L'inférence figurale: Un pas de raisonnement discursivo-graphique

This article aims at legitimating the use of the graphic registers in the written expression of mathematical reasoning. More than the defence of this legitimacy, the article shows also the risks of its use: the problems of communication which it causes as well as the difficulties, for the teachers, to evaluate the reasoning of the pupils when they integrate these registers into their solutions, and for the pupils, to understand the mathematical texts which use these registers in their discursive expansions differently than optional illustration. With the concept of graphic expansion and figural inference, the article claims to supplement the inferences in Raymond Duval's discursive plans whilst respecting the reasoning functional definition. Having considered the cognitive and semiotic aspects in the definition of figure, the article shows the use of drawings in the reasoning structure of a pupil at secondary level. Figural inference born from this study is examined then defined in terms of function, structure and quality. This revised version was published online in July 2006 with corrections to the Cover Date.     

The role of stress processing abilities in the development of bilingual reading

French and Dutch differ regarding the manifestations and lexical functions of the stress pattern of words. The present study examined group differences in stress processing abilities between French‐native and Dutch‐native listeners, thus extending previous cross‐linguistic comparisons involving Spanish‐native and French‐native adults. The results show that Dutch‐native first‐graders significantly outperformed French monolinguals, and that French‐native listeners schooled in Dutch produced intermediary performances, suggesting that stress‐processing abilities are a learnable set of skills. The present study also examined the contribution of stress processing abilities to reading development in Dutch, a stress‐based language, compared to that in French, a syllable‐based language. Although the expected correlation between stress processing abilities and reading was not observed in the Dutch monolinguals, such correlation was observed in the French‐native bilinguals schooled in Dutch and not in the Dutch‐native bilinguals schooled in French. This suggests that stress processing abilities influence reading development in a second, stress‐based, language. Moreover, the monolinguals and bilinguals schooled in Dutch showed significant associations between lexical development and stress processing abilities. Ways in which prosody might be involved in lexical and reading development are explored and discussed.     

Investigating the theoretical structure of the DAS‐II core battery at school age using Bayesian structural equation modeling

Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales—Second Edition core battery using the standardization sample normative data for ages 7–17. Results revealed plausibility of a three‐factor model, consistent with publisher theory, expressed as either a higher‐order (HO) or a bifactor (BF) model. The results also revealed an alternative structure with the best model fit, a two‐factor BF model with Matrices (MA) and Sequential and Quantitative Reasoning (SQ) loading on g only with no respective group factor loading. This was only the second study to use BSEM to investigate the structure of a commercial ability test and the first to use a large normative sample and the specification of both approximate zero cross‐loadings and correlated residual terms. It is believed that the results produced from the current study will advance the field's understanding of not only the factor structure of the DAS‐II core battery but also the potential utility of BSEM in psychometric investigations of intelligence test structures.     

Climate and litter C/N ratio constrain soil organic carbon accumulation

Soil organic carbon (SOC) plays critical roles in stabilizing atmospheric CO₂ concentration, but the mechanistic controls on the amount and distribution of SOC on global scales are not well understood. In turn, this has hampered the ability to model global C budgets and to find measures to mitigate climate change. Here, based on the data from a large field survey campaign with 2600 plots across China''s forest ecosystems and a global collection of published data from forested land, we find that a low litter carbon-to-nitrogen ratio (C/N) and high wetness index (P/PET, precipitation-to-potential-evapotranspiration ratio) are the two factors that promote SOC accumulation, with only minor contributions of litter quantity and soil texture. The field survey data demonstrated that high plant diversity decreased litter C/N and thus indirectly promoted SOC accumulation by increasing the litter quality. We conclude that any changes in plant-community composition, plant-species richness and environmental factors that can reduce the litter C/N ratio, or climatic changes that increase wetness index, may promote SOC accumulation. The study provides a guideline for modeling the carbon cycle of various ecosystem scales and formulates the principle for land-based actions for mitigating the rising atmospheric CO₂ concentration.     

Data-driven estimates of global nitrous oxide emissions from croplands

Croplands are the single largest anthropogenic source of nitrous oxide (N₂O) globally, yet their estimates remain difficult to verify when using Tier 1 and 3 methods of the Intergovernmental Panel on Climate Change (IPCC). Here, we re-evaluate global cropland-N₂O emissions in 1961–2014, using N-rate-dependent emission factors (EFs) upscaled from 1206 field observations in 180 global distributed sites and high-resolution N inputs disaggregated from sub-national surveys covering 15593 administrative units. Our results confirm IPCC Tier 1 default EFs for upland crops in 1990–2014, but give a ∼15% lower EF in 1961–1989 and a ∼67% larger EF for paddy rice over the full period. Associated emissions (0.82 ± 0.34 Tg N yr^–1) are probably one-quarter lower than IPCC Tier 1 global inventories but close to Tier 3 estimates. The use of survey-based gridded N-input data contributes 58% of this emission reduction, the rest being explained by the use of observation-based non-linear EFs. We conclude that upscaling N₂O emissions from site-level observations to global croplands provides a new benchmark for constraining IPCC Tier 1 and 3 methods. The detailed spatial distribution of emission data is expected to inform advancement towards more realistic and effective mitigation pathways.     

Human activities aggravate nitrogen-deposition pollution to inland water over China

In the past three decades, China has built more than 87 000 dams with a storage capacity of ≈6560 km³ and the total surface area of inland water has increased by 6672 km². Leaching of N from fertilized soils to rivers is the main source of N pollution in China, but the exposure of a growing inland water area to direct atmospheric N deposition and N leaching caused by N deposition on the terrestrial ecosystem, together with increased N deposition and decreased N flow, also tends to raise N concentrations in most inland waters. The contribution of this previously ignored source of  N deposition to freshwaters is estimated in this study, as well as mitigation strategies. The results show that the annual amounts of N depositions ranged from 4.9 to 16.6 kg · ha⁻¹ · yr⁻¹ in the 1990s to exceeding 20 kg · ha⁻¹ · yr⁻¹ in the 2010s over most of regions in China, so the total mass of ΔN (the net contribution of N deposition to the increase in N concentration) for lakes, rivers and reservoirs change from 122.26 Gg N · yr⁻¹ in the 1990s to 237.75 Gg N · yr⁻¹ in the 2010s. It is suggested that reducing the N deposition from various sources, shortening the water-retention time in dams and decreasing the degree of regulation for rivers are three main measures for preventing a continuous increase in the N-deposition pollution to inland water in China.