Showing papers by "Donald L. DeAngelis published in 2015"

Equation-free modeling unravels the behavior of complex ecological systems

Abstract: Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future.

Effects of dispersal on total biomass in a patchy, heterogeneous system: Analysis and experiment.

Abstract: An intriguing recent result from mathematics is that a population diffusing at an intermediate rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. We extended the current mathematical theory to apply to logistic growth and also showed that the result applies to patchy systems with dispersal among patches, both for continuous and discrete time. This allowed us to make specific predictions, through simulations, concerning the biomass dynamics, which were verified by a laboratory experiment. The experiment was a study of biomass growth of duckweed (Lemna minor Linn.), where the resources (nutrients added to water) were distributed homogeneously among a discrete series of water-filled containers in one treatment, and distributed heterogeneously in another treatment. The experimental results showed that total biomass peaked at an intermediate, relatively low, diffusion rate, higher than the total carrying capacity of the system and agreeing with the simulation model. The implications of the experiment to dynamics of source, sink, and pseudo-sink dynamics are discussed.

Modelling the effects of seasonality and socioeconomic impact on the transmission of rift valley Fever virus.

Abstract: Rift Valley fever (RVF) is an important mosquito-borne viral zoonosis in Africa and the Middle East that causes human deaths and significant economic losses due to huge incidences of death and abortion among infected livestock. Outbreaks of RVF are sporadic and associated with both seasonal and socioeconomic effects. Here we propose an almost periodic three-patch model to investigate the transmission dynamics of RVF virus (RVFV) among ruminants with spatial movements. Our findings indicate that, in Northeastern Africa, human activities, including those associated with the Eid al Adha feast, along with a combination of climatic factors such as rainfall level and hydrological variations, contribute to the transmission and dispersal of the disease pathogen. Moreover, sporadic outbreaks may occur when the two events occur together: 1) abundant livestock are recruited into areas at risk from RVF due to the demand for the religious festival and 2) abundant numbers of mosquitoes emerge. These two factors have been shown to have impacts on the severity of RVF outbreaks. Our numerical results present the transmission dynamics of the disease pathogen over both short and long periods of time, particularly during the festival time. Further, we investigate the impact on patterns of disease outbreaks in each patch brought by festival- and seasonal-driven factors, such as the number of livestock imported daily, the animal transportation speed from patch to patch, and the death rate induced by ceremonial sacrifices. In addition, our simulations show that when the time for festival preparation starts earlier than usual, the risk of massive disease outbreaks rises, particularly in patch 3 (the place where the religious ceremony will be held).

A plant toxin mediated mechanism for the lag in snowshoe hare population recovery following cyclic declines

Abstract: A necessary condition for a snowshoe hare population to cycle is reduced reproduction after the population declines. But the cause of a cyclic snowshoe hare population’s reduced reproduction during the low phase of the cycle, when predator density collapses, is not completely understood. We propose that moderate-severe browsing by snowshoe hares upon preferred winter-foods could increase the toxicity of some of the hare’s best winter-foods during the following hare low, with the result being a decline in hare nutrition that could reduce hare reproduction. We used a combination of modeling and experiments to explore this hypothesis. Using the shrub birch Betula glandulosa as the plant of interest, the model predicted that browsing by hares during a hare cycle peak, by increasing the toxicity B. glandulosa twigs during the following hare low, could cause a hare population to cycle. The model’s assumptions were verified with assays of dammarane triterpenes in segments of B. glandulosa twigs and captive hare feeding experiments conducted in Alaska during February and March 1986. The model’s predictions were tested with estimates of hare density and measurements of B. glandulosa twig growth made at Kluane, Yukon from 1988–2008. The empirical tests supported the model’s predictions. Thus, we have concluded that a browsing-caused increase in twig toxicity that occurs during the hare cycle’s low phase could reduce hare reproduction during the low phase of the hare cycle.

Application of a Coupled Vegetation Competition and Groundwater Simulation Model to Study Effects of Sea Level Rise and Storm Surges on Coastal Vegetation

Abstract: Global climate change poses challenges to areas such as low-lying coastal zones, where sea level rise (SLR) and storm-surge overwash events can have long-term effects on vegetation and on soil and groundwater salinities, posing risks of habitat loss critical to native species. An early warning system is urgently needed to predict and prepare for the consequences of these climate-related impacts on both the short-term dynamics of salinity in the soil and groundwater and the long-term effects on vegetation. For this purpose, the U.S. Geological Survey’s spatially explicit model of vegetation community dynamics along coastal salinity gradients (MANHAM) is integrated into the USGS groundwater model (SUTRA) to create a coupled hydrology–salinity–vegetation model, MANTRA. In MANTRA, the uptake of water by plants is modeled as a fluid mass sink term. Groundwater salinity, water saturation and vegetation biomass determine the water available for plant transpiration. Formulations and assumptions used in the coupled model are presented. MANTRA is calibrated with salinity data and vegetation pattern for a coastal area of Florida Everglades vulnerable to storm surges. A possible regime shift at that site is investigated by simulating the vegetation responses to climate variability and disturbances, including SLR and storm surges based on empirical information.

Advantages of concurrent use of multiple software frameworks in water quality modelling using a database approach

Abstract: Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches. PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework – including runtime performance – can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers.

A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission

Abstract: Agent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour. A spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared. When the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P < 0.01). Survival was greater when sugar sources were randomly distributed in the whole village compared to clustering around outdoor resting sites or houses. Increases in densities of sugar sources or outdoor resting sites significantly increase the survival and human biting rates of An. gambiae mosquitoes. Survival of An. gambiae is more supported by random distribution of sugar sources than clustering of sugar sources around resting sites or houses. Density and spatial distribution of natural sugar sources and outdoor resting sites modulate vector populations and human biting rates, and thus malaria parasite transmission.

Modeling apple snail population dynamics on the Everglades landscape

Abstract: The Florida Everglades has diminished in size and its existing wetland hydrology has been altered. The endangered snail kite (Rostrhamus sociabilis) has nearly abandoned the Everglades, and its prey, the apple snail (Pomacea paludosa), has declined. We developed a population model (EverSnail) to understand apple snail response to inter- and intra-annual fluctuations in water depths over the Everglades landscape. EverSnail was developed as a tool to understand how apple snails respond to different hydrologic scenarios. EverSnail is an age- and size-structured, spatially-explicit landscape model of P. paludosa in the Everglades. Landscape-level inputs are water depth and air temperature. We conducted sensitivity analyses by running EverSnail with ±20 % the baseline value of eight parameters. EverSnail was sensitive to changes in survival and water depth associated with reproduction. The EverSnail population varied with changes and/or differences in depth generally consistent with empirical data; site-specific comparisons to field data proved less reliable. A simulated 3-year wet period resulted in a shift in apple snail distribution, but little change in total abundance over the landscape. In contrast, a simulated 3-year succession of relatively dry years resulted in overall lower snail abundances. Comparisons of model output to empirical data indicate the need for more data to better understand, and eventually parameterize, several aspects of snail ecology in support of EverSnail. A primary value of EverSnail is its capacity to describe the relative response of snail abundance to alternative hydrologic scenarios considered for Everglades water management and restoration.

Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

Abstract: Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.