Chinstrap Penguins Research Articles

Comment on Krüger, L. Decreasing Trends of Chinstrap Penguin Breeding Colonies in a Region of Major and Ongoing Rapid Environmental Changes Suggest Population Level Vulnerability. Diversity 2023, 15, 327

Historical data on chinstrap penguin (Pygoscelis antarctica) breeding population sizes are sparse and sometimes highly uncertain, making it hard to estimate true population trajectories. Yet, information on population trends is desirable as changes in population size can help inform conservation assessments. Recently, Krüger (2023) (Diversity 2023, 15, 327) used chinstrap penguin nest count data to predict breeding colony size trends between 1960 and 2020, to estimate whether the level of population change within three generations exceeded IUCN Red List Criteria for “Vulnerable” populations. Chinstrap penguin population trends are an important research topic, but we caution that Krüger (2023)’s statistical analyses (intended to form the foundation for drawing valid, evidence-based inferences from sparse data) contain fundamental errors that invalidate that paper’s findings. We discuss oversights in several key steps (data processing, exploratory data analysis, model fitting, model evaluation, and prediction) of that paper’s analysis to help others detect and avoid some of the pitfalls associated with estimating population trends via mixed models. We also show through reanalysis that improved statistical modelling can yield better predictions of chinstrap penguin population trends, at least within the range of observed data. This case study highlights (1) the profound influence that seemingly minor differences in modelling procedures (both unintentional errors and other decisions) can have on predictions of population trends, and (2) the substantial inherent uncertainty in population trend predictions derived from sparse, heterogenous data.

Seasonal variation in the stomach microbiota of two sympatrically breeding Pygoscelis penguin species at Signy Island, South Orkney Islands.

The gut microbiomes of Antarctic penguins are important for the fitness of the host birds and their chicks. The compositions of microbial communities in Antarctic penguin guts are strongly associated with the birds' diet, physiological adaptation and phylogeny. Whilst seasonal changes in food resources, distribution and population parameters of Antarctic penguins have been well addressed, little research is available on the stability or variability of penguin stomach microbiomes over time. Here, we focused on two Pygoscelis penguin species breeding sympatrically in the maritime Antarctic and analysed their stomach contents to assess whether penguin gut microbiota differed over three austral summer breeding seasons. We used a high-throughput DNA sequencing approach to study bacterial diversity in stomach regurgitates of Adélie (Pygoscelis adeliae) and chinstrap (Pygoscelis antarctica) penguins that have a similar foraging regime on Signy Island (South Orkney Islands). Our data revealed significant differences in bacterial alpha and beta diversity between the study seasons. We also identified bacterial genera that were significantly associated with specific breeding seasons, diet compositions, chick-rearing stages and sampling events. This study provides a baseline for establishing future monitoring of penguin gut microbiomes in a rapidly changing environment.

Influence of migration range and foraging ecology on mercury accumulation in Southern Ocean penguins

In order to evaluate mercury (Hg) accumulation patterns in Southern Ocean penguins, we measured Hg concentrations and carbon (δ13C) and nitrogen (δ15N) stable isotope ratios in body feathers of adult Adélie (Pygoscelis adeliae), gentoo (Pygoscelis papua), and chinstrap (Pygoscelis antarctica) penguins living near Anvers Island, West Antarctic Peninsula (WAP) collected in the 2010/2011 austral summer. With these and data from Pygoscelis and other penguin genera (Eudyptes and Aptenodytes) throughout the Southern Ocean, we modelled Hg variation using δ13C and δ15N values. Mean concentrations of Hg in feathers of Adélie (0.09 ± 0.05 μg g−1) and gentoo (0.16 ± 0.08 μg g−1) penguins from Anvers Island were among the lowest ever reported for the Southern Ocean. However, Hg concentrations in chinstrap penguins (0.80 ± 0.20 μg g−1), which undertake relatively broad longitudinal winter migrations north of expanding sea ice, were significantly higher (P < 0.001) than those in gentoo or Adélie penguins. δ13C and δ15N values for feathers from all three Anvers Island populations were also the lowest among those previously reported for Southern Ocean penguins foraging within Antarctic and subantarctic waters. These observations, along with size distributions of WAP krill, suggest foraging during non-breeding seasons as a primary contributor to higher Hg accumulation in chinstraps relative to other sympatric Pygoscelis along the WAP. δ13C values for all Southern Ocean penguin populations, alone best explained feather Hg concentrations among possible generalized linear models (GLMs) for populations grouped by either breeding site (AICc = 36.9, wi = 0.0590) or Antarctic Frontal Zone (AICc = 36.9, wi = 0.0537). Although Hg feather concentrations can vary locally by species, there was an insignificant species-level effect (wi < 0.001) across the full latitudinal range examined. Therefore, feeding ecology at breeding locations, as tracked by δ13C, control Hg accumulation in penguin populations across the Southern Ocean.

