TIMBER HARVEST IMPACTS ON SMALL HEADWATER STREAM CHANNELS IN THE COAST RANGES OF WASHINGTON1

ABSTRACT: We evaluated changes in channel habitat distributions, particle‐size distributions of bed material, and stream temperatures in a total of 15 first‐or second‐order streams within and nearby four planned commercial timber harvest units prior to and following timber harvest. Four of the 15 stream basins were not harvested, and these streams served as references. Three streams were cut with unthinned riparian buffers; one was cut with a partial buffer; one was cut with a buffer of non‐merchantable trees; and the remaining six basins were clearcut to the channel edge. In the clearcut streams, logging debris covered or buried 98 percent of the channel length to an average depth of 0.94 meters. The slash trapped fine sediment in the channel by inhibiting fluvial transport, and the average percentage of fines increased from 12 percent to 44 percent. The trees along buffered streams served as a fence to keep out logging debris during the first summer following timber harvest. Particle size distributions and habitat distributions in the buffered and reference streams were largely unchanged from the pre‐harvest to post‐harvest surveys. The debris that buried the clearcut streams effectively shaded most of these streams and protected them from temperature increases. These surveys have documented immediate channel changes due to timber harvest, but channel conditions will evolve over time as the slash decays and becomes redistributed and as new vegetation develops on the channel margins.     

ESTABLISHING WATERSHED MANAGEMENT IN LAW: NEW ZEALAND'S EXPERIENCE1

ABSTRACT: New Zealand is one of the first countries in the world to enshrine the concept of watershed management in law, through institutional arrangements and the Resource Management Act of 1991 ‐ a law constructed on a watershed management legacy begun in 1941. This paper outlines the development of New Zealand's Resource Management Act (as it applies to water management) and the lessons that have been learned in its implementation.     

USING FIELD SCALE MODELS TO PREDICT PEAK FLOWS ON AGRICULTURAL WATERSHEDS1

The goal of this study was to develop a methodology for generating storm hydrographs at a watershed scale based on daily runoff estimates from a field scale model. The methodology was evaluated on a small agricultural watershed using the ADAPT field scale process model. A comparison of observed and predicted peak flows for 11 of the largest events that occurred in a three year period gave r² values of 0.84, 0.82, and 0.81 when the watershed was subdivided into 1, 5, and 10 sub watersheds. However, all other statistical measures improved when the watershed was subdivided into at least five sub watersheds. Guidelines need to be developed on the use of the procedure but it first needs to be evaluated on several watersheds that exhibit a range in sizes, land uses, slopes, and soil properties.     

Pyrrhic victories: the cost to the board of ousting the CEO

Going against anecdotal evidence and common perception, the findings presented here show that boards who take action against their CEOs do so only at great cost to themselves, winning only a pyrrhic victory. Indeed, the findings presented show three distinct levels of board turnover. Normal attrition in periods of continuity produced a turnover of 10.99 per cent over two years; routine retirement exists (22.35 per cent) produced a similar turnover level to forced exits which did not imply a failure of the board to perform its monitoring function (25.36 per cent). However, forced CEO exits which implied a failure in the board's monitoring and advising roles caused a dramatically higher level of subsequent board turnover (40.55 per cent). These findings demonstrate that is not only the CEO that is forced to sacrifice his or her job when a company is in distress, but that the board is also accountable for its failure to perform its monitoring and advising duties adequately. Copyright © 1999 John Wiley & Sons, Ltd.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.