Investigating the Bilingual Aging Lexicon: A Network Analysis of Word Associations in Chinese-English Bilinguals.

This study examined the development of bilingual lexical networks in adolescence through word association task and network analysis. Participants were Chinese-English bilinguals in Grade 8 (middle school; aged 13-14years) and Grade 11 (high school; aged 16-17years). Networks were constructed based on word association responses separately for each grade and language, and structural properties of networks were computed. Results showed that from Grade 8 to Grade 11, the Chinese networks displayed increased within-group convergence while maintaining overall structural stability and small-world features. In contrast, the English networks expanded in size, with longer average shortest paths, higher local clustering, and greater modularity (Q), reflecting rapid growth and restructuring, while also exhibiting small-world features. Across grades, L1 networks remained larger and more structured than L2 networks, though the gap decreased over time, indicating increasing cross-language similarity. These findings provide new insights into bilingual lexical development during the adolescent years.

This study examined Mandarin-speaking children’s development in relating narrative events in terms of both global and local connections. Thirty Mandarin-speaking five-year-olds, 30 nine-year-olds and 30 adults participated. The narrative data were elicited using Frog, where are you? The plot-structure and the goal-plan schemes were used to examine participants’ ability to maintain global connections; a complex event and a sequence of events were chosen to assess local connections. The results displayed children’s significant progress in establishing global connections and in employing goal-plan knowledge. Regarding local connections, children exhibited increasing ability to encode and to integrate essential event components. Findings suggest that five-year-olds had insufficient ability to establish both global and local connections. Nine-year-olds were more advanced in encoding global connections; however, they were inadequate in integrating event components and in chaining a sequence of events at the local level. Adults could properly relate narrative events at both levels and were more likely to encode characters’ internal responses to enhance thematic coherence. Results were considered in relation to capacities for working memory, theory of mind and integration. Narrators’ differences in communicative competence and cognitive preferences were also discussed.

The ever-growing bilingual population worldwide has fuelled research on how a first (L1) and a second (L2) language interact to affect bilinguals’ language and reading acquisition. The present thesis centred on bilinguals’ syntactic skills in L1 Chinese and in typologically distant L2 English, and their cross-language interactions with reading development.
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\nStudy 1 was a two-year longitudinal study in which 198 grade 1 and 203 grade 3 Hong Kong Chinese-English bilinguals participated. The children were assessed on syntactic skills and reading comprehension in Chinese and in English, nonverbal intelligence, working memory, language-related skills, and were re-tested after one year. Study 1A primarily examined the contrasting roles of morphosyntactic and word order skills in Chinese and English reading across grades. Hierarchical regression analyses revealed that reading comprehension was differentially dependent on the two syntactic skills across ages and languages. Word order, relative to morphosyntactic skill, was critical to text comprehension at an earlier time. Word order was also more important to reading in Chinese, whereas reading in English gradually relied more on morphosyntactic skill.
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\nStudy 1B used structural equation modelling to study the cross-language relationships. Mediation analyses showed that L1 Chinese syntactic skills cross-linguistically predicted L2 English reading comprehension over time; this prospective association was largely mediated by L2 English syntactic skills among the fourth graders. Further analyses suggested that word order skill was more transfer-ready than morphosyntactic skill, indicating an effect of linguistic distance upon language transfer.
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\nBeyond a mere cross-language syntactic transfer, Study 2 was designed to examine if bilinguals’ dual-language experience fostered further syntactic advancement via enhancing sensitivity to underlying syntactic structures. Participants in Study 2 comprised three age cohorts, including 69 primary school children, 56 secondary school adolescents, and 73 undergraduate adults. They were tested on morphosyntactic skill, word order skill, artificial syntax learning, and general cognitive abilities. Across the three cohorts, the Chinese-English bilinguals performed better than their English monolingual peers in acquiring a novel syntax and processing morphosyntax specific to English. The bilingual adults also performed better than their monolingual peers in manipulating language-specific word order. Moreover, the adolescent and adult bilinguals were also assessed on analogical reasoning; the bilinguals who were more skilled at abstracting similarities and differences between structures were generally superior in learning the new syntactic patterns and processing language-specific word order. Study 2 thus supports the structural sensitivity hypothesis that bilinguals’ advantage is not confined to knowledge and strategies specific to the additional language, but constitutes a more abstract representation of underlying linguistic structures in general.
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\nThe findings collectively suggest how syntactic and reading skills can be developed in a bilingual learning context. Teachers may evoke L1 syntactic knowledge and map it onto L2 corresponding features to facilitate L2 reading. Drawing analogy between parallel L1 and L2 constructions works through making bilinguals taking linguistic structures more analytically. Building up L2 proficiency is also necessary because it is the prerequisite for reaping the bilingual benefits in maximising L2 learning. To conclude, skilled L2 reading necessitates a careful consideration of the cross-language syntactic development.

