{"title":"量化解释北海道田鼠种群时间泰勒定律斜率的因素","authors":"Takashi Saitoh, Joel E. Cohen","doi":"10.1002/1438-390x.12176","DOIUrl":null,"url":null,"abstract":"Taylor's law (TL) describes the relationship between the variance and mean of population density: log10(variance) ≈ log10(a) + b × log10(mean), a > 0. This study analyzed the temporal TL, for which mean and variance are calculated over time, separately for each population in a collection of populations, considering the effects of the parameters of the Gompertz model (a second‐order autoregressive time‐series model) and the skewness of the density frequency distribution. Time series of 162 populations of the gray‐sided vole in Hokkaido, Japan, spanning 23–31 years, satisfied the temporal TL: log10(variancej) ≈ 0.199 + 1.687 × log10(meanj). This model explained 62% of the variation of log10(variancej). An extended model with explanatory variables log10(meanj), the density‐dependent coefficient for 1‐year lag (α1,j), that for 2‐year lag (α2,j), the density‐independent variability (σj2), and the skewness (γj), explained 93.9% of the log10(variancej) variation. In the extended model, the coefficient of log10(meanj) was 1.949, close to the null value (b = 2) of the TL slope. The standardized partial regression coefficients indicated that density‐independent effects (σj2 and γj) dominated density‐dependent effects (α1,j and α2,j) apart from log10(meanj). The negative correlations observed between σj2 and log10(meanj), and between γj and log10(meanj), played an essential role in explaining the difference between the estimated slope of TL (b = 1.687) and the null slope (b = 2). The effects of those explanatory variables on log10(variancej) were interpreted based on the theory of a second‐order autoregressive time‐series model.","PeriodicalId":54597,"journal":{"name":"Population Ecology","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying factors that explain the slopes of the temporal Taylor's law of Hokkaido vole populations\",\"authors\":\"Takashi Saitoh, Joel E. Cohen\",\"doi\":\"10.1002/1438-390x.12176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Taylor's law (TL) describes the relationship between the variance and mean of population density: log10(variance) ≈ log10(a) + b × log10(mean), a > 0. This study analyzed the temporal TL, for which mean and variance are calculated over time, separately for each population in a collection of populations, considering the effects of the parameters of the Gompertz model (a second‐order autoregressive time‐series model) and the skewness of the density frequency distribution. Time series of 162 populations of the gray‐sided vole in Hokkaido, Japan, spanning 23–31 years, satisfied the temporal TL: log10(variancej) ≈ 0.199 + 1.687 × log10(meanj). This model explained 62% of the variation of log10(variancej). An extended model with explanatory variables log10(meanj), the density‐dependent coefficient for 1‐year lag (α1,j), that for 2‐year lag (α2,j), the density‐independent variability (σj2), and the skewness (γj), explained 93.9% of the log10(variancej) variation. In the extended model, the coefficient of log10(meanj) was 1.949, close to the null value (b = 2) of the TL slope. The standardized partial regression coefficients indicated that density‐independent effects (σj2 and γj) dominated density‐dependent effects (α1,j and α2,j) apart from log10(meanj). The negative correlations observed between σj2 and log10(meanj), and between γj and log10(meanj), played an essential role in explaining the difference between the estimated slope of TL (b = 1.687) and the null slope (b = 2). The effects of those explanatory variables on log10(variancej) were interpreted based on the theory of a second‐order autoregressive time‐series model.\",\"PeriodicalId\":54597,\"journal\":{\"name\":\"Population Ecology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Population Ecology\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1002/1438-390x.12176\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Population Ecology","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1002/1438-390x.12176","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECOLOGY","Score":null,"Total":0}
Quantifying factors that explain the slopes of the temporal Taylor's law of Hokkaido vole populations
Taylor's law (TL) describes the relationship between the variance and mean of population density: log10(variance) ≈ log10(a) + b × log10(mean), a > 0. This study analyzed the temporal TL, for which mean and variance are calculated over time, separately for each population in a collection of populations, considering the effects of the parameters of the Gompertz model (a second‐order autoregressive time‐series model) and the skewness of the density frequency distribution. Time series of 162 populations of the gray‐sided vole in Hokkaido, Japan, spanning 23–31 years, satisfied the temporal TL: log10(variancej) ≈ 0.199 + 1.687 × log10(meanj). This model explained 62% of the variation of log10(variancej). An extended model with explanatory variables log10(meanj), the density‐dependent coefficient for 1‐year lag (α1,j), that for 2‐year lag (α2,j), the density‐independent variability (σj2), and the skewness (γj), explained 93.9% of the log10(variancej) variation. In the extended model, the coefficient of log10(meanj) was 1.949, close to the null value (b = 2) of the TL slope. The standardized partial regression coefficients indicated that density‐independent effects (σj2 and γj) dominated density‐dependent effects (α1,j and α2,j) apart from log10(meanj). The negative correlations observed between σj2 and log10(meanj), and between γj and log10(meanj), played an essential role in explaining the difference between the estimated slope of TL (b = 1.687) and the null slope (b = 2). The effects of those explanatory variables on log10(variancej) were interpreted based on the theory of a second‐order autoregressive time‐series model.
期刊介绍:
Population Ecology, formerly known as Researches on Population Ecology launched in Dec 1952, is the official journal of the Society of Population Ecology. Population Ecology publishes original research articles and reviews (including invited reviews) on various aspects of population ecology, from the individual to the community level. Among the specific fields included are population dynamics and distribution, evolutionary ecology, ecological genetics, theoretical models, conservation biology, agroecosystem studies, and bioresource management. Manuscripts should contain new results of empirical and/or theoretical investigations concerning facts, patterns, processes, mechanisms or concepts of population ecology; those purely descriptive in nature are not suitable for this journal. All manuscripts are reviewed anonymously by two or more referees, and the final editorial decision is made by the Chief Editor or an Associate Editor based on the referees'' evaluations.