From: Tim Trohimovich To: zSMP; Ballard, Greg Cc: Amy Waterman; Janet; Rein Attemann Subject: RE: Comments on Clallam Co SMP Update (External Email: USE Caution) Date: Monday, December 11, 2017 4:23:32 PM Attachments: Estuarine Author Info Pack.pdf 1-s2.0-S0272771416301007-main.pdf Millions projected to be at risk from sea-level rise in the conteinental United States.pdf Nature Climate Chance Instructions to Authors.pdf image001.png image003.png

Dear Sirs and Madams:

Here is the first set of enclosures.

Tim Trohimovich, AICP Director of Planning & Law

816 Second Avenue, Suite 200 Seattle, WA 98104-1530 connect: futurewise.org

From: Tim Trohimovich Sent: Monday, December 11, 2017 4:22 PM To: '[email protected]' < >; ' Cc: Amy Waterman < org>; 'Janet' >; 'Rein Attemann'

Subject: Comments on Clallam Co SMP Update

Dear Sirs and Madams:

Enclosed please find comments by Futurewise, the Sierra Club North Olympic Group, and the Washington Environmental Council on the Planning Commission Recommendation – September 2017 Draft - Clallam County Shoreline Master Program for the December 12th public hearing. In two separate emails we are emailing the documents identified as enclosures in the letter.

Thank you for considering our comments.

Tim Trohimovich, AICP Director of Planning & Law

816 Second Avenue, Suite 200 Seattle, WA 98104-1530 connect: futurewise.org

Estuarine, Coastal and Shelf Science 175 (2016) 106 117

Contents lists available at ScienceDirect

Estuarine, Coastal and Shelf Science

journal homepage: www.elsevier.com/locate/ecss

Multiscale impacts of armoring on Salish Sea shorelines: Evidence for cumulative and threshold effects

* Megan N. Dethier a, , Wendel W. Raymond a, Aundrea N. McBride b, Jason D. Toft c, Jeffery R. Cordell c, Andrea S. Ogston d, Sarah M. Heerhartz c, Helen D. Berry e a Friday Harbor Laboratories, University of Washington, Friday Harbor, WA 98250, USA b Skagit River System Cooperative, LaConner, WA 98257, USA c School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA d School of Oceanography, University of Washington, Seattle, WA 98195, USA e Washington State Department of Natural Resources, Olympia, WA 98504, USA article info abstract

Article history: Shoreline armoring is widespread in many parts of the protected inland waters of the Pacific Northwest, Received 23 June 2015 U.S.A, but impacts on physical and biological features of local nearshore ecosystems have only recently Received in revised form begun to be documented. Armoring marine shorelines can alter natural processes at multiple spatial and 29 March 2016 temporal scales; some, such as starving the beach of sediments by blocking input from upland bluffs may Accepted 30 March 2016 take decades to become visible, while others such as placement loss of armoring construction are im Available online 1 April 2016 mediate. We quantified a range of geomorphic and biological parameters at paired, nearby armored and unarmored beaches throughout the inland waters of Washington State to test what conditions and Keywords: Armoring parameters are associated with armoring. We gathered identical datasets at a total of 65 pairs of beaches: Gravel 6 in South Puget Sound, 23 in Central Puget Sound, and 36 pairs North of Puget Sound proper. At this Threshold broad scale, demonstrating differences attributable to armoring is challenging given the high natural Grain size variability in measured parameters among beaches and regions. However, we found that armoring was Detritus consistently associated with reductions in beach width, riparian vegetation, numbers of accumulated Long-term changes logs, and amounts and types of beach wrack and associated invertebrates. Armoring related patterns at lower beach elevations (further vertically from armoring) were progressively harder to detect. For some parameters, such as accumulated logs, there was a distinct threshold in armoring elevation that was associated with increased impacts. This large dataset for the first time allowed us to identify cumulative impacts that appear when increasing proportions of shorelines are armored. At large spatial and tem poral scales, armoring much of a sediment drift cell may result in reduction of the finer grain size fractions on beaches, including those used by spawning forage fish. Overall we have shown that local impacts of shoreline armoring can scale up to have cumulative and threshold effects these should be considered when managing impacts to public resources along the coast. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction British Columbia (Canada) and of Washington State (USA), has shorelines that range from virtually pristine beaches to concrete Anthropogenic alteration of shorelines is a worldwide phe covered commercial ports. In the face of increasing coastal urban nomenon as a significant proportion of population growth is in growth and sea level rise, effective management of our shorelines coastal communities. Types of shoreline development are diverse, requires understanding both functions of natural beaches and the ranging from simply building houses overlooking the water to scales at which we are impacting them (Arkema et al., 2013; Harris completely altering the shore by covering it with fill or structures. et al., 2015). The Salish Sea, which includes all the inland marine waters of One of the most prevalent forms of coastal development in the Salish Sea and worldwide is shoreline armoring, comprising various artificial means of stabilizing banks and bluffs that might * Corresponding author. 620 University Road, Friday Harbor, WA 98250, USA. otherwise erode and endanger infrastructure. A recent conservative E-mail address: [email protected] (M.N. Dethier). http://dx.doi.org/10.1016/j.ecss.2016.03.033 0272-7714/© 2016 Elsevier Ltd. All rights reserved. M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117 107 estimate of armored shoreline in the continental US is 14% (Gittman likely with many geomorphic processes. In Europe, extensive et al., 2015). Local, mostly biological, effects of shoreline armoring coastal armoring is thought to have contributed to broad scale are well known for some types of embayments and marshes (e.g., steepening of the shoreline (Taylor et al., 2004), but many other Bozek and Burdick, 2005; Chapman and Underwood, 2011) and processes could be important. open coast sandy beaches (e.g., Dugan et al., 2008; review by In the southern part of the Salish Sea (in Washington State), Nordstrom, 2014), and recently for the gravel sand beaches of which includes Puget Sound, extensive shoreline armoring has Puget Sound (Sobocinski et al., 2010; Heerhartz et al., 2014). accompanied the last 100 years of development along the greater Armoring locally reduces retention of logs and wrack (algae, sea Everett Seattle Tacoma urban corridor, and is thought to signifi grass, leaf litter, and other organic and inorganic debris left by cantly impair nearshore ecosystem processes (Simenstad et al., ebbing tides) and the invertebrate communities that inhabit this 2011). While local effects have recently been documented (e.g., detritus. It can also have indirect effects on seabird and shorebird Sobocinski et al., 2010; Heerhartz et al., 2014), broader or cumu use (Dugan et al., 2008) as well as abundance and diversity of large lative impacts have not. This uncertainty stymies managers and mobile invertebrates (Chapman, 2003). Potential spawning loca regulators who lack compelling data that would provide the “best tions for beach spawning forage fish, such as surf smelt (Hypomesus available science” to inform guidelines. Pressures to relax armoring pretiosus), are reduced when armoring covers the high shore, and regulations stem from the need to protect valuable infrastructure egg mortality increases when beach temperatures are raised by from erosion, especially with risk exacerbated by sea level rise. shoreline modifications (Rice, 2006). These trophically important Sociological studies show that decisions by a few homeowners to fish may also be negatively impacted in cases where armoring armor their shoreline often triggers neighbors to do the same, coarsens the sediment due to local winnowing of finer grain sizes leading to cascading local impacts (Scyphers et al., 2015). In addi (Penttila, 2007; Quinn et al., 2012; Fox et al., 2015; Greene et al., tion to such possible cumulative effects, regulators are particularly 2015). By changing the nearshore habitats encountered by juve interested in which types or locations of armoring have greater nile migrating salmon, armoring affects their diets (Munsch et al., impacts than others, and whether there are thresholds that trigger 2015) and possibly residence time (Heerhartz and Toft, 2015). these impacts. Samhouri et al. (2010) define an ecological threshold Considerable study of physical impacts of armoring on beaches as a point at which small changes in environmental conditions has been conducted, although the results are contradictory. In some produce large (non linear) responses in ecosystem state. For circumstances, interactions of sediment impoundment, wave example, ecological thresholds have been associated with habitat reflection, and alterations to nearshore water currents may alter fragmentation (e.g., Andren, 1994) and edge effects (Toms and beach scour, mobilization of sediment, and recovery from storms. Lesperance, 2003). One possible threshold that may apply to In theory, these processes may result in narrower, steeper, and shoreline armoring is the extent that structures encroach on the coarser grained beaches (Pilkey and Wright, 1988; Bozek and beach. In addition, slow and delayed “latent impacts” (Coverdale Burdick, 2005; Nordstrom, 2014). One clear effect is that passive et al., 2013) may exist but are very difficult to detect, especially erosion (e.g., caused by relative sea level rise) causes narrowing of given signal to noise problems. armored shorelines because the upper beach is prevented from Previous studies by our research team have focused on local migrating inland. In contrast, whether active erosion is induced by impacts of shoreline armoring in central and southern Puget Sound seawalls is still argued (reviews by Kraus and McDougal, 1996; (Heerhartz et al., 2014, 2015). We dealt with among site ‘noise’ by Ruggiero, 2010); few long term studies have been attempted but use of a paired sampling design, focusing our surveys on nearby, generally do not show a definitive armoring effect (e.g., Griggs et al., physically paired, armored and unarmored beaches. Here we 1994; Griggs, 2010). Modeling work (e.g., Ruggiero, 2010) suggests broaden our geographic scale to test whether the documented that contradictions seen in the literature may stem from variation biological effects of armoring exist on beaches in the Salish Sea among study systems in key physical parameters, in particular the north of Puget Sound. We also test whether any physical impacts relative elevation of the seawall and the morphology of the beach are detectable, because our previous work in central and southern and nearshore, including their slopes. Puget Sound found few differences in quantified physical parame Even for the more consistent biological impacts of armoring, ters that were correlated with armoring. The northern region has translating local effects to a landscape scale is challenging because more bedrock shorelines and different oceanographic characteris of the myriad other natural and anthropogenic factors that affect tics, so we anticipated that there would be some regional differ shoreline processes. The signal to noise problem is particularly ences in beach parameters. Based on our own localized studies and large in inland waters such as the Salish Sea because of the com on literature from other systems (e.g., open coast beaches), we plexities of underlying geology, shoreline shape, freshwater input, hypothesized that: 1) Armoring associated reduction of logs, wave fetch, orientation to prevailing winds, nearshore bathymetry, wrack, and invertebrates would be consistent across regions in and sources of sediments, vegetation, and organisms. In most of the paired beach analyses; 2) These associations would be increasingly world, beach sediments derive predominantly from rivers. On clear when armoring is lower on the beach face; 3) By examining a sandy shorelines, these sediments are jealously retained with large range of sites, the predicted pattern of armoring altering groins, and millions of dollars are spent annually to replenish beach slope and sediment coarseness might be detectable; and 4) beaches where natural sources have been locked up by dams (Berry Such geomorphic signals would be most distinct where extensive et al., 2013). Although numerous rivers empty into the Salish Sea stretches of armoring have “locked up” more sediment sources in and a few of them create large deltas, much of the riverine sedi an area. To address these questions, we discuss regional patterns ment is deposited in deep fjord like basins rather than building but ignore the huge beach to beach variation in geomorphic con beaches. Instead, most beach building sediment comes from ditions, to be discussed elsewhere (A.N. McBride, pers. comm.). erosion of bluffs (Keuler, 1988). It follows that “locking up” these sediments by armoring shorelines should have large scale and 2. Methods long term impacts, including cumulative effects if few sediment sources are left unaltered (reviewed by Berry et al., 2013; 2.1. Sites Nordstrom, 2014). However, demonstrating cumulative effects, e.g. changes that continue to worsen with additional armoring, is Our analyses include data from 65 pairs of armored and unar notoriously difficult especially if changes appear gradually, as is mored beaches in the inside marine waters of Washington State, 108 M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117 from the southern extent of Puget Sound to the Canadian border 2.3. Geomorphic survey methods (Fig. 1). The data thus encompass three oceanographic regions: South (6 site pairs), landward of a sill at the Tacoma Narrows; We characterized sediment grain sizes from the wrackline from Central (23 site pairs), inside Puget Sound proper, south of a sill at three to five of the core samples by sieving dried sediments smaller Admiralty Inlet; and North (36 site pairs), outside of the Sound but than 16 mm through progressively finer sieves (1/2 phi intervals) within the Salish Sea. The south sites and to a lesser extent the using a RoTap shaker, and weighing the amount retained in each central ones are influenced by constrained water exchange caused sieve. Coarser sediments (cobbles) were individually measured. by the sills, and by freshwater input from several rivers. The north Elevations of wracklines were measured; because these differed sites have greater oceanic flushing but have substantial seasonal within and among pairs, sediments were not all collected from the freshwater input from several large rivers, especially the Fraser in same elevation on the beach. In addition, we assessed grain sizes, Canada and the Skagit in Washington. The primary sediment with lower precision, along a transect at Mean Low Water (MLW: composition on our study beaches was a mix of sand and gravel ca. þ1 m above MLLW). At three randomly selected points we used predominantly derived from glacial and interglacial deposits, a50 50 cm quadrat to estimate percent cover of cobbles (>6 cm), delivered to beaches via episodic bluff erosion, and distributed by pebbles (4 mm e 6 cm), granules (2e4 mm), sand (<2 mm), and longshore transport (Shipman, 2010). Wave energy regime and mud (smooth) at the surface and at 5 cm subsurface. The two sets of local geology are then the primary drivers of beach sediment estimates were averaged for per quadrat proportions. character and gradient in the Salish Sea. Pairs of beaches were Beach profiles were obtained on low tides using a laser level and within the same drift cell (independent zone of littoral sediment stadia rod or RTK GPS, measuring from the top of the berm or toe of transport from source to deposition area) and same component of the eroding bluff (on unarmored beaches) to elevations approach that drift cell (erosional or depositional). The 65 pairs were within ing mean lower low water (MLLW), depending on the tide. On 49 different drift cells (out of over 600 in the Washington state armored beaches the profiles were measured from the lowest portion of the Salish Sea). These 49 cells ranged from 1.8 to 60.4 km elevation on the armoring structure to MLLW. Beach slope was long, and varied from 0 to 99% armored. calculated for the upper portion of each beach from the wrack line Sites had armoring at different elevations and of different types to ~0.6 vertical meters above local MLW. This section was consis (e.g., concrete seawalls, stone riprap, retaining walls of wood pil tently in the active sediment transport zone of the foreshore (an ings). Paired beaches were matched as closely as possible in terms area of similar energy) of our beach transects. See Supplementary of geomorphic setting and geology of the bluff, aspect to prevailing Material for additional methods and data sources. winds and sun, wave exposure, and nearshore bathymetry. Bea Due to the fjord like shape and complex bathymetry of the ches in a pair were always nearby; mean distance between Salish Sea, the magnitude of the vertical tidal range varied greatly members of a pair was 383 m, maximum distance was 1 km. All from our northern to southern sites. Mean tidal range varied from field data reported here were collected in summer (June to Aug.); 1.39 to 3.19 m, and the elevation of the mean higher high water central and south sites were surveyed in 2010e2012, north sites in (MHHW) datum varied from 2.39 (in the north) to 4.32 m (far inside 2012e2013. Puget Sound) above MLLW. To standardize our elevation mea surements in relation to tidal range and enable us to meaningfully assess impacts of armoring emplaced at various elevations, we 2.2. Biological surveys calculated a “relative encroachment” (RE) metric by subtracting the elevation of armoring or toe of bluff from the MHHW datum for Data collection followed procedures described in Heerhartz each beach. Datum information for nearby sites was obtained from: et al. (2014).Briefly, at all sites we placed a 50 m shore parallel http://tidesandcurrents.noaa.gov/; in some cases it was necessary transect high on the shore near the wrack zone; this line was to interpolate between distant stations. Positive RE values indicated used for both biological and sediment sampling. We define beach that the toe (of armoring or bluff) was lower than MHHW, and wrack as organic matter consisting of detached and stranded negative values were higher. RE at our study sites are reported in algae, seagrass, and terrestrial debris. We surveyed the most vertical feet, and ranged from 5.1 ft ( 1.55 m) to þ7.0 ft recent line of beach wrack and avoided older and usually more ( 2.14 m), with a mean of 0.33 ft ± 0.16 SEM (standard error of the desiccated wrack. Armored beaches lacking wrack and logs were mean) ( 0.10 m ± 0.05 SEM). surveyed at the highest elevation where natural beach sediments We tested whether the proportion of the drift cell that was were present (i.e., at the toe of armoring). At 10 randomly selected armored (hereafter referred to as DCA: data from various sources) points we estimated the percent cover of each type of wrack (i.e., would generate cumulative armoring impacts, for example by seagrass, algae, or terrestrial source), and noted the most abun blocking increasing proportions of sediment sources. Variables that dant types of algae. At 5 of these points we collected samples of could be affected by large scale and long term impacts of armoring wrack and the top 2.5 cm of sediment using a 15 cm diameter might show these effects, including some parameters where local benthic corer, and quantified the number of logs (less or greater and short term impacts were not seen. Of particular interest was than 2 m length). We also measured the width of the log line testing our hypotheses of a correlation between sediment grain size perpendicular to shore. In the lab, wrack samples were sorted into or beach slope and DCA. types, dried, and weighed. All invertebrates were extracted (using 106 mm sieves) from the wrack, and identified and counted using a 2.4. Statistical analyses dissecting microscope; talitrid “beach hopper” amphipods and other crustaceans were identified to genus, and other in We assessed local impacts of armoring using paired t tests, vertebrates to family (except oligochaetes, which were not iden taking advantage of our sampling design to compare the differ tified beyond class). Invertebrate dense samples were split with a ences between mean values of each measured response parameter Folsom Plankton Splitter and abundances were back calculated. at each pair of beaches. Parameters tested are listed in Table 1. For analyses, all parameters were averaged (percent covers) or We tested larger scale effects of RE and DCA on response vari summed (biomasses, invertebrate counts) across the transect ables of interest using a mixed effects model. For all analyses “Site” (n 5 for wrack core and log samples, n 10 for wrack percent was defined as a random effect and RE or DCA as a fixed effect. Each covers). “Site” had two sampled beaches, the armored beach and its M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117 109