ObjectiveThe aim of this study is to investigate changes in metabolic networks based on fluorodeoxyglucose positron emission tomography (FDG-PET) in patients with drug-resistant temporal lobe epilepsy (TLE) (with and without hippocampal sclerosis [HS]) when compared with healthy controls. MethodsWe retrospectively enrolled 30 patients with drug-resistant temporal lobe epilepsy (17 patients with HS and 13 patients without HS) and 39 healthy controls. All subjects underwent interictal FDG-PET scans, which were analyzed to obtain metabolic connectivity using graph theoretical analysis. We investigated the differences in metabolic connectivity between patients with drug-resistant TLE (with and without HS) and healthy controls. ResultsWhen compared with healthy controls, TLE patients with HS showed alterations of global and local metabolic connectivity. When considering global connectivity, TLE patients with HS had a decreased average degree with increased modularity. When considering local connectivity, TLE patients with HS displayed alterations of betweeness centrality in widespread regions. However, there were no alterations of global metabolic connectivity in TLE patients without HS when compared with healthy controls. In addition, when compared to TLE patients without HS, TLE patients with HS had increased modularity. SignificanceOur study demonstrates more severe alterations in metabolic networks based on FDG-PET in TLE patients with HS than in those without HS and healthy controls. This may represent distinct epileptic networks in TLE patients with HS versus those without HS, although both are drug-resistant focal epilepsy.

Link between hippocampus' raised local and eased global intrinsic connectivity in AD

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder.

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Psycholinguistic studies have argued for the age of acquisition (AoA) of words as a marker of concept learning, showing that the semantic features of concepts themselves influence the age at which their labels are learned. However, empirical evidence suggests that semantic features such as imageability and linguistic phenomena such as frequency do not adequately predict AoA. The present study takes the developmental approach of embodied cognition and investigates the effects of sensorimotor experiences on the ease of acquisition of the concept acquired in bilinguals. Specifically, we investigated (1) whether the sensorimotor experience can explain AoA beyond frequency; (2) and whether these patterns are consistent across L1 Chinese and L2 English. We conducted sensorimotor rating measures in both Chinese and English on 207 items in which Chinese-English bilingual adults were requested to evaluate the extent to which they experienced concepts by employing six perceptual senses and five effectors for actions located in various regions of the body. Meanwhile, data on AoA and frequency were collected. The present study showed the sensorimotor experience was closely linked with AoAs in both languages. However, the correlation analysis revealed a trend of higher correlations between AoAs for the same concepts and L1 Chinese, relative to L2 English for the present Chinese-English bilinguals. Importantly, the hierarchical regression analysis demonstrated that after controlling for frequency, sensorimotor experience explained additional variance in L1 AoA. However, L2 sensorimotor experience did not explain the variance in L2 AoA. Sensorimotor experience explained more share of variance in L1 AoA but frequency accounted for more variance in L2 AoA. The findings suggest that concept acquisition should consider the grounding in appropriate sensorimotor experience beyond linguistic phenomena like frequency.

Peatlands are important natural sources of atmospheric methane (CH4) emissions. The emissions are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The formation of anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat, can also be conceptualized through a pore network approach. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of CH4 transport as the distance from the peat layer to the soil–air interface increases. Hysteresis was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to drying conditions. This hysteretic behavior should be taken into account in biogeochemical models to explain the hotspots and episodic spikes of CH4 emissions. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of CH4 diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and global continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways.

<strong class="journal-contentHeaderColor">Abstract.</strong> Peatlands are important natural sources of atmospheric methane (<span class="inline-formula">CH₄</span>) emissions. The production and emission of <span class="inline-formula">CH₄</span> are strongly influenced by the diffusion of oxygen into the soil and of <span class="inline-formula">CH₄</span> from the soil to the atmosphere, respectively. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give conceptual insight into how the relationship between the microscale pore space properties and <span class="inline-formula">CH₄</span> emissions on a macroscopic scale is shaped. The evolution of the pore space that is connected to the atmosphere can also be conceptualized through a pore network modeling approach. Pore regions isolated from the atmosphere may further develop into anaerobic pockets, which are local hotspots of <span class="inline-formula">CH₄</span> production in unsaturated peat. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (<span class="inline-formula">µ</span>CT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of gas transport as the distance from the peat layer to the soil–air interface increases. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of gas diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways. The hysteresis of peat water content between wetting and drying was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to in drying conditions. This hysteretic behavior might explain the hotspots and episodic spikes of <span class="inline-formula">CH₄</span> emissions, and therefore, it should be taken into account in biogeochemical models.

Abstract. Peatlands are important natural sources of atmospheric methane (CH4) emissions. The production and emission of CH4 are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere, respectively. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give conceptual insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The evolution of the pore space that is connected to the atmosphere can also be conceptualized through a pore network modeling approach. Pore regions isolated from the atmosphere may further develop into anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of gas transport as the distance from the peat layer to the soil–air interface increases. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of gas diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways. The hysteresis of peat water content between wetting and drying was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to in drying conditions. This hysteretic behavior might explain the hotspots and episodic spikes of CH4 emissions, and therefore, it should be taken into account in biogeochemical models.