Kinetic and equilibrium analysis of penguin guano trace elements release to Antarctic seawater and snow meltwater

The present work extends the scope of prior studies through analysis, modelling and simulation of the As, Cd, Co, Cu, Fe Mn, Mo, Ni and Zn release from Gentoo (Pygoscelis papua) and Chinstrap (Pygoscelis antarcticus) penguin guano to the Southern Ocean seawater and to Antarctic snow meltwater. Laboratory experimental results have been modelled considering kinetic processes between water and guano using two element pools in the guano compartment; its application allows us to interpret behaviours and predict release concentrations of dissolved trace elements from guano which are potentially useful for incorporation as elements source into biogeochemical models applied in the Southern Ocean. Variations in quantities and release patterns depending on the type of guano and aqueous medium in contact have been identified. The release percentages from the guano to the aqueous medium, once the steady state has been reached, vary depending on the water medium and guano type in the ranges of 100–2.9 % for Mo; 91.5–68.6 % for Ni; 81.8–22.8 % As; 52.0–43.9 % Cu; 26.9–7.4 % Mn; 24.9–5.4 for Co; 4.4–3.2 % for Zn and 0.94–0.51 % for Fe. Considering a penguin population of 774,000 Gentoo and 8,000,000 Chinstrap, the estimated annual mass released to the both seawater and freshwater would be ≈18,500 kg for Cu, ≈1710 kg for Zn, ≈1944 kg for Fe, ≈1640 kg for Mn, ≈499 kg for As, ≈289 kg for Ni, ≈155 kg for Mo, ≈36.7 kg for Cd and ≈8.1 kg for Co. These contributions can be locally significant both in promoting phytoplankton growth and in their role as inhibitors of primary productivity.

A method to estimate prey densityfrom single-camera images: A case study with chinstrap penguins and Antarctic krill.

Estimating the densities of marine prey observed in animal-borne video loggers when encountered by foraging predators represents an important challenge for understanding predator-prey interactions in the marine environment. We used video images collected during the foraging trip of one chinstrap penguin (Pygoscelis antarcticus) from Cape Shirreff, Livingston Island, Antarctica to develop a novel approach for estimating the density of Antarctic krill (Euphausia superba) encountered during foraging activities. Using the open-source Video and Image Analytics for a Marine Environment (VIAME), we trained a neural network model to identify video frames containing krill. Our image classifier has an overall accuracy of 73%, with a positive predictive value of 83% for prediction of frames containing krill. We then developed a method to estimate the volume of water imaged, thus the density (N·m-3) of krill, in the 2-dimensional images. The method is based on the maximum range from the camera where krill remain visibly resolvable and assumes that mean krill length is known, and that the distribution of orientation angles of krill is uniform. From 1,932 images identified as containing krill, we manually identified a subset of 124 images from across the video record that contained resolvable and unresolvable krill necessary to estimate the resolvable range and imaged volume for the video sensor. Krill swarm density encountered by the penguins ranged from 2 to 307 krill·m-3 and mean density of krill was 48 krill·m-3 (sd = 61 krill·m-3). Mean krill biomass density was 25 g·m-3. Our frame-level image classifier model and krill density estimation method provide a new approach to efficiently process video-logger data and estimate krill density from 2D imagery, providing key information on prey aggregations that may affect predator foraging performance. The approach should be directly applicable to other marine predators feeding on aggregations of prey.

Deep dive into the feeding habits of chinstrap penguins

Deep dive into the feeding habits of chinstrap penguins

Identifying prey capture events of a free-ranging marine predator using bio-logger data and deep learning.

