Threats to Coral Reefs of Bermuda

Smith, Struan R.; Sarkis, S.; Murdoch, Thaddeus J. T.; Weil, Ernesto; Cróquer, Aldo; Bates, Nicholas R.; Johnson, Rodney J.; Putron, Samantha J. de; Andersson, Andréas

doi:10.1007/978-94-007-5965-7_13

Cited by 27 publications

(21 citation statements)

References 46 publications

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“…The first lionfish recorded in Bermuda was collected in 2000, yet despite being one of the first locations outside the United States to report the presence of lionfish (Smith et al, 2013), surveys indicate that the abundance of lionfish in shallow reef zones has remained relatively low (Eddy, 2016). However, lionfish populations extend well beyond shallow reefs across the invaded range, with sightings reported down to 55 m in Puerto Rico (Bejarano et al, 2014), over 100 m in The Bahamas (Lesser and Slattery, 2011), 112 m in the northwestern Gulf of Mexico (Nuttall et al, 2014), and 250 m in Honduras (Gress et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Ecological Drivers of Invasive Lionfish (Pterois volitans and Pterois miles) Distribution Across Mesophotic Reefs in Bermuda

Goodbody‐Gringley

Eddy

Pitt³

et al. 2019

Front. Mar. Sci.

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Invasive lionfish (Pterois volitans and P. miles) are now ubiquitous throughout the Caribbean and Western Atlantic on shallow and deep reefs. Recent surveys in Bermuda have revealed dense aggregations of lionfish on mesophotic reefs (60 m depth), yet these densities are not pervasive across reefs at this depth. Using diver-led visual surveys of mesophotic reef sites, this study examines how variations in potential ecological drivers may affect lionfish distribution. Significant correlations of lionfish densities were found with prey fish density and prey fish biomass, where sites with higher abundances of prey fishes have greater densities of lionfish. Furthermore, higher densities of lionfish also correlated significantly with higher juvenile Paranthias furcifer biomass, a preferred prey type for lionfish. Prey fish diversity, on the other hand, was not related to lionfish density, nor did prey fish community composition differ in a way that reflected lionfish distributions. The influence of seawater temperature was found to have the strongest effect on lionfish distribution, where higher lionfish densities were found at sites with lower bottom temperature. However, temperature co-varied with prey fish density, prey fish biomass, and P. furcifer biomass, implying that physical parameters of the environment (i.e., temperature) likely influence ecological parameters (i.e., prey fish abundance), contributing to the structuring of lionfish distributions. We suggest, therefore, that cold-water upwelling currents may be fueling the food chain in certain locations, resulting in high abundances of prey fishes and thus lionfish. Understanding the factors that influence lionfish distributions will ultimately increase the efficacy of management strategies, which, as the data presented here suggest, must incorporate mesophotic lionfish populations.

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Section: Introductionmentioning

confidence: 99%

Ecological Drivers of Invasive Lionfish (Pterois volitans and Pterois miles) Distribution Across Mesophotic Reefs in Bermuda

Goodbody‐Gringley

Eddy

Pitt³

et al. 2019

Front. Mar. Sci.

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“…Aquatic habitats of particular concern are coral reefs, which are under threat from multiple anthropogenic sources ( Smith et al, 2013 ). Such threats include warming waters ( Doney et al, 2012 ), ocean acidification ( Hooidonk et al, 2014 ), eutrophication/pollution ( Jessen et al, 2013 ; Koop et al, 2001 ), and overfishing ( Loh et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

GoPros™ as an underwater photogrammetry tool for citizen science

Raoult

David

Dupont

et al. 2016

PeerJ

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Citizen science can increase the scope of research in the marine environment; however, it suffers from necessitating specialized training and simplified methodologies that reduce research output. This paper presents a simplified, novel survey methodology for citizen scientists, which combines GoPro imagery and structure from motion to construct an ortho-corrected 3D model of habitats for analysis. Results using a coral reef habitat were compared to surveys conducted with traditional snorkelling methods for benthic cover, holothurian counts, and coral health. Results were comparable between the two methods, and structure from motion allows the results to be analysed off-site for any chosen visual analysis. The GoPro method outlined in this study is thus an effective tool for citizen science in the marine environment, especially for comparing changes in coral cover or volume over time.

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“…The abundance of Flavobacteriia increased in the microbiome of P. strigosa in the summer compared to winter (78) and both taxa have been associated with elevated temperatures in coral reef environments (27,33,(80)(81)(82). The overrepresentation of members of these classes in the microbiomes of corals from inner reefs of Bermuda may be related to the warmer local temperature profile but can also be simultaneously influenced by other factors (e.g., fluctuations in dissolved organic carbon [DOC]) (83,84). The coral holobiont responds to fluctuations in abiotic factors such as light availability, pCO 2 , total alkalinity, pH, dissolved inorganic carbon (DIC) (76), and DOC (12,14,85).…”

Section: Figmentioning

confidence: 99%

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network

Lima

Weissman

Reed

et al. 2020

mBio

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Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer (SML) of corals using temperature as an extrinsic factor and microbial network as an intrinsic factor. The model was validated by comparing the predicted relative abundances of microbial taxa to the relative abundances of microbial taxa from the sample data. The SML microbiome from Pseudodiploria strigosa was collected across reef zones in Bermuda, where inner and outer reefs are exposed to distinct thermal profiles. A shotgun metagenomics approach was used to describe the taxonomic composition and the microbial network of the coral SML microbiome. By simulating the annual temperature fluctuations at each reef zone, the model output is statistically identical to the observed data. The model was further applied to six scenarios that combined different profiles of temperature and microbial network to investigate the influence of each of these two factors on the model accuracy. The SML microbiome was best predicted by model scenarios with the temperature profile that was closest to the local thermal environment, regardless of the microbial network profile. Our model shows that the SML microbiome of P. strigosa in Bermuda is primarily structured by seasonal fluctuations in temperature at a reef scale, while the microbial network is a secondary driver. IMPORTANCE Coral microbiome dysbiosis (i.e., shifts in the microbial community structure or complete loss of microbial symbionts) caused by environmental changes is a key player in the decline of coral health worldwide. Multiple factors in the water column and the surrounding biological community influence the dynamics of the coral microbiome. However, by including only temperature as an external factor, our model proved to be successful in describing the microbial community associated with the surface mucus layer (SML) of the coral P. strigosa. The dynamic model developed and validated in this study is a potential tool to predict the coral microbiome under different temperature conditions.

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Threats to Coral Reefs of Bermuda

Cited by 27 publications

References 46 publications

Ecological Drivers of Invasive Lionfish (Pterois volitans and Pterois miles) Distribution Across Mesophotic Reefs in Bermuda

Ecological Drivers of Invasive Lionfish (Pterois volitans and Pterois miles) Distribution Across Mesophotic Reefs in Bermuda

GoPros™ as an underwater photogrammetry tool for citizen science

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network

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