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Dive into the research topics where Ana M. M. Sequeira is active.

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Featured researches published by Ana M. M. Sequeira.


Trends in Ecology and Evolution | 2016

Key Questions in Marine Megafauna Movement Ecology

Graeme C. Hays; Luciana C. Ferreira; Ana M. M. Sequeira; Mark G. Meekan; Carlos M. Duarte; Helen Bailey; Fred Bailleul; W. Don Bowen; M. Julian Caley; Daniel P. Costa; Víctor M. Eguíluz; Sabrina Fossette; Ari S. Friedlaender; Nick Gales; Adrian C. Gleiss; John Gunn; Robert G. Harcourt; Elliott L. Hazen; Michael R. Heithaus; Michelle R. Heupel; Kim N. Holland; Markus Horning; Ian D. Jonsen; Gerald L. Kooyman; Christopher G. Lowe; Peter T. Madsen; Helene Marsh; Richard A. Phillips; David Righton; Yan Ropert-Coudert

It is a golden age for animal movement studies and so an opportune time to assess priorities for future work. We assembled 40 experts to identify key questions in this field, focussing on marine megafauna, which include a broad range of birds, mammals, reptiles, and fish. Research on these taxa has both underpinned many of the recent technical developments and led to fundamental discoveries in the field. We show that the questions have broad applicability to other taxa, including terrestrial animals, flying insects, and swimming invertebrates, and, as such, this exercise provides a useful roadmap for targeted deployments and data syntheses that should advance the field of movement ecology.


Journal of Hazardous Materials | 2009

Nitrate removal in a closed marine system through the ion exchange membrane bioreactor

Cristina T. Matos; Ana M. M. Sequeira; Svetlozar Velizarov; João G. Crespo; Maria A.M. Reis

The accumulation of nitrate in closed marine systems presents a problem for both the marine life and the environment. The present study, proposes the application of the ion exchange membrane bioreactor (IEMB) concept for removing nitrate from marine systems, such as aquaculture tanks or marine aquariums. The results obtained demonstrate that the IEMB was able to remove naturally accumulated nitrate from water taken from a public marine aquarium (Oceanário de Lisboa) and bioconvert it, in an isolated compartment (biocompartment), to molecular nitrogen, thus preventing secondary contamination of the treated water by microbial cells, metabolic by-products and excess of carbon source (ethanol). This system allowed for the removal of nitrate at concentrations of 251 and 380 mg/l down to below 27 mg/l exchanging it for chloride. Under the studied operating conditions, the IEMB proves to be a selective nitrate removing technology preserving the initial water composition with respect to cations, due to the Donnan exclusion effect from the membrane, and minimizing the counter diffusion of anions other than nitrate and chloride, due to the use of water with the same ionic composition in the biocompartment. This is an advantage of the IEMB concept, since the quality of the water produced would allow for the reutilisation of the treated water in the aquarium, thereby reducing both the wastewater volume and the use of fresh water.


Nature Communications | 2016

Humans and seasonal climate variability threaten large-bodied coral reef fish with small ranges

Camille Mellin; David Mouillot; Michel Kulbicki; Tim R. McClanahan; Laurent Vigliola; Russell E. Brainard; Pascale Chabanet; Graham J. Edgar; Damien A. Fordham; Alan M. Friedlander; Valeriano Parravicini; Ana M. M. Sequeira; Rick D. Stuart-Smith; Laurent Wantiez; M. J. Caley

Coral reefs are among the most species-rich and threatened ecosystems on Earth, yet the extent to which human stressors determine species occurrences, compared with biogeography or environmental conditions, remains largely unknown. With ever-increasing human-mediated disturbances on these ecosystems, an important question is not only how many species can inhabit local communities, but also which biological traits determine species that can persist (or not) above particular disturbance thresholds. Here we show that human pressure and seasonal climate variability are disproportionately and negatively associated with the occurrence of large-bodied and geographically small-ranging fishes within local coral reef communities. These species are 67% less likely to occur where human impact and temperature seasonality exceed critical thresholds, such as in the marine biodiversity hotspot: the Coral Triangle. Our results identify the most sensitive species and critical thresholds of human and climatic stressors, providing opportunity for targeted conservation intervention to prevent local extinctions.


