Initial Population Density Research Articles

Exploring the dynamics of leprosy transmission with treatment through a fractal–fractional differential model

Leprosy continues to be a significant public health challenge in many parts of the world, necessitating novel approaches to understanding and controlling its transmission. The dynamics of leprosy are examined in this study by means of a caputo fabrizio fractal–fractional differential system model. Leprosy transmission and treatment are complex and non-linear processes that can be captured by fractal–fractional derivatives. The temporal progression of the disease is the primary focus of our mathematical analysis, which evaluates a variety of parameter values, including initial population densities and compartmental transitions. Through simulations, we examine the impact of critical parameters on the severity and spread of diseases, as well as the rates of recovery and treatment. Numerical results of the model offer valuable insights into the impact of these parameters on leprosy dynamics, which is beneficial for public health interventions. The stability analysis of the model identifies supplementary conditions that are necessary for the success of disease control. By incorporating these novel mathematical techniques, we hope to improve our understanding of leprosy transmission and ultimately contribute to more effective control strategies. Based on our findings, additional studies investigating the relation between population density, treatment accessibility, and recovery rates are warranted. We hope that by graphically representing the relationships between these factors, we can draw attention to the possibility of targeted interventions that can reduce the transmission of leprosy. This study provides a strong basis for future studies on infectious disease modeling and aids leprosy-affected communities in developing strategies to mitigate the disease’s impact.

Threshold temperature of superfluorescence generation in CuCl quantum dots under resonant excitation of excitons and resonant two-photon excitation of biexcitons

We studied the threshold temperature of superfluorescence (SF) generation with regard to biexcitons in CuCl quantum dots (QDs) under resonant two-photon excitation of biexcitons and resonant excitation of excitons to demonstrate the influence of initial population densities in the QDs on SF generation. As a result, the threshold temperature under the resonant excitation of excitons was higher than that under the two-photon excitation of biexcitons. This indicates that the high density of excited dots facilitates the rapid establishment of coherence among the dots, overcoming disadvantages of incomplete population inversion and formation process of biexcitons. We performed a theoretical calculation of the time profiles of the biexcitonic emission based on semiconductor luminescence equations. The experimentally obtained temperature dependence of the time profiles was qualitatively reproduced by calculating their dependence on the dephasing rate. In addition, we estimated the temperature dependence of the phase relaxation time of the biexcitons in the CuCl QDs by analyzing the temperature dependence of SF.

Partial tipping in bistable ecological systems under periodic environmental variability.

Periodic environmental variability is a common source affecting ecosystems and regulating their dynamics. This paper investigates the effects of periodic variation in species growth rate on the population dynamics of three bistable ecological systems. The first is a one-dimensional insect population model with coexisting outbreak and refuge equilibrium states, the second one describes two-species predator-prey interactions with extinction and coexistence states, and the third one is a three-species food chain model where chaotic and limit cycle states may coexist. We demonstrate with numerical simulations that a periodic variation in species growth rate may cause switching between two coexisting attractors without crossing any bifurcation point. Such a switchover occurs only for a specific initial population density close to the basin boundary, leading to partial tipping if the frozen system is non-chaotic. Partial tipping may also occur for some initial points far from the basin boundary if the frozen system is chaotic. Interestingly, the probability of tipping shows a frequency response with a maximum for a specific frequency of periodic forcing, as noticed for equilibrium and non-equilibrium limit cycle systems. The findings suggest that unexpected outbreaks or abrupt declines in population density may occur due to time-dependent variations in species growth parameters. Depending on the selective frequency of the periodic environmental variation, this may lead to species extinction or help the species to survive.

Recovering initial population density of fractional pseudo-parabolic problem associated with a nonlinear reaction

Recovering initial population density of fractional pseudo-parabolic problem associated with a nonlinear reaction

Counting nematodes made easy: leveraging AI-powered automation for enhanced efficiency and precision.

