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We used simple regression models to demonstrate an association between land use and parr survival of chinook salmon Oncorhynchus tshawytscha from overwintering areas in the Snake River drainage of Idaho and Oregon to the first main‐stem dam encountered during emigration to the Pacific Ocean. We used data on tagged (passive integrated transponder tags) releases of naturally produced Snake River spring–summer chinook parr and subsequent tag detections, as well as indices of land use, vegetation, and road density. We spot‐checked the land‐use and vegetation indices in a field survey of spawning and rearing areas in the summer of 1999, and we believe that they are reliable indicators of land‐use patterns. The models also employed month of release, length of parr at release, and a drought index as independent variables. The models were developed and tested using parr tagged from 1992 through 1998. Age‐0 parr that reared in wilderness areas (a land‐use category; not necessarily federally designated Wilderness Areas) had the highest survival during their last 6–9 months of freshwater residence. In contrast, parr that reared in young, dry forests (typically, intensively managed timber lands) had the lowest survival. Similarly, parr that reared in areas of low road density had substantially higher survival than those in areas of high road density. We concluded that in the area studied there is a close association between land‐use indices and survival of chinook salmon parr during their last 6–9 months of freshwater residence. This analysis suggests that road‐building and associated land‐use activities in the region may have a detrimental effect on the survival of juvenile chinook salmon and that mitigative changes in these activities could be warranted because Snake River spring–summer chinook salmon are listed as threatened under the Endangered Species Act.

We assessed covariability among a number of spawning populations of spring-summer run chinook salmon (Oncorhynchus tshawytscha) in the Columbia River basin by computing correlations among several different types of spawner and recruit data. We accounted for intraseries correlation explicitly in judging the significance of correlations. To reduce the errors involved in computing effective degrees of freedom, we computed a generic effective degrees of freedom for each data type. In spite of the fact that several of these stocks have declined, covariability among locations using several different combinations of spawner and recruitment data indicated no basinwide covariability. There was, however, significant covariability among index populations within the three main subbasins: the Snake River, the mid-Columbia River, and the John Day River. This covariability was much stronger and more consistent in data types reflecting survival (e.g., the natural logarithm of recruits per spawner) than in data reflecting abundance (e.g., spawning escapement). We also tested a measure of survival that did not require knowing the age structure of spawners, the ratio of spawners in one year to spawners 4 years earlier. It displayed a similar spatial pattern.

We used 11 years of parr-to-smolt survival estimates from 33 Snake River sites to demonstrate that despite a number of confounding factors higher numbers of past habitat remediation or enhancement actions are associated with higher parr-to-smolt survival of endangered wild Snake River springϪsummer (stream-type) Chinook salmon Oncorhynchus tshawytscha. Information-theoretic weights were applied to help distinguish between statistical models based on their relative plausibility. In the models with the highest estimated weights, actions taken to improve fish habitat showed a positive association with increased parr-to-smolt survival. However, because the actions were not sited randomly on the landscape, and because the actions may also have influenced other potentially important covariates, it is difficult to separate habitat action effects from effects due to other important factors.