&amp;lt;p&amp;gt;Peatlands are globally significant modulators of biogeochemical cycles and important natural sources of methane. The emissions are strongly influenced by the diffusion of oxygen into the peat and the diffusion of methane from the peat to the atmosphere. The structure of peat macropore networks controls the gas transport. The characterization of peat pore structure and connectivity using complex network theory methods can give important conceptual insight into the relationship between the microscale pore space characteristics and methane emissions on a macroscopic scale. Both gas transfer in unsaturated peat and the evolution of the connected air-filled pore space can be conceptualized through a pore network modeling approach. Pores that become isolated from the atmosphere may eventually develop into anaerobic pockets, which are local hotspots of methane production in unsaturated peat.&amp;lt;br&amp;gt;We extracted macropore (diameter greater than 0.1 mm) networks from three-dimensional X-ray micro-computed tomography (micro-CT) images of peat samples collected from a boreal forested peatland and evaluated local and global connectivity metrics for the networks. We also simulated the soil-water retention curves of the peat samples using pore network modeling and compared the results with measured water retention characteristics. There were fundamental differences in macropore structure and connectivity between vertical peat layers. Macropore connectivity was higher and the flow routes through the peat matrix were less tortuous in the near-surface peat than in the deeper layers. Furthermore, the number and volume of macropores, the average width of pore throats, and the structural anisotropy of peat decreased with depth. Therefore, gas exchange with the atmosphere may be slowed down because of narrower and more tortuous air-filled diffusion channels as the distance between the peat layer and the soil-atmospheric interface increases.&amp;lt;br&amp;gt;The network analysis also suggests that local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might be proxies for gas diffusion capability in air-filled pore networks. However, the applicability of the metrics was restricted to the topmost peat layer with high porosity. The spatial extent and larger-scale connectivity of the network and the spatial distribution of the pores within the network may be reflected in different network metrics in contrasting ways.&amp;lt;br&amp;gt;The hysteresis of peat water content was found to affect the evolution of the interconnected air-filled pore volume in unsaturated peat. Therefore, the volume available for the formation of anaerobic pockets may be smaller and methane production may be slower in wetting conditions than in drying conditions. This hysteretic behavior might be one of the reasons behind observed hotspots and episodic spikes of methane emissions, and therefore hysteresis should be included in biogeochemical models describing methane dynamics in peat.&amp;lt;/p&amp;gt;

Peatlands are important natural sources of atmospheric methane (CH4) emissions. The emissions are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The formation of anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat, can also be conceptualized through a pore network approach. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of CH4 transport as the distance from the peat layer to the soil–air interface increases. Hysteresis was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to drying conditions. This hysteretic behavior should be taken into account in biogeochemical models to explain the hotspots and episodic spikes of CH4 emissions. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of CH4 diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and global continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways.

Peatlands are important natural sources of atmospheric methane (CH4) emissions. The emissions are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The formation of anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat, can also be conceptualized through a pore network approach. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of CH4 transport as the distance from the peat layer to the soil–air interface increases. Hysteresis was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to drying conditions. This hysteretic behavior should be taken into account in biogeochemical models to explain the hotspots and episodic spikes of CH4 emissions. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of CH4 diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and global continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways.

Peatlands are important natural sources of atmospheric methane (CH4) emissions. The emissions are strongly influenced by the diffusion of oxygen into the soil and of CH4 from the soil to the atmosphere. This diffusion, in turn, is controlled by the structure of macropore networks. The characterization of peat pore structure and connectivity through complex network theory approaches can give insight into how the relationship between the microscale pore space properties and CH4 emissions on a macroscopic scale is shaped. The formation of anaerobic pockets, which are local hotspots of CH4 production in unsaturated peat, can also be conceptualized through a pore network approach. In this study, we extracted interconnecting macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and evaluated local and global connectivity metrics for the networks. We also simulated the water retention characteristics of the peat samples using a pore network modeling approach and compared the simulation results with measured water retention characteristics. The results showed large differences in peat macropore structure and pore network connectivity between vertical soil layers. The macropore space was more connected and the flow paths through the peat matrix were less tortuous near the soil surface than at deeper depths. In addition, macroporosity, structural anisotropy, and average pore throat diameter decreased with depth. Narrower and more winding air-filled diffusion channels may reduce the rate of CH4 transport as the distance from the peat layer to the soil–air interface increases. Hysteresis was found to affect the evolution of the volume of connected air-filled pore space in unsaturated peat. Thus, the formation of anaerobic pockets may occur in a smaller soil volume and methanogenesis may be slower when the peat is wetting compared to drying conditions. This hysteretic behavior should be taken into account in biogeochemical models to explain the hotspots and episodic spikes of CH4 emissions. The network analysis also suggests that both local and global network connectivity metrics, such as the network average clustering coefficient and closeness centrality, might serve as proxies for assessing the efficiency of CH4 diffusion in air-filled pore networks. However, the applicability of the network metrics was restricted to the high-porosity near-surface layer. The spatial extent and global continuity of the pore network and the spatial distribution of the pores may be reflected in different network metrics in contrasting ways.