Marine predators are integral to the functioning of marine ecosystems, and their consumption requirements should be integrated into ecosystem-based management policies. However, estimating prey consumption in diving marine predators requires innovative methods as predator-prey interactions are rarely observable. We developed a novel method, validated by animal-borne video, that uses tri-axial acceleration and depth data to quantify prey capture rates in chinstrap penguins (Pygoscelis antarctica). These penguins are important consumers of Antarctic krill (Euphausia superba), a commercially harvested crustacean central to the Southern Ocean food web. We collected a large data set (n = 41 individuals) comprising overlapping video, accelerometer and depth data from foraging penguins. Prey captures were manually identified in videos, and those observations were used in supervised training of two deep learning neural networks (convolutional neural network (CNN) and V-Net). Although the CNN and V-Net architectures and input data pipelines differed, both trained models were able to predict prey captures from new acceleration and depth data (linear regression slope of predictions against video-observed prey captures = 1.13; R 2 ≈ 0.86). Our results illustrate that deep learning algorithms offer a means to process the large quantities of data generated by contemporary bio-logging sensors to robustly estimate prey capture events in diving marine predators.

Lack of Highly Pathogenic Avian Influenza H5N1 in the South Shetland Islands in Antarctica, Early 2023.

In January 2023, an active surveillance initiative was undertaken in the South Shetland Islands, Antarctica, with the specific objective of ascertaining evidence for the presence of avian influenza, and specifically the highly pathogenic avian influenza virus subtype H5N1 (HPAIV H5N1). The investigation encompassed diverse locations, including Hanna Point (Livingston Island), Lions Rump (King George Island), and Base Escudero (King George Island), with targeted observations on marine mammals (southern elephant seals), flying birds (the kelp gull, snowy sheathbill and brown skua), and penguins (the chinstrap penguin and gentoo penguin). The study encompassed the examination of these sites for signs of mass mortality events possibly attributable to HPAIV H5N1, as well as sampling for influenza detection by means of real-time RT-PCR. Two hundred and seven (207) samples were collected, including 73 fecal samples obtained from the environment from marine mammals (predominantly feces of southern elephant seals), and 77 cloacal samples from penguins of the genus Pygoscelis (predominantly from the gentoo penguin). No evidence of mass mortality attributable to HPAIV H5N1 was observed, and all the collected samples tested negative for the presence of the virus, strongly suggesting the absence of the virus in the Antarctic territory during the specified period. This empirical evidence holds significant implications for both the ecological integrity of the region and the potential zoonotic threats, underscoring the importance of continued surveillance and monitoring in the Antarctic ecosystem.

Fungal and fungal-like diversity present in ornithogenically influenced maritime Antarctic soils assessed using metabarcoding.

We assessed soil fungal and fungal-like diversity using metabarcoding in ornithogenically influenced soils around nests of the bird species Phalacrocorax atriceps, Macronectes giganteus, Pygoscelis antarcticus, and Pygoscelis adelie on the South Shetland Islands, maritime Antarctic. A total of 1,392,784 fungal DNA reads was obtained and assigned to 186 amplicon sequence variants (ASVs). The dominant fungal phylum was Ascomycota, followed by Basidiomycota, Chytridiomycota, Blastocladiomycota, Rozellomycota, Mortierellomycota, Monoblepharomycota, Aphelidiomycota, Basidiobolomycota, Mucoromycota, and the fungal-like Oomycota (Stramenopila), in rank order. Antarctomyces sp., Blastocladiomycota sp., Pseudogymnoascus pannorum, Microascaceae sp., Mortierella sp., Lobulomycetales sp., Sordariomycetes sp., Fungal sp., Rhizophydiales sp., Pseudeurotiaceae sp., Chytridiomycota sp. 1, Filobasidiella sp., Tausonia pullulans, Betamyces sp., and Leucosporidium sp. were the most abundant assigned taxa. The fungal assemblages present in the different ornithogenically influenced soils displayed different diversity indices. However, in general, we detected high fungal diversity and few taxa shared between the samples. Despite the polyextreme environmental conditions experienced in these Antarctic soils, the metabarcoding approach detected a rich and complex fungal community dominated by saprophytes, but with some pathogenic taxa also present. The community was dominated by psychrophilic and psychrotolerant taxa, some apparently endemic to Antarctica, and those identified only at higher taxonomic levels, which may represent currently undescribed fungi. The mycobiome detected included taxa characterized by different ecological roles, including saprotrophic, human- and animal-associated, phytopathogenic, mutualistic, and cosmopolitan. These fungi may potentially be dispersed by birds or in the air column over great distances, including between different regions within Antarctica and from South America, Africa, and Oceania.

