Explore the vast range of titles available.

To determine if the temporal and spatial pattern of alien plant invasion and native plant expansion can be observed using 100 years of herbarium data from Oklahoma, USA, and to eliminate herbarium collection biases in such analyses. Oklahoma, USA. Using herbarium records from the Oklahoma Vascular Plants Database from 1903 to 2004, we reconstructed the spatial and temporal collection history of two alien invasive taxa (Lonicera japonica and Tamarix spp.) and three native expansive species (Ambrosia psilostachya, Amphiachyris dracunculoides and Juniperus virginiana). To compare the overall collecting trend, groups of native non-expansive taxa were selected as counterparts. We recorded the year of the first collection in each township in Oklahoma for all taxa. The cumulative number of occupied townships was log-transformed, plotted against time and modelled with linear regression. The slope of the linear regression represented collection trend over time for the non-expansive counterpart group. However, for the invasive and expansive species, the regression slope represented the collection effort plus the invasion or expansion rate. We calculated the proportion of invasive and expansive species to non-expansive species by dividing the cumulative number of townships for each invasive or expansive species by the cumulative number of townships occupied by the counterpart group (proportion curve). Maps of the collection records of invasive and expansive taxa illustrated no discernible spatial invasion or expansion pattern. The slopes of the linear regression for alien invasive taxa were significantly steeper than those of their associated native non-expansive counterparts, indicating an increase in abundance. Juniperus virginiana, L. japonica and Tamarix spp. exhibited one or more periods during which they were collected at a disproportionately higher rate than their native non-expansive counterparts. Patterns of species invasion and expansion in Oklahoma were detected using techniques developed for regions with longer collecting plant histories. The proportion curve analysis eliminated some biases inherent in herbarium data by reducing the effect of collecting effort. Both the regression model and proportion curve analyses illustrate the temporal invasion patterns of alien invasive species. The native species did not show a clear expansion pattern. The information found in recently established herbaria may not be sensitive enough to detect the increase in abundance of native species.

Areas of endemism are the fundamental units of cladistic biogeographical analysis but there is no consensus on the most appropriate method for their delimitation. In this paper, the relative performance of a number of algorithmic approaches for the delimitation of areas of endemism is investigated within the context of the Canary Islands flora, and areas of endemism within the Canary Islands archipelago are defined. The Canary Islands. A data matrix comprising the distributions of 609 endemic spermatophyte taxa (c. 90% of the endemic flora) scored on a 10 x 10 km UTM grid was analysed using: (1) UPGMA (unweighted pair group method with arithmetic mean) clustering of Jaccard and Kulczynski similarity coefficient matrices, (2) parsimony analysis of endemicity (PAE), and (3) the program ndm (eNDeMism). The performance of each method was then determined by the extent to which the resulting areas of endemism met three criteria: (1) possession of two or more strict endemic taxa, (2) diagnosability, and (3) geographical contiguity. Each of the four methods resulted in substantially different sets of areas. ndm analysis resolved 17 areas of endemism consistent with all three criteria, and collectively these accounted for 59% of all cells. In the hierarchical analyses none of the methods recovered more than eight areas of endemism, and the total coverage of cells ranged from 13% to 33% when the results were confined to intra-island areas of endemism. ndm outperforms hierarchical clustering methods in terms of both the number of intra-island areas of endemism delimited that meet the three evaluation criteria and the total coverage of those areas. ndm may also be considered preferable because it is non-hierarchical, incorporates spatial information into the delimitation of areas, and permits overlap between areas of endemism where there is evidence to support it. The results support the use of ndm as the most appropriate method currently available for the delimitation of areas of endemism. The areas of endemism identified by the ndm analysis are discussed.

Various methods are employed to recover patterns of area relationships in extinct and extant clades. The fidelity of these patterns can be adversely affected by sampling error in the form of missing data. Here we use simulation studies to evaluate the sensitivity of an analytical biogeographical method, namely tree reconciliation analysis (TRA), to this form of sampling failure. Simulation study. To approximate varying degrees of taxonomic sampling failure within phylogenies varying in size and in redundancy of biogeographical signal, we applied sequential pruning protocols to artificial taxon-area cladograms displaying congruent patterns of area relationships. Initial trials assumed equal probability of sampling failure among all areas. Additional trials assigned weighted probabilities to each of the areas in order to explore the effects of uneven geographical sampling. Pruned taxon-area cladograms were then analysed with TRA to determine if the optimal area cladograms recovered match the original biogeographical signal, or if they represent false, ambiguous or uninformative signals. The results indicate a period of consistently accurate recovery of the true biogeographical signal, followed by a nonlinear decrease in signal recovery as more taxa are pruned. At high levels of sampling failure, false biogeographical signals are more likely to be recovered than the true signal. However, randomization testing for statistical significance greatly decreases the chance of accepting false signals. The primary inflection of the signal recovery curve, and its steepness and slope depend upon taxon-area cladogram size and area redundancy, as well as on the evenness of sampling. Uneven sampling across geographical areas is found to have serious deleterious effects on TRA, with the accuracy of recovery of biogeographical signal varying by an order of magnitude or more across different sampling regimes. These simulations reiterate the importance of taxon sampling in biogeographical analysis, and attest to the importance of considering geographical, as well as overall, sampling failure when interpreting the robustness of biogeographical signals. In addition to randomization testing for significance, we suggest the use of randomized sequential taxon deletions and the construction of signal decay curves as a means to assess the robustness of biogeographical signals for empirical data sets.

