Integrates Population Dynamics Research Articles

Population dynamics and cultural niche construction during the Late Holocene in a mediterranean ecosystem (central Chile, 32°S−36°S)

Understanding socio-ecological systems over the long term can shed light on past adaptive strategies in environmentally sensitive regions. Central Chile is an emblematic case study for mediterranean ecosystems, where a progressive and sustained population increase began approximately 2000 years ago alongside significant landscape changes. In this work we analyzed regional paleo-demographic trends by compiling a new database of archaeological dates over the last 3000 years, and integrating population dynamics theory with an analysis of the spatio-temporal variation of regional cultural stages. Results show three moments of marked acceleration in population growth: just before agricultural adoption, during the Archaic Period (c. 700-300 BCE); during the second half of the ECP (500–900 CE); and during the Late Intermediate Period (1200–1400 CE). We also identified periods of deceleration in per capita growth rates, although population size continued to increase (300 BCE−500 CE, 900–1200 CE and after 1400 CE). These large shifts in the per capita growth rates coincide with major cultural changes associated with social and economic aspects. The pulses of major occupation show in general terms a more intensive use of the valleys as the population size increased, although the remaining ecosystems never ceased to be occupied with different economic and symbolic emphases.

Dengue Fever Dynamics in Bali, Indonesia 2010-2018: An Interplay of Population Density and Climatic Factors

Dengue Fever (DF) incidence in Bali has been the highest in Indonesia for decades. This study describes the annual distribution of DF and analyzes its association with population density, number of rainy days, and average humidity during 2010-2018 at the district level. The choropleth maps and Poisson regression were employed to provide geographical distribution and quantify the association. The P, 95% confidence interval (CI), and Akaike Information Criterion (AIC) were adopted to assess the significance and the goodness of the association. During 2010-2018 there were 55 215 new DF cases notified. The annual incidence of dengue cases in Bali increased with IRR: 1.000186 (95% CI:1.0000183:1.000189) for every increment of population density per kilometers square and increased by IRR: 1.01043 (95% CI: 1.01019: 1.01078) for every additional one rainy day annually. The dengue cases also increased with IRR 1.0172 (95% CI: 1.0137: 1.0208) for every 1% increase in average humidity. Population density and climate factors are positively associated with dengue cases incidence in Bali from 2010 to 2018. The results underline the urgency of integrating population dynamics and climatic determinants into the DF control program and customizing the intervention program based on local characteristics.

Integrated multi-timescale modeling untangles anthropogenic, environmental, and biological effects on catchability

Catchability plays a central role in fisheries stock assessment. Since catchability often varies with time depending on population density, environmental factors, and anthropogenic effects, assuming constant catchability in population models can lead to biased abundance estimates. Here we present a novel way to simultaneously estimate time-varying catchability and abundance by integrating a short-term (month-based) removal method and a long-term (year-based) age-structured population dynamics model. We applied this approach to commercial fishery data for a Japanese pufferfish (Takifugu rubripes) population and found that the models with time-varying catchability greatly outperformed the models with constant catchability in terms of predictive ability and model consistency. The temporal variation in catchability was parsimoniously predicted by fishing effort and population size, indicating the existence of effort- and density-dependent catchability. Our approach, integrating population dynamics at different timescales, will help avoid inadvertent overexploitation and contribute to sustainable harvesting by enhancing the estimation accuracy of time-varying catchability and abundance.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E.coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

Integrating population dynamics into mapping human exposure to seismic hazard

Abstract. Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Evolutionary suicide as a consequence of runaway selection for greater aggregation tendency

Aggregation of individuals is a common phenomenon in nature. By aggregating, individuals can reap benefits but may also be subject to associated costs from increased competition. The benefits of aggregation can depend on population density, which in turn can be affected by aggregation when it determines reproductive success of individuals. The Allee effect is often considered to be one of the factors that can explain the evolution of aggregation behavior. We investigated this hypothesis with a mathematical model which integrates population dynamics and evolution. Individuals gain synergistically from aggregation but suffer from scramble competition with aggregation tendency as an evolving trait. We found that aggregation behavior can stabilize the population dynamics and reduce population growth. The results show that the Allee effect alone is not sufficient for aggregative behavior to evolve as an evolutionarily stable strategy. We also found that weak local competition does not promote aggregation due to feedback from the population level: under low competition, the population can achieve high density such that aggregation becomes costly rather than beneficial. Our model instead exhibits an escalation of aggregation tendency, leading to the extinction of the population in a process known as evolutionary suicide. We conclude that for aggregation to evolve as an evolutionarily stable strategy we need to consider other factors such as inter-patch dispersal to new patches and avoidance of excessively large groups.

The role of larval dispersal in metapopulation gene flow: Local population dynamics matter

The degree of genetic connectivity among populations in a metapopulation has direct consequences for species evolution, development of disease resistance, and capacity of a metapopulation to adapt to climate change. This study used a metapopulation model that integrates population dynamics, dispersal, and genetics within an individual-based model framework to examine the mechanisms and dynamics of genetic connectivity within a metapopulation. The model was parameterized to simulate four populations of oysters (Crassostrea virginica) from Delaware Bay on the mid-Atlantic coast of the United States. Differences among the four populations include a strong spatial gradient in mortality, a spatial gradient in growth rates, and uneven population abundances. Simulations demonstrated a large difference in the magnitude of neutral allele transfer with changes in population abundance and mortality (on average between 14 and 25% depending on source population), whereas changes in larval dispersal were not effective in altering genetic connectivity (on average between 1 and 8%). Simulations also demonstrated large temporal changes in metapopulation genetic connectivity including shifts in genetic sources and sinks occurring between two regimes, the 1970s and 2000s. Although larval dispersal in a sessile marine population is the mechanism for gene transfer among populations, these simulations demonstrate the importance of local dynamics and characteristics of the adult component of the populations in the flow of neutral alleles within a metapopulation. In particular, differential adult mortality rates among populations exert a controlling influence on dispersal of alleles, an outcome of latent consequence for management of marine populations.

