Publications

In boreal and subarctic regions, sea ice scouring increases benthic heterogeneity of shallow coastal ecosystems. The ice foot can trap eelgrass (Zostera marina) leaves and sediments, and, as it breaks, patches of vegetation are either displaced or destroyed, creating a mosaic of vegetated and bare sediment habitats. This spatial heterogeneity reflects on environmental differences where biodiversity and ecosystem functioning (BEF) relationships can diverge. This study aims to explore the relationships between biodiversity and functioning in the boreal ice-scoured eelgrass meadow of Rimouski Bay (Québec, Canada). We assessed changes in diversity of the macrobenthic community and ecosystem functioning (based on carbon, oxygen, and nutrient fluxes) in 9 bare sediment and 9 vegetated cores sampled from the meadow, over a 20-day experiment. We hypothesized that bare sediment would exhibit lower species density, richness, and community functioning than vegetated habitats. Indeed, the absence of the foundation species Z. marina resulted in a less diverse macrofaunal community, as abundant in both habitats tough. During immersion, net community production and respiration were five-times higher in vegetated cores at the beginning of the experiment. However, this gap decreased by two throughout the experiment due to the natural recruitment of green algae (Ulva) and its functional redundancy in primary production. However, the non-perennial nature of Ulva questions functional redundancy all year long continuity, showing the need to integrate seasonal fluctuations in biodiversity and functioning assessment informing BEF theory.

Early life stages play a critical role in shaping recruitment dynamics and population structure in marine fishes, with implications for conservation and resource management. After declining in the 1950s, Atlantic halibut (Hippoglossus hippoglossus (Linnaeus, 1758)) in the Gulf of St. Lawrence (GSL), Canada, has shown a marked comeback since the early 2000s, now ranking as the most valuable groundfish resource. Given its socio-economic importance, understanding larval ecology and early life stages is key to sustainable management. Spawning occurs in deep GSL channels and individuals exhibit summer site fidelity. Recently, otolith chemistry provided insights into lifetime movements and revealed three migratory contingents: annual migrants, irregular migrants, and residents. We analyzed the cores of 187 otoliths from halibut with known migration histories using laser ablation inductively coupled plasma mass spectrometry to quantify the number of nurseries and their contributions to the stock. To assess temporal trends, we examined four cohorts (2006, 2007, 2009, and 2010). Our findings suggest that Atlantic halibut in the GSL forms a philopatric population with multiple nurseries, and that natal origin does not influence later migration strategies. Given the role of early life stages in stock recruitment, these insights enhance our understanding of natal sources and support more informed management strategies.

The analysis of a short sediment core retrieved from the Bay of Sept-Îles, a high-use coastal region in Québec, Canada, provided information on changes in geochemical composition and foraminiferal assemblages during the pre- and post-industrial period in this region (i.e., before and after 1950 CE). The vertical distribution of the major elements suggests that the effects of anthropogenic industrial activities in Sept-Îles began to be felt in the mid- 1960s. Results showed fluctuations in metal concentrations, with notable shifts in iron (Fe), manganese (Mn), and calcium (Ca) levels between the pre- and post-industrial periods, accompanied by a shift from calcareous to agglutinated foraminifera. This points to a stressful environment for the calcareous species, potentially influenced by factors such as calcium limitation and carbonate dissolution. Overall, the findings show that none of the element concentrations are above the contamination threshold but the escalation in the relative prevalence of metals, especially iron, demands careful consideration, as it potentially signifies alterations within the environmental conditions.

Many species of fishes around the world are soniferous. The types of sounds fishes produce vary among species and regions but consist typically of low-frequency (<1.5 kHz) pulses and grunts. These sounds can potentially be used to monitor fishes non-intrusively and could complement traditional monitoring techniques. However, the significant time required for human analysts to manually label fish sounds in acoustic recordings does not yet allow passive acoustics to be used as a viable tool for monitoring fishes. In this paper, we compare two different approaches to automatically detect fish sounds. One is a more traditional machine learning technique based on the detection of acoustic transients in the spectrogram and the classification using Random Forest (RF). The other is using a deep learning approach and is based on the classification of overlapping segments (0.2 s) of spectrogram using a ResNet18 Convolutional Neural Network (CNN). Both algorithms were trained using 21,950 manually annotated fish and non-fish sounds collected from 2014 to 2019 at five different locations in the Strait of Georgia, British Columbia, Canada. The performance of the detectors was tested on part of the data from the Strait of Georgia that was withheld from the training phase, data from Barkley Sound, British Columbia, and data collected in the Port of Miami, Florida, United States. The CNN performed up to 1.9 times better than the RF (F1 score: 0.82 vs. 0.43). In some cases, the CNN was able to find more faint fish sounds than the analyst and performed well in environments different from the one it was trained in (Miami F1 score: 0.88). Noise analysis in the 20–1,000 Hz frequency band shows that the CNN is still reliable in noise levels greater than 130 dB re 1 μPa in the Port of Miami but becomes less reliable in Barkley Sound past 100 dB re 1 μPa due to mooring noise. The proposed approach can efficiently monitor (unidentified) fish sounds in a variety of environments and can also facilitate the development of species-specific detectors. We provide the software FishSound Finder, an easy-to-use open-source implementation of the CNN detector with detailed documentation.

Benthic foraminifera are useful bioindicators of heavy metal and organic enrichment in northern temperate coastal zones: An executive summary review. In: Phillips, M.R.; AlNaemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 926-930. Charlotte (North Carolina), ISSN 0749-0208.

Connections among habitat patches through propagule dispersal are critical for designing effective networks of marine protected areas. To meet targets, managers need a diverse toolkit for…