The Influence of Oyster Farming on Sediment Bacterial Communities

Aquaculture currently provides half of all fish for human consumption, and this proportion is expected to increase to meet the growing global demand for protein. As aquaculture, including oyster farming, expands, it is increasingly important to understand effects on coastal ecosystems. The broad-scale ecological effects of oyster aquaculture are well documented; however, less is known regarding the influence of oyster aquaculture on sediment bacterial communities. To better understand this relationship, we compared three different oyster farming practices that varied in oyster biomass and proximity of oysters to the sediment. We used high-throughput sequencing and quantitative polymerase chain reaction to examine the effect of oyster farming on sediment bacterial communities. We examined the entire bacterial community and looked specifically at bacteria that support essential estuarine ecosystem services (denitrifiers), as well as bacteria that can be detrimental to human health (members of the Vibrio genus). We found that oyster biomass increased Vibrio richness and sediment carbon content, which influenced bacterial community composition. When compared to reference sites, the overall abundance of bacteria was increased by the bottom planting method, but the associated increases in denitrifiers and Vibrio were not significant. We were unable to detect V. parahaemolyticus, V. vulnificus, or V. cholera, the three most common Vibrio pathogens, in any sample, suggesting that oyster farming did not enhance these potential human pathogens in sediments at the time of sampling. These results highlight how differences in oyster farming practice can affect sediment bacterial communities, and the ecosystem services they provide.     

Longitudinal Social Science Research in Natural Resource Communities: Lessons and Considerations

The majority of social science research is cross-sectional in nature, with data collected at a single point in time. However, social systems are dynamic and many of the variables of interest to social scientists may change over time. Longitudinal research methods enable data collection at two or more points in time among a population of interest to examine change in measured variables and influencing factors. Despite the opportunities it affords, longitudinal research is relatively uncommon in natural-resource-based social science research as compared to other fields (e.g., medical, criminal, education). We feel that the field of natural resource social science is ripe for a proliferation of longitudinal studies, now that a substantial body of cross-sectional data has been built. In the spirit of encouraging more of this type of research, we draw on our collective experiences in longitudinal studies to share lessons learned in research design, sampling, and data management.     

A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development

Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sage grouse leks and piñon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, development alternatives, and impacts. The framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.     

Forthcoming papers

Abstract

The Hai River Basin (HRB) is a heavily irrigated region encompassing the North China Plain (NCP) in northeast China. In the last decades, continuous lowering of groundwater levels had been reported in the NCP. This study used data from the Gravity Recovery and Climate Experiment (GRACE) and in situ measurements to quantify recent changes in groundwater storage from 2003 to 2012. The signal from GRACE observations highlight a sharp decline in the deep subsurface water stores (deep unsaturated zone and groundwater systems) up to a rate of 17.0 ± 4.3 mm year^-1 between 2003 and 2012 over the HRB, equal to a volumetric loss of 5.5 ± 1.4 km³ year^-1. This result shows good consistency with in situ observations of groundwater hydraulic heads compiled from monitoring bores, and emphasizes GRACE’s ability to monitor large-scale groundwater storage variations. Results from GRACE also provide an independent assessment of the effectiveness of water saving programmes that have been implemented by the government so far. Our study indicates that groundwater overdrawal is still prevalent and the dominant factor for the persistent loss in groundwater storage over the HRB/NCP; the current groundwater consumption pattern is far beyond the natural recharge ability in groundwater system.

Editor D. Koutsoyiannis; Associate editor T. Wagener     

The relationship between fire behaviour measures and community loss: an exploratory analysis for developing a bushfire severity scale

Current fire danger scales do not adequately reflect the potential destructive force of a bushfire in Australia and, therefore, do not provide fire prone communities with an adequate warning for the potential loss of human life and property. To determine options for developing a bushfire severity scale based on community impact and whether a link exists between the energy release rate (power) of a fire and community loss, this paper reviewed observations of 79 wildfires (from 1939 to 2009) across Victoria and other southern states of Australia. A methodology for estimating fire power based on fuel loading, fire size and progression rate is presented. McArthur??s existing fire danger indices (FDIs) as well as fuel- and slope-adjusted FDIs were calculated using fire weather data. Analysis of possible relationships between fire power, FDIs, rate of spread and Byram??s fireline intensity and community loss was performed using exposure as a covariate. Preliminary results showed that a stronger relationship exists between community loss and the power of the fire than between loss and FDI, although fuel-adjusted FDI was also a good predictor of loss. The database developed for this study and the relationships established are essential for undertaking future studies that require observations of past fire behaviour and losses and also to form the basis of developing a new severity scale.     

