Use of data on avian demographics and site persistence during overwintering to assess quality of restored riparian habitat

Monitoring responses by birds to restoration of riparian vegetation is relatively cost-effective, but in most assessments species-specific abundances, not demography, are monitored. Data on birds collected during the nonbreeding season are particularly lacking. We captured birds in mist nets and resighted banded birds to estimate species richness and diversity, abundance, demographic indexes, and site-level persistence of permanent-resident and overwintering migrants in remnant and restored riparian sites in California. Species richness in riparian remnants was significantly higher than in restored sites because abundances of uncommon permanent residents were greater in remnants. Species richness of overwintering migrants did not differ between remnants and restored sites. Responses among overwintering migrants (but not permanent residents) to remnant and restored riparian sites differed. Capture rates were higher in remnant or restored riparian sites for 7 of 10 overwintering migratory species. For Lincoln's Sparrows (Melospiza lincolnii) and White-crowned Sparrows (Zonotrichia leucophrys) proportions of older birds were significantly higher in remnants, even though capture rates of these species were higher in restored sites. Overwinter persistence of 4 migrant species was significantly higher in remnant than in restored sites. A higher proportion of Hermit Thrushes (Catharus guttatus, 56.3%), older Fox Sparrows (Passerella iliaca, 57.1%), Lincoln's Sparrows (59.7%), and White-crowned Sparrows (67.8%) persisted in remnants than restored sites. Our results suggest restored riparian sites provide habitat for a wide variety of species in comparable abundances and diversity as occurs in remnant riparian sites. Our demographic and persistence data showed that remnants supported some species and age classes to a greater extent than restored sites.     

Effects of river-flow regulation on anuran occupancy and abundance in riparian zones

The natural flow regimes of rivers worldwide have been heavily altered through anthropogenic activities, and dams in particular have a pervasive effect on riverine ecosystems. Flow-regulation effects of dams negatively affect species diversity and abundance of a variety of aquatic animals, including invertebrates and fishes. However, the effects on semiaquatic animals are relatively unknown. We conducted anuran calling surveys at 42 study locations along the Broad and Pacolet Rivers in South Carolina to address the potential effects of flow regulation by damming on anuran occupancy and abundance. We estimated occupancy and abundance with Program PRESENCE. Models incorporated distance upstream and downstream from the nearest dam as covariates and urbanization pressure as an alternative stressor. Distance from dam was associated with occupancy of 2 of the 9 anuran species in our analyses and with abundance of 6 species. In all cases, distance downstream from nearest dam was a better predictor of occupancy and abundance than distance upstream from nearest dam. For all but one species, distance downstream from nearest dam was positively correlated with both occupancy and abundance. Reduced occupancy and abundance of anurans likely resulted from downstream alterations in flow regime associated with damming, which can lead to reduced area of riparian wetlands that serve as anuran breeding habitat. Our results showed that damming has a strong negative effect on multiple anuran species across large spatial extents and suggest that flow regulation can affect semiaquatic animals occupying riparian zones.     

Growth and sexual maturity of the northern propellerclam (<Emphasis Type="Italic">Cyrtodaria siliqua</Emphasis>) in Eastern Canada,with bomb radiocarbon age validation

The northern propellerclam Cyrtodaria siliqua is a common bycatch in the Arctic surfclam, Mactromeris polynyma fishery on Banquereau Bank in Eastern Canada. Samples of the propellerclam from this exploited fishery were used to determine the life history characteristics of the population. The age structure of the population is dominated by old animals to ages exceeding 100 years. We validated the age estimates for the propellerclam through analysis of bomb-produced radiocarbon in the shell growth increments deposited before, during and after the atmospheric atomic bomb testing periods of the 1950s and 1960s. Radiocarbon from shells with presumed birth dates between the late 1950s and 1970s clearly reflected the sharp increase in oceanic radiocarbon attributable to previous nuclear testing, indicating that age estimates based on shell increment counts are accurate. Estimates of von Bertalanffy growth parameters revealed that the growth rate of the population was relatively rapid for the first 20 years of life, slowing down to very low growth rates thereafter. Sexual maturity was estimated as being reached at 28.6 mm in length and 4.7 years in age. Size–weight morphometric relationships were also calculated.     

