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catch_synchrony(): 渔获量的同步性与稳定性

Source: vignettes/articles/zh/reference/catch_synchrony.Rmd
catch_synchrony.Rmd

英文原页：catch_synchrony()

说明

本函数衡量数据中各物种（或各国家）渔获量波动的同步程度，以及它们的非同步性在多大程度上使总渔获量更稳定：包括Loreau和de Mazancourt（2008）的同步性指数、Ong等（2021）用于FAO渔获量序列的组合效应、Thibaut和Connolly（2013）对总渔获量变异性的分解，以及序列之间的两两相关系数。

English

This function measures how synchronously the catches of the species (or countries) of the data fluctuate, and how much their asynchrony stabilises the total catch: the synchrony index of Loreau and de Mazancourt (2008), the portfolio effect used by Ong et al. (2021) for FAO catch series, the decomposition of the variability of the total catch of Thibaut and Connolly (2013), and the pairwise correlations of the series.

用法 

catch_synchrony(
  area_data,
  by = c("species", "country"),
  detrend = c("linear", "none"),
  window = 20,
  top_n = 20,
  min_median = 10,
  min_nonzero = 0.75,
  plot = TRUE,
  table = TRUE,
  lang = NULL,
  pptx = getOption("faofishingreport.pptx", FALSE),
  plot_show = fao_setting("plot_show"),
  label = NULL
)

参数

area_data
FAO渔获数据：fishing_area_data()$area_data，或load_fao_data()的任意子集（例如一个国家，或几个渔区）。
English FAO catch data: fishing_area_data()$area_data, or any subset of load_fao_data() (e.g. one country, or several fishing areas).
by
一条序列由什么构成：“species”（默认）或”country”。
English What a series is: “species” (default) or “country”.
detrend
“linear”（默认）表示去除每条序列的线性趋势，“none”表示不去除。
English “linear” (default) to remove a linear trend from each series, or “none”.
window
滑动窗口的长度（年）。默认为20。
English The length in years of the moving windows. Default is 20.
top_n
图表中显示的渔获量最大的序列数。默认为20。
English The number of series with the largest catch shown in the charts. Default is 20.
min_median, min_nonzero
序列的渔获量中位数须高于min_median吨/年，且有渔获量的年份须超过全部年份的min_nonzero。默认分别为10和0.75（Ong等，2021）。
English Series need a median catch above min_median tonnes a year and catch in more than min_nonzero of the years. Defaults are 10 and 0.75 (Ong et al. 2021).
plot
逻辑值。为TRUE（默认）时，图表保存在figures/png/summary/。
English A logical value. If TRUE (default), charts are saved in figures/png/summary/.
table
逻辑值。为TRUE（默认）时，表格保存在tables/。
English A logical value. If TRUE (default), tables are saved in tables/.
lang
图表文字和名称的语言：“en”（英文）、“zh”（中文）或”both”（中英双语）。默认为NULL，即使用fao_settings()设置的语言（未更改时为”en”）。
English The language of the chart text and names: “en” (English), “zh” (Chinese) or “both” (Chinese and English). Default is NULL, which uses the language set with fao_settings() (“en” unless changed).
pptx
逻辑值。为TRUE时，图表还另存为可编辑的PowerPoint文件，保存在figures/pptx/summary/。默认为FALSE，可以用fao_settings(pptx = TRUE)为所有函数统一更改。
English A logical value. If TRUE, charts are also saved as editable PowerPoint files in figures/pptx/summary/. Default is FALSE, which can be changed for all functions with fao_settings(pptx = TRUE).
plot_show
逻辑值。为TRUE时，每张图在保存的同时也画在绘图窗口中（例如RStudio的Plots窗格），便于立即查看。默认为FALSE，可以用fao_settings(plot_show = TRUE)为所有函数统一更改。无论是否显示，图表都会保存为文件（plot = TRUE）。
English A logical value. If TRUE, each chart is also drawn in the plot window (e.g. the Plots pane of RStudio) as it is saved, to look at it at once. Default is FALSE, which can be changed for all functions with fao_settings(plot_show = TRUE). The charts are saved as files (plot = TRUE) either way.
label
输出文件名中使用的名称。默认为数据所属的渔区（或国家）。
English The name used in the output file names. Default is the fishing area (or the country) of the data.

返回值

以不可见方式返回一个列表，包括summary（同步性、各项CV和组合效应）、series（每条序列的平均值、标准差和CV，其标准差占各序列标准差之和的比例sd_share_pct，以及其对总渔获量方差的贡献variance_contribution_pct：即该序列与总量的协方差除以总量的方差，缓冲总量波动的序列为负值）、windows（每个滑动窗口中的各项指标）和correlation（序列之间的两两相关系数）。

English

Invisibly, a list with summary (synchrony, CVs and portfolio effect), series (mean, standard deviation and CV of each series, the share of its standard deviation in the sum of the standard deviations, sd_share_pct, and its contribution to the variance of the total catch, variance_contribution_pct: its covariance with the total divided by the variance of the total, negative for a series that damps the total), windows (the measures in each moving window) and correlation (pairwise correlations of the series).