We used modern pollen assemblages to develop a method for climate reconstruction that reduces the spatial autocorrelation of residuals and accounts for the strong topographic and climatic variation that occurs in British Columbia, Canada. British Columbia, Canada, including sites both on the mainland and on adjacent islands (Queen Charlotte Islands and Vancouver Island). New pollen assemblages from surface-sediment samples collected in British Columbia were combined with other published and unpublished samples (n = 284). Multivariate rank-distances between sample sites and a randomized set of sites within the province were calculated for climate parameters to determine whether gaps in the current network of present-day pollen sample sites exist. Lacustrine surface-sediment pollen assemblages (n = 145) were ordinated using non-metric multidimensional scaling (NMDS), and a generalized additive model (GAM) was used to reconstruct modern mean warmest month temperature (MWMT) and mean annual precipitation (MAP) from the NMDS ordination. The results were compared with standard climate reconstruction techniques, including the modern analogue technique, partial least squares, weighted averaging, weighted averaging-partial least squares and factor analysis. Reconstructions of MWMT and MAP using NMDS and GAM were comparable to those of existing models. When reconstructing MWMT, the NMDS/GAM method had a lower root-mean-squared error of prediction (RMSEP), lower spatial autocorrelation and higher correlation with observed temperature values than the other methods tested. When reconstructing MAP, the partial least squares method performed better than the NMDS/GAM method for RMSEP and correlation with observed values; however, the NMDS/GAM method had a lower spatial autocorrelation of residuals. NMDS reveals strong relationships among modern pollen assemblages, vegetation and climate parameters. Climate models using NMDS and GAM are comparable to other palaeoecological reconstruction models, but provide lower spatial autocorrelation of residuals for both parameters tested. An inverse distance-weighted surface of multivariate rank-climate distances generated from the network of pollen sample sites indicates that greater sampling intensity in north-western and central-interior British Columbia is required in order to obtain an accurate representation of climatic and vegetation diversity in the province.

The FAO land-cover classification system (LCCS) represents an innovative approach to standardizing and harmonizing land-cover classifications based on remote sensing data. The thematic information considered by the LCCS, however, is intrinsically related to vegetation physiognomy and does not report important eco-climatic features. Our aim is to develop a methodology to enrich LCCS maps with information on vegetation productivity and phenology derived from Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data. The LCCS has recently been applied in East Africa by the Africover project. The proposed methodology is developed and tested in Tanzania using MODIS NDVI data for a 5-year period (2001-05). Annual NDVI profiles of Africover polygons were extracted from MODIS imagery. These profiles, composed of 23 NDVI values per year, were averaged over the study period, purified for possible land-cover errors and converted into a more manageable format composed of 24 half-month values. The resulting NDVI profiles were first analysed visually and then evaluated statistically against rainfall measurements taken at 12 Tanzanian stations. The steps involved were as follows: NDVI values were aggregated on a monthly basis and represented with a one-digit integer to obtain an extended code; a subset of parameters describing vegetation development and phenology was identified, thus obtaining a restricted codification; and finally, the information loss resulting from both the extended and restricted codification was evaluated with respect to the original NDVI profiles. NDVI profiles of different Africover classes can differ in mean values but tend to have a similar shape, linked to the seasonality of local vegetation. Both NDVI annual averages and seasonal variations are strictly dependent on rainfall patterns, particularly in arid zones. The tested codifications effectively summarize the eco-climatic information contained in the polygon NDVI profiles, with the extended and restricted codifications retaining > 90% and 80% of such information, respectively. The proposed methodology is capable of enriching LCCS polygons with eco-climatic information derived from MODIS NDVI data. Such information is related to vegetation development and seasonality, and can be efficiently condensed at various levels of detail.

