Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Dynamics of ''internal'' interannual variability of the Indian summer monsoon in a GCM

1] The poor predictability of the Indian summer monsoon ( ISM) appears to be due to the fact that a large fraction of interannual variability (IAV) is governed by unpredictable "internal'' low frequency variations. Mechanisms responsible for the internal IAV of the monsoon have not been clearly identified. Here, an attempt has been made to gain insight regarding the origin of internal IAV of the seasonal ( June - September, JJAS) mean rainfall from "internal'' IAV of the ISM simulated by an atmospheric general circulation model (AGCM) driven by fixed annual cycle of sea surface temperature (SST). The underlying hypothesis that monsoon ISOs are responsible for internal IAV of the ISM is tested. The spatial and temporal characteristics of simulated summer intraseasonal oscillations ( ISOs) are found to be in good agreement with those observed. A long integration with the AGCM forced with observed SST, shows that ISO activity over the Asian monsoon region is not modulated by the observed SST variations. The internal IAV of ISM, therefore, appears to be decoupled from external IAV. Hence, insight gained from this study may be useful in understanding the observed internal IAV of ISM. The spatial structure of the ISOs has a significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season ( seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broad-band nature of the ISO spectrum allowing the time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relation is a manifestation of the binomial character of rainfall time series. The remaining 50% of the IAV may arise due to land-surface processes, interaction between high frequency variability and ISOs, etc.

DETERMINATION OF THE MASS OF IGR J17091-3624 FROM ``SPECTRO-TEMPORAL'' VARIATIONS DURING THE ONSET PHASE OF THE 2011 OUTBURST

The 2011 outburst of the black hole candidate IGR J17091-3624 followed the canonical track of state transitions along with the evolution of quasi-periodic oscillation (QPO) frequencies before it began exhibiting various variability classes similar to GRS 1915+105. We use this canonical evolution of spectral and temporal properties to determine the mass of IGR J17091-3624, using three different methods: photon index (Gamma)-QPO frequency (nu) correlation, QPO frequency (nu)-time (day) evolution, and broadband spectral modeling based on two-component advective flow (TCAF). We provide a combined mass estimate for the source using a naive Bayes based joint likelihood approach. This gives a probable mass range of 11.8 M-circle dot-13.7 M-circle dot. Considering each individual estimate and taking the lowermost and uppermost bounds among all three methods, we get a mass range of 8.7 M-circle dot-15.6 M-circle dot with 90% confidence. We discuss the possible implications of our findings in the context of two-component accretion flow.

Variability of Temperature and Salinity in the Middle Atlantic Bight and Gulf of Maine

Monitoring of the waters of the Middle Atlantic Bight and Gulf of Maine has been conducted by the MARMAP Ships of Opportunity Program since the early 1970's. Presented in this atlas are portrayals of the temporal and spatial patterns of surface and bottom temperature and surface salinity for these areas during the period 1978-1990. These patterns are shown in the form of time-space diagrams for single-year and multiyear (base period) time frames. Each base period figure shows thirteen-year (1978-1990) mean conditions, sample variance in the form of standard deviations of the measured values, and data locations. Each single-year figure displays annual conditions, sampling locations, and departures of annual conditions from the thirteen-year means, expressed as algebraic anomalies and standardized anomalies. (PDF file contains 112 pages.)

Variability in the air-sea interaction patterns and timescales within the south-eastern Bay of Biscay, as observed by HF radar data

Two high-frequency (HF) radar stations were installed on the coast of the south-eastern Bay of Biscay in 2009, providing high spatial and temporal resolution and large spatial coverage of currents in the area for the first time. This has made it possible to quantitatively assess the air-sea interaction patterns and timescales for the period 2009-2010. The analysis was conducted using the Barnett-Preisendorfer approach to canonical correlation analysis (CCA) of reanalysis surface winds and HF radar-derived surface currents. The CCA yields two canonical patterns: the first wind-current interaction pattern corresponds to the classical Ekman drift at the sea surface, whilst the second describes an anticyclonic/cyclonic surface circulation. The results obtained demonstrate that local winds play an important role in driving the upper water circulation. The wind-current interaction timescales are mainly related to diurnal breezes and synoptic variability. In particular, the breezes force diurnal currents in waters of the continental shelf and slope of the south-eastern Bay. It is concluded that the breezes may force diurnal currents over considerably wider areas than that covered by the HF radar, considering that the northern and southern continental shelves of the Bay exhibit stronger diurnal than annual wind amplitudes.

