Appendix B. The DNA extraction and amplified fragment length polymorphism (AFLP) protocols.

The DNA extraction and amplified fragment length polymorphism (AFLP) protocols

Appendix E. Female Phyllospadix serrulatus spadix removal experiment.

Female Phyllospadix serrulatus spadix removal experiment

Appendix A. A map of the study area.

A map of the study area

Appendix C. S:O ratio as a function of distance from (1) MB male and (2) the CR male cluster.

S:O ratio as a function of distance from (1) MB male and (2) the CR male cluster

Appendix A. Location of the study areas.

Location of the study areas

Appendix D. Number of Phyllospadix serrulatus and P. scouleri seedlings found recruited to algae and seagrass, years 2006 and 2007 combined; ANOVA table for the percent cover of Phyllospadix spp. found in surveys for seedling recruitment conducted in April and May 2006 and 2007, at four sites; and ANOVA table for the percent cover of articulated coralline algae, Neorhodamela larix and Odonthalia spp., found in surveys for seedling recruitment conducted in April and May 2006 and 2007, at four...

Number of Phyllospadix serrulatus and P. scouleri seedlings found recruited to algae and seagrass, years 2006 and 2007 combined; ANOVA table for the percent cover of Phyllospadix spp. found in surveys for seedling recruitment conducted in April and May 2006 and 2007, at four sites; and ANOVA table for the percent cover of articulated coralline algae, Neorhodamela larix and Odonthalia spp., found in surveys for seedling recruitment conducted in April and May 2006 and 2007, at four sites

Appendix B. Probability mass functions and R code to fit the Poisson, Negative Binomial, Generalized Poisson, and CMP distributions (and their zero-truncated versions).

Probability mass functions and R code to fit the Poisson, Negative Binomial, Generalized Poisson, and CMP distributions (and their zero-truncated versions)

Appendix A. Best fit parameters and model comparison for Case Studies 1, 2, and 3 (Tables A1 –A3); empirical histograms and best fit probability mass functions comparing the Poisson, Generalized Poisson, Negative Binomial, and Conway-Maxwell Poisson distribution fits for Case Studies 1 and 2 (Fig. A1); and point patterns from Jeltsch Fig. 7 used in Case Study 2 (Fig. A2).

Best fit parameters and model comparison for Case Studies 1, 2, and 3 (Tables A1 –A3); empirical histograms and best fit probability mass functions comparing the Poisson, Generalized Poisson, Negative Binomial, and Conway-Maxwell Poisson distribution fits for Case Studies 1 and 2 (Fig. A1); and point patterns from Jeltsch Fig. 7 used in Case Study 2 (Fig. A2)

Steelhead Size Data

This file contains length and weight time series for individual steelhead trout raised in tanks in Santa Cruz California during 2006. Individual fish were measured on a series of days starting in spring 2006 to spring 2007. The fish were derived from two hatcheries (Scott Creek Hatchery and Coleman National Fish Hatchery, denoted as "Scott" and "Coleman" respectively) and raised in set of tanks. The tank number in which each fish grew is noted in the file. The fish were fed two rations levels (high or low) and the ration associated with each time is noted in the column labeled "Ration." The sequence of feeding treatments determine the "Treatment" column which has four levels (1,2,3, or 4). See the publication for more detailed information

DataSheet_1_How much city is too much city? Biodiversity and ecosystem functioning along an urban gradient at the interface of land and sea.docx

A huge proportion of the world’s population resides in urban areas along the coast. As cities expand, the ability of coastal ecosystems to provide the benefits people derive from nature, ranging from food from fisheries to coastal defense to maritime transportation and beyond, is in question. While it is well understood that coastal development changes ecosystems, quantitative insights about how terrestrial urbanization fundamentally alters ecosystem structure and function in adjacent freshwater and downstream coastal marine habitats remain rare, though a general expectation is that impacts of terrestrial urbanization will attenuate from land to freshwater to coastal marine habitats. Empirical assessments of these phenomena are especially important for species that rely on freshwater and coastal marine habitats at multiple points in their life cycles, including endangered and threatened Pacific salmon (Oncorhynchus spp.). We investigated associations between landscape-scale urbanization and ecosystem structure (biodiversity of epibenthic invertebrate taxa) and function (benthic net primary productivity and decomposition) in freshwater and coastal marine habitats across six pairs of more and less urbanized, coastal watersheds in Puget Sound, WA, USA, using principal components analysis, analysis of covariance, and Mantel tests. Greater upland urbanization was associated with greater reductions in freshwater biodiversity, measured as the density and evenness of epibenthic invertebrate families. In contrast and surprisingly, however, coastal marine biodiversity (measured as the density and evenness of epibenthic invertebrate families) tended to be higher at more urbanized sites, suggesting the potential role of low to moderate levels of urbanization-related disturbance in determining coastal marine biodiversity patterns. We found no statistical association between urbanization and freshwater and coastal marine ecosystem functions, estimated from changes in accumulated algal biomass on tiles (benthic net primary productivity) and loss of biomass from litter bags (decomposition). In addition, there was no evidence that changes in ecosystem structure and function with urbanization were more severe in freshwater than coastal marine habitats, as might be expected if the land-sea boundary diminished effects of landscape-scale urbanization. Our results suggest that the effects of urbanization can be complex and that attention to terrestrial, freshwater, and coastal marine systems in concert will produce more effective, ecosystem-based management.</p