Methods in Ecology and Evolution | 2018

Transferring biodiversity models for conservation: Opportunities and challenges

Ana M. M. Sequeira; Phil J. Bouchet; Katherine L. Yates; Kerrie Mengersen; M. Julian Caley

After decades of extensive surveying, knowledge of the global distribution of species still remains inadequate for many purposes. In the short to medium term, such knowledge is unlikely to improve greatly given the often prohibitive costs of surveying and the typically limited resources available. By forecasting biodiversity patterns in time and space, predictive models can help fill critical knowledge gaps and prioritise research to support better conservation and management. The ability of a model to predict biodiversity metrics in novel environments is termed “transferability,” and models with high transferability will be the most useful in this context. Despite their potentially broad utility, little guidance exists on what confers high transferability to biodiversity models. We synthesise recent advances in biodiversity model transfers to facilitate increased understanding of what underpins successful model transferability, demonstrating that a consistent approach has so far been lacking but is essential for achieving high levels of repeatability, transparency and accountability of model transfers. We provide a set of guidelines to support efficient learning and the improvement of model transferability.


Trends in Ecology and Evolution | 2017

The Ecology of Human Mobility

Mark G. Meekan; Carlos M. Duarte; Juan Fernández-Gracia; Michele Thums; Ana M. M. Sequeira; Robert G. Harcourt; Víctor M. Eguíluz

Mobile phones and other geolocated devices have produced unprecedented volumes of data on human movement. Analysis of pooled individual human trajectories using big data approaches has revealed a wealth of emergent features that have ecological parallels in animals across a diverse array of phenomena including commuting, epidemics, the spread of innovations and culture, and collective behaviour. Movement ecology, which explores how animals cope with and optimize variability in resources, has the potential to provide a theoretical framework to aid an understanding of human mobility and its impacts on ecosystems. In turn, big data on human movement can be explored in the context of animal movement ecology to provide solutions for urgent conservation problems and management challenges.


Royal Society Open Science | 2016

Error and bias in size estimates of whale sharks: implications for understanding demography

Ana M. M. Sequeira; Michele Thums; Kim Brooks; Mark G. Meekan

Body size and age at maturity are indicative of the vulnerability of a species to extinction. However, they are both difficult to estimate for large animals that cannot be restrained for measurement. For very large species such as whale sharks, body size is commonly estimated visually, potentially resulting in the addition of errors and bias. Here, we investigate the errors and bias associated with total lengths of whale sharks estimated visually by comparing them with measurements collected using a stereo-video camera system at Ningaloo Reef, Western Australia. Using linear mixed-effects models, we found that visual lengths were biased towards underestimation with increasing size of the shark. When using the stereo-video camera, the number of larger individuals that were possibly mature (or close to maturity) that were detected increased by approximately 10%. Mean lengths calculated by each method were, however, comparable (5.002 ± 1.194 and 6.128 ± 1.609 m, s.d.), confirming that the population at Ningaloo is mostly composed of immature sharks based on published lengths at maturity. We then collated data sets of total lengths sampled from aggregations of whale sharks worldwide between 1995 and 2013. Except for locations in the East Pacific where large females have been reported, these aggregations also largely consisted of juveniles (mean lengths less than 7 m). Sightings of the largest individuals were limited and occurred mostly prior to 2006. This result highlights the urgent need to locate and quantify the numbers of mature male and female whale sharks in order to ascertain the conservation status and ensure persistence of the species.


