Variation in sex steroids and phallus size in juvenile American alligators (Alligator mississippiensis) collected from 3 sites within the Kissimmee-Everglades drainage in Florida (USA)

This 3-year study was designed to examine variation in plasma sex steroids, phallus size, and the standard error (S.E.) associated with these endpoints in juvenile alligators collected from 3 sites within the Kissimmee-Everglades drainage (Florida, USA) with varying concentrations of sediment organochlorine contaminants. We hypothesized that decreased plasma sex steroid concentrations and phallus size would be observed in the higher contaminant site when compared to the intermediate and lower contaminant sites. Furthermore, we hypothesized that greater S.E. associated with these endpoints would be observed for the populations from more contaminated sites. We found that differences existed with females from the higher contaminant site exhibiting lower plasma estradiol-17beta (E2) and testosterone (T) concentrations. Males from the higher contaminant site exhibited smaller phallus sizes than males from the intermediate and lower contaminant sites. Smaller phallus size in this case differed from that reported in Lake Apopka male alligators [Gen. Comp. Endocrinol. 116 (1999) 356] in that a significant positive relationship between body size and phallus size existed. No difference among sites was observed in plasma T for males. Lower S.E. was associated with E2 and T concentrations in females from the higher contaminant site and in phallus size in males from the higher contaminant site. This pattern was opposite to what we had hypothesized. We concluded that variation in plasma E2 and T concentrations, phallus size, and the S.E. associated with these endpoints exists among the 3 sites with the patterns matching the patterns of organochlorine contamination, although S.E. patterns were opposite to what was predicted.     

Biological and environmental influences on the trophic ecology of leatherback turtles in the northwest Atlantic Ocean

Understanding the causes and consequences of variability in trophic status is important for interpreting population dynamics and for identifying important habitats for protected species like marine turtles. In the northwest Atlantic Ocean, many leatherback turtles (Dermochelys coriacea) from distinct breeding stocks throughout the Wider Caribbean region migrate to Canadian waters seasonally to feed, but their trophic status during the migratory and breeding cycle and its implications have not yet been described. In this study, we used stable carbon and nitrogen isotope analyses of bulk skin to characterize the trophic status of leatherbacks in Atlantic Canadian waters by identifying trophic patterns among turtles and the factors influencing those patterns. δ¹⁵N values of adult males and females were significantly higher than those of turtles of unknown gender (i.e., presumed to be subadults), and δ¹⁵N increased significantly with body size. We found no significant differences among average stable isotope values of turtles according to breeding stock origin. Significant inter-annual variation in δ¹⁵N among cohorts probably reflects broad-scale oceanographic variability that drives fluctuations in stable isotope values of nutrient sources transferred through several trophic positions to leatherbacks, variation in baseline isotope values among different overwintering habitats used by leatherbacks, or a combination of both. Our results demonstrate that understanding effects of demographic and physiological factors, as well as oceanographic conditions, on trophic status is key to explaining observed patterns in population dynamics and for identifying important habitats for widely distributed, long-lived species like leatherbacks.     

Assessment of the aquatic biodiversity of a threatened coastal lagoon at Bimini, Bahamas

Coastal biodiversity is threatened worldwide by both direct and indirect anthropogenic activities. To more effectively manage and protect coastal biodiversity, accurate assessments of genetic, species, and ecosystem level diversity are required. We present the results from an assessment of the aquatic species diversity of a small (3?km²), shallow, mangrove-fringed Bahamian lagoon (the North Sound) subject to ongoing anthropogenic development. The assessment was conducted through a collation of field observations and data in published literature. We found that eight angiosperm species, 30 macroalgal species, and 370 animal species (including 95 fishes, 69 arthropods, 56 birds, and 45 mollusks) were documented within the lagoon. At least 11 of these species are of conservation concern, such as the critically endangered smalltooth sawfish (Pristis pectinata) and hawksbill turtle (Eretmochelys imbricata). Comparisons of community similarity indicated that the North Sound has a relatively distinct fauna and flora, but available data suggest that the species found there are most similar to those found in nearby habitats in Cuba. The lagoon forms a key nursery habitat for many species, including lemon sharks (Negaprion brevirostris), Caribbean spiny lobsters (Panulirus argus), and queen conch (Strombas gigas). Recently, the lagoon was included as part of a new marine protected area (MPA), but much of the habitat has already experienced considerable anthropogenic disturbance and the MPA boundaries have yet to be established. We have therefore analyzed the lagoon biodiversity and expect the data presented here to serve as a baseline for future comparisons.     