A framework for evaluating regional-scale numerical photochemical modeling systems

This paper discusses the need for critically evaluating regional-scale (~200–2,000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model’s credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper.     

Reconstructing the historic demography of an endangered seabird

Reducing extinction risk for threatened species requires determining which demographic parameters are depressed and causing population declines. Museum collections may constitute a unique, underutilized resource for measuring demographic changes over long time periods using age-ratio analysis. We reconstruct the historic demography of a U.S. federally endangered seabird, the Marbled Murrelet (Brachyramphus marmoratus), from specimens collected approximately 100 years ago for comparison with predictions from comparative analyses and with results from contemporary field studies using both age-ratio analysis and conventional demographic estimators. Reproduction in the late 1800s and early 1900s matched predictions from comparative analysis, but was 8-9 times greater than contemporary estimates, whereas adult survival was unchanged. Historic reproductive rates would support stable populations, but contemporary levels should result in population declines. Contemporary demographic estimates derived from age-ratio analysis were similar to estimates from conventional estimators. Using museum specimens to reconstruct historic demography provides a unique approach to identify causes of decline and to set demographic benchmarks for recovery of endangered species that meet most assumptions of age-ratio analysis.     

Effects of four decades of fire manipulation on woody vegetation structure in Savanna

The amount of carbon stored in savannas represents a significant uncertainty in global carbon budgets, primarily because fire causes actual biomass to differ from potential biomass. We analyzed the structural response of woody plants to long-term experimental burning in savannas. The experiment uses a randomized block design to examine fire exclusion and the season and frequency of burn in 192 7-ha experimental plots located in four different savanna ecosystems. Although previous studies would lead us to expect tree density to respond to the fire regime, our results, obtained from four different savanna ecosystems, suggest that the density of woody individuals was unresponsive to fire. The relative dominance of small trees was, however, highly responsive to fire regime. The observed shift in the structure of tree populations has potentially large impacts on the carbon balance. However, the response of tree biomass to fire of the different savannas studied were different, making it difficult to generalize about the extent to which fire can be used to manipulate carbon sequestration in savannas. This study provides evidence that savannas are demographically resilient to fire, but structurally responsive.     

Globalization of human infectious disease

Globalization has facilitated the spread of numerous infectious agents to all corners of the planet. Analysis of the Global Infectious Disease and Epidemiology Network (GIDEON) database quantitatively illustrates that the globalization of human infectious agents depends significantly on the range of hosts used. Infectious agents specific to humans are broadly and uniformly distributed, whereas zoonotic infectious agents are far more localized in their geographical distribution. Moreover, these patterns vary depending on transmission mode and infectious agent taxonomy. This dichotomy is unlikely to persist if certain aspects of globalization (for example, exotic species introductions) continue unabated. This raises a serious concern for public health and leaves nations with the task of determining the infectious agents that have the greatest potential to establish within their borders. At the advent of a century characterized by an apparent increase in emerging infectious diseases, these results have critical implications for public-health policy and future research pathways of infectious disease ecology.     