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Abstract.-Because many stocks of Pacific salmon Oncorhynchus spp. are listed under the U.S. Endangered Species Act (ESA), research has focused on predicting the future population dynamics for these low-abundance stocks. One method used to make predictions is known as population viability analysis. Pacific salmon populations exhibit much higher apparent variability than other ESA-listed vertebrates, and high variability increases the probability of extinction. If the high variability is primarily due to counting methods, it could be reduced in model predictions by using methods that correct for measurement error, sampling error, or both. Using data from British Columbia pink salmon O. gorbuscha and Snake River springor summer-run Chinook salmon O. tshawytscha and several modeling approaches (Ricker, Dennis, and statespace models), we compared repeated counts of the same population (e.g., spawner and fry, dam and redd counts). We applied the methods to the first half of the time series and compared the predictions with the last half of the time series. The results demonstrated that having counts of all life stages of a Pacific salmon population is no guarantee that variability will be markedly reduced. Measurement error is not the primary cause of high variability in empirical estimates of abundance or in predicted future abundance for the stocks analyzed. The very wide bounds on predicted abundance limit the utility of the model predictions for making management decisions. Furthermore, obtaining more accurate or complete measurements of population abundance is unlikely to reduce the wide error bounds in predictions of future abundances.Over the past 15 years many stocks of Pacific salmon Oncorhynchus spp. have been listed as threatened or endangered under the U.S. Endangered Species Act (ESA) (NOAA Fisheries 2005). This has focused researchers' attention on a difficult problem: how best to predict the future course of population dynamics for listed stocks whose abundances are often greatly reduced from historic levels. One method used to make such predictions is known as population viability analysis (PVA). Several PVA methods have been used for modeling listed salmon populations, beginning with spawner-recruit (SR) models familiar to many fisheries biologists (e.g., Marmorek et al. 1998;Paulsen and Hinrichsen 2002). More recently, researchers, drawing on methods used for other ESAlisted vertebrate species (e.g., northern spotted owl Strix occidentalis caurina, loggerhead sea turtle Caretta caretta, snail kite Rostrhamus sociabilis, and Bachman's sparrow Aimophifa aestivulis; Morris et al. 2002), have employed diffusion approximation methods (e.g., Holmes 2004;Holmes and Semmens 2004). These methods have also been applied for long-term projections by management agencies at the evolutionarily significant unit (ESU) and population levels (NOAA 2000). Unlike spawner-recruit models diffusion approximation methods do not require information on the age of returning progeny (recruits) and, therefore, can be employed for...

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Using Snake River spring-summer chinook (Oncorhynchus tshawytscha) as an example, we explore tradeoffs between conservation (restoring population abundance to self-sustaining levels) and learning (reliably estimating how management strategies affect productivity). The population has been studied extensively, especially since 1992, when the evolutionarily significant unit (ESU) was listed under the U.S. Endangered Species Act. Understanding both the conservation and learning dimensions is crucial in evaluating management actions. Using a Bayesian simulation model calibrated with 40+ years of spawner-recruit estimates, we performed population viability analyses to examine the biological risks of an array of management strategies. We also performed power analyses to estimate the precision of estimates of the actions' effects. The results suggest that if one can take actions that increase productivity and manage those actions as experiments, one can simultaneously increase fish numbers and reduce the uncertainty about the effects of those actions. However, because more powerful experiments will utilize controls where no action is taken, an experimental approach may increase risks to the ESU when compared to a strategy that tries to maximize productivity as soon as possible.Résumé : L'exemple de la population de printemps et d'été du saumon quinnat (Oncorhynchus tshawytscha) de la rivière Snake nous a permis d'évaluer les compromis entre la conservation (restauration de la densité de la population à un niveau d'autosuffisance) et l'avancement des connaissances (estimation fiable des effets des stratégies de gestion sur la productivité). Cette population a été étudiée en profondeur, particulièrement depuis 1992, lorsqu'elle a été désignée comme unité évolutive importante (ESU, « evolutionarily significant unit ») dans le cadre de la loi américaine sur les espèces menacées (U.S. Endangered Species Act). La compréhension à la fois des aspects de conservation et ceux d'avancement des connaissances est vitale dans l'évaluation des opérations de gestion. À l'aide d'un modèle de simulation bayésien calibré avec des estimations de la relation reproducteurs-recrues sur une période de plus de 40 ans, nous avons pu procéder à des analyses de viabilité dans le but de déterminer les risques biologiques associés à une gamme de stratégies de gestion. Des analyses de puissance ont servi à déterminer la précision des estimations des effets des diverses stratégies. Nos résultats montrent que si on peut procéder à des opérations qui augmentent la productivité et les gérer comme des expériences, on peut accroître la densité des poissons, tout en réduisant l'incertitude associée aux effets de ces opérations. Cependant, parce que des expériences plus rigoureuses nécessitent l'utilisation de témoins qui ne reçoivent aucun traitement, une approche expérimentale pourrait augmenter les risques courus par l'ESU, par comparaison à une stratégie qui cherche à maximiser la productivité le plus rapidement possible. [Traduit par la Rédaction]Paulsen...