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Implementation of wildfire- and climate-adaptation strategies in seasonally dry forests of western North America is impeded by numerous constraints and uncertainties. After more than a century of resource and land use change, some question the need for proactive management, particularly given novel social, ecological, and climatic conditions. To address this question, we first provide a framework for assessing changes in landscape conditions and fire regimes. Using this framework, we then evaluate evidence of change in contemporary conditions relative to those maintained by active fire regimes, i.e., those uninterrupted by a century or more of human-induced fire exclusion. The cumulative results of more than a century of research document a persistent and substantial fire deficit and widespread alterations to ecological structures and functions. These changes are not necessarily apparent at all spatial scales or in all dimensions of fire regimes and forest and nonforest conditions. Nonetheless, loss of the once abundant influence of low- and moderate-severity fires suggests that even the least fire-prone ecosystems may be affected by alteration of the surrounding landscape and, consequently, ecosystem functions. Vegetation spatial patterns in fire-excluded forested landscapes no longer reflect the heterogeneity maintained by interacting fires of active fire regimes. Live and dead vegetation (surface and canopy fuels) is generally more abundant and continuous than before European colonization. As a result, current conditions are more vulnerable to the direct and indirect effects of seasonal and episodic increases in drought and fire, especially under a rapidly warming climate. Long-term fire exclusion and contemporaneous social-ecological influences continue to extensively modify seasonally dry forested landscapes. Management that realigns or adapts fire-excluded conditions to seasonal and episodic increases in drought and fire can moderate ecosystem transitions as forests and human communities adapt to changing climatic and disturbance regimes. As adaptation strategies are developed, evaluated, and implemented, objective scientific evaluation of ongoing research and monitoring can aid differentiation of warranted and unwarranted uncertainties.

This paper provides empirical evidence that helps to answer several key questions relating to the extent of urban sprawl in Europe. Building on the monocentric city model, this study uses existing data sources to derive a set of panel data for 282 European cities at three time points (1990, 2000 and 2006). Two indices of urban sprawl are calculated that, respectively, reflect changes in artificial area and the levels of urban fragmentation for each city. These are supplemented by a set of data on various economic and geographical variables that might explain the variation of the two indices. Using a Hausman-Taylor estimator and random regressors to control for the possible correlation between explanatory variables and unobservable city-level effects, we find that the fundamental conclusions of the standard monocentric model are valid in the European context for both indices. Although the variables generated by the monocentric model explain a large part of the variation of artificial area, their explanatory power for modelling the fragmentation index is relatively low.

As we human beings are living in a multidimensional space all the time. Therefore, spatial ability is vital for the survival and development of individuals. However, males and females show gender differences in this ability. So, are these gender differences influenced by the scale type of spatial ability? It's not well specified. Therefore, to tackle this issue, we conducted the current research from the behavioral and neural level. Study 1 used the general meta-analysis method to explore whether individuals display the same gender differences in large- and small-scale spatial ability. Study 2 used the method of Activation Likelihood Estimation to identify the commonalities and distinctions of the brain activity between males and females on large- and small-scale spatial ability. Study 1 showed that in behavior performance, males outperformed females in both large-scale and small-scale spatial ability, but the effect size of the gender difference in large-scale spatial ability is significantly greater than that in small-scale spatial ability. In addition, Study 2 showed that in terms of neural activity, males and females exhibited both similarities and differences no matter in large-scale or small-scale spatial ability. Especially, the contrast analysis between females and males demonstrated a stronger activation in the brain regions of bilateral lentiform nucleus and bilateral parahippocampal gyrus in large-scale spatial ability, and correspondence in right sub-gyral, right precuneus, and left middle frontal gyrus in small-scale spatial ability. The results indicated that the reason why females performed not so well in large-scale spatial ability was that they were more susceptible to emotions and their parahippocampal gyrus worked less efficiently than males; females performed not so well in small-scale spatial ability because they mostly adopted the egocentric strategy and their sub-gyral also worked less efficiently than males. The two different reasons have made for gender differences in favor of males in terms of spatial ability and such gender differences have different manifestations in large-scale and small-scale spatial ability. Possible implications of the results for understanding the issue of gender differences in spatial ability are discussed.

