The scale and cause of spatial heterogeneity in strength of temporal density dependence

The importance of density dependence in natural communities continues to spark much debate because it is fundamental to population regulation. We used temporal manipulations of density to explore potentially stabilizing density dependence in early survivorship among six local populations of a tropical damselfish (Dascyllus flavicaudus). Specifically, we tested the premise that spatial heterogeneity in the strength of temporal density dependence would reflect variation in density of predators, the agent of mortality. Our field manipulations revealed that mortality among successive cohorts of young fishes was density dependent at each reef, but that its strength varied by approximately 1.5 orders of magnitude. This spatial heterogeneity was well predicted by variation among the six reefs in the density of predatory fishes that consume juvenile damselfishes. Because density dependence arose from competition for enemy-free space within a shelter coral, the mortality consequence of the competition depended on the neighborhood density of predators. Thus, the scale of heterogeneity in the density dependence largely reflected attributes of the environment that shaped the local abundance of predators. These results have important implications for how ecologists explore regulatory processes in nature. Failure to account for spatial variation could frequently yield misleading conclusions regarding density dependence as a stabilizing process, obscure underlying mechanisms influencing its strength, and provide no insight into the spatial scale of the heterogeneity. Further, models of population dynamics will be improved when experimental approaches better estimate the magnitude and causes of variation in strength of stabilizing density dependence.     

Variation in herbivore-mediated indirect effects of an invasive plant on a native plant

Theory predicts that damage by a shared herbivore to a secondary host plant species may either be higher or lower in the vicinity of a preferred host plant species. To evaluate the importance of ecological factors, such as host plant proximity and density, in determining the direction and strength of such herbivore-mediated indirect effects, we quantified oviposition by the exotic weevil Rhinocyllus conicus on the native wavyleaf thistle Cirsium undulatum in midgrass prairie on loam soils in the upper Great Plains, USA. Over three years (2001-2003), the number of eggs laid by R. conicus on C. undulatum always decreased significantly with distance (0-220 m) from a musk thistle (Carduus nutans L.) patch. Neither the level of R. conicus oviposition on C. undulatum nor the strength of the distance effect was predicted by local musk thistle patch density or by local C. undulatum density (<5 m). The results suggest that high R. conicus egg loads on C. undulatum near musk thistle resulted from the native thistle's co-occurrence with the coevolved preferred exotic host plant and not from the weevil's response to local host plant density. Mean egg loads on C. undulatum also were greater at sites with higher R. conicus densities. We conclude that both preferred-plant proximity and shared herbivore density strongly affected the herbivore-mediated indirect interaction, suggesting that such interactions are important pathways by which invasive exotic weeds can indirectly impact native plants.     

Chinook salmon use of spawning patches: relative roles of habitat quality, size, and connectivity.

Declines in many native fish populations have led to reassessments of management goals and shifted priorities from consumptive uses to species preservation. As management has shifted, relevant environmental characteristics have evolved from traditional metrics that described local habitat quality to characterizations of habitat size and connectivity. Despite the implications this shift has for how habitats may be prioritized for conservation, it has been rare to assess the relative importance of these habitat components. We used an information-theoretic approach to select the best models from sets of logistic regressions that linked habitat quality, size, and connectivity to the occurrence of chinook salmon (Oncorhynchus tshawytscha) nests. Spawning distributions were censused annually from 1995 to 2004, and data were complemented with field measurements that described habitat quality in 43 suitable spawning patches across a stream network that drained 1150 km2 in central Idaho. Results indicated that the most plausible models were dominated by measures of habitat size and connectivity, whereas habitat quality was of minor importance. Connectivity was the strongest predictor of nest occurrence, but connectivity interacted with habitat size, which became relatively more important when populations were reduced. Comparison of observed nest distributions to null model predictions confirmed that the habitat size association was driven by a biological mechanism when populations were small, but this association may have been an area-related sampling artifact at higher abundances. The implications for habitat management are that the size and connectivity of existing habitat networks should be maintained whenever possible. In situations where habitat restoration is occurring, expansion of existing areas or creation of new habitats in key areas that increase connectivity may be beneficial. Information about habitat size and connectivity also could be used to strategically prioritize areas for improvement of local habitat quality, with areas not meeting minimum thresholds being deemed inappropriate for pursuit of restoration activities.     