Fig. 1. Map of the Washington State portion of the Salish Sea, showing study site locations and major cities. Each pair of beaches (armored and unarmored) is represented by a dot. North sites are represented by letters, Central by #1 25, and South by #26 31. Basemap data courtesy of Washington Dept. of Ecology (WA State Basemap, Place Names) http:// www.ecy.wa.gov/services/gis/data.htm and Washington State Dept. of Transportation (Shoreline) http://www.wsdot.wa.gov/mapsdata/geodatacatalog/. 110 M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117

Table 1 Summary of statistical tests.

Paired t-tests RE DCA

Description p value Direction p value Direction Test type p value Direction Test type

Beach Width 0.0104 U > A Beach Slope ns 0.0453 neg C 0.0028 pos C Shade on upper shore <0.0001 U > A Number of logs <0.0001 U > A Width of log line <0.0001 U > A Wrack Terrestrial Percent Cover <0.0001 U > A <0.0001 neg B ns B Wrack Algae Percent Cover 0.0012 U > A 0.0002 neg B ns B Wrack Total Percent Cover <0.0001 U > A <0.0001 neg B ns B Wrack Total Mass <0.0001 U > A <0.0001 neg A 0.0074 neg A Wrack Algae Mass 0.00773 U > A <0.0001 neg A 0.0247 neg A Wrack Terrestrial Mass 0.00013 U > A <0.0001 neg A ns A Wrack Total Invertebrates ns 0.0001 neg A 0.0051 neg A Wrack Total Amphipods ns 0.003 neg A ns A Wrack Total Insects ns <0.0001 neg A ns A Wrack Total Collembola 0.00759 U > A 0.0001 neg A 0.0293 neg A Wrack Oligochaeta þ Nematoda ns Wrack Megalorchestia 0.0002 U > A Very Coarse Gravel ns ns B 0.0001 pos B Coarse Gravel ns ns B ns B Medium Gravel ns ns B ns B Fine Gravel ns ns B ns B Very Fine Gravel ns ns B ns B Very Coarse Sand ns ns B ns B Coarse Sand ns ns B ns B Medium Sand ns ns B 0.0042 neg B Fine Sand ns ns B 0.0008 neg B Fines ns ns B ns B

