Volatility in coral cover erodes niche structure, but not diversity, in reef fish assemblages

Environmental fluctuations are becoming increasingly volatile in many ecosystems, highlighting the need to better understand how stochastic and deterministic processes shape patterns of commonness and rarity, particularly in high-diversity systems like coral reefs. We analyzed reef fish time-series across the Great Barrier Reef to show that approximately 75% of the variance in relative species abundance is attributable to deterministic, intrinsic species differences. Nevertheless, the relative importance of stochastic factors is markedly higher on reefs that have experienced stronger coral cover volatility. By contrast, alpha-diversity and species composition are independent of coral cover volatility but depend on latitudinal and cross-shelf position gradients. Our findings imply that increased environmental volatility on coral reefs erodes assemblage's niche structure and temporal stability in fish abundances, an erosion that is not detectable from static measures of biodiversity.Archived file name: "Tsai_etal_2022_ScienceAdvances_archive.RData" 1. "Tsai_etal_sumzdata": Reef fish community structure variables and environmental variables across 40 reefs are stored as R data.frame object. Within this data.frame object, the reef IDs ("reefID"), latitude ("lat"), cross-shelf position ("shelf"), mean coral cover ("mC"), and standard deviation ("sdC") and log-standard deviation ("logsdC") in coral cover, (time-averaged) Poisson-lognormal estimated richness ("plnRichness"), (time-averaged) Poisson-lognormal estimated unevenness ("plnUnevenness"), and VPRSA variance components due to persistent species differences ("Vr"), stochastic fluctuations ("Ve"), and overdispersion (demographic/sampling stochasticity) ("Vd") are recorded. A transformed shelf position, 1 - "shelf", was used for the piecewise SEM analysis in the MS. 2. "AIMSLTMPfishcomm.list" and "AIMSLTMPfishcomm.list.reefID": We extracted and compiled the community dynamics data of LTMP from 1994 to 2004 (11 years) for analyses. We pooled fish community and coral cover data at the scale of the entire reef, summing species abundances over all 15 transects laid on each reef. Percentage living hard coral cover is averaged across transects and sites within reefs. We adopted this approach to reduce stochastic sampling error, thereby obtaining more precise estimates of the community structure statistics that are of interest. Because the small-sized fish taxa (mainly Pomacentridae) were surveyed in narrower transects than other, larger fish taxa, we used subsampling (Poisson samples) to rescale the abundances of large-sized species to standardize sampling effort. Each fish counted on the wider transects was given a 20% probability of appearing in the sub-sample (because the small-fish transects cover only 20% of the area of large-fish transects). Sub-sampled data were used for the analyses.Compiled data were extracted from 40 reefs from 1994 to 2004 (11 years) from the Australian Institute of Marine Science's Long-Term Monitoring Program (LTMP), which has made visual surveys of benthos and fish communities on reefs spanning 10 degrees of latitude on the Great Barrier Reef for more than 20 years. The surveys themselves were hierarchically structured: 3 sites on the reef slope at approximately 6-9m depth were selected, usually on the NE faces of each reef. At each site, five permanently marked 5m × 50m transects were established for censusing larger, noncryptic fishes. Smaller damselfishes, which were counted on 1m × 50m sections of the same transects. Transects were separated by about 10m. Counts of fish were identified to species and on percentage cover of living hard coral at each survey reef. Fish species from a prescribed list of species representing 13 families were counted visually. Families were Pomacentridae, Acanthuridae, Serranidae, Lutjanidae, Scaridae, Caesionidae, Chaetodontidae, Labridae, Lethrinidae, Haemulidae, Holocentridae, Siganidae, and Zanclidae. All species examined here were largely non-cryptic and easily identified underwater, and thus cryptic species groups, such as gobies, were excluded. A full list of species observed each year was included in the appendices of each LTMP status report. Corals were identified into broad taxonomic and morphological categories, but we considered only total hard coral cover. We pooled fish community and coral cover data for each reef, summing abundances over all 15 transects surveyed at each reef. Percentage cover was similarly averaged across transects and sites within reefs. We adopted this approach to reduce stochastic sampling error. Because the small-sized fish taxa (mainly Pomacentridae) were surveyed in narrower transects than other larger fish taxa, we used subsampling to rescale the abundances of large-sized species to standardize sampling effort. Each fish counted on the wider transects was given a 20% probability of appearing in the sub-sample (because the small-fish transects covered only 20% of the area of large-fish transects). For each reef, we extracted the temporal average (11-yr mean) and standard deviation (SD) in coral cover as proxies for disturbance-mediated coral cover fluctuations. We also extracted each reef's latitude and cross-shelf position, where latitude was measured by degrees from the equator and cross-shelf position was the standardized distance to the nearest continental shelf boundary (i.e., 0 represents the shelf boundary and 1 represents the coast, respectively)