Counting nematodes is a labor-intensive and time-consuming task, yet it is a pivotal step in various quantitative nematological studies; preparation of initial population densities and final population densities in pot, micro-plot and field trials for different objectives related to management including sampling and location of nematode infestation foci. Nematologists have long battled with the complexities of nematode counting, leading to several research initiatives aimed at automating this process. However, these research endeavors have primarily focused on identifying single-class objects within individual images. To enhance the practicality of this technology, there's a pressing need for an algorithm that cannot only detect but also classify multiple classes of objects concurrently. This study endeavors to tackle this challenge by developing a user-friendly Graphical User Interface (GUI) that comprises multiple deep learning algorithms, allowing simultaneous recognition and categorization of nematode eggs and second stage juveniles of Meloidogyne spp. In total of 650 images for eggs and 1339 images for juveniles were generated using two distinct imaging systems, resulting in 8655 eggs and 4742 Meloidogyne juveniles annotated using bounding box and segmentation, respectively. The deep-learning models were developed by leveraging the Convolutional Neural Networks (CNNs) machine learning architecture known as YOLOv8x. Our results showed that the models correctly identified eggs as eggs and Meloidogyne juveniles as Meloidogyne juveniles in 94% and 93% of instances, respectively. The model demonstrated higher than 0.70 coefficient correlation between model predictions and observations on unseen images. Our study has showcased the potential utility of these models in practical applications for the future. The GUI is made freely available to the public through the author's GitHub repository (https://github.com/bresilla/nematode_counting). While this study currently focuses on one genus, there are plans to expand the GUI's capabilities to include other economically significant genera of plant parasitic nematodes. Achieving these objectives, including enhancing the models' accuracy on different imaging systems, may necessitate collaboration among multiple nematology teams and laboratories, rather than being the work of a single entity. With the increasing interest among nematologists in harnessing machine learning, the authors are confident in the potential development of a universal automated nematode counting system accessible to all. This paper aims to serve as a framework and catalyst for initiating global collaboration toward this important goal.

Recognizing urban shrinkage and growth patterns from a global perspective

The incongruous patterns of urban growth often give rise to a myriad of issues, notably urban sprawl and urban shrinkage. These challenges frequently coexist and interact, presenting formidable obstacles to achieving sustainable city development. Therefore, investigations that endeavor to scrutinize both urban expansion and shrinkage in concert from a comprehensive perspective are essential. Present works of defining this trajectory are still vague, in which there is no clear clarification, and the relationship with socioeconomic also tends to be neglected. Thus, we proposed a new framework utilizing characteristic changes over 30 years in population and density to conduct a synthesis of urban growth patterns in 3911 cities worldwide along with their driving factors. We found that the development stage played a crucial role in urban growth pattern. Specifically, the densification cities were mostly found in the early stages of industrialization and urbanization. However, in accelerated industrialization and fast-developing regions, sprawl cities progressively gained dominance. Most cities followed the sprawl pattern and more shrinkage cities began to emerge in regions which in post-industrialization developed at high stages. Factors including industrialization level, urbanization rate, initial population density, terrain, and cultivated land conditions all exerted notable influences revolving around the urban growth process. Our study aims to help gain an overall sense of the global urbanization process as well as guide decision-makers to search for tailor-made management policies and urban planning for cities at various development stages. The patterns of expansion and shrinkage could offer support for a more comprehensive assessment of SDG indicators 11.3.1 and thus inform policies for urban sustainable development.

Scalable Learning for Spatiotemporal Mean Field Games Using Physics-Informed Neural Operator

This paper proposes a scalable learning framework to solve a system of coupled forward–backward partial differential equations (PDEs) arising from mean field games (MFGs). The MFG system incorporates a forward PDE to model the propagation of population dynamics and a backward PDE for a representative agent’s optimal control. Existing work mainly focus on solving the mean field game equilibrium (MFE) of the MFG system when given fixed boundary conditions, including the initial population state and terminal cost. To obtain MFE efficiently, particularly when the initial population density and terminal cost vary, we utilize a physics-informed neural operator (PINO) to tackle the forward–backward PDEs. A learning algorithm is devised and its performance is evaluated on one application domain, which is the autonomous driving velocity control. Numerical experiments show that our method can obtain the MFE accurately when given different initial distributions of vehicles. The PINO exhibits both memory efficiency and generalization capabilities compared to physics-informed neural networks (PINNs).