Rural organizations and adaptation to climate change and variability in rural Kenya

Numerous studies have shown that collective action affects the type and efficiency of short- and long-term adaptation to climate change. This empirical study contributes to the body of the literature on collective action and adaptive capacity by demonstrating how organizations frame responses to climate variability and change in rural Kenya by promoting local rural institutions. By analyzing interviews, role-playing games, and household surveys, we ask how local rural organizations shape coping strategies to climate variability and how they may structure future adaptations to climate change. We also investigate what types of households participate in those organizations and how their participation may impact their vulnerability to climate change and variability. Our analysis shows that in places rendered especially vulnerable to climate change by arid climatic conditions, the disengagement of governmental services, and a limited access to income-generating activities, local rural organizations increase livelihood security. Those organizations reduce local vulnerabilities and enhance collective action. In contrast to common diversification and livelihood security strategies which rely on the access to urban or peri-urban structures, local rural institutions and organizations allow for rural and grassroots sustainable adaptation strategies. In that respect, they constitute a resilient and mostly untapped resource for visibly strengthening livelihood security and adaptive capacities in rural Kenya.     

Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

Estimation of Model VII humic binding constants for Pd2+, Sn2+, U4+, NpO2(2+), Pu4+ and PuO2(2+)

Using previously established procedures that utilise linear free energy relationships, we estimated binding constants for the Windermere Humic Aqueous Model VII (WHAM/Model VII) for several radionuclide cations (Pd(2+), Sn(2+), U(4+), NpO(2)(2+), Pu(4+) and PuO(2)(2+)). This extends the number of cations that can be calculated with the model above the 40 included in the original Model VII work. When combined with equilibrium constants for inorganic species this allows the calculation of equilibrium distributions of chemical species under a wide range of conditions.     

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform, triangular, and exponential random variables.     

Zinc removal from synthetic waters using magnetite/graphene oxide composites

The removal of heavy metals from wastewater has become a global challenge, which demands the continuous study of efficient and low-cost treatment alternatives such as adsorption. In this research, the removal of zinc was evaluated using batch adsorption processes with nonconventional materials such as graphene oxide (GO), magnetite (MG), and their composites (GO:MG), formulated with three weight ratios (2:1, 1:1, and 1:2). Graphene was synthesized by the modified Marcano method, using pencil lead graphite as a precursor. MG and the composites were synthesized by chemical coprecipitation of ferrous sulfate and ferric chloride. The materials were characterized by Raman and Fourier transform infrared spectroscopies, scanning electron microscopy, X-ray diffraction, and the Brunauer–Emmett–Teller method to determine the functional groups, microstructural and morphological characteristics, and specific surface area. Batch adsorption tests were carried out to optimize the adsorbent dose and contact time with zinc solutions of 10 ppm. Zinc adsorption reached equilibrium at 2 h, with an optimal dose between 0.25 and 1.0 g/L. The maximum zinc removal efficiencies/adsorption capacities were 98.6%/165.6, 83.4%/47.6, 83.5%/21.9, 72.8%/19.9, and 82.2%/9.25 mg/g using GO, 2GO:1MG, 1GO:1MG, 1GO:2MG, and MG, respectively. Furthermore, the analysis of the isotherm and adsorption kinetics models determined that the adsorption processes using MG and the composites fit the Sips and pseudo-second-order models.     

Spatial and Temporal Variations in Trace Metal Concentrations in the Cockle, Austrovenus Stutchburyi from Otago, New Zealand

This is the first comprehensive study of sources of variation in metal concentrations within the whole tissues of a shallow burrowing, filter-feeding intertidal clam, Austrovenus stutchburyi. Samples were collected from 12 sites in April, August, November and February in 1993–1994 in the vicinity of Otago Harbour and Peninsula, New Zealand. Total tissue trace metal concentrations (μg g⁻¹ dry weight) were measured in individual animals for the essential metals : Mn, Cu, Zn, Ni and the non-essential Cr using trace-metal clean acid-digestion and ICP-OAES techniques. Average metal concentrations were 3–60 μg g⁻¹ for Cu, 40–118 μg g⁻¹ for Zn, 2–12 μg g⁻¹ for Mn, 5–35 μg g⁻¹ for Ni and 1–44 μg g⁻¹ for Cr. These levels decreased with body weight and differed amongst sites except for Cr in February (mid-summer). Highest concentrations occurred at sites close to a city (Dunedin) and within the central harbour region although the Cu, Zn, Ni and Cr concentrations did not correlate with the environmental gradient or season. At one coastal site, samples of both the blue mussel Mytilus galloprovincialis and cockles gave similar trends in trace metal levels. These results suggest that the cockle could be a useful trace metal biomonitor within NZ estuaries.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.