Haul-Out Behavior of Harbor Seals (Phoca vitulina) in Hood Canal, Washington

The goal of this study was to model haul-out behavior of harbor seals (Phoca vitulina) in the Hood Canal region of Washington State with respect to changes in physiological, environmental, and temporal covariates. Previous research has provided a solid understanding of seal haul-out behavior. Here, we expand on that work using a generalized linear mixed model (GLMM) with temporal autocorrelation and a large dataset. Our dataset included behavioral haul-out records from archival and VHF radio tag deployments on 25 individual seals representing 61,430 seal hours. A novel application for increased computational efficiency allowed us to examine this large dataset with a GLMM that appropriately accounts for temporal autocorellation. We found significant relationships with the covariates hour of day, day of year, minutes from high tide and year. Additionally, there was a significant effect of the interaction term hour of day : day of year. This interaction term demonstrated that seals are more likely to haul out during nighttime hours in August and September, but then switch to predominantly daylight haul-out patterns in October and November. We attribute this change in behavior to an effect of human disturbance levels. This study also examined a unique ecological event to determine the role of increased killer whale (Orcinus orca) predation on haul-out behavior. In 2003 and 2005 these harbor seals were exposed to unprecedented levels of killer whale predation and results show an overall increase in haul-out probability after exposure to killer whales. The outcome of this study will be integral to understanding any changes in population abundance as a result of increased killer whale predation

Quantification and analysis of icebergs in a tidewater glacier fjord using an object-based approach

Tidewater glaciers are glaciers that terminate in, and calve icebergs into, the ocean. In addition to the influence that tidewater glaciers have on physical and chemical oceanography, floating icebergs serve as habitat for marine animals such as harbor seals (Phoca vitulina richardii). The availability and spatial distribution of glacier ice in the fjords is likely a key environmental variable that influences the abundance and distribution of selected marine mammals; however, the amount of ice and the fine-scale characteristics of ice in fjords have not been systematically quantified. Given the predicted changes in glacier habitat, there is a need for the development of methods that could be broadly applied to quantify changes in available ice habitat in tidewater glacier fjords. We present a case study to describe a novel method that uses object-based image analysis (OBIA) to classify floating glacier ice in a tidewater glacier fjord from high-resolution aerial digital imagery. Our objectives were to (i) develop workflows and rule sets to classify high spatial resolution airborne imagery of floating glacier ice; (ii) quantify the amount and fine-scale characteristics of floating glacier ice; (iii) and develop processes for automating the object-based analysis of floating glacier ice for large number of images from a representative survey day during June 2007 in Johns Hopkins Inlet (JHI), a tidewater glacier fjord in Glacier Bay National Park, southeastern Alaska. On 18 June 2007, JHI was comprised of brash ice ([Formula: see text] = 45.2%, SD = 41.5%), water ([Formula: see text] = 52.7%, SD = 42.3%), and icebergs ([Formula: see text] = 2.1%, SD = 1.4%). Average iceberg size per scene was 5.7 m2 (SD = 2.6 m2). We estimate the total area (± uncertainty) of iceberg habitat in the fjord to be 455,400 ± 123,000 m2. The method works well for classifying icebergs across scenes (classification accuracy of 75.6%); the largest classification errors occur in areas with densely-packed ice, low contrast between neighboring ice cover, or dark or sediment-covered ice, where icebergs may be misclassified as brash ice about 20% of the time. OBIA is a powerful image classification tool, and the method we present could be adapted and applied to other ice habitats, such as sea ice, to assess changes in ice characteristics and availability

The european water framework directive facing current challenges: recommendations for a more efficient biological assessment of inland surface waters

High quality water is vital for human life, and ensuring its availability is a basic requirement and a major societal aim. The Water Framework Directive (WFD; 2000/60/EC) is a key piece of legislation for the protection and sustainable use of water in the European Union. In this work we briefly review the WFD directive and the current status of European inland surface waters. Additionally, we summarize major challenges and threats for the biological assessment of inland surface waters under climate change effects and invasion by alien species, and highlight the emerging tools and approaches that might help improve biological assessments, including molecular indices based on environmental DNA (eDNA), to new data from the Earth Observation programmes, and data-sharing platforms. Finally, we present recommendations to improve monitoring systems and assessments in the context of the WFD. Developments in this field may increase the likelihood of assuring high quality water for societyFRESHING Project funded by the Portuguese Foundation for Science and Technology (FCT) and COMPETE (PTDC/AAG-MAA/ 2261/2014 – POCI-01-0145-FEDER-356 016824). AFF, AGR, and JPR were supported by FRESHING. FMSM was supported by FCT grant SFRH/BD/104703/2014. MJF was supported by the strategic project UID/MAR/04292/2013 granted to MAR

