Papers by Miguel Socrates Ibarra Fernandez
Frontiers in Earth Science, 2017
Predicting the impact of sea-level (SL) rise on coral reefs requires reliable models of reef accr... more Predicting the impact of sea-level (SL) rise on coral reefs requires reliable models of reef accretion. Most assume that accretion results from vertical growth of coralgal framework, but recent studies show that reefs exposed to hurricanes consist of layers of coral gravel rather than in-place corals. New models are therefore needed to account for hurricane impact on reef accretion over geological timescales. To investigate this geological impact, we report the configuration and development of a 4-km-long fringing reef at Punta Maroma along the northeast Yucatan Peninsula. Satellite-derived bathymetry (SDB) shows the crest is setback a uniform distance of 315 ±15 m from a mid-shelf slope break, and the reef-front decreases 50% in width and depth along its length. A 12-core drill transect constrained by multiple 230 Th ages shows the reef is composed of an ∼2-m thick layer of coral clasts that has retrograded 100 m over its back-reef during the last 5.5 ka. These findings are consistent with a hurricane-control model of reef development where large waves trip and break over the mid-shelf slope break, triggering rapid energy dissipation and thus limiting how far upslope individual waves can fragment corals and transport clasts. As SL rises and water depth increases, energy dissipation during wave-breaking is reduced, extending the clast-transport limit, thus leading to reef retrogradation. This hurricane model may be applicable to a large subset of fringing reefs in the tropical Western-Atlantic necessitating a reappraisal of their accretion rates and response to future SL rise.
Frontiers in Earth Science, Oct 12, 2017
Predicting the impact of sea-level (SL) rise on coral reefs requires reliable models of reef accr... more Predicting the impact of sea-level (SL) rise on coral reefs requires reliable models of reef accretion. Most assume that accretion results from vertical growth of coralgal framework, but recent studies show that reefs exposed to hurricanes consist of layers of coral gravel rather than in-place corals. New models are therefore needed to account for hurricane impact on reef accretion over geological timescales. To investigate this geological impact, we report the configuration and development of a 4-km-long fringing reef at Punta Maroma along the northeast Yucatan Peninsula. Satellite-derived bathymetry (SDB) shows the crest is setback a uniform distance of 315 ±15 m from a mid-shelf slope break, and the reef-front decreases 50% in width and depth along its length. A 12-core drill transect constrained by multiple 230 Th ages shows the reef is composed of an ∼2-m thick layer of coral clasts that has retrograded 100 m over its back-reef during the last 5.5 ka. These findings are consistent with a hurricane-control model of reef development where large waves trip and break over the mid-shelf slope break, triggering rapid energy dissipation and thus limiting how far upslope individual waves can fragment corals and transport clasts. As SL rises and water depth increases, energy dissipation during wave-breaking is reduced, extending the clast-transport limit, thus leading to reef retrogradation. This hurricane model may be applicable to a large subset of fringing reefs in the tropical Western-Atlantic necessitating a reappraisal of their accretion rates and response to future SL rise.
Biodiversity Informatics, 2009
We address a poorly understood aspect of ecological niche modeling: its sensitivity to different ... more We address a poorly understood aspect of ecological niche modeling: its sensitivity to different levels of geographic uncertainty in organism occurrence data. Our primary interest was to assess how accuracy degrades under increasing uncertainty, with performance measured indirectly through model consistency. We used Monte Carlo simulations and a similarity measure to assess model sensitivity across three variables: locality accuracy, niche modeling method, and species. Randomly generated data sets with known levels of locality uncertainty were compared to an original prediction using Fuzzy Kappa. Data sets where locality uncertainty is low were expected to produce similar distribution maps to the original. In contrast, data sets where locality uncertainty is high were expected to produce less similar maps. BIOCLIM, DOMAIN, Maxent and GARP were used to predict the distributions for 1200 simulated datasets (3 species x 4 buffer sizes x 100 randomized data sets). Thus, our experimental design produced a total of 4800 similarity measures, with each of the simulated distributions compared to the prediction of the original data set and corresponding modeling method. A general linear model (GLM) analysis was performed which enables us to simultaneously measure the effect of buffer size, modeling method, and species, as well as interactions among all variables. Our results show that modeling method has the largest effect on similarity scores and uniquely accounts for 40% of the total variance in the model. The second most important factor was buffer size, but it uniquely accounts for only 3% of the variation in the model. The newer and currently more popular methods, GARP and Maxent, were shown to produce more inconsistent predictions than the earlier and simpler methods, BIOCLIM and DOMAIN. Understanding the performance of different niche modeling methods under varying levels of geographic uncertainty is an important step toward more productive applications of historical biodiversity collections.
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Papers by Miguel Socrates Ibarra Fernandez