Large-scale seabird community structure along oceanographic gradients in the Scotia Sea and northern Antarctic Peninsula

Summary

This study used cruise ships as observation platforms to survey seabird communities across the Scotia Sea and Antarctic Peninsula during 2019-2020. The research analyzed species composition, population density, and species diversity in relation to environmental factors using 636 standardized survey strips covering 690 square kilometers. Twenty-eight different taxonomic groups were observed during the surveys.Ocean surface temperature and distance from shore were the most important factors determining seabird distribution, with communities showing geographic separation rather than concentrated hotspots.The research demonstrates that large-scale oceanographic features structure seabird communities through their influence on prey distribution and availability. The study also establishes that cruise vessels can serve as cost-effective platforms for ecosystem monitoring when combined with dedicated research surveys.

Map of the study area showing average positions of major ocean current boundaries and cruise ship survey routes marked as black lines. Map created using Quantarctica mapping software (Matsuoka et al., 2021) and associated datasets (Orsi et al., 1995; Amante & Eakins, 2009; NOAA National Geophysical Data Center, 2009; Arndt et al., 2013; Liu et al., 2015, SCAR Antarctic Digital Database) in QGIS mapping software (QGIS.org, 2019).

Key Findings

Ocean surface temperature and distance from shore explained 13.8% of the variation in seabird community composition.

Species diversity peaked at 3°C ocean surface temperature and decreased with greater distance from the coast.

Geographic separation of communities was clear: Antarctic Peninsula areas had ice-associated species, Falkland Islands had temperate species, with varying open ocean communities between regions.

Cruise vessels provided a cost-effective monitoring platform for observing large-scale distribution patterns.

Seabird communities were structured by ocean water characteristics and food availability patterns.

Abstract

The Scotia Sea and Antarctic Peninsula are warming rapidly and changes in species distribution are expected. In predicting habitat shifts and considering appropriate management strategies for marine predators, a community-level understanding of how these predators are distributed is desirable. Acquiring such data, particularly in remote areas, is often problematic given the cost associated with the operation of research vessels. Here we use cruise vessels as sampling platforms to explore seabird distribution relative to habitat characteristics. Data on seabird at-sea distribution were collected using strip-transect counts throughout the Antarctic Peninsula and Scotia Sea in the austral summer of 2019-2020. Constrained correspondence analysis (CCA) and generalized additive models (GAM) were used to relate seabird community composition, density, and species richness to environmental covariates. Species assemblages differed between oceanographic areas, with sea surface temperature and distance to coast being the most important predictors of seabird distribution. Our results further revealed a geographic separation of distinct communities rather than hotspot regions in the study area in summer. These findings highlight the importance of large-scale environmental characteristics in shaping seabird community structure, presumably through underlying prey distribution and interspecific interactions. The present study contributes to the knowledge of seabird distribution and habitat use as well as the baseline for assessing the response of Antarctic seabird communities to climate warming. We argue that cruise vessels, when combined with structured research surveys, can provide a cost-effective additional tool for the monitoring of community and ecosystem level changes.

Published in

Frontiers in Marine Science

2023

Authors

Ollus, V. M. S., Biuw, M., Lowther, A., Fauchald, P., Deehr Johannessen, J. E., Martín López, L. M., Gkikopoulou, K. C., Oosthuizen, W. C., Lindstrøm, U.

Institutions

UiT The Arctic University of Norway, Department of Arctic and Marine BiologyDepartment of Arctic Ecology, Norwegian Institute for Nature ResearchNorwegian Institute of Marine Research, Marine Mammal Research GroupNorwegian Polar InstituteAsociación Ipar PerspectiveSea Mammal Research Unit, Scottish Ocean Institute, University of St AndrewsCenter for Statistics in Ecology, Environment and Conservation, Department of Statistical Sciences, University of Cape Town

Methods

Biological sampling DataField

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