Biodiversity Patterns and Ecological Preferences of the Photobionts Associated With the Lichen-Forming Genus Parmelia

The worldwide, ecologically relevant lichen-forming genus Parmelia currently includes 41 accepted species, of which the Parmelia sulcata group (PSULgp) and the Parmelia saxatilis group (PSAXgp) have received considerable attention over recent decades; however, phycobiont diversity is poorly known in Parmelia s. lat. Here, we studied the diversity of Trebouxia microalgae associated with 159 thalli collected from 30 locations, including nine Parmelia spp.: P. barrenoae, P. encryptata, P. ernstiae, P. mayi, P. omphalodes, P. saxatilis, P. serrana, P. submontana, and P. sulcata. The mycobionts were studied by carrying out phylogenetic analyses of the nrITS. Microalgae genetic diversity was examined by using both nrITS and LSU rDNA markers. To evaluate putative species boundaries, three DNA species delimitation analyses were performed on Trebouxia and Parmelia. All analyses clustered the mycobionts into two main groups: PSULgp and PSAXgp. Species delimitation identified 13 fungal and 15 algal species-level lineages. To identify patterns in specificity and selectivity, the diversity and abundance of the phycobionts were identified for each Parmelia species. High specificity of each Parmelia group for a given Trebouxia clade was observed; PSULgp associated only with clade I and PSAXgp with clade S. However, the degree of specificity is different within each group, since the PSAXgp mycobionts were less specific and associated with 12 Trebouxia spp., meanwhile those of PSULgp interacted only with three Trebouxia spp. Variation-partitioning analyses were conducted to detect the relative contributions of climate, geography, and symbiotic partner to phycobiont and mycobiont distribution patterns. Both analyses explained unexpectedly high portions of variability (99 and 98%) and revealed strong correlations between the fungal and algal diversity. Network analysis discriminated seven ecological clusters. Even though climatic conditions explained the largest proportion of the variation among these clusters, they seemed to show indifference relative to climatic parameters. However, the cluster formed by P. saxatilis A/P. saxatilis B/Trebouxia sp. 2/Trebouxia sp. S02/Trebouxia sp. 3A was identified to prefer cold-temperate as well as humid summer environments.

The Relative Importance of Human Disturbance, Environmental and Spatial Factors on the Community Composition of Wetland Birds

The present study investigates the relative importance of human disturbance, local environmental and spatial factors on variations in bird community composition in natural Ethiopian wetlands with high biodiversity conservation value. We quantified bird abundances, local environmental variables and human disturbances at 63 sites distributed over ten wetlands in two subsequent years. Variation partitioning analyses were used to explore the unique and shared contributions of human disturbance, local environmental variables and spatial factors on variations in community compositions of wetland bird species. Local environmental variables explained the largest amount of compositional variation of wetland bird species. Productivity-related variables were the most important local environmental variables determining bird community composition. Human disturbance was also an important determinant for wetland bird community composition and affected the investigated communities mainly indirectly through its effect on local environmental conditions. Spatial factors only played a minor role in variations in bird community composition. Our study highlights the urgent need for integrated management approaches that consider both nature conservation targets and socio-economic development of the region for the sustainable use and effective conservation of wetland resources.

Deciphering Main Climate and Edaphic Components Driving Oat Adaptation to Mediterranean Environments

Oat, Avena sativa, is an important crop traditionally grown in cool-temperate regions. However, its cultivated area in the Mediterranean rim steadily increased during the last 20 years due to its good adaptation to a wide range of soils. Nevertheless, under Mediterranean cultivation conditions, oats have to face high temperatures and drought episodes that reduce its yield as compared with northern regions. Therefore, oat crop needs to be improved for adaptation to Mediterranean environments. In this work, we investigated the influence of climatic and edaphic variables on a collection of 709 Mediterranean landraces and cultivars growing under Mediterranean conditions. We performed genotype–environment interaction analysis using heritability-adjusted genotype plus genotype–environment biplot analyses to determine the best performing accessions. Further, their local adaptation to different environmental variables and the partial contribution of climate and edaphic factors to the different agronomic traits was determined through canonical correspondence, redundancy analysis, and variation partitioning. Here, we show that northern bred elite cultivars were not among the best performing accessions in Mediterranean environments, with several landraces outyielding these. While all the best performing cultivars had early flowering, this was not the case for all the best performing landraces, which showed different patterns of adaption to Mediterranean agroclimatic conditions. Thus, higher yielding landraces showed adaptation to moderate to low levels of rain during pre- and post-flowering periods and moderate to high temperature and radiation during post-flowering period. This analysis also highlights landraces adapted to more extreme environmental conditions. The study allowed the selection of oat genotypes adapted to different climate and edaphic factors, reducing undesired effect of environmental variables on agronomic traits and highlights the usefulness of variation partitioning for selecting genotypes adapted to specific climate and edaphic conditions.

