Urban Areas Research Articles

The linkage of government assistance programs towards digital and financial well-being of small household income families in Urban Area: Lesson from COVID-19 pandemic

The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being and digital well-being of B40 or small household income families in urban areas. In responding to the crisis, the government had launched multiple assistance programs to assist the group. Hence, the study intends to examine the relationship of government assistance towards digital and financial well-being of the group. Utilizing survey, the study involved 417 respondents living at the Public Housing Project (PPR) residential areas in Kuala Lumpur—the capital of Malaysia. The data was analyzed using Smart PLS and the key findings were (1) government assistance programs significantly affect the digital well-being and financial well-being of B40 urban families. However, there is no significant relationship between financial well-being and digital well-being. Besides, the Importance-Performance Analysis (IPA) indicated that the importance of government assistance programs towards digital well-being performance is higher than financial well-being. The assistance programs offered by the government plays essential role to ease the digital and financial constraints of B40 urban families during a difficult time. Reforms to the government assistance programs, the empowerment of digital aid packages, and the enhancement of social security net initiatives for B40 urban families are necessary to enhance the group’s preparedness and resilience in the face of new shocks in the future.

Microplastics in Urban Bird Feces: A Methodological Approach and Case Study in Mexico City

Microplastics (MP) are ubiquitous contaminants in diverse environmental matrices, including biota. Urban birds, such as pigeons (Columba livia), are particularly vulnerable to MP exposure due to their scavenging habits and proximity to human activities. This study developed and applied a methodology to assess MP presence in pigeon feces, starting with a review of existing methods for extracting MPs from organic matrices. Of all the methodologies investigated, a method was established to be tested, varying the reagent, using pigeon feces collected from the Universidad Autónoma Metropolitana, Azcapotzalco Unit (UAM-A) and 15 virgin microplastics of five different types. Of both reagents, it was found that the method with 50% H2O2 presented better results (degradation of almost all organic matter and recovery efficiency of 93.33%). The selected method was optimized before being applied to feces collected from three sites in Mexico City (n = 10 samples per site). MPs were extracted using a digestion process with 50% hydrogen peroxide, flotation test with CaCl2, staining with red Nile dye and vacuum filtration and analyzed by microscopy and FTIR. Concentrations ranged from 16.4 to 27.8 MP/g dry feces, with fragments (80%) and fibers (20%) being the predominant shapes. The most common colors were black (32%) and white (22%), the polymers identified included polystyrene and polyethylene and the most common size was < 1 mm (54%). These findings suggest that pigeons ingest MP during feeding, likely due to confusion with organic matter, highlighting the risks of urban plastic pollution to avian health. The ingestion of MPs could lead to malnutrition, organ damage, and ecosystem imbalances, underscoring the need for improved waste management in urban areas. This study provides evidence of the pervasive impact of plastic pollution in non-marine environments, demonstrating the potential of urban birds as bio-indicators of local contamination.

Disparities in cocaine use disorder among Alabama Medicaid recipients

ABSTRACT Objective To examine racial and sex disparities in Cocaine Use Disorder (CoUD) use among rural and urban Medicaid recipients in the state of Alabama between 2016 and 2020. Methods Alabama Medicaid administrative claims were extracted for the period between January 1 2016, and December 31 2020. Our dataset included 100% of claims for the study period. We examined trends in CoUD rates, and disparities in county-level CoUD rates by sex, race, and rurality. Results Results showed a greater decrease in CoUD rate in urban areas than rural. Among racial groups, there were no changes among Black females, Black males, nor White females, but only among White males. Conclusion Findings provide understanding of racial and sex differences in CoUD among rural and urban Medicaid recipients.

Towards Sustainable Development in South Asian Countries: The Role of Economic Complexity and Globalization on Environmental Pollution

In the context of developing economies, this study aims to investigate the insights found in the literature on economic complexity, globalization, and environmental pollution institutions. The available theoretical and empirical literature on the subject is reviewed and summarized in this work. It begins with a summary of Pakistan's environmental contamination, globalization, and economic complexity. By using the theoretical and empirical insights from the published literature, it identifies the literature in the second place. This article also clarified theoretical approaches that explain how and why they function. Third, this paper suggests three useful areas for additional study. By critically examining and combining current environmental theory and research institutions, this work advances the fields of economic complexity, institutions, globalization, and environmental degradation. The rapid urban expansion, there is frequently an increase in the quantity of energy utilized, the amount of trash created, and the amount of pollution produced. In order to lessen the amount of environmental damage that is caused by urban areas, it is essential to implement waste management systems that are both effective and environmentally friendly. This is accomplished via the use of urban planning strategies.