Inhibition of pancreatic carboxypeptidase A: A possible mechanism of interaction between penicillic acid and ochratoxin A

Abstract

Penicillic acid and ochratoxin A are environmentally important toxic fungal metabolites (mycotoxins) that are synergistic in combination. The effects of penicillic acid on the pancreatic enzyme, :arboxypeptidase A were investigated in vitro and in vivo. A broad range of inhibition in vitro of the enzyme by PA was demonstrated with a half‐maximal inhibitory concentration equal to 1.1 x 10^‐4M PA. Inhibition of carboxypeptidase A was time and temperature dependent, and resulted in decreased conversion of parent ochratoxin A to the non‐toxic metabolite, ochratoxin alpha. Studies in vivo demonstrated a penicillic acid‐dependent inhibition of pancreatic carboxypeptidase A activity in the mouse and the chicken following multiple oral exposure. It is postulated that the mode of toxic interaction of the two mycotoxins may be due, in part, to impaired detoxification of ochratoxin A through peni‐cillic acid depletion of carboxypeptidase A activity.     

Airshed Model Evaluation of Reactivity Adjustment Factors Calculated with the Maximum Incremental Reactivity Scale for Transitional-Low Emission Vehicles

Abstract

The California Air Resources Board recently adopted regulations for light- and medium-duty vehicles that require reductions in the ozone-forming potential or “reactivity,” rather than the mass, of nonmethane organic gas (NMOG) emissions. The regulations allow sale of all alternatively fueled vehicles (AFVs) that meet NMOG exhaust emission standards equivalent in reactivity to those set for vehicles fueled with conventional gasoline. Reactivity adjustment factors (RAFs), the ratio of the reactivity (per gram) of the AFV exhaust to that of the conventionally fueled vehicle (CFV), are used to correct the stringent exhaust emission standards. Complete chemical speciation of the exhaust and conversion of each NMOG species to an appropriate mass of ozone using the maximum incremental reactivity (MIR) scale of Carter determines the RAF. The MIR approach defines reactivity where NMOG control is the most effective strategy in reducing ozone concentrations, and assumes it is not important to define reactivity at other conditions, i.e., where NO_x is the limiting precursor.

This study used the Carnegie/California Institute of Technology airshed model to evaluate whether the RAF-adjusted AFV emissions result in ozone impacts equivalent to those of CFV emissions. A matrix of two ozone episodes in the South Coast Air Basin (SoCAB) of California, two base emission inventories, and exhaust emissions from three alternative fuels that meet the first level of the low emission vehicle standards bounds the expected range of conditions. Although very good agreement was found previously for individual NMOG species,² this study noted deviations of up to ±15 percent from the equal ozone impacts for any vehicle/fuel combination required by the California regulations. These deviations appear to be attributable to differences in spatial and temporal patterns of emissions between vehicle fleets, rather than a problem with the MIR approach. The first formally adopted RAF, a value of 0.41 for 85 percent methanol/15 percent gasoline-fueled vehicles, includes a 10 percent increase based on the airshed modeling. The correction to the RAF is different for other fuels and may be different for air basins other than the SoCAB.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Four priorities for new links between conservation science and accounting research

Article impact statement: New collaborations with accounting research can improve conservation impact of ecosystem-based information systems.     

