Spatio-temporal Population Dynamics Research Articles

SPATIAL ORGANIZATION OF BIRD POPULATION OF THE URUP AND ITURUP ISLANDS (KURIL ISLANDS)

The ecological and geographical differentiation of the bird population at 18 sites of the Urup and Iturup islands was analyzed. The method of route accounting was applied. A total of 109 species were recorded, 62 of them on both islands. The coefficient of faunal commonality between the terrestrial habitats of the islands is 72%, and between the coastal-marine - 71%. The coefficient of similarity of the bird population between the land habitats of the islands is 36%, and between the coastal-marine - 29%. The values of bird population density on the islands are close both between terrestrial (610-757 ind./km2) and coastal-marine (536-607 ind./km2) habitats. The high population density is everywhere due to the abundance of numerically predominant species of the Far Eastern island and the Chinese fauna types. The total population of species of these faunas accounts for more than 50% of the population in terrestrial (282-469 ind./km2) and coastal marine (172-333 ind./km2) habitats. The spatio-temporal dynamics of the bird population is characteristic.

The Poultry Red Mite, Dermanyssus gallinae, travels far but not frequently, and takes up permanent residence on farms

Management of Dermanyssus gallinae, a cosmopolitan hematophagous mite responsible for damage in layer poultry farming, is hampered by a lack of knowledge of its spatio-temporal population dynamics. Previous studies have shown that the circulation of this pest between farms is of strictly anthropogenic origin, that a mitochondrial haplogroup has been expanding on European farms since the beginning of the 21st century and that its local population growth may be particularly rapid. To refine our understanding of how D. gallinae spreads within and among farms, we characterized the genetic structure of mite populations at different spatial scales and sought to identify the main factors interrupting gene flow between poultry houses and between mitochondrial haplogroups. To this end, we selected and validated the first set of nuclear microsatellite markers for D. gallinae and sequenced a region of the CO1-encoding mitochondrial gene in a subsample of microsatellite-genotyped mites. We also tested certain conditions required for effective contamination of a poultry house through field experimentation, and conducted a survey of practices during poultry transfers. Our results confirm the role of poultry transport in the dissemination of mite populations, but the frequency of effective contamination after the introduction of contaminated material into poultry houses seems lower than expected. The high persistence of mites on farms, even during periods when poultry houses are empty and cleaned, and the very large number of nodes in the logistic network (large number of companies supplying pullets or transporting animals) undoubtedly explain the very high prevalence on farms. Substantial genetic diversity was measured in farm populations, probably as a result of the mite's known haplodiploid mode of sexual reproduction, coupled with the dense logistic network. The possibility of the occasional occurrence of asexual reproduction in this sexually reproducing mite was also revealed in our analyses, which could explain the extreme aggressiveness of its demographic dynamics under certain conditions.

Drivers of spatio-temporal population dynamics of game species in a mountain landscape

Since the end of the nineteenth century, socio-economic changes have greatly altered the Central European landscape and the structural and functional quality of habitats. Urban sprawl areas have appeared, a reduction of multiple forest uses has resulted in the densification of forests and agricultural land use has changed fundamentally through specialisation and intensification. Many of these changes affect biodiversity. To determine the important drivers of spatio-temporal dynamics of the population of 28 game species, we first considered a total of 130 potential explanatory variables. Second, we aggregated the main drivers of single-species models for habitat guilds. Third, we evaluated the results to aid in the development and implementation of mitigation measures for different ecoregions. We used harvest data as a surrogate for population density from 1875 to 2014 in South Tyrol, Italy. In generalised linear models, we used environmental characteristics such as climate, landscape diversity and structures, land cover, hunting, wildlife diseases, competition and predation, land-use type, and intensity (including pesticide use) as explanatory variables to predict the spatio-temporal dynamics of game species. The important drivers are land use and management changes (intensification in the agriculturally favourable areas, extensification or abandonment in the unfavourable areas) as well as associated changes in the landscape features, diversity and structure, and hunting management. Climatic variables, interspecific competition and diseases only play a subordinate role. The dynamics of the habitat guilds and their drivers provide concrete indications for measures to maintain or improve the habitat quality for the investigated species. Particularly important are transfer payments to ensure extensive agricultural use, increasingly through the takeover of personnel costs, but also for the installation of an independent body that monitors and evaluates the effectiveness of the measures.

