Self-organization as a mechanism of resilience in dryland ecosystems.

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the resilience of drylands. Overall, our findings contribute to a deeper understanding of the relationship between spatial vegetation patterns and dryland resilience. They also represent a significant step forward in the development of indicators for ecosystem resilience, which are critical tools for managing and preserving these valuable ecosystems in a warmer and more arid world.

The global biogeography and environmental drivers of fairy circles.

Fairy circles (FCs) are regular vegetation patterns found in drylands of Namibia and Western Australia. It is virtually unknown whether they are also present in other regions of the world and which environmental factors determine their distribution. We conducted a global systematic survey and found FC-like vegetation patterns in 263 sites from 15 countries and three continents, including the Sahel, Madagascar, and Middle-West Asia. FC-like vegetation patterns are found in environments characterized by a unique combination of soil (including low nutrient levels and high sand content) and climatic (arid regions with high temperatures and high precipitation seasonality) conditions. In addition to these factors, the presence of specific biological elements (termite nests) in certain regions also plays a role in the presence of these patterns. Furthermore, areas with FC-like vegetation patterns also showed more stable temporal productivity patterns than those of surrounding areas. Our study presents a global atlas of FCs and provides unique insights into the ecology and biogeography of these fascinating vegetation patterns.

Temporal dynamic patterns of the ventromedial prefrontal cortex underlie the association between rumination and depression.

As a major contributor to the development of depression, rumination has proven linked with aberrant default-mode network (DMN) activity. However, it remains unclear how the spontaneous spatial and temporal activity of DMN underlie the association between rumination and depression. To illustrate this issue, behavioral measures and resting-state functional magnetic resonance images were connected in 2 independent samples (NSample1 = 100, NSample2 = 95). Fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) were used to assess spatial characteristic patterns, while voxel-wise functional concordance (across time windows) (VC) and Hurst exponent (HE) were used to assess temporal dynamic patterns of brain activity. Results from both samples consistently show that temporal dynamics but not spatial patterns of DMN are associated with rumination. Specifically, rumination is positively correlated with HE and VC (but not fALFF and ReHo) values, reflecting more consistent and regular temporal dynamic patterns in DMN. Moreover, subregion analyses indicate that temporal dynamics of the ventromedial prefrontal cortex (VMPFC) reliably predict rumination scores. Furthermore, mediation analyses show that HE and VC of VMPFC mediate the association between rumination and depression. These findings shed light on neural mechanisms of individual differences in rumination and corresponding risk for depression.

Near-natural streams: Spatial factors are key in shaping multiple facets of zooplankton α and ß diversity.

In near-natural basins, zooplankton are key hubs for maintaining aquatic food webs and organic matter cycles. However, the spatial patterns and drivers of zooplankton in streams are poorly understood. This study registered 165 species of zooplankton from 147 sampling sites (Protozoa, Rotifers, Cladocera and Copepods), integrating multiple dimensions (i.e., taxonomic, functional, and phylogenetic) and components (i.e., total, turnover, and nestedness) of α and ß diversity. This study aims to reveal spatial patterns, mechanisms, correlations, and relative contribution of abiotic factors (i.e., local environment, geo-climatic, land use, and spatial factors) through spatial interpolation (ordinary kriging), mantel test, and variance partitioning analysis (VPA). The study found that α diversity is concentrated in the north, while ß diversity is more in the west, which may be affected by typical habitat, hydrological dynamics and underlying mechanisms. Taxonomic and phylogenetic ß diversity is dominated by turnover, and metacommunity heterogeneity is the result of substitution of species and phylogeny along environmental spatial gradients. Taxonomic and phylogenetic ß diversity were strongly correlated (r from 0.91 to 0.95), mainly explained by historical/spatial isolation processes, community composition, generation time, and reproductive characteristics, and this correlation provides surrogate information for freshwater conservation priorities. In addition, spatial factors affect functional and phylogenetic α diversity (26%, 28%), and environmental filtering and spatial processes combine to drive taxonomic α diversity (10%) and phylogenetic ß diversity (11%). Studies suggest that spatial factors are key to controlling the community structure of zooplankton assemblages in near-natural streams, and that the relative role of local environments may depend on the dispersal capacity of species. In terms of diversity conservation, sites with high variation in uniqueness should be protected (i) with a focus on the western part of the thousand islands lake catchment and (ii) increasing effective dispersal between communities to facilitate genetic and food chain transmission.

