Compensatory density feedback of Oncomelania hupensis populations in two different environmental settings in China
© Yang et al; licensee BioMed Central Ltd. 2011
Received: 26 April 2011
Accepted: 13 July 2011
Published: 13 July 2011
The most recent strategy for schistosomiasis control in the People's Republic of China aims to reduce the likelihood of environmental contamination of schistosome eggs. Despite considerable progress, it is believed that achievements would be further consolidated with additional intermediate host snail control measures. We provide an empirical framework for discerning the relative contribution of intrinsic effects (density feedback) from other extrinsic drivers of snail population dynamics.
We set up experiments in two study locations to collect reproduction data of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum. We applied a set of four population dynamic models that have been widely used to study phenomenological time-series data to examine the properties of demographic density feedback patterns from abundance data. We also contrasted the obtained results with the component feedback of density on survival rate to determine whether adult survival was the principal driver of the demographic feedback observed.
Demographic density feedback models (Ricker- and Gompertz-logistic) accounted for > 99% of Akaike's information criterion model weight, with the Gompertz ranking highest in all O. hupensis population groups. We found some evidence for stronger compensatory feedback in the O. hupensis population from Sichuan compared to a Jiangsu population. Survival rates revealed strong component feedback, but the log-linear relationships (i.e. Gompertz) had less support in the demographic feedback analysis.
Our findings indicate that integrated schistosomiasis control measures must continue to reduce parasite abundance further because intermediate host snail populations tend to grow exponentially at low densities, especially O. hupensis populations in mountainous regions. We conclude that density feedback in adult survival is the principal component contribution to the demographic phenomenon observed in the population fitness (r)-abundance relationship.
In the People's Republic of China (P.R. China), schistosomiasis caused by the blood fluke Schistosoma japonicum has a documented history of more than 2,000 years [1, 2]. The first large-scale surveys done in the mid-1950s suggested that the disease was endemic in 12 provinces located along and south of the Yangtze River. More than 10 million people were infected, causing considerable morbidity and even mortality [3, 4]. Hence, a national schistosomiasis control programme was launched, placing particular emphasis on the control of the intermediate host snail Oncomelania hupensis, including environmental management and chemical mollusciciding [2–6]. As a result, snail-infested areas have been reduced from approximately 14,320 km2 in the mid-1950s to 3,720 km2 in 2008 [6, 7].
Recently, a comprehensive strategy was proposed with the ultimate aim to reduce further the likelihood of contamination of the environment with schistosome eggs. This integrated control strategy consists of health education, access to clean water and adequate sanitation, mechanization of agriculture and fencing of domesticated bovines, along with preventive chemotherapy [8, 9]. The main rationale for implementing this new strategy is that schistosomiasis is an environmentally mediated disease, and that it is difficult to eliminate all snail habitats, particularly in lake and marshland regions . However, this new strategy alone does not succeed in eliminating or substantially reducing the incidence of schistosomiasis , especially in mountainous regions where suitable snail habitats persist. Additional control measures are needed, such as mollusciciding, which is a time-consuming and costly strategy, because large fluctuations in snail abundance [12, 13] can arise from flooding [14, 15]. Hence, measures for increasing the effectiveness of mollusciciding, which in turn reduce intermediate host snail abundance and limit the likelihood of re-emergence of schistosomiasis, are required .
For the effective control of O. hupensis populations, a fundamental step is a deeper understanding of the snail's intrinsic population dynamics because these properties influence the rate of recovery after withdrawal of snail control . There is, however, a paucity of information describing even basic population dynamics for this species, which severely limits our understanding of the processes of schistosomiasis transmission, and hence hampers the development of effective control approaches. here is a general consensus among ecologists that account must be taken of intrinsic and extrinsic population controls  when analysing time-series data, and growing emphasis is placed on determining the degree of interaction between the two aspects driving fluctuations in abundance [18–22]. Intrinsic control normally operates via density feedback whereby component vital rates (e.g. survival and fertility) and/or individual fitness change in response to population density . However, vital rates can respond differently to density changes, meaning that the influence of density on the rate of population growth (termed demographic feedback) as measured by changes in abundance should reflect the net contributions of all component vital rates and extrinsic perturbations . Extrinsic processes include stochastic environmental pressures and human control activities that affect population density, but are not directly affected by population density themselves .
