Social Cognition And Functional Brain Imaging: Extending The Broader Autism Phenotype

Evidence suggests that the social cognition deficits prevalent in autism spectrum disorders (ASDs) are widely distributed in first degree and extended relatives. This ¿broader autism phenotype¿ (BAP) can be extended into non-clinical populations and show wide distributions of social behaviors such as empathy and social responsiveness ¿ with ASDs exhibiting these behaviors on the lower ends of the distributions. Little evidence has previously shown relationships between self-report measures of social cognition and more objective tasks such as face perception in functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). In this study, three specific hypotheses were addressed: a) increased social ability, as measured by an increased Empathy Quotient, decreased Social Responsiveness Scale (SRS-A) score, and increased Social Attribution Task score, will predict increased activation of the fusiform gyrus in response to faces as compared to houses; b) these same measures will predict N170 amplitude and latency showing decreased latency and increased amplitude for faces as compared to houses with increased social ability; c) increased amygdala volume will predict increased fusiform gyrus activation when viewing faces as compared to houses. Findings supported all of the hypotheses. Empathy scores significantly predicted both right FFG activation [F(1,20) = 4.811, p = .041, ß = .450, R2 = 0.20] and left FFG activation [F(1,20) = 7.70, p = .012, ß = .537, R2 = 0.29]. Based on ERP results increased right lateralization face-related N170 was significantly predicted by the EQ [F(1,54) = 6.94, p = .011, ß = .338, R2 = 0.11]. Finally, total amygdala volume significantly predicted right [F(1,20) = 7.217, p = .014, ß = .515, R2 = 0.27] and left [F(1,20) = 36.77, p < .001, ß = .805, R2 = 0.65] FFG activation. Consistent with the a priori hypotheses, traits attributed to the BAP can significantly predict neural responses to faces in a non-clinical population. This is consistent with the face processing deficits seen in ASDs. The findings presented here contribute to the extension of the BAP from unaffected relatives of individuals with ASDs to the general population. These findings also give continued evidence in support of a continuous distribution of traits found in psychiatric illnesses in place of a traditional, dichotomous ¿all-or-nothing¿ diagnostic framework of neurodevelopmental and neuropsychiatric disorders.

Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines

Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

Genome-wide analysis reveals selection for important traits in domestic horse breeds.

Intense selective pressures applied over short evolutionary time have resulted in homogeneity within, but substantial variation among, horse breeds. Utilizing this population structure, 744 individuals from 33 breeds, and a 54,000 SNP genotyping array, breed-specific targets of selection were identified using an F(ST)-based statistic calculated in 500-kb windows across the genome. A 5.5-Mb region of ECA18, in which the myostatin (MSTN) gene was centered, contained the highest signature of selection in both the Paint and Quarter Horse. Gene sequencing and histological analysis of gluteal muscle biopsies showed a promoter variant and intronic SNP of MSTN were each significantly associated with higher Type 2B and lower Type 1 muscle fiber proportions in the Quarter Horse, demonstrating a functional consequence of selection at this locus. Signatures of selection on ECA23 in all gaited breeds in the sample led to the identification of a shared, 186-kb haplotype including two doublesex related mab transcription factor genes (DMRT2 and 3). The recent identification of a DMRT3 mutation within this haplotype, which appears necessary for the ability to perform alternative gaits, provides further evidence for selection at this locus. Finally, putative loci for the determination of size were identified in the draft breeds and the Miniature horse on ECA11, as well as when signatures of selection surrounding candidate genes at other loci were examined. This work provides further evidence of the importance of MSTN in racing breeds, provides strong evidence for selection upon gait and size, and illustrates the potential for population-based techniques to find genomic regions driving important phenotypes in the modern horse.