Salt Marsh Fucoid Algae: Overlooked Ecosystem Engineers of North Temperate Salt Marshes

Salt marsh fucoid algae are a conspicuous component of north temperate marshes, yet comparatively little research has been conducted to examine their ecological effects. We examined the influence of salt marsh fucoids on physical conditions and the biotic community in a manipulative experiment conducted in a southern Maine back-barrier salt marsh. The biomass of salt marsh fucoids was higher than that of aboveground Spartina alterniflora in the zone where we conducted the experiment. Average daytime temperatures at the sediment surface were significantly reduced by the presence of salt marsh fucoids. Density and biomass of standing-dead S. alterniflora was significantly higher when salt marsh fucoids were removed. In contrast, the abundance of various species of epifauna and infauna were significantly enhanced by the presence of salt marsh fucoids. A regional survey indicated that results from the study site may be conservative because the biomass of salt marsh fucoids was lowest among other back-barrier marshes. Salt marsh fucoids are little studied ecosystem engineers whose presence affects the microclimate and biotic community, especially the animals that constitute the basal components of the salt marsh trophic relay.     

Accurate Measurement of Rare Earth Elements by ICP‐MS after Ion‐Exchange Separation: Application to Ultra‐Depleted Samples

This study reports precise and accurate data for rare earth elements (REE) measured on eight geological reference materials, five enriched in REE (BE‐N, BHVO‐2, BR, BR‐24 and RGM‐1) and three very depleted in REE (BIR‐1, UB‐N and DTS‐2). Data were acquired by quadrupole ICP‐MS after isolation of the REE using an ion‐exchange chromatography procedure. All the measured REE abundances were similar within ≈ 5% (10% for the most REE‐depleted sample DTS‐2) to the high‐quality measurements previously published in the literature. We also show that by using an internal Tm spike, the reproducibility of the data was improved to ～ 1%. Applying this technique to the analysis of ultra‐depleted rock samples (sub ng g^?1), we show that significant improvements were obtained relative to the routine trace element measurement method. The chondrite‐normalised patterns were smooth instead of displaying irregularities. Although the classical method gives excellent results on REE‐rich samples, we believe that our technique improves the precision and accuracy of measurements for highly REE‐depleted rocks.     

The 2010/2011 Canterbury earthquakes: context and cause of injury

The aim of this study was to investigate causes of injury during the 2010/2011 Canterbury earthquakes. Data on patients injured during the Darfield (4 September 2010) and Christchurch (22 February 2011) earthquakes were sourced from the New Zealand Accident Compensation Corporation. The total injury burden was analyzed for demography, context of injury, causes of injury, and injury type. Injury context was classified as direct (shaking of the primary earthquake or aftershocks causing unavoidable injuries), action (movement of person during the primary earthquake or aftershocks causing potentially avoidable injuries), and secondary (cause of injury after shaking ceased). Nine categories of injury cause were identified. Three times as many people were injured in the Christchurch earthquake as in the Darfield earthquake (7,171 vs. 2,256). The primary shaking caused approximately two-thirds of the injuries from both quakes. Actions during the primary shaking and aftershocks led to many injuries (51.3 % Darfield and 19.4 % Christchurch). Primary direct caused the highest proportion of injuries during the daytime Christchurch quake (43.6 %). Many people were injured after shaking stopped in both events: 499 (22.1 % Darfield) and 1,881 (26.2 % Christchurch). Most of these people were injured during clean-up (320 (14.2 %) Darfield; 622 (8.7 %) Christchurch). In both earthquakes, more females than males (1,453 vs. 803 Darfield; 4,646 vs. 2,525 Christchurch) were injured (except by masonry, damaged ground, and during clean-up); trip/fall (27.9 % Darfield; 26.1 % Christchurch) was the most common cause of injury; and soft tissue injuries (74.1 % Darfield; 70.4 % Christchurch) was the most common type of injury. This study demonstrated that where people were and their actions during and after earthquakes influenced their risk of injury.     

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.     

Mapping ideas from cyberspace to realspace: visualizing the spatial context of keywords from web page search results

We introduce a new method for visualizing and analyzing information landscapes of ideas and events posted on public web pages through customized web-search engines and keywords. This research integrates GIScience and web-search engines to track and analyze public web pages and their web contents with associated spatial relationships. Web pages searched by clusters of keywords were mapped with real-world coordinates (by geolocating their Internet Protocol addresses). The resulting maps represent web information landscapes consisting of hundreds of populated web pages searched by selected keywords. By creating a Spatial Web Automatic Reasoning and Mapping System prototype, researchers can visualize the spread of web pages associated with specific keywords, concepts, ideas, or news over time and space. These maps may reveal important spatial relationships and spatial context associated with selected keywords. This approach may provide a new research direction for geographers to study the diffusion of human thought and ideas. A better understanding of the spatial and temporal dynamics of the ‘collective thinking of human beings’ over the Internet may help us understand various innovation diffusion processes, human behaviors, and social movements around the world.