Local Population Density Research Articles

Estimating school provision, access and costs from local pupil counts under decentralised governance

This study proposes a sequence of methods to obtain geolocated estimates of primary school provision, costs, and access. This sequence entails: (1) location-allocation, an approach that mimics school location patterns in case of decentralised governance, such as exists in the EU and UK; (2) balanced floating catchment areas, an approach to assign pupils to schools assuming free school choice; and (3) school costs estimates, which are induced from pupil counts and the distributional properties of observed school costs. The method is fine-tuned using observed school locations and school-level costs data. It is developed to assess how much local population densities and demography affects school access and schooling costs across Europe. Its results can be aggregated by degree of urbanisation to quantify the differences across human settlements ranging from mostly uninhabited areas to densely populated cities.

A pathogen's spatial range is not constrained by geographical features in the flax rust pathosystem.

Climate change and shifting environmental conditions can allow pathogens to spread into previously unburdened areas. For plant pathogens, this dynamic has the potential to disrupt natural ecosystem equilibria and human agriculture, making predicting plant pathogen range shifts increasingly important. Although such predictions will hinge on an accurate understanding of the determinants of pathogen range-namely the environmental, geographical, and host range characteristics that modulate local pathogen habitation-few studies to date have probed these in natural plant populations. Here, we characterize range determinants for the model system of Lewis flax (Linum lewisii) and its pathogen, flax rust (Melampsora lini), in the Rocky Mountains. Transect surveys were performed to assess three relationships: (i) the effect of geographical features-elevation, slope aspect, slope grade, and land cover-on flax presence and density, (ii) the effect of geographical features on flax rust presence and prevalence, and (iii) the effects of flax's local population density and metapopulation structure on flax rust presence and prevalence. We found that flax population density, but not host metapopulation structure, influences the distribution of flax rust. Additionally, we showed that, while the distribution of flax was broadly constrained to a relatively narrow range of geographical and resulting environmental features, flax rust was evenly distributed across the full range of settings measured. These results indicate that a warming environment, which is expected to modulate such features, may restrict the optimal range of the plant more than that of its pathogen. Importantly, our results also suggest that even if flax shifts its spatial range to escape increasing climatic pressures, flax rust will not face any significant barriers to track this movement.

Characterization of an Autoinducing Peptide Signal Reveals Highly Efficacious Synthetic Inhibitors and Activators of Quorum Sensing and Biofilm Formation in Listeria monocytogenes.

Bacteria can use chemical signals to assess their local population density in a process called quorum sensing (QS). Many of these bacteria are common pathogens, including Gram-positive bacteria that utilize agr QS systems regulated by macrocyclic autoinducing peptide (AIP) signals. Listeria monocytogenes, an important foodborne pathogen, uses an agr system to regulate a variety of virulence factors and biofilm formation, yet little is known about the specific roles of agr in Listeria infection and its persistence in various environments. Herein, we report synthetic peptide tools that will enable the study of QS in Listeria. We identified a 6-mer AIP signal in L. monocytogenes supernatants and selected it as a scaffold around which a collection of non-native AIP mimics was designed and synthesized. These peptides were evaluated in cell-based agr reporter assays to generate structure-activity relationships for AIP-based agonism and antagonism in L. monocytogenes. We discovered synthetic agonists with increased potency relative to native AIP and a synthetic antagonist capable of reducing agr activity to basal levels. Notably, the latter peptide was able to reduce biofilm formation by over 90%, a first for a synthetic QS modulator in wild-type L. monocytogenes. The lead agr agonist and antagonist in L. monocytogenes were also capable of antagonizing agr signaling in the related pathogen Staphylococcus aureus, further extending their utility and suggesting different mechanisms of agr activation in these two pathogens. This study represents an important first step in the application of chemical methods to modulate QS and concomitant virulence outcomes in L. monocytogenes.

Ecological Barriers for an Amphibian Pathogen: A Narrow Ecological Niche for Batrachochytrium salamandrivorans in an Asian Chytrid Hotspot.

