Optimal sampling effort required to characterize wetland fish communities

Abstract

Wetlands are increasingly in peril as a result of human activities. In the Laurentian Great Lakes, coastal wetlands provide essential habitats for many fishes. Consequently, efficient sampling approaches for wetland fishes are needed for effective management. We employed a repeat-sampling strategy using a seine to collect fishes from seven wetlands. The data set was used to develop guidance for optimizing wetland fish sampling. To meet richness targets, the required number of sampling sites decreases as sampling intensity increases. Half the number of sites was required when three seine hauls per site were done compared with one haul. On average, 97 one-haul sites were required to detect 90% of species, whereas only 47 three-haul sites were required. Sampling effort is predicted to be greater in areas with more species and larger wetlands. The number of individuals and sites needed to detect 90% of species increased exponentially as species richness increased, and the number of individuals needed was positively related to wetland area. The use of block nets did not improve species detection or affect the composition.

The Effects of Sampling-Site Intervals on Fish Species Richness in Wadeable Rivers: A Case Study from Taizi River Basin, Northeastern China

“…This indicates that the greater the sampling effort, the more species are collected. Similar research has demonstrated that an increased sampling effort helps to collect more new species, but the chances of acquiring new species will gradually decrease [4,7,40]. For each river, the SACs of SS2 and SS3 had an asymptotic trend but did not reach the asymptotic level (Figure 1).…”

“…The adequacy of site numbers is often addressed in terms of sampling goals. In previous studies, sampling effort was quantified at different levels, typically ranging from 75% to 95% of the species target [7,10,41]. We quantified the number of sites required to capture 80% to 90% of species targets.…”

“…Fish richness is partially affected by sampling effort, so it is important to prioritize sampling efficiency in survey designs [3]. Some studies have revealed that fish richness rises rapidly with increasing sampling effort, but the number of new species collected by further sampling gradually declines, which is known as the accumulation curve of species richness [4][5][6][7]. The smaller number of sampling locations greatly underestimates the fish species richness of a river or region, but a greater number of sampling locations does not obtain an infinite number of new species, resulting in unnecessary waste [8].…”

“…Fischer and Paukert [5] suggested that more sites and shorter sampling lengths were needed to assess the estimated fish richness with a lower total sampling effort. Samarasin et al [7] also determined that more sites were required to meet fish richness targets when decreasing sampling intensity (i.e., one seine haul replaced three hauls). Because the sampling intensity on a site is strictly regulated according to the fish protocols [16], the number of sampling sites is the key consideration to optimize sampling design in most cases.…”

Imperfect detection biases extinction‐debt assessments

“…The accuracy of ED estimates using S-A relationships could be improved through a combination of refined sampling and statistical analysis. Optimal sampling design should incorporate multiple gear types that may target different species (e.g., Haynes et al 2013;Wedderburn, 2018), seasonality (e.g., Rook, Mandrak, Reid, & Barnucz, 2016), and repeat sampling (Samarasin, Reid, & Mandrak, 2017). While our simulations were built on the assumption that all species have random, equal spatial distributions, species abundance and spatial aggregation can, in fact, influence survival and detectability, shaping the S-A curves (Cencini, Pigolotti, & Munoz, 2011;Yamaura et al, 2016) and, consequently, the magnitude of ED.…”