Modern pollen–climate relationships and their application for pollen-based quantitative climate reconstruction of the mid-Holocene on the southern Korean Peninsula

A modern pollen dataset is a prerequisite for reconstructing quantitative paleoclimate and paleovegetation cover using fossil pollen records. Although multiple modern pollen–climate datasets have been established covering a wide range of climate conditions, such datasets are exceedingly rare for the Korean Peninsula (KP). In this study, we acquired a modern pollen dataset from 198 surface soil samples collected on 37 mountains on the southern KP. Redundancy analysis (RDA) and variation partitioning results identified mean annual temperature (Tann) as the most important climate variable shaping pollen assemblages on the southern KP. Using the pollen–climate relationships inferred from the RDA, we applied the Huisman–Olff–Fresco model and determined that arboreal pollen taxa responded sensitively to the climatic gradient, whereas non-arboreal pollen taxa did not. We applied weighted averaging–partial least squares (WA-PLS) and the modern analog technique (MAT) to the pollen dataset, and a comparison of the results showed that MAT performed better than WA-PLS. A transfer function was applied to fossil pollen records from the areas covered by our dataset; the results confirmed that annual precipitation (Pann) and Tann were modulated by different mechanisms, with Pann strongly affected by El Niño–Southern Oscillation-driven typhoons during the Holocene, whereas Tann was mainly influenced by the Tsushima Warm Current from 7500 to 5100 cal yr BP depending on Kuroshio Current inflow intensity, and subsequently followed by the East Asian winter monsoon during 5100–3400 cal yr BP.

The Relative Importance of Niche Process and Neutral Process in the Community Assembly of Subtropical Karst Forest: A Perspective on the Changes of Species Distribution Patterns at Different Scales

Background and aimsThe importance of niche processes and neutral processes to community assembly has been affirmed by most studies, although their relative importance needs to be determined in many systems. Moreover, as the spatial scale changes, the ecological processes that determine the community pattern may differ. We tested these ideas in subtropical karst forest in southwestern China in order to aid efforts of community reconstruction.MethodsTo test the importance of niche-based and neutral mechanisms we compared the fit six models to the observed SAD of the plot at three different sampling scales (10 m × 10 m, 20 m × 20 m, 50 m × 50 m). We also used spatial autocorrelation and distance-based Moran's eigenvector maps (dbMEM) combined with variation partitioning to further determine the relative contribution of the niche process and the neutral process under different sampling scales.ResultsThe neutral theoretical and statistical models fit the observed species abundance distribution curve best at each sampling scale. And variation partitioning showed that although the contribution of spatial structure was lower at larger sampling scales, it was still important, suggesting that neutral processes drive community structure at all sampling scales. In contrast, habitat filtering and interspecies competition may lead to a net weakening of the contribution of the niche process to the species abundance pattern of the community because they act in opposite directions. ConclusionsIn the restoration and reconstruction of local karst forest communities, environmental heterogeneity, inter-species relationships, and geographic spatial differences should all be considered.

Effects of biodiversity, stand factors and functional identity on biomass and productivity during the restoration of subtropical forests in Central China

Aims Biodiversity is found to have a significant promotion effect on ecosystem functions in manipulation experiments on grassland communities. However, its relative role compared with stand factors or functional identity is still controversial in natural forests. Here we examined their relative effects on biomass and productivity during forest restoration. Methods We investigated stand biomass and productivity for 24 plots (600 m 2) across restoration stages in the subtropical forests of Mt. Shennongjia, central China. We measured five key functional traits and calculated functional diversity (functional richness, evenness, and dispersion) and community-weighted mean (CWM) of traits. We used general linear models (GLMs), variation partitioning methods to test the relative importance of stand factors (density, stand age, maximum height, etc.), functional identity, species and functional diversity on biomass and productivity. Important Findings Our results illustrated that stand biomass and productivity increased significantly as forest restoration, and that community species richness increased significantly, while functional dispersion decreased significantly. Variation partitioning analyses showed that diversity had no significant pure effects on biomass and productivity. However, diversity can affect biomass and productivity through the joint effect with stand factors and functional identity. Overall, we found that stand factors had the strongest effect on biomass and productivity, while functional identity significantly affects productivity but not biomass, suggesting that modulating stand structure and species identity are effective ways to enhance forest carbon storage and sequestrations potential in forest management.

