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This article examines how salespeople's personality traits influence their adaptive selling skills and exploited cross-selling potential. We collect both a cross-industry and cross-country dataset of 430 salespeople who engage in cross-selling activities. In contrast with prior research on the relationship between personality traits and general sales performance, we find none of the big-five personality traits to have a significant direct effect on the exploited cross-selling potential. However, drawing on the theory of self-monitoring, we find that the big-five traits have dimensionally varying, significant effects on adaptive selling skills. In turn, adaptive selling skills have a significant direct effect on exploited cross-selling potential. Moreover, our analyses reveal that the personality traits conscientiousness and extraversion have indirect positive effects on exploited cross-selling potential. These findings provide beneficial insights for human resources as well as human development practice in both recruiting and training initiatives. In particular, we provide guidance on how to hire and train the best personnel for intensive cross-selling sales positions in firms. In addition, we introduce new perspectives for research on the relationship between personality traits and performance measures by identifying the importance of possible mediators. [ABSTRACT FROM AUTHOR]

Microbes are essential for the functioning of all ecosystems, and as global warming and anthropogenic pollution threaten ecosystems, it is critical to understand how microbes respond to these changes. We investigated the climate response of Sphingomonas, a widespread gram-negative bacterial genus, during an 18-month microbial community reciprocal transplant experiment across a Southern California climate gradient. We hypothesized that after 18 months, the transplanted Sphingomonas clade and functional composition would correspond with site conditions and reflect the Sphingomonas composition of native communities. We extracted Sphingomonas sequences from metagenomic data across the gradient and assessed their clade and functional composition. Representatives of at least 12 major Sphingomonas clades were found at varying relative abundances along the climate gradient, and transplanted Sphingomonas clade composition shifted after 18 months. Site had a significant effect (PERMANOVA; P < 0.001) on the distribution of both Sphingomonas functional (R2 = 0.465) and clade composition (R2 = 0.400), suggesting that Sphingomonas composition depends on climate parameters. Additionally, for both Sphingomonas clade and functional composition, ordinations revealed that the transplanted communities shifted closer to the native Sphingomonas composition of the grassland site compared with the site they were transplanted into. Overall, our results indicate that climate and substrate collectively determine Sphingomonas clade and functional composition.IMPORTANCESphingomonas is the most abundant gram-negative bacterial genus in litter-degrading microbial communities of desert, grassland, shrubland, and forest ecosystems in Southern California. We aimed to determine whether Sphingomonas responds to climate change in the same way as gram-positive bacteria and whole bacterial communities in these ecosystems. Within Sphingomonas, both clade composition and functional genes shifted in response to climate and litter chemistry, supporting the idea that bacteria respond similarly to climate at different scales of genetic variation. This understanding of how microbes respond to perturbation across scales may aid in future predictions of microbial responses to climate change.

IntroductionMethodsKey results and discussionThere is an increasingly urgent need for knowledge of primary succession along glacier forelands in order to improve our understanding of biodiversity changes at high elevations. Bryophytes play a key ecological role in primary succession, especially in the early stages, but bryophyte colonisation on alpine glacier forelands is still poorly studied. We investigated the first stages of bryophyte primary succession along a chronosequence on a glacier foreland in the European Alps.Bryophytes on the Sforzellina glacier (Central Italian Alps) were sampled during the summer of 2022 in areas where the glacial front occurred in 1989, 2003, 2015 and 2019. At each site, six plots of 1 m × 1 m (5 m apart from each other) were sampled. For the most frequent species, plant and shoot size were measured to analyse growth trends throughout the succession.In total, 13 moss species and two liverwort species were found. The mean number of species increased with the number of years since deglaciation, following an ‘addition and persistence’ model. The first pioneer species, Pohlia filum (Schimp.) Mårtensson and Ptychostomum sp., were present only 3 years after deglaciation; the occurrence of bulbils may help the former colonise bare ground quickly. Sporophytes had appeared 7 years after deglaciation. In P. filum, both shoot and plant size increased during the first stages of succession but had decreased on 33-year-old substrates. This pattern could be related to the fact that this species usually occurs on soils with very low organic matter content. [ABSTRACT FROM AUTHOR]