The role of memory-based movements in the formation of animal home ranges.

Most animals live in spatially-constrained home ranges. The prevalence of this space-use pattern in nature suggests that general biological mechanisms are likely to be responsible for their occurrence. Individual-based models of animal movement in both theoretical and empirical settings have demonstrated that the revisitation of familiar areas through memory can lead to the formation of stable home ranges. Here, we formulate a deterministic, mechanistic home range model that includes the interplay between a bi-component memory and resource preference, and evaluate resulting patterns of space-use. We show that a bi-component memory process can lead to the formation of stable home ranges and control its size, with greater spatial memory capabilities being associated with larger home range size. The interplay between memory and resource preferences gives rise to a continuum of space-use patterns-from spatially-restricted movements into a home range that is influenced by local resource heterogeneity, to diffusive-like movements dependent on larger-scale resource distributions, such as in nomadism. Future work could take advantage of this model formulation to evaluate the role of memory in shaping individual performance in response to varying spatio-temporal resource patterns.

Cluster pattern analysis of environmental stressors and quantifying their impact on all-cause mortality in Belgium.

Environmental stress represents an important burden on health and leads to a considerable number of diseases, hospitalisations, and excess mortality. Our study encompasses a representative sample size drawn from the Belgian population in 2016 (n = 11.26 million, with a focus on n = 11.15 million individuals). The analysis is conducted at the geographical level of statistical sectors, comprising a total of n = 19,794 sectors, with a subset of n = 18,681 sectors considered in the investigation. We integrated multiple parameters at the finest spatial level and constructed three categories of environmental stress through clustering: air pollution, noise stress and stress related to specific land-use types. We observed identifiable patterns in the spatial distribution of stressors within each cluster category. We assessed the relationship between age-standardized all-cause mortality rates (ASMR) and environmental stressors. Our research found that especially very high air pollution values in areas where traffic is the dominant local component of air pollution (ASMR + 14,8%, 95% CI: 10,4 - 19,4%) and presence of industrial land (ASMR + 14,7%, 95% CI: 9,4 - 20,2%) in the neighbourhood are associated with an increased ASMR. Cumulative exposure to multiple sources of unfavourable environmental stress (simultaneously high air pollution, high noise, presence of industrial land or proximity of primary/secondary roads and lack of green space) is associated with an increase in ASMR (ASMR + 26,9%, 95% CI: 17,1 - 36,5%).

Tracing spatial patterns of lacustrine groundwater discharge in a closed inland lake using stable isotopes.

Tracing lacustrine groundwater discharge (LGD) is essential for understanding the hydrological cycle and water chemistry behaviour of lakes. LGD usually exhibits large spatial variability, but there are few reports on quantitatively revealing the spatial patterns of LGD at the whole lake scale. This study investigated the spatial patterns of LGD in Daihai Lake, a typical closed inland lake in northern China, based on the stable isotopes (δ2H and δ18O) of groundwater, surface water, and sediment pore water (SPW). The results showed that there were significant differences between the δ2H and δ18O values of different water bodies in the Daihai Lake Basin: groundwater < SPW < lake water. The LGD through SPW was found to be an important recharge pathway for the lake. Accordingly, stable isotopes of SPW showed that LGD in the northeastern and northwestern of Daihai Lake was significantly greater both horizontally and vertically than that in the other regions, and the proportions of groundwater in SPW in these two regions were 55.53% and 29.84%, respectively. Additionally, the proportion of groundwater in SPW showed a significant increase with profile depth, and the proportion reached 100% at 50 cm below the sediment surface in the northeastern of the lake where the LGD intensity was strongest. The total LGD to Daihai Lake was 1.47 × 107 m3/a, while the LGD in the northeastern and northwestern of the lake exceeded 1.9 × 106 m3/a. This study provides new insights into assessing the spatial patterns of LGD and water resource management in lakes.