Spatio-temporal Distribution and Population Dynamics of the Red Mullet Mullus barbatus Linnaeus, 1758 from the South-east Black Sea

A total of 2930 Mullus barbatus individuals collected from the Southeastern Black Sea coast between March 2017 and April 2018 were investigated regarding growth, mortality rates and the distribution determined by depth and season. M. barbatus is abundant along of 30-45 m depth in winter. Total length-weight relationship was determined as W=0.005L3.2344. Von Bertalanffy growth parameters for all individuals were calculated as L∞=28.19 cm, K=0.16 years-1, t0=-0.144 years. The maximum age was 5 years. The total length at 50% maturity was estimated as 11.63 cm in males and 11.68 cm in females. Exponential coefficients of natural mortality, total mortality, and fishing mortality rate of red mullet are estimated as 0.33 year-1, 1.001 year-1 and 0.67 year-1, respectively. The exploitation rate of population was calculated as 0.66 year-1. The fact that exploitation rate is above 0.5 may reflect a high fishing pressure on stock.

Emergence of task-related spatiotemporal population dynamics in transplanted neurons

Loss of nervous system tissue after severe brain injury is a main determinant of poor functional recovery. Cell transplantation is a promising method to restore lost tissue and function, yet it remains unclear if transplanted neurons can demonstrate the population level dynamics important for movement control. Here we present a comprehensive approach for long-term single neuron monitoring and manipulation of transplanted embryonic cortical neurons after cortical injury in adult male mice performing a prehension task. The observed patterns of population activity in the transplanted network strongly resembled that of healthy networks. Specifically, the task-related spatiotemporal activity patterns of transplanted neurons could be represented by latent factors that evolve within a low dimensional manifold. We also demonstrate reliable modulation of the transplanted networks using minimally invasive epidural stimulation. Our approach may allow greater insight into how restoration of cell-type specific network dynamics in vivo can restore motor function.

A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study

Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine-scale spatial heterogeneities based on theories of fish population dynamics and spatiotemporal statistics. Specifically, we developed a size-based state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS) to refine the representation of spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice. The model fits to spatial survey and fishery-dependent catch data. It implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers. We quantify, for the first time, spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance. The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS. Few spatial assessments have been used as the basis for management advice and we consider this study as a step towards the integration of spatial dynamics in stock assessment.

How environmental drivers of spatial synchrony interact

Spatial synchrony, the tendency for populations across space to show correlated fluctuations, is a fundamental feature of population dynamics, linked to central topics of ecology such as population cycling, extinction risk, and ecosystem stability. A common mechanism of spatial synchrony is the Moran effect, whereby spatially synchronized environmental signals drive population dynamics and hence induce population synchrony. After reviewing recent progress in understanding Moran effects, we here elaborate a general theory of how Moran effects of different environmental drivers acting on the same populations can interact, either synergistically or destructively, to produce either substantially more or markedly less population synchrony than would otherwise occur. We provide intuition for how this newly recognized mechanism works through theoretical case studies and application of our theory to California populations of giant kelp. We argue that Moran interactions should be common. Our theory and analysis explain an important new aspect of a fundamental feature of spatiotemporal population dynamics.

Prevalence of major pests and diseases in wild and cultivated coffee in Ethiopia

The study of pests and diseases on crops and crop relatives in the wild is valuable from both a theoretical and an applied point of view. Few studies have addressed multiple pests and diseases in such ecosystems. Our objectives were to (1) compare the prevalence of multiple pests and diseases on coffee in forests and more managed landscapes and (2) assess how spatial, environmental, host density and management factors affect the incidence and severity of coffee pests and diseases across forests.To achieve these objectives we studied different pests, diseases and one hyperparasite on wild and semi-wild coffee from 84 plots of 20 × 20 m across a forested landscape in southwest Ethiopia and compared the results to previous studies of more intensively managed adjacent landscapes.The prevalence of all surveyed coffee leaf pests and diseases was high (>71% of investigated plots) and very similar to the levels in more intensively managed landscapes reported in the literature. The incidence rates of all pests, diseases and the hyperparasite showed a high variation among the plots, and correlation with each other in some cases. However, this variation was weakly related to the measured environmental and management variables, but coffee pests and diseases were often positively related to high coffee density.One possible explanation for the similar prevalence is that, although the landscapes are different, the local environmental conditions have much in common since coffee is also grown under indigenous shade trees in more intensively managed landscapes. However, the variability in pest and disease levels among sites was large and it is difficult to predict where they attain high levels. There is a need of detailed investigations on drivers of spatio-temporal population dynamics of these species, including their natural enemies, to be able to provide advice for development of sustainable coffee disease management.