Water quality assessment and characterisation of chlorophyll-a variability related to river discharges, within the southeastern Bay of Biscay : evaluation and development of chlorophyll-a algorithms for MODIS and MERIS imagery

222 p. : il.

Spatial-temporal excess mortality patterns of the 1918-1919 influenza pandemic in Spain

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

Spatial and temporal distribution of grouper larvae (Serranidae: Epinephelinae: Epinephelini) in the Gulf of Mexico and Straits of Florida

Little is known about the seasonality and distribution of grouper larvae (Serranidae: Epinephelini) in the Gulf of Mexico and Atlantic Ocean off the coast of the southeast United States. Grouper larvae were collected from a transect across the Straits of Florida in 2003 and 2004 and during the Southeast Area Monitoring and Assessment Program spring and fall surveys from 1982 through 2005. Analysis of these larval data provided information on location and timing of spawning, larval distribution patterns, and interannual occurrence for a group of species not easily studied as adults. Our analyses indicated that shelf-edge habitat is important for spawning of many species of grouper—some species for which data were not previously available. Spawning for some species may occur year-round, but two peak seasons are evident: late winter and late summer through early fall. Interannual variability in the use of three important subregions by species or groups of species was partially explained by environmental factors (surface temperature, surface salinity, and water depth). A shift in species dominance over the last three decades from spring-spawned species (most of the commercial species) to fall-spawned species also was documented. The results of these analyses expand our understanding of the basic distribution and spawning patterns of northwest Atlantic grouper species and indicate a need for further examination of the changing population structure of individual species and species dominance in the region.

Seasonal variability in ichthyoplankton abundance and assemblage composition in the northern Gulf of Mexico off Alabama

Multiyear ichthyoplankton surveys used to monitor larval fish seasonality, abundance, and assemblage structure can provide early indicators of regional ecosystem changes. Numerous ichthyoplankton surveys have been conducted in the northern Gulf of Mexico, but few have had high levels of temporal resolution and sample replication. In this study, ichthyoplankton samples were collected monthly (October 2004–October 2006) at a single station off the coast of Alabama as part of a long-term biological survey. Four seasonal periods were identified from observed and historic water temperatures, including a relatively long (June–October) “summer” period (water temperature >26°C). Fish egg abundance, total larval abundance, and larval taxonomic diversity were significantly related to water temperature (but not salinity), with peaks in the spring, spring–summer, and summer periods, respectively. Larvae collected during the survey represented 58 different families, of which engraulids, sciaenids, carangids, and clupeids were the most prominent. The most abundant taxa collected were unidentified engraulids (50%), sand seatrout (Cynoscion arenarius, 7.5%), Atlantic bumper (Chloroscombrus chrysurus, 5.4%), Atlantic croaker (Micropogonias undulatus, 4.4%), Gulf menhaden (Brevoortia patronus, 3.8%), and unidentified gobiids (3.6%). Larval concentrations for dominant taxa were highly variable between years, but the timing of seasonal occurrence for these taxa was relatively consistent. Documented increases in sea surface temperature on the Alabama shelf may have various implications for larval fish dynamics, as indicated by the presence of tropical larval forms (e.g., fistularids, labrids, scarids, and acanthurids) in our ichthyoplankton collections and in recent juvenile surveys of Alabama and northern Gulf of Mexico seagrass habitats.

Spatial and temporal distribution of North Atlantic right whales (Eubalaena glacialis) in Cape Cod Bay, and implications for management

Cape Cod Bay (Massachusetts) is the only known winter and early spring feeding area for concentrations of the endangered North Atlantic right whale (Eubalaena glacialis) population. During January–May, 1998–2002, 167 aerial surveys were conducted (66,466 km of total survey effort), providing a complete representation of the spatiotemporal distribution of right whales in the bay during winter and spring. A total of 1553 right whales were sighted; some of these sightings were multiple sightings of the same individuals. Right whale distribution and relative abundance patterns were quantified as sightings per unit of effort (SPUE) and partitioned into 103 23-km2 cells and 12 2-week periods. Significant interannual variations in mean SPUE and timing of SPUE maxima were likely due to physically forced changes in available food resources. The area of greatest SPUE expanded and contracted during the season but its center remained in the eastern bay. Most cells with SPUE>0 were inside the federal critical habitat (CH) and this finding gave evidence of the need for management measures within CH boundaries to reduce anthropogenic mortality from vessel strikes and entanglement. There was significant within-season SPUE variability: low in December−January, increasing to a maximum in late February−early April, and declining to zero in May; and these results provide support for management measures from 1 January