Effects of two traits of the ecological state equation on our understanding of species coexistence and ecosystem services

Species coexistence has been a fundamental issue to understand ecosystem functioning since the beginnings of ecology as a science. The search of a reliable and all-encompassing explanation for this issue has become a complex goal with several apparently opposing trends. On the other side, seemingly unconnected with species coexistence, an ecological state equation based on the inverse correlation between an indicator of dispersal that fits gamma distribution and species diversity has been recently developed. This article explores two factors, whose effects are inconspicuous in such an equation at the first sight, that are used to develop an alternative general theoretical background in order to provide a better understanding of species coexistence. Our main outcomes are: (i) the fit of dispersal and diversity values to gamma distribution is an important factor that promotes species coexistence mainly due to the right-skewed character of gamma distribution; (ii) the opposite correlation between species diversity and dispersal implies that any increase of diversity is equivalent to a route of “ecological cooling” whose maximum limit should be constrained by the influence of the third law of thermodynamics; this is in agreement with the well-known asymptotic trend of diversity values in space and time; (iii) there are plausible empirical and theoretical ways to apply physical principles to explain important ecological processes; (iv) the gap between theoretical and empirical ecology in those cases where species diversity is paradoxically high could be narrowed by a wave model of species coexistence based on the concurrency of local equilibrium states. In such a model, competitive exclusion has a limited but indispensable role in harmonious coexistence with functional redundancy. We analyze several literature references as well as ecological and evolutionary examples that support our approach, reinforcing the meaning equivalence between important physical and ecological principles.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Identification of genes associated with quantitative traits involved in cardiovascular disease and lipoprotein metabolism

Cardiovascular disease (CVD) is a threat to public health. It has been reported to be the leading cause of death in United States. The invention of next generation sequencing (NGS) technology has revolutionized the biomedical research. To investigate NGS data of CVD related quantitative traits would contribute to address the unknown etiology and disease mechanism of CVD. NHLBI's Exome Sequencing Project (ESP) contains CVD related phenotypes and their associated NGS exomes sequence data. Initially, a subset of next generation sequencing data consisting of 13 CVD-related quantitative traits was investigated. Only 6 traits, systolic blood pressure (SBP), diastolic blood pressure (DBP), height, platelet counts, waist circumference, and weight, were analyzed by functional linear model (FLM) and 7 currently existing methods. FLM outperformed all currently existing methods by identifying the highest number of significant genes and had identified 96, 139, 756, 1162, 1106, and 298 genes associated with SBP, DBP, Height, Platelet, Waist, and Weight respectively. ^

Regenerative morphological traits in a woody species community in Tumbesian tropical dry forest.

The study of functional morphological traits enables us to know fundamental aspects of the dynamics of plant communities in local and global habitats. Regenerative morphological traits play an important role in defining plant history and ecological behavior. Seed and fruit characteristics determine to a large extent the patterns for dispersal, germination, establishment and seedling recruitment a given species exhibits on its natural habitat. Despite their prominent role, seed and fruit traits have been poorly studied at the community level of woody plant species in neo-tropical dry forests. In the present study we aimed at i) evaluate the functional role of morphological traits of seeds, fruits and embryo in woody plant species; ii) determine which are the morphological patterns present in seeds collected from the community of woody species that occur in neo-tropical dry forests; and iii) compare woody plant species seed mass values comparatively between neo-tropical dry and tropical forests. To do so, mature seeds were collected from 79 plant species that occur in the Tumbesian forest of Southwest Ecuador. The studied species included the 42 and 37 most representative tree and shrubbery species of the Tumbesian forest respectively. A total of 18 morphological traits (seven quantitative and 11 qualitative) were measured and evaluated in the seeds, fruits and embryos of the selected species, and we compared the seeds mass with other forest types. Our results showed a huge heterogeneity among traits values in the studied species. Seed mass, volume and number were the traits that vary the most at the community level, i.e. seed length ranged from 1.3 to 39 mm, and seed width from 0.6 to 25 mm. Only six embryo types were found among the 79 plant species. In 40 % of the cases, fully developed inverted embryos with large and thick cotyledons to store considerable amount of nutrients were recorded. We concluded that highly variable and functionally complementary morphological traits occur among the studied woody plants of the dry Tumbesian forest. The latter favors a plethora of behavioral mechanisms to coexist among woody species of the dry forest in response to the environmental stress that is typical of arid areas.

