Ryan Reisinger

Dr. Ryan Reisinger

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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 March 2020 in Nature
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MHMark A. Hindell
Mark A. Hindell
RRRyan Reisinger
Ryan Reisinger
YRYan Ropert-Coudert
Yan Ropert-Coudert
LHLuis A. Hückstädt
Luis A. Hückstädt
PTPhilip N. Trathan
Philip N. Trathan
BRBen Raymond
Ben Raymond
Southern Ocean ecosystems are under pressure from resource exploitation and climate change1,2. Mitigation requires the identification and protection of Areas of Ecological Significance (AESs), which have so far not been determined at the ocean-basin scale. Here, using assemblage-level tracking of marine predators, we identify AESs for this globally important region and assess current threats and protection levels. Integration of more than 4,000 tracks from 17 bird and mammal species reveals AESs around sub-Antarctic islands in the Atlantic and Indian Oceans and over the Antarctic continental shelf. Fishing pressure is disproportionately concentrated inside AESs, and climate change over the next century is predicted to impose pressure on these areas, particularly around the Antarctic continent. At present, 7.1% of the ocean south of 40°S is under formal protection, including 29% of the total AESs. The establishment and regular revision of networks of protection that encompass AESs are needed to provide long-term mitigation of growing pressures on Southern Ocean ecosystems.

22 December 2020 in Biological Reviews
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Journal Article
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JGJulian Gutt
Julian Gutt
EIEnrique Isla
Enrique Isla
JXJosé C. Xavier
José C. Xavier
BAByron J. Adams
Byron J. Adams
IAIn‐Young Ahn
In‐Young Ahn
DWDiana H. Wall
Diana H. Wall
Important findings from the second decade of the 21st century on the impact of environmental change on biological processes in the Antarctic were synthesised by 26 international experts. Ten key messages emerged that have stakeholder‐relevance and/or a high impact for the scientific community. They address (i) altered biogeochemical cycles, (ii) ocean acidification, (iii) climate change hotspots, (iv) unexpected dynamism in seabed‐dwelling populations, (v) spatial range shifts, (vi) adaptation and thermal resilience, (vii) sea ice related biological fluctuations, (viii) pollution, (ix) endangered terrestrial endemism and (x) the discovery of unknown habitats. Most Antarctic biotas are exposed to multiple stresses and considered vulnerable to environmental change due to narrow tolerance ranges, rapid change, projected circumpolar impacts, low potential for timely genetic adaptation, and migration barriers. Important ecosystem functions, such as primary production and energy transfer between trophic levels, have already changed, and biodiversity patterns have shifted. A confidence assessment of the degree of ‘scientific understanding’ revealed an intermediate level for most of the more detailed sub‐messages, indicating that process‐oriented research has been successful in the past decade. Additional efforts are necessary, however, to achieve the level of robustness in scientific knowledge that is required to inform protection measures of the unique Antarctic terrestrial and marine ecosystems, and their contributions to global biodiversity and ecosystem services.

8 January 2018 in Diversity and Distributions
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Journal Article
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RRRyan Reisinger
Ryan Reisinger
BRBen Raymond
Ben Raymond
MHMark A. Hindell
Mark A. Hindell
MBMarthán N. Bester
Marthán N. Bester
RCRobert J. M. Crawford
Robert J. M. Crawford
PPPierre A. Pistorius
Pierre A. Pistorius
Aim: The distribution of marine predators is driven by the distribution and abundance of their prey; areas preferred by multiple marine predator species should therefore indicate areas of ecological significance. The Southern Ocean supports large populations of seabirds and marine mammals and is undergoing rapid environmental change. The management and conservation of these predators and their environment relies on understanding their distribution and its link with the biophysical environment, as the latter determines the distribution and abundance of prey. We addressed this issue using tracking data from 14 species of marine predators to identify important habitat.Location: Indian Ocean sector of the Southern Ocean.Methods: We used tracking data from 538 tag deployments made over a decade at the Subantarctic Prince Edward Islands. For each real track, we simulated a set of pseudo‐tracks that allowed a presence‐availability habitat modelling approach that estimates an animal's habitat preference. Using model ensembles of boosted regression trees and random forests, we modelled these tracks as a response to a set of 17 environmental variables. We combined the resulting species‐specific models to evaluate areas of mean importance.Results: Real tracking locations covered 39.75 million km2, up to 7,813 km from the Prince Edward Islands. Areas of high mean importance were located broadly from the Subtropical Zone to the Polar Frontal Zone in summer and from the Subantarctic to Antarctic Zones in winter. Areas of high mean importance were best predicted by factors including wind speed, sea surface temperature, depth and current speed.Main conclusions: The models and predictions developed here identify important habitat of marine predators around the Prince Edward Islands and can support the large‐scale conservation and management of Subantarctic ecosystems and the marine predators they sustain. The results also form the basis of future efforts to predict the consequences of environmental change.