Notes: Type of test: A Mixed-effect ANOVA on quasi-Poisson data; B Mixed-effects on arcsin sqrt transformed data; C normal linear mixed effect model. ‘ns’ non- significant. ‘neg’ and ‘pos’ refer to the direction of effect of the parameter on the response variable, e.g. large RE is associated with low wrack cover. unarmored pair. In this setting the model is allowed to vary the 2010). Our analyses used an approach based on Crawley (2007) (see intercept for each “Site,” therefore accounting for both within site Supplementary Material). All univariate analyses were run in R (R and among site variation, i.e. acknowledging that sites are repre Development Core Team, 2014). sentative of Salish Sea beaches and were randomly selected. For We used permutational multivariate analysis of variance models testing counts of wrack invertebrates (either summed, or (PRIMER v6 with PERMANOVAþ; Clarke and Gorley, 2006; separately for particular taxa) or components of wrack mass we Anderson et al., 2008) to test for differences in sediment grain used a generalized mixed effects model with a quasi Poisson dis sizes between armored and unarmored beaches (type as fixed tribution using the glmmPQL function in the MASS package in R factor) with sites as replicates (pair as random factor). Multivariate (Venables and Ripley, 2002; R Development Core Team, 2014). A relationships between environmental predictor variables and quasi Poisson distribution was chosen over a Poisson distribution wrack sample invertebrate assemblages were investigated using to account for overdispersion and to adequately fit biological count distance based linear modeling (DISTLM) conducted using the data. For all model fits, residual plots and fitted values were step wise selection procedure to minimize the Akaike information examined, and all appeared reasonable considering the inherent criterion (AIC). These analyses partition the multivariate variability variability of the dataset. For models testing the effect of RE or DCA of the invertebrate assemblages along best fit axes and then test on percent cover or proportion data (including wrack cover and the environmental variables that are most closely related to these sediment grain sizes) we used a normal linear mixed effects model axes. with “Site” as the random effect on arcsine square root trans formation of the response variable, as is common with such data to 3. Results improve normality. The mixed effects models testing the effect of fi DCA all showed high correlation between the xed effect and the 3.1. Regional differences random effect of Site (Supplemental Table 1). This was expected since each member of a Site existed in the same drift cell by design. Although we were interested in testing for armoring effects on fi Because of the dif culty of deciding what constitutes an indepen beach parameters that might exist despite regional variation, the dent test, and lack of agreement in the literature on adjusting alpha physical backdrop for testing such local impacts includes regional levels for multiple testing (e.g., Hurlbert and Lombardi, 2003, 2012), differences in bluff geology and shoreline geomorphology. There we present p values as reported by individual tests, and interpret are fundamental geologic differences among regions that result in our results conservatively. variation in bluff material (Fig. 2). The north region experienced Some regression analyses showed non linear changes in the advance and retreat of glaciers so that surface morphology reflects response variable, suggesting a threshold or breakpoint. For these the zone of ice grinding on bedrock; the exposed sediment in the we applied segmented (piecewise) regression to search for statis central region transitions to a glacial outwash zone; and the sedi fi tically signi cant two segment relationships; these can be com ment deposits in the south are dominated by outwash that was at mon in ecological systems and are characterized by an abrupt the front edge of the ice. These influences are also seen in sediment “ ” change in a response variable at some point ( threshold )inan grain sizes at the wrackline of the study beaches (Fig. 2). Grain size independent variable (Toms and Lesperance, 2003; Samhouri et al., distributions were quite consistent between armored and

116 M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117 has been removed and there is physical space on the upper shore some even graciously. We gratefully acknowledge field and lab for it to accumulate; colonization by arthropods and other de assistance from UW SAFS: M. Ramirez, E. Morgan, C. Levy; Ocean composers is likely to follow quickly if there are local sources of ography: N. Twomey, A. Fricke, E. Ewings, R. Hale, K. Boldt, K. L. colonists. Terrestrial birds will probably visit restored spaces Webster; Friday Harbor Labs: T. Stephens, M. Eisenlord, M. Krauszer, quickly, once invertebrate food becomes available, and rapid juve A. Thomson, L. Watson; Skagit River System Coop: E. Beamer, B. nile salmonid use of a restored beach has already been demon Brown, K. Wolf, J. Demma, R. Haase; Tulalip Tribes: T. Zackey; Swi strated at a site in Puget Sound (Toft et al., 2013). If sediments are nomish Tribe: J. Barber, C. Greiner, S. Grossman; DNR: J. Gaeckle, and appropriate for spawning forage fish, or if armoring removal is extensive logistical support and matching funds; Hugh Shipman accompanied by beach nourishment with appropriate sediment, and other members of the Shoreline Armoring Workgroup; Casey then egg laying may occur during the next spawning season; but Rice; personnel from Snohomish County and the Northwest Straits even spawning on appropriate sediment is unpredictable in space Foundation. This research was funded in part by a grant from the and time (e.g., surf smelt: Penttila, 2007). These biotic changes may Washington Sea Grant program, University of Washington, pur happen on relatively short temporal scales, for example seasonally, suant to National Oceanic and Atmospheric Administration Award rather than taking years over which some armoring impacts may No. R/ES 57. The views expressed herein are those of the authors develop. Recovery of geomorphic parameters such as beach shape and do not necessarily reflect the view of NOAA or any of its sub and pre armoring sediment grain sizes will depend on sediment agencies. Additional support was generously provided by the sources, whether from updrift, upslope, or artificial delivery. Washington Dept. of Fish and Wildlife Agreement #12 1249 as Multiscale spatial and temporal impacts of armoring are also grant administrator for the U.S. Environmental Protection Agency. likely to be seen on open coast sandy beaches or other systems The manuscript was substantially improved following input from such as armored estuarine marshes. On sandy beaches, the effects anonymous reviewers and Editors Valiela and Cahoon. of armoring on wrack accumulation and on other trophic levels have been well studied (e.g., Dugan et al., 2008). A relatively unique Appendix A. Supplementary data feature of Pacific Northwest beaches is extensive windrows of beach logs, but these may have some parallel in marsh vegetation Supplementary data related to this article can be found at http:// that can only develop when armoring is absent or very high on the dx.doi.org/10.1016/j.ecss.2016.03.033. shoreline (Bozek and Burdick, 2005). As in the Salish Sea, on both sandy beaches and marshes the direction of drift (e.g., longshore References currents, estuarine outflow) should affect the location and spatial scale of armoring impacts because the accumulation of both sedi Anderson, M.J., Gorley, R.N., Clarke, K.R., 2008. PERMANOVAþ for PRIMER: Guide to ments and organic matter are important in those ecosystems. Software and Statistical Methods. PRIMER-E, Plymouth, UK.  Geomorphic effects of armoring on open beaches or marshes are Andren, H., 1994. Effects of habitat fragmentation on birds and mammals in land- scapes with different proportions of suitable habitat a review. Oikos 71, similarly likely to be slow or highly episodic, depending on types of 355 366. sediment sources and their proximity, as well as variations in wave Arkema, K.K., Guannel, G., Verutes, G., Wood, S.A., Guerry, A., Ruckelshaus, M., energy. The degree to which sediment sources are locked up, either Kareiva, P., Lacayo, M., Silver, J.M., 2013. Coastal habitats shield people and property from sea-level rise and storms. Nat. Clim. Change 3, 913 918. by extensive alongshore armoring or by dams on riverine sources, Berry, A., Fahey, S., Meyers, N., 2013. Changing of the guard: adaptation options that may have cumulative effects; investigating possible thresholds in maintain ecologically resilient sandy beach ecosystems. J. Coast. Res. 29, the interactions between sediment budgets and marsh health or 899 908. Berry, A.J., Fahey, S., Meyers, N., 2014. Boulderdash and beachwalls the erosion of beach geomorphology would be useful but temporally challenging. sandy beach ecosystem resilience. Ocean. Coast. Manage 96, 104 111. In conclusion, our broad study covering a wide range of beaches Bozek, C.M., Burdick, D.M., 2005. Impacts of seawalls on saltmarsh plant commu- and drift cells with different types, elevations, and degrees of nities in the Great Bay Estuary, New Hampshire USA. Wetl. Ecol. Manage 13, armoring has allowed us to quantify hitherto elusive patterns of 553 568. Chapman, M.G., 2003. Paucity of mobile species on constructed seawalls: effects of impacts of armoring on beach processes. Armoring alters beach urbanization on biodiversity. Mar. Ecol. Prog. Ser. 264, 21 29. conditions from the local to the sound wide scale, with its effects Chapman, M.G., Underwood, A.J., 2011. Evaluation of ecological engineering of “ ” likely emerging on time scales that range from immediate to years armoured shorelines to improve their value as habitat. J. Exp. Mar. Biol. Ecol. 400, 302 313. or decades. In the Salish Sea, there is great variation among beaches Clarke, K.R., Gorley, R.N., 2006. PRIMER V6: User Manual/Tutorial. PRIMER-E, and regions in upper shore parameters such as logs, wrack, and Plymouth. invertebrates, but in many cases an armoring signal overrides these Coverdale, T.C., Herrmann, N.C., Altieri, A.H., Bertness, M.D., 2013. Latent impacts: the role of historical human activity in coastal habitat loss. Front. Ecol. Environ. complex processes, and broad associations are visible. The changes 11, 69 74. in the geomorphic character of beaches towards steeper and Crawley, M., 2007. The R Book, first ed. John Wiley & Sons Inc., West Sussex, coarser conditions appear to be slow and subtle, but ultimately can England. fi Duffy, E.J., Beauchamp, D.A., Sweeting, R.M., Beamish, R.J., Brennan, J.S., 2010. ramify to impact beach functions, including supporting forage sh Ontogenetic diet shifts of juvenile Chinook salmon in nearshore and offshore use and altering the infauna. The elevation of armoring on the shore habitats of Puget Sound. Trans. Amer. Fish. Soc. 139, 803 823. clearly does make a difference to numerous functional character Dugan, J.E., Hubbard, D.M., McCrary, M.D., Pierson, M.O., 2003. The response of macrofauna communities and shorebirds to macrophyte wrack subsidies on istics, and at least in the case of log accumulation, there is a exposed sandy beaches of southern California. Estuar. Coast. Shelf Sci. 58, threshold for this effect. Our data also suggest that adding more 25 40. armoring within drift cells may lead to cumulative impacts on Dugan, J.E., Hubbard, D.M., Rodil, I.F., Revell, D.L., Schroeter, S., 2008. Ecological several geomorphic and biological parameters. The mechanisms effects of coastal armoring on sandy beaches. Mar. Ecol. An Evol. Perspect. 29, 160 170. that might cause these cumulative effects, for example starving the Dugan, J.E., Hubbard, D.M., Quigley, B.J., 2013. Beyond beach width: steps toward beaches of sediment supply or altering local hydrodynamics, identifying and integrating ecological envelopes with geomorphic features and require further investigation. datums for sandy beach ecosystems. Geomorphology 199, 95 105. Fox, C.H., Pacquet, P.C., Reimchen, T.E., 2015. Novel species interactions: american black bears respond to Pacific herring spawn. BMC Ecol. 15 http://dx.doi.org/ Acknowledgements 10.1186/s12898-015-0045-9. Gittman, R.K., Fodrie, F.J., Popowich, A.M., Keller, D.A., Bruno, J.F., Currin, C.A., Peterson, C.H., Piehler, M.F., 2015. Engineering away our natural defenses: an This type of broad study takes a village. We thank many prop analysis of shoreline hardening in the US. Front. Ecol. Environ. 13, 301 307. erty owners in the Salish Sea who allowed access to their beaches, Greene, C., Kuehne, L., Rice, C., Fresh, K., Penttila, D., 2015. Forty years of change in M.N. Dethier et al. / Estuarine, Coastal and Shelf Science 175 (2016) 106 117 117