The structure of a PII signaling protein from a halophilic archaeon reveals novel traits and high-salt adaptations

To obtain insights into archaeal nitrogen signaling and haloadaptation of the nitrogen/carbon/energy-signaling protein PII, we determined crystal structures of recombinantly produced GlnK2 from the extreme halophilic archaeon Haloferax mediterranei, complexed with AMP or with the PII effectors ADP or ATP, at respective resolutions of 1.49 Å, 1.45 Å, and 2.60 Å. A unique trait of these structures was a three-tongued crown protruding from the trimer body convex side, formed by an 11-residue, N-terminal, highly acidic extension that is absent from structurally studied PII proteins. This extension substantially contributed to the very low pI value, which is a haloadaptive trait of H. mediterranei GlnK2, and participated in hexamer-forming contacts in one crystal. Similar acidic N-extensions are shown here to be common among PII proteins from halophilic organisms. Additional haloadaptive traits prominently represented in H. mediterranei GlnK2 are a very high ratio of small residues to large hydrophobic aliphatic residues, and the highest ratio of polar to nonpolar exposed surface for any structurally characterized PII protein. The presence of a dense hydration layer in the region between the three T-loops might also be a haloadaptation. Other unique findings revealed by the GlnK2 structure that might have functional relevance are: the adoption by its T-loop of a three-turn α-helical conformation, perhaps related to the ability of GlnK2 to directly interact with glutamine synthetase; and the firm binding of AMP, confirmed by biochemical binding studies with ATP, ADP, and AMP, raising the possibility that AMP could be an important PII effector, at least in archaea.

Gasterosteus aculeatus egg traits and fish lengths vs. experiment setup

1) Our study addresses the role of non-genetic and genetic inheritance in shaping the adaptive potential of populations under a warming ocean scenario. We used a combined experimental approach (transgenerational plasticity and quantitative genetics) to partition the relative contribution of maternal vs. paternal (additive genetic) effects to offspring body size (a key component of fitness), and investigated a potential physiological mechanism (mitochondrial respiration capacities) underlying whole organism growth/size responses. 2) In very early stages of growth (up to 30 days), offspring body size of marine sticklebacks benefited from maternal transgenerational plasticity (TGP): offspring of mothers acclimated to17°C were larger when reared at 17°C, and offspring of mothers acclimated to 21°C were larger when reared at 21°C. The benefits of maternal TGP on body size were stronger and persisted longer (up to 60 days) for offspring reared in the warmer (21°C) environment, suggesting that maternal effects will be highly relevant for climate change scenarios in this system. 3) Mitochondrial respiration capacities measured on mature offspring (F1 adults) matched the pattern of TGP for juvenile body size, providing an intuitive mechanistic basis for the maternal acclimation persisting into adulthood. Size differences between temperatures seen at early growth stages remained in the F1 adults, linking offspring body size to maternal inheritance of mitochondria. 4) Lower maternal variance components in the warmer environment were mostly driven by mothers acclimated to ambient (colder) conditions, further supporting our tenet that maternal effects were stronger at elevated temperature. Importantly, all parent-offspring temperature combination groups showed genotype x environment (GxE) interactions, suggesting that reaction norms have the potential to evolve. 5) To summarise, transgenerational plasticity and genotype x environment interactions work in concert to mediate impacts of ocean warming on metabolic capacity and early growth of marine sticklebacks. TGP can buffer short-term detrimental effects of climate warming and may buy time for genetic adaptation to catch up, therefore markedly contributing to the evolutionary potential and persistence of populations under climate change.

