An environmentally based growth model that uses finite difference calculus with maximum likelihood method: its application to the brackish water bivalve Corbicula japonica in Lake Abashiri, Japan

We present a growth analysis model that combines large amounts of environmental data with limited amounts of biological data and apply it to Corbicula japonica. The model uses the maximum-likelihood method with the Akaike information criterion, which provides an objective criterion for model selection. An adequate distribution for describing a single cohort is selected from available probability density functions, which are expressed by location and scale parameters. Daily relative increase rates of the location parameter are expressed by a multivariate logistic function with environmental factors for each day and categorical variables indicating animal ages as independent variables. Daily relative increase rates of the scale parameter are expressed by an equation describing the relationship with the daily relative increase rate of the location parameter. Corbicula japonica grows to a modal shell length of 0.7 mm during the first year in Lake Abashiri. Compared with the attain-able maximum size of about 30 mm, the growth of juveniles is extremely slow because their growth is less susceptible to environmental factors until the second winter. The extremely slow growth in Lake Abashiri could be a geographical genetic variation within C. japonica.

Characterization of the benthos, marine debris and bottom fish at Gray’s Reef National Marine Sanctuary

Executive Summary: Baseline characterization of resources is an essential part of marine protected area (MPA) management and is critical to inform adaptive management. Gray’s Reef National Marine Sanctuary (GRNMS) currently lacks adequate characterization of several key resources as identified in the 2006 Final Management Plan. The objectives of this characterization were to fulfill this need by characterizing the bottom fish, benthic features, marine debris, and the relationships among them for the different bottom types within the sanctuary: ledges, sparse live bottom, rippled sand, and flat sand. Particular attention was given to characterizing the different ledge types, their fish communities, and the marine debris associated with them given the importance of this bottom type to the sanctuary. The characterization has been divided into four sections. Section 1 provides a brief overview of the project, its relevance to sanctuary needs, methods of site selection, and general field procedures. Section 2 provides the survey methods, results, discussion, and recommendations for monitoring specific to the benthic characterization. Section 3 describes the characterization of marine debris. Section 4 is specific to the characterization of bottom fish. Field surveys were conducted during August 2004, May 2005, and August 2005. A total of 179 surveys were completed over ledge bottom (n=92), sparse live bottom (n=51), flat sand (n=20), and rippled sand (n=16). There were three components to each field survey: fish counting, benthic assessment, and quantification of marine debris. All components occurred within a 25 x 4 m belt transect. Two divers performed the transect at each survey site. One diver was responsible for identification of fish species, size, and abundance using a visual survey. The second diver was responsible for characterization of benthic features using five randomly placed 1 m2 quadrats, measuring ledge height and other benthic structures, and quantifying marine debris within the entire transect. GRNMS is composed of four main bottom types: flat sand, rippled sand, sparsely colonized live bottom, and densely colonized live bottom (ledges). Independent evaluation of the thematic accuracy of the GRNMS benthic map produced by Kendall et al. (2005) revealed high overall accuracy (93%). Most discrepancies between map and diver classification occurred during August 2004 and likely can be attributed to several factors, including actual map or diver errors, and changes in the bottom type due to physical forces. The four bottom types have distinct physical and biological characteristics. Flat and rippled sand bottom types were composed primarily of sand substrate and secondarily shell rubble. Flat sand and rippled sand bottom types were characterized by low percent cover (0-2%) of benthic organisms at all sites. Although the sand bottom types were largely devoid of epifauna, numerous burrows indicate the presence of infaunal organisms. Sparse live bottom and ledges were colonized by macroalgae and numerous invertebrates, including coral, gorgonians, sponges, and “other” benthic species (such as tunicates, anemones, and bryozoans). Ledges and sparse live bottom were similar in terms of diversity (H’) given the level of classification used here. However, percent cover of benthic species, with the exception of gorgonians, was significantly greater on ledge than on sparse live bottom. Percent biotic cover at sparse live bottom ranged from 0.7-26.3%, but was greater than 10% at only 7 out of 51 sites. Colonization on sparse live bottom is likely inhibited by shifting sands, as most sites were covered in a layer of sediment up to several centimeters thick. On ledge bottom type, percent cover ranged from 0.42-100%, with the highest percent cover at ledges in the central and south-central region of GRNMS. Biotic cover on ledges is influenced by local ledge characteristics. Cluster analysis of ledge dimensions (total height, undercut height, undercut width) resulted in three main categories of ledges, which were classified as short, medium, and tall. Median total percent cover was 97.6%, 75.1%, and 17.7% on tall, medium, and short ledges, respectively. Total percent cover and cover of macroalgae, sponges, and other organisms was significantly lower on short ledges compared to medium and tall ledges, but did not vary significantly between medium and tall ledges. Like sparse live bottom, short ledges may be susceptible to burial by sand, however the results indicate that ledge height may only be important to a certain threshold. There are likely other factors not considered here that also influence