Population Density Gradients Research Articles

Constitutive innate immune defenses in relation to urbanization and population density in an urban bird, the feral pigeon Columba livia domestica.

Urbanization processes modulate the immunological challenges faced by animals. Urban habitat transformations reshape pathogen diversity and abundance, while high population density-common in urban exploiter species-promotes disease transmission. Responses to urbanization may include adaptive adjustments of constitutive innate immune defenses (e.g. complement system and natural antibodies [NAbs]), which serve as first-line protection against infections. Here, we investigated associations of habitat urbanization and host population density with complement and NAbs in an urban bird, the feral pigeon Columba livia domestica. To do so, we employed the hemolysis-hemagglutination assay to analyze nearly 200 plasma samples collected across urbanization and pigeon population density gradients in five major cities in Poland. We found a negative association between urbanization score and hemagglutination (i.e. NAbs activity), but not hemolysis (i.e. complement activity), indicating either immunosuppression or adaptive downregulation of this immune defense in highly transformed urban landscape. Population density was not significantly related to either immune parameter, providing no evidence for density-dependent modulation of immune defenses. At the same time, there was a negative association of hemolysis with condition (scaled mass index), suggesting resource allocation trade-offs or contrasting effects of the urban environment on immune defenses and body condition. The results demonstrate that habitat structure can be an important factor shaping the immune defenses of the feral pigeon, although these associations were not mediated by variation in population density. Our study highlights the complexity of the links between immune defenses in wildlife and urbanization and reinforces the need for comprehensive ecoimmunological studies on urban animals.

Complex cocoa agroforestry systems shaped within specific socioeconomic and historical contexts in Africa: Lessons from Cameroonian farmers

CONTEXTIn the humid tropics, the socioecological advantages of family-based, multistory agroforestry systems are well recognized. Yet public policies tend to focus on conservation and land-sparing strategies alongside the promotion of modern intensive agriculture, neglecting these biodiverse agroecosystems, which are in decline. This is a particularly central issue in cocoa cultivation. In Africa's two largest cocoa-producing countries (Côte d'Ivoire and Ghana), cocoa plantations with few associated trees contribute to deforestation and biodiversity loss. In contrast, in regions like Cameroon, biodiversity-rich cocoa agroforests prevail. Considering global changes and rising cocoa demand, it is crucial to preserve and develop these agroforestry systems that reconcile cocoa production with ecosystem services. OBJECTIVEThis study, conducted in Cameroon between 2013 and 2017, aimed to pinpoint the socioeconomic factors influencing the characteristics, maintenance, and degradation of cocoa agroforests, with the ultimate goal of identifying intervention strategies to promote their preservation and development. METHODSThe study collected data from (i) on-field measurements in 95 cocoa agroforestry plots, (ii) interviews with the 95 farmers managing the plots, and (iii) historical interviews with 50 key informants. We focused on five sites across a gradient of population density, encompassing various socioecological environments and types of cocoa agroforests. Through thematic and statistical analyses, we evaluated differences between the five sites. RESULTS AND CONCLUSIONSOur results indicated contrasting management practices, dendrometric structure, species composition, and cocoa yields between sites. These contrasts largely reflected socioeconomic factors and site-specific dynamics. Cocoa agroforests were less rich in biodiversity in sites where farmers with capital using hired labor had acquired land than in sites where family farmers predominated. A trade-off was found between the richness of companion trees and cocoa yields. Plots managed by smallholder family farmers near urban areas tended to better reconcile cocoa production and biodiversity conservation. These farmers had gradually transformed their traditional agroforests to adapt to increasing demographic pressure by integrating diverse fruit tree species, using pesticides sparingly, and introducing selected cocoa varieties mixed with older varieties. SIGNIFICANCEThe small-scale family-managed cocoa agroforests, which incorporate fruit species as described in this study, could serve as a model for a more sustainable cocoa production strategy. However, developing such a strategy would require greater investment and support from policymakers. This includes supporting the marketing of products from companion trees, stabilizing cocoa prices at a high level, and implementing land policies that protect small and medium-sized family farmers.

