DOI: 10.5061/dryad.31zcrjdrz
title: Data from: Direct and indirect effects of a fishing ban on lacustrine fish community do not result in a full recovery

description: Protected areas are increasingly being promoted as an important means of
 protecting freshwater biological diversity and ecological processes. A
 robust assessment of ecological changes in protected areas is fundamental
 to optimize conservation policies and adaptive management. China's
 efforts to establish aquatic reserves have attracted worldwide attention,
 especially the "10-year fishing ban" implemented in the Yangtze
 River basin. We focused on Liangzi Lake, a freshwater protected area in
 the Yangtze River basin, to understand the effect of a fishing ban
 occurring after a short period of overfishing. In this aim, the time
 series of fish community taxonomic and functional structure encompassing
 the overfishing period and a post-ban period have been analyzed. Fish
 community metrics with direct, indirect, and no responses to fishing bans
 were identified. The results indicate that in the early period of the
 fishing ban, the trophic level and body size structure of the fish
 community were in the way of recovery. However, species that prefer
 benthic habitats did not recover after fishing-induced habitat
 degradation. Functional traits were more sensitive than taxonomic indices
 and revealed subtle community changes, such as the recovery of some
 ecological functions, despite a non-recovering species richness. Synthesis
 and applications. This study provides a rare case of a freshwater
 protected area in which the effects of conservation measures are studied
 with a temporal survey. The effectiveness of the functional trait approach
 in the application of protected area assessment was demonstrated by
 revealing the recovery of trophic level and body size structure of fish
 communities after the implementation of the fishing ban and the inadequacy
 of habitat restoration efforts. We suggest that in freshwater protected
 areas, insistence on a fishing ban is necessary but not sufficient for
 full biodiversity recovery, and other measures are needed, such as habitat
 restoration and species-focused stocking.
description: Field surveys were conducted
 four times a year (April-spring; July-summer; October-autumn;
 January-winter) from April 2016 to January 2022 for a total of 24 sampling
 occasions. At each sampling occasion, fish were collected at eight sites
 along the littoral zone of Liangzi Lake. For each
 site, we collected fish using two multi-mesh
 gillnets, one benthic and one pelagic. This standard multi-mesh gillnet
 measuring 30 m in length and 2.0 m in height (modified from European
 standard methods, CEN,
 2015), has 12 panels (2.5
 × 2 m) with respective mesh sizes of 5, 6.25, 8, 10, 12.5, 15.5, 19.5, 24,
 30, 35, 43 and 55 mm. The gillnets were set in the afternoon (approx.
 18:00) and harvested in the following morning (approx. 6:00) for three
 days in a row (36 h of sampling in total). All fish collected were
 individually identified with species (Department of Ichthyology, Institute of
 Hydrobiology, CAS 1976),
 counted and weighed at 0.01 g. The scientific names of the 45 species
 collected (Table S3) were updated according to FishBase
 (Froese &
 Pauly
 2021). No fieldwork
 permits and ethics approvals were required.
 Functional traits were
 classified into three trait categories reflecting the life history
 strategy (11
 traits), feeding (5
 traits) and habitat use (6
 traits). We used six
 community metrics to describe the fish assemblage on each occasion and at
 each site of sampling. The
 metrics used cover three aspects of fish community information, community
 size, taxonomic diversity, and functional diversity. Community size (total
 number of individuals, total biomass) is often used to assess recovery of
 fish community productivity under fishing bans (Babcock et al. 2010; Coleman et al.
 2015). Total abundance and
 biomass of fish were expressed per unit effort, number of individuals
 m<sup>-2</sup> h<sup>-1</sup> (NPUE) and
 g m<sup>-2</sup> h<sup>-1</sup> (BPUE),
 respectively. Two taxonomic metrics, species richness (SRic) and inverse
 Simpson index (invsimpson) and two functional metrics, function richness
 (FRic) and Rao’s quadratic entropy (RaoQ) were calculated.
 Functional richness represents the volume of the minimum convex hull
 filled by the community without considering the species abundances
 (Villéger et al.
 2008). Rao’s quadratic
 entropy is an index of functional diversity based on the sum of squared
 distances among all species in the multidimensional functional space
 (Botta-Dukát
 2005). RaoQ is not
 affected by species richness but is sensitive to species relative
 abundances used as weight for pairwise distances into functional
 space. All analyses in
 this study were performed in R version 4.2.0 (R Core Team 2022). The function <em>dpFD</em> of
 package “FD” was used to calculate the functional richness and Rao’s
 quadratic entropy (Laliberté et al. 2014).