Population Dynamics of a Seed Feeding Bug, Lygaeus Equestris. 2. Temporal Dynamics

Oikos ◽  
1990 ◽  
Vol 58 (2) ◽  
pp. 210 ◽  
Author(s):  
Birgitta Sillén-Tullberg ◽  
Christer Solbreck ◽  
Birgitta Sillen-Tullberg
Keyword(s):  
Population Dynamics ◽  
Temporal Dynamics ◽  
Lygaeus Equestris

scholarly journals Increasing frequency of low summer precipitation synchronizes dynamics and compromises metapopulation stability in the Glanville fritillary butterfly

2015 ◽  
Vol 282 (1806) ◽  
pp. 20150173 ◽  
Author(s):  
Ayco J. M. Tack ◽  
Tommi Mononen ◽  
Ilkka Hanski
Keyword(s):  
Population Dynamics ◽  
Population Change ◽  
Temporal Dynamics ◽  
Summer Precipitation ◽  
Life History Stage ◽  
General Effect ◽  
Spatial Synchrony ◽  
Glanville Fritillary Butterfly ◽  
Spatio Temporal

Climate change is known to shift species' geographical ranges, phenologies and abundances, but less is known about other population dynamic consequences. Here, we analyse spatio-temporal dynamics of the Glanville fritillary butterfly ( Melitaea cinxia ) in a network of 4000 dry meadows during 21 years. The results demonstrate two strong, related patterns: the amplitude of year-to-year fluctuations in the size of the metapopulation as a whole has increased, though there is no long-term trend in average abundance; and there is a highly significant increase in the level of spatial synchrony in population dynamics. The increased synchrony cannot be explained by increasing within-year spatial correlation in precipitation, the key environmental driver of population change, or in per capita growth rate. On the other hand, the frequency of drought during a critical life-history stage (early larval instars) has increased over the years, which is sufficient to explain the increasing amplitude and the expanding spatial synchrony in metapopulation dynamics. Increased spatial synchrony has the general effect of reducing long-term metapopulation viability even if there is no change in average metapopulation size. This study demonstrates how temporal changes in weather conditions can lead to striking changes in spatio-temporal population dynamics.

Population Dynamics of a Seed Feeding Bug, Lygaeus Equestris. 1. Habitat Patch Structure and Spatial Dynamics

Oikos ◽  
1990 ◽  
Vol 58 (2) ◽  
pp. 199 ◽  
Author(s):  
Christer Solbreck ◽  
Birgitta Sillén-Tullberg ◽  
Birgitta Sillen-Tullberg
Keyword(s):  
Population Dynamics ◽  
Spatial Dynamics ◽  
Habitat Patch ◽  
Patch Structure ◽  
Lygaeus Equestris

Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth

2012 ◽  
pp. 201-220
Author(s):  
Belgacem Ben Youssef ◽  
Lenny Tang
Keyword(s):  
Population Dynamics ◽  
Cellular Automata ◽  
Temporal Dynamics ◽  
Discrete Systems ◽  
Tissue Growth ◽  
State Transitions ◽  
Extended Model ◽  
Alternative Approach ◽  
Continuous Models ◽  
Multiple Cell

In this paper, the authors describe a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to simulate the tissue growth rates and population dynamics of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics. These random dynamic processes can be modeled by appropriately choosing the governing rules of the state transitions of each computational site. This extended model contains a number of system parameters that allow their effects on the volume coverage, the overall tissue growth rate, and some other aspects of cell behavior like the average speed of locomotion to be explored. These discrete systems provide an alternative approach to continuous models for the purpose of describing the temporal dynamics of complex systems.

scholarly journals Mapping subregional types of population dynamics of Irkutsk region

2021 ◽  
Vol 27 (4) ◽  
pp. 361-372
Author(s):  
Nikolay Vorobyev ◽  
Alexander Vorobyev
Keyword(s):  
Population Dynamics ◽  
Temporal Dynamics ◽  
System Development ◽  
Rural Settlements ◽  
Population System ◽  
General Direction ◽  
Regional Center ◽  
Real Distribution ◽  
Irkutsk Region ◽  
Populated Region