The adaptive value of density-dependent habitat specialization and social network centrality

Density dependence is a fundamental ecological process. In particular, animal habitat selection and social behavior often affect fitness in a density-dependent manner. The Ideal Free Distribution (IFD) and niche variation hypothesis (NVH) present distinct predictions associated with Optimal Foraging Theory about how the effect of habitat selection on fitness varies with population density. Using caribou (Rangifer tarandus) in Canada as a model system, we test competing hypotheses about how habitat specialization, social behavior, and annual reproductive success (co)vary across a population density gradient. Within a behavioral reaction norm framework, we estimate repeatability, behavioral plasticity, and covariance among social behavior and habitat selection to investigate the adaptive value of sociality and habitat selection. In support of NVH, but not the IFD, we find that at high density habitat specialists had higher annual reproductive success than generalists, but were also less social than generalists, suggesting the possibility that specialists were less social to avoid competition. Our study supports niche variation as a mechanism for density-dependent habitat specialization.

Population density and ranging behaviour of a generalist carnivore varies with human population.

Canid species are highly adaptable, including to urban and peri-urban areas, where they can come into close contact with people. Understanding the mechanisms of wild canid population persistence in these areas is key to managing any negative impacts. The resource dispersion hypothesis predicts that animal density increases and home range size decreases as resource concentration increases, and may help to explain how canids are distributed in environments with an urban-natural gradient. In Australia, dingoes have adapted to human presence, sometimes living in close proximity to towns. Using a targeted camera trap survey and spatial capture-recapture models, we estimated spatial variation in the population density and detection rates of dingoes on Worimi Country in the Great Lakes region of the NSW coast. We tested whether dingo home range and population densities varied across a gradient of human population density, in a mixed-use landscape including, urban, peri-urban, and National Park environs. We found human population density to be a strong driver of dingo density (ranging from 0.025 to 0.433 dingoes/km2 across the natural-urban gradient), and to have a negative effect on dingo home range size. The spatial scale parameter changed depending on survey period, being smaller in the peak tourism period, when human population increases in the area, than in adjacent survey periods, potentially indicating reduced home range size when additional resources are available. Our study highlights the potential value of managing anthropogenic resource availability to manage carnivore densities and potential risk of human-carnivore interactions.

Urban form in India 1975–2015: Have India's cities become flat?

We focus on two questions in this paper. First, are Indian cities suburbanizing or is their growth compact? Second, what explains the differences in suburbanization or compact growth across cities and regions? We answer these questions using granular, grid-level data from the Global Human Settlements Layer.We take three approaches to understanding the evolution of urban form. First, we explain changes in population density based on concentric rings around the city centre for 100 cities in India. Second, we use these same data to estimate population density gradients in 1975 and 2015. Finally, we use regressions to test hypotheses about relationships between city characteristics and the density gradient.We find that although cities in India densified within their 1975 city limits, they also expanded outward. We find the negative exponential density function is useful for studying urban form in India. South Indian cities and those in urbanized states sprawled more than their northern and less urbanized counterparts. Both the social conditions of central cities such as the literacy rate and the historical pattern of population suburbanization are statistically significantly associated with suburbanization. This suggests the need for greater investment in public infrastructure in central cities to support compact urban growth.

Numerical simulation and evaluation of global ultrafine particle concentrations at the Earth's surface

Abstract. A new global dataset of annually averaged ultrafine particle (UFP) concentrations at the Earth's surface for the years 2015–2017 has been developed through numerical simulations using the ECHAM/MESSy Atmospheric Chemistry model (EMAC). We present total and size-resolved concentrations along with their interannual variability. Size distributions of emitted particles from the contributing source sectors have been derived based on literature reports. The model results of UFP concentrations are evaluated using particle size distribution and particle number concentration measurements from available datasets and the literature. While we obtain reasonable agreement between the model results and observations (logarithmic-scale correlation of r=0.76 for non-remote, polluted regions), the highest values of observed, street-level UFP concentrations are systematically underestimated, whereas in rural environments close to urban areas the model generally overestimates observed UFP concentrations. As the relatively coarse global model does not resolve concentration gradients in urban centres and industrial UFP hotspots, high-resolution data of anthropogenic emissions are used to account for such differences in each model grid box, obtaining UFP concentrations with unprecedented 0.1∘×0.1∘ horizontal resolution at the Earth's surface. This observation-guided downscaling further improves the agreement with observations, leading to an increase in the logarithmic-scale correlation between observed and simulated UFP concentrations to r=0.84 in polluted environments (and 0.95 in all regions), a decrease in the root mean squared logarithmic error (from 0.57 to 0.43), and removal of discrepancies associated with air quality and population density gradients within the model grid boxes. The model results are made publicly available for studies on public health and other impacts of atmospheric UFPs, as well as for intercomparison with other regional and global models and datasets.