Apple crops experience significant yield and quality losses due to the incidence of apple scab, caused by the fungal pathogen Venturia inaequalis. This study presents the development of six hybrid apple varieties for economically important traits such as scab resistance, high yield, better fruit quality and better pollinizer ability. Morphological characterization, biochemical analysis, and hybridity confirmation through S-allele typing were conducted. The scab-resistant variety 'Prima,' which carries the Vf resistance gene, was utilized as the donor. This resistance gene was introgressed into other commercially significant apple varieties. Three apple hybrids, viz., 'CITH-Priame' (CITH-Ambri-1 × Prima), 'CITH-PRIDE' (Red Delicious x Prima) and 'CITH-Pritor' (Top Red x Prima) were developed for scab resistance carrying Vf gene confirmed through three dominant markers (AM19, Rvi6 & U1400) and one codominant marker (AL07). The hybrids, viz., 'CITH-AMMOL' (CITH-Ambri-1 × Mollies Delicious) and 'CITH-Ambrit' (CITH-Ambri-1 × Top Red) were produced for the better fruit quality, having total soluble solids (TSS) of 13.06 and 13.8°Brix, respectively. One more apple hybrid 'CITH-Golden Snow' (Golden Delicious x Snowdrift) was identified as pollinizer with better quality traits. S-allele typing is being used for compatibility studies in apple through identification of suitable pollinizer. This is the first report for use of S-alleles in identification of hybrids. [ABSTRACT FROM AUTHOR]

Invasive species have been drivers of biodiversity loss and functional changes in aquatic ecosystems, including in protected areas. Therefore, monitoring population invasion dynamics and biological traits is fundamental to better understand their ecological and economic impacts and for management actions development. We followed signal crayfish (Pacifastacus leniusculus) invasion in Rabaçal River upper reach at Montesinho Natural Park, Portugal. We collected information on the spread and biological traits (abundance, size, weight, physical condition, sex ratio, and aggressiveness) to assess differences between invasion core and front areas and among years. Signal crayfish population remained restricted since first reports in 2013 in the invasion core until 2017. After 2019, signal crayfish population has been spreading downstream, decreasing abundance at invasion core but increasing at invasion front. Significant higher number of crayfish with claw loss indicate potential higher signs of aggressiveness in the invasion front. Results also demonstrate a significant dominance of females although sex ratio is closer to 1:1 at the invasion front. Overall, results indicate signal crayfish is spreading and increasing their abundance at Rabaçal River highlighting the need for immediate management actions to hold dispersion and mitigate possible impacts. [ABSTRACT FROM AUTHOR]

Brown cotton and white cotton are two important raw materials used in the cotton fiber industry. Clarifying the differences in morphology, agronomic traits, and fiber pigments between these varieties can facilitate the implementation of corresponding cultivation and breeding techniques. Therefore, we obtained F2 generation brown cotton plants through hybridization and compared them with their parents. In terms of agronomic traits, plant morphology and leaf shape were similar, but brown cotton presented more villi on the main stem. The first fruiting branch node was within the range of 4–6 cm, and the first fruiting branch node height was greater than that of TM-1, i.e., between 13.25 cm and 22.79 cm, with no difference compared with that of P26. The plant height was greater than that of the parents, and the number of bolls was essentially the same as that in TM-1 and greater than that in P26. The lint percentage and average fiber length were lower in TM-1 than in P26, and the seed index was greater than that in TM-1 and P26. Pigment measurements revealed that the chlorophyll a content in brown cotton during the boll stage was lower than that in white cotton, and the content of proanthocyanidin in the cotton fibers was greater in brown cotton than in white cotton. At 15 days after pollination, the highest content was 159.8 mg/g. To determine the differences in gene expression levels, we conducted transcriptome sequencing. Gene Ontology (GO) analysis revealed that the differentially expressed genes (DEGs) were enriched in pathways related to the cell wall and enzyme activity, whereas Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the DEGs were enriched in flavonoid synthesis pathways. Transcription factor analysis revealed that the expression of the MYB3 transcription factor (Ghir_D07G002110) was higher in brown cotton, and bioinformatics analysis revealed that this gene has regulatory effects on the CHS, CHI1, and F3H genes. [ABSTRACT FROM AUTHOR]

