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Predicting potential ecological distribution of Bactrocera dorsalis in China using GARP ecological niche modeling
利用GARP生态位模型预测桔小实蝇(Bactrocera dorsalis)在中国的适生区域

ZHOU Guo-Liang,CHEN Chen,YE Jun,HU Bai-Shi,LIU Feng-Quan,
周国梁
,陈晨,叶军,胡白石,刘凤权

生态学报 , 2007,
Abstract: 桔小实蝇Bactrocera dorsalis (Hendel)是一种多食性害虫,明确其可能适生的区域对该虫的科学监测及防治意义重大。利用桔小实蝇在我国的已知分布点数据和亚洲地区的14个环境地理变量图层,运用GARP生态位模型结合GIS空间分析模块预测了该虫在亚洲的地理分布。结果表明桔小实蝇可分布在中国、日本、菲律宾、马来西亚、泰国北部、越南、柬埔寨、老挝、缅甸、尼泊尔、巴基斯坦、孟加拉国和斯里兰卡,这与EPPO报道的分布区域一致。将拟合过程中获得的生态位运算法则投影到我国,并考虑模型间的一致性,预测桔小实蝇在我国各省及市县范围的分布:云南大部、四川南部和东部、贵州大部、重庆大部、广西、广东、台湾、香港、澳门、海南、福建、江西、浙江大部、湖南大部、湖北大部、上海、江苏南部、河南局部及安徽部分地区为桔小实蝇的适生区。次适生区沿适生区周围分布,为四川、贵州、重庆、湖北北部、河南南部和江苏南部的一些零星地区。适生区和次适生区大多有较高密度的寄主果树,为桔小实蝇的生存提供了条件。预测结果经独立验证数据的适合性测验表明,选择的最优模型具有显著的统计学意义,显示了很好的预测能力。GARP生态位模型可以解决生态学、生物地理学和环境保护方面的一系列问题,具有广泛的应用前景,为物种已知基础分布点资料的综合分析以及有害生物的适生性分析、监测和防治提供了技术平台。
Ecological Niche Modelling of Bank Voles in Western Europe  [PDF]
Sara Amirpour Haredasht,Miguel Barrios,Jamshid Farifteh,Piet Maes,Jan Clement,Willem W. Verstraeten,Katrien Tersago,Marc Van Ranst,Pol Coppin,Daniel Berckmans,Jean-Marie Aerts
International Journal of Environmental Research and Public Health , 2013, DOI: 10.3390/ijerph10020499
Abstract: The bank vole (Myodes glareolus) is the natural host of Puumala virus (PUUV) in vast areas of Europe. PUUV is one of the hantaviruses which are transmitted to humans by infected rodents. PUUV causes a general mild form of hemorrhagic fever with renal syndrome (HFRS) called nephropathia epidemica (NE). Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover influences disease transmission by controlling both the spatial distribution of vectors or hosts, as well as by facilitating the human contact with them. In this study the use of ecological niche modelling (ENM) for predicting the geographical distribution of bank vole population on the basis of spatial climate information is tested. The Genetic Algorithm for Rule-set Prediction (GARP) is used to model the ecological niche of bank voles in Western Europe. The meteorological data, land cover types and geo-referenced points representing the locations of the bank voles (latitude/longitude) in the study area are used as the primary model input value. The predictive accuracy of the bank vole ecologic niche model was significant (training accuracy of 86%). The output of the GARP models based on the 50% subsets of points used for testing the model showed an accuracy of 75%. Compared with random models, the probability of such high predictivity was low (χ 2 tests, p < 10 ?6). As such, the GARP models were predictive and the used ecologic niche model indeed indicates the ecologic requirements of bank voles. This approach successfully identified the areas of infection risk across the study area. The result suggests that the niche modelling approach can be implemented in a next step towards the development of new tools for monitoring the bank vole’s population.
The Genotypic Structure of a Multi-Host Bumblebee Parasite Suggests a Role for Ecological Niche Overlap  [PDF]
Rahel M. Salathé,Paul Schmid-Hempel
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0022054
Abstract: The genotypic structure of parasite populations is an important determinant of ecological and evolutionary dynamics of host-parasite interactions with consequences for pest management and disease control. Genotypic structure is especially interesting where multiple hosts co-exist and share parasites. We here analyze the natural genotypic distribution of Crithidia bombi, a trypanosomatid parasite of bumblebees (Bombus spp.), in two ecologically different habitats over a time period of three years. Using an algorithm to reconstruct genotypes in cases of multiple infections, and combining these with directly identified genotypes from single infections, we find a striking diversity of infection for both data sets, with almost all multi-locus genotypes being unique, and are inferring that around half of the total infections are resulting from multiple strains. Our analyses further suggest a mixture of clonality and sexuality in natural populations of this parasite species. Finally, we ask whether parasite genotypes are associated with host species (the phylogenetic hypothesis) or whether ecological factors (niche overlap in flower choice) shape the distribution of parasite genotypes (the ecological hypothesis). Redundancy analysis demonstrates that in the region with relatively high parasite prevalence, both host species identity and niche overlap are equally important factors shaping the distribution of parasite strains, whereas in the region with lower parasite prevalence, niche overlap more strongly contributes to the distribution observed. Overall, our study underlines the importance of ecological factors in shaping the natural dynamics of host-parasite systems.
Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling  [PDF]
Hannah Slater, Edwin Michael
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032202
Abstract: Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.
Use of ecological niche modeling as a tool for predicting the potential distribution of Microcystis sp (cyanobacteria) in the Aguamilpa Dam, Nayarit, Mexico  [cached]
José L. Ibarra-Montoya,Gabriel Rangel-Peraza,Fernando A. González-Farias,José De Anda
Ambiente e água : An Interdisciplinary Journal of Applied Science , 2012,
Abstract: Ecological niche modeling is an important tool to evaluate the spatial distribution of terrestrial species, however, its applicability has been little explored in the aquatic environment. Microcystis sp., a species of cyanobacteria, is widely recognized for its ability to produce a group of toxins known as microcystins, which can cause death of animals as fish, birds and mammals depending on the amount of toxin absorbed. Like any taxonomic group, cyanobacteria has environmental thresholds, therefore, a suitable ecological niche will define their distribution. This study was conducted in Aguamilpa Hydroelectric Reservoir, an artificial ecosystem that started operations in 1994. In this system we evaluated the potential distribution of Microcystis sp., by generating a prediction model based on the concept of ecological niche MAXENT, using a Digital Elevation Model in cells of 100 m x 100 m (1 ha) spatial resolution and monitoring eleven physicochemical and biological variables and nutrients in water. The distribution maps were developed using ArcMap 9.2 . The results indicated that Microcystis sp., is distributed mainly in the upper tributary basin (Huaynamota basin) during the dry season. There was less chance to find cyanobacteria in the entire system during the cold dry season, while during the warm dry season cyanobacteria was recognized at the confluence of two rivers. During the rainfall season there were no reports of cyanobacteria presence. This species is often associated with arising trophic processes of anthropogenic origin; therefore, attention is required in specific areas that have been identified in this work to improve Aguamilpa’s watershed management and restoration. It was also recognized the importance of phosphorus and nitrogen interaction, which determines the distribution of Microcystis sp., in the Aguamilpa Reservoir. The results of this study demonstrated that ecological niche modeling was a suitable tool to assess the spatial distribution of microalgae in freshwater environments.
Ecological niche of plant pathogens
Ecaterina Fodor
Annals of Forest Research , 2011,
Abstract: Disease ecology is a new approach to the understanding of the spread and dynamics of pathogens in natural and man-made environments. Defining and describing the ecological niche of the pathogens is one of the major tasks for ecological theory, as well as for practitioners preoccupied with the control and forecasting of established and emerging diseases. Niche theory has been periodically revised, not including in an explicit way the pathogens. However, many progresses have been achieved in niche modeling of disease spread, but few attempts were made to construct a theoretical frame for the ecological niche of pathogens. The paper is a review of the knowledge accumulated during last decades in the niche theory of pathogens and proposes an ecological approach in research. It quest for new control methods in what concerns forest plant pathogens, with a special emphasis on fungi like organisms of the genus Phytophthora. Species of Phytophthora are the most successful plant pathogens of the moment, affecting forest and agricultural systems worldwide, many of them being invasive alien organisms in many ecosystems. The hyperspace of their ecological niche is defined by hosts, environment and human interference, as main axes. To select most important variables within the hyperspace, is important for the understanding of the complex role of pathogens in the ecosystems as well as for control programs. Biotic relationships within ecosystem of host-pathogen couple are depicted by ecological network and specific metrics attached to this. The star shaped network is characterized by few high degree nodes, by short path lengths and relatively low connectivity, premises for a rapid disturbance spread.
