Alimentary niche partitioning in the Galapagos sea lion, Zalophus wollebaeki

Sea lions are generally considered opportunistic feeders. However, studies from different areas suggest their diet consists mostly of four to five types of prey. Previous studies in Galapagos sea lions have identified at least three feeding strategies for this species, suggesting diversification of their diet. Diet diversification is favored in organisms with relatively high trophic position and subject to high intra-specific and low inter-specific competition. Zalophus wollebaeki meet these criteria as the only pinniped on San Cristobal Island, where three sea lion rookeries are located within 11 km: a distance considerably shorter than their 41 km foraging range. To measure the degree of diet diversification, we used scats and stable isotope analyses. A total of 270 scat samples from lactating females and 142 fur samples from sea lion pups were collected during the breeding season 2006. The scat analysis identified distinct diets among rookeries, with minimal trophic overlap (Cλ = 0.19), a trophic level TL = 4.5 (secondary–tertiary carnivore), and trophic breadth of a specialist predator (B _i  = 0.37). The mean δ¹⁵N and δ¹³C values were 13.07 ± 0.52 and −16.34 ± 0.37, respectively. No significant difference was found in the δ¹⁵N values from the sea lion rookeries, but differences were found inter- and intra-population in δ¹³C values for pups from different groups (ANOVA P < 0.05). Our results indicate that diet diversification is present in the Galapagos sea lion and may play important role to the survival of the species in a habitat where pinniped populations are limited.     

Bold minnows consistently approach danger in the field and lab in response to either chemical or visual indicators of predation risk

A behavioral syndrome is a suite of behaviors correlated across multiple social contexts. In this study, boldness in the face of predation risk was assessed twice in fish across two different sensory modalities in both the field and lab to ascertain the biological relevance and complexity of this attribute. Individual fathead minnows were captured from a natural field population using traps that either contained chemical alarm cues (conspecific skin extract) or control (well water) and their responses to the presence of predator behind a glass partition assessed in the laboratory. Although fewer fish were captured in alarm cue-labeled traps, these bold fish performed longer predator inspections than shy fish captured in control traps. Thus, a shy/bold behavioral syndrome was expressed consistently across field and lab settings in response to both chemical and visual indicators of danger. Shy and bold individuals did not differ in sex, body length, secondary sexual characteristics, or parasite load but were of more robust physical condition.     

Uncertainty characterization for emergy values

While statistical estimation of uncertainty has not typically accompanied published emergy values, as with any other quantitative model, uncertainty is embedded in these values, and lack of uncertainty characterization makes their accuracy not only opaque, it also prevents the use of emergy values in statistical tests of hypotheses. This paper first attempts to describe sources of uncertainty in unit emergy values (UEVs) and presents a framework for estimating this uncertainty with analytical and stochastic models, with model choices dependent upon on how the UEV is calculated and what kind of uncertainties are quantified. The analytical model can incorporate a broader spectrum of uncertainty types than the stochastic model, including model and scenario uncertainty, which may be significant in emergy models, but is only appropriate for the most basic of emergy calculations. Although less comprehensive in its incorporation of uncertainty, the proposed stochastic method is suitable for all types of UEVs. The distributions of unit emergy values approximate the lognormal distribution with variations depending on the types of uncertainty quantified as well as the way the UEVs are calculated. While both methods of estimating uncertainty in UEVs have their limitations in their presented stage of development, this paper provides methods for incorporating uncertainty into emergy, and demonstrates how this can be depicted and propagated so that it can be used in future emergy analyses and permit emergy to be more readily incorporated into other methods of environmental assessment, such as LCA.     

Physiochemical properties influencing biomass abundance and primary production in Lake Hoare, Antarctica

The perennially ice-covered, closed basin lakes in the McMurdo Dry Valleys respond rapidly to environmental changes, especially climate. For the past 15 years, the McMurdo Dry Valleys Long-Term Ecological Research (MCM-LTER) program has monitored the physical, chemical and biological properties of the lakes in Taylor Valley. In order to better assess the physiochemical controls on the biological process within one of these lakes (Lake Hoare), we have used vertical profile data to estimate depth-dependent correlations between various lake properties. Our analyses reveal the following results. Primary production rates (PPR) are strongly correlated to light (PAR) at 12-15 m and to soluble reactive phosphorus (SRP) at 8-22 m. Chlorophyll-a (CHL) is also positively correlated to PAR at 14 m and greater depths, and SRP from 15 m and greater. This preliminary statistical analysis supports previous observations that both PAR and SRP play significant roles in driving plant growth in Lake Hoare. The lack of a strong relationship between bacterial production (BP) and dissolved organic carbon (DOC) is an intriguing result of the analysis.     