Perceived stress and death-related distress in older adults: Exploring the role of social support and emotional loneliness.

The purpose of this study was to examine whether emotional loneliness and social support mediated the association between perceived stress and death distress in older adults. The sample consisted of 524 older adults, aged between 65 and 88, living in an urban area in Türkiye (M = 70.05, SD = 5.01). Mediation analyses revealed that perceived stress is positively associated with death distress and emotional loneliness, and negatively associated with social support. Both social support and emotional loneliness mediate the relationship between perceived stress and death-related distress. Additionally, social support mediates the association between emotional loneliness and perceived stress with death distress in older adults. These findings underscore the importance of social resources in promoting mental health and well-being, and in mitigating the adverse effects of stress and loneliness on death-related feelings and thoughts in older adults. By providing emotional and practical assistance, social support can significantly enhance the mental health and well-being of older adults.

Urban resignification areas in the production of space in Cuenca: El Barranco case

Urban resignification areas in the production of space in Cuenca: El Barranco case

Multi-scenario modelling framework for afforestation strategies to mitigate runoff and flooding across storm return periods in tropical large river basins: the Upper Citarum case

ABSTRACT Flooding is a frequent disaster in Indonesia, especially in the Upper Citarum River Basin, causing substantial damage. This study assesses the impact of afforestation on runoff, peak discharge and flood risks under different storm conditions using hydrological (HEC-HMS) and hydraulic (HEC-RAS) models. Six afforestation scenarios were analyzed: No Forest (NF), Medium Afforestation (MF), Bandung's 2029 spatial plan (F-2029), Riverbank Afforestation (RF), spatial plan for 2029 (SP-2029) and No Built-up (NB), with Land Cover 2021 (LC-2021) as the baseline. Rainfall return periods (2, 5, 10, 20, 50 and 100 years) were generated from 32 years of rainfall data. The results show land cover changes significantly influence runoff, with urbanization increasing flood risks and afforestation improving water retention. Riverbank afforestation (RF) and reduced built-up areas (NB) were the most effective in mitigating flood risks, while reduced forest cover (NF) and urban expansion (SP-2029) exacerbated flooding. Validation with historical flood data highlighted flood-prone areas like Margahayu, Bojongsoang, Dayeuhkolot and Baleendah. Frequent but less severe floods were noted in 2- and 5-year return period scenarios. These findings emphasize the critical role of afforestation and land cover management in reducing flood risks and enhancing resilience in the Upper Citarum Basin.

Studying the impact of rainfall and LULC changes in the reservoir water level of the Hatia dam, Ranchi, India

ABSTRACT This study aimed to analyse the pattern of rainfall and land use land cover (LULC) changes and their impact on the water level of the Hatia dam, a crucial source of the water supply for Ranchi city in Jharkhand, India. High-resolution daily-gridded rainfall and temperature data from 1991 to 2023 were collected from IMD Pune and analyzed using Mann–Kendall and Sen's slope estimator. The results showed a significant decline in annual, monsoon, post-monsoon, and winter rainfall, while pre-monsoon rainfall increased during the study period. The Google Earth Engine was used to observe LULC changes at 5-year intervals. The analysis revealed significant changes in the waterbody, built-up, forest cover, barren land, and agriculture before and after the monsoon. The analysis show that during the pre-monsoon season, the waterbody decreased from 8.68 to 4.94%, while the built-up area increased from 2.71 to 11.08%. Similar trends were observed during the post-monsoon season, with the waterbody decreasing from 10.06 to 7.3% and the built-up area increasing from 2.74 to 11.27%. It is observed from the rainfall analysis that the annual rainfall is decreasing from 1,561 to 703 mm and the reservoir surface area has also decreased from 126.31 to 37.44 ha. The findings highlight the need for sustainable water management strategies.