Climate and human stressors on global penguin hotspots: Current assessments for future conservation.

As charismatic and iconic species, penguins can act as "ambassadors" or flagship species to promote the conservation of marine habitats in the Southern Hemisphere. Unfortunately, there is a lack of reliable, comprehensive, and systematic analysis aimed at compiling spatially explicit assessments of the multiple impacts that the world's 18 species of penguin are facing. We provide such an assessment by combining the available penguin occurrence information from Global Biodiversity Information Facility (>800,000 occurrences) with three main stressors: climate-driven environmental changes at sea, industrial fisheries, and human disturbances on land. Our analyses provide a quantitative assessment of how these impacts are unevenly distributed spatially within species' distribution ranges. Consequently, contrasting pressures are expected among species, and populations within species. The areas coinciding with the greatest impacts for penguins are the coast of Perú, the Patagonian Shelf, the Benguela upwelling region, and the Australian and New Zealand coasts. When weighting these potential stressors with species-specific vulnerabilities, Humboldt (Spheniscus humboldti), African (Spheniscus demersus), and Chinstrap penguin (Pygoscelis antarcticus) emerge as the species under the most pressure. Our approach explicitly differentiates between climate and human stressors, since the more achievable management of local anthropogenic stressors (e.g., fisheries and land-based threats) may provide a suitable means for facilitating cumulative impacts on penguins, especially where they may remain resilient to global processes such as climate change. Moreover, our study highlights some poorly represented species such as the Northern Rockhopper (Eudyptes moseleyi), Snares (Eudyptes robustus), and Erect-crested penguin (Eudyptes sclateri) that need internationally coordinated efforts for data acquisition and data sharing to understand their spatial distribution properly.

Penguins found to take thousands of naps a day.

Georgina Mills discusses research into chinstrap penguins that discovers they use a series of microsleeps through the day.

A first estimation of the role of penguin guano on copper cycling and organic speciation in Antarctic coastal waters

Cu is a vital micronutrient, but free Cu ions (Cu2+) in seawater, even at subnanomolar concentrations, can impede phytoplankton growth. Natural Cu complexation with organic ligands regulates Cu acquisition and, in most instances, reduces Cu2+ concentrations below toxic thresholds. Along the Antarctic coast, the sources and sinks of Cu and its associated ligands remain poorly defined. Despite the high productivity in the area, there are no studies on the role of trophic transfer in Cu cycling.This study explores penguin guano release of Cu and Cu ligands and its potential in neutralizing copper toxicity along the Antarctic coast. We collected guano in a Chinstrap penguin nesting location in the West coast of Deception Island and extracted its components into aqueous solution imitating natural processes. Copper concentration in guano was 0.4 mg (dry weight g)−1 constituting a potential toxic threat and showed biomagnification with respect to krill. Surface seawater samples collected from various locations varying in penguin activity, were analyzed to assess the potential influence of guano on the area. Visual examination and elevated levels of Al suggested that a substantial portion of guano was lithogenic. Consequently, only a modest 16 % of the total Cu present in guano could be extracted using mechanical methods. Notably, the concentrations of the extracted organic ligands were approximately 23 times higher than the concentrations of the extracted Cu. This significant presence of ligands effectively nullifies any potential toxicity that could have arisen from free Cu2+ ions. Guano ligands' conditional stability constants were lower than those in surface seawater suggesting phytoplankton exudation was the main ligand source in the area. Overall, guano acts as a key node for Cu cycling in coastal Antarctic waters but its deleterious potential is neutralized by ligands from krill digestion and the high background concentration of phytoplankton exudates.

Nesting chinstrap penguins accrue large quantities of sleep through seconds-long microsleeps.

Microsleeps, the seconds-long interruptions of wakefulness by eye closure and sleep-related brain activity, are dangerous when driving and might be too short to provide the restorative functions of sleep. If microsleeps do fulfill sleep functions, then animals faced with a continuous need for vigilance might resort to this sleep strategy. We investigated electroencephalographically defined sleep in wild chinstrap penguins, at sea and while nesting in Antarctica, constantly exposed to an egg predator and aggression from other penguins. The penguins nodded off >10,000 times per day, engaging in bouts of bihemispheric and unihemispheric slow-wave sleep lasting on average only 4 seconds, but resulting in the accumulation of >11 hours of sleep for each hemisphere. The investment in microsleeps by successfully breeding penguins suggests that the benefits of sleep can accrue incrementally.

