Predator stomach contents can provide accurate indices of prey biomass

Abstract

Diet-based annual biomass indices can potentially use predator stomach contents to provide information about prey biomass and may be particularly useful for species that are otherwise poorly sampled, including ecologically important forage fishes. However, diet-based biomass indices may be sensitive to underlying ecological dynamics between predators and prey, such as predator functional responses and changes in overlap in space and time. To evaluate these factors, we fit spatio-temporal models to stomach contents of five Atlantic herring (Clupea harengus) predators and survey catch data for predators and Atlantic herring. We identified drivers of variation in stomach contents, evaluated spatial patterns in stomach content data, and produced predator-specific indices of seasonal Atlantic herring biomass. After controlling for spatio-temporal processes and predator length, diet-based indices of biomass shared similar decadal trends but varied substantially between predators and seasons on shorter time scales. Diet-based indices reflected prey biomass more than prey availability, but weak correlations indicated that not all biological processes were controlled for. Results provide potential guidance for developing diet-based biomass indices and contribute to a body of evidence demonstrating the utility of predator diet data to provide information about relative prey biomass.

Accounting for a nonlinear functional response when estimating prey dynamics using predator diet data

“…Variability in prey distribution across space and time may be accounted for by using habitat covariates (e.g. bottom type, temperature) in a similar way to how covariates are added to delta models (Zuur et al., 2009) or by adding spatio‐temporal error structures (Ng et al., 2021). Similarly, incorporating covariates to account for variability in gut evacuation rates (e.g.…”

“…Staudinger et al., 2020). Since predators are often the main targets of research surveys and commercial harvests, they tend to be better sampled and their stomachs contents can be indicative of prey abundance/biomass (Dwyer et al., 2010; Link, 2004; Ng et al., 2021). For instance, trends in the frequency of occurrence of capelin and sand lance in fish predator stomachs contents in the Gulf of Alaska matched abundance estimates from research surveys and seabird diet data (Piatt et al., 2018).…”

Trophic importance of small pelagic fish to marine predators of the Mediterranean Sea

“…This is of particular interest in the current situation of global change, as not all SPF species or their predators are responding in the same way to environmental change and may be spatially heterogeneous. Thus, monitoring predator responses to those changes can be of great value to assess SPF populations and the health of the marine ecosystems, as has been demonstrated in the Northwest Atlantic (Ng et al 2021). This can be particularly challenging due to predator−prey, species-specific differences in response to environmental change, but could be achieved by routinely monitoring particular species (e.g.…”

“…In this study, we faced some challenges and limitations. First, there are inherent biases and limitations when using stomach content data, as most studies are often conducted on relatively small scales and with a limited number of species, which leads to patchiness in data collection (Ng et al 2021, but see Eriksen et al 2020). Also, we only gathered data on %W in order to have a common metric to compare across the basin.…”

Using the diet of fish to reflect spatial patterns of their benthic prey

“…An alternative to scientific surveys has been to collect information from the principal foragers of marine ecosystems, including fishers (Marchal et al 2003, Maunder and Punt 2004, Bourdaud et al 2017), but also other marine predators. Foraging fish are thus considered adequate biological samplers and their digestive tracts (DT) have been examined to infer the spatial and/or temporal dynamics of various prey, including fishes (Fahrig et al 1993, Ng et al, 2021, crustaceans (Lasley-Rasher et al 2015), cephalopods (Staudinger et al 2013), common gelatinous invertebrates (Link & Ford 2006), benthic invertebrates (Frid & Hall 1999, Link 2004, Smith et al 2013, or a combination of these (Dwyer et al 2010). These diet-based studies provide valuable information on the distribution of a variety of species which could otherwise not have been collected by traditional sampling.…”