Spatial variability of groundwater quality in four mega-cities of India and impact of land use types on groundwater quality

ABSTRACT The deterioration of groundwater quality is a global concern, particularly in densely populated urban areas. This study examines spatial variability in groundwater quality across four major Indian cities – Mumbai, Delhi, Chennai and Kolkata – using water quality index (WQI) and remote sensing techniques. Groundwater data from the 2018 report of the Central Groundwater Board was analyzed using 12 parameters, while Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI) indices were calculated from Landsat imageries to assess land use impacts. Findings indicate significant variability: Delhi shows 44.62% unsuitable samples, Chennai 12.12%, Kolkata 0% and Mumbai 2%. Urbanization (NDBI) negatively affects WQI, while green spaces (NDVI) improve it. NDWI impacts vary, being negative in Mumbai but positive in Kolkata, Chennai and Delhi. Welch’s analysis of variance (ANOVA) and post hoc analysis confirms significant WQI differences across cities. These results highlight the urgent need for sustainable urban infrastructure, increased green spaces and pollutant-free waterbodies to improve groundwater quality in urban India.

Urban Planning for the Contemporary Age: Navigating Complexities and Shaping Urban Futures

The term “urban planning for the contemporary age” describes the process of creating and overseeing urban areas to meet the many complex issues of the current times, such as social justice, climate change, growing urbanisation, and technological advancement. It places a strong emphasis on flexible, inclusive, and progressive approaches that strike a balance between sustainable development and the changing demands of various urban populations. Urban planning, particularly in the contemporary age, is a multidisciplinary discipline that tackles the complexity of contemporary cities that is influenced by social injustices, fast urbanisation, climate change, and technology breakthroughs. This entry paper examines how planners deal with these issues by using flexible, inclusive, and sustainable approaches that strike a balance between community well-being, environmental conservation, and growth. It looks at important topics including incorporating smart technology, building climate impact resilience, and creating inclusive, accessible, and egalitarian urban environments. The conflict between tradition and modernisation is also highlighted in the chapter, underscoring the necessity of creative solutions that protect cultural legacy while meeting contemporary needs. By examining global trends, this study offers insights into how urban planning is changing to satisfy the demands of a dynamic and connected society. The study used a literature review to identify the main areas that are influencing innovation in urban planning. It then delves into discussions on contemporary issues and complexities in shaping urban futures. The main research methods were a literature review and empirical analysis. In the end, it makes the case for rethinking urban futures with an emphasis on resilience, sustainability, and the welfare and well-being of urban residents.

Perceived urban environment elements associated with momentary and long-term well-being: An experience sampling method approach

Abstract Well-being (WB) extends beyond physical health, as defined by the World Health Organization and encompasses two aspects: (1) long-term WB (LWB), such as overall life satisfaction; and (2) momentary WB (MWB), such as immediate mood. While research has demonstrated a positive association between one’s environment and LWB, limited studies have explored the association between environmental characteristics and MWB. We applied the experience sampling method (ESM) to collect data on location, perceived environmental characteristics, MWB, and LWB of adult participants living in Kashiwa-no-ha area, Kashiwa City, Japan. Structural equation modeling was used to calculate the correlation coefficients between different environments and both MWB and LWB. LWB was positively associated with MWB (standardized coefficient=0.24) and urban elements—cafés/restaurants/bars (0.11), cultural/sports/education facilities (0.04), and public spaces (0.11). Meanwhile, relaxing/clean (0.56) and natural environments (0.14) were associated with higher MWB. Conversely, vibrant environments (−0.14) and being on the move (−0.11) were linked to lower MWB. LWB was positively associated with being at cultural/sports/educational facilities (0.06), and vibrant (0.15) and communicative (0.13) urban settings. MWB was associated with various built environments, emphasizing the need for places like parks and cafés that promote a positive mood, and well-designed transportation and roads. These elements are important for developing urban areas that meet the physical requirements of residents while supporting their emotional and psychological well-being.

Beyond averages: dissecting urban-rural disparities in skilled antenatal care utilization in Bangladesh - a conway-maxwell-poisson regression analysis.