详细说明

序列的选取与Ong等（2021）相同：渔获量中位数高于min_median（10）吨/年，且超过min_nonzero（3/4）的年份有渔获量；by = "species"时，只使用鉴定到种的条目（Ong等剔除了其他类（miscellaneous）条目和”nei”（未另列明）条目）。每条序列都对年份做线性回归以去除趋势（与Ong等相同），因为趋势会使序列看起来同步（Lepš等，2019）；用detrend = "none"可保留趋势。根据各序列的标准差\sigma_i、总渔获量的标准差\sigma_T及其平均值m_T：

  • 同步性\phi = \sigma_T^2 / (\sum_i \sigma_i)^2，取值从0（波动完全相互抵消）到1（完全同步）（Loreau和de Mazancourt，2008，式9）；
  • 总渔获量的变异系数（CV）等于\sqrt{\phi}乘以各序列的加权平均CV，即\sum_i \sigma_i / m_T（Thibaut和Connolly，2013，式2—4）：同步性越低，总量越稳定；
  • 组合效应 =（各序列的平均CV - 总量的CV）/ 总量的CV × 100（Ong等，2021，依据Carlson和Satterthwaite，2011）：单条序列的变异性比它们的总量高出多少，以百分比表示。

同样的指标还在长度为window年的滑动窗口中计算（在每个窗口内去除线性趋势，这是本包的设定），以显示同步性随时间的变化。Ong等（2021）用小波相干（wavelet coherence）衡量同步性，可以区分不同的时间尺度；本函数使用的是上述较简单的、基于相关的指标。

English

Series are chosen as by Ong et al. (2021): the median catch is above min_median (10) tonnes a year and more than min_nonzero (3/4) of the years have catch; with by = "species", only items identified to species are used (Ong et al. left out miscellaneous and “nei” items). Each series is detrended with a linear regression on year (as by Ong et al.), since trends make series look synchronous (Lepš et al. 2019); use detrend = "none" to keep them. From the standard deviations \sigma_i of the series, the standard deviation \sigma_T of the total catch and its mean m_T:

  • synchrony \phi = \sigma_T^2 / (\sum_i \sigma_i)^2, from 0 (fluctuations fully compensate each other) to 1 (perfectly synchronous) (Loreau and de Mazancourt 2008, eq. 9);
  • the coefficient of variation (CV) of the total catch equals \sqrt{\phi} times the weighted mean CV of the series, \sum_i \sigma_i / m_T (Thibaut and Connolly 2013, eqs. 2-4): the lower the synchrony, the more stable the total;
  • portfolio effect = (mean CV of the series - CV of the total) / CV of the total x 100 (Ong et al. 2021, after Carlson and Satterthwaite 2011): how much more variable the single series are than their total, in percent.

The same measures are computed in moving windows of window years (linear trend removed in each window, a choice of this package) to show how synchrony changed over time. Ong et al. (2021) measured synchrony with wavelet coherence, which separates time scales; this function uses the simpler correlation-based measures above.

参考文献

Carlson, S.M. and Satterthwaite, W.H. (2011). Weakened portfolio effect in a collapsed salmon population complex. Canadian Journal of Fisheries and Aquatic Sciences 68: 1579-1589. doi:10.1139/f2011-084

Lepš, J., Götzenberger, L., Valencia, E. and de Bello, F. (2019). Accounting for long-term directional trends on year-to-year synchrony in species fluctuations. Ecography 42: 1728-1741. doi:10.1111/ecog.04528

Loreau, M. and de Mazancourt, C. (2008). Species synchrony and its drivers: neutral and nonneutral community dynamics in fluctuating environments. American Naturalist 172: E48-E66. doi:10.1086/589746

Ong, J.J.L., Walter, J.A., Jensen, O.P. and Pinsky, M.L. (2021). Global hotspots of coherent marine fishery catches. Ecological Applications 31: e02321. doi:10.1002/eap.2321

Thibaut, L.M. and Connolly, S.R. (2013). Understanding diversity-stability relationships: towards a unified model of portfolio effects. Ecology Letters 16: 140-150. doi:10.1111/ele.12019

示例 

FAO27 <- fishing_area_data("Atlantic, Northeast", plot = FALSE)
catch_synchrony(FAO27$area_data, lang = "zh")
catch_synchrony(FAO27$area_data, by = "country", window = 15)