The spatio-temporal dynamics of urban growth and population in metropolitan regions of Iran

The spatial configuration and the dynamics of urban physical growth are important topics of analysis in contemporary urban studies. This paper examined urban land expansion and population distribution evolution and their coupling in seven major Iranian metropolitan regions (pop>1M), and it contributes to understanding diverse urban physical growth patterns in the vast Global South. The analysis is based on an innovative approach of integrating two growth indices: a) ULE (urban land expansion) and b) PPE (population pattern evolution), applied to the demographic data and satellite imageries from 1990 to 2020. The findings show that population decentralization and land consumption have been significant over the previous three decades, although spatial growth patterns varied significantly across the chosen metropolitan regions. Furthermore, Iran's urban physical growth pattern goes from monocentric to polycentric, which is largely associated with the parent city's dominance. In fact, urban physical growth follows a concentrated-decentralization trend, with the latter spreading quicker than the former. Despite expectations, the infill growth has not essentially exposed to higher population density. This study's findings can help readers understand the urbanisation pattern and occurrence in Iran, and may assist policy-makers in understanding the physical impact of conflicting national executive policies, such as mass housing supply projects in urban edges versus inner-urban regeneration projects. In addition, it gives a major knowledge of the evolution of urban physical growth patterns, intra-city interactions, and growth drivers.

Clustering Synchronization in a Model of the 2D Spatio-Temporal Dynamics of an Age-Structured Population with Long-Range Interactions

The inhomogeneous population distribution appears as various population densities or different types of dynamics in distant sites of the extended habitat and may arise due to, for example, the resettlement features, the internal population structure, and the population dynamics synchronization mechanisms between adjacent subpopulations. In this paper, we propose the model of the spatio-temporal dynamics of two-age-structured populations coupled by migration (metapopulation) with long-range displacement. We study mechanisms leading to inhomogeneous spatial distribution as a type of cluster synchronization of population dynamics. To study the spatial patterns and synchronization, we use the method of constructing spatio-temporal profiles and spatial return maps. We found that patterns with spots or stripes are typical spatial structures with synchronous dynamics. In most cases, the spatio-temporal dynamics are mixed with randomly located single populations with strong burst (outbreak) of population size (solitary states). As the coupling parameters decrease, the number of solitary states grows, and they increasingly synchronize and form the clusters of solitary states. As a result, there are the several clusters with different dynamics. The appearance of these spatial patterns most likely occurs due to the multistability of the local age-structured population, leading to the spatio-temporal multistability.

Spatiotemporal dynamics of forest insect populations under climate change.

Effects of climate on forest insect populations are complex, often involving drivers that are opposing, nonlinear, and nonadditive. Overall, climate change is driving an increase in outbreaks and range shifts. Links between climate and forest insect dynamics are becoming clearer; however, the underlying mechanisms remain less clear. Climate alters forest insect population dynamics directly through life history, physiology, and voltinism, and indirectly through effects on host trees and natural enemies. Climatic effects on bark beetles, wood-boring insects, and sap-suckers are often indirect, through effects on host-tree susceptibility, whereas climatic effects on defoliators are comparatively more direct. We recommend process-based approaches to global distribution mapping and population models to identify theunderlying mechanisms and enable effective management of forest insects.

