Field validation of habitat suitability models for vulnerable marine ecosystems in the South Pacific Ocean:Implications for the use of broad-scale models in fisheries management

AbstractManagement of human activities which impact the seafloor in the deep ocean is becoming increasingly important as bottom trawling and exploration for minerals, oil, and gas continue to extend into regions where fragile ecosystems containing habitat-forming deep-sea corals and sponges may be found. Spatial management of these vulnerable marine ecosystems requires accurate knowledge of their distribution. Predictive habitat suitability modelling, using species presence data and a suite of environmental predictor variables, has emerged as a useful tool for inferring distributions outside of known areas. However, validation of model predictions is typically performed with non-independent data. In this study, we describe the results of habitat suitability models constructed for four deep-sea reef-forming coral species across a large region of the South Pacific Ocean using MaxEnt and Boosted Regression Tree modelling approaches. In order to validate model predictions we conducted a photographic survey on a set of seamounts in an un-sampled area east of New Zealand. The likelihood of habitat suitable for reef-forming corals on these seamounts was predicted to be variable, but very high in some regions, particularly where levels of aragonite saturation, dissolved oxygen, and particulate organic carbon were optimal. However, the observed frequency of coral occurrence in analyses of survey photographic data was much lower than expected, and patterns of observed versus predicted coral distribution were not highly correlated. The poor performance of these broad-scale models is attributed to lack of recorded species absences to inform the models, low precision of global bathymetry models, and lack of data on the geomorphology and substrate of the seamounts at scales appropriate to the modelled taxa. This demonstrates the need to use caution when interpreting and applying broad-scale, presence-only model results for fisheries management and conservation planning in data poor areas of the deep sea. Future improvements in the predictive performance of broad-scale models will rely on the continued advancement in modelling of environmental predictor variables, refinements in modelling approaches to deal with missing or biased inputs, and incorporation of true absence data

Global Diversity of the Stylasteridae (Cnidaria: Hydrozoa: Athecatae)

The history and rate of discovery of the 247 valid Recent stylasterid species are discussed and graphed, with emphasis on five historical pulses of species descriptions. A table listing all genera, their species numbers, and their bathymetric ranges are presented. The number of species in 19 oceanographic regions is mapped, the southwestern temperate Pacific (region including New Zealand) having the most species; species are cosmopolitan from the Arctic Circle to the Antarctic at depths from 0 to 2789 m. The current phylogenetic classification of the genera is briefly discussed. An illustrated glossary of 53 morphological characters is presented. Biological and ecological information pertaining to reproduction, development, commensals, and distribution is discussed. Aspects of stylasterid mineralogy and taxa of commercial value are discussed, concluding with suggestions for future work

Predicted habitat suitability for all taxa.

<p>a) 0.5 threshold as per the previous figures, b) 0.75 threshold. The higher threshold greatly constrains the output, producing predictions that are more focused on areas of the highest suitability.</p

Environmental, physical, and chemical layers developed for this study.

1<p>Derived using ArcGIS spatial analyst and in several layers created using moving windows of 500 m, 1 km, 2.5 km, 5 km, 20 km. ²Extracted from OCMIP2 model data for 1995. ³Extracted from SRES B1 scenario model; mean 2000–2009. ^aIndicates a surface variable. ^bindicates a seafloor variable.</p

Depth – coral habitat suitability relationships.

<p>a) Predicted coral habitat suitability by depth within the New Zealand high seas bottom trawl footprint area (mean, standard deviation and range). The orange line shows the depth range (dotted line = total catch, bar = 90% of catch) over which bottom trawl catches are made; b) Relationship between the proportion of fishable depth (0 m–1600 m) and average, all-depths, predicted habitat suitability per 20-minute block in the New Zealand high-seas bottom trawl footprint. (Data from Davies &Guinotte 2011).</p

High-seas fishing footprint coral habitat suitability – western region.

<p>Distribution of predicted scleractinian coral habitat suitability in each of 20-minute latitude/longitude blocks constituting the New Zealand bottom trawl footprint in the Lord Howe Rise, Northwest Challenger Plateau and West Norfolk Ridge fishing areas (Davies &Guinotte 2011).</p

Validation statistics and jack-knife analysis of variable contributions to the models for all taxa (50^th percentile), Alcyoniina, Antipatharia and Calcaxonia.

<p>Higher values for the regularized training gain of the jack-knife test indicates greater contribution to the model for a variable (these values are not directly comparable between the different taxa). Test AUC numbers in parentheses are the standard deviation of the Test AUC scores. The top three variables are highlighted in bold for each taxon, both for the jack-knife variable contribution and test AUC values for Maxent models generated using a single variable. *indicates cross-validation cells that were eliminated due to low Test AUC scores.</p

Spatial distribution of predicted habitat suitability and bottom trawl closures for areas designated Essential Fish Habitat (stippled) and CCA-West closures (hatched areas).

<p>a) Overview with 0.75 threshold suitability for all taxa, b) northern region (Washington and Oregon) and prediction for Scleractinia, c) central region (northern California) and prediction for Scleraxonia, d) southern region (central and southern California) and prediction for Antipatharia. Location abbreviations: O2: Olympic 2, B1: Biogenic 1, B2: Biogenic 2, B3: Biogenic 3, GC: Grays Canyon, N: Nehalem Bank/Shale Pile, AC: Astoria Canyon, TS: Thompson Seamount, S: Siletz Deepwater, DB: Daisy Bank/Nelson Island, NR: Newport Rockpile/Stonewall Bank, HB: Heceta Bank, CD: Deepwater off Coos Bay, BH: Brandon High Spot, RC: Rogue Canyon, JS: President Jackson Seamount, ER: Eel River Canyon, BL: Blunts Reef, MR: Mendocino Ridge, DC: Delgada Canyon, TB: Tolo Bank, AN: Pt. Arena North, AS: Pt. Arena South, CB: Cordell Bank Biogenic Area, FI: Farallon Islands/Fanny Shaol, HM: Half Moon Bay, MB: Monterey Bay/Canyon, PS: Point Sur Deep, BS: Big Sur Coast/Port San Luis, DS: Davidson Seamount, ES: East San Lucia Bank, PC: Point Conception, RR: Richardson Rock, JR: Judith Rock, HP: Harris Point, CP: Carrington Point, SP: South Point, SK: Skunk Point, S: Scorpion, PA: Painted Cave, AI: Anacopa Island, F: Footprint, HR: Hidden Reef/Kidney Bank, CI: Catalina Island, CC: Cowcod Conservation East Area, SB: Santa Barbara, CH: Cherry Bank, PO: Potato Bank, GI: Gull Island.</p