Citizen science in the marine environment: estimating common dolphin densities in the north-east Atlantic

Abstract

Background Citizen science is increasingly popular and has the potential to collect extensive datasets at lower costs than traditional surveys conducted by professional scientists. Ferries have been used to collect data on cetacean populations for decades, providing long-term time series for monitoring of cetacean populations. One cetacean species of concern is the common dolphin, which has been found stranded around the north-east Atlantic in recent years, with high numbers on French coasts being attributed to fisheries bycatch. We estimate common dolphin densities in the north-east Atlantic and investigate the ability of citizen science data to identify changes in marine mammal densities and areas of importance. Materials and Methods Data were collected by citizen scientists on ferries between April and October in 2006–2017. Common dolphin sightings data from two ferry routes across three regions, Bay of Biscay (n = 569); south-west United Kingdom to the Isles of Scilly in the Celtic Sea (n = 260); and English Channel (n = 75), were used to estimate density across ferry routes. Two-stage Density Surface Models accounted for imperfect detection, and tested the influence of environmental (chlorophyll a, sea surface temperature, depth, and slope), spatial (latitude and longitude) and temporal terms (year and Julian day) on occurrence. Results Overall detection probability was highest in the areas sampled within the English Channel (0.384) and Bay of Biscay (0.348), and lowest on the Scilly’s route (0.158). Common dolphins were estimated to occur in higher densities on the Scilly’s route (0.400 per km2) and the Bay of Biscay (0.319 per km2), with low densities in the English Channel (0.025 per km2). Densities on the Scilly’s route appear to have been relatively stable since 2006 with a slight decrease in 2017. Densities peaked in the Bay of Biscay in 2013 with lower numbers since. Densities in the English Channel appear to have increased over time since 2009. Discussion This study highlights the effectiveness of citizen science data to investigate the distribution and density of cetaceans. The densities and temporal changes shown by this study are representative of those from wider-ranging robust estimates. We highlight the ability of citizen science to collect data over extensive periods of time which complements dedicated, designed surveys. Such long-term data are important to identify changes within a population; however, citizen science data may, in some situations, present challenges. We provide recommendations to ensure high-quality data which can be used to inform management and conservation of cetacean populations.

The Role of Climate, Oceanography, and Prey in Driving Decadal Spatio-Temporal Patterns of a Highly Mobile Top Predator

“…The annual abundances of common dolphin predicted for the study area were then analyzed by means of a linear regression to identify significant temporal trends and compared by means of a correlation test with an observed abundance index to check model fit. The observed abundance index was based on the encounter rate (individuals/km) of common dolphin estimated from monthly at-sea observations taken by a team of experienced observers in a constant effort-based systematic sampling scheme, i.e., the Pride of Bilbao ferry (Louzao et al, 2015;Robbins et al, 2020). This survey consistently crosses the BoB using the same route every year (Figure 1), and although it was also used as input for the baseline model, it only forms the 8% of the whole data set.…”

Likely year-round presence of beaked whales in the Bay of Biscay

“…Data collection followed established methods (Matear et al, 2019;Robbins et al, 2019Robbins et al, , 2020 in…”

“…Data on environmental conditions (e.g. sea state or precipitation), vessel location ('effort' data), and sightings data on cetacean occurrence were collected from the bridge of the Pont-Aven (21.6 m height) at the front of the vessel, with a team of four trained observers following distance sampling methodologies outlined in Robbins et al (2020). Data were collected from March to October between 2006 and 2017, for as long as daylight hours allowed for one return crossing approximately once per month, between Plymouth-Santander-Portsmouth only.…”

Modeling Fine-Scale Cetaceans’ Distributions in Oceanic Islands: Madeira Archipelago as a Case Study

“…Lately, several studies found that non-traditional data sources (such as opportunistic or citizen science data; e.g., Catlin-Groves, 2012;Embling et al, 2015) can be a cost-effective solution to overcome some of the challenges mentioned, allowing to produce relatively accurate cetacean abundance and distributional estimates (e.g., Fernandez et al, 2018;Robbins et al, 2019). When studying species in dynamic habitats, opportunistic surveys (and citizen science) can have many advantages over traditional methods.…”