Polychaete (Annelida) Diversity Patterns in Southern Gulf of Mexico: The Influence of Spatial Structure and Environmental Variables

A comprehensive database was built to examine the spatial diversity patterns of polychaete species from the continental shelf in Southern Gulf of Mexico. Using Cluster and nMDS analysis we found the composition of polychaete species to be different between the terrigenous and carbonate regions of the Gulf. To test the relative importance of spatial and environmental components in the polychaetae community structure in the Southern Gulf of Mexico, we examined the spatial relationships between polychaetae assemblages and environmental variables over broad geographical scales. A distance-based redundancy analysis (dbRDA) and variation partitioning was used to quantify the relative importance of these explanatory variables on the spatial variations of species richness and composition. Variation partitioning is an important tool to investigate the importance of spatial structure to species distribution in communities, but it has not yet been used in marine ecosystems. The significance level of spatial and environmental components to the distribution of polychaete species showed that the combined effect of spatial processes and sediment characteristics explained a higher percentage of variance than those parameters could alone.

Effects of Age, Diet CP, NDF, EE, and Starch on the Rumen Bacteria Community and Function in Dairy Cattle

To understand the effects of diet and age on the rumen bacterial community and function, forty-eight dairy cattle at 1.5 (M1.5), 6 (M6), 9 (M9), 18 (M18), 23 (M23), and 27 (M27) months old were selected. Rumen fermentation profile, enzyme activity, and bacteria community in rumen fluid were measured. The acetate to propionate ratio (A/P) at M9, M18, and M23 was higher than other ages, and M6 was the lowest (p < 0.05). The total volatile fatty acid (TVFA) at M23 and M27 was higher than at other ages (p < 0.05). The urease at M18 was lower than at M1.5, M6, and M9, and the xylanase at M18 was higher than at M1.5, M23, and M27 (p < 0.05). Thirty-three bacteria were identified as biomarkers of the different groups based on the linear discriminant analysis (LDA) when the LDA score >4. The variation partitioning approach analysis showed that the age and diet had a 7.98 and 32.49% contribution to the rumen bacteria community variation, respectively. The richness of Succinivibrionaceae_UCG-002 and Fibrobacter were positive correlated with age (r > 0.60, p < 0.01) and positively correlated with TVFA and acetate (r > 0.50, p < 0.01). The Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans has a positive correlation (r > 0.80, p < 0.05) with diet fiber and a negative correlation (r < −0.80, p < 0.05) with diet protein and starch, which were also positively correlated with the acetate and A/P (r > 0.50, p < 0.01). The genera of Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans could be worked as the target bacteria to modulate the rumen fermentation by diet; meanwhile, the high age correlated bacteria such as Succinivibrionaceae_UCG-002 and Fibrobacter also should be considered when shaping the rumen function.

Variation partitioning in double-constrained multivariate analyses: linking communities, environment, space, functional traits, and ecological niches

Constrained multivariate analysis is a common tool for linking ecological communities to environment. The follow-up is the development of the double-constrained correspondence analysis (dc-CA), integrating traits as species-related predictors. Further, methods have been proposed to integrate information on phylogenetic relationships and space variability. We expand this framework, proposing a dc-CA-based algorithm for decomposing variation in community structure and testing the simple and conditional effects of four sets of predictors: environment characteristics and space configuration as predictors related to sites, while traits and niche (dis)similarities as species-related predictors. In our approach, ecological niches differ from traits in that the latter are distinguished by and characterize the individual level, while niches are measured on the species level, and when compared, they are characteristics of communities and should be used as separate predictors. The novelties of this approach are the introduction of new niche parameters, niche dissimilarities, synthetic niche-based diversity which we related to environmental features, the development of an algorithm for the full variation decomposition and testing of the community–environment–niche–traits–space (CENTS) space by dc-CAs with and without covariates, and new types of diagrams for the results. Applying these methods to a dataset on freshwater mollusks, we learned that niche predictors may be as important as traits in explaining community structure and are not redundant, overweighting the environmental and spatial predictors. Our algorithm opens new pathways for developing integrative methods linking life, environment, and other predictors, both in theoretical and practical applications, including assessment of human impact on habitats and ecological systems.