Taking a sufficient number of skilled antenatal care (SANC) visits is incontrovertibly connected to safe motherhood. This study aims to shed light on the prevalence and potential factors associated with disparities in the SANC taking behavior of pregnant mothers in rural and urban Bangladesh. For this purpose, a nationally representative secondary dataset from the Bangladesh Demographic and Health Survey (BDHS, 2017-18) has been considered. The information regarding the last birth of mothers who delivered within three years preceding the survey has been analyzed. We have applied the Conway-Maxwell-Poisson regression model (CMPRM) to deal with the overdispersion in skilled ANC count data, as this model shows the least AIC compared to the classical negative-binomial regression model (NBRM) and the generalized Poisson regression model (GPRM). Significant disparity (p-value < 0.001) has been observed in the mean number of SANC taken by rural (3.17) and urban (4.52) women. The analysis revealed that covariates have significantly different effects on SANC visits in rural areas compared to urban areas. For instance, women aged 35 and above in rural settings exhibited a 37% higher incidence rate of SANC visits (IRR = 1.37) compared to those under 20. Educational attainment had a pronounced impact, with rural women showing a 39% (IRR = 1.39) increase in SANC visits for primary education, 57% (IRR = 1.57) for secondary education, and 64% (IRR = 1.64) for higher education, compared to uneducated women. In contrast, in urban areas, higher education resulted in only a 35% (IRR = 1.35) increase. Our findings from this study indicate that the concerned authority should come forward, and policymakers should emphasize various factors that are mainly responsible for the noteworthy different SANC status of pregnant women living in rural and urban areas in Bangladesh. Doing so, it can be hoped that the required number of ANC visits (eight or more) in both types of residences in Bangladesh, recommended by the World Health Organization (WHO), will be satisfied to ensure safer motherhood.

Fifth-Generation (5G) Communication in Urban Environments: A Comprehensive Unmanned Aerial Vehicle Channel Model for Low-Altitude Operations in Indian Cities

Unmanned aerial vehicles (UAVs) significantly shape the evolution of 5G and 6G technologies in India, particularly in reconfiguring communication networks. Through their deployment as base stations or relays, these aerial vehicles substantially enhance communication performance and extend network coverage in areas characterized by high demand and challenging topographies. Accurate modelling of the UAV-to-ground channel is imperative for gaining valuable insights into UAV-assisted communication systems, particularly within India’s rapidly expanding metropolitan cities and their diverse topographical complexities. This study proposes an approach to model low-altitude channels in urban areas, offering specific scenarios and tailored solutions to facilitate radio frequency (RF) planning for Indian metropolitan cities. The proposed model leverages the International Telecommunication Union recommendation (ITU-R) for city mapping and utilizes frequency ranges from 1.8 to 6 GHz and altitudes up to 500 m to comprehensively model both line-of-sight (LoS) and non-line-of-sight (NLoS) communications. It employs the uniform theory of diffraction to calculate the additional path loss for non-line-of-sight (NLoS) communication for both vertical and horizontal polarizations. The normal distribution for additional shadowing loss is discerned from simulation results. This study outlined the approach to derive a comprehensive statistical channel model based on the elevation angle and evaluate model parameters at various frequencies and altitudes for both vertical and horizontal polarization. The model was subsequently compared with existing models for validation, showing close alignment. The ease of implementation and practical application of this proposed model render it an invaluable tool for planning and simulating mobile networks in urban areas, thus facilitating the seamless integration of advanced communication technologies in India.

Human mobility is well described by closed-form gravity-like models learned automatically from data.

Modeling human mobility is critical to address questions in urban planning, sustainability, public health, and economic development. However, our understanding and ability to model flows between urban areas are still incomplete. At one end of the modeling spectrum we have gravity models, which are easy to interpret but provide modestly accurate predictions of flows. At the other end, we have machine learning models, with tens of features and thousands of parameters, which predict mobility more accurately than gravity models but do not provide clear insights on human behavior. Here, we show that simple machine-learned, closed-form models of mobility can predict mobility flows as accurately as complex machine learning models, and extrapolate better. Moreover, these models are simple and gravity-like, and can be interpreted similarly to standard gravity models. These models work for different datasets and at different scales, suggesting that they may capture the fundamental universal features of human mobility.

