Hand tool injuries at work: A surveillance perspective

This paper reports results of a surveillance study of work injuries caused by power and nonpower hand tools. Analyzing 129,399 case reports of hand tool injury compensation claims from the 1983 Supplementary Data System of the Bureau of Labor Statistics, the authors determined that nonpower hand tool injury rates were highest in agriculture, followed by construction, mining, and retail trades. For power hand tool injury rates, the order was: construction, agriculture, manufacturing, and mining. Among nonpower hand tools, hand knives were prominent, causing large proportions of injuries to workers in the food preparation occupations and farm laborers. Power hand tool injuries were most often associated with saws, which accounted for large proportions of injuries to lumbermen, carpenters, and miscellaneous laborers. Most injuries could be described as acute trauma involving upper extremities, but musculoskeletal injuries were also documented in substantial numbers. The authors provide suggestions for focused investigations to follow the surveillance effort reported here.     

Spatially constrained clustering and upper level set scan hotspot detection in surveillance geoinformatics

We discuss upper level set (ULS) scan as a type of spatially constrained clustering in relation to two ways of imposing the spatial constraint, retrospectively versus progressively. We show that ULS scan produces the same results both ways; whereas two popular clustering techniques, single-linkage and K-means, can yield different results when spatial constraints are imposed retrospectively versus progressively. The ULS scan approach examines spatially connected components of a tessellation as a threshold is moved from the highest level (value) in the data to the lowest level. When the variable of interest on the tessellation is a rate of incidence, then a significance test is available based on binomial or Poisson null models and Monte Carlo techniques. This is a common context for detecting hotspots of diseases in epidemiological work. We also discuss an approach for extending the univariate methodology to accommodate multivariate contexts. Received: September 2005 / Revised: February 2006 This material is based upon work supported by (i) the National Science Foundation under Grant No. 0307010, (ii) the United States Environmental Protection Agency under Grant No. CR-83059301 and (iii) the Pennsylvania Department of Health using Tobacco Settlement Funds under Grant No. ME 01324. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the agencies.     

Multiscale advanced raster map analysis system: Definition, design and development

This paper brings together a multidisciplinary initiative to develop advanced statistical and computational techniques for analyzing, assessing, and extracting information from raster maps. This information will provide a rigorous foundation to address a wide range of applications including disease mapping, emerging infectious diseases, landscape ecological assessment, land cover trends and change detection, watershed assessment, and map accuracy assessment. It will develop an advanced map analysis system that integrates these techniques with an advanced visualization toolbox, and use the system to conduct large case studies using rich sets of raster data, primarily from remotely sensed imagery. As a result, it will be possible to study and evaluate raster maps of societal, ecological, and environmental variables to facilitate quantitative characterization and comparative analysis of geospatial trends, patterns, and phenomena. In addition to environmental and ecological studies, these techniques and tools can be used for policy decisions at national, state, and local levels, crisis management, and protection of infrastructure. Geospatial data form the foundation of an information-based society. Remote sensing has been a vastly under-utilized resource involving a multi-million dollar investment at the national levels. Even when utilized, the credibility has been at stake, largely because of lack of tools that can assess, visualize, and communicate accuracy and reliability in timely manner and at desired confidence levels. Consider an imminent 21st century scenario: What message does a multi-categorical map have about the large landscape it represents? And at what scale, and at what level of detail? Does the spatial pattern of the map reveal any societal, ecological, environmental condition of the landscape? And therefore can it be an indicator of change? How do you automate the assessment of the spatial structure and behavior of change to discover critical areas, hot spots, and their corridors? Is the map accurate? How accurate is it? How do you assess the accuracy of the map? How do we evaluate a temporal change map for change detection? What are the implications of the kind and amount of change and accuracy on what matters, whether climate change, carbon emission, water resources, urban sprawl, biodiversity, indicator species, human health, or early warning? And with what confidence? The proposed research initiative is expected to find answers to these questions and a few more that involve multi-categorical raster maps based on remote sensing and other geospatial data. It includes the development of techniques for map modeling and analysis using Markov Random Fields, geospatial statistics, accuracy assessment and change detection, upper echelons of surfaces, advanced computational techniques for geospatial data mining, and advanced visualization techniques.     

Chemical defense of a rare mint plant

Summary Analyses of leaf extracts ofDicerandra frutescens, a highly aromatic mint plant from central Florida listed as an endangered species, revealed presence of 12 closely related monoterpenes. The principal of these, (+)—trans-pulegol, is a new natural product, the synthesis of which is described. The terpenes are produced in glandular capsules that release their contents upon injury of the leaf. Data from bioassays with ants and cockroaches indicate that the terpenes serve for defense against insects.Dicerandra does, however, have a leaf-eating enemy, the caterpillar of a pyralid moth,Pyrausta panopealis. The discovery of a new natural product from an endangered species raises questions about the chemical implications of species extinction.     