Spatial Agglomeration and Diffusion of Population Based on a Regional Density Function Approach: A Case Study of Shandong Province in China

Population density functions have long been used to describe the spatial structure of regional population distributions. Several studies have been conducted to examine the population distribution in Shandong Province, China, but few have applied regional density functions to the analysis. Therefore, based on the 2000, 2010, and 2020 population censuses, this study used monocentric and polycentric regional density functions to study the characteristics of population agglomeration and diffusion in Shandong. This is followed by an in-depth discussion based on population growth rate data and hot- and cold-spot analyses. The results showed that the Shandong Province population was spatially unevenly distributed. Population growth rates were higher in urban centers and counties, with more significant changes in population size in the eastern coastal areas than in the inland areas. As verified in this study, the logarithmic form of the single-center regional density function R2 was greater than 0.8, which was in line with the population spatial structure of Shandong Province. During the study period, the estimated population density of the regional center and the absolute value of the regional population density gradient both increased, indicating a clear and increasing trend of centripetal agglomeration of regional centers over the study period. Overall, the R2 value of the multicenter region density function was higher than that of the single-center region density function. The polycentric regional density function showed that the population density gradient of some centers had a downward trend, which reflected the spatial development trend of outward diffusion in these centers. Meanwhile, the variation in the estimated population density and the population density gradient exhibited differences in the central population distribution patterns at different levels.

Spatial Matrices of Urban Expansion in Lafia, North-Central Nigeria

Rapid urbanisation in African cities has caused considerable problems by hindering their ability to meet infrastructure and service needs, resulting in rising land-use consumption. This study examines how land use/land cover change in Lafia, a city in North-central Nigeria, has impacted the city's boundaries between 1999 and 2019 and includes a projection using GIS simulation of land use/ land cover to 2029. The methodology includes remote sensing techniques, spatiotemporal analysis of geographical measurements, and statistical models. This study involved spatial analysis and projection of city growth from 1999 to 2029 in Lafia using GIS. This analysis focuses on the changes in built-up areas, vegetal cover, bare land, and water bodies using land-use/landcover data. The results indicated significant urban expansion and its impact on the city's spatial patterns. The Urban Expansion Differentiation Index (UEDI) and Urban Expansion Intensity Index (UEII)were used to assess urban sprawl and socioeconomic patterns such as population density and density gradient. High residential and employment densities, varied land uses, continuous development, and multi-modal transportation are all important for sustainable urban growth. The study indicates a direct relationship between population growth and urban expansion, as seen in Lafia. Furthermore, the findings suggest that cities grow beyond their typical boundaries, resulting in peri-urban expansion, as shown in the Alakio districts of the Lafia Metropolis. The study findings have important implications for urban growth policy and land use/land cover change. They will contribute to a better understanding of the effects of urban growth on the spatial matrix and morphology of cities, assisting city planners in recognizing these effects. Furthermore, the study adds evidence to the continuing debate about urban expansion, liveability, and spatial sustainability in African cities. The thorough examination of land use/land cover change in Lafia sheds light on the spatial dynamics of urbanisation and its implications for sustainable urban development.

Urban density does not impact tree growth and canopy cover in native species in Melbourne, Australia

Trees provide multiple ecosystem services in urban centers and increases in tree canopy cover is a key strategy for many municipalities. However, urban trees also experience multiple stresses and tree growth can be impacted by urban density and impervious surfaces. We investigated the impact of differences in urban form on tree growth in the City of Merri-bek, a local government area in metropolitan Melbourne, which is the temperate climate zone. Merri-bek has a gradient in population density and urban greenness from north to south, and we hypothesized that tree growth in the southern areas would be lower because trees were more likely to have less access to water with high levels of impervious surfaces. We selected three common native evergreen species, Eucalyptus leucoxylon, Melaleuca linariifolia, and Lophostemon confertus that exhibit differences in climate vulnerability and assessed the tree canopy expansion in four urban density zones in Merri-bek between 2009 and 2020 using aerial image analysis. The differences in urban form did not significantly influence tree canopy growth and all species showed similar canopy expansion rates. However, smaller trees showed a greater relative canopy increase in the ten years, whereas larger trees had a greater absolute canopy growth. Thus, older and larger trees should be protected and maintained to achieve the canopy expansion. Our study indicated that differences in urban form are unlikely to have major impacts on the growth and canopy expansion of well adapted native tree species in open, suburban centers.