12 October 2014 in Molecular Ecology
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Journal Article
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AMAndre E. Moura
Andre E. Moura
JKJohn Kenny
John Kenny
RCRoy Chaudhuri
Roy Chaudhuri
MHMargaret A. Hughes
Margaret A. Hughes
AWAndreanna J. Welch
Andreanna J. Welch
AHA. Rus Hoelzel
A. Rus Hoelzel
The evolution of diversity in the marine ecosystem is poorly understood, given the relatively high potential for connectivity, especially for highly mobile species such as whales and dolphins. The killer whale (Orcinus orca) has a worldwide distribution, and individual social groups travel over a wide geographic range. Even so, regional populations have been shown to be genetically differentiated, including among different foraging specialists (ecotypes) in sympatry. Given the strong matrifocal social structure of this species together with strong resource specializations, understanding the process of differentiation will require an understanding of the relative importance of both genetic drift and local adaptation. Here we provide a high‐resolution analysis based on nuclear single‐nucleotide polymorphic markers and inference about differentiation at both neutral loci and those potentially under selection. We find that all population comparisons, within or among foraging ecotypes, show significant differentiation, including populations in parapatry and sympatry. Loci putatively under selection show a different pattern of structure compared to neutral loci and are associated with gene ontology terms reflecting physiologically relevant functions (e.g. related to digestion). The pattern of differentiation for one ecotype in the North Pacific suggests local adaptation and shows some fixed differences among sympatric ecotypes. We suggest that differential habitat use and resource specializations have promoted sufficient isolation to allow differential evolution at neutral and functional loci, but that the process is recent and dependent on both selection and drift.

1 December 2015 in Journal of Experimental Marine Biology and Ecology
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Journal Article
Closed access
RRRyan Reisinger
Ryan Reisinger
MKMark Keith
Mark Keith
RARussel D. Andrews
Russel D. Andrews
PBP.J.N. de Bruyn
P.J.N. de Bruyn

12 June 2013 in PLOS ONE
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Journal Article
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ATAlison V. Towner
Alison V. Towner
MWMichelle A. Wcisel
Michelle A. Wcisel
RRRyan Reisinger
Ryan Reisinger
DEDavid Edwards
David Edwards
OJOliver J. D. Jewell
Oliver J. D. Jewell
South Africa is reputed to host the world’s largest remaining population of white sharks, yet no studies have accurately determined a population estimate based on mark-recapture of live individuals. We used dorsal fin photographs (fin IDs) to identify white sharks in Gansbaai, South Africa, from January 2007 – December 2011. We used the computer programme DARWIN to catalogue and match fin IDs of individuals; this is the first study to successfully use the software for white shark identification. The programme performed well despite a number of individual fins showing drastic changes in dorsal fin shape over time. Of 1682 fin IDs used, 532 unique individuals were identified. We estimated population size using the open-population POPAN parameterisation in Program MARK, which estimated the superpopulation size at 908 (95% confidence interval 808–1008). This estimated population size is considerably larger than those described at other aggregation areas of the species and is comparable to a previous South African population estimate conducted 16 years prior. Our assessment suggests the species has not made a marked recovery since being nationally protected in 1991. As such, additional international protection may prove vital for the long-term conservation of this threatened species.