Previous research pertaining to O. hupensis focused mainly on the environmental conditions correlated with snail abundance, and hence particular emphasis was placed on elucidating extrinsic influences. Similar to mosquito vector species [25–27], snail population dynamics can also exhibit strong density feedback, and the form and relative strength of feedback might differ markedly among populations given the strong genetic differentiation observed in intermediate host snails [28, 29]. Failure to take intrinsic dynamics into account can lead to an over-estimation of the medium- to long-term effectiveness of density control methods, such as mollusciciding or habitat modification .
Here we provide an empirical framework for discerning the relative contributions of intrinsic drivers of snail population dynamics for a better understanding of the eco-epidemiology and control of schistosomiasis. We first examine the evidence for, strength and form of phenomenological (demographic) density feedback operating in focal snail populations based on a series of biological experiments under quasi-field conditions. We also test whether the intrinsic dynamics of O. hupensis follow a Gompertz-like compensatory feedback, which is consistent with organisms having high turn-over rates such as insects [30, 31]. The Gompertz model and its analogues express population growth (r) or vital rates such as survival (s) as a negative log-linear relationship with density, with high r or s at low densities which decline rapidly as population size increases and then tapers to an asymptote . Examining the patterns of component feedback in snail survival provides insight into the principal drivers of the strength and form of the demographic response. The relevant elements derived from the intrinsic model will provide an ecologically based evidence to formulate cost-effective control strategies towards schistosomiasis elimination, and to ensure the lowest transmission risk or density of O. hupensis.
In late September 2009, we repeated the experiment until the following year. We randomly selected adult snails in the second experiment from the new generation of snails obtained in the first experiment. We assembled the data obtained from the two experiments and subjected them to a pooled analysis.
Demographic density feedback
where N t = snail population size at time t, r = realized population rate of change, r m = maximum rate of population change, K = carrying capacity and process error ε t ~ Normal(0, σ2). We fitted all models on the basis of maximum-likelihood using linear regression.
Component density feedback
where n l = number of live snails, n d = number of dead snails, n i = initial number of snails (n l + n d ), s m = the mean or maximum survival rate (intercept), β= coefficient (slope) of the abundance (n i ) parameter and ε = process error (as described above).
We also estimated each model's goodness of fit using the percentage of deviance explained (%DE) relative to the null (intercept-only) model.
Breeding patterns of O. hupensis
Contrasting four demographic density feedback models for O.hupensis snail density
w AIC c
The effective population growth rates of mountainous snails in low-density groups are about 3-4 times higher than those observed in the marshland.
Contrasting three models of O.hupensis snail survival rate as a function of density: density-independent (DI), linear decline (DDL) and log-linear decline (DDLL)
w AIC c
First experiences with implementing a new integrated control strategy for schistosomiasis control in P.R. China are promising [8, 9, 11]. However, we speculate that control efforts could be further enhanced by rigorously implementing intermediate host-snail suppression until snail densities are below a pre-set detection threshold. Our models revealed a strong feedback mechanism, whereby extremely low-density habitats following control can in fact produce the largest subsequent pulses of snails, thus potentially continuing or even exacerbating schistosomiasis outbreaks . Hence, snail control, in concert with the new comprehensive schistosomiasis control strategy , would also act to suppress natural fluctuations of the disease in humans and animals, especially in areas of low prevalence. There is a need to continue suppression given that in lake districts, fishermen and river-transportation workers regularly come into contact with contaminated freshwater bodies (schistosome eggs and, most importantly, schistosome cercariae, which are the infective stages), and thus perpetuate local outbreaks. In mountainous regions, buffalo (Bubalus bubalis) act as the major definitive host of S. japonicum, and are still used as the core farming animal in agriculture, and hence cannot be replaced immediately by more modern mechanical farming equipment. It follows that the persistence of suitable snail habitats, and hence intermediate host snails, calls for sustained control via chemical mollusciciding and environmental management.
A better understanding of the population dynamics of intermediate host snails holds promise to render snail control more effective. With regard to the work presented here, the following conclusions can be drawn. First, we showed that effective mollusciciding must reduce snail density to less than two specimens per 0.5 m2 because even at these low densities, populations can increase quickly to over 50 times initial abundance given low initial competition among individuals. Second, the only molluscicide currently recommended by the World Health Organization is niclosamide . At present in P.R. China, the most commonly used formula of molluscicide is 50% wettable powder of niclosamide ethanolamine salt (Bayluscide) . A recent systematic review showed that snail mortality is around 88% using a 50% wettable powder of niclosamide ethanolamine salt post spraying for 15 days . There is considerable concern that, if mollusciciding is only attempted once by spraying niclosamide in the field, the few surviving snails will engender a rapid re-bound in the months to come. We therefore recommend applying molluscicide at least twice yearly and, if financial and technical resources allow, even more frequently.
