A biogeographic assessment of the Channel Islands National Marine Sanctuary: a review of boundary expansion concepts for NOAA’s National Marine Sanctuary Program

The priority management goal of the National Marine Sanctuaries Program (NMSP) is to protect marine ecosystems and biodiversity. This goal requires an understanding of broad-scale ecological relationships and linkages between marine resources and physical oceanography to support an ecosystem management approach. The Channel Islands National Marine Sanctuary (CINMS) is currently reviewing its management plan and investigating boundary expansion. A management plan study area (henceforth, Study Area) was described that extends from the current boundary north to the mainland, and extends north to Point Sal and south to Point Dume. Six additional boundary concepts were developed that vary in area and include the majority of the Study Area. The NMSP and CINMS partnered with NOAA’s National Centers for Coastal Ocean Science Biogeography Team to conduct a biogeographic assessment to characterize marine resources and oceanographic patterns within and adjacent to the sanctuary. This assessment includes a suite of quantitative spatial and statistical analyses that characterize biological and oceanographic patterns in the marine region from Point Sal to the U.S.-Mexico border. These data were analyzed using an index which evaluates an ecological “cost-benefit” within the proposed boundary concepts and the Study Area. The sanctuary resides in a dynamic setting where two oceanographic regimes meet. Cold northern waters mix with warm southern waters around the Channel Islands creating an area of transition that strongly influences the regions oceanography. In turn, these processes drive the biological distributions within the region. This assessment analyzes bathymetry, benthic substrate, bathymetric life-zones, sea surface temperature, primary production, currents, submerged aquatic vegetation, and kelp in the context of broad-scale patterns and relative to the proposed boundary concepts and the Study Area. Boundary cost-benefit results for these parameters were variable due to their dynamic nature; however, when analyzed in composite the Study Area and Boundary Concept 2 were considered the most favorable. Biological data were collected from numerous resource agencies and university scientists for this assessment. Fish and invertebrate trawl data were used to characterize community structure. Habitat suitability models were developed for 15 species of macroinvertebrates and 11 species of fish that have significant ecological, commercial, or recreational importance in the region and general patterns of ichthyoplankton distribution are described. Six surveys of ship and plane at-sea surveys were used to model marine bird diversity from Point Arena to the U.S.-Mexico border. Additional surveys were utilized to estimate density and colony counts for nine bird species. Critical habitat for western snowy plover and the location of California least tern breeding pairs were also analyzed. At-sea surveys were also used to describe the distribution of 14 species of cetaceans and five species of pinnipeds. Boundary concept cost-benefit indices revealed that Boundary Concept 2 and the Study Area were most favorable for the majority of the species-specific analyses. Boundary Concept 3 was most favorable for bird diversity across the region. Inadequate spatial resolution for fish and invertebrate community data and incompatible sampling effort information for bird and mammal data precluded boundary cost-benefit analysis.

Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.