Direct and indirect effects of climate and habitat factors on butterfly diversity

Many factors, including climate, resource availability, and habitat diversity, have been proposed as determinants of global diversity, but the links among them have rarely been studied. Using structural equation modeling (SEM), we investigated direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain, at 20-km grid resolution. These factors were all important determinants of butterfly diversity, but their relative contributions differed between habitat generalists and specialists, and whether the effects were direct or indirect. Climate variables had strong effects on habitat generalists, whereas host-plant richness and habitat diversity contributed relatively more for habitat specialists. Considering total effects (direct and indirect together), climate variables had the strongest link to butterfly species richness for all groups of species. The results suggest that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists, with generalists hypothesized to show direct physiological limitations and specialists additionally being constrained by trophic interactions (climate affecting host-plant richness).     

Designing the Environmental Results Workshop: Historical Context, Causality and Candidate Species

During the past thirty years, researchers have been documenting the concentrations and effects of persistent toxic substances, such as DDT, PCBs, dioxins and furans, in populations of Great Lakes organisms. In designing the International Joint Commission's Workshop on Environmental Results, the organizers on the Great Lakes Science Advisory Board started from the premise that the selection of indicator organisms for long-term trend analysis requires that the causal relationships between the observed effects and the putative cause should be demonstrated and believed. However, the causal relationships that have been documented have generally been met with skepticism by fellow scientists and by regulatory officials resulting in no agreement on valid indicator organisms. To overcome this skepticism, wildlife, fisheries and human health researchers have adapted the epidemiological criteria used by medical and veterinary researchers for synthesizing the causal evidence. Brief reviews of several candidate species and of their suitability as long term monitors are presented, and the adequacy of monitoring programs for determining trends in the incidence of chemically-induced effects is assessed.     

Trapping phosphorus in runoff with a phosphorus removal structure

Reduction of phosphorus (P) inputs to surface waters may decrease eutrophication. Some researchers have proposed filtering dissolved P in runoff with P-sorptive byproducts in structures placed in hydrologically active areas with high soil P concentrations. The objectives of this study were to construct and monitor a P removal structure in a suburban watershed and test the ability of empirically developed flow-through equations to predict structure performance. Steel slag was used as the P sorption material in the P removal structure. Water samples were collected before and after the structure using automatic samples and analyzed for total dissolved P. During the first 5 mo of structure operation, 25% of all dissolved P was removed from rainfall and irrigation events. Phosphorus was removed more efficiently during low flow rate irrigation events with a high retention time than during high flow rate rainfall events with a low retention time. The six largest flow events occurred during storm flow and accounted for 75% of the P entering the structure and 54% of the P removed by the structure. Flow-through equations developed for predicting structure performance produced reasonable estimates of structure "lifetime" (16.8 mo). However, the equations overpredicted cumulative P removal. This was likely due to differences in pH, total Ca and Fe, and alkalinity between the slag used in the structure and the slag used for model development. This suggests the need for an overall model that can predict structure performance based on individual material properties.     

Design and Operating Parameters for a Large Ambient Aerosol Chamber

Recent investigations of ambient aerosol behavior over urban areas have pointed out the need for controlled experimental data to link together field investigation results and computer simulation studies. This paper describes the design considerations, construction details and operating parameters of a large (8000 ft³) outside reaction chamber constructed in rural North Carolina. The chamber is triangular in cross-section, 20 ft wide, 20 ft high and 40 ft long, and is covered with clear 5 ml Teflon film. The outdoor location of the chamber permits the reaction volume to be exposed to the natural conditions of temperature and solar radiation. A recirculating air system allows the air in the chamber to be passed through an “absolute” fiberglas filter for adjustment of condensation nuclei concentration and also through driers for humidity adjustment. Internal fans are provided for mixing of the chamber contents without use of the recirculating system so that various degrees of turbulence can be approximated. A sampling line from the chamber passes directly to an instrument room, located directly under the chamber, where direct analyses for particle composition, concentration, and size, and gas composition and concentration are carried out. Parameters which can be varied in this system include number, size, distribution, and chemical composition of pre-existing nuclei, as well as humidity, solar radiation, temperature, and trace gas concentration and composition.     

Photochemical Conversion of NO to NO2 by Hydrocarbons in an Outdoor Chamber

Significant differences occur between results of chamber work conducted outdoors versus work conducted indoors under constant light intensity. Under outdoor conditions at constant [NO_X]_O, lower [HC]o resulted in lower [NO₂]_max and NO₂ dosage during the daylight hours. The percent reduction in [NO₂]_max was a function of the [HC]₀ reduction and the [NO_X]_O level. Under all experimental conditions the 10 hour N0₂ average to maximum N0₂ concentration ratio appeared to be constant at 0.73 during the daylight hours. A regression equation relating [NO_x]_max to [NO_X]_O, [HC]_O, and measures of solar radiation accounted for 92% of the variance in the data. Although there is unavoidable confoundment between [HC]₀ and solar radiation, the HC term in this regression equation can introduce ±20 % change in [N0₂]_max - This variation can be partially offset or enhanced by variations in solar radiation.     