Exploring the Spatial and Temporal Patterns of Children and Adolescents with COVID-19 Infections in Slovakia during March 2020 to July 2022.

Background and Objectives: The COVID-19 pandemic has had a significant global impact, necessitating a comprehensive understanding of its spatiotemporal patterns. The objective of this study is to explore the spatial and temporal patterns of COVID-19 infections among five age groups (<1, 1-4, 5-9, 10-14, and 15-19 years) in 72 districts of Slovakia on a quarterly basis from March 2020 to July 2022. Material and Methods: During the study period, a total of 393,429 confirmed PCR cases of COVID-19 or positive antigen tests were recorded across all studied age groups. The analysis examined the spatiotemporal spread of COVID infections per quarter, from September 2021 to May 2022. Additionally, data on hospitalizations, intensive care unit (ICU) admissions, pulmonary ventilation (PV), and death cases were analyzed. Results: The highest number of COVID-19 infections occurred between September 2021 and May 2022, particularly in the 10-14-year-old group (68,695 cases), followed by the 15-19-year-old group (62,232 cases), while the lowest incidence was observed in the <1-year-old group (1235 cases). Out of the total confirmed PCR cases, 18,886 individuals required hospitalization, 456 needed ICU admission, 402 received pulmonary ventilation, and only 16 died. The analysis of total daily confirmed PCR cases for all regions showed two major peaks on 12 December 2021 (6114 cases) and 1 February 2022 (3889 cases). Spatial mapping revealed that during December 2021 to February 2022, the highest number of infections in all age groups were concentrated mainly in Bratislava. Moreover, temporal trends of infections within each age group, considering monthly and yearly variations, exhibited distinct spatial patterns, indicating localized outbreaks in specific regions. Conclusions: The spatial and temporal patterns of COVID-19 infections among different age groups in Slovakia showed a higher number of infections in the 10-14-year-old age group, mainly occurring in urban districts. The temporal pattern of the spread of the virus to neighboring urban and rural districts reflected the movement of infected individuals. Hospitalizations, ICU and PV admissions, and deaths were relatively low. The study highlights the need for more proactive measures to contain outbreaks promptly and ensure the resilience of healthcare systems against future pandemics.

Exploring the geospatial epidemiology of breast cancer in Iran: identifying significant risk factors and spatial patterns for evidence-based prevention strategies.

BACKGROUND: Breast Cancer (BC) is a formidable global health challenge, and Iran is no exception, with BC accounting for a significant proportion of women's malignancies. To gain deeper insights into the epidemiological characteristics of BC in Iran, this study employs advanced geospatial techniques and feature selection methods to identify significant risk factors and spatial patterns associated with BC incidence. METHODS: Using rigorous statistical methods, geospatial data from Iran, including cancer-related, sociodemographic, healthcare infrastructure, environmental, and air quality data at the provincial level, were meticulously analyzed. Age-standardized incidence rates (ASR) are calculated, and different regression models are used to identify significant variables associated with BC incidence. Spatial analysis techniques, including global and local Moran's index, geographically weighted regression, and Emerging hotspot analysis, were utilized to examine geospatial patterns, identify clustering and hotspots, and assess spatiotemporal distribution of BC incidence. RESULTS: The findings reveal that BC predominantly affects women (98.03%), with higher incidence rates among those aged 50 to 79. Isfahan (ASR = 26.1) and Yazd (ASR = 25.7) exhibit the highest rates. Significant predictors of BC incidence, such as marriage, tertiary education attainment rate, physician-to-population ratio, and PM2.5 air pollution, are identified through regression models. CONCLUSION: The study's results provide valuable information for the development of evidence-based prevention strategies to reduce the burden of BC in Iran. The findings underscore the importance of early detection, health education campaigns, and targeted interventions in high-risk clusters and adjacent regions. The geospatial insights generated by this study have implications for policy-makers, researchers, and public health practitioners, facilitating the formulation of effective BC prevention strategies tailored to the unique epidemiological patterns in Iran.