Factors affecting fruit damage caused by Thrips hawaiiensis (Morgan) (Thysanoptera: Thripidae) in citrus lemon groves in Turkey

The Hawaiian flower thrips, Thrips hawaiiensis (Morgan) (Thysanoptera: Thripidae) is an economically important invasive species in citrus grown in the eastern Mediterranean region of Turkey. The diverse impacts of temperature on arthropods are well documented. This study was conducted with the aim of determining the influence of day-degree on insect population dynamics and crop damage levels in Mersin Province, Turkey during 2018–2019. In 2018, the first damage caused by T. hawaiiensis was observed at 300 degree-days (DD), while in 2019, it occurred at 800 DD. The damage percentage was recorded as 28% in the lemon grove, where the population of second instar larvae briefly reached a high level (approximately 2 individuals per fruit). During 2019, the average temperature remained relatively low, and the initial population density of thrips was below the 33-day development threshold (10.4 °C) from January to April. This pattern was observed even during the mild spring season. Additionally, in both sampling locations, the high adult densities, mainly adult females, led to the shedding of a limited number of flowers that had formed in June.

A molecular toolkit of cross-feeding strains for engineering synthetic yeast communities

Engineered microbial consortia often have enhanced system performance and robustness compared with single-strain biomanufacturing production platforms. However, few tools are available for generating co-cultures of the model and key industrial host Saccharomyces cerevisiae. Here we engineer auxotrophic and overexpression yeast strains that can be used to create co-cultures through exchange of essential metabolites. Using these strains as modules, we engineered two- and three-member consortia using different cross-feeding architectures. Through a combination of ensemble modelling and experimentation, we explored how cellular (for example, metabolite production strength) and environmental (for example, initial population ratio, population density and extracellular supplementation) factors govern population dynamics in these systems. We tested the use of the toolkit in a division of labour biomanufacturing case study and show that it enables enhanced and tuneable antioxidant resveratrol production. We expect this toolkit to become a useful resource for a variety of applications in synthetic ecology and biomanufacturing.

Native forest and proximity to humans are stronger drivers of Brazilian cottontail habitat use than invasive European hare

AbstractHuman activities and biological invasions have caused unprecedented biodiversity loss over the past 500 years. Proximity to humans drives the spatial distribution of species toward less disturbed habitats. Invasive species can competitively exclude native species, but species may coexist due to different habitat preferences. Here, we investigated how proximity to farms and the presence of the non‐native European hare (Lepus europaeus) influence the habitat use by the Brazilian cottontail (Sylvilagus minensis) in southeastern Brazil. We found that the probability of cottontail site use increased with native forest cover and decreased with farmhouse proximity, ranging from 0.05 (SE = 0.02) at sites close to farmhouses (≅900 m) with no native forest to 0.70 (SE = 0.15) at sites far from farmhouses (≅2500 m) dominated by native forest. Higher risk of harassment and predation by free‐roaming dogs and cats may explain the negative effect of farmhouse proximity on cottontail habitat use. We found little evidence for competitive exclusion by the European hare. Instead, our results suggest that the two species spatially segregate due to different habitat preferences. While the European hare more likely uses farmland in its native and non‐native range, our results suggest that the Brazilian cottontail is a forest dweller. Although we found only weak evidence of competitive exclusion, we advise caution because invasive species may delay the onset of detrimental effects due to initial low population densities in newly invaded areas as is the case of the European hare in southeastern Brazil.Abstract in Portuguese is available with online material.

Adhesion and volume filling in one-dimensional population dynamics under Dirichlet boundary condition

We generalize the one-dimensional population model of Anguige & Schmeiser [1] reflecting the cell-to-cell adhesion and volume filling and classify the resulting equation into the six types. Among these types, we fix one that yields a class of advection-diffusion equations of forward-backward-forward type and prove the existence of infinitely many global-in-time weak solutions to the initial-Dirichlet boundary value problem when the maximum value of an initial population density exceeds a certain threshold. Such solutions are extracted from the method of convex integration by Müller & Šverák [12]; they exhibit fine-scale density mixtures over a finite time interval, then become smooth and identical, and decay exponentially and uniformly to zero as time approaches infinity. TE check: Please check the reference citation in abstract.

