Direct and indirect effects of mother's spatial ability on child's spatial ability: What role does the home environment play?

Individual differences in spatial thinking are predictive of children's math and science achievement and later entry into Science, Technology, Engineering, and Mathematics (STEM) disciplines. Little is known about whether parent characteristics predict individual differences in children's spatial thinking. This study aims to understand whether, and to what extent, mother's intrinsic (i.e., mental rotation) and extrinsic (i.e., spatial scaling) spatial ability directly and indirectly, via the variation in home spatial environment, predicts children's intrinsic and extrinsic spatial ability. A total of 165 mothers and their 4-6-year-old children were recruited to participate in a remote video session with an experimenter. Mothers were administered a forced-choice Intrinsic Spatial Toy Preference Task gauging their preference for highly spatial versus less spatial toys and asked questions with the Home Intrinsic Spatial Environmental Questionnaire about the frequency with which they engage their child in spatial activities at home. Mothers completed a Mental Rotations Test and a Spatial Scaling Task adapted for adults. Children were administered the Picture Rotation Task, the Spatial Scaling Task, and the Peabody Picture Vocabulary Test. Structural equation modeling was used to examine direct and indirect, via home spatial environment and toy choices, influences of mother spatial ability on child spatial ability. Contrary to our predictions, we did not find direct, nor indirect, relations between mother and child spatial ability. These findings suggest that researchers should consider alternative conceptualizations of the early home spatial environment beyond the frequency of spatial play in the home. RESEARCH HIGHLIGHTS: The identification of factors that predict individual differences in children's spatial ability is important in order to maximize STEM learning outcomes. Data collection was conducted remotely rather than in traditional preschool or laboratory settings. Contrary to our pre-registered hypotheses, no significant relations between mother spatial ability, the early home spatial environment, and children's development of spatial skills were found. Future research should consider examining the amount of spatial language used in the home or the quality of parent-child interactions during spatial play as potential explanations for individual differences in children's spatial ability.

Differential distribution patterns and assembly processes of soil microbial communities under contrasting vegetation types at distinctive altitudes in the Changbai Mountain

Diversity patterns and community assembly of soil microorganisms are essential for understanding soil biodiversity and ecosystem processes. Investigating the impacts of environmental factors on microbial community assembly is crucial for comprehending the functions of microbial biodiversity and ecosystem processes. However, these issues remain insufficiently investigated in related studies despite their fundamental significance. The present study aimed to assess the diversity and assembly of soil bacterial and fungal communities to altitude and soil depth variations in mountain ecosystems by using 16S and ITS rRNA gene sequence analyses. In addition, the major roles of environmental factors in determining soil microbial communities and assembly processes were further investigated. The results showed a U-shaped pattern of the soil bacterial diversity at 0-10  cm soil depth along altitudes, reaching a minimum value at 1800 m, while the fungal diversity exhibited a monotonically decreasing trend with increasing altitude. At 10-20  cm soil depth, the soil bacterial diversity showed no apparent changes along altitudinal gradients, while the fungal Chao1 and phylogenetic diversity (PD) indices exhibited hump-shaped patterns with increasing altitude, reaching a maximum value at 1200 m. Soil bacterial and fungal communities were distinctively distributed with altitude at the same depth of soil, and the spatial turnover rates in fungi was greater than in bacteria. Mantel tests suggested soil physiochemical and climate variables significantly correlated with the β diversity of microbial community at two soil depths, suggesting both soil and climate heterogeneity contributed to the variation of bacterial and fungal community. Correspondingly, a novel phylogenetic null model analysis demonstrated that the community assembly of soil bacterial and fungal communities were dominated by deterministic and stochastic processes, respectively. The assembly processes of bacterial community were significantly related to the soil DOC and C:N ratio, while the fungal community assembly processes were significantly related to the soil C:N ratio. Our results provide a new perspective to assess the responses of soil microbial communities to variations with altitude and soil depth.

