Using Public Participation Geographic Information Systems to Identify Places of Watershed Service Provisioning

In this study, we used public participation geographic information systems methods to collect spatial data identifying places that stakeholders in Mobile Bay, Alabama think are important providers of watershed services. These methods allowed us to spatially analyze participatory data from general public respondents and directly compare them with other scientific data in a geographic information systems database. This study identified which places in the region participants believe are important providers of specific watershed services, including fish nurseries, storm protection, flood protection, and water quality protection, which would likely have public support for conservation. Additionally, we assessed the accuracy of participant watershed service identification using land cover data to identify inconsistencies and participant knowledge gaps. This information can be used to target outreach education efforts. We found that the accuracy with which participants correctly identified places with the necessary land cover to provide each service varied considerably. We believe this to be a useful tool for managers to elicit stakeholder input and to identify knowledge gaps regarding the provisioning of watershed services.     

Empirical Estimation of Stream Discharge Using Channel Geometry in Low‐Gradient,Sand‐Bed Streams of the Southeastern Plains

Manning's equation is used widely to predict stream discharge (Q) from hydraulic variables when logistics constrain empirical measurements of in‐bank flow events. Uncertainty in Manning's roughness (n_M) is the major source of error in natural channels, and sand‐bed streams pose difficulties because flow resistance is affected by flow‐dependent bed configuration. Our study was designed to develop and validate models for estimating Q from channel geometry easily derived from cross‐sectional surveys and available GIS data. A database was compiled consisting of 484 Q measurements from 75 sand‐bed streams in Alabama, Georgia, South Carolina, North Carolina (Southeastern Plains), and Florida (Southern Coastal Plain), with six New Zealand streams included to develop statistical models to predict Q from hydraulic variables. Model error characteristics were estimated with leave‐one‐site‐out jackknifing. Independent data of 317 Q measurements from 55 Southeastern Plains streams indicated the model (Q = A_cR_H^0.6906S^0.1216; where A_c is the channel area, R_H is the hydraulic radius, and S is the bed slope) best predicted Q, based on Akaike's information criterion and root mean square error. Models also were developed from smaller Q range subsets to explore if subsets increased predictive ability, but error fit statistics suggested that these were not reasonable alternatives to the above equation. Thus, we recommend the above equation for predicting in‐bank Q of unbraided, sandy streams of the Southeastern Plains.     

Cloud chemistry in the eastern United States, as sampled from three high-elevation sites along the Appalachian Mountains

Atmospheric deposition of acidic cloud water is thought to be one of the causes for the recent forest decline in industrialized areas of the world. The present paper presents results from the Mountain Acid Deposition Program (MADPro), a part of EPA's Clean Air Status and Trends Network, (CASTnet). We used automated cloud water collectors at three selected mountain sites (Whiteface Mt., NY; Whitetop Mt., VA; and Clingman's Dome, TN) to take hourly samples from non-precipitating clouds during temperate (non- freezing) seasons of each year from 1994 to 1997. Samples were promptly analyzed for pH, conductivity, and concentration of dissolved ions. Cloud liquid water content (LWC) and meteorological parameters were measured at each site. Mean cloud frequencies and LWC of clouds were higher at Whiteface Mt., NY, than in the Southern Appalachians. The four most prevalent ions found in cloud water samples were usually, in order of decreasing concentration: sulfate (SO²⁻₄) hydrogen (H⁺), ammonium (NH₄⁺), and nitrate (NO₃⁻). Within cloud events the concentration of these major ions tended to co-vary. Typically there was an inverse relationship between LWC of the cloud and ionic concentration of the cloud water. During the sampling season, the highest ionic concentrations were seen during mid-summer. Ionic concentrations of samples from the southern sites were significantly higher than samples from Whiteface Mt., but further analysis indicates that this is at least partially due to the north–south difference in the LWC of clouds. MADPro results are shown to be comparable with previous studies of cloud chemistry in North America.     