In the rainforests of the Guineo-Congolian region, several native tree species have been tested in plantations established with different silvicultural methods and objectives. The results of these experiments remained scattered, hampering our ability to identify the key drivers of variability in survival and growth of planted species. In this study, we carried out a systematic review of the literature. From 45 selected studies, a database was compiled of 89 native tree species planted in different forest types (evergreen, semideciduous and transition). The data included plantation age, survival, height and diameter growth. For each species, information was collected on the planting method (understorey, line planting, gap, degraded area, regrowth and clear-cut), and species functional traits (species guild, dispersal mode, wood density and leaf phenology). Tree survival, height and diameter growth were modelled using linear mixed-effect models. Tree survival depended mainly on plantation age, and mortality was the highest in the seven first years. However, survival did not significantly depend on planting method or species traits. In the study plantations, height and diameter growth depended on planting method and species guild. Diameter growth was negatively correlated with wood density. Pioneer, non-pioneer light-demanding and shade-tolerant species grew faster in diameter when planted in degraded areas and clear-cuts. Pioneer species grew the fastest in gaps. Although we did not find an effect of forest type on tree survival and growth, the variability between sites was substantial. This study provides empirical evidence that planting methods need to be adapted to the species guild. [ABSTRACT FROM AUTHOR]

The worldwide value of the honey bee as an agricultural animal is increasingly being recognized. Not only does the honey bee directly produce useful agricultural products, but also large portions of crops are dependent on the pollination activities of honey bees. Apis cerana (A. cerana), the native honey bee of China, is widely distributed in the country. Studying the biological environment and colony management of A. cerana is important for its conservation and breeding. This study investigated the apiculture of A. cerana among a total of 201 beekeepers in the eastern, southern, northwestern and central regions of China and conducted data analysis on the surveyed data. The results showed that the most favorite traits for beekeepers are colony size, colony health and honey production. Compared with Apis mellifera ligustica, A. cerana is more adaptable to low temperature and scattered nectar sources. The results help to optimize the breeding programs of A. cerana and further contribute to substantive breeding accomplishments with honey bees which have enhanced their role in modern agriculture. [ABSTRACT FROM AUTHOR]

Seagrass trait variation, which results from both local genetic adaptation and phenotypic plasticity, has important effects on ecosystems. Physical drivers underlie these processes and are important determinants of trait variation. Despite this, few studies examine multivariate predictive relationships between sets of physical drivers and sets of seagrass traits. Here, we use redundancy analysis to define this relationship for eelgrass Zostera marina, using traits that represent bed structure, morphology, and physiology and physical drivers that emphasize light conditions and temperature variability on different time scales. We found a relationship between plant size (i.e., leaf length and width, rhizome width, number of leaves) and shoot density that dominated the trait variation. Specifically, as temperatures became warmer, more variable, and light was less limiting, plants became smaller (shorter, narrower, and fewer leaves, thinner rhizomes) but beds became denser. Plant biomass (leaf area index), which increased with decreasing temperature variability and bottom light, further refined this relationship. Overall, temperature variability (i.e., daily temperature range, heat accumulation, time in the optimal temperature range, and tidal and meteorological variability), as well as bottom light, were important predictors of eelgrass traits. We further identified three distinct temperature-light regimes across which traits differed; these included the cool low variability temperature regime with low light, the warm high variability temperature regime with high light, and the intermediate case between these endpoints. Our study identifies specific temperature and light drivers that define certain eelgrass traits and provides a multivariate statistical model that can be used to predict eelgrass trait values from known physical conditions. [ABSTRACT FROM AUTHOR]

Entrepreneurship is the future, particularly for developing economies that are still striving to meet societal needs with the bare minimum of resources. With the urgency of entrepreneurship in South Africa, the study sought to investigate the influence of socioeconomic characteristics and personality traits on the sustainability of women agripreneurs. The study was conducted in the Mopani district of Limpopo province, South Africa. Structured questionnaires were administered to 119 women agripreneurs during face-to-face interviews. Descriptive statistics were used to gain insight into the distribution of socioeconomic characteristics among women agripreneurs. At the same time, a multinomial logistic regression model was used to determine the influence of socioeconomic characteristics and personality traits on the sustainability of female entrepreneurship. The study discovered that the sustainability of women agripreneurs during their start-up phase was significantly influenced by their hard work and resilience traits. At the same time, their traits of innovativeness and independence positively influenced their short-term sustainability. The long-term sustainability of the women agripreneurs was primarily influenced by their willingness to learn, household size, problem-solving, and can-do attitude. The study recommends that potential women agripreneurs be assisted in developing personality traits that enhance their sustainability during different phases of their businesses. The study findings imply the importance of considering the socioeconomic status and personality traits of potential agripreneurs when developing mechanisms to enhance their agribusiness sustainability. [ABSTRACT FROM AUTHOR]

