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Climate warming disproportionately impacts countries in the Global South by increasing extreme heat exposure. However, geographic disparities in adaptation capacity are unclear. Here, we assess global inequality in green spaces, which urban residents critically rely on to mitigate outdoor heat stress. We use remote sensing data to quantify daytime cooling by urban greenery in the warm seasons across the ~500 largest cities globally. We show a striking contrast, with Global South cities having ~70% of the cooling capacity of cities in the Global North (2.5 ± 1.0 °C vs. 3.6 ± 1.7 °C). A similar gap occurs for the cooling adaptation benefits received by an average resident in these cities (2.2 ± 0.9 °C vs. 3.4 ± 1.7 °C). This cooling adaptation inequality is due to discrepancies in green space quantity and quality between cities in the Global North and South, shaped by socioeconomic and natural factors. Our analyses further suggest a vast potential for enhancing cooling adaptation while reducing global inequality. A 1.5-fold gap exists in green space cooling adaptation between cities in the Global South and North. Enhancing urban green space quality and quantity offers vast potential for improving outdoor cooling adaptation and reducing its global inequality.

Human activities currently play a dominant role in shaping and eroding Earth’s biodiversity, but the historical dynamics leading to this situation are poorly understood and contentious. Importantly, these dynamics are often studied and discussed without an emphasis on cultural evolution, despite its potential importance for past and present biodiversity dynamics. Here, we investigate whether cultural filtering, defined as the impact of cultural evolution on species presence, has driven the range dynamics of five historically widespread megafauna taxa (Asiatic elephant, rhinoceroses, tiger, Asiatic black bear, and brown bear) across China over the past 2 millennia. Data on megafauna and sociocultural history were compiled from Chinese administrative records. While faunal dynamics in China are often linked to climate change at these time scales, our results reveal cultural filtering as the dominant driver of range contractions in all five taxa. This finding suggests that the millennia-long spread of agricultural land and agricultural intensification, often accompanied by expansion of the Han culture, has been responsible for the extirpation of these megafauna species from much of China. Our results suggest that cultural filtering is important for understanding society’s role in the assembly of contemporary communities from historical regional species pools. Our study provides direct evidence that cultural evolution since ancient times has overshadowed climate change in shaping broadscale megafauna biodiversity patterns, reflecting the strong and increasing importance of sociocultural processes in the biosphere.

Urban natural surfaces and non-surface human activities are key factors determining the urban heat island (UHI), but their relative importance remains highly controversial and may vary at different spatial scales and focal urban systems. However, systematic studies on the scale-dependency system-specificity remain largely lacking. Here, we selected 32 major Chinese cities as cases and used Landsat 8 images to retrieve land surface temperature (LST) and quantify natural surface variables using point of interest (POI) data as a measure of the human activity variable and using multiple regression and relative weight analysis to study the contribution and relative importance of these factors to LST at a range of grain sizes (0.25–5 km) and spatial extents (20–60 km). We revealed that the contributions and relative importance of natural surfaces and human activities are largely scale-dependent and system-specific. Natural surfaces, especially vegetation cover, are often the most important UHI determinants for a majority of scales, but the importance of non-surface human activities is increasingly pronounced at a coarser spatial scale with respect to both grain and spatial extent. The scaling relations of the UHI determinants and their relative importance were mostly linear-like at the city-collective level, but highly diverse across individual cities, so reducing non-surface heat emissions could be the most effective measure in particular cases, especially at relatively large spatial scales. This study advances the understanding of UHI formation mechanisms and highlights the complexity of the scale issue underpinning the UHI effect.

Wetland birds are undergoing severe population declines globally, primarily attributed to extensive wetland loss and degradation. The attributes of the landscape surrounding a focal locality, referred to as ‘landscape context’, have been shown to influence the diversity of wetland birds living in the given area. At a global scale, however, the landscape context effects on wetland birds have not been assessed. Here, we assessed the effect of landscape context on the richness of threatened bird species recorded in 334 inland Ramsar wetland sites across the globe. Generalized linear mixed models were used to quantify the relationship between the richness of these bird species and the landscape context of the Ramsar sites. Variation partitioning was used to quantify the independent explanatory power of landscape context for comparison between migratory and non-migratory species. The overall and independent explanatory power of landscape context for the global-scale richness pattern of threatened avifauna reached ca. 17% and 3%, respectively, with the scale of peak explanatory power being 5 times the area of a focal Ramsar site. The independent explanatory power of landscape context was significantly higher for migratory species (ca. 30%) than for non-migratory ones (ca. 3%). Among the landscape context metrics, wetland habitat loss and fragmentation were most strongly associated with the global-scale richness of threatened migrant species at Ramsar sites. Our results suggest that even at macroecological scales, landscape context contributes to shaping the richness pattern of threatened bird species, especially for migrants. These findings provide useful insight for managing landscapes surrounding Ramsar sites, in order to improve conservation effectiveness for wetland birds worldwide.