Lichen Biomonitoring of Airborne Microplastics in Milan (N Italy).

This study investigated the deposition of airborne microplastics (MPs) in the urban area of Milan across 12 sites and at a background control site (northern Italy) using 3-month transplants of the fruticose lichen species Evernia prunastri (exposed in triplicate). The primary objective was to evaluate the use of lichen transplants for the assessment of MP deposition; as such, the study sites spanned a gradient in vehicular traffic and population density across four concentric land-use zones (i.e., urban parks, centre, semi-periphery, and periphery). A total of 149 MP particles were detected in the exposed lichen samples; 94.6% were classified as fibres and 5.4% as fragments. The control site and urban parks experienced a similar number of MPs per gram of dry lichen (20-26 MP/g), while a higher number of MPs were detected in central and peripheral areas (44-56 MP/g), with a clear increasing gradient from the city centre towards the periphery. We estimated the MP deposition in Milan to be in the range of 43-119 MPs m2/d, indicating that people living in Milan are exposed to airborne MPs, with potential health effects. This study suggests that lichens are suitable biomonitors of airborne MPs under a relatively short exposure of three months in urban environments.

Pattern formation and front stability for a moving-boundary model of biological invasion and recession

We investigate pattern formation in a two-dimensional (2D) Fisher–Stefan model, which involves solving the Fisher–KPP equation on a compactly-supported region with a moving boundary. The boundary evolves analogously to the classical one-phase Stefan problem, such that boundary speed is proportional to the local population density gradient. By combining the Fisher–KPP and classical Stefan theory, the Fisher–Stefan model alleviates two limitations of the Fisher–KPP equation for biological populations. Unlike the Fisher–KPP equation, solutions to the Fisher–Stefan model have compact support, explicitly defining the region occupied by the population. Furthermore, the Fisher–Stefan model admits travelling wave solutions with non-negative density for all wave speeds c∈(−∞,∞), and can thus model both population invasion and population recession. In this work, we investigate whether the 2D Fisher–Stefan model predicts pattern formation, by analysing the linear stability of planar travelling wave solutions to sinusoidal transverse perturbations. Planar fronts of the Fisher–KPP equation are linearly stable. Similarly, we demonstrate that invading planar fronts (c>0) of the Fisher–Stefan model are linearly stable to perturbations of all wave numbers. However, our analysis demonstrates that receding planar fronts (c<0) of the Fisher–Stefan model are linearly unstable for all wave numbers. This is analogous to unstable solutions for planar solidification in the classical Stefan problem. Introducing a surface tension regularisation stabilises receding fronts for short-wavelength perturbations, giving rise to a range of unstable modes and a most unstable wave number. We supplement linear stability analysis with level-set numerical solutions that corroborate theoretical results. Overall, front instability in the Fisher–Stefan model suggests a new mechanism for pattern formation in receding biological populations.

Spatial structure of city population growth

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data for over 3,100 U.S. counties reveals that annual population flows, resulting from domestic migration during the 2015–2019 period, are much larger than natural demographic growth, and are primarily responsible for this heterogeneous growth. More precisely, we show that intra-city flows are generally along a negative population density gradient, while inter-city flows are concentrated in high-density core areas. Intra-city flows are anisotropic and generally directed towards external counties of cities, driving asymmetrical urban sprawl. Such domestic migration dynamics are also responsible for tempering local population shocks by redistributing inflows within a given city. This spill-over effect leads to a smoother population dynamics at the county level, in contrast to that observed at the city level. Understanding the spatial structure of domestic migration flows is a key ingredient for analyzing their drivers and consequences, thus representing a crucial knowledge for urban policy makers and planners.

Future of Rural Transit

This paper provides a contemplative description of the future of rural public transportation. It considers emerging technologies along with their long-term implications and corresponding impacts on rural communities. The authors used their collective knowledge to identify key drivers of change in rural areas. As a result, the authors expect the future definition of rural areas to change and a new geographical classification to emerge. This classification is a continuum of population density gradient from highly populated urban areas to sparsely populated areas. The paper also suggests that automated vehicles and hologram telecommuting could dominate the U.S. transportation industry, even in rural settings.