Distinct Ecological Processes Mediate Domain-Level Differentiation in Microbial Spatial Scaling

The spatial scaling of biodiversity, such as the taxa-area relationship (TAR) and distance-decay relationship (DDR), is a typical ecological pattern that is followed by both microbes and macrobes in natural ecosystems. Previous studies focusing on microbes mainly aimed to address whether and how different types of microbial taxa differ in spatial scaling patterns, leaving the underlying mechanisms largely untouched. In this study, the spatial scaling of different microbial domains and their associated ecological processes in an intertidal zone were comparatively investigated. The significant spatial scaling of biodiversity could be observed across all microbial domains, including archaea, bacteria, fungi, and protists. Among them, archaea and fungi were found with much stronger DDR slopes than those observed in bacteria and protists. For both TAR and DDR, rare subcommunities were mainly responsible for the observed spatial scaling patterns, except for the DDR of protists and bacteria. This was also evidenced by extending the TAR and DDR diversity metrics to Hill numbers. Further statistical analyses demonstrated that different microbial domains were influenced by different environmental factors and harbored distinct local community assembly processes. Of these, drift was mainly responsible for the compositional variations of bacteria and protists. Archaea were shaped by strong homogeneous selection, whereas fungi were more affected by dispersal limitation. Such differing ecological processes resulted in the domain-level differentiation of microbial spatial scaling. This study links ecological processes with microbial spatial scaling and provides novel mechanistic insights into the diversity patterns of microbes that belong to different trophic levels. IMPORTANCE As the most diverse and numerous life form on Earth, microorganisms play indispensable roles in natural ecological processes. Revealing their diversity patterns across space and through time is of essential importance to better understand the underlying ecological mechanisms controlling the distribution and assembly of microbial communities. However, the diversity patterns and their underlying ecological mechanisms for different microbial domains and/or trophic levels require further exploration. In this study, the spatial scaling of different microbial domains and their associated ecological processes in a mudflat intertidal zone were investigated. The results showed different spatial scaling patterns for different microbial domains. Different ecological processes underlie the domain-level differentiation of microbial spatial scaling. This study links ecological processes with microbial spatial scaling to provide novel mechanistic insights into the diversity patterns of microorganisms that belong to different trophic levels.

Environmental drivers and spatial scaling of species abundance distributions in Palaearctic grassland vegetation

Species abundance distributions (SADs) link species richness with species abundances and are an important tool in the quantitative analysis of ecological communities. Niche‐based and sample‐based SAD models predict different spatial scaling properties of SAD parameters. However, empirical research on SAD scaling properties is largely missing. Here we extracted percentage cover values of all occurring vascular plants as proxies of their abundance in 1725 10‐m² plots from the GrassPlot database, covering 47 regional data sets of 19 different grasslands and other open vegetation types of the Palaearctic biogeographic realm. For each plot, we fitted the Weibull distribution, a model that is able to effectively mimic other distributions like the log‐series and lognormal, to the species–log abundance rank order distribution. We calculated the skewness and kurtosis of the empirical distributions and linked these moments, along with the shape and scale parameters of the Weibull distribution, to plot climatic and soil characteristics. The Weibull distribution provided excellent fits to grassland plant communities and identified four basic types of communities characterized by different degrees of dominance. Shape and scale parameter values of local communities on poorer soils were largely in accordance with log‐series distributions. Proportions of subdominant species tended to be lower than predicted by the standard lognormal SAD. Successive accumulation of plots of the same vegetation type yielded nonlinear spatial scaling of SAD moments and Weibull parameters. This scaling was largely independent of environmental correlates and geographic plot position. Our findings caution against simple generalizations about the mechanisms that generate SADs. We argue that in grasslands, lognormal‐type SADs tend to prevail within a wider range of environmental conditions, including more extreme habitats such as arid environments. In contrast, log‐series distributions are mainly restricted to comparatively species‐rich communities on humid and fertile soils.