Genetic variability in spotted seatrout (Cynoscion nebulosus), determined with microsatellite DNA markers

Variation in the allele frequencies of five microsatellite loci was surveyed in 1256 individual spotted seatrout (Cynoscion nebulosus) obtained from 12 bays and estuaries from Laguna Madre, Texas, to Charlotte Harbor, Florida, to St. John’s River on the Florida Atlantic Coast. Texas and Louisiana collection sites were resampled each year for two to four years (1998−2001). Genetic differentiation was observed. Spotted seatrout from Florida waters were strongly differentiated from spotted seatrout collected in Louisiana and Texas. The greatest genetic discontinuity was observed between Tampa Bay and Charlotte Harbor, and Charlotte Harbor seatrout were most similar to Atlantic Coast spotted seatrout. Texas and Louisiana samples were not strongly structured within the northwestern Gulf of Mexico and there was little evidence of temporal differentiation within bays. These findings are contrary to those of earlier analyses with allozymes and mitochondrial DNA (mtDNA) where evidence of spatial differentiation was found for spotted seatrout resident on the Texas coast. The differences in genetic structure observed among these markers may reflect differences in response to selective pressure, or may be due to differences in underlying genetic processes.

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.

Spatial and temporal patterns of coral bleaching around Buck Island Reef National Monument, St. Croix, U.S. Virgin Islands

Since 2001, biannual fish and habitat monitoring has been conducted for the shallow (> 30 m), colonized pavement and gorgonian dominated Buck Island Reef National Monument (BIRNM) St. Croix, USVI and adjacent waters. during October, 2005, widespread coral bleaching was observed within the ∼50 square-kilometer study area that was preceded by 10 wks of higher than average water temperatures (28.9–30.1 °C). Random transects (100 square meters) were conducted on linear reefs, patch reefs, bedrock, pavement, and scattered coral/rock habitats during October 2005, and April and October 2006, and species specific bleaching patterns were documented. During October 2005 approximately 51% of live coral cover was bleached. Nineteen of 23 coral species within 16 genera and two hydrocoral species exhibited signs of bleaching. Coral cover for Montastraea annularis and species of the genus Agaricia were the most affected, while other species exhibited variability in their susceptibility to bleaching. Bleaching was evident at all depths (1.5–28 m), was negatively correlated with depth, and positively correlated with habitat complexity. Bleaching was less prevalent at all depths and habitat types upon subsequent monitoring during April (15%) and October (3%) 2006. Four species and one genus did not exhibit signs of bleaching throughout the study period (Dendrogyra cylindrus, Eusmilia fastigata, Mussa angulosa, Mycetophyllia aliciae, Scolymia spp.).

Spatial and temporal patterns of coral bleaching around Buck Island Reef National Monument, St. Croix, U.S. Virgin Islands [poster]

Limited information currently exists on the recovery periods of bleached corals as well as the spatial extent, causative factors, and the overall impact of bleaching on coral reef ecosystems. During October, 2005, widespread coral bleaching was observed within Buck Island Reef National Monument (BUIS) St. Croix, USVI. The bleaching event was preceded by 10 weeks of higher than average water temperatures (28.9-30.1°C). Random transects (100 square meters) over hard bottom habitats (N=94) revealed that approximately 51% of live coral cover was bleached. Nineteen of 23 coral species within 16 genera and two hydrocoral species exhibited signs of bleaching; species-specific bleaching patterns were variable throughout the study area. Coral cover for Montastraea annularisand species of the genus Agariciawere the most affected, while other species exhibited variability to bleaching. Although a weak but significant negative relationship (r2=0.10, P=0.0220) was observed, bleaching was evident at all depths (1.5-28 m). Bleaching was spatially autocorrelated (P=0.001) and hot-spot analysis identified a cluster of high bleaching stations northeast of Buck Island. Bleaching was significantly reduced within all depth zones and habitat types upon subsequent monitoring during April (15%) and October (3%) 2006.