Population density mediates induced immune response, but not physiological condition in a well-adapted urban bird

Thriving under high population density is considered a major feature of urban exploiter species. Nevertheless, population density appears to be a surprisingly overlooked factor in urban ecology studies. High population numbers observed in urban species might promote pathogen transmission and negatively affect health or condition, thus requiring investments in immunocompetence. The feral pigeon Columba livia domestica is an example of a successful city-dweller, found in great abundance in large cities across the globe. We investigated the effects of population density on induced immune response (phytohaemagglutinin skin test) and body condition (blood haemoglobin concentration and size-corrected body mass) in 120 feral pigeons, captured along population density gradient in Łódź (central Poland). We found that stronger immune response was associated with higher population density, but was not related to physiological condition and physiological stress (heterophil/lymphocyte ratio). Moreover, condition indices were not associated with population density. However, since pigeon population density was highly correlated with the level of habitat urbanization, we cannot exclude that any density-dependent effects may be mediated by habitat variation. Our results indicate that urban environment, via population density, might exert different selective pressures on immunocompetence and body condition in this successful urban exploiter.

Transmission of SARS-CoV-2 in the Population Living in High- and Low-Density Gradient Areas in Dhaka, Bangladesh.

Community transmission of SARS-CoV-2 in densely populated countries has been a topic of concern from the beginning of the pandemic. Evidence of community transmission of SARS-CoV-2 according to population density gradient and socio-economic status (SES) is limited. In June–September 2020, we conducted a descriptive longitudinal study to determine the community transmission of SARS-CoV-2 in high- and low-density areas in Dhaka city. The Secondary Attack Rate (SAR) was 10% in high-density areas compared to 20% in low-density areas. People with high SES had a significantly higher level of SARS-CoV-2-specific Immunoglobulin G (IgG) antibodies on study days 1 (p = 0.01) and 28 (p = 0.03) compared to those with low SES in high-density areas. In contrast, the levels of seropositivity of SARS-CoV-2-specific Immunoglobulin M (IgM) were comparable (p > 0.05) in people with high and low SES on both study days 1 and 28 in both high- and low-density areas. Due to the similar household size, no differences in the seropositivity rates depending on the population gradient were observed. However, people with high SES showed higher seroconversion rates compared to people with low SES. As no difference was observed based on population density, the SES might play a role in SARS-CoV-2 transmission, an issue that calls for further in-depth studies to better understand the community transmission of SARS-CoV-2.

Patterns and determinants of dispersal in grey wolves (Canis lupus)

Dispersal is a key demographic process involving three stages: emigration, transience and settlement; each of which is influenced by individual, social and environmental determinants. An integrated understanding of species dispersal is essential for demographic modelling and conservation planning. Here, we review the dispersal patterns and determinants documented in the scientific literature for the grey wolf (Canis lupus) across its distribution range. We showed a surprisingly high variability within and among study areas on all dispersal parameters - dispersal rate, direction, distance, duration and success. We found that such large variability is due to multiple individual, social and environmental determinants, but also due to previously overlooked methodological research issues. We revealed a potential non-linear relationship between dispersal rate and population density, with dispersal rate higher at both ends of the gradient of population density. We found that human-caused mortality reduces distance, duration and success of dispersal events. Furthermore, dispersers avoid interaction with humans, and highly exposed areas like agricultural lands hamper population connectivity in many cases. We identified numerous methodological research problems that make it difficult to obtain robust estimates of dispersal parameters and robust inferences on dispersal patterns and their determinants. In particular, analyses where confounding factors were not accounted for led to substantial knowledge gaps on all aspects of dispersal in an otherwise much-studied species. Our understanding of wolf biology and management would significantly benefit if wolf dispersal studies reported the results and possible factors affecting wolf dispersal more transparently.

Delineating Functional Urban Areas Using a Multi-Step Analysis of Artificial Light-at-Night Data