Spatial and Temporal Patterns in Stream Habitat and Smallmouth Bass Populations in Eastern Oklahoma

AbstractThe spatial and temporal dynamics of stream habitat and fish populations are important considerations for the conservation and management of stream fishes. We determined how stream habitat and populations of smallmouth bass Micropterus dolomieu varied among third‐order to fifth‐order stream reaches in two regional streams in eastern Oklahoma from 2003 to 2005. Eastern Oklahoma represents the southwestern edge of the species' range and is where the Oklahoma Department of Wildlife Conservation focuses its stream habitat management efforts. Water temperature, streamflow, and habitat differed between Baron Fork Creek (northeast) and the Glover River (southeast) and changed longitudinally within each stream. Smallmouth bass abundance was highest downstream in Baron Fork Creek and lowest downstream in the Glover River. Recruitment was poor and variable in the upstream reaches of both streams and was strong and stable downstream in Baron Fork Creek. The survival of age‐1 and older smallmouth bass was higher in Baron Fork Creek than in the Glover River. The relative weights of smallmouth bass were higher in Baron Fork Creek than in the Glover River upstream, and they decreased downstream in Baron Fork Creek. Growth was highest from summer to fall, and relative weights were lowest in spring and highest in summer. Survival was typically lowest from summer to fall. Movement among channel units was highest from fall to winter, and there was evidence that older individuals moved more often. Smallmouth bass used different habitats for overwintering versus spring spawning, and they used most deep habitats in summer and fall. Integrating population dynamics with stream habitat helped to identify habitat management strategies that can best enhance smallmouth bass populations at the edge of their native distribution, where they provide important recreational fishing opportunities to anglers.

Cavity-nesting community webs as predictive tools: where do we go from here?

The complexities of ecological systems are often portrayed visually through the use of networks, and a number of techniques have been developed to quantify network properties in useful ways. Cavity-nesting communities may be particularly well suited for network analysis because these communities are hierarchically structured and interconnected. In addition, the mechanisms of cavity excavation and use, which mediate interactions between cavity-nesting species, are relatively clear and experimentally testable through cavity manipulation. Webs have recently been used as a visual tool to depict the structure of cavity-nesting communities. Here, we present a conceptual paper that explores future directions of nest web analysis. We provide a simple demonstration of how web visualization of cavity-nesting communities can enable the prediction of how community structure will shift when components are removed and identify non-intuitive indirect interactions within an ecological community. We also provide a brief review of some network tools used to examine ecological complexity. We hope this exercise can stimulate discussion of how nest web analysis can be advanced, for example by developing quantitative methods to describe and compare webs across different forest systems and by integrating population dynamics into nest webs to examine community-level stability. Such expansions of nest web analysis can contribute to the development of predictive capabilities for community response to environmental change and forest management.

Productivity controls food-chain properties in microbial communities

Food webs provide a framework for integrating population dynamics, community structure and ecosystem processes, but the causes of many food-web patterns remain controversial1. An unresolved issue concerns the factors that limit food-chain length in natural ecosystems, although theory predicts that length could be limited by inefficient energy transfer between trophic levels2 orby the instability of longer food chains3. Experiments provide qualitative support for the instability of longer food chains4, but, according to theory, this relationship may depend on the assumptions used to model food chains5. Here we show that experimental manipulations of productivity determine the length of microbial food chains in laboratory microcosms. Food-chain length is also predicted to determine how productivity influences population densities within trophic levels. If trophic levels consist entirely ofedible prey, and if consumers feed only on the next-lower trophic level6, population densities should alternate between increasing and constant values as food-chain length increases (Fig. 1). We find that food-chain length determines population-level responses to productivity, which is consistent with predictions from models. These results indicate that the impacts of human alterations of productivity will depend crucially on the structure of the affected food chains.

Analysis of the Allocation of Resources in Family Planning Programs

The reduction of population growth rates through family planning programs is being attempted in many of the developing nations of the world. This activity lends itself aptly to mathematical modelling. Building from the well-known difference equation model of population growth, a model is constructed which integrates population dynamics, program activities and resource consumption. The model may be used predictively to assess the outcome of various program activities. Alternatively, it may be used to determine the pattern of activities which yields the greatest reduction in births under the projected resource constraints. A further use of the model is the identification of the parameters to which predictions are most sensitive; such information provides valuable insights to those gathering the input data. The model is here applied to two family planning programs currently in progress. An evaluation of the feasibility of the program's goals is provided, as well as information on limiting resources, data sensitivity and the most important ages for contraceptive acceptance. The model's generality is such that it can be applied to most birth control programs which are planned at the national or regional level.

A mathematical model for resource allocation in population programs

Abstract The reduction of population growth rates through family planning programs is being attempted in many of the developing nations of the world. This activity lends itself aptly to mathematical modeling. Building from the well-known difference equation model of population growth, a model is constructed which integrates population dynamics, program activities, and resource consumption. The model may be used predictively to assess the outcome of various program activities. Alternatively, it may be used to determine the pattern of activities which yields the greatest reduction in births under the projected resource constraints. A further use of the model is the identification of the parameters to which predictions are most sensitive; such information provides valuable insights to those gathering the input data. The model is here applied to a family planning program currently in progress. An evaluation of the feasibility of that program’s goals is provided, as well as information on limiting resources, data sensitivity, and the most important ages for contraceptive acceptance.