The chytrid fungal pathogens Batrachochytrium salamandrivorans (Bsal) and B. dendrobatidis (Bd) are driving amphibian extinctions and population declines worldwide. As their origins are believed to be in East/Southeast Asia, this region is crucial for understanding their ecology. However, Bsal screening is relatively limited in this region, particularly in hotspots where Bd lineage diversity is high. To address this gap, we conducted an extensive Bsal screening involving 1101 individuals from 36 amphibian species, spanning 17 natural locations and four captive facilities in the biodiversity-rich Guangxi Zhuang Autonomous Region (GAR). Our PCR assays yielded unexpected results, revealing the complete absence of Bsal in all tested samples including 51 individuals with Bd presence. To understand the potential distribution of Bsal, we created niche models, utilizing existing occurrence records from both Asia and Europe. These models estimated potential suitable habitats for Bsal largely in the northern and southwestern parts of the GAR. Although Bsal was absent in our samples, the niche models identified 10 study sites as being potentially suitable for this pathogen. Interestingly, out of these 10 sites, Bd was detected at 8. This suggests that Bsal and Bd could possibly co-exist in these habitats, if Bsal were present. Several factors seem to influence the distribution of Bsal in Asia, including variations in temperature, local caudate species diversity, elevation, and human population density. However, it is climate-related factors that hold the greatest significance, accounting for a notable 60% contribution. The models propose that the specific climatic conditions of arid regions, primarily seen in the GAR, play a major role in the distribution of Bsal. Considering the increased pathogenicity of Bsal at stable and cooler temperatures (10-15 °C), species-dependent variations, and the potential for seasonal Bd-Bsal interactions, we emphasize the importance of periodic monitoring for Bsal within its projected range in the GAR. Our study provides deeper insights into Bsal's ecological niche and the knowledge generated will facilitate conservation efforts in amphibian populations devastated by chytrid pathogens across other regions of the world.

Research on Second-Hand Sailboat Prices Based on Machine Learning

With the development of the international shipping market and changes in second-hand ship prices, the operation and trade of second-hand ships are quite active. To accurately evaluate the price of second-hand ships, it is particularly important to establish a pricing model for second-hand ships. The first part of this article uses X-GBoost and PCA to rank and reduce the importance of features, and obtains four principal components. Based on 5 indicators and their importance ratios, establish an optimized X-GBoost regression model for Sine Cosine Algorithm (SCA) to predict the price of second-hand ships. In order to further investigate the impact of regional characteristics on prices, local population density, per capita GDP, and cargo throughput were selected to further classify regional characteristics. A linear regression model was established to investigate the impact of population density, per capita GDP, and cargo throughput on regional error prices, and to explore the impact of various regional characteristics on error prices. Divide sailboats into three categories – low-end sailboats, mid-range sailboats, and high-end sailboats, and discuss the impact of regional characteristics on prices. The study found that there is a significant difference in the prices of low-end sailboats and mid-range sailboats between regions, indicating consistency in regional effects. Studying the pricing of second-hand sailboats can help to correctly select trading markets, develop marketing strategies, purchase ships with higher economic priority, and promote the development and prosperity of the sailing industry.

A Hybridization of Spatial Modeling and Deep Learning for People’s Visual Perception of Urban Landscapes

The visual qualities of the urban environment influence people’s perception and reaction to their surroundings; hence the visual quality of the urban environment affects people’s mental states and can have detrimental societal effects. Therefore, people’s perception and understanding of the urban environment are necessary. This study used a deep learning-based approach to address the relationship between effective spatial criteria and people’s visual perception, as well as spatial modeling and preparing a potential map of people’s visual perception in urban environments. Dependent data on people’s visual perception of Tehran, Iran, was gathered through a questionnaire that contained information about 663 people, 517 pleasant places, and 146 unpleasant places. The independent data consisted of distances to industrial areas, public transport stations, recreational attractions, primary streets, secondary streets, local passages, billboards, restaurants, shopping malls, dilapidated areas, cemeteries, religious places, traffic volume, population density, night light, air quality index (AQI), and normalized difference vegetation index (NDVI). The convolutional neural network (CNN) algorithm created the potential map. The potential visual perception map was evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC), with the estimates of AUC of 0.877 and 0.823 for pleasant and unpleasant visuals, respectively. The maps obtained using the CNN algorithm showed that northern, northwest, central, eastern, and some southern areas of the city are potent in pleasant sight, and southeast, some central, and southern regions had unpleasant sight potential. The OneR method results demonstrated that distance to local passages, population density, and traffic volume is most important for pleasant and unpleasant sights.

Diffusible signal factor primes plant immunity against Xanthomonas campestris pv. campestris (Xcc) via JA signaling in Arabidopsis and Brassica oleracea.

