Spatially explicit modeling of schistosomiasis risk in Eastern China based on a synthesis of epidemiological, environmental and intermediate host genetic data

Schistosomiasis is considered the second most devastating parasitic disease after malaria. In China, it is transmitted to humans, cattle and other vertebrate hosts by a single intermediate snail host. It has long been suggested that the close co-evolutionary relationship between parasite and intermediate host makes the snail a major transmission bottleneck in the disease life cycle. Here, we use a novel approach to model the disease distribution in eastern China based on a combination of epidemiological, ecological, and genetic information. We found four major high risk areas for schistosomiasis occurrence in the large lakes and flood plain regions of the Yangtze River. These regions are interconnected, suggesting that the disease may be maintained in eastern China in part through the annual flooding of the Yangtze River, which drives snail transport and admixture of genotypes. The novel approach undertaken yielded improved prediction of schistosomiasis disease distribution in eastern China. Thus, it may also be of value for the predictive modeling of other host- or vector-borne diseases

Modeling seasonal dynamics of small fish cohorts in fluctuating freshwater marsh landscapes

Small-bodied fishes constitute an important assemblage in many wetlands. In wetlands that dry periodically except for small permanent waterbodies, these fishes are quick to respond to change and can undergo large fluctuations in numbers and biomasses. An important aspect of landscapes that are mixtures of marsh and permanent waterbodies is that high rates of biomass production occur in the marshes during flooding phases, while the permanent waterbodies serve as refuges for many biotic components during the dry phases. The temporal and spatial dynamics of the small fishes are ecologically important, as these fishes provide a crucial food base for higher trophic levels, such as wading birds. We develop a simple model that is analytically tractable, describing the main processes of the spatio-temporal dynamics of a population of small-bodied fish in a seasonal wetland environment, consisting of marsh and permanent waterbodies. The population expands into newly flooded areas during the wet season and contracts during declining water levels in the dry season. If the marsh dries completely during these times (a drydown), the fish need refuge in permanent waterbodies. At least three new and general conclusions arise from the model: (1) there is an optimal rate at which fish should expand into a newly flooding area to maximize population production; (2) there is also a fluctuation amplitude of water level that maximizes fish production, and (3) there is an upper limit on the number of fish that can reach a permanent waterbody during a drydown, no matter how large the marsh surface area is that drains into the waterbody. Because water levels can be manipulated in many wetlands, it is useful to have an understanding of the role of these fluctuations

The Ecological Effect of Phenotypic Plasticity - Analyzing Complex Interaction Networks (COIN) with Agent-based Models

Analyzing complex dynamics of ecological systems is complicated by two important facts: First, phenotypic plasticity allows individual organisms to adapt their reaction norms in terms of morphology, anatomy, physiology and behavior to changing local environmental conditions and trophic relationships. Secondly, individual reactions and ecological dynamics are often determined by indirect interactions through reaction chains and networks involving feedback processes. We present an agent-based modeling framework which allows to represent and analyze ecological systems that include phenotypic changes in individual performances and indirect interactions within heterogeneous and temporal changing environments. We denote this structure of interacting components as COmplex Interaction Network (COIN). Three examples illustrate the potential of the system to analyze complex ecological processes that incorporate changing phenotypes on the individual level: - A model on fish population dynamics of roach (Rutilus rutilus) leads to a differentiation in fish length resulting in a conspicuous distribution that influences reproduction capability and thus indirectly the fitness. - Modeling the reproduction phase of the passerine bird Erithacus rubecula (European Robin) illustrates variation in the behavior of higher organisms in dependence of environmental factors. Changes in reproduction success and in the proportion of different activities are the results. - The morphological reaction of plants to changes in fundamental environmental parameters is illustrated by the black alder (Alnus glutinosa) model. Specification of physiological processes and the interaction structure on the level of modules allow to represent the reaction to changes in irradiance and temperature accurately. Applying the COIN-approach, individual plasticity emerges as a structural and functional implication in a self-organized manner. The examples illustrate the potential to integrate existing approaches to represent detailed and complex traits for higher order organisms and to combine ecological and evolutionary aspects.JRC.G.4-Maritime affair

Fish population dynamics in a seasonally varying wetland

Small fishes in seasonally flooded environments such as the Everglades are capable of spreading into newly flooded areas and building up substantial biomass. Passive drift cannot account for the rapidity of observed population expansions. To test the ‘reaction–diffusion’ mechanism for spread of the fish, we estimated their diffusion coefficient and applied a reaction–diffusion model. This mechanism was also too weak to account for the spatial dynamics. Two other hypotheses were tested through modeling. The first—the ‘refuge mechanism’—hypothesizes that small remnant populations of small fishes survive the dry season in small permanent bodies of water (refugia), sites where the water level is otherwise below the surface. The second mechanism, which we call the ‘dynamic ideal free distribution mechanism’ is that consumption by the fish creates a prey density gradient and that fish taxis along this gradient can lead to rapid population expansion in space. We examined the two alternatives and concluded that although refugia may play an important role in recolonization by the fish population during reflooding, only the second, taxis in the direction of the flooding front, seems capable of matching empirical observations. This study has important implications for management of wetlands, as fish biomass is an essential support of higher trophic levels

