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Abstract: Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to each pixel in a digital landscape map. The gradient nearest neighbor method integrates vegetation measurements from regional grids of field plots, mapped environmental data, and Landsat Thematic Mapper (TM) imagery. In the Oregon coastal province, species gradients were most strongly associated with regional climate and geographic location, whereas variation in forest structure was best explained by Landsat TM variables. At the regional level, mapped predictions represented the range of variability in the sample data, and predicted area by vegetation type closely matched sample-based estimates. At the site level, mapped predictions maintained the covariance structure among multiple response variables. Prediction accuracy for tree species occurrence and several measures of vegetation structure and composition was good to moderate. Vegetation maps produced with the gradient nearest neighbor method are appropriately used for regional-level planning, policy analysis, and research, not to guide local management decisions. Résumé: Afin d’effectuer l’analyse des politiques touchant les ressources naturelles et appuyer la recherche écologique, il est nécessaire d’obtenir une information spatiale précise sur la structure de la végétation forestière et sur la composition des espèces et ce, à une vaste échelle spatiale. Nous présentons une méthode de cartographie prévisionnelle

Canonical correspondence analysis (CCA) is introduced as a multivariate extension of weighted averaging ordination, which is a simple method for arranging species along environmental variables. CCA constructs those linear combinations of environmental variables, along which the distributions of the species are max-imally separated. The eigenvalues produced by CCA measure this separation. As its name suggests, CCA is also a correspondence analysis technique, but one in which the ordination axes are constrained to be linear combinations of environmental variables. The ordination diagram generated by CCA visualizes not only a pattern of community variation (as in standard ordination) but also the main features of the distributions of species along the environmental variables. Applications demonstrate that CCA can be used both for detecting species-environment relations, and for investigating specific questions about the response of species to environmental variables. Questions in community ecology that have typically been studied by 'indirect ' gradient analysis (i.e. ordination followed by external interpretation of the axes) can now be answered more directly by CCA.

canopies: preliminary effects on understory vegetation

A nonparametric method and a Bayesian hierarchical modelling method are proposed in this paper for the detection of environmental thresholds. The nonparametric method is based on the reduction of deviance, while the Bayesian method is based on the change in the response variable distribution parameters.

Emphasis upon publication as a means of “diffusing knowledge ” was expressed by the fi rst Secretary of the Smithsonian. In his formal plan for the Institution, Joseph Henry outlined a program that included the following statement: “It is proposed to publish a series of reports, giving an account of the new discoveries in science, and of the changes made from year to year in all branches of knowledge. ” This theme of basic research has been adhered to through the years by thousands of titles issued in series publications under the Smithsonian imprint, commencing with Smithsonian Contributions to Knowledge in 1848 and continuing with the following active series:

This series of working papers is intended to provide information and to generate fruitful discussion on key issues in the sustainable and equitable use of plant resources. Please send comments on this paper and suggestions for future issues to

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Contents 23 Silvicultural Treatment 24 Underplanting 24 Top Rot Inoculation 25 Sampling Methods 25 Vegetation 29 Den Use 29 Fungi and Soil Food Webs 31 Coarse Woody Debris, Snags, and Potential Dens 32 Forest Floor and Arboreal Mammals 33 Predators and Birds 34 Baseline Conditions 35 Prethinning and Control Stand Conditions 43 Prethinning Coarse Woody Debris 43 Standing Dead Trees 43 Arboreal Rodents 43 Forest-Floor Small Mammals 46 Postthinning Conditions 46 Silvicultural Conditions 52 Postthinning Understory Vegetation 53 Postthinning Coarse Woody Debris 54 Den Site Availability and Snags 54 Supplemental Den Use 55 Fungi 57 Discussion 57 Retrospective Aspects 61 Prospective and Experimental Aspects 65 Variable-Density Thinning 66 Operational Aspects of Variable-Density Thinning 67 Summary 69 Acknowledgments 69 Metric and English Conversions 70 References 80 Appendix 1: Forest Ecosystem Study Species List 103 Appendix 2: Nestbox and Cavity Design 104 Appendix 3: Permanen...