Traditional methods of personality assessment, such as questionnaires and interviews, rely on self-reporting and subjective interpretation, which can be influenced by biases and social desirability. A handwriting-based approach offers an alternative method that provides non-verbal cues and unconscious expressions, supplementing traditional methods and potentially offering more objective insights, especially with an automated approach, into personality traits. Non-real-time methods take longer due to manual analysis, and are often subjective and prone to bias, while real-time analysis with a convolutional neural network (CNN) model provides instant results. Real-time tools would have no human intervention, are more convenient and easily accessible. Reducing human intervention through real-time analysis with a CNN model enhances the reliability, objectivity, scalability, and speed of the handwriting assessment process, providing a significant advantage over traditional methods. The proposed system focuses on the use of deep learning (DL) techniques to determine a person's personality by analyzing their handwriting. With the use of deep learning, human intervention is much less, thus the variance in the results is also much less which ultimately increases precision in the final predictions or results. Not only does the project predict personality traits through handwriting analysis, but also does that in a real-time environment. Steps such as preprocessing, feature extraction, and label classification are involved in the prediction process. CNN model has been used in the proposed system, for the final Personality Prediction. The CNN model for handwriting analysis must balance speed and accuracy through efficient architecture design and parameter optimization, minimizing computational complexity and inference time. To achieve this challenge two models (or versions) were built, the second having better data augmentation with respect to image sizing to be given to the CNN Network. Performance using the evaluation metrics was calculated with a testing efficiency of 0.71 in model 1 and 0.74 in model 2 and 82% accuracy was obtained on this real-time data. [ABSTRACT FROM AUTHOR]

Cashew is a tree of great commercial importance. The demand for cashew nuts and by-products is increasing. An increase in cashew production is possible through genetic enhancement by effective utilization of germplasm. However, the utility of cashew germplasm in the breeding programme is limited by the lack of reliable data on germplasm characterizations. In this research study, we identified 11 germplasm accessions with unique traits through a genebank survey and evaluated them for morphological and biochemical characteristics and genetic diversity. Morphological characterization revealed significant variations, and high variability was observed for qualitative characteristics like nut stylar region width, cashew apple shape, and color. The morphometric traits such as the cashew nut, kernel, and cashew apple dimensions and weights also showed great variability. The correlation analysis showed that the nut weight had strong correlations with traits like kernel weight (r = 0.95) and shell thickness (r = 0.95). Biochemical analysis for cashew nut shell liquid (CNSL), kernel oil, and cashew apple juice content and TSS showed significant variations in the tested accessions. Correlations were observed between CNSL content and shell thickness. Further, genetic diversity analysis of accessions using nine genic simple sequence repeats (SSRs) detected a sum of 64 alleles, and the accessions were divided into three major clusters by the neighbor-joining method. This study confirms that the identified accessions are genetically diverse and are promising candidates for varietal development. The correlations between characters indicated the scope for simultaneous selections for the strongly correlated characters with economic importance. [ABSTRACT FROM AUTHOR]

Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a "top 10" list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Recent studies have demonstrated regional differences in marine ecosystem C:N:P with implications for carbon and nutrient cycles. Due to strong co-variance, temperature and nutrient stress explain variability in C:N:P equally well. A reductionistic approach can link changes in individual environmental drivers with changes in biochemical traits and cell C:N:P. Thus, we quantified effects of temperature and nutrient stress on Synechococcus chemistry using laboratory chemostats, chemical analyses, and data-independent acquisition mass spectrometry proteomics. Nutrient supply accounted for most C:N:Pcell variability and induced tradeoffs between nutrient acquisition and ribosomal proteins. High temperature prompted heat-shock, whereas thermal effects via the translation-compensation hypothesis were only seen under P-stress. A Nonparametric Bayesian Local Clustering algorithm suggested that changes in lipopolysaccharides, peptidoglycans, and C-rich compatible solutes may also contribute to C:N:P regulation. Physiological responses match field-based trends in ecosystem stoichiometry and suggest a hierarchical environmental regulation of current and future ocean C:N:P.