A functional urban area (FUA) is a geographic entity that consists of a densely inhabited city and a less densely populated commuting zone, both highly integrated through labor markets. The delineation of FUAs is important for comparative urban studies and it is commonly performed using census data and data on commuting flows. However, at the national scale, censuses and commuting surveys are performed at low frequency, and, on the global scale, consistent and comparable data are difficult to obtain overall. In this paper, we suggest and test a novel approach based on artificial light at night (ALAN) satellite data to delineate FUAs. As ALAN is emitted by illumination of thoroughfare roads, frequented by commuters, and by buildings surrounding roads, ALAN data can be used, as we hypothesize, for the identification of FUAs. However, as individual FUAs differ by their ALAN emissions, different ALAN thresholds are needed to delineate different FUAs, even those in the same country. To determine such differential thresholds, we use a multi-step approach. First, we analyze the ALAN flux distribution and determine the most frequent ALAN value observed in each FUA. Next, we adjust this value for the FUA’s compactness, and run regressions, in which the estimated ALAN threshold is the dependent variable. In these models, we use several readily available, or easy-to-calculate, characteristics of FUA cores, such as latitude, proximity to the nearest major city, population density, and population density gradient, as predictors. At the next step, we use the estimated models to define optimal ALAN thresholds for individual FUAs, and then compare the boundaries of FUAs, estimated by modelling, with commuting-based delineations. To measure the degree of correspondence between the commuting-based and model-predicted FUAs’ boundaries, we use the Jaccard index, which compares the size of the intersection with the size of the union of each pair of delineations. We apply the proposed approach to two European countries—France and Spain—which host 82 and 72 FUAs, respectively. As our analysis shows, ALAN thresholds, estimated by modelling, fit FUAs’ commuting boundaries with an accuracy of up to 75–100%, being, on the average, higher for large and densely-populated FUAs, than for small, low-density ones. We validate the estimated models by applying them to another European country—Austria—which demonstrates the prediction accuracy of 47–57%, depending on the model type used.

Impact of the affected population size assessment on the decision-making after a nuclear event

In this study an improvised nuclear device (IND) is simulated using a software called HotSpot. The explosion took place in a theoretical central business district (CBD), for the major issue addressed in this paper is the comparison of two methods used for estimating the size of the potentially affected population. The first method estimates the size by multiplying the local average demographic density by the area of the zone of interest. The second method uses the population density gradient model developed by Colin Clark in 1951. The comparison of the two methods enables authorities to better estimate the allocation of resources. The conservative approach allocates the maximum resources possible. However, the Clark model enables a more realistic approach which allocates minimum resources to the emergency response. This study shows how accurate information can be quintessential for authorities to maximize the efficiency of their decisions.

A Local and Time Resolution of the COVID-19 Propagation—A Two-Dimensional Approach for Germany Including Diffusion Phenomena to Describe the Spatial Spread of the COVID-19 Pandemic

The understanding of factors that affect the dissemination of a viral infection is fundamental to help combat it. For instance, during the COVID-19 pandemic that changed the lives of people all over the world, one observes regions with different incidences of cases. One can speculate that population density might be one of the variables that affect the incidence of cases. In populous areas, such as big cities or congested urban areas, higher COVID-19 incidences could be observed than in rural regions. It is natural to think that if population density is such an important factor, then a gradient or difference in population density might lead to a diffusion process that will proceed until equilibrium is reached. The aim of this paper consists of the inclusion of a diffusion concept into the COVID-19 modeling. With this concept, one covers a gradient-driven transfer of the infection next to epidemic growth models (SIR-type models). This is discussed for a certain period of the German situation based on the quite different incidence data for the different federal states of Germany. With this ansatz, some phenomena of the actual development of the pandemic are found to be confirmed. The model provides a possibility to investigate certain scenarios, such as border-crossings or local spreading events, and their influence on the COVID-19 propagation. The resulting information can be a basis for the decisions of politicians and medical persons in charge of managing a pandemic.

Investigating persistent measles dynamics in Niger and associations with rainfall.

Measles is a major cause of child mortality in sub-Saharan Africa. Current immunization strategies achieve low coverage in areas where transmission drivers differ substantially from those in high-income countries. A better understanding of measles transmission in areas with measles persistence will increase vaccination coverage and reduce ongoing transmission. We analysed weekly reported measles cases at the district level in Niger from 1995 to 2004 to identify underlying transmission mechanisms. We identified dominant periodicities and the associated spatial clustering patterns. We also investigated associations between reported measles cases and environmental drivers associated with human activities, particularly rainfall. The annual and 2–3-year periodicities dominated the reporting data spectrum. The annual periodicity was strong with contiguous spatial clustering, consistent with the latitudinal gradient of population density, and stable over time. The 2–3-year periodicities were weaker, unstable over time and had spatially fragmented clustering. The rainy season was associated with a lower risk of measles case reporting. The annual periodicity likely reflects seasonal agricultural labour migration, whereas the 2–3-year periodicity potentially results from multiple mechanisms such as reintroductions and vaccine coverage heterogeneity. Our findings suggest that improving vaccine coverage in seasonally mobile populations could reduce strong measles seasonality in Niger and across similar settings.