Although the population growth dynamic of snails in both marshland and mountainous regions followed the same pattern, we observed some notable differences. For example, the slope of the regression model for O. hupensis in the mountainous areas is considerably greater than that for the marshland (-1.133 versus -0.502), which translates to the prediction that mountainous snails are likely more sensitive to variation in density than marshland strains at low population sizes. As a result, O. hupensis from mountainous regions seem more elusive to control than marshland snails because of the high rebound rate expected subsequent to mollusciciding. Compared to marshland O. hupensis, our findings suggest that snail control in mountainous regions must be implemented with utmost vigilance to reduce population rate of increase that tends constantly towards exponential growth at low densities. If possible, environmental management in mountainous regions should be recommended with the ultimate goal to eliminate suitable snail habitats. Recent work indicated that schistosomiasis is re-emerging in mountainous regions, perhaps explained by the overall high rate of snail rebound .
Although we could not test the component contribution of reproduction explicitly given the confounding effects of a semelparous, annual-breeding species (i.e. a generation lasts only until the next breeding cycle), it is clear that adult survival contributes a large component to the demographic response. We also found that the decline in survival with density was greatest and linear for the first generation, but weaker and log-linear for the second (Figure 4). This might arise from differing environmental conditions experienced by each generation, or differential mortality patterns, or a combination of both. Thus, examining patterns of density feedback across a wider range of experimental conditions will further enhance our understanding of snail rebound potential following control.
Of course, snail population size is not solely a product of density feedback. In addition to intrinsic influences, the distribution, extent and density of O. hupensis depend on a complex interaction of different environmental factors, of which temperature, rainfall and flooding are the three most important . Future modelling must consider these factors and the potential influence of environmental changes (e.g. climate change) on long-term predictions of the cost-effectiveness of control interventions.
This project received financial support from the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR) (A70530), Shanghai S & T Project (11XD1405400), and the National S & T Major Program (2008ZX10004-011). CJAB is partially funded by the Australian Academy of Science.
- Zhou XN, Wang LY, Chen MG, Wu XH, Jiang QW, Chen XY, Zheng J, Utzinger J: The public health significance and control of schistosomiasis in China - then and now. Acta Trop. 2005, 96: 97-105. 10.1016/j.actatropica.2005.07.005.View ArticlePubMed
- Utzinger J, Zhou XN, Chen MG, Bergquist R: Conquering schistosomiasis in China: the long march. Acta Trop. 2005, 96: 69-96.View ArticlePubMed
- Mao CP, Shao BR: Schistosomiasis control in the People's Republic of China. Am J Trop Med Hyg. 1982, 31: 92-99.PubMed
- Maegraith B: Schistosomiasis in China. Lancet. 1958, 271: 208-214.View Article
- Chen MG, Feng Z: Schistosomiasis control in China. Parasitol Int. 1999, 48: 11-19. 10.1016/S1383-5769(99)00004-5.View Article
- Zhou XN, Bergquist R, Leonardo L, Yang GJ, Yang K, Sudomo M, Olveda R: Schistosomiasis japonica: control and research needs. Adv Parasitol. 2010, 72: 145-178.View ArticlePubMed
- Hao Y, Yi DH, Zhang XF, Xiong JJ, Yuan WZ, Hu SJ, Wu XH, Zhu R, Guo JG, Huang XB: Assessment report on infection control of schistosomiasis in China, 2008. Chin J Schisto Cont. 2009, 21: 457-463.
