988 resultados para morphological traits


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Addressing two aspects of morphological awareness – derivational and compound, this study investigates the relationships between morphological awareness and vocabulary and reading comprehension in English-Chinese bilingual primary 3 children in Singapore (N = 76). Comparable tasks in Chinese and English were administered to examine the children’s morphological awareness, vocabulary, and reading comprehension. The results show that morphological awareness is highly related to vocabulary and reading comprehension, with higher correlations between morphological awareness and reading comprehension than between morphological awareness and vocabulary. This indicates that morphological awareness may have direct influence on reading comprehension beyond the mediating effect of vocabulary. Furthermore, the results indicate that children displayed more compound than derivational morphological awareness for Chinese due to the dominance of compound morphology in Chinese. However the children also displayed similar levels of derivational and compound morphological awareness for English despite far more derivatives than compounds in English. The robust cross-linguistic correlations suggest that Chinese compound morphological knowledge plays a facilitating role not only in learning English compounds, but also in learning transparently derived words that do not involve phonological or orthographic shifts.

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1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

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A deficit in empathy has been suggested to underlie social behavioural atypicalities in autism. A parallel theoretical account proposes that reduced social motivation (i.e., low responsivity to social rewards) can account for the said atypicalities. Recent evidence suggests that autistic traits modulate the link between reward and proxy metrics related to empathy. Using an evaluative conditioning paradigm to associate high and low rewards with faces, a previous study has shown that individuals high in autistic traits show reduced spontaneous facial mimicry of faces associated with high vs. low reward. This observation raises the possibility that autistic traits modulate the magnitude of evaluative conditioning. To test this, we investigated (a) if autistic traits could modulate the ability to implicitly associate a reward value to a social stimulus (reward learning/conditioning, using the Implicit Association Task, IAT); (b) if the learned association could modulate participants’ prosocial behaviour (i.e., social reciprocity, measured using the cyberball task); (c) if the strength of this modulation was influenced by autistic traits. In 43 neurotypical participants, we found that autistic traits moderated the relationship of social reward learning on prosocial behaviour but not reward learning itself. This evidence suggests that while autistic traits do not directly influence social reward learning, they modulate the relationship of social rewards with prosocial behaviour

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Background Children with callous-unemotional (CU) traits, a proposed precursor to adult psychopathy, are characterized by impaired emotion recognition, reduced responsiveness to others’ distress, and a lack of guilt or empathy. Reduced attention to faces, and more specifically to the eye region, has been proposed to underlie these difficulties, although this has never been tested longitudinally from infancy. Attention to faces occurs within the context of dyadic caregiver interactions, and early environment including parenting characteristics has been associated with CU traits. The present study tested whether infants’ preferential tracking of a face with direct gaze and levels of maternal sensitivity predict later CU traits. Methods Data were analyzed from a stratified random sample of 213 participants drawn from a population-based sample of 1233 first-time mothers. Infants’ preferential face tracking at 5 weeks and maternal sensitivity at 29 weeks were entered into a weighted linear regression as predictors of CU traits at 2.5 years. Results Controlling for a range of confounders (e.g., deprivation), lower preferential face tracking predicted higher CU traits (p = .001). Higher maternal sensitivity predicted lower CU traits in girls (p = .009), but not boys. No significant interaction between face tracking and maternal sensitivity was found. Conclusions This is the first study to show that attention to social features during infancy as well as early sensitive parenting predict the subsequent development of CU traits. Identifying such early atypicalities offers the potential for developing parent-mediated interventions in children at risk for developing CU traits.