In the article the results of research of specifics of digital mapping of spatial and temporal dynamics of the population in a sparsely populated region (on the example of Irkutsk region). The study area is mainly inhomogeneously populated, with a sparse network of settlements (mainly spatially contiguous). The exception is the south territory along the Trans-Siberian Railway. To identify subregional and local characteristics of distribution of the population, the famous dazimetric method of V.P. Semyonov-Tyan-Shansky was used (adjusted for the features of sparsely populated regions). The boundaries of the areal inhabited territory are defined by the method of spots with a buffer radius of 3 km from the borders of populated locality. The overlapping spots, form a solidly populated space, from which depart linear-band elements of settlement, formed on the base of settlements dislocated along the paths of old communications (rivers and roads). The article presents a geoinformation methodology for collecting and processing available statistical data about population movement. In contrast to usual mapping, the calculation of general population dynamics, growth component and subsequent mapping were implemented not in municipal districts, urban and rural settlements, but within localities and settlement areas formed by them, ignoring official boundaries. The mapping allowed to identify patterns and detailing of the dynamics of the population considering the features of real distribution of the population in Irkutsk region. There is a discrepancy between the tendencies of demographic and economic development. The growth of resource complex comes at the expense of the northern periphery of the region, and the general direction of the population system development—growth of demographic potential around the regional center in conditions of depopulation of the periphery. The experience of mapping subregional types of population dynamics in Irkutsk region can be used in mapping similar regions.

Simulation of Multiple Cell Population Dynamics Using a 3-D Cellular Automata Model for Tissue Growth

2010 ◽  
Vol 1 (3) ◽  
pp. 1-18 ◽  
Author(s):  
Belgacem Ben Youssef ◽  
Lenny Tang
Keyword(s):  
Population Dynamics ◽  
Cellular Automata ◽  
Temporal Dynamics ◽  
Discrete Systems ◽  
Tissue Growth ◽  
State Transitions ◽  
Extended Model ◽  
Alternative Approach ◽  
Continuous Models ◽  
Multiple Cell

In this paper, the authors describe a computational model for the growth of multicellular tissues using a discrete approach based on cellular automata to simulate the tissue growth rates and population dynamics of multiple populations of proliferating and migrating cells. Each population of cells has its own division, motion, collision, and aggregation characteristics. These random dynamic processes can be modeled by appropriately choosing the governing rules of the state transitions of each computational site. This extended model contains a number of system parameters that allow their effects on the volume coverage, the overall tissue growth rate, and some other aspects of cell behavior like the average speed of locomotion to be explored. These discrete systems provide an alternative approach to continuous models for the purpose of describing the temporal dynamics of complex systems.

scholarly journals Temporal Variability and Ecological Interactions of Parasitic Marine Syndiniales in Coastal Protist Communities

mSphere ◽  
2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Sean R. Anderson ◽  
Elizabeth L. Harvey
Keyword(s):  
Population Dynamics ◽  
Network Analysis ◽  
Food Web ◽  
Relative Abundance ◽  
Temporal Variability ◽  
Temporal Dynamics ◽  
Host Cells ◽  
Ecosystem Models ◽  
Infection Dynamics ◽  
Host Infection