Presently, China has the largest high-speed rail (HSR) system in the world. However, our understanding of the network structure of the world's largest HSR system remains largely incomplete due to the limited data available. In this study, a publicly available data source, namely, information from a ticketing website, was used to collect an exhaustive dataset on the stations and routes within the Chinese HSR system. The dataset included all 704 HSR stations that had been built as of June, 2016. A classical set of frequently used metrics based on complex network theory were analyzed, including degree centrality, betweenness centrality, and closeness centrality. The frequency distributions of all three metrics demonstrated highly consistent bimodal-like patterns, suggesting that the Chinese HSR network consists of two distinct regimes. The results indicate that the Chinese HSR system has a hierarchical structure, rather than a scale-free structure as has been commonly observed. To the best of our knowledge, such a network structure has not been found in other railway systems, or in transportation systems in general. Follow-up studies are needed to reveal the formation mechanisms of this hierarchical network structure.

Biotic interactions that hierarchically organize ecosystems by driving ecological and evolutionary processes across spatial scales are ubiquitous in our biosphere. Biotic interactions have been extensively studied at local and global scales, but how long-distance, cross-ecosystem interactions at intermediate landscape scales influence the structure, function, and resilience of ecological systems remains poorly understood. We used remote sensing, modeling, and field data to test the hypothesis that the long-distance impact of an invasive species dramatically affects one of the largest tidal flat ecosystems in East Asia. We found that the invasion of exotic cordgrass Spartina alterniflora can produce long-distance effects on native species up to 10 km away, driving decadal coastal ecosystem transitions. The invasive cordgrass at low elevations facilitated the expansion of the native reed Phragmites australis at high elevations, leading to the massive loss and reduced resilience of the iconic Suaeda salsa “Red Beach” marshes at intermediate elevations, largely as a consequence of reduced soil salinity across the landscape. Our results illustrate the complex role that long-distance interactions can play in shaping landscape structure and ecosystem resilience and in bridging the gap between local and global biotic interactions.

Context Urbanization has a profound impact on biodiversity worldwide. The commonly applied ‘urban–rural gradient’ approach often yields contrasting patterns of insect diversity. Integrating local-scale habitat and landscape-scale attributes that act as filters of community assemblage (‘local-landscape filtering’) may help reconcile these contrasting patterns. Objectives Our objective is to evaluate if and to what extent the urban–rural gradient or the local-landscape filtering approach can explain insect diversity patterns across a dryland city. Methods We conducted field surveys of insects at 73 diurnal sites and 20 nocturnal sites across the urban landscape of Urumqi, China. We measured habitat variables and landscape attributes surrounding the local sites. We assessed the urban–rural gradient using distance to urban center, population density, artificial light at night, and impervious surfaces. We used generalized linear mixed models to assess the effects of these factors. Results Insect species richness did not follow clear urban–rural gradient patterns. For diurnal and nocturnal insects, local habitat factors (including plant richness and soil properties) explained ~ 68% and ~ 77% of the variation, whereas landscape attributes explained ~ 32% and ~ 23%, respectively. Diurnal ants and nocturnal mosquitoes/flies were more strongly associated with landscape attributes, while diurnal leafhoppers, moths/butterflies, along with nocturnal thrips, were mostly associated with local habitat. Conclusions Well-tailored local-landscape filtering approaches better explain insect diversity patterns across urban landscapes. Complementary to the urban–rural gradient, this framework facilitates understanding of how urban biodiversity patterns are shaped by particular factors at given spatial scales.

Despite releases of governmental guidelines for promoting physical fitness among the youth in China, the performance of college students in fitness tests has been declining over the past three decades. Obesity and physical inactivity have been proposed as two main causes. However, their relative importance for improving physical fitness remains unclear. To address this knowledge gap, we collected longitudinal data spanning four consecutive years on the physical fitness test for students from Nanjing University, China. Physical education classes of two hours per week were mandatory for the first two years. Using mixed effects models, we quantify the within-subject effects of weight, muscular endurance, sex, and mandatory physical education courses, among other variables, on physical fitness total score. We found that, in spite of the dominance of normal weight among the students, losing weight was positively associated with the total score, with significant sex differences in the associations. Compulsory exercise provided by physical education classes per week had strong positive impacts on the total score, comparable to losing weight of roughly 15–17 kg for males and 5–10 kg for females. Half sex difference in the total score was explained by male students’ poor performance in the muscular endurance represented by pull-ups. Our results suggest that college students in China should engage in physical activity of higher levels to improve their physical fitness, with a heightened awareness of extra fat under normal weight and insufficient muscular endurance.

