Historical Growth Research Articles

Tribal Middle Class in India

The article presents a historical overview of the emergence of the tribal middle class in India, and how this history has shaped their social identity, location and participation in the Indian society, polity and economy. It initiates a discussion on the conceptual issues associated with identifying the tribal middle class, given its specific historical origins, growth and diversification through colonialism and in post-colonial India. While the article distinguishes between the old and new tribal middle class, it also attempts to delineate its overarching features, particularly that of reconciling the processes of diversification with the politics of evolving a distinct tribal identity. The article argues that the question of tribal integration is at the core of this endeavour. Therefore, it is important to consider the role and participation of the tribal middle class in shaping the nature and politics of tribal integration in India.

A comprehensive review of soil organic carbon estimates: Integrating remote sensing and machine learning technologies

Abstract Purpose Accurately assessing soil organic carbon (SOC) content is vital for ecosystem services management and addressing global climate challenges. This study undertakes a comprehensive bibliometric analysis of global estimates for SOC using remote sensing (RS) and machine learning (ML) techniques. It showcases the historical growth and thematic evolution in SOC research, aiming to amplify the understanding of SOC estimation themes and provide scientific support for climate change adaptation and mitigation. Materials and Methods Employing extensive literature database analysis, bibliometric network analysis, and clustering techniques, the study reviews 1,761 articles on SOC estimation using RS technologies and 490 articles on SOC employing both RS and ML technologies. Results and Discussion The results indicate that satellite-based RS, particularly the Landsat series, is predominant for estimation of SOC and other associated studies, with North America, China, and Europe leading in evaluations with Africa is having low evaluations adopting RS technology. Trends in the research demonstrate an evolution from basic mapping to advanced topics such as carbon (C) sequestration, complex modeling, and big data utilization. Thematic clusters from co-occurrence analysis suggest the interplay between technology development, environmental surveys, soil properties, and climate dynamics. Conclusion The study highlights the synergy between RS and ML, with advanced ML techniques proving to be critical for accurate SOC estimation. These findings are crucial for comprehensive ecosystem SOC estimation, informed environmental management and strategic decision-making.

Chiefdom, Vassalage and Empire: The Political Structures of Arabia from the First CE to the Advent of Islam

No political system could ever evolve in isolation fr om the environment in which it emerged. Similarly, no particular system can be understood as stagnant. It is actually the culmination or an improved form of a long historical growth. Keeping in view this synopsis, Islamic political institutions could be placed in the time and space in which the salient political features and social trends of the Jahiliyah Arabia and the neighboring political cultures contributed to their foundation and evolution. In addition to the compact political structures of Aksum, Rome and Persia, and then Byzantine and Sassanid on the borders, internally the pre-Islamic Arabs had a diverse mechanism for managing their affairs. The Arabian South experienced organized governance as compared to the north and central regions. This diversity can be attributed to the geo-strategic location and ecological environment of the peninsula. The fertile South was more supportive to the growth of a political mechanism than the arid, geopolitically more vulnerable north and central regions. In a nutshell, a proper study of the less discussed Jahiliyah politics could minimize assumptions about the complete lawlessness and political unawareness of the Arabs in politics and governance.

Advancing timber construction: historical growth, research frontiers, and time series forecasting

ABSTRACT Lauded for its capacity to curtail building energy consumption and enhance environmental performance compared to traditional mineral-based materials, wood has gained substantial traction in the construction sector. Timber construction, which is a focal point of growing interest in both industry and academia, warrants a reassessment of its historical trajectory and future prospects. This study examines publications on timber construction from 1990 to 2022 to analyze the growth path, shifting hotspots, and potential research directions in this field. By employing scientometric analysis, influential journals, articles, countries, and keywords are identified. Integration into a logistic growth model (LGM) showcases publication trends, while the Prophet model forecasts global growth. Research frontiers and emerging themes are revealed through keyword bursts surge evolution. This study offers a visualized knowledge framework, bridging current research with future trends and enabling practitioners and researchers to comprehensively grasp the evolution of timber construction.

Estimating Treatment Goal Weights in Adolescents With Anorexia Nervosa and Atypical Anorexia Nervosa: Comparison of the Median BMI and Historical BMI Percentile.