Global consistency of urban scaling evidenced by remote sensing

Abstract The urban scaling theory (UST) strives for a universal taxonomy that depicts relationships among urban indicators (e.g., energy consumption, economic output) with city size. However, the lack of international agreement on city definitions and statistics complicates cross-country comparisons of urban scaling performance. Remote sensing provides a uniform standard for measuring cities around the world. To scrutinize the consistency of UST, we quantified changes in remotely sensed urban built-up areas (UBA) and nighttime lights (NTL) distributions from 11,581 cities in 61 countries spanning 2000-2020, representing urban physical elements and socioeconomic activities respectively. We find that UBA is well-described by UST in all analyzed countries, while NTL aligns with 98% of them. UST quantified by remote sensing shows greater robustness than country-dependent aggregate statistics. We also observed disparities of scaling exponents (β) among countries, with UBA all being sub-linear (β &amp;lt; 1), and NTL ranging from 0.46 to 1.22 with a median of 0.94. Both UST and rank-size distributions of urban area and population show stronger scaling relationships for countries with larger networks of built environments, (Brazil, China, Germany, Japan, Russia, USA) suggesting that both size and evolution of urban systems impact the underlying scaling processes. Comparison of scaling properties of remotely sensed UBA and NTL captures complementary physical characteristics of built environments while minimizing the Modifiable Area Unit Problem introduced using spatially aggregated metrics within administrative units. Our findings highlight the consistency of urban growth patterns while confirming the systematic socioeconomic disparities among urban systems of varying size and growth trajectory.

Effects of a Carboxyl Group on the Products, Mechanism, and Kinetics of the OH Radical-Initiated Oxidation of 3-Butenoic Acid Under Low NOx Conditions.

Concentrations of nitrogen oxides (NOx) in the U.S. have decreased so much in the last few decades that the oxidation of volatile organic compounds (VOCs), which plays a critical role in the formation of ozone and fine particles, now often occurs in urban areas under conditions that are historically associated with remote rural locations. As a result, alkylperoxy radicals (RO2•), which are key intermediates in VOC oxidation, can react with NO, HO2, and RO2• radicals, and isomerize. In this study, we primarily investigated the products, mechanism, and kinetics of the OH radical-initiated oxidation of 3-butenoic acid under conditions where the dominant products of a similar reaction of 1-pentene were hydroxy-hydroperoxides formed through RO2• + HO2 reactions. 3-Butenoic acid has some structural properties that made it ideally suited for this study, which was conducted in an environmental chamber using iodide chemical ionization mass spectrometry and authentic standards. The major reaction products were oxo-propanoic acid, hydroxyoxo-butanoic acid, dihydroxy-butanoic acid, and dihydroxy-dicarboxybutyl-peroxide (a ROOR dimer) formed with measured molar yields of 0.74, 0.09, 0.08, and 0.03 for a total molar yield of 0.94 that effectively achieved a mole balance. Unlike in the 1-pentene reaction, reaction of the dominant RO2• radical with HO2 led almost solely to formation of oxo-propanoic acid + formaldehyde + OH + HO2, apparently due to hydrogen bonding involving the carboxyl group in the ROO-OOH intermediate complex. Similar hydrogen bonding in the ROO-OOR complex was likely responsible for the formation of the peroxide dimer and the exceptional speed of RO2• + RO2• reactions, which were competitive with RO2• + HO2 reactions and were calculated from measurements and kinetics modeling to occur with a rate constant ≥3 × 10-11 cm3 molecule-1 s-1 that may approach the collision limit value of about 5 × 10-10 cm3 molecule-1 s-1. The results of the study demonstrate that functional groups can have dramatic effects on the atmospheric chemistry of VOCs.

Integrating Conservation and Community Engagement in Free-Roaming Cat Management: A Case Study from a Natura 2000 Protected Area

La Graciosa, a Natura 2000 site in the Canary Islands, faces substantial conservation challenges, including a large free-roaming cat population that threatens the island’s native biodiversity. In July 2024, a Trap–Neuter–Return (TNR) campaign achieved an 81.4% sterilization rate within urban areas, highlighting TNR’s short-term effectiveness in reducing reproductive potential and, consequently, mitigating predation pressures primarily through the prevention of new litters and reduced reproductive activity in cats. The campaign’s success relied heavily on the active involvement of the local community, who assisted with identifying, trapping, and monitoring free-roaming cats, thereby facilitating a high sterilization rate. However, administrative restrictions hindered access to peri-urban zones, leaving essential population clusters unsterilized and limiting the campaign’s overall scope. Additionally, strong opposition from conservation groups, amplified by extensive media coverage, halted the project prematurely, reducing the effective sterilization rate to 69.3% within three months. Population Viability Analysis (PVA) suggests that achieving high sterilization rates could lead to population reduction over time; however, the inability to access all population segments and to reach the ideal 93–95% sterilization threshold limits TNR’s potential as a long-term standalone solution. Our findings underscore the need for adaptive, context-specific management frameworks in ecologically sensitive areas that integrate TNR with complementary measures, consider regulatory barriers, and value community involvement. This case study provides crucial insights for policymakers and conservationists seeking to balance biodiversity conservation with humane management practices in protected areas.

