life‐history differences among lubber populations in the field.     

Tracking genes of ecological relevance using a genome scan in two independent regional population samples of Arabis alpina

Understanding the genetic basis of adaptation in response to environmental variation is fundamental as adaptation plays a key role in the extension of ecological niches to marginal habitats and in ecological speciation. Based on the assumption that some genomic markers are correlated to environmental variables, we aimed to detect loci of ecological relevance in the alpine plant Arabis alpina L. sampled in two regions, the French (99 locations) and the Swiss (109 locations) Alps. We used an unusually large genome scan [825 amplified fragment length polymorphism loci (AFLPs)] and four environmental variables related to temperature, precipitation and topography. We detected linkage disequilibrium among only 3.5% of the considered AFLP loci. A population structure analysis identified no admixture in the study regions, and the French and Swiss Alps were differentiated and therefore could be considered as two independent regions. We applied generalized estimating equations (GEE) to detect ecologically relevant loci separately in the French and Swiss Alps. We identified 78 loci of ecological relevance (9%), which were mainly related to mean annual minimum temperature. Only four of these loci were common across the French and Swiss Alps. Finally, we discuss that the genomic characterization of these ecologically relevant loci, as identified in this study, opens up new perspectives for studying functional ecology in A. alpina, its relatives and other alpine plant species.