Measuring climate for work group innovation: development and validation of the team climate inventory

This paper reports the development and psychometric validation of a multi-dimensional measure of facet-specific climate for innovation within groups at work: the Team Climate Inventory (TCI). Brief reviews of the organizational climate and work group innovation literatures are presented initially, and the need for measures of facet-specific climate at the level of the proximal work group asserted. The four-factor theory of facet-specific climate for innovation, which was derived from these reviews, is described, and the procedures used to operationalize this model into the original version measure described. Data attesting to underlying factor structure, internal homogeneity, predictive validity and factor replicability across groups of the summarized measure are presented. An initial sample of 155 individuals from 27 hospital management teams provided data for the exploratory factor analysis of this measure. Responses from 121 further groups in four occupations (35 primary health care teams, 42 social services teams, 20 psychiatric teams and 24 oil company teams; total N=971) were used to apply confirmatory factor analysis techniques. This five-factor, 38-item summarized version demonstrates robust psychometric properties, with acceptable levels of reliability and validity. Potential applications of this measure are described and the implication of these findings for the measurement of proximal work group climate are discussed. © 1998 John Wiley & Sons, Ltd.     

Bench-scale testing of a novel soil PFAS treatment train for informed remedial planning and decision-making

Bench-scale batch tests were conducted to assess the potential applicability of a combined separation/concentration/destruction treatment train to address soils and sediments impacted by per- and polyfluoroalkyl substances (PFAS) contamination at Schriever Space Force Base with historic aqueous film-forming foam (AFFF). Specifically, a novel treatment train coupling soil washing (for treatment of impacted soil/sediment) with foam fractionation (for treatment of the wash water [WW] generated during soil washing) and electrochemical oxidation (ECO, for treatment of the foam fractionate generated during foam fractionation) was evaluated at the bench scale using site-specific materials. Results presented herein show that the AFFF-impacted sandy soils with low organic content were amenable to treatment via soil washing. However, the removal of hydrophobic PFAS, such as perfluorooctanesulfonic acid (PFOS), from the organic-rich sediments was challenging. Results from batch desorption experiments were within a factor of 2 of those generated by soil washing bench studies, suggesting that simple batch tests can potentially be used to reasonably predict the treatment efficacy of soil washing. Long-chained perfluoroalkyl acids (PFAAs) within the WW were removed more effectively in the foam fractionation studies as compared to short-chain PFAAs. Addition of a surfactant, such as cetrimonium bromide (CTAB), enhanced foaming but only marginally improved the treatment of short-chained PFAAs and in some cases inhibited PFOS removal. ECO reduced PFAS concentrations in the foam fractionate generated during foam fractionation by several orders of magnitude. However, generation of unwanted byproducts may warrant further treatment and/or disposal. Overall, results from this study provide a novel data set highlighting the site-dependent nature of these PFAS remedial technologies and how simple, low-cost bench tests can be reliably leveraged for informed decision-making during PFAS remedial planning.     

Trait groups as management entities in a complex,multispecies reef fishery

Localized stressors compound the ongoing climate-driven decline of coral reefs, requiring natural resource managers to work with rapidly shifting paradigms. Trait-based adaptive management (TBAM) is a new framework to help address changing conditions by choosing and implementing management actions specific to species groups that share key traits, vulnerabilities, and management responses. In TBAM maintenance of functioning ecosystems is balanced with provisioning for human subsistence and livelihoods. We first identified trait-based groups of food fish in a Pacific coral reef with hierarchical clustering. Positing that trait-based groups performing comparable functions respond similarly to both stressors and management actions, we ascertained biophysical and socioeconomic drivers of trait-group biomass and evaluated their vulnerabilities with generalized additive models. Clustering identified 7 trait groups from 131 species. Groups responded to different drivers and displayed divergent vulnerabilities; human activities emerged as important predictors of community structuring. Biomass of small, solitary reef-associated species increased with distance from key fishing ports, and large, solitary piscivores exhibited a decline in biomass with distance from a port. Group biomass also varied in response to different habitat types, the presence or absence of reported dynamite fishing activity, and exposure to wave energy. The differential vulnerabilities of trait groups revealed how the community structure of food fishes is driven by different aspects of resource use and habitat. This inherent variability in the responses of trait-based groups presents opportunities to apply selective TBAM strategies for complex, multispecies fisheries. This approach can be widely adjusted to suit local contexts and priorities.     

Does invasion by Pteridium aquilinum (Dennstaedtiaceae) affect the ecological succession in Atlantic Forest areas after a fire?

Environmental Science and Pollution Research - Pteridium aquilinum (Dennstaedtiaceae) colonization affects ecological and restoration processes. The knowledge of the impacts on the ecological...