Coastal habitats have experienced significant degradation and fragmentation in recent decades under the strain of interacting ecosystem stressors. To maintain biodiversity and ecosystem functioning, coastal managers and restoration practitioners face the urgent tasks of identifying priority areas for protection and developing innovative, scalable approaches to habitat restoration. Facilitating these efforts are models of seascape connectivity, which represent ecological linkages across heterogeneous marine environments by predicting species-specific dispersal between suitable habitat patches. However, defining the suitable habitat patches and migratory pathways required to construct ecologically realistic connectivity models remains challenging. Focusing on two reef-associated fish species of the Florida Keys, United States of America (USA), we compared two methods for constructing species- and life stage-specific spatial models of habitat suitability—penalized logistic regression and maximum entropy (MaxEnt). The goal of the model comparison was to identify the modeling algorithm that produced the most realistic and detailed products for use in subsequent connectivity assessments. Regardless of species, MaxEnt’s ability to distinguish between suitable and unsuitable locations exceeded that of the penalized regressions. Furthermore, MaxEnt’s habitat suitability predictions more closely aligned with the known ecology of the study species, revealing the environmental conditions and spatial patterns that best support each species across the seascape, with implications for predicting connectivity pathways and the distribution of key ecological processes. Our research demonstrates MaxEnt’s promise as a scalable, species-specific, and spatially explicit tool for informing models of seascape connectivity and guiding coastal conservation efforts.
We explored patterns, rates and unexpected socio‐ecological consequences of tooth replacement in serrasalmids and characids of the Peruvian Amazon using microcomputed tomography. Of 24 specimens collected in February 2019, representing a mix of red‐bellied piranha Pygocentrus nattereri, redeye piranha Serrasalmus rhombeus, silver dollar fish Ctenobrycon hauxwellianus and mojara Astyanax abramis, six individuals possessed edentulous jaw quadrants. On average, 22.9% of fish collected per day from these species featured incomplete dentition, a value three to five times higher than anticipated based on replacement rates estimated from captive fish, differences that may be driven by ontogeny, seasonality or environmental quality.
Coral reefs are experiencing unprecedented levels of stress from global warming, ocean acidification, fishing, and water pollution. In the Caribbean and Western Atlantic, multiple stressors have resulted in widespread losses of the dominant reefbuilding Acroporid corals, two of which are listed as threatened species under the 1973 U.S. Endangered Species Act. In response, active coral reef restoration through the outplanting of live corals has become a widespread intervention technique. To increase restoration success, active coral reef restoration requires significant investment and careful planning, and selection of suitable sites for coral outplanting is an essential early step with considerable influence on restoration outcomes. We applied a maximum entropy model to predict and map habitat suitability for the reef-building coral species, Acropora palmata, around the island of St. Croix in the U.S. Virgin Islands. Based mostly on bathymetry and benthic habitat type, the highest performing model predicted approximately 21.75 km 2 of the highest probability of suitable habitat, of which over half occurred within existing marine protected areas (MPAs). Outplanted coral at 60% of sites coincided with predicted maximum habitat suitability index values greater than 0.75 and 35% with values greater than 0.90. The model reveals that all three statutory MPAs with shallow water coral reefs have a considerable area (13.24 km 2 ) of predicted high suitability seabed with potential for active A. palmata restoration efforts. The predictive spatial modeling approach provides a cost-effective tool to inform future coral restoration design and to evaluate the habitat suitability of coral outplanting sites.
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