Aim The aim was to assess whether and to what extent the role of local landscape attributes in shaping macroscopic biodiversity patterns is sensitive to spatial and thematic resolutions of land cover data. Location Sub‐Saharan Africa and continental China. Time period Early 21st century. Taxa studied Terrestrial mammals. Methods We conducted spatial and thematic scaling analyses to generate land cover datasets of different spatial (0.3, 0.5, 1.0 and 9.0 km) and thematic (two, three and five classes) resolutions. We calculated landscape metrics based on the resulting land cover maps and examined the power of landscape metrics for explaining species richness patterns, using non‐spatial (OLS) and spatial (SAR) linear models and random forest (RF) models. We systematically assessed the resolution dependence of explanatory power for different geographical regions, different scaling approaches and different model types. We also compared the explanatory power of landscape attributes with that of macroclimate. Results Collectively, local landscape attributes generally had strong explanatory power for species richness. For the African system, the largest explanatory power was c. 60% based on the OLS models and random forest models and c. 30% based on the non‐spatial components of the SAR models. For the Chinese system, the largest explanatory power was c. 35% based on the OLS models and c. 40% based on the SAR and random forest models. We observed a linear scaling relationship, which is robust to studied systems, scaling approaches and model types. In contrast, the scaling relationship varies substantially among single landscape metrics. At coarse resolutions, the addition of landscape attributes collectively would not improve climate‐envelope models significantly, whereas at finer resolutions, landscape attributes collectively have explanatory power that is close to or even exceeds climate. Main conclusions Local landscape attributes play an important role in shaping macroscopic biodiversity patterns. However, their strength is highly sensitive to both spatial and thematic resolutions of land cover data, with stronger explanatory power detected at finer resolutions. Strong sensitivity to spatial and thematic resolutions makes landscape attributes highly plastic determinants, leading to contrasting conclusions if based on greatly different resolutions of land cover data. Scaling analyses are needed to examine such cross‐scale effects of macroecological determinants systematically.

Purpose of Review Despite the decades-long recognition of the importance of scaling in ecology, our knowledge about many ecological patterns and processes is still largely restricted to particular spatial and temporal scale domains with relatively narrow ranges. There is no exception when it comes to the study of biodiversity, one of the most important and active research fields in ecology. Increasing work suggests that such narrow ranges of scales are in most cases inadequate for addressing conservation challenges associated with biodiversity change. The need for understanding how biodiversity is shaped and will change across different scales is stronger than ever. Recent Findings Here, we review recent progresses of up-scaling and down-scaling biodiversity in the context of global environmental change, with focus on two relatively large spatial scale domains, i.e., the landscape and macroecological scales. Landscape ecology and macroecology are both active, but so-far poorly connected research fields. They share a common central motivation of unraveling spatial patterning of biodiversity and the underlying mechanisms. Our literature review suggests that landscape-scale processes may exert unexpected up-scaling effects to shape biodiversity patterns at macroecological scales, while macroecological processes may generate a range of down-scaling effects on landscape biodiversity. Specifically, although there is a lack of consensus on the underlying mechanisms, it is likely that landscape processes scale up through connectivity and feedback loops within and across landscapes to affect macroecological biodiversity responses. On the other hand, the down-scaling effects of macroecological processes on biodiversity is often confounded with small-scale processes, leading to various responses inconsistent with direct down-scaling extrapolations. In addition, the temporal dimension is indispensable to investigating effects and mechanisms of cross-scale processes. Specifically, long-term (decades and beyond) perspectives are necessary for re-evaluating ecological knowledge obtained from biodiversity responses to short-term environmental changes and recognizing historical legacies of both landscape and macroecological processes on biodiversity at the two spatial scales. Summary Overall, scaling analyses of ecological processes across spatial extents ranging from small habitats to the globe have revealed biodiversity responses to anthropogenic environmental changes as inconsistent with assumptions and extrapolations based on extant ecological knowledge at a few fixed scales. Such analyses are needed to better inform conservation actions and planning practiced mainly at local to macroecological scales. We suggest that elucidating cross-scaling mechanisms and accumulating long-term time series at multiple spatial scales are key to linking landscape ecology and macroecology in terms of biodiversity dynamics. Such efforts would be an important contribution to the ecological basis for managing biodiversity change in the Anthropocene, as these dynamics involve multiple up-scaling and down-scaling processes over time.