Scientific Reports | 2017

Big data analyses reveal patterns and drivers of the movements of southern elephant seals

Jorge P. Rodríguez; Juan Fernández-Gracia; Michele Thums; Mark A. Hindell; Ana M. M. Sequeira; Mark G. Meekan; Daniel P. Costa; Christophe Guinet; Robert G. Harcourt; Clive R. McMahon; Carlos M. Duarte; Víctor M. Eguíluz

The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with “big data”, that require no ‘a priori’ assumptions about the behaviour of the target agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in the Southern Ocean, that was comprised of >500,000 location estimates collected over more than a decade. Our analyses showed that the displacements of these seals were described by a truncated power law distribution across several spatial and temporal scales, with a clear signature of directed movement. This pattern was evident when analysing the aggregated tracks despite a wide diversity of individual trajectories. We also identified marine provinces that described the migratory and foraging habitats of these seals. Our analysis provides evidence for the presence of intrinsic drivers of movement, such as memory, that cannot be detected using common models of movement behaviour. These results highlight the potential for “big data” techniques to provide new insights into movement behaviour when applied to large datasets of animal tracking.


Proceedings of the National Academy of Sciences of the United States of America | 2018

Convergence of marine megafauna movement patterns in coastal and open oceans

Ana M. M. Sequeira; J. P. Rodríguez; Víctor M. Eguíluz; Robert G. Harcourt; Mark A. Hindell; David W. Sims; Carlos M. Duarte; Daniel P. Costa; Juan Fernández-Gracia; Luciana C. Ferreira; Graeme C. Hays; Michelle R. Heupel; Mark G. Meekan; A. Aven; Frédéric Bailleul; Alastair M. M. Baylis; Michael L. Berumen; Camrin D. Braun; Jennifer M. Burns; M. J. Caley; R. Campbell; R. H. Carmichael; Eric Clua; Luke D. Einoder; Ari S. Friedlaender; Michael E. Goebel; Simon D. Goldsworthy; Christophe Guinet; John Gunn; D. Hamer

Significance Understanding the key drivers of animal movement is crucial to assist in mitigating adverse impacts of anthropogenic activities on marine megafauna. We found that movement patterns of marine megafauna are mostly independent of their evolutionary histories, differing significantly from patterns for terrestrial animals. We detected a remarkable convergence in the distribution of speed and turning angles across organisms ranging from whales to turtles (epitome for the slowest animals on land but not at sea). Marine megafauna show a prevalence of movement patterns dominated by search behavior in coastal habitats compared with more directed, ballistic movement patterns when the animals move across the open ocean. The habitats through which they move will therefore need to be considered for effective conservation. The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals’ movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyze a global dataset of ∼2.8 million locations from >2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared with more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal microhabitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise, and declining oxygen content.


PeerJ | 2018

Challenges of transferring models of fish abundance between coral reefs

Ana M. M. Sequeira; Camille Mellin; Hector M. Lozano-Montes; Jessica J. Meeuwig; Mathew A. Vanderklift; Michael D. E. Haywood; Russell C. Babcock; M. Julian Caley

Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1% <R2 < 50.6% for Acanthuridae) compared to total fish abundance (9% <R2 < 18.6%). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R2 < 6%, p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fish abundance models. However, observations of these local-scale predictors are often not available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.


Frontiers in Marine Science | 2018

How Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology

Michele Thums; Juan Fernández-Gracia; Ana M. M. Sequeira; Víctor M. Eguíluz; Carlos M. Duarte; Mark G. Meekan

AMMS was supported by an ARC Grant DE170100841 and an IOMRC (UWA, AIMS, CSIRO) fellowship. JF-G and VE were supported by Agencia Estatal de Investigacion (AEI, Spain) and Fondo Europeo de Desarrollo Regional (FEDER) through project SPASIMM (FIS2016-80067-P AEI/FEDER, UE), and by research funding from KAUST.

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Mark G. Meekan

Australian Institute of Marine Science

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Camille Mellin

Australian Institute of Marine Science

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M. Julian Caley

Australian Institute of Marine Science

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Carlos M. Duarte

King Abdullah University of Science and Technology

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Víctor M. Eguíluz

Spanish National Research Council

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Michele Thums

Australian Institute of Marine Science

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Juan Fernández-Gracia

Spanish National Research Council

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Hector M. Lozano-Montes

Commonwealth Scientific and Industrial Research Organisation

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Jessica J. Meeuwig

University of Western Australia

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