Patterns and abiotic drivers of soil organic carbon in perennial tea (Camellia sinensis L.) plantation system of China.

Understanding soil organic carbon (SOC), the largest carbon (C) pool of a terrestrial ecosystem, is essential for mitigating climate change. Currently, the spatial patterns and drivers of SOC in the plantations of tea, a perennial leaf crop, remain unclear. Therefore, the present study surveyed SOC across the main tea-producing areas of China, which is the largest tea producer in the world. We analyzed the soil samples from tea plantations under different scenarios, such as provinces, regions [southwest China (SW), south China (SC), south Yangtze (SY), and north Yangtze (NY)], climatic zones (temperate, subtropical, and tropical), and cultivars [large-leaf (LL) and middle or small-leaf (ML) cultivars]. Preliminary analysis revealed that most tea-producing areas (45%) had SOC content ranging from 10 to 20 g kg-1. The highest SOC was recorded for Yunnan among the various provinces, the SW tea-producing area among the four regions, the tropical region among the different climatic zones, and the areas with LL cultivars compared to those with ML cultivars. Further Pearson correlation analysis demonstrated significant associations between SOC and soil variables and random forest modeling (RF) identified that total nitrogen (TN) and available aluminum [Ava(Al)] of soil explained the maximum differences in SOC. Besides, a large indirect effect of geography (latitude and altitude) on SOC was detected through partial least squares path modeling (PLS-PM) analysis. Thus, the study revealed a high spatial heterogeneity in SOC across the major tea-producing areas of China. The findings also serve as a basis for planning fertilization strategies and C sequestration policies for tea plantations.

Exploring spatial patterns, and identifying factors associated with insufficient cash or food received from a productive safety net program among eligible households in Ethiopia: a spatial and multilevel analysis as an input for international food aid programmers.

BACKGROUND: In low-income countries, households' food insecurity and the undernutrition of children are the main health problems. Ethiopia is vulnerable to food insecurity and undernutrition among children because its agricultural production system is traditional. Hence, the productive safety net program (PSNP) is implemented as a social protection system to combat food insecurity and enhance agricultural productivity by providing cash or food assistance to eligible households. So, this study aimed to explore spatial patterns of households' insufficient cash or food receiving from PSNP, and identify its associated factors in Ethiopia. METHODS: The 2019 Ethiopian Mini Demographic and Health Survey dataset was used. A total of 8595 households were included in this study. Data management and descriptive analysis were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for spatial exploration and visualization. SaTScan version 9.5 software was used for spatial scan statistics reports. In the multilevel mixed effect logistic regression analysis, explanatory variables with a p-value of less than 0.05 were considered significant factors. RESULTS: Overall, 13.5% (95% CI: 12.81-14.27%) of the households' level beneficiaries received cash or food from PSNP. The spatial distribution of households' benficiaries received cash or food from PSNP was not random, and good access to cash or food from PSNP was detected in Addis Ababa, SNNPR, Amhara, and Oromia regions. Households' heads aged 25-34 (AOR:1.43, 95% CI: 1.02, 2.00), 35-44 (AOR: 2.41, 95% CI: 1.72, 3.37), and > 34 (AOR: 2.54, 95% CI: 1.83, 3.51) years, being female (AOR: 1.51, 95% CI: 1.27,1.79), poor households (AOR: 1.91, 95% CI:1.52, 2.39), Amhara (AOR:.14, 95% CI: .06, .39) and Oromia (AOR:.36, 95% CI:.12, 0.91) regions, being rural residents (AOR:2.18, 95% CI: 1.21,3.94), and enrollment in CBHS (AOR: 3.34, 95% CI:2.69,4.16) are statistically significant factors. CONCLUSIONS: Households have limited access to cash or food from the PSNP. Households in Addis Ababa, SNNPR, Amhara, and Oromia regions are more likely to receive benefits from PSNP. Encouraging poor and rural households to receive benefits from the PSNP and raise awareness among beneficiaries to use the benefits they received for productivity purposes. Stakeholders would ensure the eligibility criteria and pay close attention to the hotspot areas.