spatial distribution and community structure (e.g., small scale complexity, ocean currents, differential settlement patterns, and biological interactions). GRNMS is a popular site for recreational fishing and boating, and there has been increased concern about the accumulation of debris in the sanctuary and potential effects on sanctuary resources. Understanding the types, abundance, and distribution of debris is essential to improving debris removal and education efforts. Approximately two-thirds of all observed debris items found during the field surveys were fishing gear, and about half of the fishing related debris was monofilament fishing line. Other fishing related debris included leaders and spear gun parts, and non-gear debris included cans, bottles, and rope. The spatial distribution of debris was concentrated in the center of the sanctuary and was most frequently associated with ledges rather than at other bottom types. Several factors may contribute to this observation. Ledges are often targeted by fishermen due to the association of recreationally important fish species with this bottom type. In addition, ledges are structurally complex and are often densely colonized by biota, providing numerous places for debris to become stuck or entangled. Analysis of observed boat locations indicated that higher boat activity, which is an indication of fishing, occurs in the center of the sanctuary. On ledges, the presence and abundance of debris was significantly related to observed boat density and physiographic features including ledge height, ledge area, and percent cover. While it is likely that most fishing related debris originates from boats inside the sanctuary, preliminary investigation of ocean current data indicate that currents may influence the distribution and local retention of more mobile items. Fish communities at GRNMS are closely linked to benthic habitats. A list of species encountered, probability of occurrence, abundance, and biomass by habitat is provided. Species richness, diversity, composition, abundance, and biomass of fish all showed striking differences depending on bottom type with ledges showing the highest values of nearly all metrics. Species membership was distinctly separated by bottom type as well, although very short, sparsely colonized ledges often had a similar community composition to that of sparse live bottom. Analysis of fish communities at ledges alone indicated that species richness and total abundance of fish were positively related to total percent cover of sessile invertebrates and ledge height. Either ledge attribute was sufficient to result in high abundance or species richness of fish. Fish diversity (H`) was negatively correlated with undercut height due to schools of fish species that utilize ledge undercuts such as Pareques species. Concurrent analysis of ledge types and fish communities indicated that there are five distinct combinations of ledge type and species assemblage. These include, 1) short ledges with little or no undercut that lacked many of the undercut associated species except Urophycis earlii ; 2) tall, heavily colonized, deeply undercut ledges typically with Archosargus probatocephalus, Mycteroperca sp., and Pareques sp.; 3) tall, heavily colonized but less undercut with high occurrence of Lagodon rhomboides and Balistes capriscus; 4) short, heavily colonized ledges typically with Centropristis ocyurus, Halichoeres caudalis, and Stenotomus sp.; and 5) tall, heavily colonized, less undercut typically with Archosargus probatocephalus, Caranx crysos and Seriola sp.. Higher levels of boating activity and presumably fishing pressure did not appear to influence species composition or abundance at the community level although individual species appeared affected. These results indicate that merely knowing the basic characteristics of a ledge such as total height, undercut width, and percent cover of sessile invertebrates would allow good prediction of not only species richness and abundance of fish but also which particular fish species assemblages are likely to occur there. Comparisons with prior studies indicate some major changes in the fish community at GRNMS over the last two decades although the causes of the changes are unknown. Species of interest to recreational fishermen including Centropristis striata, Mycteroperca microlepis, and Mycteroperca phenax were examined in relation to bottom features, areas of assumed high versus low fishing pressure, and spatial dispersion. Both Mycteroperca species were found more frequently when undercut height of ledges was taller. They often were found together in small mixed species groups at ledges in the north central and southwest central regions of the sanctuary. Both had lower mode size and proportion of fish above the fishery size limit in heavily fished areas of the sanctuary (i.e. high boat density) despite the presence of better habitat in that region. Black sea bass, C. striata, occurred at 98% of the ledges surveyed and appeared to be evenly distributed throughout the sanctuary. Abundance was best explained by a positive relationship with percent cover of sessile biota but was also negatively related to presence of either Mycteroperca species. This may be due to predation by the Mycteroperca species or avoidance of sites where they are present by C. striata. Suggestions for monitoring bottom features, marine debris, and bottom fish at GRNMS are provided at the end of each chapter. The present assessment has established quantitative baseline characteristics of many of the key resources and use issues at GRNMS. The methods can be used as a model for future assessments to track the trajectory of GRNMS resources. Belt transects are ideally suited to providing efficient and quantitative assessment of bottom features, debris, and fish at GRNMS. The limited visibility, sensitivity of sessile biota, and linear nature of ledge habitats greatly diminish the utility of other sampling techniques. Ledges should receive the bulk of future characterization effort due to their importance to the sanctuary and high variability in physical structure, benthic composition, and fish assemblages. (PDF contains 107 pages.)