Many Gram-negative bacteria use quorum sensing (QS) signal molecules to monitor their local population density and to coordinate their collective behaviors. The diffusible signal factor (DSF) family represents an intriguing type of QS signal to mediate intraspecies and interspecies communication. Recently, accumulating evidence demonstrates the role of DSF in mediating inter-kingdom communication between DSF-producing bacteria and plants. However, the regulatory mechanism of DSF during the Xanthomonas-plant interactions remain unclear. Plants were pretreated with different concentration of DSF and subsequent inoculated with pathogen Xanthomonas campestris pv. campestris (Xcc). Pathogenicity, phynotypic analysis, transcriptome combined with metabolome analysis, genetic analysis and gene expression analysis were used to evaluate the priming effects of DSF on plant disease resistance. We found that the low concentration of DSF could prime plant immunity against Xcc in both Brassica oleracea and Arabidopsis thaliana. Pretreatment with DSF and subsequent pathogen invasion triggered an augmented burst of ROS by DCFH-DA and DAB staining. CAT application could attenuate the level of ROS induced by DSF. The expression of RBOHD and RBOHF were up-regulated and the activities of antioxidases POD increased after DSF treatment followed by Xcc inoculation. Transcriptome combined with metabolome analysis showed that plant hormone jasmonic acid (JA) signaling involved in DSF-primed resistance to Xcc in Arabidopsis. The expression of JA synthesis genes (AOC2, AOS, LOX2, OPR3 and JAR1), transportor gene (JAT1), regulator genes (JAZ1 and MYC2) and responsive genes (VSP2, PDF1.2 and Thi2.1) were up-regulated significantly by DSF upon Xcc challenge. The primed effects were not observed in JA relevant mutant coi1-1 and jar1-1. These results indicated that DSF-primed resistance against Xcc was dependent on the JA pathway. Our findings advanced the understanding of QS signal-mediated communication and provide a new strategy for the control of black rot in Brassica oleracea.

Environment and man in the Late Palaeolithic — Middle Ages in the southern Primorye: review

Questions concerning the effect of environment on appearance, development and disappearance of ar-chaeological cultures in the territory of southern Primorye have been addressed in the article. The chronological framework of the research is from the Late Palaeolithic through to the Middle Ages. Thirty three natural sections of different genesis have been examined for reconstruction of the Late Pleistocene — Holocene environment. Palynological, diatomic and radiocarbon methods have been used for their examination. The data on archaeologi-cal periods and cultures have been provided based on the analysis of materials of Primorye archaeological sites (including 14 Palaeolithic, 33 Neolithic, 30 Paleometal, and 15 Medieval). Climatic changes have been discussed in terms of their effect on the resource base of people. The earliest Palaeolithic sites, which 14C date approxi-mately 16,000 years BP, were found in Eastern part of Primorye. Climate warming and rise of sea level in the Early Neolithic (ca. 8,000 years 14C BP) facilitated the growth of resource base and expansion of the Neolithic people with sustainable adaptation models in Primorye. This manifested in the appearance of long-term settle-ments and differentiation of the tool sets. The beginning of the sea regression around 6,000 14С years BP resulted in the extinction of the Boysman Culture. Slight cooling and aridization of the climate 5,600–5,400 14C years BP contributed to the appearance of a new cultural tradition involved with agriculture. The long existence of cultures in the Late Neolithic and Paleometal periods, with significant climatic shifts, can be explained by introducing mixed economy model with increased role of the economy of producing type. In the Late Paleometal and Medieval periods, economic, political and military factors had a great impact on communities, along with environment and climatic factors. Correlation of palaeogeographical and archaeological data demonstrated a certain synchronicity of environmental changes and cultural events. Climatic fluctuations led to migrations, variations in local population den-sity, changes in adaptation strategies of the people, and changes of direction of economic activities.