- Wang LD, Guo JG, Wu XH, Chen HG, Wang TP, Zhu SP, Zhang ZH, Steinmann P, Yang GJ, Wang SP: China's new strategy to block Schistosoma japonicum transmission: experiences and impact beyond schistosomiasis. Trop Med Int Health. 2009, 14: 1475-1483. 10.1111/j.1365-3156.2009.02403.x.View ArticlePubMed
- Wang LD, Chen HG, Guo JG, Zeng XJ, Hong XL, Xiong JJ, Wu XH, Wang XH, Wang LY, Xia G: A strategy to control transmission of Schistosoma japonicum in China. N Engl J Med. 2009, 360: 121-128. 10.1056/NEJMoa0800135.View ArticlePubMed
- Zhu R, Gray DJ, Thrift AP, Williams GM, Zhang Y, Qiu DC, Zheng F, Li YS, Guo J, Zhu HQ: A 5-year longitudinal study of schistosomiasis transmission in Shian village, the Anning River valley, Sichuan province, the People's Republic of China. Parasit Vectors. 2011, 4: 43-10.1186/1756-3305-4-43.PubMed CentralView ArticlePubMed
- Gray DJ, McManus DP, Li YS, Williams GM, Bergquist R, Ross AG: Schistosomiasis elimination: lessons from the past guide the future. Lancet Infect Dis. 2010, 10: 733-736. 10.1016/S1473-3099(10)70099-2.View ArticlePubMed
- Zhou XN, Yang GJ, Yang K, Wang XH, Hong QB, Sun LP, Malone JB, Kristensen TK, Bergquist NR, Utzinger J: Potential impact of climate change on schistosomiasis transmission in China. Am J Trop Med Hyg. 2008, 78: 188-194.PubMed
- Yang GJ, Vounatsou P, Zhou XN, Tanner M, Utzinger J: A potential impact of climate change and water resource development on the transmission of Schistosoma japonicum in China. Parassitologia. 2005, 47: 127-134.View ArticlePubMed
- Zhou XN, Lin DD, Yang HM, Chen HG, Sun LP, Yang GJ, Hong QB, Brown L, Malone JB: Use of Landsat TM satellite surveillance data to measure the impact of the 1998 flood on snail intermediate host dispersal in the lower Yangtze River Basin. Acta Trop. 2002, 82: 199-205. 10.1016/S0001-706X(02)00011-6.View ArticlePubMed
- Lin DD, Zhou XN, Liu Y, Sun L, Hu F, Yang G, Hong Q: Prediction of snail habitats in the marshland around Poyang Lake affected by flood in 1998 using remote sensing. Chin J Schisto Cont. 2002, 14: 119-121.
- Standley CJ, Adriko M, Arinaitwe M, Atuhaire A, Kazibwe F, Fenwick A, Kabatereine NB, Stothard JR: Epidemiology and control of intestinal schistosomiasis on the Sesse Islands, Uganda: integrating malacology and parasitology to tailor local treatment recommendations. Parasit Vectors. 2010, 3: 64-10.1186/1756-3305-3-64.PubMed CentralView ArticlePubMed
- Turchin P: Population regulation: old arguments and a new synthesis. 1995, New York: Academic PressView Article
- Bjørnstad ON, Grenfell BT: Noisy clockwork: time series analysis of population fluctuations in animals. Science. 2001, 293: 638-643. 10.1126/science.1062226.View ArticlePubMed
- Clark F, Brook BW, Delean S, Akçakaya HR, Bradshaw CJA: The theta-logistic is unreliable for modelling most census data. Meth Ecol Evol. 2010, 1: 253-262.
- de Little SC, Bradshaw CJA, McMahon CR, Hindell MA: Complex interplay between intrinsic and extrinsic drivers of long-term survival trends in southern elephant seals. BMC Ecology. 2007, 7: 3-10.1186/1472-6785-7-3.PubMed CentralView ArticlePubMed
- Sæther BE: Environmental stochasticity and population dynamics of large herbivores: a search for mechanisms. Trends Ecol Evol. 1997, 12: 143-149. 10.1016/S0169-5347(96)10068-9.View ArticlePubMed
- Yang GJ, Bradshaw CJA, Whelan PI, Brook BW: Importance of endogenous feedback controlling the long-term abundance of tropical mosquito species. Popul Ecol. 2008, 50: 293-305. 10.1007/s10144-008-0082-8.View Article
- Turchin P: Complex population dynamics: a theoretical/empirical synthesis. 2003, Princeton: Princeton University Press
- Münster-Swendsen M, Berryman A: Detecting the causes of population cycles by analysis of R-functions: the spruce needle-miner, Epinotia tedella, and its parasitoids in Danish spruce plantations. Oikos. 2005, 108: 495-502. 10.1111/j.0030-1299.2005.13747.x.View Article