Using an inverse-logistic model to describe growth increments of blacklip abalone (Haliotis rubra) in Tasmania

A new description of growth in blacklip abalone (Haliotis rubra) with the use of an inverse-logistic model is introduced. The inverse-logistic model avoids the disadvantageous assumptions of either rapid or slow growth for small and juvenile individuals implied by the von Bertalanffy and Gompertz growth models, respectively, and allows for indeterminate growth where necessary. An inverse-logistic model was used to estimate the expected mean growth increment for different black-lip abalone populations around southern Tasmania, Australia. Estimates of the time needed for abalone to grow from settlement until recruitment (at 138 mm shell length) into the fishery varied from eight to nine years. The variability of the residuals about the predicted mean growth increments was described with either a second inverse-logistic relationship (standard deviation vs. initial length) or by a power relationship (standard deviation vs. predicted growth increment). The inverse-logistic model can describe linear growth of small and juvenile abalone (as observed in Tasmania), as well as a spectrum of growth possibilities, from determinate to indeterminate growth (a spectrum that would lead to a spread of maximum lengths).

Removing observational noise from fisheries-independent time series data using ARIMA models

Abundance indices derived from fishery-independent surveys typically exhibit much higher interannual variability than is consistent with the within-survey variance or the life history of a species. This extra variability is essentially observation noise (i.e. measurement error); it probably reflects environmentally driven factors that affect catchability over time. Unfortunately, high observation noise reduces the ability to detect important changes in the underlying population abundance. In our study, a noise-reduction technique for uncorrelated observation noise that is based on autoregressive integrated moving average (ARIMA) time series modeling is investigated. The approach is applied to 18 time series of finfish abundance, which were derived from trawl survey data from the U.S. northeast continental shelf. Although the a priori assumption of a random-walk-plus-uncorrelated-noise model generally yielded a smoothed result that is pleasing to the eye, we recommend that the most appropriate ARIMA model be identified for the observed time series if the smoothed time series will be used for further analysis of the population dynamics of a species.

Temporal trends (2000–2011) and influences on fishery-independent catch rates for loggerhead sea turtles (Caretta caretta) at an important coastal foraging region in the southeastern United States

Seasonal trawling was conducted randomly in coastal (depths of 4.6–17 m) waters from St. Augustine, Florida, (29.9°N) to Winyah Bay, South Carolina (33.1°N), during 2000–03, 2008–09, and 2011 to assess annual trends in the relative abundance of sea turtles. A total of 1262 loggerhead sea turtles (Caretta caretta) were captured in 23% (951) of 4207 sampling events. Capture rates (overall and among prevalent 5-cm size classes) were analyzed through the use of a generalized linear model with log link function for the 4097 events that had complete observations for all 25 model parameters. Final models explained 6.6% (70.1–75.0 cm minimum straight-line carapace length [SCLmin]) to 14.9% (75.1–80.0 cm SCLmin) of deviance in the data set. Sampling year, geographic subregion, and distance from shore were retained as significant terms in all final models, and these terms collectively accounted for 6.2% of overall model deviance (range: 4.5–11.7% of variance among 5-cm size classes). We retained 18 parameters only in a subset of final models: 4 as exclusively significant terms, 5 as a mixture of significant or nonsignificant terms, and 9 as exclusively nonsignificant terms. Four parameters also were dropped completely from all final models. The generalized linear model proved appropriate for monitoring trends for this data set that was laden with zero values for catches and was compiled for a globally protected species. Because we could not account for much model deviance, metrics other than those examined in our study may better explain catch variability and, once elucidated, their inclusion in the generalized linear model should improve model fits.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

A model for assessing the likelihood of self-sustaining populations resulting from commercial production of triploid Suminoe oysters (Crassostrea ariakensis) in Chesapeake Bay

Culture of a non-native species, such as the Suminoe oyster (Crassostrea ariakensis), could offset the harvest of the declining native eastern oyster (Crassostrea virginica) fishery in Chesapeake Bay. Because of possible ecological impacts from introducing a fertile non-native species, introduction of sterile triploid oysters has been proposed. However, recent data show that a small percentage of triploid individuals progressively revert toward diploidy, introducing the possibility that Suminoe oysters might establish self-sustaining populations. To assess the risk of Suminoe oyster populations becoming established in Chesapeake Bay, a demographic population model was developed. Parameters modeled were salinity, stocking density, reversion rate, reproductive potential, natural and harvest-induced mortality, growth rates, and effects of various management strategies, including harvest strategies. The probability of a Suminoe oyster population becoming self-sustaining decreased in the model when oysters are grown at low salinity sites, certainty of harvest is high, mini-mum shell length-at-harvest is small, and stocking density is low. From the results of the model, we suggest adopting the proposed management strategies shown by the model to decrease the probability of a Suminoe oyster population becoming self-sustaining. Policy makers and fishery managers can use the model to predict potential outcomes of policy decisions, supporting the ability to make science-based policy decisions about the proposed introduction of triploid Suminoe oysters into the Chesapeake Bay.

A statistical model of climates in the southwestern United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): We describe an empirical-statistical model of climates of the southwestern United States. Boundary conditions include sea surface temperatures, atmospheric transmissivity, and topography. Independent variables are derived from the boundary conditions along 1000-km paths of atmospheric circulation. ... Predictor equations are derived over a larger region than the application area to allow for the increased range of paleoclimate. This larger region is delimited by the autocorrelation properties of climatic data.