forage fish and jellyfish abundance across greater Puget Sound, Washington R Development Core Team, 2014. R: a Language and Environment for Statistical (USA): anthropogenic and climate associations. Mar. Ecol. Prog. Ser. 525, Computing. R Foundation for Statistical Computing, Vienna. www.R-project. 153 170. org/. Griggs, G.B., 2010. The effects of armoring shorelines the California experience. In: Rice, C.A., 2006. Effects of shoreline modification on a northern Puget Sound beach: Shipman, H., Dethier, M.N., Gelfenbaum, G., Fresh, K.L., Dinicola, R.S. (Eds.), microclimate and embryo mortality in surf smelt (Hypomesus pretiosus). Estuar. Puget Sound Shorelines and the Impacts of Armoring Proceedings of a State Coasts 29, 63 71. of the Science Workshop, May 2009: U.S. Geological Survey Scientific In- Rolet, C., Spilmont, N., Davoult, D., Goberville, E., Luczak, C., 2015. Anthropogenic vestigations Report 2010-5254, pp. 77 84. impact on macrobenthic communities and consequences for shorebirds in Griggs, G.B., Tait, J.F., Corona, W., 1994. The interaction of seawalls and beaches Northern France: a complex response. Biol. Conserv. 184, 396 404. seven years of monitoring, Monterey Bay, California. Shore Beach 62, 21 28. Ruggiero, P., 2010. Impacts of shoreline armoring on sediment dynamics. In: Harris, L., Nel, R., Holness, S., Schoeman, D., 2015. Quantifying cumulative threats to Shipman, H., Dethier, M.N., Gelfenbaum, G., Fresh, K.L., Dinicola, R.S. (Eds.), sandy beach ecosystems: a tool to guide ecosystem-based management beyond Puget Sound Shorelines and the Impacts of Armoring Proceedings of a State coastal reserves. Ocean. Coast. Manage 110, 12 24. of the Science Workshop, May 2009: U.S. Geological Survey Scientific In- Heerhartz, S.M., 2013. Shoreline Armoring Disrupts Marine-terrestrial Connectivity vestigations Report 2010-5254, pp. 179 186. across the Nearshore Ecotone. School of Aquatic and Fishery Sciences, Univer- Runge, D.A., Martin, T.G., Possingham, H.P., Willis, S.G., Fuller, R.A., 2014. Conserving sity of Washington. PhD Dissertation. mobile species. Front. Ecol. Environ. 12, 395 402. Heerhartz, S.M., Dethier, M.N., Toft, J.D., Cordell, J.R., Ogston, A.S., 2014. Effects of Samhouri, J.F., Levin, P.S., Ainsworth, C.H., 2010. Identifying thresholds for shoreline armoring on beach wrack subsidies to the nearshore ecotone in an ecosystem-based management. PLoS One 5 (1), e8907. http://dx.doi.org/ estuarine fjord. Estuar. Coasts 37, 1256 1268. http://dx.doi.org/10.1007/s12237- 10.1371/journal.pone.0008907. 013-9754-5. Scyphers, S.B., Picou, J.S., Powers, S.P., 2015. Participatory conservation of coastal Heerhartz, S.M., Toft, J.D., 2015. Movement patterns and feeding behavior of juve- habitats: the importance of understanding homeowner decision making to nile salmon (Oncorhynchus spp.) along armored and unarmored estuarine mitigate cascading shoreline degradation. Conserv. Lett. 8, 41 49. shorelines. Enviro. Biol. Fishes 98, 1501 1511. http://dx.doi.org/10.1007/s10641- Shipman, H., 2010. The geomorphic setting of Puget Sound: implications for 015-0377-5. shoreline erosion and the impacts of erosion control structures. In: Shipman, H., Heerhartz, S.M., Toft, J.D., Cordell, J.R., Dethier, M.N., Ogston, A.S., 2015. Shoreline Dethier, M.N., Gelfenbaum, G., Fresh, K.L., Dinicola, R.S. (Eds.), Puget Sound armoring in an estuary constrains wrack-associated invertebrate communities. Shorelines and the Impacts of Armoring Proceedings of a State of the Science Estuar. Coasts. http://dx.doi.org/10.1007/s12237-015-9983-x. Workshop, May 2009: U.S. Geological Survey Scientific Investigations Report Hurlbert, S.H., Lombardi, C.M., 2003. Design and analysis: uncertain intent, uncer- 2010-5254, pp. 19 34. tain result. Ecology 84, 810 812. Simenstad, C.A., Ramirez, M., Burke, J., Logsdon, M., Shipman, H., Tanner, C., Toft, J., Hurlbert, S.H., Lombardi, C.M., 2012. Lopsided reasoning on lopsided tests and Craig, B., Davis, C., Fung, J., Bloch, P., Fresh, K., Myers, D., Iverson, E., Bailey, A., multiple comparisons. Aust. N. Z. J. Stat. http://dx.doi.org/10.1111/j.1467- Schlenger, P., Kiblinger, C., Myre, P., Gerstel, W., MacLennan, A., 2011. Historical 842X.2012.00652.x. Change of Puget Sound Shorelines: Puget Sound Nearshore Ecosystem Project Keuler, R.F., 1988. Map Showing Coastal Erosion, Sediment Supply, and Longshore Change Analysis. Puget Sound Nearshore Report No. 2011-01. Published by Transport in the Port Townsend 30- by 60-minute Quadrangle, Puget Sound Washington Department of Fish and Wildlife, Olympia, Washington, and U.S. Region. U.S. Geological Survey Miscellaneous Investigations Map 1198-E, Army Corps of Engineers, Seattle, Washington. Washington. Sobocinski, K.L., Cordell, J.R., Simenstad, C.A., 2010. Effects of shoreline modifica- Koch, H., 1989. The effect of tidal inundation on the activity and behavior of the tions on supratidal macroinvertebrate fauna on Puget Sound, Washington supralittoral talitrid amphipod Traskorchestia traskiana (Stimpson, 1857). Crus- beaches. Estuar. Coasts 33, 699 711. taceana 57, 295 303. Taylor, J.A., Murdock, A.P., Pontee, N.I., 2004. A macroscale analysis of coastal Kraus, N.C., McDougal, W.G., 1996. The effects of seawalls on the beach: part 1: an steepening around the coast of England and Wales. Geogr. J. 170, 179 188. updated literature review. J. Coast. Res. 12, 691 702. Toft, J.D., Cordell, J.R., Simenstad, C.A., Stamatiou, L.A., 2007. Fish distribution, Munsch, S.H., Cordell, J.R., Toft, J.D., 2015. Effects of seawall armoring on juvenile abundance, and behavior along city shoreline types in Puget Sound. N. Amer. J. Pacific salmon diets in an urban estuarine embayment. Mar. Ecol. Prog. Ser. 535, Fish. Manage 27, 465 480. 213 229. Toft, J.D., Ogston, A.S., Heerhartz, S.A., Cordell, J.R., Flemer, E.E., 2013. Ecological Nordstrom, K.F., 2014. Living with shore protection structures: a review. Estuar. response and physical stability of habitat enhancements along an urban Coast. Shelf Sci. 150, 11 23. armored shoreline. Ecol. Eng. 57, 97 108. Pelletier, A.J.D., Jelinski, D.E., Treplin, M., Zimmer, M., 2011. Colonisation of beach- Toft, J.D., Cordell, J.R., Armbrust, E.A., 2014. Shoreline armoring impacts and beach cast macrophyte wrack patches by talitrid amphipods: a primer. Estuar. restoration effectiveness vary with elevation. Northwest Sci. 88, 367 375. Coasts 34, 863 871. Toms, J.D., Lesperance, M.L., 2003. Piecewise regression: a tool for identifying Penttila, D., 2007. Marine forage Fishes in Puget Sound. Puget Sound Nearshore ecological thresholds. Ecology 84, 2034 2041. Partnership Report No. 2007-03. Published by Seattle District. U.S. Army Corps Venables, W.N., Ripley, B.D., 2002. Modern Applied Statistics with S, fourth ed. of Engineers, Seattle, Washington. Springer, New York. ISBN 0-387-95457-0. Pilkey, O.H., Wright III, H.L., 1988. Seawalls versus beaches. J. Coast. Res. SI 4, 41 64. Viola, S.M., Hubbard, D.M., Dugan, J.H., Schooler, N.K., 2013. Burrowing inhibition by Quinn, T., Krueger, K., Pierce, K., Penttila, D., Perry, K., Hicks, T., Lowry, D., 2012. fine textured beach fill: implications for recovery of beach ecosystems. Estuar. Patterns of surf smelt, Hypomesus pretiosus, intertidal spawning habitat use in Coast. Shelf Sci. 150, 142 148. Puget Sound, Washington State. Estuar. Coasts 35, 1214 1228. ESTUARINE, COASTAL AND SHELF SCIENCE In association with the Estuarine Coastal Sciences Association (ECSA)

AUTHOR INFORMATION PACK

TABLE OF CONTENTS

• Description p.1 • Audience p.2 • Impact Factor p.2 • Abstracting and Indexing p.2 • Editorial Board p.2 • Guide for Authors p.6

ISSN: 0272-7714

DESCRIPTION

Estuarine, Coastal and Shelf Science is an international multidisciplinary journal devoted to the analysis of saline water phenomena ranging from the outer edge of the continental shelf to the upper limits of the tidal zone. The journal provides a unique forum, unifying the multidisciplinary approaches to the study of the oceanography of estuaries, coastal zones, and continental shelf seas. It features original research papers, review papers and short communications treating such disciplines as zoology, botany, geology, sedimentology, physical oceanography. Data reports of mainly local interest are discouraged.

Research areas include:

• Numerical modelling of estuarine and coastal marine ecosystems • Species distribution in relation to varying environments • Effects of waste disposal • Groundwater runoff and Chemical processes • Estuarine and fjord circulation patterns • Meteorological and oceanic forcing of semi-enclosed and continental shelf water masses • Sea-surface and sea-bed processes • Estuarine and coastal sedimentary processes and geochemistry • Brackish water and lagoon phenomena • Transitional waters

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Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our support pages: http://support.elsevier.com

For reviewers: We can provide reviewers of Estuarine, Coastal and Shelf Science with a letter of recognition or a review certificate upon request. Please contact Dr. Luaine Bandounas at [email protected], for more information.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 1 AUDIENCE

Marine biologists and ecologists, physical, chemical and biological oceanographers, marine sedimentologists, geologists and geochemists.