Simulating Mechanisms for Dispersal, Production and Stranding of Small Forage Fish in Temporary Wetland Habitats

Movement strategies of small forage fish (\u3c8 cm total length) between temporary and permanent wetland habitats affect their overall population growth and biomass concentrations, i.e., availability to predators. These fish are often the key energy link between primary producers and top predators, such as wading birds, which require high concentrations of stranded fish in accessible depths. Expansion and contraction of seasonal wetlands induce a sequential alternation between rapid biomass growth and concentration, creating the conditions for local stranding of small fish as they move in response to varying water levels. To better understand how landscape topography, hydrology, and fish behavior interact to create high densities of stranded fish, we first simulated population dynamics of small fish, within a dynamic food web, with different traits for movement strategy and growth rate, across an artificial, spatially explicit, heterogeneous, two-dimensional marsh slough landscape, using hydrologic variability as the driver for movement. Model output showed that fish with the highest tendency to invade newly flooded marsh areas built up the largest populations over long time periods with stable hydrologic patterns. A higher probability to become stranded had negative effects on long-term population size, and offset the contribution of that species to stranded biomass. The model was next applied to the topography of a 10 km × 10 km area of Everglades landscape. The details of the topography were highly important in channeling fish movements and creating spatiotemporal patterns of fish movement and stranding. This output provides data that can be compared in the future with observed locations of fish biomass concentrations, or such surrogates as phosphorus ‘hotspots’ in the marsh

Spatially explicit modeling of schistosomiasis risk in eastern China based on a synthesis of epidemiological, environmental and intermediate host genetic data.

Schistosomiasis japonica is a major parasitic disease threatening millions of people in China. Though overall prevalence was greatly reduced during the second half of the past century, continued persistence in some areas and cases of re-emergence in others remain major concerns. As many regions in China are approaching disease elimination, obtaining quantitative data on Schistosoma japonicum parasites is increasingly difficult. This study examines the distribution of schistosomiasis in eastern China, taking advantage of the fact that the single intermediate host serves as a major transmission bottleneck. Epidemiological, population-genetic and high-resolution ecological data are combined to construct a predictive model capable of estimating the probability that schistosomiasis occurs in a target area ("spatially explicit schistosomiasis risk"). Results show that intermediate host genetic parameters are correlated with the distribution of endemic disease areas, and that five explanatory variables--altitude, minimum temperature, annual precipitation, genetic distance, and haplotype diversity-discriminate between endemic and non-endemic zones. Model predictions are correlated with human infection rates observed at the county level. Visualization of the model indicates that the highest risks of disease occur in the Dongting and Poyang lake regions, as expected, as well as in some floodplain areas of the Yangtze River. High risk areas are interconnected, suggesting the complex hydrological interplay of Dongting and Poyang lakes with the Yangtze River may be important for maintaining schistosomiasis in eastern China. Results demonstrate the value of genetic parameters for risk modeling, and particularly for reducing model prediction error. The findings have important consequences both for understanding the determinants of the current distribution of S. japonicum infections, and for designing future schistosomiasis surveillance and control strategies. The results also highlight how genetic information on taxa that constitute bottlenecks to disease transmission can be of value for risk modeling

Candidate topographical and ecological characters of <i>Oncomelania h. hupensis</i> used for the SESR modeling.

<p>All original resolutions were re-sampled to 500 m.</p

Schistosomiasis study area in eastern China.

<p>The map shows the localities of the intermediate snail host <i>Oncomelania h. hupensis</i> sampled (red dots), the assumed maximum distribution area of this subspecies in the lower Yangtze River basin (dashed gray line), and previously delineated endemic areas <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Zhou2" target="_blank">[5]</a> (highlighted areas). The distribution area is based on our own sampling data and literature records <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Li1" target="_blank">[58]</a>, <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Zhao1" target="_blank">[74]</a>, <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Kumagai1" target="_blank">[80]</a>, <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Yang4" target="_blank">[81]</a>, restricted by a reasonable vertical distribution of 0 to 200 m a.s.l. <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327-Ross1" target="_blank">[2]</a>. For detailed locality information see Supporting <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002327#pntd.0002327.s002" target="_blank">Table S1</a>. TGD = Three Gorges Dam.</p

Results of jackknife testing of variable importance for the SESR modeling.

<p>The boxplots show the median goodness-of-fit values (AUC) of the models based on three environmental (bio11, bio12, altitude), two genetic (D_TN, H_D), and all five variables together with their respective 95% confidence limits (whiskers).</p