Rethinking the focus on forest fires in federal wildland fire management: Landscape patterns and trends of non-forest and forest burned area.

For most of the 20th century and beyond, national wildland fire policies concerning fire suppression and fuels management have primarily focused on forested lands. Using summary statistics and landscape metrics, wildfire spatial patterns and trends for non-forest and forest burned area over the past two decades were examined across the U.S, and federal agency jurisdictions. This study found that wildfires burned more area of non-forest lands than forest lands at the scale of the conterminous and western U.S. and the Department of Interior (DOI). In an agency comparison, 74% of DOI burned area occurred on non-forest lands and 78% of U.S. Forest Service burned area occurred on forested lands. Landscape metrics revealed key differences between forest and non-forest fire patterns and trends in total burned area, burned patch size, distribution, and aggregation over time across the western U.S. Opposite fire patterns emerged between non-forest and forest burns when analyzed at the scale of federal agency jurisdictions. In addition, a fire regime departure analysis comparing current large fire probability with historic fire trends identified certain vegetation types and locations experiencing more fire than historically. These patterns were especially pronounced for cold desert shrublands, such as sagebrush where increases in annual area burned, and fire frequency, size, and juxtaposition have resulted in substantial losses over a twenty-year period. The emerging non-forest fire patterns are primarily due to the rapid expansion of non-native invasive grasses that increase fuel connectivity and fire spread. These invasions promote uncharacteristic frequent fire and loss of native ecosystems at large-scales, accelerating the need to place greater focus on managing invasive species in wildland fire management. Results can be used to inform wildfire management and policy aimed at reducing uncharacteristic wildfire processes and patterns for both non-forest and forest ecosystems as well as identify differing management strategies needed to address the unique wildfire issues each federal agency faces.

Identification of the spatial patterns and controlling factors of Se in soil and rice in Guangxi through hot spot analysis.

Selenium (Se) is essential to human health, anti-cancer, possessing antioxidant, and antiviral properties. In this study, the spatial patterns of rice Se and their varying relationship with soil Se on a regional scale were studied using hot spot analysis for the agricultural soils in Guangxi. According to the hot and cold spot maps, rice Se correlates positively with soil Se in Guangxi agricultural soils. High rice Se accompanies high soil Se in the central part of Guangxi (e.g., Liuzhou, Laibin), and low rice Se is in line with low soil Se in the western part (e.g., Baise). However, the hot spot analysis maps indicate that southwestern Guangxi exhibits a special characteristic of low rice Se with high soil Se (e.g., Chongzuo). This special pattern is strongly associated with the high concentrations of Fe2O3 (ferromanganese nodules) in the carbonate rock area. The hot spot analysis proves useful in revealing the spatial patterns of rice Se in Guangxi and identifying the hidden patterns.

Habitat sensitivity in the West African coastal area: inferences and implications for regional adaptations to climate change and ocean acidification.

This study focuses on assessing coastal vulnerability and habitat sensitivity along the West African coast by delineating hotspots based on surface temperature, pH, chlorophyll-a, particulate organic carbon, and carbonate concentrations between 2018 and 2023 depending on data availability. Initial exploration of these variables revealed two distinct focal points i.e., the Togo-Nigerian coastal stretch and the stretch from Sierra Leone to Mauritania. Lower pH trends (acidification) in surface waters were observed off the West African coast, particularly in areas around the south-south Niger Delta in Nigeria and the coastal regions of Guinea and Guinea Bissau. Sea surface temperature analysis revealed highest temperatures (27-30°C) within Nigeria to Guinea coastal stretch, intermediate temperatures (24-27°C) within the Guinea Bissau and Senegal coastal stretch, and the lowest temperatures off the coast of Mauritania. Furthermore, correlation analysis between sea surface temperature and calcite concentration in the Mauritania-Senegal hotspot, as well as between overland runoff and particulate organic carbon in the Togo-Nigeria hotspot, revealed strong positive associations (r>0.60) and considerable predictive variability (R2 ≈ 0.40). From the habitat sensitivity analysis, certain regions, including Cape Verde, Côte d'Ivoire, Nigeria, Senegal, and Sierra Leone, exhibited high sensitivity due to environmental challenges and strong human dependence on coastal resources. Conversely, Gambia, Guinea, Guinea-Bissau, Liberia, and Togo displayed lower sensitivity, influenced by geographical-related factors (e.g. coastal layout, topography, etc.) and current levels of economic development (relatively lower industrialization levels). Regional pH variations in West African coastal waters have profound implications for ecosystems, fisheries, and communities. Addressing these challenges requires collaborative regional policies to safeguard shared marine resources. These findings underscore the link between ecosystem health, socioeconomics, and the need for integrated coastal management and ongoing research to support effective conservation.