Characterization of municipal solid waste: Measures towards management strategies using statistical analysis

Implementing unified municipal solid waste management (MSWM) is often difficult due to socio-economic variables. However, spatial GIS models and statistical analysis of solid waste characterized by the weekdays, weekends, and festivals can somewhat mitigate the variance and assist with selecting suitable waste management methods. This paper presents the example of Rajouri, India, to propose a suitable MSWM based on Inverse Distance Weighted (IDW) intensity maps and statistical findings. The considered region was divided into different sample sites based on the local population density, and Municipal Solid Waste (MSW) was collected from four locations in each site on weekdays, weekends, and festivals. Compositional analysis of the MSW was then used to generate spatial IDW models in QGIS 3.22.7 to interpolate MSW generation over the entire area. Finally, statistical analysis was conducted to gain insight into the waste generation and accumulation trends. The results show that Rajouri produces 245 tonnes of waste daily (per capita: 0.382 kg/day) with a large organic fraction compared to other waste categories. Besides, waste generation is observed to increase over weekends and festivals due to increased consumption of material goods. Composting could serve as a vector for municipal solid waste because of its increased organic component and cost constraints. However, further research on the potential segregation techniques for the organic fraction of solid waste is needed.

Environmental variation across multiple spatial scales and temporal lags influences Hendra virus spillover

Abstract Pathogens can spill over and infect new host species by overcoming a series of ecological and biological barriers. Hendra virus (HeV) circulates in Australian flying foxes and provides a data‐rich study system for identifying environmental drivers underlying spillover events. The frequency of spillover events to horses has varied interannually since the virus was first discovered in 1994. These observations suggest that HeV spillover events are driven, in part, by environmental factors, including loss of flying fox habitat and climate variability. We explicitly examine the impact of environmental variation on the risk of HeV spillover at three spatial scales relevant to this system. We use a dataset of 60 spillover events and boosted regression tree methods to identify environmental features (including concurrent and lagged temperature, rainfall, vegetation indices, land cover, and climate indices) at three spatial scales (1‐km, 20‐km, 100‐km radii) associated with horse contacts and reservoir species ecology. We find that temperature, local (1‐km radius) human population density, and landscape (100‐km radius) forest cover and pasture are the most influential environmental features associated with HeV spillover risk. By including multiple spatial scales and temporal lags in environmental features, we can more accurately quantify risk across space and time than with models that use a single scale. For example, high quality vegetation at the local scale and within a foraging radius (20‐km) in the concurrent month and previous years, combined with poorer quality vegetation at the landscape scale in the concurrent month increase risk of HeV spillover. These and other environmental associations likely influence the dynamic foraging behaviour of reservoir flying foxes and drive contacts that facilitate spillover into horse populations. Synthesis and application: Current management of HeV spillover focuses on local‐scale interventions – primarily through vaccination and detection of infected horses. Our study finds that HeV spillover risk is also driven by environmental changes over much larger scales and demonstrates management practices would benefit from incorporating landscape interventions alongside local interventions.

Dispersal inference from population genetic variation using a convolutional neural network.

The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here, we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training-including population density, demographic history, habitat size, and sampling area-and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate inference of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN," a potentially valuable new tool for estimating dispersal distance in nonmodel systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.

Global patterns and predictors of avian population density

AbstractAimHow population density varies across animal species in the context of environmental gradients, and associated migratory strategies, remains poorly understood. The recent influx of avian trait data and population density estimates allows these patterns to be described and explored in unprecedented detail. This study aims to identify the main macroecological drivers of population density in birds.LocationGlobal.Time period1970–2021.Major taxa studiedBirds (Aves).MethodsWe collated a dataset of 5072 local population density estimates for 1853 species and modelled population density as a function of trait and environmental predictors in a Bayesian framework accounting for phylogenetic and spatial autocorrelation. We explored the influence of body mass, diet, primary lifestyle, mating system, nesting behaviour, territoriality, and migratory behaviour on population density, accounting for a range of environmental variables, including preferred habitat type, primary productivity, precipitation and temperature. Based on this empirical baseline, we then predicted the mean population density for 9089 species of birds and estimated global geographic patterns of bird population density.ResultsPopulation density was lower in species with larger body mass and higher trophic levels, and also declined in territorial species, migratory species, brood parasites and species inhabiting resource‐poor habitat types (e.g., deserts). Conversely, population density increased in cooperative breeders. Environmental drivers were most influential for migratory birds, with precipitation and temperature both associated with higher population density. Overall, bird population densities were higher at lower latitudes.Main conclusionsOur results support previous findings on the role of body mass, diet and environmental gradients, but also reveal novel species‐specific drivers of avian densities related to reproduction, migration and resource‐holding behaviour. Substantial fine‐scale variation remains unexplained. We provide a global dataset of population density predictions for use in macroecological analyses and conservation assessments.

Simulating the dynamics of dispersal and dispersal ability in fragmented populations with mate-finding Allee effects.

