Speech and language processes in children who stutter compared to those who do not within an oral narrative task

Background and Purpose: Language ability in children who stutter has been linked to the occurrence of stuttering, however, the validity of research supporting this connection has been recently questioned. Previous research, within this area, has been limited by methodological confounds, such as lack of appropriately matched comparison groups, and the use of measures with insufficient sensitivity to potentially examine the subtle differences between children who stutter (CWS) and children who do not stutter (CWNS). Frequent hesitations or pauses are defining characteristics of the speech of people who stutter. However, little is known about the nature and frequency of the pauses found within the speech of CWS. Examination of pauses within speech is a novel method of analysing speech production with the potential to provide insight into the speech and language processing and an opportunity to explore differences between normal and disordered speech. This study aimed to compare the speech and language processes of CWS to CWNS. Methods and Procedures: This study compared language and pause measures taken from narrative samples of age (Mean age = 6 years and 10 months) and gender matched CWS (n= 6), and CWNS (n= 6). The oral narratives were collected using a story generation task and were transcribed and analysed using the Systematic Analysis of Language Transcription (SALT) (Miller & Iglesias, 2012). For each sample the mean length of utterance in morphemes, the total number of utterances, the number of different word roots, the % intelligible words and the % words in mazes were calculated. Additionally the computer software programme PRAAT was used to segment the samples into sections of speech and pauses and the segmented samples were transformed into two lognormal pause distributions (Boersma, & Weenink, 2013). The pauses of CWS were analysed twice, once with stutters present and once with stutters removed. For the two groups the results from the language and pause analyses were compared through ttests and the relationship between Percent Syllables stutters, and the pause and language measures, was examined through correlation. Results: For all discourse and pause measures the difference between the CWS and CWNS was not significant. The only significant difference was found between the CWS and CWNS in the degree of overlap of the short and long pause distributions (Misclassification Rate) in the samples of CWS, when stutters were present. Percent Syllables Stuttered was found to be significantly positively correlated with Percent Mazes and Syllables Spoken per Second when stutters were present in the samples of CWS. Percent Syllables Stuttered was found to be significantly negatively correlated with Short Pause Mean with stutters present in the samples of CWS. Conclusions: In this study, the connection between stuttering and language was not supported as the language measures gathered from CWS were all found to be similar to those gathered from CWNS. The findings in this research support explanations of stuttering in which stuttering is attributed to factors exclusive to language ability, such as stuttering being a difficulty in speech motor contro

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives