Analysis of population dynamics with interactive multi-dimensional graphics (original) (raw)
A Visual Analytics Approach for Ecosystem Dynamics based on Empirical Dynamic Modeling
IEEE Transactions on Visualization and Computer Graphics, 2021
Fig. 1. Schematic of visual analytics to study nonlinear interactions with empirical dynamic modeling (EDM). A dynamic graph of changing interaction coefficients is first constructed using the (A) measured time series data and (B) interaction coefficients extracted via EDM techniques. (C) Our proposed visual analytics system enables the detection and interpretation of system states using dimension reduction and brush-link visualization techniques. (D) Using the process of annotation and summarization, the state transition graph can be obtained for interpretation. Abstract-An important approach for scientific inquiry across many disciplines involves using observational time series data to understand the relationships between key variables to gain mechanistic insights into the underlying rules that govern the given system. In real systems, such as those found in ecology, the relationships between time series variables are generally not static; instead, these relationships are dynamical and change in a nonlinear or state-dependent manner. To further understand such systems, we investigate integrating methods that appropriately characterize these dynamics (i.e., methods that measure interactions as they change with time-varying system states) with visualization techniques that can help analyze the behavior of the system. Here, we focus on empirical dynamic modeling (EDM) as a state-of-the-art method that specifically identifies causal variables and measures changing state-dependent relationships between time series variables. Instead of using approaches centered on parametric equations, EDM is an equation-free approach that studies systems based on their dynamic attractors. We propose a visual analytics system to support the identification and mechanistic interpretation of system states using an EDM-constructed dynamic graph. This work, as detailed in four analysis tasks and demonstrated with a GUI, provides a novel synthesis of EDM and visualization techniques such as brush-link visualization and visual summarization to interpret dynamic graphs representing ecosystem dynamics. We applied our proposed system to ecological simulation data and real data from a marine mesocosm study as two key use cases. Our case studies show that our visual analytics tools support the identification and interpretation of the system state by the user, and enable us to discover both confirmatory and new findings in ecosystem dynamics. Overall, we demonstrated that our system can facilitate an understanding of how systems function beyond the intuitive analysis of high-dimensional information based on specific domain knowledge.
Analysis of spatial and temporal patterns of diversity and abundance in ecological data has been an important focus in ecology. Nevertheless, ecological data such as multi-species data sets are often difficult to analyze because species are usually unevenly represented and multiple environmental covariates may describe their distributions. Although typical univariate, bivariate, and multivariate statistics provide rigorous tests of hypotheses, they have limited capacity to quickly identify relationships among multiple species and environmental covariates, or detect change over time. We propose a novel visualization technique, the Diversity Map, which facilitates the visual inspection of the distribution, abundance, and covariates of large multi-species data sets using an interactive web-based visual interface. To develop this tool, we have taken a user-centered design approach, in which our team of ecologists, information managers, and computer scientists collaborate closely during the development process. Initial findings indicate that this tool is extremely valuable for ecologists in the early stages of data exploration, prior to further statistical analysis. In this paper, we discuss our design approach, the design elements, and implementation of the Diversity Map tool and we demonstrate how the tool can help scientists gain insights into spatial and temporal patterns of ecological data. The use of this tool is illustrated with data on moth diversity and abundance from the HJ Andrews Experimental Forest.
steps : Software for spatially and temporally explicit population simulations
Methods in Ecology and Evolution
1. Species population dynamics are driven by spatial and temporal changes in the environment, anthropogenic activities, and conservation management actions. Understanding how populations will change in response to these drivers is fundamental to a wide range of ecological applications, but there are few open-source software options accessible to researchers and managers that allow them to predict these changes in a flexible and transparent way. 2. We introduce an open-source, multi-platform R package, steps, that models spatial changes in species populations as a function of drivers of distribution and abundance, such as climate, disturbance, landscape dynamics, and species ecological and physiological requirements.
Study Of Spatial Biological Systems Using a Graphical User Interface
2008
In this paper, we describe a Graphical User Interface (GUI) designed to manage large quantities of image data of a biological system. After setting the design requirements for the system, we developed an ecology quantification GUI that assists biologists in analysing data. We focus on the main features of the interface and we present the results and an evaluation of the system. Finally, we provide some directions for some future work.
Computational Ecology and Software, 2014, Vol. 4, Iss. 3
Catastrophe phenomena are frequent in insect ecology, especially in aphid populations. Complexity of this phenomenon urges different modeling frameworks other than traditional methodologies to understand the trajectories of their behavior. Situations like this can be best handled using catastrophe theory. A few numbers of experiments have been conducted to develop catastrophe models in insect ecology, especially for aphids, and most of them are based on cusp catastrophe theory which is a lower dimensional model. However few attempts using higher dimensional models such as swallowtail or butterfly theory to analyze aphid population dynamics are also exist. In this paper we tried to analyze a recently developed higher dimensional catastrophe theory model (APHIDSim) in order to identify catastrophe regions, and used independent data to identify if catastrophic behavior is observed in the data and consequently to further verify the model. Here we found that identifying catastrophe regions is possible using catastrophe theory model, and it can be used to analyze catastrophes in insect ecology by graphically interpreting the simulated results. Increasing of insect population is intrinsically catastrophic and catastrophes (jumps) occur between states even if the driving variables still change smoothly. The results further verified the previously developed model, and we suggest that insect management program developers should consider this phenomenon when they design the management strategies for insect controlling.
