Genetic structure and differentiation in cultivated fig (Ficus carica L.)

One hundred ninety-four germplasm accessions of fig representing the four fig types, Common, Smyrna, San Pedro, and Caprifig were analyzed for genetic diversity, structure, and differentiation using genetic polymorphism at 15 microsatellite loci. The collection showed considerable polymorphism with observed number of alleles per locus ranging from four for five different loci, MFC4, LMFC14, LMFC22, LMFC31 and LMFC35 to nine for LMFC30 with an average of 4.9 alleles per locus. Seven of the 15 loci included in the genetic structure analyses exhibited significant deviation from panmixia, of which two showed excess and five showed deficiency of heterozygote. The cluster analysis (CA) revealed ten groups with 32 instances of synonymy among cultivars and groups differed significantly for frequency and composition of alleles for different loci. The principal components analysis (PCA) confirmed the results of CA with some groups more differentiated than the others. Further, the model based Bayesian approach clustering suggested a subtle population structure with mixed ancestry for most figs. The gene diversity analysis indicated that much of the total variation is found within groups (HG/HT = 0.853; 85.3%) and the among groups within total component (GGT = 0.147) accounted for the remaining 14.7%, of which ~64% accounted for among groups within clusters (GGC = 0.094) and ~36% among clusters (GCT = 0.053). The analysis of molecular variance (AMOVA) showed approximately similar results with nearly 87% of variation within groups and ~10% among groups within clusters, and ~3% among clusters. Overall, the gene pool of cultivated fig analyzed possesses substantial genetic polymorphism but exhibits narrow differentiation. It is evident that fig accessions from Turkmenistan are somewhat genetically different from the rest of the Mediterranean and the Caucasus figs. The long history of domestication and cultivation with widespread dispersal of cultivars with many synonyms has resulted in a great deal of confusion in the identification and classification of cultivars in fig

Covariation in Plant Functional Traits and Soil Fertility within Two Species-Rich Forests

The distribution of plant species along environmental gradients is expected to be predictable based on organismal function. Plant functional trait research has shown that trait values generally vary predictably along broad-scale climatic and soil gradients. This work has also demonstrated that at any one point along these gradients there is a large amount of interspecific trait variation. The present research proposes that this variation may be explained by the local-scale sorting of traits along soil fertility and acidity axes. Specifically, we predicted that trait values associated with high resource acquisition and growth rates would be found on soils that are more fertile and less acidic. We tested the expected relationships at the species-level and quadrat-level (20×20 m) using two large forest plots in Panama and China that contain over 450 species combined. Predicted relationships between leaf area and wood density and soil fertility were supported in some instances, but the majority of the predicted relationships were rejected. Alternative resource axes, such as light gradients, therefore likely play a larger role in determining the interspecific variability in plant functional traits in the two forests studied

Seasonal differences in leaf-level physiology give lianas a competitive advantage over trees in a tropical seasonal forest

Lianas are an important component of most tropical forests, where they vary in abundance from high in seasonal forests to low in aseasonal forests. We tested the hypothesis that the physiological ability of lianas to fix carbon (and thus grow) during seasonal drought may confer a distinct advantage in seasonal tropical forests, which may explain pan-tropical liana distributions. We compared a range of leaf-level physiological attributes of 18 co-occurring liana and 16 tree species during the wet and dry seasons in a tropical seasonal forest in Xishuangbanna, China. We found that, during the wet season, lianas had significantly higher CO2 assimilation per unit mass (Amass), nitrogen concentration (Nmass), and δ13C values, and lower leaf mass per unit area (LMA) than trees, indicating that lianas have higher assimilation rates per unit leaf mass and higher integrated water-use efficiency (WUE), but lower leaf structural investments. Seasonal variation in CO2 assimilation per unit area (Aarea), phosphorus concentration per unit mass (Pmass), and photosynthetic N-use efficiency (PNUE), however, was significantly lower in lianas than in trees. For instance, mean tree Aarea decreased by 30.1% from wet to dry season, compared with only 12.8% for lianas. In contrast, from the wet to dry season mean liana δ13C increased four times more than tree δ13C, with no reduction in PNUE, whereas trees had a significant reduction in PNUE. Lianas had higher Amass than trees throughout the year, regardless of season. Collectively, our findings indicate that lianas fix more carbon and use water and nitrogen more efficiently than trees, particularly during seasonal drought, which may confer a competitive advantage to lianas during the dry season, and thus may explain their high relative abundance in seasonal tropical forests

Determinants of change in subtropical tree diameter growth with ontogenetic stage

We evaluated the degree to which relative growth rate (RGR) of saplings and large trees is related to seven functional traits that describe physiological behavior and soil environmental factors related to topography and fertility for 57 subtropical tree species in Dinghushan, China. The mean values of functional traits and soil environmental factors for each species that were related to RGR varied with ontogenetic stage. Sapling RGR showed greater relationships with functional traits than large-tree RGR, whereas large-tree RGR was more associated with soil environment than was sapling RGR. The strongest single predictors of RGR were wood density for saplings and slope aspect for large trees. The stepwise regression model for large trees accounted for a larger proportion of variability (R 2 = 0.95) in RGR than the model for saplings (R 2 = 0.55). Functional diversity analysis revealed that the process of habitat filtering likely contributes to the substantial changes in regulation of RGR as communities transition from saplings to large trees. © 2014 Springer-Verlag Berlin Heidelberg

A theory for ecological survey methods to map individual distributions

Spatially explicit approaches are widely recommended for ecosystem management. The quality of the data, such as presence/absence or habitat maps, affects the management actions recommended and is, therefore, key to management success. However, available data are often biased and incomplete. Previous studies have advanced ways to resolve data bias and missing data, but questions remain about how we design ecological surveys to develop a dataset through field surveys. Ecological surveys may have multiple spatial scales, including the spatial extent of the target ecosystem (observation window), the resolution for mapping individual distributions (mapping unit), and the survey area within each mapping unit (sampling unit). We developed an ecological survey method for mapping individual distributions by applying spatially explicit stochastic models. We used spatial point processes to describe individual spatial placements using either random or clustering processes. We then designed ecological surveys with different spatial scales and individual detectability. We found that the choice of mapping unit affected the presence mapped fraction, and the fraction of the total individuals covered by the presence mapped patches. Tradeoffs were found between these quantities and the map resolution, associated with equivalent asymptotic behaviors for both metrics at sufficiently small and large mapping unit scales. Our approach enabled consideration of the effect of multiple spatial scales in surveys, and estimation of the survey outcomes such as the presence mapped fraction and the number of individuals situated in the presence detected units. The developed theory may facilitate management decision-making and inform the design of monitoring and data gathering