Human impact on current environmental state in Chinese lakes.

Anthropogenic and natural disturbance to inland aquatic ecosystems displays a notable spatial difference, yet data to measure these differences are scarce. This study encompasses 217 lakes distributed over five lake regions of China and elucidates the environmental factors determining the spatial variability of the water quality and trophic status. A significant correlation between human modification index in surrounding terrestrial systems (HMT) and trophic status of lake ecosystems (TSI) was found, and the regression slope in each region was similar except in the Qinghai-Tibet Plateau region. It was further noted that the pattern of environmental factor network (EF network) differed among freshwater and saline lakes. The EF network was complex for freshwater lakes in less human-influenced areas, but intensive man-made influence disrupted most relationships except for those between total nitrogen, total phosphorus, chlorophyll-a, and water turbidity. As for regions including saline lakes, correlations among water salinity and organic forms of carbon and nitrogen were apparent. Our results suggest that HMT and EF network can be useful indicators of the ecological integrity of local lake ecosystems, and integrating spatial information on a large scale provides conservation planners the option for evaluating the potential risk on inland aquatic systems.

Spatial and Genomic Data to Characterize Endemic Typhoid Transmission.

BACKGROUND: Diverse environmental exposures and risk factors have been implicated in the transmission of Salmonella Typhi, but the dominant transmission pathways through the environment to susceptible humans remain unknown. Here, we use spatial, bacterial genomic, and hydrological data to refine our view of typhoid transmission in an endemic setting. METHODS: A total of 546 patients presenting to Queen Elizabeth Central Hospital in Blantyre, Malawi, with blood culture-confirmed typhoid fever between April 2015 and January 2017 were recruited to a cohort study. The households of a subset of these patients were geolocated, and 256 S. Typhi isolates were whole-genome sequenced. Pairwise single-nucleotide variant distances were incorporated into a geostatistical modeling framework using multidimensional scaling. RESULTS: Typhoid fever was not evenly distributed across Blantyre, with estimated minimum incidence ranging across the city from <15 to >100 cases per 100 000 population per year. Pairwise single-nucleotide variant distance and physical household distances were significantly correlated (P = .001). We evaluated the ability of river catchment to explain the spatial patterns of genomics observed, finding that it significantly improved the fit of the model (P = .003). We also found spatial correlation at a smaller spatial scale, of households living <192 m apart. CONCLUSIONS: These findings reinforce the emerging view that hydrological systems play a key role in the transmission of typhoid fever. By combining genomic and spatial data, we show how multifaceted data can be used to identify high incidence areas, explain the connections between them, and inform targeted environmental surveillance, all of which will be critical to shape local and regional typhoid control strategies.

Evidence of Biological Self-Organization in Spatial Patterns of a Common Tropical Alga.

AbstractTropical reef communities contain spatial patterns at multiple scales, observable from microscope and satellite alike. Many of the smaller-scale patterns are generated physiologically (e.g., skeletal structures of corals at <1-m scale), while some of the larger patterns have been attributed to scale-dependent feedbacks (e.g., spur and groove reefs at 10-100-m scales). In describing the spatial patterning of reef benthic communities at landscape levels, we uncovered unique spatial patterning among living marine algae. Populations of the calcifying green alga Halimeda were observed to form a consistent polygonal pattern at a characteristic scale of 3-4 m. The pattern showed no clear evidence of having been formed through biologically created shifts in hydrodynamical conditions or related mechanisms. In considering the specifics of Halimeda growth patterns, a model of self-organization involving separation and patterned extension is proposed, a mechanism revealed in some geological pattern formation. This observation reinforces the diversity of pathways by which striking spatial patterns can occur in ecosystems.