Penguins snatch seconds-long microsleeps.

Chinstrap penguins fall asleep thousands of times per day in the wild.

How We Found Three New Species of Penguins

Usually, it is easy to tell species apart by what they look like, for example, a blue whale and a horse. Chinstrap and Adelie penguins are closely related species, but we can still tell them apart by their unique color patterns. However, sometimes different species look incredibly similar, and we must use special methods to tell them apart. These are called cryptic species. Gentoo penguins live across a large area, including Antarctica and many sub-Antarctic Islands. It has been suspected that gentoos might really be more than one species. To test this, we looked at their DNA and measured their flippers, legs, and beaks to compare gentoos living in four locations. We found differences that told us that there are at least four species of gentoo penguins, not just one species as previously thought.

Determination of reference values for tear production and intraocular pressure in Pygoscelis penguins of the Antarctic Peninsula

BackgroundAccording to the literature review, this is the first study investigating tear production (TP) and intraocular pressure (IOP) in the Pygoscelis penguins living in their natural habitat. The study aimed to establish normal values for standard ocular tests in the genus Pygoscelis, namely, the Adélie (Pygoscelis adeliae), gentoo (Pygoscelis papua), and chinstrap (Pygoscelis antarctica) penguins, in four different islands of Antarctica. Sampling was made by specifically using the left eye of the penguins. The Schirmer's tear test type I (STT-I) and the Tonovet® (rebound tonometer) were used to measure the TP and the IOP, respectively.ResultsThe mean TP and IOP values of 129 Adélie, chinstrap, gentoo, and 120 adult Adélie, gentoo penguins were determined as 10.2 ± 4.0 mm/min and 38.9 ± 13.2 mmHg, respectively. No statistical difference was detected between the penguin species for the mean IOP values, while the difference was determined in all the locations. However, statistical differences in the mean TP values were determined between all locations.ConclusionThe results of this study provide a reference range of Schirmer's tear test (STT) and IOP values in Pygoscelis penguins and show that the IOP is significantly affected by locations. This result can be attributed to the harsh climatic conditions of the Antarctic Peninsula that change very quickly. The described data may help diagnose clinical pathological findings in Pygoscelis penguins.The STT and rebound tonometry appears to be safe and reproducible methods in Pygoscelis penguins, as the results were obtained quickly and were well tolerated by the birds.Based on our results, we propose that similar studies can be initiated in crowded colonies of three penguin species of this genus on the Antarctic Peninsula, the southern Shetland Islands, and other frequently visited islands in Antarctica.

Mercury exposure in Antarctic seabirds: Assessing the influence of trophic position and migration patterns

Although naturally present in the environment, mercury (Hg) input is significantly amplified by anthropogenic activities on a global scale, leading to a growing concern about the recent increase in Hg levels observed in Antarctica. This study investigated total mercury (THg) concentrations in feathers and eggs of resident and migratory Antarctic seabirds. Stable isotope data (δ15N, δ13C, and δ34S) were employed to ascertain the key factors influencing the exposure of these species to Hg. We gathered feathers and eggs from three resident species - Adélie, Gentoo, and Chinstrap penguins, as well as five migratory species - Snowy Sheathbill, Antarctic Tern, Southern Giant Petrel, Kelp Gull, and South Polar Skua. These samples were collected from Admiralty Bay, King George Island, in the Antarctica Peninsula. For all species, THg concentrations were higher in feathers (mean ± SD: 2267 ± 2480 ng g−1 dw) than in eggs (906 ± 1461 ng g−1 dw). Species occupying higher trophic positions, such as the Southern Giant Petrel (5667 ± 1500 ng g−1 dw) and South Polar Skua (4216 ± 1101 ng. g−1 dw), exhibited higher THg levels in their feathers than those at lower positions, like Antarctic Tern (1254 ± 400 ng g−1 dw) and Chinstrap Penguin (910 ± 364 ng g−1 dw). The δ15N values, which serve as a proxy for the trophic position, significantly correlated with THg concentrations. These findings reveal that trophic position influences THg concentrations in Antarctic seabirds. Migration did not appear to significantly affect the exposure of seabirds to THg, contrary to initial expectations. This research highlights the importance of evaluating the impacts of THg contamination on the Antarctic ecosystem by considering a variety of species. This multi-species approach offers critical insights into the factors that may potentially influence the exposure of these species to contaminants.