IMPACT FACTOR

2014: 2.057 © Thomson Reuters Journal Citation Reports 2015

ABSTRACTING AND INDEXING

BIOBASE Current Contents ASCA/Engineering Technology & Applied Science/Science Citation Index/SCISEARCH Data Current Contents/Agriculture, Biology & Environmental Sciences Current Contents/Physics, Chemical, & Earth Sciences Marine Literature Review Meteorological and Geoastrophysical Abstracts Engineering Index Environmental Periodicals Bibliography Geo Bib & Index INSPEC Data/Cam Sci Abstr Oceanbase Oceanographic Literature Review Research Alert Scisearch Current Awareness in Biological Sciences CAB International Chemical Abstracts Service Scopus BIOSIS databases/Zoological Records

EDITORIAL BOARD

Editors D. Baird, University of Stellenbosch, Matieland, South Africa Estuarine and coastal ecosystem theory; dynamics and modelling; Ecological Network Analysis; nutrient dynamics and cycling in estuarine and marine ecosystems; water quality assessments. T.S. Bianchi, Dept. of Geological Sciences, University of Florida, Gainesville, FL 32611-2120, USA Papers dealing with water/sediment chemistry, biogeochemical cycling, water/sediment contaminants and global change M. Elliott, Inst. of Estuarine and Coastal Studies, University of Hull, Cottingham Road, Hull, HU6 7RX, UK Papers from Europe, Africa, Australasia and Asia dealing with Life Sciences (ecology, biology, ecosystems), Biota-Chemistry links, Human Impacts, Ecosystem Management and Natural Science- Social Science links T. Jennerjahn, Leibniz Center for Tropical Marine Ecology in Bremen, Bremen, Germany Biogeochemical cycling in rivers/estuaries; mangroves; seagrasses and coastal seas; Organic matter diagenesis; Tropical coastal ecosystems; Eutrophication S. Mitchell, University of Portsmouth, Portsmouth, UK Estuarine sediment transport;dynamics of turbidity maxima in estuaries;civil engineering hydraulics;coastal morphodynamics I. Valiela, Ecosystems Center, Marine Biological Laboratory, 7 MBL St. Woods Hole, MA 02543, USA Basic and applied papers from the Americas on aspects of life sciences, biogeochemical linkages, and global change , review papers from all regions, and invited feature articles

Honorary Editor E. Wolanski, Australian Institute of Marine Science, Townsville, Queensland, Australia Associate Editors R. Asmus, Alfred Wegener Institute for Polar and Marine Research, List, Germany

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 2 coastal ecology, food web analysis, primary production of seagrasses, microphytobenthos and phytoplankton, nutrient dynamics, benthic - pelagic coupling M.M. Baskaran, Wayne State University (WSU), Detroit, Michigan, USA Trace metals and isotopes D. Bowers, University of Wales, Menai Bridge, UK marine optics; remote sensing of suspended sediments and CDOM; physical oceanography of estuaries and shelf seas; suspended sediments and marine turbulence D.R. Cahoon, United States Geological Survey (USGS), Beltsville, Maryland, USA wetland vertical development processes; wetland restoration and management R. Carmichael, Dauphin Island Sea Laboratory, Dauphin Island, Alabama, USA population and trophic ecology; nutrient enrichment and wastewater sources to costal waters - covering invertebrates from bivalve shellfish and horseshoe crabs to cetaceans and manatees Z. Chen, East China Normal University, Shanghai, China hydro-geomorphology; and delta-estuary-shelf sedimentology L.M.Z. Chicharo, Universidade do Algarve, Faro, Portugal Estuarine fisheries; food web; salt marsh R. Feagin, Texas A&M University, College Station, Texas, USA Spatial analysis of the erosion in wetlands, dunes, beaches. This includes the use of GIS. A. Franco, Hull, UK fish ecology; community structure and functioning; estuaries, lagoons and coastal waters; numerical/ quantitative ecology and statistics R.W. Fulweiler, Boston University, Boston, Massachusetts, USA coastal ecology; biogeochemistry; climate change impacts on coastal systems C.K. Harris, Virginia Institute of Marine Science, Gloucester Point, Virginia, USA Sediment transport; Numerical models; Estuaries; Continental shelves J. Lambrechts, Louvain-la-Neuve, Belgium Estuarine and shelf oceanographic modeling, cohesive fine sediment modeling, modeling the dispersion of waterborne particles with/without a special behavior (e.g. swimming for fish larvae and turtle hatchlings, additional wind drift for floating debris). A. Manning, Plymouth University, Plymouth, Devon, UK Cohesive sediment transport; Flocculation process; Mixed sediment processes; Nearshore physical oceanography P. Martinetto, Universidad Nacional de Mar del Plata, Mar del Plata, Argentina eutrophication; biological interactions, C and N stable isotopes; coastal and estuarine food webs. J. McClelland, University of Texas at Austin, Port Aransas, Texas, USA fluvial export; coastal ecosystem dynamics; biogeochemistry R.N. Mead, University of North Carolina at Wilmington (UNCW), Wilmington, North Carolina, USA Organic geochemistry, molecular markers, contaminate fate, natural organic matter fate and transport in estuarine and coastal environments I. Nagelkerken, University of Adelaide, Adelaide, Australia Effects of climate change on aquatic fauna; coastal & marine fish ecology P.A. Noble, University of Washington, Seattle, Washington, USA DNA sequencing, DNA microarrays, and modelling C. Osburn, Raleigh, USA dissolved and particulate organic matter; photochemistry; absorbance; fluorescence; stable isotopes and biomarkers. M.F. Piehler, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Microbial biogeochemistry J.L. Pinckney, University of South Carolina, Columbia, South Carolina, USA Marine Ecology, phytoplankton, microphytobenthos, ecosystem processes V. Quintino, Universidade de Aveiro, Aveiro, Portugal benthic ecology (mainly Atlantic, intertidal sandy and rocky shores and subtidal estuarine and coastal shelf areas); bioassement or biomonitoring (namely sediment ecotoxicology, including integrated approaches such as the sediment quality triad, biotic indicators and indices); community level responses to natural and anthropogenic factors P.A.G. Regnier, Brussels, Belgium Estuarine and coastal carbon dynamics in the context of the global carbon cycle; reactive-transport and GIS modeling of the river-estuary-coastal zone continuum, early diagenetic modeling, greenhouse gas dynamics (CO2, CH4, N2O), anthropogenic perturbation of the coastal carbon cycle. A.M. Shiller, Stennis Space Center, USA Trace element chemistry; biogeochemical cycling; methane; carbon cycling S.A. Skrabal, Wilmington, USA

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 3 Trace metal speciation and behavior;Sediment-water intereactions;Effects of sunlight on inorganic and organic components in sediments A. Stubbins, Savannah, USA Dissolved organic matter; aquatic biogeochemistry; environmental photochemistry; glacier, riverine and marine carbon cycle P.W. Swarzenski, U.S. Geological Survey (USGS), Santa Cruz, California, USA M. Teichberg, Leibniz Center for Tropical Marine Ecology in Bremen, Bremen, Germany marine plant and algal ecology and physiology, estuarine and coastal shallow water ecosystems, eutrophication, ocean acidification I. Telesh, Russian Academy of Sciences, St. Petersburg, Russian Federation plankton ecology and biodiversity; ecosystem effects of invasive species ; Impact of salinity gradient on aquatic communities M.A. Teodósio, Faro, Portugal Estuarine and coastal ecology, plankton, fish larvae, aquatic macroinvertebrates, climate change, marine acidification S. Vizzini, Università degli Studi di Palermo, Palermo, Italy C and N stable isotopes; food webs; seagrasses; contaminant trophic transfer; ocean acidification X.H. Wang, University of New South Wales, Canberra, New South Wales, Australia coastal oceanography; numerical modelling; sediment transport dynamics A. Whitfield, South African Institute for Aquatic Biodiversity (SAIAB), Grahamstown, South Africa biology and ecology of fishes in estuaries J.G. Wilson, Trinity College, Dublin, Ireland Bioindicators and coastal management; Aquatic systems analysis; Estuarine pollution; heavy metals and nutrients; Biota/sediment/water interactions; Ecophysiology and energetics K. Xu, Baton Rouge, USA Geological oceanography; coastal morphodynamics; observation and numerical modeling of sediment transport; sediment dynamics of bottom boundary layer; sedimentary geology; coastal processes

Founding Editors N.C. Flemming E. Naylor, University of Wales, Menai Bridge, UK Editorial Board M. Alber, University of Georgia, Athens, Georgia, USA estuarine ecology; salt marsh ecology; and coastal policy. J. Bowen, University of Massachusetts Boston, Boston, Massachusetts, USA Estuarine microbial ecology; estuarine nitrogen cycling; salt marsh ecology W.R. Boynton, University of Maryland, Solomons, Maryland, USA estuarine ecology, eutrophication/water quality; nutrient cycling; nutrient mass balances O. Defeo, UNDECIMAR, Montevideo, Uruguay Ecology of sandy shores; Small-scale fisheries M. Devlin, James Cook University, Townsville, Queensland, Australia Q. Dortch, National Oceanic and Atmospheric Administration, Silver Spring, Maryland, USA phytoplankton ecology, Harmful Algal Blooms, and eutrophication J. Gomes Ferreira, University of Lisbon, Monte de Caparica, Portugal Ecological modelling of estuarine and coastal systems, particularly in the fields of aquaculture and eutrophication. R. Gowen, Agri-Food and Biosciences Institute, Belfast, Northern Ireland, UK Phytoplankton and zooplankton ecology; Marine eutrophication; Harmful algal blooms; Marine ecosystem structure and functioning F.L. Hellweger, Northeastern University, Boston, Massachusetts, USA surface water quality, microbial ecology, mathematical modeling. O. Iribarne, Universidad Nacional de Mar del Plata, Mar del Plata, Argentina Estuarine and coastal ecology; Community ecology; Food webs; Coastal fisheries E. Jaramillo, Universidad Austral de Chile, Valdivia, Chile D.S. McLusky, University of Stirling, Stirling, UK Definition of estuaries and transitional waters; Effects of salinity on estuarine invertebrates; Estuarine ecosystems, and the impact of pollution on them A.J. Mehta, University of Florida, Gainesville, Florida, USA coastal Hydraulics; cohesive sediment transport G. Millward, Plymouth University, Plymouth, UK Etuarine and marine biogeochemistry, specifically reaction kinetics in aquatic systems, involving particle-water interactions. He also works on the behaviour and transport of radionuclides in estuaries.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 4 G.M.E. Perillo, Instituto Argentino de Oceanografia, Bahia Blanca, Argentina Geomorphology and Dynamics of Estuaries and Coastal Wetlands - Dynamics of sediment transport - Physical-Biological interactions D. Prandle, Hertfordshire, UK observational, modelling and theoretical studies of: tide and storm surge propagation; tidal energy extraction; circulation and mixing; temperatures; sedimentation and water quality in shelf seas and their coastal margins J. Romero, University of Barcelona, Barcelona, Spain Seagrass biology and ecology, benthic community ecology Y. Saito, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan sedimentary process, sequence stratigraphy, all silliciclastic shallow marine sediments S.D. Sulkin, Western Washington University, Anacortes, Washington, USA W. Zhang, East China Normal University, Shanghai, China heavy metal pollution; sediment tracing using magnetic and geochemical methods; coastal environmental changes