This review article examines theoretical and methodological issues in the construction of a developmental perspective on executive function (EF) in childhood and adolescence. Unlike most reviews of EF, which focus on preschoolers, this review focuses on studies that include large age ranges. It outlines the development of the foundational components of EF— inhibition, working memory, and shifting. Cognitive and neurophysiological assessments show that although EF emerges during the first few years of life, it continues to strengthen significantly throughout childhood and adolescence. The components vary somewhat in their developmental trajectories. The article relates the findings to long-standing issues of development (e.g., developmental sequences, trajectories, and processes) and suggests research needed for constructing a developmental framework encompassing early childhood through adolescence.

The purpose of the research is to study the effectiveness of the methodological approach based on the use of podcasts in the study of Russian as a foreign language. The study involved 110 students studying Russian randomly selected from a representative sample. They were asked to listen and watch podcasts in and out of class twice a week for 4.5 months. At the end of the study a control test showed that the students’ language proficiency had increased, their grammar, writing, listening, pronunciation, and speaking skills had significantly improved. A pre- and post-test was conducted in the form of an examination with the participation of teachers, and the results were compared with a Student’s t-test to determine if there were statistically significant differences in academic achievement. After the pre-test, students received a podcast training intervention based on the author’s method. The results obtained demonstrated a statistically significant increase in the qualification level of the Russian language of the participants. An unstructured follow-up survey was also conducted regarding student assessment of classes using podcasts. A variety of assessments and explanations of the results obtained were obtained, which can be used in pedagogical practice. It was found that podcasts teach students to work on their own speech, helping to overcome the language barrier and increasing motivation to learn Russian as a foreign language. Thus, the introduction of podcasts in the study of the Russian language can solve such methodological problems: the formation of the ability to understand foreign speech by ear, improving pronunciation, expanding vocabulary, fostering the grammatical skills.

In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.

Antisociality across adolescence and young adulthood puts individuals at high risk of developing a variety of problems. Prior research has linked antisociality to autonomic nervous system and endocrinological functioning. However, there is large heterogeneity in antisocial behaviors, and these neurobiological measures are rarely studied conjointly, limited to small specific studies with narrow age ranges, and yield mixed findings due to the type of behavior examined. We harmonized data from 1489 participants (9-27 years, 67% male), from six heterogeneous samples. In the resulting dataset, we tested relations between distinct dimensions of antisociality and heart rate, pre-ejection period (PEP), respiratory sinus arrhythmia, respiration rate, skin conductance levels, testosterone, basal cortisol, and the cortisol awakening response (CAR), and test the role of age throughout adolescence and young adulthood. Three dimensions of antisociality were uncovered: 'callous-unemotional (CU)/manipulative traits', 'intentional aggression/conduct', and 'reactivity/impulsivity/irritability'. Shorter PEPs and higher testosterone were related to CU/manipulative traits, and a higher CAR is related to both CU/manipulative traits and intentional aggression/conduct. These effects were stable across age. Across a heterogeneous sample and consistent across development, the CAR may be a valuable measure to link to CU/manipulative traits and intentional aggression, while sympathetic arousal and testosterone are additionally valuable to understand CU/manipulative traits. Together, these findings deepen our understanding of the fundamental mechanisms underlying different components of antisociality. Finally, we illustrate the potential of using current statistical techniques for combining multiple datasets to draw robust conclusions about biobehavioral associations.

This study proposes the multidimensional concept of ‘student behavior at university’ and methodology for its quantitative investigation. Unlike previous concepts related to aspects of the student experience, the idea of student behavior considers the combinations and interrelations of individual and environmental characteristics affecting student experience and outcomes. It provides a new lens for viewing student experience at university, highlighting the multifacetedness of this phenomenon and the diversity of possible patterns of student behavior. Based on the conceptual model, a ten-dimensional scale measuring student behavior was developed and validated through mixed-method research with an exploratory sequential design. The following dimensions of student behavior were identified: 1) interaction with course content in class; 2) persistence; 3) self-learning; 4) irresponsible learning behavior; 5) active learning; 6) friendship; 7) study collaboration; 8) obedience; 9) creating a positive self-image; and 10) extracurricular involvement. To develop a survey instrument, we utilized semistructured in-depth interviews with Russian students (n = 119). In the quantitative phase of the study, based on the survey (n = 1,253) carried out at seven highly selective Russian universities, we tested the reliability and validity of the ten-dimensional scale. To test construct-related validity, we utilized the self-determination theory developed by Ryan and Deci and a short version of the Academic Motivation Scale developed by Gordeeva, Sychev, and Osin for the Russian educational context. Our findings are in line with assumptions of self-determination theory and the results of previous studies and can be considered evidence of construct validity. The directions for further development of the methodological approach and its practical implications are discussed.