- Kunkel KE, Novak RJ, Lampman RL, Gu W: Modeling the impact of variable climatic factors on the crossover of Culex restauns and Culex pipiens (Diptera: culicidae), vectors of West Nile virus in Illinois. Am J Trop Med Hyg. 2006, 74: 168-173.PubMed
- Russell RC: Seasonal abundance and age composition of two populations of Culex annulirostris (Diptera: Culicidae) at Darwin, Northern Territory, Australia. J Med Entomol. 1986, 23: 279-285.View ArticlePubMed
- Su T, Webb JP, Meyer RP, Mulla MS: Spatial and temporal distribution of mosquitoes in underground storm drain systems in Orange county, California. J Vector Ecol. 2003, 28: 79-89.PubMed
- Zhao QP, Jiang MS, Littlewood DT, Nie P: Distinct genetic diversity of Oncomelania hupensis, intermediate host of Schistosoma japonicum in mainland China as revealed by ITS sequences. PLoS Negl Trop Dis. 2010, 4: e611-10.1371/journal.pntd.0000611.PubMed CentralView ArticlePubMed
- Li SZ, Wang YX, Yang K, Liu Q, Wang Q, Zhang Y, Wu XH, Guo JG, Bergquist R, Zhou XN: Landscape genetics: the correlation of spatial and genetic distances of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum in mainland China. Geospat Health. 2009, 3: 221-231.View ArticlePubMed
- Brook BW, Bradshaw CJ: Strength of evidence for density dependence in abundance time series of 1198 species. Ecology. 2006, 87: 1445-1451. 10.1890/0012-9658(2006)87[1445:SOEFDD]2.0.CO;2.View ArticlePubMed
- McKinney ML: Extinction vulnerability and selectivity: combining ecological and paleontological views. Ann Rev Ecol Syst. 1997, 28: 495-516. 10.1146/annurev.ecolsys.28.1.495.View Article
- Huang QN, Tang LL, Jiang XG, Chen Z, Zhou XN: Retrieving eco-environment factors relevant to Oncomelania snail distribution based on QuickBird image. Chin J Parasitol Parasit Dis. 2007, 25: 304-309.
- Yang K, Zhou XN, Wu XH, Steinmann P, Wang XH, Yang GJ, Utzinger J, Li HJ: Landscape pattern analysis and Bayesian modeling for predicting Oncomelania hupensis distribution in Eryuan county, People's Republic of China. Am J Trop Med Hyg. 2009, 81: 416-423.PubMed
- Hall BH, Cummins C: TSP 5.0 reference manual, 2005. accessed: 10 January 2011, [http://www.tspintl.com]
- Yamamura K, Yokozawa M, Nishimori M, Ueda Y, Yokosuka T: How to analyze long-term insect population dynamics under climate change: 50-year data of three insect pests in paddy fields. Popul Ecol. 2006, 48: 31-48. 10.1007/s10144-005-0239-7.View Article
- Akaike H: Information theory as an extension of the maximum likelihood principle. Proceedings of the Second International Symposium on Information Theory. Edited by: Petrov BN, Csaki F. 1973, Budapest, Hungary, 267-281.
- Burnham KP, Anderson DR: Model selection and multimodal inference: a practical information-theoretic approach. 2002, New York: Springer-Verlag
- R Development Core Team: R: a language and environment for statistical computing. R Foundation for Statistical Computing. 2011, Vienna, Austria
- Liang S, Yang CH, Zhong B, Qiu DC: Re-emerging schistosomiasis in hilly and mountainous areas of Sichuan, China. Bull World Health Organ. 2006, 84: 139-144. 10.2471/BLT.05.025031.PubMed CentralView ArticlePubMed
- WHO: The role of mollusciciding in schistosomiasis control. 1983, Geneva: World Health Organization, 72-73.
- Bao JG, Zhang GH, Wu WD, Zhang SQ, Zhang XY, Lv DB, Fang GR, Wang FF, Zhu L, Dai QJ: Snail control effect of 4%powder of niclosamide tthanolamine salt in field trial. Parasit Infect Dis. 2004, 2: 163-165.
- Yang GJ, Li W, Sun LP, Wu F, yang K, Huang YX, Zhou XN: Molluscicidal efficacies of different formulations of niclosamide: result of meta-analysis of Chinese literature. Parasit Vectors. 2010, 3: 84-10.1186/1756-3305-3-84.PubMed CentralView ArticlePubMed
- Mao CP: Biology of schistosome and control of schistosomiasis. 1990, Beijing: People's Health Press
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