Comparison of SOC estimates and uncertainties from aerosol chemical composition and gas phase data in Atlanta

In the Southeastern US, organic carbon (OC) comprises about 30% of the PM_2.5 mass. A large fraction of OC is estimated to be of secondary origin. Long-term estimates of SOC and uncertainties are necessary in the evaluation of air quality policy effectiveness and epidemiologic studies. Four methods to estimate secondary organic carbon (SOC) and respective uncertainties are compared utilizing PM_2.5 chemical composition and gas phase data available in Atlanta from 1999 to 2007. The elemental carbon (EC) tracer and the regression methods, which rely on the use of tracer species of primary and secondary OC formation, provided intermediate estimates of SOC as 30% of OC. The other two methods, chemical mass balance (CMB) and positive matrix factorization (PMF) solve mass balance equations to estimate primary and secondary fractions based on source profiles and statistically-derived common factors, respectively. CMB had the highest estimate of SOC (46% of OC) while PMF led to the lowest (26% of OC). The comparison of SOC uncertainties, estimated based on propagation of errors, led to the regression method having the lowest uncertainty among the four methods. We compared the estimates with the water soluble fraction of the OC, which has been suggested as a surrogate of SOC when biomass burning is negligible, and found a similar trend with SOC estimates from the regression method. The regression method also showed the strongest correlation with daily SOC estimates from CMB using molecular markers. The regression method shows advantages over the other methods in the calculation of a long-term series of SOC estimates.     

Physical characterization of the fine particle emissions from commercial aircraft engines during the Aircraft Particle Emissions eXperiment (APEX) 1–3

The fine particulate matter (PM) emissions from nine commercial aircraft engine models were determined by plume sampling during the three field campaigns of the Aircraft Particle Emissions Experiment (APEX). Ground-based measurements were made primarily at 30 m behind the engine for PM mass and number concentration, particle size distribution, and total volatile matter using both time-integrated and continuous sampling techniques. The experimental results showed a PM mass emission index (EI) ranging from 10 to 550 mg kg^?1 fuel depending on engine type and test parameters as well as a characteristic U-shaped curve of the mass EI with increasing fuel flow for the turbofan engines tested. Also, the Teflon filter sampling indicated that ～40–80% of the total PM mass on a test-average basis was comprised of volatile matter (sulfur and organics) for most engines sampled. The number EIs, on the other hand, varied from ～10¹⁵ to 10¹⁷ particles kg^?1 fuel with the turbofan engines exhibiting a logarithmic decay with increasing fuel flow. Finally, the particle size distributions of the emissions exhibited a single primary mode that were lognormally distributed with a minor accumulation mode also observed at higher powers for all engines tested. The geometric (number) mean particle diameter ranged from 9.4 to 37 nm and the geometric standard deviation ranged from 1.3 to 2.3 depending on engine type, fuel flow, and test conditions.     

Genetic structure of the southeastern United States loggerhead turtle nesting aggregation: evidence of additional structure within the peninsular Florida recovery unit

The southeastern United States supports one of two large loggerhead turtle (Caretta caretta) nesting aggregations worldwide and is therefore critical to global conservation and recovery efforts for the species. Previous studies have established the presence of four demographically distinct nesting populations (management units) corresponding to beaches from (1) North Carolina through northeastern Florida, (2) peninsular Florida, (3) the Dry Tortugas, and (4) northwest Florida. Temporal and geographic genetic structure of the nesting aggregation was examined utilizing partial mitochondrial control region haplotype frequencies from 834 samples collected over the 2002 through 2008 nesting seasons from 19 beaches as well as previously published haplotype data. Most rookeries did not exhibit interannual genetic variation. However, the interannual variation detected did significantly impact the interpretation of spatial genetic structure in northeastern Florida. Based on pairwise F _ST comparisons, exact tests of population differentiation, and analysis of molecular variance, the present study upholds the distinctiveness of the four currently recognized management units and further supports recognition of discrete central eastern, southern (southeastern and southwestern), and central western Florida management units. Further subdivision may be warranted, but more intensive genetic sampling is required. In addition, tools such as telemetry and mark-recapture are needed to complement genetic data and overcome limitations of genetic markers in resolving loggerhead turtle rookery connectivity in the southeastern USA.