Dynamics-based characterisation and classification of biodiversity indicators
Data files
Jun 19, 2023 version files 36.12 KB
-
otomi_class.csv
-
otomi_cod.csv
-
otomi_fish_community_2012_2019.csv
-
README.md
Abstract
Various biodiversity indicators, such as species richness, total abundance, and species diversity indices, have been developed to capture the state of ecological communities over space and time. As biodiversity is a multifaceted concept, it is important to understand the dimension of biodiversity reflected by each indicator for successful conservation and management. Here we utilised the responsiveness of biodiversity indicators’ dynamics to environmental changes (i.e. environmental responsiveness) as a signature of the dimension of biodiversity. We present a method for characterising and classifying biodiversity indicators according to environmental responsiveness and apply the methodology to monitoring data for a marine fish community under intermittent anthropogenic warm water discharge. Our analysis showed that ten biodiversity indicators can be classified into three super-groups based on the dimension of biodiversity that is reflected. Group I (species richness and community mean of centre of distribution latitude (cCOD)) showed the greatest robustness to temperature changes; Group II (species diversity and total abundance) showed an abrupt change in the middle of the monitoring period, presumably due to a change in temperature; Group III (species evenness) exhibited the highest sensitivity to environmental changes, including temperature. These results had several ecological implications. First, the responsiveness of species diversity and species evenness to temperature changes might be related to changes in the species abundance distribution. Second, the similar environmental responsiveness of species richness and cCOD implies that fish migration from lower latitudes is a major driver of species compositional changes. The study methodology may be useful in selecting appropriate indicators for efficient biodiversity monitoring.
Methods
A long-term monitoring dataset for a marine fish community on the coast of Uchiura Bay (35 °32' N, 135 °30' E) was used. The monitoring area was located 2 km from the discharge outlet of the Takahama Nuclear Power Plant (NPP). The Takahama NPP started operation in 1974 and was shut down for two periods: 4 years from February 2012 to January 2016, and 14 months from March 2016 to May 2017 (Kansai Electric Power Group 2021). During operation, Takahama NPP drains a maximum thermal discharge of 238 m3s-1, which is 7 °C higher than the water temperature in the natural environment (Kokaji 1995). As a result, the temperature increase in the survey area due to the NPP operation is approximately 2 °C (Masuda 2020).
Abundance data for each fish species were obtained by direct visual underwater surveys, covering an area of approximately 1200 m2 (2 m wide by 600 m long). These surveys were conducted once a month from January 18, 2012, to April 26, 2019. The fish identification procedure followed that described by Nakabo et al. (2013). The survey method was previously described by Masuda (2020).
Data were obtained at 88 time-points over 7 years. A total of 95 fish species were recorded during the survey periods (Figure 1: Examples of fish species observed in the survey). Using time-series data, ten biodiversity indicators were calculated for each survey, including species richness (i.e., number of species), relative abundance of species, and differences in fish taxonomy and geographic distribution.
Usage notes
One of the R packages used for the regularised S-map analysis is available on GitHub (https://github.com/somanyfrogs/density_dependent_study/tree/main/rpkg).