Anthropogenic drivers of avian community turnover from local to regional scales

Anthropogenic change has altered the composition and function of ecological communities across the globe. As a result, there is a need for studies examining observed community compositional change and determining whether and how anthropogenic change drivers may be influencing that turnover. In particular, it is also important to determine to what extent community turnover is idiosyncratic or if turnover can be explained by predictable responses across species based on traits or niche characteristics. Here, we measured turnover in avian communities across North America from 1990 to 2016 in the Breeding Bird Survey using an ordination method, and modeled turnover as a function of land use and climate change drivers from local to regional scales. We also examined how turnover may be attributed to species groups, including foraging guilds, trophic groups, migratory distance, and breeding biomes. We found that at local scales, land use change explained a greater proportion of variance in turnover than climate change variables, while as scale increased, trends in temperature explained a greater proportion of variance in turnover. We also found across the study region, turnover could be attributed to one of a handful of species undergoing strong expansions or strong declines over the study time period. We did not observe consistent patterns in compositional change in any trait groups we examined except for those that included previously identified highly influential species. Our results have two important implications: First, the relative importance of different anthropogenic change drivers may vary with scale, which should be considered in studies' modeling impacts of global change on biodiversity. Second, in North American avian communities, individual species undergoing large shifts in population may drive signals in compositional change, and composite community turnover metrics should be carefully selected as a result.

Steeper spatial scaling patterns of subsoil microbiota are shaped by deterministic assembly process

Although many studies have investigated the spatial scaling of microbial communities living in surface soils, very little is known about the patterns within deeper strata, nor is the mechanism behind them. Here, we systematically assessed spatial scaling of prokaryotic biodiversity within three different strata (Upper: 0-20 cm, Middle: 20-40 cm, and Substratum: 40-100 cm) in a typical grassland by examining both distance-decay (DDRs) and species-area relationships (SARs), taxonomically and phylogenetically, as well as community assembly processes. Each layer exhibited significant biogeographic patterns in both DDR and SAR (p < .05), with taxonomic turnover rates higher than phylogenetic ones. Specifically, the spatial turnover rates, β and z values, respectively, ranged from 0.016 ± 0.005 to 0.023 ± 0.005 and 0.065 ± 0.002 to 0.077 ± 0.004 across soil strata, and both increased with depth. Moreover, the prokaryotic community in grassland soils assembled mainly according to deterministic rather than stochastic mechanisms. By using normalized stochasticity ratio (NST) based on null model, the relative importance of deterministic ratios increased from 48.0 to 63.3% from Upper to Substratum, meanwhile a phylogenetic based method revealed average βNTI also increased with depth, from -5.29 to 19.5. Using variation partitioning and distance approaches, both geographic distance and soil properties were found to strongly affect biodiversity structure, the proportions increasing with depth, but spatial distance was always the main underlying factor. These indicated increasingly deterministic proportions in accelerating turnover rates for spatial assembly of prokaryotic biodiversity. Our study provided new insights on biogeography in different strata, revealing importance of assembly patterns and mechanisms of prokaryote communities in below-surface soils.

An overview of agent-based models in plant biology and ecology

Agent-based modelling (ABM) has become an established methodology in many areas of biology, ranging from the cellular to the ecological population and community levels. In plant science, two different scales have predominated in their use of ABM. One is the scale of populations and communities, through the modelling of collections of agents representing individual plants, interacting with each other and with the environment. The other is the scale of the individual plant, through the modelling, by functional-structural plant models (FSPMs), of agents representing plant building blocks, or metamers, to describe the development of plant architecture and functions within individual plants. The purpose of this review is to show key results and parallels in ABM for growth, mortality, carbon allocation, competition and reproduction across the scales from the plant organ to populations and communities on a range of spatial scales to the whole landscape. Several areas of application of ABMs are reviewed, showing that some issues are addressed by both population-level ABMs and FSPMs. Continued increase in the relevance of ABM to environmental science and management will be helped by greater integration of ABMs across these two scales.

First demonstration of effective spatial training for near transfer to spatial performance and far transfer to a range of mathematics skills at 8 years

There is evidence that spatial thinking is malleable, and that spatial and mathematical skills are associated (Mix et al. [2016] Journal of Experimental Psychology: General, 145, 1206; Mix et al. [2017] Journal of Cognition and Development, 18, 465; Uttal et al. [2013] Psychological Bulletin, 139, 352). However, few studies have investigated transfer of spatial training gains to mathematics outcomes in children, and no known studies have compared different modes of spatial instruction (explicit vs. implicit instruction). Based on a sample of 250 participants, this study compared the effectiveness of explicit and implicit spatial instruction in eliciting near transfer (to the specific spatial skills trained), intermediate transfer (to untrained spatial skills) and far transfer (to mathematics domains) at age 8. Spatial scaling and mental rotation skills were chosen as training targets as previous studies have found, and proposed explanations for, associations between these skills and mathematics in children of this age (Journal of Experimental Psychology: General, 145, 2016 and 1206). In this study, spatial training led to near, intermediate and far transfer of gains. Mental visualization and proportional reasoning were proposed to explain far transfer from mental rotation and spatial scaling skills respectively. For most outcomes, except for geometry, there was no difference in the effectiveness of implicit (practice with feedback) compared to explicit instruction (instructional videos). From a theoretical perspective, the study identified a specific causal effect of spatial skills on mathematics skills in children. Practically, the results also highlight the potential of instructional videos as a method of introducing spatial thinking into the classroom.