ABSTRACT Syndiniales are a ubiquitous group of protist parasites that infect and kill a wide range of hosts, including harmful bloom-forming dinoflagellates. Despite the importance of parasitism as an agent of plankton mortality, parasite-host dynamics remain poorly understood, especially over time, hindering the inclusion of parasitism in food web and ecosystem models. For a full year in the Skidaway River Estuary (Georgia), we employed weekly 18S rRNA sampling and co-occurrence network analysis to characterize temporal parasite-host infection dynamics of Syndiniales. Over the year, Syndiniales exhibited strong temporal variability, with higher relative abundance from June to October (7 to 28%) than other months in the year (0.01% to 6%). Nonmetric dimensional scaling of Syndiniales composition revealed tight clustering in June to October that coincided with elevated temperatures (23 to 31°C), though in general, abiotic factors poorly explained composition (canonical correspondence analysis [CCA] and partial least-squares [PLS]) and were less important in the network than biotic relationships. Syndiniales amplicon sequence variants (ASVs) were well represented in the co-occurrence network (20% of edges) and had significant positive associations (Spearman r > 0.7), inferred to be putative parasite-host relationships, with known dinoflagellate hosts (e.g., Akashiwo and Gymnodinium) and other protist groups (e.g., ciliates, radiolarians, and diatoms). Positive associations rarely involved a single Syndiniales and dinoflagellate species, implying flexible parasite-host infection dynamics. These findings provide insight into the temporal dynamics of Syndiniales over a full year and reinforce the importance of single-celled parasites in driving plankton population dynamics. Further empirical work is needed to confirm network interactions and to incorporate parasitism within the context of ecosystem models. IMPORTANCE Protist parasites in the marine alveolate group, Syndiniales, have been observed within infected plankton host cells for decades, and recently, global-scale efforts (Tara Ocean exploration) have confirmed their importance within microbial communities. Yet, protist parasites remain enigmatic, particularly with respect to their temporal dynamics and parasite-host interactions. We employed weekly 18S amplicon surveys over a full year in a coastal estuary, revealing strong temporal shifts in Syndiniales parasites, with highest relative abundance during warmer summer to fall months. Though influenced by temperature, Syndiniales population dynamics were also driven by a high frequency of biological interactions with other protist groups, as determined through co-occurrence network analysis. Parasitic interactions implied by the network highlighted a range of confirmed (dinoflagellates) and putative (diatoms) interactions and suggests parasites may be less selective in their preferred hosts. Understanding parasite-host dynamics over space and time will improve our ability to include parasitism as a loss term in microbial food web models.

scholarly journals Genetic Structure and Population Dynamics of Xanthomonas axonopodis pv. manihotis in Colombia from 1995 to 1999

2004 ◽  
Vol 70 (1) ◽  
pp. 255-261 ◽  
Author(s):  
Silvia Restrepo ◽  
Claudia M. Velez ◽  
Myriam C. Duque ◽  
Valérie Verdier
Keyword(s):  
Population Dynamics ◽  
Temporal Dynamics ◽  
Disease Incidence ◽  
Bacterial Pathogen ◽  
Rate Of Change ◽  
High Genetic Diversity ◽  
Cassava Bacterial Blight ◽  
Xanthomonas Axonopodis ◽  
Haplotype Frequencies ◽  
Site Diversity

ABSTRACT Restriction fragment length polymorphisms (RFLPs) were used to study the population genetics and temporal dynamics of the cassava bacterial pathogen Xanthomonas axonopodis pv. manihotis. The population dynamics were addressed by comparing samples collected from 1995 to 1999 from six locations, spanning four different edaphoclimatic zones (ECZs). Forty-five different X. axonopodis pv. manihotis RFLP types or haplotypes were identified between 1995 and 1999. High genetic diversity of the X. axonopodis pv. manihotis strains was evident within most of the fields sampled. In all but one site, diversity decreased over time within fields. Haplotype frequencies significantly differed over the years in all but one location. Studies of the rate of change of X. axonopodis pv. manihotis populations during the cropping cycle in two sites showed significant changes in the haplotype frequencies but not composition. However, variations in pathotype composition were observed from one year to the next at a single site in ECZs 1 and 2 and new pathotypes were described after 1997 in these ECZs, thus revealing the dramatic change in the pathogen population structure of X. axonopodis pv. manihotis. Disease incidence was used to show the progress of cassava bacterial blight in Colombia during the 5-year period in different ecosystems. Low disease incidence values were correlated with low rainfall in 1997 in ECZ 1.

scholarly journals Spatio-temporal point processes as meta-models for population dynamics in heterogeneous landscapes

2021 ◽  
Author(s):  
Patrizia Zamberletti ◽  
Julien Papaix ◽  
Edith Gabriel ◽  
Thomas Opitz
Keyword(s):  
Population Dynamics ◽  
Point Processes ◽  
Temporal Dynamics ◽  
Landscape Heterogeneity ◽  
Marked Point ◽  
Local Scale ◽  
Agricultural Landscapes ◽  
Spatially Explicit ◽  
Regression Equations ◽  
Spatio Temporal