Social housing and the spread of population: Evidence from twentieth century Ireland

How does housing policy influence the long-run distribution of population? We examine the impact on long-term population dynamics of the world’s first large-scale rural public housing scheme, specifically the case of Ireland’s Labourers Acts. We link detailed data on the location of over 45,000 heavily subsidized cottages for agricultural laborers built 1883–1915 in over 200 districts to decennial Censuses between 1841 and 2002. We examine how the density of this social housing affected subsequent population change and find significant persistence in the effect of this treatment on the population. These findings are from specifications that include other factors plausibly related to future population growth, including initial housing stock, land values and population density, as well as distance to urban centres. A causal interpretation is supported by an assessment of pre-trends, by no effect of cottages authorized but not built and by an IV approach that exploits a 1906 limit on legal costs. We also highlight the role of agglomeration in amplifying the impact of the initial investment. Mediation analysis suggests that schooling was a key factor, with districts receiving more cottages less likely to lose primary schools, thus further influencing population growth.

Population dynamics and damage threshold of Pratylenchus n. sp. and Meloidogyne javanica on finger millet

Summary Finger millet (Eleusine coracana) is a staple crop for subsistence farmers and is primarily cultivated in arid and semi-arid regions. Nevertheless, there are limited data available on the occurrence of plant-parasitic nematodes that specifically target finger millet, and the damage arising from such infections. In this study, we investigated the population dynamics, damage threshold and tolerance of the lesion nematode, Pratylenchus n. sp., and the root-knot nematode, Meloidogyne javanica, on finger millet ‘P-224’. We used 11 initial population densities (Pi) of second-stage juveniles (J2): 0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32 and 64 J2 (g soil)−1 for M. javanica and the same densities of mixed life-stages for Pratylenchus n. sp. The logistic growth model, Seinhorst yield loss and population dynamic models were fitted to the shoot height, plant biomass and final nematode population density. Based on the population dynamics model parameters, maximum multiplication rates and maximum population densities for each nematode species were estimated. The maximum multiplication rates (a) were 32.39 and 17.46, whilst the maximum population densities (M) were 18.83 nematodes (g soil)−1 and 19.78 J2 (g soil)−1 for Pratylenchus n. sp. and M. javanica respectively. The maximum height reached (C) was negatively affected by increasing Pi for both nematode genera, while the rate of growth (B) and the time to reach was not affected based on the logistic model. A tolerance limit (T) of 1.70 nematodes (g soil)−1 and 0.65 J2 (g soil)−1; relative minimum grain yield (m) of 0.23 and 0.40 for Pratylenchus n. sp. and M. javanica was found, respectively. The results indicate that ‘P-224’ is a good host for both Pratylenchus n. sp. and M. javanica, which significantly reduce yield. These findings can be used as a base to develop effective nematode management strategies for finger millet.

Host-parasite Interactions between Solanum aethiopicum, Meloidogyne incognita, and Fusarium oxysporum f.sp. melongenae as Portrayed by Disease Traits and Crop Yield

Solanum aethiopicum L. cultivation is highly constrained by wilt disease induced by Fusarium oxysporum f.sp melongenae and Meloidogyne incognita. The effects of initial population densities of these pathogens on the crop were investigated to enhance knowledge of the host-parasite interactions. The 4 x 4 factorial set of treatments were laid out in the field using the randomized complete block design with three replications. Data were collected on plant vigour, vascular discoloration, fruit weight, shoot weight, root-gall index, final nematode population, disease incidence, and disease severity. The different initial population densities of Fusarium and/or Meloidogyne spp. had detrimental effects on the crop compared to the Control. The main effects of the pathogens on the crop/wilt showed the existence of cross-over interactions for all the disease parameters. The effects of the pathogens on yield (fruit weight and shoot weight) were partially directly proportional to population densities even though the effects were significantly different (P≤0.05) compared to the Control. All the disease parameters were positively correlated. Each of the pathogens was capable of causing severe damage to the crop in either single or concomitant infection.

A real time PCR assay to detect and quantify root-knot nematodes from soil extracts.