We consider the spatial propagation and genetic evolution of model populations comprising multiple subpopulations, each distinguished by its own characteristic dispersal rate. Mate finding is modeled in accord with the assumption that reproduction is based on random encounters between pairs of individuals, so that the frequency of interbreeding between two subpopulations is proportional to the product of local population densities of each. The resulting nonlinear growth term produces an Allee effect, whereby reproduction rates are lower in sparsely populated areas; the distribution of dispersal rates that evolves is then highly dependent upon the population's initial spatial distribution. In a series of numerical test cases, we consider how these dynamics affect lattice-like arrangements of population fragments, and investigate how a population's initial fragmentation determines the dispersal rates that evolve as a habitat is colonized. First, we consider a case where initial population fragments coincide with habitat islands, within which death rates differ from those that apply outside; the presence of inhospitable exterior regions exaggerates Allee effect-driven reductions in dispersal ability. We then examine how greater distances separating adjacent population fragments lead to more severe reductions in dispersal ability. For populations of a fixed initial magnitude, fragmentation into smaller, denser patches leads not only to greater losses of dispersal ability, but also helps ensure the population's long-term persistence, emphasizing the trade-offs between the benefits and risks of rapid dispersal under Allee effects. Next, simulations of well-established populations disrupted by localized depopulation events illustrate how mate-finding Allee effects and spatial heterogeneity can drive a population's dispersal ability to evolve either downward or upward depending on conditions, highlighting a qualitative distinction between population fragmentation and habitat heterogeneity. A final test case compares populations that are fragmented across multiple scales, demonstrating how differences in the relative scales of micro- and macro-level fragmentation can lead to qualitatively different evolutionary outcomes.

Microplastics in subsurface water and zooplankton from eight lakes in British Columbia

Microplastics are a global contaminant of concern, but we have little information on the characteristics and bioavailability of these pollutants in western Canadian lakes. Here, we quantify and characterize microplastics in subsurface water and zooplankton from eight lakes in BC, Canada. By sampling water and zooplankton, we provide insight into the fraction of microplastics entering the food web. We found 0.607 ± 0.153 microplastics per litre in subsurface water, 0.01 ± 0.011 microplastics per copepod, and 0.02 ± 0.014 microplastics per Daphnia. Microplastic pollution was similar in all lakes sampled and showed no relationship with local population density. Fibers were the dominant morphology observed in all lakes, and Raman spectroscopy identified polyester as the dominant polymer found both in lakes and within zooplankton. Zooplankton generally ingested microplastics that were shorter than their body length and that fell on the smaller end of the range of available microplastics. The prominence of polyester fibers and PET films and fragments suggests that the likely sources of microplastics to these lakes are recreational activities and atmospheric deposition.

Just street trees? Street trees increase local biodiversity and biomass in higher income, denser neighborhoods

AbstractTree canopy cover is a critical component of the urban environment that supports ecosystem services at multiple spatial and temporal scales. Increasing tree canopy across a matrix of public and private land is challenging. As such, municipalities often plant trees along streets in public rights‐of‐way where there are fewer barriers to establishment, and composition and biomass of street trees are inextricably linked to human decisions, management, and care. In this study, we investigated the contributions of street trees to the broader urban forest, inclusive of tree canopy distributed across both public and private parcels in Baltimore, MD, USA. We assess how species composition, biodiversity, and biomass of street trees specifically augment the urban forest at local and citywide scales. Furthermore, we evaluate how street tree contributions to the urban forest vary with social and demographic characteristics of local residential communities. Our analyses demonstrate that street trees significantly enhanced citywide metrics of the urban forests' richness and tree biomass, adding an average six unique species per site. However, street tree contributions did not ameliorate low tree canopy locations, and more street tree biomass was generally aligned with higher urban forest cover. Furthermore, species richness, abundance, and biomass added by street trees were all positively related to local household income and population density. Our results corroborate previous findings that wealthier urban neighborhoods often have greater tree abundance and canopy cover and, additionally, suggest that investment in municipally managed street trees may be reinforcing inequities in distribution and function of the urban forest. This suggests a need for greater attention to where and why street tree plantings occur, what species are selected, and how planted tree survival is maintained by and for residents in different neighborhoods.