Determining an accurate treatment goal weight (TGW) is critical for treating eating disorders requiring weight restoration. This is challenging in adolescents since body mass index (BMI) normally increases over time. Median BMI (mBMI) is often used to determine TGW, though use of historical growth trajectories is increasingly common. Using the appropriate method to set TGW may be particularly important in treating individuals with anorexia nervosa (AN) whose prior growth was substantially above or below the median, and in atypical anorexia (AAN) where prior growth is, by definition, above the median. (1) Compare differences between TGWs based on mBMI and historical BMI percentile (hBMI) in patients with AN and AAN. (2) Determine whether either TGW method better predicted scores on the Eating Disorder Examination (EDE), heart rate, and menstrual status during treatment. Retrospective chart review of 197 adolescents with AN or AAN completing a partial hospitalization program (PHP). For AN, the within-person variation between methods varied up to 11.3 kg, though the average TGW was similar if derived from the mBMI or hBMI. In AAN, the average hBMI TGW was higher than mBMI TGW, and within-person variation was up to 19.3 kg. Associations between hBMI TGW and mBMI with heart rate, menstrual status, and EDE scores varied. Within-person differences in TGWs derived from hBMI versus mBMI can be large, with prominent differences in AAN, where hBMI TGW is significantly higher.

Feasible deployment of carbon capture and storage and the requirements of climate targets

Climate change mitigation requires the large-scale deployment of carbon capture and storage (CCS). Recent plans indicate an eight-fold increase in CCS capacity by 2030, yet the feasibility of CCS expansion is debated. Using historical growth of CCS and other policy-driven technologies, we show that if plans double between 2023 and 2025 and their failure rates decrease by half, CCS could reach 0.37 GtCO2 yr−1 by 2030—lower than most 1.5 °C pathways but higher than most 2 °C pathways. Staying on-track to 2 °C would require that in 2030–2040 CCS accelerates at least as fast as wind power did in the 2000s, and that after 2040, it grows faster than nuclear power did in the 1970s to 1980s. Only 10% of mitigation pathways meet these feasibility constraints, and virtually all of them depict <600 GtCO2 captured and stored by 2100. Relaxing the constraints by assuming no failures of CCS plans and growth as fast as flue-gas desulfurization would approximately double this amount.

The Review Article: Ethiopian Coffee Production Trend Analysis: Comparison with Major Coffee Producing Countries of The World

Ethiopia is believed to be the birth place of Arabica coffee and coffee takes a lion share in Ethiopian economy and socio-economic development since it is a prime export commodity in the country. Cognizant of its importance, Ethiopian government made key development plan and strategies to increase coffee production and productivity. As a result, many efforts were made in coffee research and extension in the last five decades; but so far Ethiopia has not attained to fully capitalize its potential in the coffee sector and there is no information on change over years of production and productivity of coffee. FAOSTAT and International Coffee Organization data were used and analyzed by descriptive statistics. Descriptive results depicted that even if coffee productivity is not significantly increased in the last decades, coffee production increased from around 180,000 metric ton in 1993 to 487,808.44 metric ton in 2021. However, still Ethiopia left behind in coffee production as compared to the major world coffee producing countries and its contribution to global coffee production is less than 5% over several years. To change and improve the historical growth trend of coffee production and productivity, it is the responsibility of all stakeholders to support coffee producers to use full package of recommended production technologies and to stump old coffee trees and work on soil and water conservation practices.

The Legacy Effect of Mountain Pine Beetle Outbreaks on the Chemical and Anatomical Defences of Surviving Lodgepole Pine Trees.

The recent mountain pine beetle outbreaks have caused widespread mortality among lodgepole pine trees in western North America, resulting in a reduced population of surviving trees. While previous studies have focused on the cascading impacts of these outbreaks on the physiology and growth of the surviving trees, there remains a need for a comprehensive study into the interactions among various physiological traits and the growth in post-outbreak stands. Specifically, the relationship between chemical (primarily terpenes) and anatomical (mainly resin ducts) defences, as well as the allocation of non-structural carbohydrates (NSCs) to support these defence modalities, is poorly understood. To address these gaps, we conducted a field survey of surviving lodgepole pine trees in post-mountain pine beetle outbreak stands in western Canada. Our retrospective analysis aimed at determining correlations between the post-outbreak concentrations of monoterpenes, diterpenes, and NSCs in the phloem and the historical resin duct characteristics and growth traits before and after the outbreak. We detected strong correlations between the post-outbreak concentrations of monoterpenes and historical resin duct characteristics, suggesting a possible link between these two defence modalities. Additionally, we found a positive relationship between the NSCs and the total concentrations of monoterpenes and diterpenes, suggesting that NSCs likely influence the production of these terpenes in lodgepole pine. Furthermore, historical tree growth patterns showed strong positive correlations with many individual monoterpenes and diterpenes. Interestingly, while surviving trees had enhanced anatomical defences after the outbreak, their growth patterns did not vary before and after the outbreak conditions. The complexity of these relationships emphasizes the dynamics of post-outbreak stand dynamics and resource allocations in lodgepole pine forests, highlighting the need for further research. These findings contribute to a broader understanding of conifer defences and their coordinated responses to forest insect outbreaks, with implications for forest management and conservation strategies.

Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration

Understanding and monitoring soil organic carbon (SOC) stocks is crucial for ecosystem carbon cycling, services, and addressing global environmental challenges. This study employs the BERTopic model and bibliometric trend analysis exploration to comprehensively analyze global SOC estimates. BERTopic, a topic modeling technique based on BERT (bidirectional encoder representatives from transformers), integrates recent advances in natural language processing. The research analyzed 1761 papers on SOC and remote sensing (RS), in addition to 490 related papers on machine learning (ML) techniques. BERTopic modeling identified nine research themes for SOC estimation using RS, emphasizing spectral prediction models, carbon cycle dynamics, and agricultural impacts on SOC. In contrast, for the literature on RS and ML it identified five thematic clusters: spatial forestry analysis, hyperspectral soil analysis, agricultural deep learning, the multitemporal imaging of farmland SOC, and RS platforms (Sentinel-2 and synthetic aperture radar, SAR). From 1991 to 2023, research on SOC estimation using RS and ML has evolved from basic mapping to topics like carbon sequestration and modeling with Sentinel-2A and big data. In summary, this study traces the historical growth and thematic evolution of SOC research, identifying synergies between RS and ML and focusing on SOC estimation with advanced ML techniques. These findings are critical to global ecosystem SOC assessments and environmental policy formulation.

Peri-urban dynamics: assessing expansion patterns and influencing factors

BackgroundPeri-urbanization, the expansion of large metropolitan centers into adjacent peri-urban regions, is a growing concern due to land scarcity and escalating housing costs. These zones, a blend of rural and urban features, blur the line between urban and rural areas, creating new landscapes. This study examines historical, present, and potential growth trends in the peri-urban area surrounding Durgapur Municipal Corporation (DMC). Analytical techniques and spatial metrics are used to track development intensity changes over time, including built-up density, Shannon’s entropy, Landscape expansion index, Average Weighted Mean Expansion Index, Annual Built-Up Expansion Rate, Built-Up Expansion Intensity Index, and Built-Up Expansion Difference Index. Landscape indices like Patch Density, Edge Density, Landscape Shape Index, Largest Patch Index, Ratio of Open Space, and Area Weighted Mean Patch Fractal are used to understand fragmentation, connectivity, and spatial relationships. The Logistic Regression Model (LRM) is used to identify influencing factors and CA-Markov modeling for future built-up areas.ResultsBetween 1991 and 2001, built-up area in the region increased significantly, primarily due to urban development near industrial zones, roadways, and mining areas. The growth was primarily concentrated in the western sector and near National Highway-2 (NH-2). Urban sprawl was a continuous trend, with the highest built-up density in the South-South-East (SSE) direction from 1991 to 2011. Additionally, a key determinant of built-up development was the distance to the city core. By 2031, the built-up area is expected to concentrate in the western and southeast regions, reaching 177.90 km2.ConclusionsThis expansion is attributed to urban development near industrial zones, roadways, mining areas, and other infrastructure. The study identifies distance to the city center as a significant influencing factor for built-up development. The results emphasize the need for inclusive urban planning methods prioritizing sustainable development principles and prudent resource management for future growth and efficient management in the DMC’s peri-urban area.

The Association between Exposure to Fine Particulate Air Pollution and the Trajectory of Internalizing and Externalizing Behaviors during Late Childhood and Early Adolescence: Evidence from the Adolescent Brain Cognitive Development (ABCD) Study.

Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter () via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence. The current study evaluated whether exposure at 9-11 y of age affects both concurrent symptoms as well as the longitudinal trajectory of internalizing and externalizing behaviors across the following 3 y. This issue was examined using multiple measures of exposure and separate measures of symptoms of internalizing disorders (e.g., depression, anxiety) and externalizing disorders (e.g., conduct disorder), respectively. In a sample of more than 10,000 youth from the Adolescent Brain Cognitive Development (ABCD) Study, we used a dataset of historical levels and growth curve modeling to evaluate associations of exposure with internalizing and externalizing symptom trajectories, as assessed by the Child Behavioral Check List. Three distinct measures of exposure were investigated: annual average concentration during 2016, number of days in 2016 above the US Environmental Protection Agency (US EPA) 24-h standards, and maximum 24-h concentration during 2016. At baseline, higher number of days with levels above US EPA standards was associated with higher parent-reported internalizing symptoms in the same year. This association remained significant up to a year following exposure and after controlling for annual average, maximum 24-h level, and informant psychopathology. There was also evidence of an association between annual average and externalizing symptom levels at baseline in females only. Results suggested exposure during childhood is associated with higher symptoms of internalizing and externalizing disorders at the time of exposure and 1 y later. In addition, effects of exposure on youth internalizing symptoms may be most impacted by the number of days of exposure above US EPA standards in comparison with annual average and maximum daily exposure. https://doi.org/10.1289/EHP13427.

Estimating and forecasting suppressed electricity demand in Ghana under climate change, the informal economy and sector inefficiencies

Suppressed demand arises from inadequate energy access, resulting in unmet basic needs. Therefore, this study investigates the impact of the informal economy, rising temperatures, and electricity transmission losses on suppressed demand in Ghana from 2000 to 2020, using a quantile autoregressive distributed lag (QARDL) approach. The study forecasts suppressed demand using Shared Socioeconomic Pathway (SSP) scenarios, offering insights for energy system planning. The results indicate that all the variables significantly affect suppressed demand in the mid-quantiles. Notably, transmission losses and growth of informal economy variables significantly impact suppressed demand within the 50th to 75th quantiles but have minimal impact before the 50th and after the 75th quantiles in the long run. Additionally, rising temperatures substantially increase suppressed demand by increasing electricity demand for cooling. All future scenarios project this growth trend will continue through 2050, albeit at varying rates. In the business-as-usual (BAU) case, suppressed demand is expected to steadily increase from 1782 MW in 2020 to 8636 MW in 2050. This trajectory aligns well with historical growth trends, which saw suppressed demand increase from 659 GWh to 1782 GWh between 2000 and 2020. SSP scenarios suggest that suppressed demand could grow substantially through 2050, driven by high losses and informal sector growth. Despite sustainable development narratives like SSP1, suppressed demand remains high without major grid and governance improvements. Comparing the results with past studies shows that our findings align with previous research but provide more nuanced insights by incorporating the effects of the informal economy and using advanced forecasting techniques. Practical policy implications include investing in green infrastructure, upgrading grid infrastructure, and formalising the informal economy to alleviate suppressed demand. These actions are critical for sustainable energy access and meeting future electricity needs effectively.

Mass incarceration as a driver of the tuberculosis epidemic in Latin America and projected impacts of policy alternatives: A mathematical modeling study.

Tuberculosis incidence is increasing in Latin America, where the incarcerated population has nearly quadrupled since 1990. The full impact of incarceration on the tuberculosis epidemic, accounting for effects beyond prisons, has never been quantified. We calibrated dynamic compartmental transmission models to historical and contemporary data from Argentina, Brazil, Colombia, El Salvador, Mexico, and Peru, which comprise approximately 80% of the region's incarcerated population and tuberculosis burden. Using historical counterfactual scenarios, we estimated the transmission population attributable fraction (tPAF) for incarceration and the excess population-level burden attributable to increasing incarceration prevalence since 1990. We additionally projected the impact of alternative incarceration policies on future population tuberculosis incidence. Population tuberculosis incidence in 2019 was 29.4% (95% UI, 23.9-36.8) higher than expected without the rise in incarceration since 1990, corresponding to 34,393 (95% UI, 28,295-42,579) excess incident cases across countries. The incarceration tPAF in 2019 was 27.2% (95% UI, 20.9-35.8), exceeding estimates for other risk factors like HIV, alcohol use disorder, and undernutrition. Compared to a scenario where incarceration rates remain stable at current levels, a gradual 50% reduction in prison admissions and duration of incarceration by 2034 would reduce population tuberculosis incidence by over 10% in all countries except Mexico. The historical rise in incarceration in Latin America has resulted in a large excess tuberculosis burden that has been under-recognized to-date. International health agencies, ministries of justice, and national tuberculosis programs should collaborate to address this health crisis with comprehensive strategies, including decarceration. National Institutes of Health.