Responses of species abundance distribution patterns to spatial scaling in subtropical secondary forests

To quantify and assess the processes underlying community assembly and driving tree species abundance distributions(SADs) with spatial scale variation in two typical subtropical secondary forests in Dashanchong state-owned forest farm, two 1-ha permanent study plots (100-m × 100-m) were established. We selected four diversity indices including species richness, Shannon-Wiener, Simpson and Pielou, and relative importance values to quantify community assembly and biodiversity. Empirical cumulative distribution and species accumulation curves were utilized to describe the SADs of two forests communities trees. Three types of models, including statistic model (lognormal and logseries model), niche model (broken-stick, niche preemption, and Zipf-Mandelbrodt model), and neutral theory model, were estimated by the fitted SADs. Simulation effects were tested by Akaike's information criterion (AIC) and Kolmogorov-Smirnov test. Results found that the Fagaceae and Anacardiaceae families were their respective dominance family in the evergreen broad-leaved and deciduous mixed communities. According to original data and random sampling predictions, the SADs were hump-shaped for intermediate abundance classes, peaking between 8 and 32 in the evergreen broad-leaved community, but this maximum increased with size of total sampled area size in the deciduous mixed community. All niche models could only explain SADs patterns at smaller spatial scales. However, both the neutral theory and purely statistical models were suitable for explaining the SADs for secondary forest communities when the sampling plot exceeded 40 m. The results showed the SADs indicated a clear directional trend toward convergence and similar predominating ecological processes in two typical subtropical secondary forests. The neutral process gradually replaced the niche process in importance and become the main mechanism for determining SADs of forest trees as the sampling scale expanded. Thus, we can preliminarily conclude that neutral processes had a major effect on biodiversity patterns in these two subtropical secondary forests but exclude possible contributions of other processes.

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

Coarse climate change projections for species living in a fine-scaled world

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change.

A Matter of Balance: Motor Control is Related to Children's Spatial and Proportional Reasoning Skills

Recent research has shown close links between spatial and mathematical thinking and between spatial abilities and motor skills. However, longitudinal research examining the relations between motor, spatial, and mathematical skills is rare, and the nature of these relations remains unclear. The present study thus investigated the relation between children's motor control and their spatial and proportional reasoning. We measured 6-year-olds' spatial scaling (i.e., the ability to reason about different-sized spaces), their mental transformation skills, and their ability to balance on one leg as an index for motor control. One year later (N = 126), we tested the same children's understanding of proportions. We also assessed several control variables (verbal IQ and socio-economic status) as well as inhibitory control, visuo-spatial and verbal working memory. Stepwise hierarchical regressions showed that, after accounting for effects of control variables, children's balance skills significantly increased the explained variance in their spatial performance and proportional reasoning. Our results suggest specific relations between balance skills and spatial as well as proportional reasoning skills that cannot be explained by general differences in executive functioning or intelligence.

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Small-scale field experiments accurately scale up to predict density dependence in reef fish populations at large scales

Field experiments provide rigorous tests of ecological hypotheses but are usually limited to small spatial scales. It is thus unclear whether these findings extrapolate to larger scales relevant to conservation and management. We show that the results of experiments detecting density-dependent mortality of reef fish on small habitat patches scale up to have similar effects on much larger entire reefs that are the size of small marine reserves and approach the scale at which some reef fisheries operate. We suggest that accurate scaling is due to the type of species interaction causing local density dependence and the fact that localized events can be aggregated to describe larger-scale interactions with minimal distortion. Careful extrapolation from small-scale experiments identifying species interactions and their effects should improve our ability to predict the outcomes of alternative management strategies for coral reef fishes and their habitats.