Root-knot nematodes cause forking and stubbing of the growing carrot root tip, decreasing market value and reducing yield by up to 45%. Since crop damage by these nematodes depends on their initial population densities at planting, pre-plant detection of potentially low nematode numbers is critical for predicting future yield loss. The aim of this study was to overcome some of the drawbacks of the labor and time-intensive process of root-knot nematode identification and quantification by developing and field testing a real time PCR (qPCR) assay. Primers were designed targeting the root-knot nematode Meloidogyne incognita species complex, which includes M. incognita as well as the closely related Meloidogyne javanica and Meloidogyne arenaria. The qPCR assay successfully detected each species and showed little amplification for non-target nematode groups except for the sister group Meloidogyne enterolobii, which is not known to occur in California. Predicted nematode densities related well with microscopic counts of nematodes from prepared solutions, as well as from solutions extracted from field soil. In a greenhouse experiment, the qPCR assay distinguished between low, medium and high levels of M. incognita infection and qPCR predicted densities at planting were negatively related in linear models with final carrot fresh weight, length and diameter. These results suggest that qPCR assays could be a valuable diagnostic tool to predict nematode infections and prevent crop losses.

Impact of cover crops on population density of the root-knot nematode Meloidogyne chitwoodi

Summary Management strategies applied to reduce Meloidogyne chitwoodi populations below economic damage threshold depend strongly on measures taken during the intercrop period. Therefore, this study evaluated the reproductive potentials of M. chitwoodi on different cultivars of cover crops. Twenty-two different cultivars were evaluated against M. chitwoodi at low and high initial inoculum density in a pot experiment under controlled conditions. Fallow was used as control. Based on the reproductive factor, the cover crops were classified under five different categories: Non-host, Poor host, Maintenance host, Good host and Excellent host. In this study, at both low (10 second-stage juveniles (J2) 100 cm−3 soil) and high (100 J2 100 cm−3 soil) initial inoculum density of M. chitwoodi, fodder radish ‘Maximus’, ‘Contra’, ‘Dacapo’ and ‘Defender’, Italian ryegrass ‘Meroa’, rye ‘Matador’ and bird’s foot trefoil ‘Barguay’, ‘Franco’ and ‘Lotar’ were considered poor hosts reducing the M. chitwoodi population in the pot test based on reproductive factor (RF) values. Field experiments were carried out that confirmed most of our results in the pot experiments. However, the field experiments showed that the rotations in which the cover crops are implemented are influenced by weather conditions, previous crop grown, their growing period and initial population densities. Based on our findings, selected non- and poor-host cover crops could be recommended for integrated management of M. chitwoodi.

Dynamic characteristics of a hyperbolic reaction–diffusion predator–prey system with self‐diffusion and nonidentical inertia

Hyperbolic reaction–diffusion (HRD) systems have emerged as a better descriptor of the macroscopic spatial interaction models used for studying pattern formation in chemical and biological systems. In contrast to the parabolic reaction–diffusion (PRD) models, the spatial disturbances in an HRD system travel through space with finite velocity. This paper considers the simplest two‐species HRD model with different inertia based on the telegraph equation. The underlying reaction terms are considered as a predator–prey interaction with type III response function and prey refuge. We prescribe the analytical conditions for the existence of diffusion‐driven instabilities of the considered system. Simulation results further verify the theoretical results. A connection between the refuge parameter and inertial time is discussed in generating different spatiotemporal patterns. Extension of the two‐species PRD system to HRD system with diagonal diffusion matrix causes a diffusion‐driven wave instability, which is never possible for its parabolic counterpart. Furthermore, the patterns under pure wave instability are dependent on the initial population density.

Rhizoctonia potato disease in production conditions in the forest-steppe of Western Siberia