Geographic information system based manure application plan

A geographic information system (GIS) based manure application plan has been developed for the site-specific application of animal waste to agricultural fields in the Westbrook sub-catchment of the Murray-Darling Basin, south-east Queensland, Australia. Sites suitable for animal waste application were identified using a GIS based weighted linear combination (WLC) model. The degree of land suitability for animal waste application was determined using a range of social, economic, environmental, and agricultural factors. As eutrophication and toxic blue-green algae blooms are a known problem in the catchment, the manure application rates were limited to the rate of crop phosphorus removal. Maximum manure application rate was calculated spatially by taking the crop nutrient (P2O5) requirement and the manure nutrient (P2O5) content into account. The environmental suitability of the fields receiving animal waste was considered in prescribing the final application rate of solid and liquid manures generated by local animal production facilities. The degree of site suitability of the agricultural fields was also used to suggest manure management practices to minimise the socio-environmental risks and increase the nutrient use efficiency of the applied manure. The amount of ammonium nitrogen (NH4-N) that would be added to the soil by satisfying the P2O5 requirement using manure sources was also calculated and an applied NH4-N map was created. This map could be used to assist farmers identify additional nitrogen requirements after manure application.     

Carrying capacity as "Informed Judgment": the values of science and the science of values

Contemporary park and wilderness carrying capacity frameworks rely on formulation of standards of quality, which are defined as minimum acceptable resource and social conditions. Formulation of standards of quality involves elements of both science and values, and both of these elements must be integrated into informed judgments on the part of park and wilderness managers. That is, managers must ultimately make value-based judgments about the maximum acceptable level of visitor-caused impacts to the resource base and the quality of the visitor experience. However, such judgments should be as informed as possible by scientific data on the relationships between visitor use and resulting impacts and the degree to which park and wilderness visitors and other interest groups judge such impacts to be acceptable. Such information represents the “values of science” to managing carrying capacity in parks and wilderness. A growing body of literature has begun to address the corresponding “science of values,” and how this type of information might be integrated in park and wilderness management. Visitor-based research has employed normative theory and techniques to explore the acceptability of a range of resource and social impacts related to visitor use, and findings from these studies are being integrated into a body of knowledge and applied in management decision-making. Conceptual and methodological extensions of the normative approach are currently being explored in a variety of park and wilderness contexts, and new theoretical and empirical approaches are being adapted to address trade-offs inherent in carrying capacity. In these ways, the science of values is progressing to meet the opportunities and challenges of the values of science to park and wilderness management. The concept of carrying capacity, along with the theoretical and methodological approaches described in this paper, can be extended to a large number of natural resource and environmental issues.     

Using continuous PM2.5 monitoring data to report an air quality index

As stated in 40 CFR 58, Appendix G (2000), statistical linear regression models can be applied to relate PM2.5 continuous monitoring (CM) measurements with federal reference method (FRM) measurements, collocated or otherwise, for the purpose of reporting the air quality index (AQI). The CM measurements can then be transformed via the model to remove any bias relative to FRM measurements. The resulting FRM-like modeled measurements may be used to provide more timely reporting of a metropolitan statistical area's (MSA's) AQI. Of considerable importance is the quality of the model used to relate the CM and FRM measurements. The use of a poor model could result in misleading AQI reporting in the form of incorrectly claiming either good or bad air quality. This paper describes a measure of adequacy for deciding whether a statistical linear regression model that relates FRM and continuous PM2.5 measurements is sufficient for use in AQI reporting. The approach is the U.S. Environmental Protection Agency's (EPA's) data quality objectives (DQO) process, a seven-step strategic planning approach to determine the most appropriate data type, quality, quantity, and synthesis for a given activity. The chosen measure of model adequacy is r2, the square of the correlation coefficient between FRM measurements and their modeled counterparts. The paper concludes by developing regression models that meet this desired level of adequacy for the MSAs of Greensboro/Winston-Salem/High Point, NC; and Davenport/Moline/Rock Island, IA/IL. In both cases, a log transformation of the data appeared most appropriate. For the data from the Greensboro/Winston-Salem/High Point MSA, a simple linear regression model of the FRM and CM measurements had an r2 of 0.96, based on 227 paired observations. For the data from the Davenport/Moline/Rock Island MSA, due to seasonal differences between CM and FRM measurements, the simple linear regression model had to be expanded to include a temperature dependency, resulting in an r2 of 0.86, based on 214 paired observations.