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The aim of this study was to investigate the capacity of three perennial legume species to access sources of varyingly soluble phosphorus (P) and their associated morphological and physiological adaptations. Two Australian native legumes with pasture potential (Cullen australasicum and Kennedia prostrata) and Medicago sativa cv. SARDI 10 were grown in sand under two P levels (6 and 40 µg P g−1) supplied as Ca(H2PO4)2·H2O (Ca-P, highly soluble, used in many fertilizers) or as one of three sparingly soluble forms: Ca10(OH)2(PO4)6 (apatite-P, found in relatively young soils; major constituent of rock phosphate), C6H6O24P6Na12 (inositol-P, the most common form of organic P in soil) and FePO4 (Fe-P, a poorly-available inorganic source of P). All species grew well with soluble P. When 6 µg P g−1 was supplied as sparingly soluble P, plant dry weight (DW) and P uptake were very low for C. australasicum and M. sativa (0.1–0.4 g DW) with the exception of M. sativa supplied with apatite-P (1.5 g). In contrast, K. prostrata grew well with inositol-P (1.0 g) and Fe-P (0.7 g), and even better with apatite-P (1.7 g), similar to that with Ca-P (1.9 g). Phosphorus uptake at 6 µg P g−1 was highly correlated with total root length, total rhizosphere carboxylate content and total rhizosphere acid phosphatase (EC 3.1.3.2) activity. These findings provide strong indications that there are opportunities to utilize local Australian legumes in low P pasture systems to access sparingly soluble soil P and increase perennial legume productivity, diversity and sustainability.

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Change in morphological and physiological parameters in response to phosphorus (P) supply was studied in 11 perennial herbaceous legume species, six Australian native (Lotus australis, Cullen australasicum, Kennedia prorepens, K. prostrata, Glycine canescens, C. tenax) and five exotic species (Medicago sativa, Lotononis bainesii, Bituminaria bituminosa var albomarginata, Lotus corniculatus, Macroptilium bracteatum). We aimed to identify mechanisms for P acquisition from soil. Plants were grown in sterilised washed river sand; eight levels of P as KH2PO4 ranging from 0 to 384 μg P g−1 soil were applied. Plant growth under low-P conditions strongly correlated with physiological P-use efficiency and/or P-uptake efficiency. Taking all species together, at 6 μg P g−1 soil there was a good correlation between P uptake and both root surface area and total root length. All species had higher amounts of carboxylates in the rhizosphere under a low level of P application. Six of the 11 species increased the fraction of rhizosphere citrate in response to low P, which was accompanied by a reduction in malonate, except L. corniculatus. In addition, species showed different plasticity in response to P-application levels and different strategies in response to P deficiency. Our results show that many of the 11 species have prospects for low-input agroecosystems based on their high P-uptake and P-use efficiency.

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Joint attention (JA) and spontaneous facial mimicry (SFM) are fundamental processes in social interactions, and they are closely related to empathic abilities. When tested independently, both of these processes have been usually observed to be atypical in individuals with autism spectrum conditions (ASC). However, it is not known how these processes interact with each other in relation to autistic traits. This study addresses this question by testing the impact of JA on SFM of happy faces using a truly interactive paradigm. Sixty-two neurotypical participants engaged in gaze-based social interaction with an anthropomorphic, gaze-contingent virtual agent. The agent either established JA by initiating eye contact or looked away, before looking at an object and expressing happiness or disgust. Eye tracking was used to make the agent's gaze behavior and facial actions contingent to the participants' gaze. SFM of happy expressions was measured by Electromyography (EMG) recording over the Zygomaticus Major muscle. Results showed that JA augments SFM in individuals with low compared with high autistic traits. These findings are in line with reports of reduced impact of JA on action imitation in individuals with ASC. Moreover, they suggest that investigating atypical interactions between empathic processes, instead of testing these processes individually, might be crucial to understanding the nature of social deficits in autism

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Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

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Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

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Understanding what makes some species more vulnerable to extinction than others is an important challenge for conservation. Many comparative analyses have addressed this issue exploring how intrinsic and extrinsic traits associate with general estimates of vulnerability. However, these general estimates do not consider the actual threats that drive species to extinction and hence, are more difficult to translate into effective management. We provide an updated description of the types and spatial distribution of threats that affect mammals globally using data from the IUCN for 5941 species of mammals. Using these data we explore the links between intrinsic species traits and specific threats in order to identify key intrinsic features associated with particular drivers of extinction. We find that families formed by small-size habitat specialists are more likely to be threatened by habitat-modifying processes; whereas, families formed by larger mammals with small litter sizes are more likely to be threatened by processes that directly affect survival. These results highlight the importance of considering the actual threatening process in comparative studies. We also discuss the need to standardize and rank threat importance in global assessments such as the IUCN Red List to improve our ability to understand what makes some species more vulnerable to extinction than others.