Comparison of models for defining nearshore flatfish nursery areas in Alaskan waters

Abstract

Because it is unrealistic to assess fishes in all locations, models are needed to characterize the nursery habitats of flatfish species. Descriptive habitat models of species presence and categorical analysis regression tree (CART) models of species abundance have been developed in previous studies. Based on collections around Kodiak Island, Alaska in 1991 and 1992, these models have been developed for: age‐0 flathead sole (Hippoglossoides elassodon); age‐0 Pacific halibut (Hippoglossus stenolepis); age‐1 yellowfin sole (Pleuronectes asper); and age‐0 rock sole (Pleuronectes bilineatus). In 1995, collections were made in bays along the Alaska Peninsula (an area never before sampled for juvenile flatfishes) and were compared with the previous models developed for Kodiak Island in 1991 and 1992. Very simple descriptive models for Kodiak Island ( Norcross et al., 1995 , Neth. J. Sea Res. 34: 161–175) accurately predicted the abundance along the Alaska Peninsula of flathead sole (78%), Pacific halibut (96%), yellowfin sole (75%) and rock sole (99%) in specific depth ranges and on specific substrate types. More complex CART models of species abundance ( Norcross et al., 1997 , Fish. Bull. (US) 95: 504–520) were more precise but not as accurate as the descriptive models because some parameters were not always available at the test locations. Flathead sole were found at temperatures ≤ 8.9°C on mud and mixed mud substrates in similar proportions in 1995 (66%) as in 1991–92 (71%). Similarly, Pacific halibut were ≤ 7.9 km inside bays and at depths ≤ 40 m in 93% of the sites of this study, compared with 89% previously. Seventy‐five per cent of yellowfin sole were at depths ≤ 28 m on mixed substrates in both study periods. Rock sole were found on sand and muddy sand substrates at temperatures above 8.7°C in 52% of the sites in present and 69% of the sites in previous studies. This field test demonstrated that both descriptive and CART models were very useful at identifying juvenile habitat parameters, but are insufficient for areas not previously sampled. The resource‐selection models verified the importance of a subset of parameters used in earlier models and provided a statistical means (78–87% correct) for prediction of fish distribution in similar areas of the eastern North Pacific.

Larval distribution of offshore spawning flatfish in the Gulf of Alaska: potential transport pathways and enhanced onshore transport during ENSO events

“…In spite of relatively similar life histories and larval transport patterns, it is not necessarily expected that these 2 species would have similar recruitment patterns, because the central Gulf of Alaska is at the northern end of the range of Hippoglossus stenolepis and at the southern end of the range of Atheresthes stomias. Juvenile A. stomias prefer colder nursery habitats (Norcross et al 1999) and the northern Gulf of Alaska is at the warm end of their preferred habitat. Conversely, juvenile H. stenolepis prefer warmer nursery habitats, and the northern Gulf of Alaska is at the cold end of their preferred habitat (Norcross et al 1999).…”

“…Juvenile A. stomias prefer colder nursery habitats (Norcross et al 1999) and the northern Gulf of Alaska is at the warm end of their preferred habitat. Conversely, juvenile H. stenolepis prefer warmer nursery habitats, and the northern Gulf of Alaska is at the cold end of their preferred habitat (Norcross et al 1999). The influence of critical factors such as larval transport on recruitment may vary over the range of a species because species life history traits vary over their ranges (Miller et al 1991).…”

“…1; Thompson & Van Cleve 1936, St. Pierre 1989, Rickey 1995. Both species have juvenile nurseries that are inshore in bays or at the mouths of bays (Norcross et al 1999). In the Gulf of Alaska, surface currents are dominated by the Alaska Coastal Current and the offshore Alaskan Stream (Fig.…”

Using decision trees to predict benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea

“…In environmental sciences application examples can be found in environmental monitoring (Ryan 1995;Schröder and Schmidt 2003), global change biology (Thuiller 2003), applied forestry (Lawrence and Labus 2003) and meteorology (Walmsley et al 2001). In marine biology Norcross et al (1999) used CART to classify near shore flatfish habitats in Alaska's waters. Huetmann and Diamond (2001) predicted and modelled the distribution of seabirds in the Canadian North Atlantic by applying CART.…”

Using ecologically based relationships to predict distribution of flathead sole Hippoglossoides elassodon in the eastern Bering Sea

“…These models include simple comparisons of habitat use between areas of high and low density (McConnaughy & Smith 2000), categorical analysis regression trees (Norcross et al 1999) and generalized additive models (Swartzman et al 1992, O'Brian & Rago 1996, Stoner et al 2001. General additive models (GAMs) have the advantage of exhibiting nonlinear response curves describing the relationship between fish distributions and habitat, but the shape of the response curves may be difficult to explain in terms of organism ecology.…”