Patterns and Contexts of Anti-COVID-19 Vaccination in Romanian Local Communities

Background: Are local communities relevant units for the analysis of anti-COVID 19 vaccination? This is the question we are addressing here for the case of Romania as an Eastern European society. Methods: To answer the question we used multiple regression models to predict cumulative rates of vaccination in rural communes and cities or towns of the country. The same relations among vaccination rates and several predictors were analysed not only in all the localities of the country but also in historical regions and urban versus rural areas. Results: Infection rates, the average age of the local population, population density and local human development proved to be rather stable predictors. Communities with higher vaccination rates are mostly urban, higher developed, with an older population, and also with higher rates of COVID-19 infections. Once local communities are placed in their regional context, significant differences emerge. Conclusions: Some variables are efficient discriminators of the vaccination behaviour irrespective of individual or aggregated level of the data. This is the case of age. If one considers only aggregated data at the community level in Romania, one can add infection rates and local development levels as invariant predictors acting beyond context

Equity versus efficiency: A spatial analysis of residential aged care resources in Beijing

Based on data collected from residential aged care facility websites and the Sixth China National Population Census, this paper studies the spatial pattern of Beijing's aged care resources in the framework of spatial location of public facilities. The results show that at the township/street level, the overall distribution of public aged care resources is relatively balanced, showing positive spatial autocorrelation, while private aged care resources show partially negative spatial autocorrelation. Spatial regression analysis indicates that the dispersed and clustered distribution of private aged care resources are more sensitive to the density of local elderly population, although the distribution of two types of resources is affected by the absolute number of service objects in respective administrative areas. In short, the spatial distribution pattern of public and private aged care resources reflects the contrast between efficiency and equity in providing aging care in China, a fact that is shaped by both administrative and market forces.

The time course of behavioural phase change in the Central American locust Schistocerca piceifrons.

Locusts exhibit an extreme form of phenotypic plasticity and can exist as two alternative phenotypes, known as solitarious and gregarious phases. These phases, which can transform from one to another depending on local population density, show distinctly different behavioural characteristics. The proximate mechanisms of behavioural phase polyphenism have been well studied in the desert locust Schistocerca gregaria and the migratory locust Locusta migratoria, and what is known in these species is often treated as a general feature of locusts. However, this approach might be flawed, given that there are approximately 20 locust species that have independently evolved phase polyphenism. Using the Central American locust Schistocerca piceifrons as a study system, we characterised the time course of behavioural phase change using standard locust behavioural assays, using both a logistic regression-based model and analyses of separate behavioural variables. We found that for nymphs of S. piceifrons, solitarisation was a relatively fast, two-step process, but that gregarisation was a much slower process. Additionally, the density of the gregarisation treatment seemed to have no effect on the rate of phase change. These data are at odds with what we know about the time course of behavioural phase change in S. gregaria, suggesting that the mechanisms of locust phase polyphenism in these two species are different and may not be phylogenetically constrained. Our study represents the most in-depth study of behavioural gregarisation and solitarisation in locusts to date.

City centrality, population density and energy efficiency

We use continuous night light data and LandScan population data to construct a monocentric index to measure whether a city tends to be a monocentric or polycentric spatial structure, and estimate the impact of such structure on energy efficiency by using a two-way fixed effects model. In order to solve the endogeneity of urban structure, the historical census data and topographic relief data at the city level are used to construct the instrumental variables. We find that an increase in the urban monocentricity index would significantly reduce the level of the urban energy intensity. Meanwhile, the relationship between monocentricity and urban energy intensity is U-shaped. When the degree of monocentricity is at relatively low level, its impact on energy efficiency is positive, implying the dominance of agglomeration effect. When economic agglomeration is greater than a certain degree, the impact of monocentricity becomes negative which results from the dominance of congestion effect. Moreover, impact of urban structure on energy intensity varies with urban population density. An increase in population density would weaken the negative impact of monocentricity on energy intensity, that is, in sparsely populated cities, the monocentricity is more conducive to energy saving. In terms of city form, monocentric structure may improve energy efficiency in the cities with poor transportation infrastructure more than in the cities with good transportation infrastructure. Monocentricity facilitates energy efficiency primarily by increasing corporate innovation and saving commuting time and distance. We perform a series of robustness tests and the findings are basically consistent with the baseline result. Our findings suggest that the cities at this stage should continue to strengthen the development of monocentricity, pay attention to compactness of urban spatial structure, and develop the polycentric structure cautiously. Meanwhile, in the development process, the local population density and the carrying capacity of the transportation infrastructure should be taken into consideration to avoid the negative effects caused by the congestion in main center.

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.