Urban Power Line Extraction from Mobile LiDAR Point Clouds based on Local Line-plane seperation Model and Global Refinement

Abstract Power line extraction from three-dimensional (3D) point clouds is a key step for power inspection. However, the power line is intertwined and covered with trees and other objects in the urban area, which brings a tremendous challenge to its extraction. This article proposed a local-to-global method to extract power lines from mobile LiDAR point clouds based on multiple characteristics. Firstly, initial point clouds clusters are selected through data preprocessing. Secondly, given the linearity and independence of the power line, we innovatively design a local line-plane separation modeling to divide the point clouds into high-confidence power line points, non-power line points, and unconfirmed points. Then, a novel global energy function is designed for the graph cut model according to the long linear and short radius characteristics of the power line. The proposed method has been tested on Toronto 3D and WuHan Avenue datasets. The average Precision, Recall, and F1score can reach up to 0.92, 0.73, and 0.79 respectively, which is superior to state-of-the-art approaches. The result demonstrates the efficacy and robustness of our proposed approach in extracting power lines within urban environments using a mobile laser scanning system.

Transformer-based travel time estimation method for plateau and mountainous environments.

Travel time estimation (TTE) is a critical function in intelligent driving systems. Current research and applications related to TTE primarily focus on urban environments. The objective of this study is to develop TTE methods that are applicable to wilderness areas characterized by plateau and mountainous topography. We selected Transformer, which has greater robustness in capturing long-distance dependencies than LSTM, to develop a Transformer-based model. The model simultaneously integrates positional encoding and multi-head self-attention mechanisms with the objective of enhancing the accuracy of travel time predictions based on a substantial number of trajectory points in wilderness settings. A meta-learning strategy was employed to improve the model's generalization ability, thereby ensuring its applicability for accurate travel time estimation across a range of challenging environments. Two datasets were constructed based on measurements from two selected areas in eligible plateau and mountainous regions of western China. For each dataset, two categories of features were defined: terrain-weather features and spatio-temporal features. These categories were established in accordance with the influence of seven specific features on traffic conditions in both urban and wilderness areas. Experiments were conducted on both datasets utilizing terrain-weather features. When evaluated alongside the five models that are most commonly utilized in urban settings, the mean absolute percentage error (MAPE) of our model exhibited a 14.89% improvement in plateau environments and a 12.20% improvement in mountainous environments in comparison with the most effective model, namely MetaTTE-GRU. These findings substantiate the assertion that the proposed model is an effective means of estimating travel times in complex environments, and that it exhibits superior accuracy compared to existing LSTM-based estimation models.

A systematic scoping review reveals that geographic and taxonomic patterns influence the scientific and societal interest in urban soil microbial diversity.

Urban green areas provide multiple ecosystem services in cities, mitigating environmental risks and providing a healthier environment for humans. Even if urban ecology has become popular in the last decade, the soil environment with its microbiota, which sustains many other biodiversity layers, remains overlooked. Here, a comprehensive database of scientific papers published in the last 30 years investigating different aspects of soil microbial diversity was built and systematically reviewed. The aim was to identify the taxa, experimental methods and geographical areas that have been investigated, and to highlight gaps in knowledge and research prospects. Our results show that current knowledge on urban soil microbiota remains incomplete, mainly due to the lack of publications on functional aspects, and is biased, in terms of investigated taxa, with most studies focused on Prokaryotes, and geographic representativeness, with the interest focused on a few large cities in the Northern hemisphere. By coupling bibliometrics with statistical modelling we found that soil microbial traits such as biomass and respiration and omics techniques attract the interest of the scientific community while multi-taxa and time-course studies appeal more to the general public.