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Effects of temperature variation on TSD in turtle (C. picta) populations

We formulate a two-sex model of temperature-dependent sex determination (TSD) for a freshwater turtle (C. picta) population. The aim is to understand how environmental temperature variations and nest heat conduction properties affect the long term dynamics of the population. This is a key to understanding how global temperature changes may affect their survival. With stochastic inputs of ambient temperature and solar radiation, the model uses the heat equation to determine the temperature in the egg layer in the nest; in turn, this determines the sex ratio in the egg clutch using a variable degree-day model. Finally, a nonlinear Leslie type, stage-based, two-sex model, is used to determine the long term male and female populations. A two-sex model is required because of different development rates for males and females. The model is flexible enough to enable other researchers to examine the effects of temperature variation variations on other species with TSD, e.g., crocodilians, reptilians, as well as other turtle species. It can be adapted to study effects of nest location, soil type, rain events, different incubation periods, and density effects, for example, the dependence of the mating function on the ratio of males to females and each’s contribution to the sex of hatchlings. Modifications can be easily made to fit a specific life history traits. The model is a beginning step in understanding the long term, high fitness shown by many reptile species with TSD, and it may suggest to experimentalists what data may be relevant to these issues; it can also be useful to wildlife managers in developing strategies for intervention if needed. Among the principal findings are that temperature variability and detailed nest heat conduction properties may buffer projected negative effects on a population.     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

Allometric scaling predicts preferences for burned patches in a guild of East African grazers

The high herbivore diversity in savanna systems has been attributed to the inherent spatial and temporal heterogeneity related to the quantity and quality of food resources. Allometric scaling predicts that smaller-bodied grazers rely on higher quality forage than larger-bodied grazers. We replicated burns at varying scales in an East African savanna and measured visitation by an entire guild of larger grazers ranging in size from hare to elephant. We found a strong negative relationship between burn preference and body mass with foregut fermenters preferring burns to a greater degree than hindgut fermenters. Burns with higher quality forage were preferred more than burns with lower quality forage by small-bodied grazers, while the opposite was true for large-bodied grazers. Our results represent some of the first experimental evidence demonstrating the importance of body size in predicting how large herbivores respond to fire-induced changes in plant quality and quantity.     

High connectivity among locally adapted populations of a marine fish (Menidia menidia)

Patterns of connectivity are important in understanding the geographic scale of local adaptation in marine populations. While natural selection can lead to local adaptation, high connectivity can diminish the potential for such adaptation to occur. Connectivity, defined as the exchange of individuals among subpopulations, is presumed to be significant in most marine species due to life histories that include widely dispersive stages. However, evidence of local adaptation in marine species, such the Atlantic silverside, Menidia menidia, raises questions concerning the degree of connectivity. We examined geochemical signatures in the otoliths, or ear bones, of adult Atlantic silversides collected in 11 locations along the northeastern coast of the United States from New Jersey to Maine in 2004 and eight locations in 2005 using laser ablation inductively coupled plasma mass spectrometry (ICP-MS) and isotope ratio monitoring mass spectrometry (irm-MS). These signatures were then compared to baseline signatures of juvenile fish of known origin to determine natal origin of these adult fish. We then estimated migration distances and the degree of mixing from these data. In both years, fish generally had the highest probability of originating from the same location in which they were captured (0.01-0.80), but evidence of mixing throughout the sample area was present. Furthermore, adult M. menidia exhibit highly dispersive behavior with some fish migrating over 700 km. The probability of adult fish returning to natal areas differed between years, with the probability being, on average, 0.2 higher in the second year. These findings demonstrate that marine species with largely open populations are capable of local adaptation despite apparently high gene flow.     

Bioreduction of nitrate in groundwater using a pilot-scale hydrogen-based membrane biofilm reactor

A long-term pilot-scale H₂-based membrane biofilm reactor (MBfR) was tested for removal of nitrate from actual groundwater. A key feature of this second-generation pilot MBfR is that it employed lower cost polyester hollow fibers and still achieved high loading rate. The steady-state maximum nitrate surface loading at which the effluent nitrate and nitrite concentrations were below the Maximum Contaminant Level (MCL) was at least 5.9 g·N·(m²·d)^?1, which corresponds to a maximum volumetric loading of at least 7.7 kg·N·(m³·d) ^?1. The steady-state maximum nitrate surface area loading was higher than the highest nitrate surface loading reported in the first-generation MBfRs using composite fibers (2.6 g·N·(m²·d)^?1). This work also evaluated the H₂-utilization efficiency in MBfR. The measured H₂ supply rate was only slightly higher than the stoichiometric H₂-utilization rate. Thus, H₂ utilization was controlled by diffusion and was close to 100% efficiency, as long as biofilm accumulated on the polyester-fiber surface and the fibers had no leaks.