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 5 GUIDE FOR AUTHORS

Your Paper Your Way We now differentiate between the requirements for new and revised submissions. You may choose to submit your manuscript as a single Word or PDF file to be used in the refereeing process. Only when your paper is at the revision stage, will you be requested to put your paper in to a 'correct format' for acceptance and provide the items required for the publication of your article. To find out more, please visit the Preparation section below. Types of paper Estuarine, Coastal and Shelf Science is an international multidisciplinary journal devoted to the analysis of saline water phenomena ranging from the outer edge of the continental shelf to the upper limits of the tidal zone. The journal provides a unique forum, unifying the multidisciplinary approaches to the study of the oceanography of estuaries, coastal zones, and continental shelf seas. It features original research papers, review papers and short communications treating such disciplines as zoology, botany, geology, sedimentology, physical oceanography. Data reports of mainly local interest are discouraged. An original research paper should not contain more than 8000 words, and no more than 8 figures and 3 tables. A research note/short communication should not contain more than 4,000 words and no more than 3 figures and 1 table. The Journal also welcomes suggestions from leading and internationally renowned scientists for in-depth Reviews and Invited Feature Articles on wide- ranging and contemporary topics. These Reviews can be approx. 12,000 words but the suggestions should be discussed with one of the Editors-in-Chief in the first instance.

Research areas include: Numerical modelling of estuarine and coastal marine ecosystems; Species distribution in relation to varying environments; Effects of waste disposal; Groundwater runoff and Chemical processes; Estuarine and fjord circulation patterns; Meteorological and oceanic forcing of semi-enclosed and continental shelf water masses; Sea-surface and sea-bed processes; Estuarine and coastal sedimentary processes and geochemistry; Brackish water and lagoon phenomena; Transitional waters.

Up-front rejections of papers submitted to Estuarine, Coastal and Shelf Science

ECSS handles about 1000 papers per year and over 3000 reviewers are involved in assisting the journal each year.

As editors we follow the declared guidelines for the journal and we also receive advice and comments from the publishers, and members of the editorial board as well as reviewers. The consistent advice that we have received from everyone is that the editors should reject papers which are likely to be rejected at the beginning of the process rather than sending them out for review, knowing what the answer is likely to be. Over 25% of papers are now rejected at the editorial submission phase.

The papers are subject to an initial technical pre-screening process by the publisher. This process checks on submission format and examines matters such as the provision of suitable keywords and legible figures. It also tries to check up on the standard of English, as it is totally inappropriate to expect a reviewer to undertake linguistic revision.

The pre-screening process however makes no judgement on the suitability of the paper for ECSS. This judgement is made by one of the editors who will up-front reject a paper judged unsuitable without going to review. These up-front rejections are due to three principal reasons:

Firstly, we receive several papers each year that have been submitted to the "wrong journal". We have received, for example, papers on inland freshwater lakes or palaeontology, and other topics which are clearly beyond the scope of the journal. As a simple guide, if there is no mention of any previous ECSS paper in the reference list, it strongly suggests that the paper has been submitted to the wrong journal.

Secondly, papers that are "data reports" or "reports of local interest" will be rejected up-front. Papers in this category may describe a particular estuary in great detail, but fail to advance estuarine, coastal and shelf science. The overwhelming feeling when reading such a paper is "so-what!"

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 6 Thirdly, other reasons for up-front rejection can be a lack of a valid Discussion which integrates the study with the peer-reviewed literature or else relies on excessive self-citation, or a lack of appropriate statistical analysis, or purely statistical analyses without considering processes.

We at ECSS seek that all papers are based on hypothesis testing and that the hypotheses should be of general and international interest. We are interested in contributions that add to general knowledge, and move the field forward.

By up-front rejection we hope to give the authors a chance to quickly submit to a more appropriate journal. We do accept that we will sometimes make mistakes in this process, but we do this to protect the reviewers by offering them only relevant papers that are potentially publishable in ECSS. Up- front rejected papers will not be reconsidered for publication and we have a similar policy for papers rejected after review. BEFORE YOU BEGIN Ethics in publishing For information on Ethics in publishing and Ethical guidelines for journal publication see https://www.elsevier.com/publishingethics and https://www.elsevier.com/journal-authors/ethics. Conflict of interest All authors are requested to disclose any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the submitted work that could inappropriately influence, or be perceived to influence, their work. See also https://www.elsevier.com/conflictsofinterest. Further information and an example of a Conflict of Interest form can be found at: http://service.elsevier.com/app/answers/detail/a_id/286/supporthub/publishing. Submission Declaration and Verefication Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis or as an electronic preprint, see http://www.elsevier.com/postingpolicy), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder. To verify originality, your article may be checked by the originality detection service CrossCheck http://www.elsevier.com/editors/plagdetect. The cover letter must include a declaration that all authors agree to the submission Contributors Each author is required to declare his or her individual contribution to the article: all authors must have materially participated in the research and/or article preparation, so roles for all authors should be described. The statement that all authors have approved the final article should be true and included in the disclosure. Changes to authorship Authors are expected to consider carefully the list and order of authors before submitting their manuscript and provide the definitive list of authors at the time of the original submission. Any addition, deletion or rearrangement of author names in the authorship list should be made only before the manuscript has been accepted and only if approved by the journal Editor. To request such a change, the Editor must receive the following from the corresponding author: (a) the reason for the change in author list and (b) written confirmation (e-mail, letter) from all authors that they agree with the addition, removal or rearrangement. In the case of addition or removal of authors, this includes confirmation from the author being added or removed. Only in exceptional circumstances will the Editor consider the addition, deletion or rearrangement of authors after the manuscript has been accepted. While the Editor considers the request, publication of the manuscript will be suspended. If the manuscript has already been published in an online issue, any requests approved by the Editor will result in a corrigendum.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 7 Article transfer service This journal is part of our Article Transfer Service. This means that if the Editor feels your article is more suitable in one of our other participating journals, then you may be asked to consider transferring the article to one of those. If you agree, your article will be transferred automatically on your behalf with no need to reformat. Please note that your article will be reviewed again by the new journal. More information about this can be found here: https://www.elsevier.com/authors/article-transfer-service. Copyright Upon acceptance of an article, authors will be asked to complete a 'Journal Publishing Agreement' (for more information on this and copyright, see https://www.elsevier.com/copyright). An e-mail will be sent to the corresponding author confirming receipt of the manuscript together with a 'Journal Publishing Agreement' form or a link to the online version of this agreement.

Subscribers may reproduce tables of contents or prepare lists of articles including abstracts for internal circulation within their institutions. Permission of the Publisher is required for resale or distribution outside the institution and for all other derivative works, including compilations and translations (please consult https://www.elsevier.com/permissions). If excerpts from other copyrighted works are included, the author(s) must obtain written permission from the copyright owners and credit the source(s) in the article. Elsevier has preprinted forms for use by authors in these cases: please consult https://www.elsevier.com/permissions.

For open access articles: Upon acceptance of an article, authors will be asked to complete an 'Exclusive License Agreement' (for more information see https://www.elsevier.com/OAauthoragreement). Permitted third party reuse of open access articles is determined by the author's choice of user license (see https://www.elsevier.com/openaccesslicenses).

Author rights As an author you (or your employer or institution) have certain rights to reuse your work. For more information see https://www.elsevier.com/copyright. Role of the funding source You are requested to identify who provided financial support for the conduct of the research and/or preparation of the article and to briefly describe the role of the sponsor(s), if any, in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. If the funding source(s) had no such involvement then this should be stated. Funding body agreements and policies Elsevier has established a number of agreements with funding bodies which allow authors to comply with their funder's open access policies. Some authors may also be reimbursed for associated publication fees. To learn more about existing agreements please visit https://www.elsevier.com/fundingbodies. Open access This journal offers authors a choice in publishing their research:

Open access • Articles are freely available to both subscribers and the wider public with permitted reuse. • An open access publication fee is payable by authors or on their behalf (e.g. by their research funder or institution). Subscription • Articles are made available to subscribers as well as developing countries and patient groups through our universal access programs (https://www.elsevier.com/access). • No open access publication fee payable by authors.

Regardless of how you choose to publish your article, the journal will apply the same peer review criteria and acceptance standards.

For open access articles, permitted third party (re)use is defined by the following Creative Commons user licenses:

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 8 Creative Commons Attribution (CC BY) Lets others distribute and copy the article, create extracts, abstracts, and other revised versions, adaptations or derivative works of or from an article (such as a translation), include in a collective work (such as an anthology), text or data mine the article, even for commercial purposes, as long as they credit the author(s), do not represent the author as endorsing their adaptation of the article, and do not modify the article in such a way as to damage the author's honor or reputation. Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) For non-commercial purposes, lets others distribute and copy the article, and to include in a collective work (such as an anthology), as long as they credit the author(s) and provided they do not alter or modify the article. The open access publication fee for this journal is USD 3000, excluding taxes. Learn more about Elsevier's pricing policy: https://www.elsevier.com/openaccesspricing. Green open access Authors can share their research in a variety of different ways and Elsevier has a number of green open access options available. We recommend authors see our green open access page for further information (http://elsevier.com/greenopenaccess). Authors can also self-archive their manuscripts immediately and enable public access from their institution's repository after an embargo period. This is the version that has been accepted for publication and which typically includes author-incorporated changes suggested during submission, peer review and in editor-author communications. Embargo period: For subscription articles, an appropriate amount of time is needed for journals to deliver value to subscribing customers before an article becomes freely available to the public. This is the embargo period and it begins from the date the article is formally published online in its final and fully citable form. This journal has an embargo period of 24 months. Elsevier Publishing Campus The Elsevier Publishing Campus (www.publishingcampus.com) is an online platform offering free lectures, interactive training and professional advice to support you in publishing your research. The College of Skills training offers modules on how to prepare, write and structure your article and explains how editors will look at your paper when it is submitted for publication. Use these resources, and more, to ensure that your submission will be the best that you can make it. Language and language services Manuscripts should be written in English. Authors who are unsure of correct English usage should have their manuscript checked by someone proficient in the language. Manuscripts in which the English is difficult to understand may be returned to the author for revision before scientific review. Please write your text in good English (American or British usage is accepted, but not a mixture of these). Authors who require information about language editing and copyediting services pre- and post-submission please visit http://www.elsevier.com/languagepolishing or our customer support site at service.elsevier.com for more information. Please note Elsevier neither endorses nor takes responsibility for any products, goods or services offered by outside vendors through our services or in any advertising. For more information please refer to our Terms & Conditions: http://www.elsevier.com/termsandconditions. Submission Submission to this journal proceeds totally online and you will be guided stepwise through the creation and uploading of your files. The system automatically converts source files to a single PDF file of the article, which is used in the peer-review process. Please note that even though manuscript source files are converted to PDF files at submission for the review process, these source files are needed for further processing after acceptance. All correspondence, including notification of the Editor's decision and requests for revision, takes place by e-mail removing the need for a paper trail.