Identifying Important Bird and Biodiversity Areas in Antarctica Using RPAS Surveys—A Case Study of Cape Melville, King George Island, Antarctica

A remotely piloted aircraft system (RPAS) survey of an area containing the eastern extremity of King George Island, including Cape Melville and an extensive part of Destruction Bay, as well as small offshore islands, was undertaken in December 2022. Using RPAS, an inventory of the Destruction Bay area was performed. Chinstrap penguin and Antarctic shag nests were found on Cape Melville and on Trowbridge Island, Middle Island, and an unnamed area located between the Ørnen Rocks formation and Trowbridge Island. During the survey, 507 Antarctic shag nests and over 9000 chinstrap penguin nests were mapped in the investigated area; 458 Antarctic shag nests and 4960 ± 19 chinstrap penguin nests aggregated together on an 8.61 ha land section of Cape Melville were identified. The quantity of Antarctic shag nests found allows for the classification of the area of Cape Melville as an IBA. Among the 175 currently known colonies of Antarctic shags in Antarctica, this is the fifth largest. In this paper, we present the results of the survey, including orthophotos with mapped nest locations. We propose the following recommendations to policy makers and the scientific community: (1) the area of Cape Melville should be classified as an Antarctic Important Bird and Biodiversity Area; (2) based on the RPAS flight, a new boundary of the Cape Melville IBA is proposed; (3) the threshold value (based on &gt;1% of species) to establish an IBA for Antarctic shags should be changed to 122 to reflect the increased estimate of the global population of Antarctic shags; and (4) an inventory of all areas, including previous IBAs that can be qualified as “major colonies of breeding native birds”, should be recommended at the Antarctic Treaty Consultative Meeting (ATCM). In logistically inaccessible bird breeding sites, such as the one presented here, RPASs should be used to carry out regular monitoring of Antarctic Important Bird and Biodiversity Areas.

Is Penguin Circovirus Circulating Only in the Antarctic Circle? Lack of Viral Detection in Namibia.

The known host range of circoviruses is continuously expanding because of more intensive diagnostic activities and advanced sequencing tools. Recently, a new circovirus (penguin circovirus (PenCV)) was identified in the guano and cloacal samples collected from Adélie penguins (Pygoscelis adeliae) and chinstrap penguins (Pygoscelis antarcticus) in Antarctica. Although the virus was detected in several asymptomatic subjects, a potential association with feather disease was speculated. To investigate the occurrence and implications of PenCV in other penguin species located outside of Antarctica, a broad survey was undertaken in African penguins (Spheniscus demersus) on two islands off the southern Namibian coast. For this purpose, specific molecular biology assays were developed and validated. None of the 151 blood samples tested positive for PenCV. Several reasons could explain the lack of PenCV positive samples. African penguins and Pygoscelis species are separated by approximately 6000 km, so there is almost no opportunity for transmission. Similarly, host susceptibility to PenCV might be penguin genus-specific. Overall, the present study found no evidence of PenCV in African penguin colonies in Namibia. Further dedicated studies are required to assess the relevance of PenCV among different penguin species.

The contribution of penguin guano to the Southern Ocean iron pool

Iron plays a crucial role in the high-nutrient, low-chlorophyll Southern Ocean regions, promoting phytoplankton growth and enhancing atmospheric carbon sequestration. In this area, iron-rich Antarctic krill (Euphausia superba) and baleen whale species, which are among their main predators, play a large role in the recycling of iron. However, penguins have received limited attention despite their representing the largest seabird biomass in the southern polar region. Here, we use breeding site guano volumes estimated from drone images, deep learning-powered penguin census, and guano chemical composition to assess the iron export to the Antarctic waters from one of the most abundant penguin species, the Chinstrap penguin (Pygoscelis antarcticus). Our results show that these seabirds are a relevant contributor to the iron remobilization pool in the Southern Ocean. With an average guano concentration of 3 mg iron g−1, we estimate that the Chinstrap penguin population is recycling 521 tonnes iron yr−1, representing the current iron contribution half of the amount these penguins were able to recycle four decades ago, as they have declined by more than 50% since then.