PREDICTING POTENTIAL DISTRIBUTIONS OF DOMINANT WOODY PLANT KEYSTONE SPECIES IN A NATURAL TROPICAL FOREST LANDSCAPE OF BAWANGLING, HAINAN ISLAND, SOUTH CHINA
海南岛霸王岭热带天然林景观中主要木本植物关键种的潜在分布

ZHANG Zhi-Dong,ZANG Run-Guo,
张志东
,臧润国

植物生态学报 , 2007,
Abstract: Aims Our major objectives were to 1)identify keystone species within the context of functional groups,2)develop potential distributional predictions for keystone species using ecological niche model,3)confirm factors determining potential distributions of keystone species,and 4)test if the performances of ecological niche model are better than those of a random model and differ in predicting different keystone species.Methods Based on the investigation of 135 plots in a natural tropical forest landscape,we classified woody plant functional groups based on successional status and potential maximum height.Keystone species within each functional group were identified using a dominance index(DI).We used the genetic algorithm for rule-set prediction(GARP)to estimate the keystone species' potential distribution and then used the receiver operating characteristics to evaluate predictive performance.Applying multiple linear regression analysis,we identified major factors determining potential distributions of keystone species.Important findings Identification of keystone species within pioneer species,climax shrub and emergent tree functional groups was clearer than within climax subcanopy and climax canopy tree functional groups.Generally,among the eight keystone species,pioneer species Melastoma sanquiueum,Aporosa chinensis and Liquidambar formosana(but not Adinandra hainanensis)have high probability of occurrence in the north,west and southwest regions of Bawangling.However,climax species Psychotria rubra,Ardisia quinquegona and Castanopsis hainanensis(but not Pinus merkusii)have high probability of occurrence in the central,southeast and south regions.Minimum and maximum temperature,mean annual temperature and precipitation,aspect and altitude were the key factors determining potential distributions of keystone species.Evaluation of GARP model's performance indicated excellent predictive ability of all eight keystone species' distribution.This study suggests the DI method is more suitable to identify keystone species within woody plant functional groups in which a single or a few species are dominant.Findings will assist decision makers in planning conservation and management policies in tropical rainforest areas.
Improving ecological niche models by data mining large environmental datasets for surrogate models  [PDF]
David R. B. Stockwell
Computer Science , 2005,
Abstract: WhyWhere is a new ecological niche modeling (ENM) algorithm for mapping and explaining the distribution of species. The algorithm uses image processing methods to efficiently sift through large amounts of data to find the few variables that best predict species occurrence. The purpose of this paper is to describe and justify the main parameterizations and to show preliminary success at rapidly providing accurate, scalable, and simple ENMs. Preliminary results for 6 species of plants and animals in different regions indicate a significant (p<0.01) 14% increase in accuracy over the GARP algorithm using models with few, typically two, variables. The increase is attributed to access to additional data, particularly monthly vs. annual climate averages. WhyWhere is also 6 times faster than GARP on large data sets. A data mining based approach with transparent access to remote data archives is a new paradigm for ENM, particularly suited to finding correlates in large databases of fine resolution surfaces. Software for WhyWhere is freely available, both as a service and in a desktop downloadable form from the web site http://biodi.sdsc.edu/ww_home.html.
Predicting Prokaryotic Ecological Niches Using Genome Sequence Analysis  [PDF]
Garret Suen, Barry S. Goldman, Roy D. Welch
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000743
Abstract: Automated DNA sequencing technology is so rapid that analysis has become the rate-limiting step. Hundreds of prokaryotic genome sequences are publicly available, with new genomes uploaded at the rate of approximately 20 per month. As a result, this growing body of genome sequences will include microorganisms not previously identified, isolated, or observed. We hypothesize that evolutionary pressure exerted by an ecological niche selects for a similar genetic repertoire in those prokaryotes that occupy the same niche, and that this is due to both vertical and horizontal transmission. To test this, we have developed a novel method to classify prokaryotes, by calculating their Pfam protein domain distributions and clustering them with all other sequenced prokaryotic species. Clusters of organisms are visualized in two dimensions as ‘mountains’ on a topological map. When compared to a phylogenetic map constructed using 16S rRNA, this map more accurately clusters prokaryotes according to functional and environmental attributes. We demonstrate the ability of this map, which we term a “niche map”, to cluster according to ecological niche both quantitatively and qualitatively, and propose that this method be used to associate uncharacterized prokaryotes with their ecological niche as a means of predicting their functional role directly from their genome sequence.
A framework for analyzing ecological trait-based models in multi-dimensional niche spaces  [PDF]
Tommaso Biancalani,Lee DeVille,Nigel Goldenfeld
Mathematics , 2014, DOI: 10.1103/PhysRevE.91.052107
Abstract: We develop an theoretical approach for predicting biodiversity in multi-dimensional niche spaces, arising due to ecological drivers such as competitive exclusion. The novelty of our approach relies on the fact that ecological niches are described by sequences of strings, which allows us to describe multiple traits. We define the mathematical framework for analyzing pattern forming instabilities in these models, showing surprisingly that the analytic linear theory predicts the asymptotically long time population distributions of niches in the model. We propose a test for identifying ecological drivers in biodiversity distributions, based on representing ecosystem data by means of a certain transform introduced in the theory.
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