Psychophysiological responses to visceral and somatic pain in functional chest pain identify clinically relevant pain clusters

Background: Despite chronic pain being a feature of functional chest pain (FCP) its experience is variable. The factors responsible for this variability remain unresolved. We aimed to address these knowledge gaps, hypothesizing that the psychophysiological profiles of FCP patients will be distinct from healthy subjects. Methods: 20 Rome III defined FCP patients (nine males, mean age 38.7 years, range 28-59 years) and 20 healthy age-, sex-, and ethnicity-matched controls (nine males, mean 38.2 years, range 24-49) had anxiety, depression, and personality traits measured. Subjects had sympathetic and parasympathetic nervous system parameters measured at baseline and continuously thereafter. Subjects received standardized somatic (nail bed pressure) and visceral (esophageal balloon distension) stimuli to pain tolerance. Venous blood was sampled for cortisol at baseline, post somatic pain and post visceral pain. Key Results: Patients had higher neuroticism, state and trait anxiety, and depression scores but lower extroversion scores vs controls (all p < 0.005). Patients tolerated less somatic (p < 0.0001) and visceral stimulus (p = 0.009) and had a higher cortisol at baseline, and following pain (all p < 0.001). At baseline, patients had a higher sympathetic tone (p = 0.04), whereas in response to pain they increased their parasympathetic tone (p ≤ 0.008). The amalgamating the data, we identified two psychophysiologically distinct 'pain clusters'. Patients were overrepresented in the cluster characterized by high neuroticism, trait anxiety, baseline cortisol, pain hypersensitivity, and parasympathetic response to pain (all p < 0.03). Conclusions & Inferences: In future, such delineations in FCP populations may facilitate individualization of treatment based on psychophysiological profiling. © 2013 John Wiley & Sons Ltd.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

Biomass, quality traits and methane production of extensive grassland: biodiversity effects and sensor approaches

Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

The role of relevant information in functional counterfactual thinking

Although counterfactual thinking is typically activated by a negative outcome, it can have positive effects by helping to regulate and improve future behavior. Known as the content-specific pathway, these counterfactual ruminations use relevant information (i.e., information that is directly related to the problem at hand) to elicit insights about the problem, create a connection between the counterfactual and the desired behavior, and strengthen relevant behavioral intentions. The current research examines how changing the type of relevant information provided (i.e., so that it is either concrete and detailed or general and abstract) influences the relationship between counterfactual thinking and behavioral intentions. Experiments 1 and 2 found that counterfactual thinking facilitated relevant intentions when these statements involved detailed information (Experiment 1) or specific behaviors (Experiment 2) compared to general information (Experiment 1), categories of behavior, or traits (Experiment 2). Experiment 3 found that counterfactuals containing a category of behavior facilitated specific behavioral intentions, relative to counterfactuals focusing on a trait. However, counterfactuals only facilitated intentions that included specific behaviors, but not when intentions focused on categories of behaviors or traits (Experiment 4). Finally, this effect generalized to other relevant specific behaviors; a counterfactual based on one relevant specific behavior facilitated an intention based on another relevant specific behavior (Experiment 5). Together, these studies further clarify our understanding of the content-specific pathway and provide a more comprehensive understanding of functional counterfactual thinking.

Biological significance of dead biomass retention trait in Mediterranean Basin species: an analysis between different successional niches and regeneration strategies as functional groups

Standing dead biomass retention is considered one of the most relevant fuel structural traits to affect plant flammability. However, very little is known about the biological significance of this trait and its distribution between different functional groups. Our aim was to analyse how the proportion of dead biomass produced in Mediterranean species is related to the successional niche of species (early-, mid- and late-successional stages) and the regeneration strategy of species (seeders and resprouters). We evaluated biomass distribution by size classes and standing dead biomass retention in nine dominant species from the Mediterranean Basin in different development stages (5, 9, 14 and 26 years since the last fire). The results revealed significant differences in the standing dead biomass retention of species that presented a distinct successional niche or regeneration strategy. These differences were restricted to the oldest ages studied (>9 years). Tree and small tree resprouters, typical in late-successional stages, presented slight variations with age and a less marked trend to retain dead biomass, while seeder shrubs and dwarf shrubs, characteristic of early-successional stages, showed high dead biomass loads. Our results suggest that the species that tend to retain more dead branches are colonising species that may promote fire in early-successional stages.