Bayesian Multimodel Inference for Geostatistical Regression Models

The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection methods. A Markov chain Monte Carlo (MCMC) method is investigated for the calculation of parameter estimates and posterior model probabilities for spatial regression models. The method can accommodate normal and non-normal response data and a large number of covariates. Thus the method is very flexible and can be used to fit spatial linear models, spatial linear mixed models, and spatial generalized linear mixed models (GLMMs). The Bayesian MCMC method also allows a priori unequal weighting of covariates, which is not possible with many model selection methods such as Akaike's information criterion (AIC). The proposed method is demonstrated on two data sets. The first is the whiptail lizard data set which has been previously analyzed by other researchers investigating model selection methods. Our results confirmed the previous analysis suggesting that sandy soil and ant abundance were strongly associated with lizard abundance. The second data set concerned pollution tolerant fish abundance in relation to several environmental factors. Results indicate that abundance is positively related to Strahler stream order and a habitat quality index. Abundance is negatively related to percent watershed disturbance

Spatial effects of mosquito bednets on child mortality

<p>Abstract</p> <p>Background</p> <p>Insecticide treated nets (ITN) have been proven to be an effective tool in reducing the burden of malaria. Few randomized clinical trials examined the spatial effect of ITNs on child mortality at a high coverage level, hence it is essential to better understand these effects in real-life situation with varying levels of coverage. We analyzed for the first time data from a large follow-up study in an area of high perennial malaria transmission in southern Tanzania to describe the spatial effects of bednets on all-cause child mortality.</p> <p>Methods</p> <p>The study was carried out between October 2001 and September 2003 in 25 villages in Kilombero Valley, southern Tanzania. Bayesian geostatistical models were fitted to assess the effect of different bednet density measures on child mortality adjusting for possible confounders.</p> <p>Results</p> <p>In the multivariate model addressing potential confounding, the only measure significantly associated with child mortality was the bed net density at household level; we failed to observe additional community effect benefit from bed net coverage in the community.</p> <p>Conclusion</p> <p>In this multiyear, 25 village assessment, despite substantial known inadequate insecticide-treatment for bed nets, the density of household bed net ownership was significantly associated with all cause child mortality reduction. The absence of community effect of bednets in our study area might be explained by (1) the small proportion of nets which are treated with insecticide, and (2) the relative homogeneity of coverage with nets in the area. To reduce malaria transmission for both users and non-users it is important to increase the ITNs and long-lasting nets coverage to at least the present untreated nets coverage.</p

Community-based management induces rapid recovery of a high-value tropical freshwater fishery

Tropical wetlands are highly threatened socio-ecological systems, where local communities rely heavily on aquatic animal protein, such as fish, to meet food security. Here, we quantify how a ‘win-win’ community-based resource management program induced stock recovery of the world’s largest scaled freshwater fish (Arapaima gigas), providing both food and income. We analyzed stock assessment data over eight years and examined the effects of protected areas, community-based management, and landscape and limnological variables across 83 oxbow lakes monitored along a ~500-km section of the Juruá River of Western Brazilian Amazonia. Patterns of community management explained 71.8% of the variation in arapaima population sizes. Annual population counts showed that protected lakes on average contained 304.8 (±332.5) arapaimas, compared to only 9.2 (±9.8) in open-access lakes. Protected lakes have become analogous to a high-interest savings account, ensuring an average annual revenue of US$10,601 per community and US$1046.6 per household, greatly improving socioeconomic welfare. Arapaima management is a superb window of opportunity in harmonizing the co-delivery of sustainable resource management and poverty alleviation. We show that arapaima management deserves greater attention from policy makers across Amazonian countries, and highlight the need to include local stakeholders in conservation planning of Amazonian floodplains

Fishery Discards: Factors Affecting Their Variability within a Demersal Trawl Fishery

Discards represent one of the most important issues within current commercial fishing. It occurs for a range of reasons and is influenced by an even more complex array of factors. We address this issue by examining the data collected within the Danish discard observer program and describe the factors that influence discarding within the Danish Kattegat demersal fleet over the period 1997 to 2008. Generalised additive models were used to assess how discards of the 3 main target species, Norway lobster, cod and plaice, and their subcomponents (under and over minimum landings size) are influenced by important factors and their potential relevance to management. Our results show that discards are influenced by a range of different factors that are different for each species and portion of discards. We argue that knowledge about the factors influential to discarding and their use in relation to potential mitigation measures are essential for future fisheries management strategies