Appreciating spatial scale is crucial for our understanding of the sociospatial context. Multiscale measures of population have been developed in the segregation and neighborhood effects literatures, which have acknowledged the role of a variety of spatial contexts for individual outcomes and intergroup contacts. Although existing studies dealing with sociospatial inequalities increasingly explore the effects of spatial scale, there has been little systematic evidence on how exposure to sociospatial contexts changes across urban space, both within and between cities. This article presents a multiscale approach to measuring potential exposure to others. Using individual-level register data for the full population of The Netherlands and an exceptionally detailed multiscalar framework of bespoke neighborhoods at 101 spatial scales, we measured the share of non-Western ethnic minorities for three Dutch cities with different urban forms. We created individual and cumulative distance profiles of ethnic exposure, mapped ethnic exposure surfaces, and applied entropy as a measure of scalar variation to compare potential exposure to others in different locations both within and between cities. The multiscale approach can be implemented for examining a variety of social processes, notably segregation and neighborhood effects.

Interest in studying the urban real estate market, especially in investigating the relationship between house prices and related housing characteristics, is rapidly growing. However, this increasing attention is handicapped by a limited consideration of the multi-scale spatial heterogeneity in these relationships. This study uses the rental price data of 72,466 apartments in the Tokyo metropolitan area to examine spatial heterogeneity in the real estate market at multiple spatial scales. Within the framework of spatially varying coefficient (SVC) modeling, we utilized a random effect eigenvector spatial filtering-based SVC (RE-ESF-SVC) model, an approach not previously employed in real estate studies, and compared it with the traditional ESF-SVC model, which has no random effects. Our results show that: (1) except for one housing characteristic that impacts prices consistently throughout the Tokyo metropolitan area, relationships between other characteristics and prices vary from local to global spatial scales; (2) because of the utilization of random effects, RE-ESF-SVC has the unique advantage of making estimations flexibly while maintaining a high performance.

Fine‐scale spatial genetic structure (fine‐scale SGS) refers to the pattern of spatial distribution of genetic variation at the local scale, which can indirectly estimate gene flow among individuals and reveal microevolutionary processes in plant populations. Although fine‐scale SGS is important in explaining dispersal patterns and adaptive variation in plants, few studies have explored its potential application in species conservation strategies. In addition, phenotypic traits, particularly leaf shape, may also exhibit specific spatial variation patterns at fine scales. In this study, we investigated the genetic and leaf shape variation of two genus Quercus species (Quercus glauca Thunb. and Q. multinervis J. Q. Li) and three genus Castanopsis species (Castanopsis tibetana Hance, C. faberi Hance, and C. fargesii Franch.) in Wuyishan National Park in southeastern China. Using genetic markers, we found that Quercus species exhibited stronger fine‐scale SGS and more limited gene flow than Castanopsis species, suggesting greater habitat fragmentation affecting local Quercus species. Leaf morphological analysis revealed inter‐generic differences and partial overlap in leaf shape between Quercus and Castanopsis species, with the greatest variation observed in leaf area (LA) and leaf mass (LM). In addition, all five Fagaceae species exhibited significant diminishing returns, with C. fargesii showing the most pronounced effect and possessing the smallest leaves, which may enhance its adaptability to the harsh environments. Despite the leaf shape overlaps blurring species boundaries between Quercus and Castanopsis species, their genetic structure is remained clearly distinct. The observed differences in the intensity of fine‐scale SGS and leaf shape variation between the two genera reflect their different environmental adaptability, offering new insights into the integration of genetic and phenotypic data for conservation planning. We investigated both fine‐scale SGS and leaf shape variation in five Fagaceae species (Q. glauca, Q. multinervis, C. tibetana, C. faberi, and C. fargesii) from the genera Quercus and Castanopsis in Wuyishan National Park. We found that Quercus species exhibit stronger fine‐scale SGS than Castanopsis species. These two genera show differences in leaf shape, and all five species exhibit a pattern of diminishing returns in leaf trait scaling. Our findings underscore the importance of conserving fine‐scale SGS and considering leaf shape variation in the design of effective conservation strategies.

