Incorporating reef fish avoidance behavior improves accuracy of species distribution models

Abstract

Species distribution models (SDMs) are used to interpret and map fish distributions based on habitat variables and other drivers. Reef fish avoidance behavior has been shown to vary in the presence of divers and is primarily driven by spearfishing pressure. Diver avoidance behavior or fish wariness may spatially influence counts and other descriptive measures of fish assemblages. Because fish assemblage metrics are response variables for SDMs, measures of fish wariness may be useful as predictors in SDMs of fishes targeted by spearfishing. We used a diver operated stereo-video system to conduct fish surveys and record minimum approach distance (MAD) of targeted reef fishes inside and outside of two marine reserves on the island of Oʻahu in the main Hawaiian Islands. By comparing MAD between sites and management types we tested the assumption that it provides a proxy for fish wariness related to spearfishing pressure. We then compared the accuracy of SDMs which included MAD as a predictor with SDMs that did not. Individual measures of MAD differed between sites though not management types. When included as a predictor, MAD averaged at the transect level greatly improved the accuracy of SDMs of targeted fish biomass.

Depth as a fish refuge from spearfishing at Rapa Nui: Flight behaviour in the Pacific rudderfish Kyphosus sandwicensis

“…Many factors can influence fish flight behaviour in response to divers, such as the proximity to refuges, heritable and comprehensive learning, reproductive status, the current activity of an individual, the angle and initial distance at which the diver began the chase, or the fish size (Stamoulis et al, 2020). In this study, fish size did not have a significant effect on the flight behaviour of the species studied.…”

“…were the main variables of interest in this research; however, fish body length (covariate) and starting distance (factor, two levels: 1-3 m and >3 m) were also included as fixed effects in the model as they have previously been reported to influence fish escape behaviour (Stamoulis et al, 2019;Stamoulis et al, 2020). Date was also included in the model as a random factor to account for any temporal effect on FID.…”

“…Analyses were complemented by Tukey’s Honestly Significant Difference (HSD) tests with pairwise comparisons of factor levels, when applicable. Islands (factor, two levels: Rapa Nui and Isla Salas y Gómez), sites (factor, four levels: Motu Nui, Poike, Pirámide, and MMHMP), and depth strata (factor, two levels: shallow and deep) were the main variables of interest in this research; however, fish body length (covariate) and starting distance (factor, two levels: 1–3 m and >3 m) were also included as fixed effects in the model as they have previously been reported to influence fish escape behaviour (Stamoulis et al, 2019; Stamoulis et al, 2020). Date was also included in the model as a random factor to account for any temporal effect on FID.…”

“…This can affect fish assemblages through the modification of the size and age structure of target species, changes in fish assemblage composition, decreases in abundance and biomass of target species, and modifications in fish behaviour (e.g. time invested in foraging behaviour or reproductive activities) (Godoy et al, 2010; Lindfield et al, 2015; Cooke et al, 2017; Stamoulis et al, 2020).…”

Trends in sightings of the stingrays of southern Mozambique

“…However, it is important to point out that the variable number of divers and researchers in the diving group could affect the number of stingrays detected per diving trip. Collecting observational data while near to a commercial dive group of mixed diving experience could negatively influence the sightings of stingrays, because they could be disturbed and swim away from a novice diver before being seen by a researcher (Stamoulis et al 2020). Also, it could be assumed that with a larger dive group, it would be more likely that stingrays would be sighted.…”