Modification of a full-scale sequencing batch reactor operational mode for biological nutrient removal.

Two biological nutrient removal modes, consisting of anaerobic, anoxic, and oxic sequences, were tested in a full-scale sequencing batch reactor. The modes, identified as BNR-S1 and BNR-S2, had average total nitrogen removals of 84 and 89%, respectively, for the months of August to October. Over the same period, total phosphorus removals for BNR-S1 and BNR-S2 were 88 and 87%, respectively. In contrast, total nitrogen and total phosphorus removals for the regular aerobic mode were 54.7 and 44.7%, respectively. When the wastewater temperature changed from approximately 20 to 15 degrees C in the winter months, total nitrogen and total phosphorus removals for BNR-S2 were reduced to 81 and 70%, respectively. Total nitrogen effluent concentrations were between 2.5 and 4 mg-N/L (at approximately 20 degrees C), while the effluent total phosphorus concentrations were between 1 and 2 mg/L. The BNR-S2 mode was found to require less energy per kilogram of soluble chemical oxygen demand removed than the regular and BNR-S1 modes.     

Comparison of Aquifer Sustainability Under Groundwater Administrations in Oklahoma and Texas1

Mittelstet, Aaron R., Michael D. Smolen, Garey A. Fox, and Damian C. Adams, 2011. Comparison of Aquifer Sustainability Under Groundwater Administrations in Oklahoma and Texas. Journal of the American Water Resources Association (JAWRA) 1‐8. DOI: 10.1111/j.1752‐1688.2011.00524.x Abstract: We compared two approaches to administration of groundwater law on a hydrologic model of the North Canadian River, an alluvial aquifer in northwestern Oklahoma. Oklahoma limits pumping rates to retain 50% aquifer saturated thickness after 20 years of groundwater use. The Texas Panhandle Groundwater Conservation District’s (GCD) rules limit pumping to a rate that consumes no more than 50% of saturated thickness in 50 years, with reevaluation and readjustment of permits every 5 years. Using a hydrologic model (MODFLOW), we simulated river‐groundwater interaction and aquifer dynamics under increasing levels of “development” (i.e., increasing groundwater withdrawals). Oklahoma’s approach initially would limit groundwater extraction more than the GCD approach, but the GCD approach would be more protective in the long run. Under Oklahoma rules more than half of aquifer storage would be depleted when development reaches 65%. Reevaluation of permits under the Texas Panhandle GCD approach would severely limit pumping as the 50% level is approached. Both Oklahoma and Texas Panhandle GCD approaches would deplete alluvial base flow at approximately 10% development. Results suggest periodic review of permits could protect aquifer storage and river base flow. Modeling total aquifer storage is more sensitive to recharge rate and aquifer hydraulic conductivity than to specific yield, while river leakage is most sensitive to aquifer hydraulic conductivity followed by specific yield.     

Demographic heterogeneity, cohort selection, and population growth

Demographic heterogeneity--variation among individuals in survival and reproduction--is ubiquitous in natural populations. Structured population models address heterogeneity due to age, size, or major developmental stages. However, other important sources of demographic heterogeneity, such as genetic variation, spatial heterogeneity in the environment, maternal effects, and differential exposure to stressors, are often not easily measured and hence are modeled as stochasticity. Recent research has elucidated the role of demographic heterogeneity in changing the magnitude of demographic stochasticity in small populations. Here we demonstrate a previously unrecognized effect: heterogeneous survival in long-lived species can increase the long-term growth rate in populations of any size. We illustrate this result using simple models in which each individual's annual survival rate is independent of age but survival may differ among individuals within a cohort. Similar models, but with nonoverlapping generations, have been extensively studied by demographers, who showed that, because the more "frail" individuals are more likely to die at a young age, the average survival rate of the cohort increases with age. Within ecology and evolution, this phenomenon of "cohort selection" is increasingly appreciated as a confounding factor in studies of senescence. We show that, when placed in a population model with overlapping generations, this heterogeneity also causes the asymptotic population growth rate lambda to increase, relative to a homogeneous population with the same mean survival rate at birth. The increase occurs because, even integrating over all the cohorts in the population, the population becomes increasingly dominated by the more robust individuals. The growth rate increases monotonically with the variance in survival rates, and the effect can be substantial, easily doubling the growth rate of slow-growing populations. Correlations between parent and offspring phenotype change the magnitude of the increase in lambda, but the increase occurs even for negative parent-offspring correlations. The effect of heterogeneity in reproductive rate on lambda is quite different: growth rate increases with reproductive heterogeneity for positive parent-offspring correlation but decreases for negative parent-offspring correlation. These effects of demographic heterogeneity on lambda have important implications for population dynamics, population viability analysis, and evolution.