Application of interaction models in predicting the simultaneous growth of Staphylococcus aureus and different concentrations of background microbiota in Chinese-style braised beef

This study aimed to investigate the growth kinetics of S. aureus and different concentrations of background microbiota in Chinese-style braised beef (CBB). A one-step analysis method was applied to develop predictive model to describe the simultaneous growth and interaction of S. aureus with different concentrations of background microbiota in CBB. The results show that a one-step method successfully models the growth of S. aureus and background microbiota in CBB and the competing interactions between the two. In sterile CBB, the estimated minimum growth temperatures (Tmin,S) and the maximum growth concentrations (Ymax,S) were 8.76 °C and 9.58 log CFU/g for S. aureus. Under competition, the growth of background microbiota was not affected by S. aureus, the estimated Tmin,B and Ymax,B was 4.46 °C and 9.94 log CFU/g. The background microbiota in CBB did not affect the growth rate of S. aureus (α1 = 1.04), but had an inhibitory effect on the number of S. aureus (α2 = 0.69) at the later growth stage. The Root Mean Square Error (RMSE) of the modeling data was 0.34 log CFU/g, with 85.5% of the residual errors within ±0.5 log CFU/g of experimental observations. The one-step analysis and dynamic temperatures (8 °C–32 °C) verification indicated that the RMSE of prediction was <0.5 log CFU/g for both S. aureus and background microbiota. This study demonstrates that microbial interaction models are a useful and promising tool for predicting and evaluating the spatiotemporal population dynamics of S. aureus and background microbiota in CBB products.

Spatiotemporal population dynamics of aflatoxigenic Aspergillus species and their ecological requirements across groundnut-growing areas of Ethiopia

Spatiotemporal population dynamics of aflatoxigenic Aspergillus species and their ecological requirements across groundnut-growing areas of Ethiopia

Of clockwork and catastrophes: advances in spatiotemporal dynamics of forest Lepidoptera.

We applied a systematic global literature survey from the last 2.5 years on spatiotemporal population dynamics - broadly defined - of Lepidopteran forest pests. Articles were summarized according to domain-specific (planetary ecology - remote sensing,evolutionary ecology - genetics and genomics,and theoretical ecology - modeling) contributions to contemporary investigation of the above theme. 'Model systems' dominating our literature survey were native Choristoneura fumiferana and invasive Lymantria dispar. These systems represent opposing ends of a more general equilibrium-disequilibrium gradient, with implications for less-studied taxa. Thedynamics of Lepidopteran systems defy simple modeling approaches. Technologies and insights emerging from 'slower' science domains are informing more complex theory, including predictions of spread, impacts, or both posed by more recent invasions and the disrupting effects of climate change.

Spatiotemporal dynamics of forest geometrid outbreaks.

We highlight recent developments and avenues for advancement, which can improve insight into the causes of changes in the spatiotemporal dynamics of forest Geometridea moth species (hereafter 'geometrids'). Some forest geometrids possess fundamental biological traits, which make them particularly liable to outbreak range expansions and host shifts mitigated by climate change. Indeed, recently observed changes in geometrid spatiotemporal dynamics represent both new research opportunities and challenges for empirically testing drivers of intra- and interspecific spatial synchrony, including the role of trophic interactions and biological traits (e.g. dispersal ability). We advocate that the emerging field of near-term ecological forecasting holds promise for studies of the spatiotemporal dynamics of forest geometrids and could be tailored to give both accurate predictions at management-relevant timescales and new insights into the mechanisms that underlie spatiotemporal population dynamics.

Individual-Based Modeling of Spatial Dynamics of Chemotactic Microbial Populations.

One important direction of synthetic biology is to establish desired spatial structures from microbial populations. Underlying this structural development process are different driving factors, among which bacterial motility and chemotaxis serve as a major force. Here, we present an individual-based, biophysical computational framework for mechanistic and multiscale simulation of the spatiotemporal dynamics of motile and chemotactic microbial populations. The framework integrates cellular movement with spatial population growth, mechanical and chemical cellular interactions, and intracellular molecular kinetics. It is validated by a statistical comparison of single-cell chemotaxis simulations with reported experiments. The framework successfully captures colony range expansion of growing isogenic populations and also reveals chemotaxis-modulated, spatial patterns of a two-species amensal community. Partial differential equation-based models subsequently validate these simulation findings. This study provides a versatile computational tool to uncover the fundamentals of microbial spatial ecology as well as to facilitate the design of synthetic consortia for desired spatial patterns.

Pest population dynamics are related to a continental overwintering gradient

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests.

