Seasonal occupancy and connectivity amongst nearshore flats and reef habitats by permit Trachinotus falcatus: considerations for fisheries management

Conservation connections: incorporating connectivity into management and conservation of flats fishes and their habitats in a multi-stressor world

Coastal marine fisheries and the habitats that support them are under extensive and increasing pressures from numerous anthropogenic stressors that occur at multiple spatial and temporal scales and often intersect in unexpected ways. Frequently, the scales at which these fisheries are managed do not match the scales of the stressors, much less the geographic scale of species biology. In general, fishery management is ill prepared to address these stressors, as underscored by the continuing lack of integration of fisheries and habitat management. However, research of these fisheries is increasingly being conducted at spatial and temporal scales that incorporate biology and ecological connectivity of target species, with growing attention to the foundational role of habitat. These efforts are also increasingly engaging stakeholders and rights holders in research, education, and conservation. This multi-method approach is essential for addressing pressing conservation challenges that are common to flats ecosystems. Flats fisheries occur in the shallow, coastal habitat mosaic that supports fish species that are accessible to and desirable to target by recreational fishers. Because these species rely upon coastal habitats, the anthropogenic stressors can be especially intense-habitat alteration (loss and degradation) and water quality declines are being exacerbated by climate change and increasing direct human impacts (e.g., fishing effort, boat traffic, depredation, pollution). The connections necessary for effective flats conservation are of many modes and include ontogenetic habitat connectivity; connections between stressors and impacts to fishes; connections between research and management, such as research informing spawning area protections; and engagement of stakeholders and rights holders in research, education, and management. The articles included in this Special Issue build upon a growing literature that is filling knowledge gaps for flats fishes and their habitats and increasingly providing the evidence to inform resource management. Indeed, numerous articles in this issue propose or summarize direct application of research findings to management with a focus on current and future conservation challenges. As with many other fisheries, a revised approach to management and conservation is needed in the Anthropocene.

Cascading effects of climate change on recreational marine flats fishes and fisheries

Tropical and subtropical coastal flats are shallow regions of the marine environment at the intersection of land and sea. These regions provide myriad ecological goods and services, including recreational fisheries focused on flats-inhabiting fishes such as bonefish, tarpon, and permit. The cascading effects of climate change have the potential to negatively impact coastal flats around the globe and to reduce their ecological and economic value. In this paper, we consider how the combined effects of climate change, including extremes in temperature and precipitation regimes, sea level rise, and changes in nutrient dynamics, are causing rapid and potentially permanent changes to the structure and function of tropical and subtropical flats ecosystems. We then apply the available science on recreationally targeted fishes to reveal how these changes can cascade through layers of biological organization-from individuals, to populations, to communities-and ultimately impact the coastal systems that depend on them. We identify critical gaps in knowledge related to the extent and severity of these effects, and how such gaps influence the effectiveness of conservation, management, policy, and grassroots stewardship efforts.

Predator-prey landscapes of large sharks and game fishes in the Florida Keys

Interspecific interactions can play an essential role in shaping wildlife populations and communities. To date, assessments of interspecific interactions, and more specifically predator-prey dynamics, in aquatic systems over broad spatial and temporal scales (i.e., hundreds of kilometers and multiple years) are rare due to constraints on our abilities to measure effectively at those scales. We applied new methods to identify space-use overlap and potential predation risk to Atlantic tarpon (Megalops atlanticus) and permit (Trachinotus falcatus) from two known predators, great hammerhead (Sphyrna mokarran) and bull (Carcharhinus leucas) sharks, over a 3-year period using acoustic telemetry in the coastal region of the Florida Keys (USA). By examining spatiotemporal overlap, as well as the timing and order of arrival at specific locations compared to random chance, we show that potential predation risk from great hammerhead and bull sharks to Atlantic tarpon and permit are heterogeneous across the Florida Keys. Additionally, we find that predator encounter rates with these game fishes are elevated at specific locations and times, including a prespawning aggregation site in the case of Atlantic tarpon. Further, using machine learning algorithms, we identify environmental variability in overlap between predators and their potential prey, including location, habitat, time of year, lunar cycle, depth, and water temperature. These predator-prey landscapes provide insights into fundamental ecosystem function and biological conservation, especially in the context of emerging fishery-related depredation issues in coastal marine ecosystems.

Application of machine learning algorithms to identify cryptic reproductive habitats using diverse information sources

Information on ecological systems often comes from diverse sources with varied levels of complexity, bias, and uncertainty. Accordingly, analytical techniques continue to evolve that address these challenges to reveal the characteristics of ecological systems and inform conservation actions. We applied multiple statistical learning algorithms (i.e., machine learning) with a range of information sources including fish tracking data, environmental data, and visual surveys to identify potential spawning aggregation sites for a marine fish species, permit (Trachinotus falcatus), in the Florida Keys. Recognizing the potential complementarity and some level of uncertainty in each information source, we applied supervised (classic and conditional random forests; RF) and unsupervised (fuzzy k-means; FKM) algorithms. The two RF models had similar predictive performance, but generated different predictor variable importance structures and spawning site predictions. Unsupervised clustering using FKM identified unique site groupings that were similar to the likely spawning sites identified with RF. The conservation of aggregate spawning fish species depends heavily on the protection of key spawning sites; many of these potential sites were identified here for permit in the Florida Keys, which consisted of relatively deep-water natural and artificial reefs with high mean permit residency periods. The application of multiple machine learning algorithms enabled the integration of diverse information sources to develop models of an ecological system. Faced with increasingly complex and diverse data sources, ecologists, and conservation practitioners should find increasing value in machine learning algorithms, which we discuss here and provide resources to increase accessibility.