Aim: The need to go beyond taxonomy to understand patterns in microbial function has led to an increased use of trait-based approaches, yet we know little about how microbial functional traits vary across large-scale environmental gradients in natural ecosystems. Here, we apply a trait-based approach to explore the large-scale variability in the trait structure underlying the processing of dissolved organic matter (DOM) by boreal bacterioplankton communities, as well as its regulation and links to taxonomic composition. Location: Samples were collected from 296 rivers and lakes across five regions in northern Quebec (Canada), which span large gradients in environmental, climatic and geographical properties typical of the boreal zone. Methods: We used the metabolic profiles obtained with Biolog EcoPlates® as an imprint of the trait structure underlying bacterial processing of DOM, and Illumina sequencing of the 16SrRNA gene to characterize the taxonomic composition of these bacterial assemblages. The resulting spatial patterns were compared with an array of climatic, landscape and limnological properties varying at the landscape scale. Results: Despite a clear regional segregation of the sampled sites based on environmental variables, the trait structure of boreal bacteria did not show any regional or ecosystem-specific patterns, but rather was linked to a gradient of quality of DOM. Community trait configurations diverged progressively with decreasing terrestrial influence, probably due to local processes that transform and diversify the available pool of DOM. This DOM quality gradient did not explain the taxonomic biogeography of these communities, which was controlled by a different set of environmental factors. Main conclusions: The functional biogeography of boreal bacterioplankton is driven by the nature of the DOM pool, and particularly by the influence of terrestrial DOM. The lack of coherence between functional and taxonomic biogeographies implies that the environmental controls of freshwater bacterial performance cannot be directly inferred from spatial patterns in taxonomic composition.

Long‐term exposure to particulate matter (PM) pollution may directly increase the risk of developing tuberculosis (TB). Despite the known link, the multi–scale spatiotemporal variations in the burden of TB attributable to long‐term PM exposure remain largely unclear in China. In this study, we conducted a nationwide, multi‐scale risk assessment of the burden of TB attributable to long‐term PM2.5, PM2.5–10, and PM10 exposure from 2013 to 2019, employing the multivariate distributed lag nonlinear model (MVDLNM), Lorenz curve and Gini index. Our health impact assessments indicate that PM exposure has resulted in significant increases in TB burden. Specifically, approximately$1,202 million (95% CI: 801–1,573 million), $ 486 million (95% CI: 398–572 million), and $944 million (95% CI: 767–1,115 million) of health economic costs could be attributed to long‐term exposure to PM2.5, PM2.5–10, and PM10, respectively. Although the overall the burden of TB attributable to PM exposure was significantly reduced from 2013 to 2019, regional inequalities have become more pronounced. The Gini index reveals a clear disparity in the burden of TB related to PM exposure across provincial, city, and county levels. These disparities are most pronounced at the county level (0.4914–0.6801), followed by the city level (0.4135–0.6382), and are least evident at the province level (0.3672–0.6078). Overall, the regional inequalities in the burden of TB are more pronounced at finer spatial scales. Our study highlights the health impacts of long‐term exposure to PM on the incidence of TB across different spatiotemporal scales, and the findings provide strong scientific evidence for pollution mitigation and efforts to reduce regional inequality. Plain Language Summary Ambient particulate matter (PM) pollution is a significant environmental risk factor contributing to the high tuberculosis (TB) burden in China. Although substantial improvements in air quality have been achieved in recent years, the impact of these improvements on TB incidence remains unclear, and regional exposure inequity has seldom been explored. This study systematically evaluates how regional disparities in health economic costs attributable to long‐term exposure to different sizes of PM (PM2.5, PM2.5–10, and PM10) vary over time and across spatial scales, including the macro‐scale (provincial level), meso‐scale (city level), and micro‐scale (county level). It found that long‐term PM exposure caused billions of dollars in TB‐related health costs, with PM2.5 being the largest contributor. While overall PM‐related TB burden decreased nationwide from 2013 to 2019, inequalities between regions grew, especially at finer scales like counties. Disparities in TB burden were highest at the county level, demonstrating that local conditions strongly influence health risks. This study highlights the urgent need for targeted air quality and health policies in high‐risk areas to reduce TB burden and address health inequalities. Key Points Long‐term exposure to PM2.5–10 was associated with an increased risk of tuberculosis incidence Health economic losses attributable to long‐term particulate matter exposure exceeded one billion USD from 2013 to 2019 Regional inequalities in the tuberculosis burden were more pronounced at finer spatial scales

