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Studies on the spatial distribution pattern of larvae of the mosquito, Anopheles sinensis , in rice fields
Author(s) -
Ikemoto Takaya
Publication year - 1978
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/bf02518830
Subject(s) - biology , population , larva , spatial distribution , ecology , field (mathematics) , regression analysis , distribution (mathematics) , statistics , linear regression , paddy field , common spatial pattern , population density , mathematics , demography , mathematical analysis , sociology , pure mathematics
Summary The spatial distribution patterns of the population of Anopheles sinensis larvae were studied in the rice field area in the suburb of Urawa city in Japan, during the summer seasons in 1973 and 1974. The distribution pattern of the larval population within the field, analysed by the m−m regression method, indicated that the basic component of larval distribution was not a group of individuals but a single individual and such components were distributed contagiously over the field. This basic pattern did not change significantly according to developmental stage, census date or field. Therefore, we could describe the distribution pattern of the population in a rice field by the single linear regression, x=0.021+1.339x(r 2 −0.912). Also, the relation for the whole population in the field area including the five fields could be shown by the linear regression, x=0.049+1.749x(r 2 −0.959). The value of α remained to be nearly equal to zero, but the value of β became larger than the value for the single‐field relation. Such a change in distribution pattern seemed to reflect the greater heterogeneity in conditions among the fields than within individual field. Using the information on the distribution patterns mentioned above, some considerations were given on the sampling plans for mosquito larvae, including samplesize determination and application of sequential methods to estimate population size as well as to classify population level.