In the case of Special Issues, authors should ensure that they submit manuscripts and meet any additional requirements in line with deadlines set by the Guest Editor(s) to ensure that the entire Special Issue can be published in a timely fashion.

The above represents a very brief outline of this type submission. It can be advantageous to print this "Guide for Authors" section from the site for reference in the subsequent stages of article preparation.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 9 Note: electronic articles submitted for the review process may need to be edited after acceptance to follow journal standards. For this an "editable" file format is necessary. See the section on "Electronic format requirements for accepted articles" and the further general instructions on how to prepare your article below.

Please submit, with the manuscript, the names and addresses of 4 potential Referees. You may also mention persons who you would prefer not to review your paper.

After peer review, authors will have a 60 days period for submitting their revised manuscript. Submit your article Please submit your article via http://ees.elsevier.com/ecss/

When submitting a manuscript, the author must carefully select the type of paper because several options are possible including normal research papers, short contributions, invited feature papers, review papers, invited editorials, and Special Issues. In the case of Special Issues, several Special issues may be in preparation at the same time and therefore authors must be very careful to select the correct Special Issue. Referees Please submit, with the manuscript, the names, addresses and current email addresses of four experts on the topic of the manuscript. To fit the broad scope of the journal, possible reviewers should include experts from a range of regional and international locations. You may also mention, with a brief reason, persons whom you would prefer not to review your paper. PREPARATION NEW SUBMISSIONS Submission to this journal proceeds totally online and you will be guided stepwise through the creation and uploading of your files. The system automatically converts your files to a single PDF file, which is used in the peer-review process. As part of the Your Paper Your Way service, you may choose to submit your manuscript as a single file to be used in the refereeing process. This can be a PDF file or a Word document, in any format or lay- out that can be used by referees to evaluate your manuscript. It should contain high enough quality figures for refereeing. If you prefer to do so, you may still provide all or some of the source files at the initial submission. Please note that individual figure files larger than 10 MB must be uploaded separately. References There are no strict requirements on reference formatting at submission. References can be in any style or format as long as the style is consistent. Where applicable, author(s) name(s), journal title/book title, chapter title/article title, year of publication, volume number/book chapter and the pagination must be present. Use of DOI is highly encouraged. The reference style used by the journal will be applied to the accepted article by Elsevier at the proof stage. Note that missing data will be highlighted at proof stage for the author to correct. Formatting requirements There are no strict formatting requirements but all manuscripts must contain the essential elements needed to convey your manuscript, for example Abstract, Keywords, Introduction, Materials and Methods, Results, Conclusions, Artwork and Tables with Captions. If your article includes any Videos and/or other Supplementary material, this should be included in your initial submission for peer review purposes. Divide the article into clearly defined sections. Please ensure the text of your paper is double-spaced and includes page numbers this is an essential peer review requirement. Figures and tables embedded in text Please ensure the figures and the tables included in the single file are placed next to the relevant text in the manuscript, rather than at the bottom or the top of the file. REVISED SUBMISSIONS

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 10 Use of word processing software Regardless of the file format of the original submission, at revision you must provide us with an editable file of the entire article. Keep the layout of the text as simple as possible. Most formatting codes will be removed and replaced on processing the article. The electronic text should be prepared in a way very similar to that of conventional manuscripts (see also the Guide to Publishing with Elsevier: https://www.elsevier.com/guidepublication). See also the section on Electronic artwork. To avoid unnecessary errors you are strongly advised to use the 'spell-check' and 'grammar-check' functions of your word processor. Article structure Subdivision - numbered sections Divide your article into clearly defined and numbered sections. Subsections should be numbered 1.1 (then 1.1.1, 1.1.2 ...), 1.2, etc. (the abstract is not included in section numbering). Use this numbering also for internal cross-referencing: do not just refer to "the text". Any subsection may be given a brief heading. Each heading should appear on its own separate line. Introduction State the objectives of the work and provide an adequate background, avoiding a detailed literature survey or a summary of the results. Material and methods Provide sufficient detail to allow the work to be reproduced. Methods already published should be indicated by a reference: only relevant modifications should be described. Theory/calculation A Theory section should extend, not repeat, the background to the article already dealt with in the Introduction and lay the foundation for further work. In contrast, a Calculation section represents a practical development from a theoretical basis. Results Results should be clear and concise. Discussion This should explore the significance of the results of the work, not repeat them. A combined Results and Discussion section is often appropriate. Avoid extensive citations and discussion of published literature. However, if the paper reads better with a combined section and this prevents an undue amount of repetition then we allow a joint section. Conclusions A short Conclusions section can be presented at the end of the Discussion.

Place Acknowledgements, including information on grants received, before the references in a separate section, and not as a footnote on the title page. Figure captions, tables, figures and schemes should be presented in this order at the end of the article. They are described in more detail below. Glossary Please supply, as a separate list, the definitions of field-specific terms used in your article if applicable. Appendices If there is more than one appendix, they should be identified as A, B, etc. Formulae and equations in appendices should be given separate numbering: Eq. (A.1), Eq. (A.2), etc.; in a subsequent appendix, Eq. (B.1) and so on. Similarly for tables and figures: Table A.1; Fig. A.1, etc. Paper length The paper should not contain more than 8000 words, and not more than 8 figures and 3 tables. Essential title page information • Title. Concise and informative. Titles are often used in information-retrieval systems. Avoid abbreviations and formulae where possible. • Author names and affiliations. Please clearly indicate the given name(s) and family name(s) of each author and check that all names are accurately spelled. Present the authors' affiliation addresses (where the actual work was done) below the names. Indicate all affiliations with a lower- case superscript letter immediately after the author's name and in front of the appropriate address. Provide the full postal address of each affiliation, including the country name and, if available, the e-mail address of each author.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 11 • Corresponding author. Clearly indicate who will handle correspondence at all stages of refereeing and publication, also post-publication. Ensure that the e-mail address is given and that contact details are kept up to date by the corresponding author. • Present/permanent address. If an author has moved since the work described in the article was done, or was visiting at the time, a 'Present address' (or 'Permanent address') may be indicated as a footnote to that author's name. The address at which the author actually did the work must be retained as the main, affiliation address. Superscript Arabic numerals are used for such footnotes. Abstract A concise and factual abstract is required. The abstract should state briefly the purpose of the research, the principal results and major conclusions. An abstract is often presented separately from the article, so it must be able to stand alone. For this reason, References should be avoided, but if essential, then cite the author(s) and year(s). Also, non-standard or uncommon abbreviations should be avoided, but if essential they must be defined at their first mention in the abstract itself. Graphical abstract A Graphical abstract is mandatory for this journal. It should summarize the contents of the article in a concise, pictorial form designed to capture the attention of a wide readership online. Authors must provide images that clearly represent the work described in the article. Graphical abstracts should be submitted as a separate file in the online submission system. Image size: please provide an image with a minimum of 531 × 1328 pixels (h × w) or proportionally more. The image should be readable at a size of 5 × 13 cm using a regular screen resolution of 96 dpi. Preferred file types: TIFF, EPS, PDF or MS Office files. See https://www.elsevier.com/graphicalabstracts for examples. Authors can make use of Elsevier's Illustration and Enhancement service to ensure the best presentation of their images also in accordance with all technical requirements: Illustration Service. Highlights Highlights are mandatory for this journal. They consist of a short collection of bullet points that convey the core findings of the article and should be submitted in a separate editable file in the online submission system. Please use 'Highlights' in the file name and include 3 to 5 bullet points (maximum 85 characters, including spaces, per bullet point). See https://www.elsevier.com/highlights for examples. Keywords Authors must provide 4 to 6 keywords plus regional index terms. At least four of the subject keywords should be selected from the Aquatic Science & Fisheries Thesaurus. An electronic version of the Thesaurus can be found at http://www.csa.com/csa/support/demo.shtml. You may also find a paper version in your library. The Regional Terms should be provided as a hierarchical string (e.g.: USA, California, Monterey Bay). Authors are also encouraged to submit geographic bounding coordinates at the end of the keyword string. These keywords will be used for indexing purposes. Abbreviations Define abbreviations that are not standard in this field in a footnote to be placed on the first page of the article. Such abbreviations that are unavoidable in the abstract must be defined at their first mention there, as well as in the footnote. Ensure consistency of abbreviations throughout the article if applicable. Acknowledgements Collate acknowledgements in a separate section at the end of the article before the references and do not, therefore, include them on the title page, as a footnote to the title or otherwise. List here those individuals who provided help during the research (e.g., providing language help, writing assistance or proof reading the article, etc.). Reporting of Salinity Measurements In articles in ECSS, salinity should be reported using the Practical Salinity Scale. In the Practical Salinity Scale salinity is defined as a pure ratio, and has no dimensions or units. By decision of the Joint Panel of Oceanographic Tables and Standards it does not have any numerical symbol to indicate parts per thousand. Salinity should be reported as a number with no symbol or indicator of proportion after it. In particular, it is not correct to add the letters PSU, implying Practical Salinity Units, after the number.

An example of correct phrasing is as follows: 'The salinity of the water was 34.2'. It is reasonable to state at some point early in the paper that salinity was measured using the Practical Salinity Scale.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 12 Formatting of funding sources List funding sources in this standard way to facilitate compliance to funder's requirements:

Funding: This work was supported by the National Institutes of Health [grant numbers xxxx, yyyy]; the Bill & Melinda Gates Foundation, Seattle, WA [grant number zzzz]; and the United States Institutes of Peace [grant number aaaa].

It is not necessary to include detailed descriptions on the program or type of grants and awards. When funding is from a block grant or other resources available to a university, college, or other research institution, submit the name of the institute or organization that provided the funding.