For decades researches have been conducted in Ethiopia to improve wheat productivity and quality. This involved extensive selection of breeding lines based on agronomic and laboratory data from numerous trials. However, generating laboratory data for all these services was both time-consuming and expensive. Hence, the study aimed to develop a very rapid and cost-effective testing method for wheat genotypes and varieties using near-infrared spectroscopy. For this purpose, we collected 155 bread wheat samples from high-growing potential areas of Sinana, Kulumsa, and Holeta. The wet chemistry analysis was done in duplicate following the international standard official methods. The same samples were also scanned using TANGO’S Bruker NIRS machine in duplicate to acquire spectral data. A calibration model was then developed by fitting the reference and spectral data using the partial least square (PLS). The calibration models exhibited a high level of strength for all parameters. The performance of the calibration model for protein (R2 = 0.99; RPD = 9.63), moisture (R2 = 0.96; RPD = 5.29), ash (R2 = 0.98; RPD = 6.39), total gluten (R2 = 0.98; RPD = 8.09), dry gluten (R2 = 0.97; RPD = 5.57), gluten index (R2 = 0.96; RPD = 5.23), and falling number (R2 = 0.97 and RPD = 6.23) were deemed suitable for wheat process and quality control purposes. But the models for moisture and gluten index (R2 = 0.96) were found to be suitable for screening and simple quality control purposes only. Therefore, this study clearly demonstrated that the near-infrared spectroscopy model is a highly reliable and robust method for predicting the key quality traits of bread wheat grains, serving the needs of both breeding programs and industry raw material control.

Abstract The genus amaranth is comprised of 60–70 species. This climate hardy plant is grown as a vegetable as well as cereal crop in many areas of the world. Current study multivariate analysis was used to characterize the exotic vegetable amaranth genotypes. The experiment was conducted in the research area of Muhammad Nawaz Shareef University of Agriculture, Multan under RCBD design with three replications of 50 exotic amaranth genotype. 22 different variables were investigated for the principal component and cluster analysis using different software packages in R studio. According to the results of principal component analysis the first five PCs had eigenvalues greater than one and they explained the 84.59% diversity in exotic vegetable amaranth accessions. First two principal components explained 57.31% of variation. Traits that loaded highly for first PC include moisture (-0.892), carbohydrates (0.938), energy (0.920), stomatal conductance (0.803), net photosynthesis (0.795) and dry weight (0.770). The traits which impacted the second PC highly include protein (0.692), fat (-0.571), nitrogen (0.692), calcium (0.545), phosphorus (0.908), zinc (0.960), iron (0.826) and potassium (0.872). For future breeding program the selection based on these results will be effective for crop enhancement drive in exotic vegetable amaranth genotypes. Hierarchical clustering was done and dendrogram split the 50 genotypes into 5 groups using silhouette method. The pairwise clustering revealed that intra cluster distance is smaller than inter cluster distance. The maximum inter cluster distance was observed between cluster I and II (9.88); between cluster I and III (9.47); between cluster II and IV (9.27). Clinical trial number Clinical trial number not applicable.

Societal Impact Statement Summary The rapid global loss of biodiversity, especially in the Neotropics, underscores the need to understand how deforestation impacts endemic plant species' extinction risk and conservation status. Due to limited ranges and habitat specialization, endemics are particularly vulnerable. Our study reveals that around 14% and 47% of Ecuadorian Amazon endemic trees are Critically Endangered and Endangered, respectively, with 41% facing high extinction risk. Traits like life‐form, fruit size, and height relate to extinction vulnerability. These findings highlight the factors driving Amazonian tree flora endangerment, providing crucial insights for conservation efforts of this fundamental component of Amazon hyper‐diverse forests. Comprehensive analyses of the global conservation statuses of endemic tree species are scarce, especially for species‐rich forests. Endemic trees arguably suffer a higher extinction risk than other plant species due to their restricted geographic range and habitat specialization. Here, we present an updated assessment of the conservation status and extinction risk estimates for the endemic tree flora of the Ecuadorian Amazon, a darkspot of biodiversity. We combined an extensively verified taxonomic database of Amazon tree species abundance and occurrence with the most updated data of deforestation for this region. We found that approximately one sixth of the Ecuadorian Amazon endemic tree flora is Critically Endangered. A few clades, including Myrtaceae, Elaeocarpaceae, Fabaceae s.l., and Lauraceae, harbor one third of the Critically Endangered endemic tree species. According to our analysis, the extinction risk for endemic trees is associated not only with extrinsic factors such as deforestation but also with their ecology. Life‐form, fruit size, and maximum height are significantly related to extinction risk. Thus, endemic understory and canopy trees with small fruits are more prone to suffer extinction than emergent tree species. We argue that assessment programs should also include biological trait information in addition to geographic ranges and habitat specialization for the establishment of effective conservation strategies of this hyper‐diverse region of the Amazon. [ABSTRACT FROM AUTHOR]