Century-long changes and drivers of soil nitrous oxide (N2 O) emissions across the contiguous United States.

The atmospheric concentration of nitrous oxide (N2 O) has increased by 23% since the pre-industrial era, which substantially destructed the stratospheric ozone layer and changed the global climate. However, it remains uncertain about the reasons behind the increase and the spatiotemporal patterns of soil N2 O emissions, a primary biogenic source. Here, we used an integrative land ecosystem model, Dynamic Land Ecosystem Model (DLEM), to quantify direct (i.e., emitted from local soil) and indirect (i.e., emissions related to local practices but occurring elsewhere) N2 O emissions in the contiguous United States during 1900-2019. Newly developed geospatial data of land-use history and crop-specific agricultural management practices were used to force DLEM at a spatial resolution of 5 arc-min by 5 arc-min. The model simulation indicates that the U.S. soil N2 O emissions totaled 0.97 ± 0.06 Tg N year-1 during the 2010s, with 94% and 6% from direct and indirect emissions, respectively. Hot spots of soil N2 O emission are found in the US Corn Belt and Rice Belt. We find a threefold increase in total soil N2 O emission in the United States since 1900, 74% of which is from agricultural soil emissions, increasing by 12 times from 0.04 Tg N year-1 in the 1900s to 0.51 Tg N year-1 in the 2010s. More than 90% of soil N2 O emission increase in agricultural soils is attributed to human land-use change and agricultural management practices, while increases in N deposition and climate warming are the dominant drivers for N2 O emission increase from natural soils. Across the cropped acres, corn production stands out with a large amount of fertilizer consumption and high-emission factors, responsible for nearly two-thirds of direct agricultural soil N2 O emission increase since 1900. Our study suggests a large N2 O mitigation potential in cropland and the importance of exploring crop-specific mitigation strategies and prioritizing management alternatives for targeted crop types.

Crowding, climate, and the case for social distancing among trees.

In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate-vegetation-disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets-each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence-in a post-hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk (Pm ) was higher in crowded local neighborhoods that burned in wet years (Pm  = 42%) compared with sparse neighborhoods that burned during drought (Pm  = 30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought-related mortality over short timespans (<7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought.

Examining the predictors of healthcare facility choice for outpatient care among older adults in India using Andersen's revised healthcare utilization framework model.

BACKGROUND: In India, the demand for outpatient care is substantially higher than inpatient care among older adults. Therefore, the current study examines the level, patterns, and factors associated with outpatient care use. METHODS: The present research used data from the first wave of the Longitudinal Ageing Study in India (LASI, 2017-18). A total of 34,588 older adults (45 years and above) who accessed outpatient healthcare services in one year prior to the survey were included in this study. A bivariate chi-square test was applied to present the percentage distribution of types of outpatient healthcare utilization by background characteristics and healthcare responsiveness. Multinomial logistic regression analyses were employed to explore the interplay of outpatient healthcare utilization and allied predisposing, enabling, and need factors. RESULTS: About 63.7% of total older adults used a private facility, followed by 22.8% used a public facility, and 13.5% used other facilities. Years of schooling, household wealth status, place of residence, self-rated health, and health insurance were all found to be significant determinants of public or private facility use. In contrast, respondents' sex was found to be a significant determinant of private healthcare use only. The study finds that there was inadequate healthcare reaction to public health facilities. CONCLUSION: The current study revealed that the use of private facility for outpatient care is noticeably high in India. Older adults' educational attainments, health insurance coverage, and household level economic background were found to be significant factors in healthcare choice. The current study emphasizes the need to strengthen public healthcare services for outpatient care.