Abstract
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.
Highlights
Understanding the spatial, temporal, and environmental drivers of marine species distributions is paramount to developing ecologically sound conservation and place-based management strategies [1,2]
As functional connectivity for L. griseus and H. sciurus across the Florida Keys seascape is maintained primarily by the cross-shelf (5–15 km) ontogenetic migrations of their subadult life stage, we focused our habitat suitability modeling efforts on this subpopulation
We used the area under the receiver-operator curve (AUC) test statistic to determine whether penalized logistic regression and maximum entropy (MaxEnt) modeling techniques differ in their ability to discriminate between suitable and unsuitable locations across a variety of thresholds
Summary
Understanding the spatial, temporal, and environmental drivers of marine species distributions is paramount to developing ecologically sound conservation and place-based management strategies [1,2]. Management programs that maximize functional connectivity across scales and communities, including through place-based conservation measures such as marine protected areas, are expected to achieve greater ecological outcomes [13,14,15] Facilitating these efforts are models of potential connectivity, in which limited data on species behavior or dispersal are related to metrics of seascape structure [20]. These include graph-theoretic approaches, in which the seascape is represented by a spatial graph constructed of suitable habitat patches (nodes) connected by a series of dispersal links (edges) [22]. Our secondary objective was to identify the most influential environmental and spatial predictors of habitat suitability for each species to better understand the species-seascape interactions that shape patterns of connectivity
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