This study elucidates to generate a linkage map for Portuguese oysters, Crassostrea angulata, and recognise potential markers linked to economical traits in C. angulata. Genome-wide association studies (GWAS) using 19,475 single nucleotide polymorphisms (SNPs) generated by a genotyping-by-sequencing approach consisting of 647 individuals in two selection generations of C. angulata, consisting of 57 full-sib family of the first generation and 33 full-sib family of the second generation. GWAS identified six significant SNPs linked to whole weight (P < 10−4). These six SNPs explained 10.2% of the total genetic variance of whole weight. Additionally, three SNPs were identified linked to meat yield (i.e., soft tissue weight) and contributed to 9.2% of the total genetic variance for this trait. By linkage analysis on the raw data, a total of 19,475 SNP markers were mapped to 10 linkage groups, with an average density of 19.1 SNPs per cM. This linkage map was developed and potential markers identified for whole weight and soft tissue weight provide a novel resource to characterise the genetic structure of economic traits in C. angulata. [ABSTRACT FROM AUTHOR]

Premise: In the Amazon basin, seasonally flooded (SF) forests offer varying water constraints, providing an excellent way to investigate the role of habitat selection on microbial communities within plants. However, variations in the microbial community among host plants cannot solely be attributed to environmental factors, and how plant traits contribute to microbial assemblages remains an open question. Methods: We described leaf‐ and root‐associated microbial communities using ITS2 and 16 S high‐throughput sequencing and investigated the stochastic‐deterministic balance shaping these community assemblies using two null models. Plant ecophysiological functioning was evaluated by focusing on 10 leaf and root traits in 72 seedlings, belonging to seven tropical SF tree species in French Guiana. We then analyzed how root and leaf traits drove the assembly of endophytic communities. Results: While both stochastic and deterministic processes governed the endophyte assembly in the leaves and roots, stochasticity prevailed. Discrepancies were found between fungi and bacteria, highlighting that these microorganisms have distinct ecological strategies within plants. Traits, especially leaf traits, host species and spatial predictors better explained diversity than composition, but they were modest predictors overall. Conclusions: This study widens our knowledge about tree species in SF forests, a habitat sensitive to climate change, through the combined analyses of their associated microbial communities with functional traits. We emphasize the need to investigate other plant traits to better disentangle the drivers of the relationship between seedlings and their associated microbiomes, ultimately enhancing their adaptive capacities to climate change. [ABSTRACT FROM AUTHOR]

There is strong evidence that landscape‐scale factors such as habitat diversity, composition and configuration are important drivers of declines in pollinators and pollination services. However, context and species‐specific responses make it challenging to draw general conclusions about the most important components of landscapes that support diverse and abundant pollinator communities.In this study, we took a functional‐traits approach to community assembly and tested the hypothesis that landscape properties act most strongly on pollinators indirectly, through their influence on flowering plant communities. Using plant and pollinator data from 96 landscapes in Britain, we tested the associations between plant and pollinator communities and local environmental factors, such as habitat cover and configuration, using path analysis based on Mantel and partial Mantel statistics.When all pollinators were considered, we found that the environmental factors had stronger links to the composition of flowering plant communities than to the composition of pollinator communities. Further, the flowering plant community was strongly linked to the pollinator community suggesting a mediating role between land use and pollinators. When separating the pollinator community into taxonomic groups, we found the same result for hoverflies, but wild bees were linked to both environmental factors and flowering plants.We further explored these links with structural equation models using the response‐effect trait framework as a guiding principle. We found strong evidence that land‐use composition and configuration influence the trait distribution and functional diversity of the pollinator community via plant community composition.These findings suggest that the indirect effect of land use on pollinators via flowering plants should be considered in informing the design of pollinator friendly landscapes and in future research of the effects of land use and management on wild pollinators. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Mental health and well-being tend to improve with age, and personality differences affect these trajectories. Although it is well established that dispositional traits, such as extraversion and neuroticism, relate to well-being, the incremental validity of other important personality constructs, such as narrative identity, remains unknown. Across 9 years, 157 late-midlife adults (M age = 56.4 years, SD = 0.96) self-reported their well-being and symptoms of depression each year and wrote an annual narrative account describing their greatest life challenge (N challenges = 1,211). The narrative accounts were content-coded for themes of agency and communion. Results showed that themes of agency and communion in narrative identity were significantly and uniquely associated with well-being and depression across time, over and above the effects of traits. The benefits of considering both narrative identity and dispositional personality traits as they jointly apply to mental health are discussed. [ABSTRACT FROM AUTHOR]