Results of the Far East Mortgage Program for Consumers, Developers, and the Government

The volume of mortgage loans issued in eleven regions of the Far Eastern Federal District at the end of 2023 increased 2.5 times by the start of the Far Eastern Mortgage program in 2020. The most interesting result of the program is an increase in demand for primary real estate and a simultaneous decrease in the affordability of this housing. Since the start of the program, prices have increased by 116% vs. 26% while maintaining historical growth rates. By the end of 2021, the price of an apartment, including interest under the Far East Program, has become higher than that of an apartment while maintaining the historical rate of price appreciation under the family mortgage rate. The program has effectively made housing less affordable. The main conclusion is that for program participants (young families under 35), the most effective benefit of stimulating home buying is lower interest payments, not down payments. The main beneficiaries of rising prices and the scale of lending are developers. Considering the increased price of construction materials, the developers’ margin in the Far Eastern Federal District in 2023 increased to 58%. On the one hand, the government has achieved its goal of boosting the housing market in the Far East and has found an effective tool to encourage young families to buy real estate. This is evidenced by the extension of the program until 2030. On the other hand, several economic shocks led to a significant increase in the key interest rate and the accompanying growth of the program implementation costs.

Modelling volumetric growth of emerging urban areas around new transit stations

Cities in developing countries are fast transforming from area-based expansion, representing spatial growth, to volumetric expansion, representing a higher skyline. Existing urban growth prediction models predict only spatial or two-dimensional growth. This paper demonstrates a volumetric urban growth model, incorporating the vertical expansion of urban areas. Two separate models were calibrated for spatial and built-up height growth, using historical growth patterns of transit-triggered new town development in India. The models were applied to upcoming transit station areas in India to predict the volumetric urban expansion for the next twenty years.

An Investigation on the Effectiveness and Trade Direction of ASEAN Trade Agreements

This study aims to evaluate the effectiveness of the ASEAN regional trade agreement by comparing the growth rates of intra-ASEAN trade with those of the rest of the world as well as with major trading countries, China, the USA, the EU, and India. The objective of this research is threefold: To identify existing trade trends, to determine the underlying explanations for these trends, and finally, to compare intra-ASEAN trade trends with the inter-ASEAN countries’ trade trends. This paper takes a descriptive approach and dynamic panel GMM methods spanning the years 1990 to 2019. Between 2005 and 2019, growth rates among members of intra-ASEAN, Indonesia-Malaysia, Indonesia-Thailand, Singapore-Thailand, Malaysia-Philippines, and Philippines-Thailand, all decreased. Additionally, although the market share of imports and exports within ASEAN has decreased over time, the market share of imports and exports of inter-ASEAN has increased, especially with China and India. The results of descriptive analysis of inter-ASEAN trade openness are supported by first-differenced GMM and system GMM. This is the first study to examine historical intra-ASEAN trade trends and growth and compare them to inter-ASEAN trade trends and growth to determine whether AFTA has a greater impact on intra-ASEAN trade growth than on inter-ASEAN trade growth using updated aggregated data. This study sheds light on the fact that over the periods intra-ASEAN trade could not outperform inter-ASEAN trade by a significant margin due to trade diversity challenges and incomplete implementation of WTO regulations.

