Publications by authors named "Eynaud Y"

Geographical comparisons suggest that coral reef communities can vary as a function of their environmental context, differing not just in terms of total coral cover but also in terms of relative abundance (or coverage) of coral taxa. While much work has considered how shifts in benthic reef dynamics can shift dominance of stony corals relative to algal and other benthic competitors, the relative performance of coral types under differing patterns of environmental disturbance has received less attention. We construct an empirically-grounded numerical model to simulate coral assemblage dynamics under a spectrum of disturbance regimes, contrasting hydrodynamic disturbances (which cause morphology-specific, whole-colony mortality) with disturbances that cause mortality independently of colony morphology.

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The impacts of sea-level rise (SLR) are likely to be the greatest for ecosystems that exist at the land-sea interface, where small changes in sea-level could result in drastic changes in habitat availability. Rocky intertidal ecosystems possess a number of characteristics which make them highly vulnerable to changes in sea-level, yet our understanding of potential community-scale responses to future SLR scenarios is limited. Combining remote-sensing with in-situ large-area imaging, we quantified habitat extent and characterized the biological community at two rocky intertidal study locations in California, USA.

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We take advantage of a natural gradient of human exploitation and oceanic primary production across five central Pacific coral reefs to examine foraging patterns in common coral reef fishes. Using stomach content and stable isotope (δN and δC) analyses, we examined consistency across islands in estimated foraging patterns. Surprisingly, species within the piscivore-invertivore group exhibited the clearest pattern of foraging consistency across all five islands despite there being a considerable difference in mean body mass (14 g-1.

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Nonlinear time-series forecasting, or empirical dynamic modelling, has been used extensively in the past two decades as a tool for distinguishing between random temporal behaviour and nonlinear deterministic dynamics. Previous authors have extended nonlinear time-series forecasting to continuous spatial data. Here, we adjust spatial forecasting to handle discrete data and apply the technique to explore the ubiquity of nonlinear determinism in irregular spatial configurations of coral and algal taxa from Palmyra Atoll, a relatively pristine reef in the central Pacific Ocean.

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Background: The metabolic rate of consumers is a key driver of ecosystem dynamics. On coral reefs, herbivorous echinoids consume fleshy algae, facilitating the growth of reef-building calcified organisms; however, little is known about differences among species in their metabolic and functional ecology. Here, we used log-linear (log-log) regression models to examine the allometric scaling of mass and routine metabolic rate for five common herbivorous echinoids on a Hawaiian coral reef: Echinothrix calamaris, E.

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Patterns of species resource use provide insight into the functional roles of species and thus their ecological significance within a community. The functional role of herbivorous fishes on coral reefs has been defined through a variety of methods, but from a grazing perspective, less is known about the species-specific preferences of herbivores on different groups of reef algae and the extent of dietary overlap across an herbivore community. Here, we quantified patterns of redundancy and complementarity in a highly diverse community of herbivores at a reef on Maui, Hawaii, USA.

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Herbivores play an important role in marine communities. On coral reefs, the diversity and unique feeding behaviours found within this functional group can have a comparably diverse set of impacts in structuring the benthic community. Here, using a spatially explicit model of herbivore foraging, we explore how the spatial pattern of grazing behaviours impacts the recovery of a reef ecosystem, considering movements at two temporal scales-short term (e.

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Over-parametrization in modelling is a well-known issue that makes it hard to identify which part of a model is responsible for a given behaviour. In line with that ascertainment, this work presents the outline of an empirical method to simplify models by decreasing the number of parameters. By using regression trees to classify outputs according to related input parameters, the method provides the modeller with an objective tool to reduce the range of the used parameters and, under certain conditions, to establish relations between them.

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