AQUATIC HABITAT CONDITION INDEX,STREAM TYPE,AND LWESTOCK BANK DAMAGE IN NORTHERN NEVADA1

ABSTRACT: The quality of stream habitat varies for a variety of natural and anthropogenic reasons not identified by a condition index. However, many people use condition indices to indicate management needs or even direction. To better sort natural from livestock influences, stream types and levels of ungulate bank damage were regulated to estimates of aquatic habitat condition index and stream width parameters in a large existing stream inventory data base. Pool/riffle ratio, pool structure, stream bottom materials, soil stability, and vegetation type varied significantly with stream type. Pool/riffle ratio, soil and vegetation stability varied significantly with ungulate bank damage level. Soil and vegetation stability were highly cross-correlated. Riparian area width did not vary significantly with either stream type or ungulate bank damage. Variation among stream types indicates that riparian management and monitoring should be stream type and reach specific.     

LONG-TERM AQUATIC HABITAT RESTORATION: MAHOGANY CREEK,NEVADA, AS A CASE STUDY1

ABSTRACT: We compared the recovery from abusive grazing of aquatic habitat due to different range management on two geomorphically similar rangeland streams in northwest Nevada. Managers excluded livestock from the Mahogany Creek watershed from 1976 to 1990 while allowing rotation of rest grazing on its tributary Summer Camp Creek. Bank stability, defined as the lack of apparent bank erosion or deposition, improved through the study period on both streams, but periodic grazing and flooding decreased stability more on Summer Camp Creek than flooding alone on Mahogany Creek. Pool quantity and quality on each stream decreased because of coarse woody debris removal and sediment deposition during a drought. Fine stream bottom sediments decreased five years after the removal of livestock, but sedimentation increased during low flows in both streams below road crossings. Tree cover increased 35 percent at both streams. Thus, recovery of stability and cover and decreased sedimentation are compatible with rotation of rest grazing on Summer Camp Creek. Width/depth ratio and gravel/cobble percent did not change because they are inherently stable in this stream type. Management activities such as coarse woody debris removal limited pool recover and road crossings increased sedimentation.     

PREDICTABILITY OF SURFACE WATER POLLUTION LOADING IN PENNSYLVANIA USING WATERSHED‐BASED LANDSCAPE MEASUREMENTS1

ABSTRACT: We formally evaluated the relationship between landscape characteristics and surface water quality in the state of Pennsylvania (USA) by regressing two different types of pollutant responses on landscape variables that were measured for whole watersheds. One response was the monthly exported mass of nitrogen estimated from field measurements, while the other response was a GIS‐modeled pollution potential index. Regression models were built by the stepwise selection protocol, choosing an optimal set of landscape predictors. After factoring out the effect of physiography, the dominant predictors were the proportion of “annual herbaceous” land and “total herbaceous” land for the nitrogen loading and pollution potential index, respectively. The strength of these single predictors is encouraging because the marginal land cover proportions are the simplest landscape measurements to obtain once a land cover map is in hand; however, the optimal set of predictors also included several measurements of spatial pattern. Thus, for watersheds at this general hierarchical scale, gross landscape pattern may be an important influence on instream pollution loading. Overall, there is strong evidence that using landscape measurements alone, obtained solely from remotely sensed data, can explain most of the water quality variability (R²= approx. 0.75) within these watersheds.     

Life-history correlates of extinction risk and recovery potential

Extinction risk is inversely associated with maximum per capita population growth rate (r(max)). However, this parameter is not known for most threatened species, underscoring the value in identifying correlates of r(max) that, in the absence of demographic data, would indirectly allow one to identify species and populations at elevated risk of extinction and their associated recovery potential. We undertook a comparative life-history analysis of 199 species from three taxonomic classes: Chondrichthyes (e.g., sharks; n = 82), Actinopterygii (teleost or bony fishes; n = 47), and Mammalia (n = 70, including 16 marine species). Median r(max) was highest for (and similar between) terrestrial mammals (0.71) and teleosts (0.43), significantly lower among chondrichthyans (0.26), and lower still in marine mammals (0.07). Age at maturity was the primary (and negative) correlate of r(max). In contrast, although body size was negatively correlated with r(max) in chondrichthyans and mammals, evidence of an association in teleosts was equivocal, and fecundity was not related to r(max) in fishes, despite recurring assertions to the contrary. Our analyses suggest that age at maturity can serve as a universal predictor of extinction risk in fishes and mammals when r(max) itself is unknown. Moreover, in contrast to what is generally expected, the recovery potential of teleost fishes does not differ from that of terrestrial mammals. Our findings are supportive of the application of extinction-risk criteria that are based on generation time and that are independent of taxonomic affinity.     

Fragmentation profiles for real and simulated landscapes

When a natural landscape is represented by a series of categorical raster maps of varying resolution, a multiresolution characterization of spatial pattern can be obtained in which entropy is computed at each resolution conditional on the next coarser resolution. The series of entropy values is plotted as a function of resolution, resulting in a multiresolution profile of fragmentation pattern in the landscape. If a categorical raster map is available at a single resolution only, a series of degraded maps at increasingly coarser resolutions is generated and the fragmentation profile is computed for this series. An algorithm has been developed for obtaining the profile directly from the single resolution map without having to generate and store the coarser resolution maps. A hierarchical stochastic model is described for simulating categorical raster maps and the fragmentation profile of the generating process is obtained in terms of the model parameters. These process profiles provide benchmarks for assessing empirical profiles obtained from raster maps of actual landscapes. Methods of the paper are applied to several watersheds of Pennsylvania using landcover maps derived from satellite imagery. These examples indicate that characteristic landscape types induce characteristic features in their fragmentation profiles.