Opportunities and Challenges of China’s Economic and Political Development under the Third Term of Xi Leadership: A Viewpoint of Indonesia

This article examines China’s recent economic and political progress under the leadership of President Xi Jinping, focusing on the opportunities and problems faced. It also explores the concept of the "China dream" and its impact from the perspective of Indonesia. This research is an analysis of the perceptions of Indonesia’s elite and the general public on Chinese political influence and economic cooperation. Multiple discussions will be examined. Firstly, it outlines the characteristics of China’s global development plan, which encompasses the Belt and Road Initiative (BRI) and Global Development Initiatives. What is the impact of Chinese development policies on the ASEAN Outlook of Indo-Pacific (AOIP) suggested by Indonesia? Furthermore, Indonesia, as the longstanding dominant force in Southeast Asia, plays a pivotal role in upholding regional stability and the important position of ASEAN in relation to China. This research examines the historical and contemporary strategic cooperation and growth between Indonesia and China, as well as the chances and difficulties that China’s third term under Xi Jinping presents for Indonesia’s development. Additionally, this analysis will examine the fundamental strategic decision that Indonesia must make in response to China’s influence through the Belt and Road Initiative. Indonesia will strategically hedge its position toward China’s rising power while leveraging China’s ongoing soft power to preserve its prominent role in ASEAN.

Explosive increase and decrease in articles, citations, impact factor, and immediacy index during the COVID-19 pandemic: a bibliometric study

Purpose: This study investigated how Journal Citation Reports (JCR) metrics changed during the COVID-19 pandemic (2020–2022), with the aim of sharing this information with stakeholders in the publishing community.Methods: In total, 7,689 journals listed in the JCR-Science Citation Index Expanded (SCIE) from 2016 to 2022 were selected. Data were analyzed using pivot tables in Microsoft Excel. We calculated the compound annual growth rate to investigate changes in JCR-SCIE articles, citations, the journal impact factor, and the immediacy index during the COVID-19 period.Results: A marked increase was noted in the number of articles and citations during the COVID-19 pandemic from 2020 to 2022. This surge was primarily driven by a significant rise in COVID-19–related articles. Consequently, four JCR metrics exhibited a sharp increase in 2020, followed by an unusually steep decline in 2022. Articles, citations, and the journal impact factor reached their highest recorded levels in 2021, while the immediacy index saw its most significant growth and intense citation activity in 2020 before experiencing notable decreases in 2021 and 2022. Our findings indicate that there was an unprecedented and dramatic shift in these four JCR metrics during the COVID-19 period, with current trends suggesting a reversion to historical compound annual growth rate levels.Conclusion: The journal publishing and scientific communities should consider these explosive changes when applying JCR metrics to evaluate articles and endeavor to mitigate the adverse effects of the unusual concentration of articles and citations during the COVID-19 period. These results constitute valuable information to be shared among researchers and stakeholders within the journal publishing community.

Financial Development and Economic Growth: A Bibliometric Analysis

This research conducts a bibliometric analysis of 662 documents from the Scopus database (1986-2022), using tools like Harzing’s Publish or Perish, Tableau Public, Biblioshiny - RStudio, Microsoft Excel, and VOSviewer for data visualization. It highlights historical trends, growth, and future prospects in finance, identifying key authors, publications, countries, and institutions. China, Turkey, and Malaysia lead in publications, with the University of South Africa being the most productive institution. The study offers insights into future research in green finance, FinTech, and sustainability, emphasizing the evolution of concepts like “financial inclusion” and “fintech.”

Urban colonization of invasive species on islands: Mus musculus and Rattus rattus genetics of establishment on Cozumel Island

Humans and wildlife experience complex interactions in urban ecosystems, favoring the presence of commensal species, among which invasive species are particularly successful. Rodents are the main vertebrate group introduced to oceanic islands, where the invasion process and dispersal patterns strongly influence their evolutionary and genetic patterns. We evaluated the house mouse Mus musculus and the black rat Rattus rattus on Cozumel Island, Mexico. We assessed genetic diversity and structure, connectivity, gene flow, relatedness and bottleneck signals based on microsatellite loci. Our genetic findings suggest that introduction of individuals of different geographic sources to the island promotes high allelic diversity and the effective establishment of migrants. We identified a clear genetic structure and low connectivity for the two species, tightly linked with anthropogenic and urban features. Notably, we found that the genetic structure of the house mouse sampled within the city of San Miguel Cozumel is associated with the historical human population growth pulses accompanying the urbanization of the city. At the fine-scale genetic level, the main urban drivers of connectivity of the house mouse were both the impervious land surfaces, i.e. the urban landscape, and the informal commerce across the city (a proxy of resources availability). Chances of a secondary invasion to natural environments have been relatively low, which is crucial for the endemic taxa of the island. Nonetheless, improving urban planning to regulate future expansions of San Miguel Cozumel is of the outmost importance to prevent these invasive species to disperse further.