Landscape heterogeneity affects population dynamics, which determine species persistence, diversity and interactions. These relationships can be accurately represented by advanced spatially-explicit models (SEMs) allowing for high levels of detail and precision. However, such approaches are characterised by high computational complexity, high amount of data and memory requirements, and spatio-temporal outputs may be difficult to analyse. A possibility to deal with this complexity is to aggregate outputs over time or space, but then interesting information may be masked and lost, such as local spatio-temporal relationships or patterns. An alternative solution is given by meta-models and meta-analysis, where simplified mathematical relationships are used to structure and summarise the complex transformations from inputs to outputs. Here, we propose an original approach to analyse SEM outputs. By developing a meta-modelling approach based on spatio-temporal point processes (STPPs), we characterise spatio-temporal population dynamics and landscape heterogeneity relationships in agricultural contexts. A landscape generator and a spatially-explicit population model simulate hierarchically the pest-predator dynamics of codling moth and ground beetles in apple orchards over heterogeneous agricultural landscapes. Spatio-temporally explicit outputs are simplified to marked point patterns of key events, such as local proliferation or introduction events. Then, we construct and estimate regression equations for multi-type STPPs composed of event occurrence intensity and magnitudes. Results provide local insights into spatio-temporal dynamics of pest-predator systems. We are able to differentiate the contributions of different driver categories (i.e., spatio-temporal, spatial, population dynamics). We highlight changes in the effects on occurrence intensity and magnitude when considering drivers at global or local scale. This approach leads to novel findings in agroecology where the organisation of cultivated fields and semi-natural elements are known to play a crucial role for pest regulation. It aids to formulate guidelines for biological control strategies at global and local scale.

scholarly journals The Ecological Structure of Mosquito Population Dynamics: Insights from India

2021 ◽  
Author(s):  
Charles Whittaker ◽  
Peter Winskill ◽  
Marianne Sinka ◽  
Samuel Pironon ◽  
Claire Massey ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Temporal Dynamics ◽  
Local Environment ◽  
Malaria Risk ◽  
Mosquito Population ◽  
Ecological Structure ◽  
Temporal Properties ◽  
Species Complexes ◽  
Specific Factors ◽  
Mosquito Population Dynamics

AbstractUnderstanding the temporal dynamics (including the start, duration and end) of malaria transmission is key to optimising various control strategies, enabling interventions to be deployed at times when they can have the most impact. This temporal profile of malaria risk is intimately related to the dynamics of the mosquito populations underlying transmission. However, many outstanding questions remain surrounding these dynamics, including the specific drivers and their dependence on the ecological structure of a setting. Here we collate mosquito time-series catch data from across India in order to better understand these dynamics and the factors shaping them. Our analyses reveal pronounced heterogeneity in mosquito population dynamics, both within (across different locations) and between (in the same location) species complexes. Despite this variation, we show that these time-series can be clustered into a small number of categories characterised by distinct temporal properties and driven by a largely unique set of environmental factors. Exploration of these categories highlights that an interplay of species complex-specific factors and the ecological structure of the local environment together shape the temporal dynamics (including timing and extent of seasonality) of mosquito populations. The results of these analyses are then integrated with spatial predictions of species presence/absence in order to generate predictive maps of mosquito population seasonality across India, to inform the planning and timing of malaria control efforts.SignificanceEffective planning and control of malaria requires an understanding of the underlying mosquito population dynamics that determine the temporal profile of malaria risk. Here, we collate a database of monthly mosquito catch data spanning 40 years and 117 unique locations across India to explore the factors shaping these dynamics. Our analyses reveal pronounced heterogeneity in mosquito population dynamics, both within (across different locations) and across (in the same location) species complexes: this heterogeneity is driven by an interplay between species complex-specific factors and the ecological structure of the local environment. Despite this variation, the temporal patterns of mosquito abundance across these different locations can be categorised into a small number of clusters, each characterised by distinct temporal properties and each of which is influenced by a largely unique set of environmental factors. Based on these results, we create a tool to predict mosquito population seasonality in a given location, to inform the planning and timing of control efforts.

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