The authors carried out a scientific study from 1990 to 2022 on 20 varieties of potatoes to study the pathogenesis of Rhizoctonia in crop production conditions and substantiate the methods of the system of protection against the disease. The fungus R. Solani persists annually in the soil and on seed tubers in the form of mycelium and sclerotia. It was found that more than 60% of the grounds of potato agroecosystems have the content of the causative agent of Rhizoctonia is many times higher than the established ETH (Economic threshold of harmfulness). Furthermore, monitoring of the phytosanitary state of potato seed material showed that, on average, about 60% of the tubers are inhabited by the causative agent of Rhizoctonia, including about 30% of the sclerotial form, which is six times higher than the phytosanitary regulations. Thus, in the region’s conditions, a double mechanism of phytopathogen transmission is provided annually. The causative agent of Rhizoctonia infects potato sprouts, subsequently causing their complete death (on average 12%) and shootouts, reducing the density of productive plants in crop plantings. At subsequent stages of growth and development of potatoes, significant expansion of the disease on the stems was noted (on average 31.4%), and stolons were damaged and died (9.3 and 5.5%, respectively), which disrupted the processes of stolon and tuberization. In the region’s conditions, Rhizoctonia occurs in the form of epiphytotic with a prevalence of 88% or more. Therefore, the potato protection strategy against Rhizoctonia should be based on methods that reduce the initial population density of the R. Solani fungus in the soils of agroecosystems and on seed tubers. Essential elements of potato cultivation technology are cropping rotation with a saturation of no more than 30% (biological efficiency - 43.2–79.5%); phytosanitary precursor, including green manure pairs (biological efficiency - 49.0–75.9%); mandatory etching with chemical preparations (biological efficiency - 54.9–98.8%) or natural origin. Using entomopathogenic fungi Metarhizium robertsii and Baeuveria bassiana can be a promising direction in reducing Rhizoctonia. Dressing seed tubers with conidia of entomopathogenic fungi suppressed the development of the disease in potato plantings by 1.8–3.7%, providing an increase in yield by 12.1–19.2%. The study of the influence of Metarhizium robertsii and Baeuveria bassiana on the pathogenesis of Rhizoctonia will be continued.

Multimodal distribution of transient time of predator extinction in a three-species food chain.

The transient dynamics capture the time history in the behavior of a system before reaching an attractor. This paper deals with the statistics of transient dynamics in a classic tri-trophic food chain with bistability. The species of the food chain model either coexist or undergo a partial extinction with predator death after a transient time depending upon the initial population density. The distribution of transient time to predator extinction shows interesting patterns of inhomogeneity and anisotropy in the basin of the predator-free state. More precisely, the distribution shows a multimodal character when the initial points are located near a basin boundary and a unimodal character when chosen from a location far away from the boundary. The distribution is also anisotropic because the number of modes depends on the direction of the local of initial points. We define two new metrics, viz., homogeneity index and local isotropic index, to characterize the distinctive features of the distribution. We explain the origin of such multimodal distributions and try to present their ecological implications.

Unmanned Aerial Vehicle (UAV) for Detection and Prediction of Damage Caused by Potato Cyst Nematode G. pallida on Selected Potato Cultivars

High population densities of the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis cause substantial yield losses to potato production (Solanum tuberosum) due to the delay caused to tuber formation by the retardation of plant growth. It requires meticulous estimation of the population densities by using soil sampling and applying the right combination of nematode management to deal with the PCN problem. This study aims to assess the use of an unmanned vehicle (UAV) in detecting and estimating the effect of ranges of densities of a PCN, G. pallida, on four cultivated potato cultivars with resistance to PCN in a naturally infested potato field in The Netherlands. First, the initial population density (Pi) of G. pallida was estimated by using an intensive sampling method of collecting about 1.5 kg of soil per m2 from the center of each 3 × 5 m plot. At harvest, the fresh tuber yield of the potato cultivars (Avarna, Fontane, Sarion, and Serresta) were assessed. The Seinhorst yield loss model was used to investigate the relationship between Pi and fresh tuber yield. Secondly, the spatial data of UAV with optical and thermal sensors were analyzed to find any relationship between Pi and UAV indices. By using the classical yield loss model, all four cultivars were found to be affected by Pi with a relative minimum fresh tuber yield m, which ranged from 0.26 to 0.40. The maximum fresh tuber yield varied from 49.48 to 80.36 tons (ha)−1. The density at which the fresh tuber yield started to deteriorate was in the range of 0.62–2.16 eggs (g dry soil)−1. A regression was observed between Pi, and all UAV indices in a similar pattern to that of the fresh tuber yield by using the Seinhorst yield loss model, except for the cultivar Avarna for the two UAV indices (NDRE and NDVI). Unlike the tolerance limit, the relative minimum values of the UAV indices—except the chlorophyll index—differ when compared among each other and when compared with that of the fresh tuber yield within the same cultivar. This indicates that all indices can be useful for detection and decision making for statutory purposes but not for estimating damage (except the chlorophyll index).