I summarize an early effort to provide a conceptual basis for psychology. Natural science studies material objects, and its methods and assumptions may not be appropriate for the study of persons. Persons exist within the natural attitude and are characterized by such properties as temporality, responsibility, normality, and identity. Contemporary theories of mind focus on people's understanding of how minds make decisions and shape behavior, but say little about the nature of the entity that possesses a mind; ethnopsychologies are concerned with cultural variations in beliefs about accidental rather than essential aspects of human psychology. The lay philosophical view of the person sketched here is intended to be broader and deeper. It is particularly relevant to trait psychology, appears to have been implicit in much trait research, and is generally consistent with empirical findings on personality traits. [ABSTRACT FROM AUTHOR]

Fine roots are key to ecosystem-scale nutrient, carbon (C), and water cycling, yet our understanding of fine root trait variation within and among tropical forests, one of Earth's most C-rich ecosystems, is limited. We characterized root biomass, morphology, nutrient content, and arbuscular mycorrhizal fungal (AMF) colonization to 1.2 m depths across four distinct lowland Panamanian forests, and related root characteristics to soil C stocks. We hypothesized that: (H1) Fine root characteristics vary consistently with depth across seasonal tropical forests, with deeper roots exhibiting more exploratory traits, such as for deep water acquisition; (H2) fine root characteristics vary among tropical forests mainly in surface soils, where resource availability also varies. We found consistent variation with depth across the four forests, including decreased root biomass, root tissue density, and AMF, and increased specific root length. Among the forests, there was variation in some fine root characteristics, including greater surface root biomass and lower SRL in the wettest forest, and smaller fine root diameter in the driest forest. We also found that root characteristics were related to total soil C stocks, which were positively related to root biomass and negatively related to specific root length. These results indicate emergent properties of root variation with depth across tropical forests, and show site-scale variation in surface root characteristics. Future work could explore the flexibility in root characteristics under changing conditions such as drought. [ABSTRACT FROM AUTHOR]

Aim: Human activities pose many challenges to freshwater biodiversity. Among these, is landscape transformation, such as conversion of natural grassland to plantation forestry, impacting both terrestrial and freshwater biodiversity. Functional diversity measures provide substantial information on current and emerging impacts on biological communities, and aid conservation decisions relative to anthropogenic impacts. We determined (1) environmental similarities among 10 freshwater biotope types; (2) whether freshwater biotopes in conservation corridor networks support equal levels of functional richness and divergence compared with an extensive neighbouring protected area; (3) whether certain biotopes are more important for maintaining functional richness and divergence than others; and (4) whether associations between traits and biotope types could be identified. Location: The northeastern coastal region of South Africa. Methods: Using dragonflies as model organisms, and data from 140 freshwater lotic and lentic sites, we investigated the distribution of dragonfly traits across a plantation forestry‐natural grassland landscape mosaic with a range of biotope types. Results: Lake sites were different in their environmental conditions compared with the other biotopes. Environmental conditions were variable among the other biotope types and were difficult to distinguish. Freshwater biotopes in the conservation corridors supported equal levels of functional richness and divergence compared with those in the protected area. Overall, dragonfly functional richness and divergence were low at lake sites and wallows, while all other biotopes supported high levels of functional richness and divergence. Trait associations were complex across the waterscape and driven by habitat selection, flight behaviour and ecological sensitivity. Main Conclusions: Maintaining a mosaic of small lentic and lotic habitats would best support dragonfly conservation in this transformed landscape. A combination of biotopes offers a wide range of environmental conditions essential for conserving the full range of dragonfly traits and species across the region. [ABSTRACT FROM AUTHOR]