Question It is debated whether forest understory communities will be sensitive to projected climate change or inert due to the regulating effect of local site conditions and soil parameters. A distinction between the relative importance of climate or soil is often hardly possible because both factors usually change at different spatial scales in forests. Here, we compare the relative influence of climate and soil on the forest understory vegetation in lowland beech forest ecosystems (Fagus sylvatica), which were selected for their ecological homogeneity. Location Nine sites along a strong temperature gradient (ΔT = 4 K from east to west in winter, south to north in summer) between Rostock (Germany) and Gdańsk (Poland) in a Baltic Quaternary ground moraine landscape. Methods We conducted a vegetation survey in 55 vegetation plots (80 m2 each) across nine forest sites mono‐dominated by European beech and analysed how much variation in understory plant composition is explained by climate and soil parameters. Results Soil explained 32% of the compositional variation of understory vegetation across sites, climate 22%, and their interaction 14%. Topsoil pH, subsoil organic matter content, and subsoil C/N ratio were the most important soil variables; growing season temperature and annual water availability were the most important climatic variables. Conclusion The strong dependence on soil properties could moderate the response of the forest understory vegetation to projected climate change. Forest soil properties, however, also depend on the dominant tree species and the macroclimate. To predict climate change impacts on forest understory vegetation, climate change assessments should consider indirect climate change effects as well as interactions between climate and soil. In European lowland beech forests, soil explained 32% of the compositional variation of understory vegetation across sites, climate 22%, and their interaction 14%. The stronger dependence on soil properties could moderate the response of the forest understory vegetation to projected climate change. Future climate change assessments should also account for interactions between climate and soil.

Aim In a selected literature survey we reviewed studies on the habitat heterogeneity-animal species diversity relationship and evaluated whether there are uncertainties and biases in its empirical support. Location World-wide. Methods We reviewed 85 publications for the period 1960-2003. We screened each publication for terms that were used to define habitat heterogeneity, the animal species group and ecosystem studied, the definition of the structural variable, the measurement of vegetation structure and the temporal and spatial scale of the study. Main conclusions The majority of studies found a positive correlation between habitat heterogeneity/diversity and animal species diversity. However, empirical support for this relationship is drastically biased towards studies of vertebrates and habitats under anthropogenic influence. In this paper, we show that ecological effects of habitat heterogeneity may vary considerably between species groups depending on whether structural attributes are perceived as heterogeneity or fragmentation. Possible effects may also vary relative to the structural variable measured. Based upon this, we introduce a classification framework that may be used for across-studies comparisons. Moreover, the effect of habitat heterogeneity for one species group may differ in relation to the spatial scale. In several studies, however, different species groups are closely linked to 'keystone structures' that determine animal species diversity by their presence. Detecting crucial keystone structures of the vegetation has profound implications for nature conservation and biodiversity management.