Real-time 4D visualization of migratory insect dynamics within an integrated spatiotemporal system
Ecological Informatics, 2006
This paper presents a new approach of spatiotemporally visualizing the simulation output of migratory insect dynamics and resultant vegetation changes in real-time. The visualization is capable of displaying simulated ecological phenomena in an intuitive manner, which allows research results to be easily understood by a wide range of users. In order to design a fast and efficient visualization technique, a simplified mathematical model is applied to intelligibly represent migrating groups of insects. In addition, impostors are used to accelerate rendering processes. The presented visualization method is implemented in an integrated spatiotemporal analysis system, which models, simulates and analyzes ecological phenomena such as insect migration through time at a variety of spatial resolutions.
Modeling Population Dynamics: a Graphical Approach
to biology students. She taught me the strength of phase plane analysis and simple caricature models. Some of the most interesting exercises in this book stem from that course. After I started teaching this course its contents and presentation have evolved, and have adapted to the behavior, the questions, and the comments from numerous students having attended this course. which says that the variable M increases at a rate k per time unit. For instance, this could describe the amount of pesticides in your body when you eat the same amount of fruit sprayed with pesticides every day. Another example is to say that M is the amount of money in your bank account, and that k is the amount of Euros that are deposited in this account on a daily basis. In the latter case the "dimension" of the parameter k is "Euros per day". The ODE formalism assumes that the changes in your bank account are continuous. Although this is evidently wrong, because money is typically deposited on a monthly basis, this makes little difference when one considers time scales longer than one month. 2N (0) = N (0)e rt gives ln 2 = rt or t = ln[2]/r. (2.8) This model also has only one steady state,N = 0, which is unstable because any small perturbation above N = 0 will initiate unlimited growth of the population. To obtain a non-trivial (or non-zero) steady state population size in populations maintaining themselves by reproduction one needs density dependent birth or death rates. This is the subject of the next chapter.
PopPlanner: visually constructing demographic models for simulation
Frontiers in genetics, 2015
Currently there are a number of coalescent simulation programs that support a wide range of features, such as arbitrary demographic models, migration, and sub structure. Defining the model is done typically with either text files or command line switches. Although this has proven to be a powerful method of defining models of high complexity, it is often error prone and difficult to read without familiarity both with command lines and the program in question. A intuitive GUI based population structure program that can both read and write applicable command lines would dramatically simplify the construction, modification, and error checking of such models by a wider user base. PopPlanner is a tool to both construct and inspect complicated demographic models visually with a GUI where the user's primary interaction is through mouse gestures. Because of their popularity, we focus on ms and by extension msms, command line coalescent simulation programs. Our program can be used to find...
A computer tool to develop individual-based models for simulation of population interactions
The CENOCON system was developed as a computer tool to build individual-based models for simulation of population interactions. This system allows creation of very complex ecological communities, with up to 256 species of plants and up to 256 species of animals. Population dynamics, study of intra-and inter-population interactions with intricate food chains, are the main areas where this tool can be used. A special feature, pesticide impact, is added to fit the application to pest management. Single-and multi-generation simulations are possible. There is no restriction on the number of involved individuals and the only limitation is the computer memory. The process of building a concrete model is very easy and straightforward: the writing of a text file describing a number of organisms–participants. No programming skills are required to use the software, the modeller can concentrate just on the essence of the problem.
Interactive visual analysis promotes exploration of long-term ecological data
Long-term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, these kinds of data sets are difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods and spreadsheet software permit rigorous tests of pre-conceived hypotheses and static charts for simple data exploration, they have limited capacity to provide an overview of the data and to enable ecologists to explore data iteratively, and interactively, before committing to statistical analysis. These issues hinder how ecologists gain knowledge and generate hypotheses from long-term data. We present Ecological Distributions and Trends Explorer (EcoDATE), a web-based, visual-analysis tool that facilitates exploratory analysis of long-term ecological data (i.e., generating hypotheses as opposed to confirming hypotheses). The tool, which is publicly available online, was created and refined through a user-centered design process in which our team of ecologists and visualization researchers collaborated closely. The results of our collaboration were (1) a set of visual representation and interaction techniques well suited to communicating distribution patterns and temporal trends in ecological data sets, and (2) an understanding of processes ecologists use to explore data and generate and test hypotheses. We present three case studies to demonstrate the utility of EcoDATE and the exploratory analysis processes using long-term data on cone production, stream chemistry, and forest structure collected as part of the H.J. Andrews Experimental Forest (HJA), Long Term Ecological Research (LTER), and US Forest Service Pacific Northwest Research Station programs. We also present results from a survey of 15 participants of a working group at the 2012 LTER All Scientists Meeting that showed that users appreciated the tool for its ease of use, holistic access to large data sets, and interactivity.