Spatiotemporal dynamics of global population and heat exposure (2020–2100): based on improved SSP-consistent population projections

To address future environmental change and consequent social vulnerability, a better understanding of future population (FPOP) dynamics is critical. In this regard, notable progress has been made in producing FPOP projections that are consistent with the Shared Socioeconomic Pathways (SSPs) at low resolutions for the globe and high resolutions for specific regions. Building on existing endeavors, here we contribute a new set of 1 km SSP-consistent global population projections (FPOP in short for the dataset) under a machine learning framework. Our approach incorporates a recently available SSP-consistent global built-up land dataset under the Coupled Model Intercomparison Project 6, with the aim to address the misestimation of future built-up land dynamics underlying existing datasets of future global population projections. We show that the overall accuracy of our FPOP outperforms five existing datasets at multiple scales and especially in densely-populated areas (e.g. cities and towns). Followingly, FPOP-based assessments of future global population dynamics suggest a similar trend by population density and a spatial Matthew effect of regional population centralization. Furthermore, FPOP-based estimates of global heat exposure are around 300 billion person-days in 2020 under four SSP-Representative Concentration Pathway (RCPs), which by 2100 could increase to as low as 516 billion person-days under SSP5-RCP4.5 and as high as 1626 billion person-days under SSP3-RCP8.5—with Asia and Africa contributing 64%–68% and 21%–25%, respectively. While our results shed lights on proactive policy interventions for addressing future global heat hazard, FPOP will enable future-oriented assessments of a wide range of environmental hazards, e.g. hurricanes, droughts, and flooding.

Spatiotemporal connectivity dynamics in spatially structured populations.

Connectivity is a fundamental concept linking dispersal to the emergent dynamics and persistence of spatially structured populations. Functional measures of connectivity typically seek to integrate aspects of landscape structure and animal movement to describe ecologically meaningful connectedness at the landscape and population scale. Despite this focus on function, traditional measures of landscape connectivity assume it is a static property of the landscape, hence abstracting out the underlying spatiotemporal population dynamics. Connectivity is, arguably, a dynamic property of landscapes, and is inherently related to the spatial distribution of individuals and populations across the landscape. Static representations of connectivity potentially overlook this variation and therefore adopting a dynamic approach should offer improved insights about connectivity and associated ecological processes. Using a large-scale, long-term time series of occupancy data from a metapopulation of water voles Arvicola amphibius, we tested competing hypotheses about how considering the dynamic nature of connectivity improves the ability of spatially explicit occupancy models to recover population dynamics. Iteratively relaxing standing assumptions of connectivity metrics, these models ranged from spatially and temporally fixed connectivity metrics that are widely applied, to the more flexible, but lesser used model that allowed temporally varying connectivity measures that incorporate spatiotemporally dynamic patch occupancy states. Our results provide empirical evidence that demographic weighting using patch occupancy dynamics and temporal variability in connectivity measures are important for describing metapopulation dynamics. We highlight the implications of commonly held assumption in connectivity modelling and demonstrate how they result in different and highly variable predictions of metapopulation capacity. Thus, we argue that the concept of connectivity and its potential applications would benefit from recognizing inherent spatiotemporal variation in connectivity that is explicitly linked to underlying ecological state variables.

Spatio-temporal demographic dynamics of the human populations from Northwest Patagonia and central Chile during the Pleistocene-Holocene

Our goal is to study the spatio-temporal changes in human demographic density in Northwest Patagonia and central Chile throughout the Late Pleistocene-Holocene using geo-referenced absolute dates. Given the heterogeneous environmental and cultural characteristics of this region, differences in the demographic dynamics across geographic areas are expected. Using 1,284 absolute dates we explored different null and continuous piecewise linear (CPL) models of regional population change. We also estimated density curves along with a local geometric growth rate analysis. The best fit model was a flexible CPL model, showing an initial increase in population density between ca. 15,500–12,500 years BP, a second rise after 6,500 years BP and a third increase after 2,500 years BP, although disparate spatio-temporal changes in the relative density were found. These results were robust when the effect of potential biases was considered –e.g., dates with large errors, marine-reservoir and old-wood effects– and the frequency distribution of absolute dates and sites were estimated. We observed significant spatio-temporal changes in human population density, which might be related to the complex environmental and cultural changes: the megafaunal extinction, the incorporation of marine resources and the acquisition of techniques for cultivating and processing food. The results of this study remark that, compared to other types of data, the use of absolute dates allows paleo-demographic reconstructions at regional geographical scales with higher spatial and temporal resolution.