If no funding has been provided for the research, please include the following sentence:

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Nomenclature and units Follow internationally accepted rules and conventions: use the international system of units (SI). If other quantities are mentioned, give their equivalent in SI. You are urged to consult IUPAC: Nomenclature of Organic Chemistry: http://www.iupac.org/ for further information. Math formulae Please submit math equations as editable text and not as images. Present simple formulae in line with normal text where possible and use the solidus (/) instead of a horizontal line for small fractional terms, e.g., X/Y. In principle, variables are to be presented in italics. Powers of e are often more conveniently denoted by exp. Number consecutively any equations that have to be displayed separately from the text (if referred to explicitly in the text). Footnotes Footnotes should be used sparingly. Number them consecutively throughout the article. Many word processors build footnotes into the text, and this feature may be used. Should this not be the case, indicate the position of footnotes in the text and present the footnotes themselves separately at the end of the article. Artwork Electronic artwork General points • Make sure you use uniform lettering and sizing of your original artwork. • Preferred fonts: Arial (or Helvetica), Times New Roman (or Times), Symbol, Courier. • Number the illustrations according to their sequence in the text. • Use a logical naming convention for your artwork files. • Indicate per figure if it is a single, 1.5 or 2-column fitting image. • For Word submissions only, you may still provide figures and their captions, and tables within a single file at the revision stage. • Please note that individual figure files larger than 10 MB must be provided in separate source files. A detailed guide on electronic artwork is available on our website: https://www.elsevier.com/artworkinstructions. You are urged to visit this site; some excerpts from the detailed information are given here. Formats Regardless of the application used, when your electronic artwork is finalized, please 'save as' or convert the images to one of the following formats (note the resolution requirements for line drawings, halftones, and line/halftone combinations given below): EPS (or PDF): Vector drawings. Embed the font or save the text as 'graphics'. TIFF (or JPG): Color or grayscale photographs (halftones): always use a minimum of 300 dpi. TIFF (or JPG): Bitmapped line drawings: use a minimum of 1000 dpi. TIFF (or JPG): Combinations bitmapped line/half-tone (color or grayscale): a minimum of 500 dpi is required. Please do not: • Supply files that are optimized for screen use (e.g., GIF, BMP, PICT, WPG); the resolution is too low. • Supply files that are too low in resolution. • Submit graphics that are disproportionately large for the content.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 13 Color artwork Please make sure that artwork files are in an acceptable format (TIFF, EPS or MS Office files) and with the correct resolution. If, together with your accepted article, you submit usable color figures then Elsevier will ensure, at no additional charge that these figures will appear in color on the Web (e.g., ScienceDirect and other sites) regardless of whether or not these illustrations are reproduced in color in the printed version. For color reproduction in print, you will receive information regarding the costs from Elsevier after receipt of your accepted article. Please indicate your preference for color in print or on the Web only. For further information on the preparation of electronic artwork, please see http://www.elsevier.com/artworkinstructions. Please note: Because of technical complications which can arise by converting color figures to "gray scale" (for the printed version should you not opt for color in print) please submit in addition usable black and white versions of all the color illustrations. Figure captions Ensure that each illustration has a caption. A caption should comprise a brief title (not on the figure itself) and a description of the illustration. Keep text in the illustrations themselves to a minimum but explain all symbols and abbreviations used. Tables Please submit tables as editable text and not as images. Tables can be placed either next to the relevant text in the article, or on separate page(s) at the end. Number tables consecutively in accordance with their appearance in the text and place any table notes below the table body. Be sparing in the use of tables and ensure that the data presented in them do not duplicate results described elsewhere in the article. Please avoid using vertical rules. References Citation in text Responsibility for the accuracy of bibliographic citations lies entirely with the Author(s). Please ensure that every reference cited in the text is also present in the reference list (and vice versa). Any references cited in the abstract must be given in full. Unpublished results and personal communications are not recommended in the reference list, but may be mentioned in the text as "unpublished results" or "personal communication". Citation of a reference as 'in press' implies that the item has been accepted for publication. Papers which have been submitted are not valid as references until accepted. Web references As a minimum, the full URL should be given and the date when the reference was last accessed. Any further information, if known (DOI, author names, dates, reference to a source publication, etc.), should also be given. Web references can be listed separately (e.g., after the reference list) under a different heading if desired, or can be included in the reference list. References in a special issue Please ensure that the words 'this issue' are added to any references in the list (and any citations in the text) to other articles in the same Special Issue. Reference management software Most Elsevier journals have their reference template available in many of the most popular reference management software products. These include all products that support Citation Style Language styles (http://citationstyles.org), such as Mendeley (http://www.mendeley.com/features/reference-manager) and Zotero (https://www.zotero.org/), as well as EndNote (http://endnote.com/downloads/styles). Using the word processor plug-ins from these products, authors only need to select the appropriate journal template when preparing their article, after which citations and bibliographies will be automatically formatted in the journal's style. If no template is yet available for this journal, please follow the format of the sample references and citations as shown in this Guide. Users of Mendeley Desktop can easily install the reference style for this journal by clicking the following link: http://open.mendeley.com/use-citation-style/estuarine-coastal-and-shelf-science When preparing your manuscript, you will then be able to select this style using the Mendeley plug- ins for Microsoft Word or LibreOffice.

AUTHOR INFORMATION PACK 26 Apr 2016 www.elsevier.com/locate/ecss 14 Reference formatting There are no strict requirements on reference formatting at submission. References can be in any style or format as long as the style is consistent. Where applicable, author(s) name(s), journal title/book title, chapter title/article title, year of publication, volume number/book chapter and the pagination must be present. Use of DOI is highly encouraged. The reference style used by the journal will be applied to the accepted article by Elsevier at the proof stage. Note that missing data will be highlighted at proof stage for the author to correct. If you do wish to format the references yourself they should be arranged according to the following examples: Reference style All citations in the text should refer to: 1. Single Author's name (without initials) and year of publication. 2. Two Authors' names and the year of publication. 3. Three or more Authors; first Author's name followed by "et al." and the year of publication. In the list of references names of authors and all co-authors must be given in full. References in the text should be arranged chronologically. References in the Reference List should be arranged first alphabetically, and then further sorted chronologically if necessary. More than one reference from the same Author(s) in the same year must be identified by the letters "a", b", "c", etc., placed after the year of publication. Examples: References to a journal publication: Names and initials of all authors, year. Title of paper. Journal name (given in full), volume number: first and last page numbers of the paper. Gooday, A.J., Bett, B.J., Shires, R., Lambshead, P.J.D., 1998. Deep-sea benthic foraminiferal species diversity in the NE Atlantic and NW Arabian sea: a synthesis. Deep Sea Research Part II 45, 165-201.

References to a book: Names and initials of all authors, year. Title of the book. Publisher, location of publisher, total number of pages. Fennel, W. and Neumann, T., 2004. Introduction to the Modelling of Marine Ecosystems. Elsevier, Amsterdam, 297 pp.

Reference to a chapter in an edited book: Names and initials of all authors, year. Title of paper. Names and initials of the volume editors, title of the edited volume. Publisher, location of publisher, first and last page numbers of the paper. Thomas, E., 1992. Middle Eocene-late Oligocene bathyal benthic foraminifera (Weddell Sea): faunal changes and implications for ocean circulation. In: Prothero, D.R., Berggren, W.A. (Eds.), Eocene Oligocene Climatic and Biotic Evolution. Princeton Univ. Press, Princeton, NJ, pp. 245-271.

Conference proceedings papers: Names and initials of all authors, year. Title of paper. Name of the conference. Publisher, location of publisher, first and last page numbers of the paper. Smith, M.W., 1988. The significance of climatic change for the permafrost environment. Final Proceedings International Conference on Permafrost. Tapir, Trondheim, Norway, pp. 18-23. Unpublished theses, reports, etc.: Use of unpublished theses and reports is strongly discouraged. If they are essential and the editors agree, you must supply: Names and initials of all authors, year. Title of item. All other relevant information needed to identify the item (e.g., technical report, Ph.D. thesis, institute, current status i.e. in press/unpublished etc.). Moustakas, N., 1990. Relationships of Morphological and Physiochemical Properties of Vertisols under Greek Climate Conditions. Ph.D. Thesis, Agricultural Univ. Athens, Greece, unpublished.

In the case of publications in any language other than English, the original title is to be retained. Titles of publications in non-Latin alphabets should be transliterated, and a note such as '(in Russian)' or '(in Japanese, with English Abstract)' should be added at the end of the reference.

The following provide examples of appropriate citation formats for non-text and electronic-only information. However, it is requested that a Web site address or list server message is given as a reference ONLY where the information is unavailable in a more permanent form. If such sources are given, then please give as complete information as possible. Jones, P., 1996. Research activities at Smith Technology Institute. WWW Page, http://www.sti.com/about_us/research.

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LETTERS NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE2961

Research indicating how populations might adapt to SLR is 3. Vermeer, M. & Rahmstorf, S. Global sea level linked to global temperature. still in its infancy, thus limiting our ability to model how future Proc. Natl Acad. Sci. USA 106, 21527–21532 (2009). populations might organically adapt to rising seas and the loss 4. Parris, A. et al. Global Sea Level Rise Scenarios for the United States National of both current and future coastal human habitat. For instance, Climate Assessment (US Department of Commerce, National Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research, Climate Venice, Italy has seen its population remain stable over the past Program Office, 2012). 26 decade in spite of widely documented tidal flooding from both 5. Gregory, J. N. The Southern Diaspora: How the Great Migrations of Black and land subsidence and SLR, suggesting a complicated relationship White Southerners Transformed America (Univ. North Carolina, 2005). between population dynamics and SLR. Furthermore, adaptation 6. Wu, S.-Y., Yarnal, B. & Fisher, A. Vulnerability of coastal communities to and mitigation strategies are likely to be employed, shaping future sealevel rise: a case study of Cape May county, New Jersey, USA. Clim. Res. 22, population scenarios through unknown future public policies. Our 255–270 (2002). 7. Lutsey, N. & Sperling, D. America’s bottom-up climate change mitigation projections of inundated populations could be biased upwards by policy. Energy Policy 36, 673–685 (2008). the limited interaction between SLR and population growth. 8. Titus, J. et al. State and Local government plant for development of most land Uncertainty in our projections result from the sensitivity of vulnerable to rising sea level along the US Atlantic Coast. Environ. Res. Lett. long-term population to both the selection of base period length 4, 044008 (2009). and projection horizon length27. By using the longest possible 9. Black, R., Bennett, S. R. G., Thomas, S. M. & Beddington, J. R. Migration as base period, we do find acceptable accuracy for these projections, adaptation. Nature 478, 447–449 (2011). 10. Gray, C. & Bilsborrow, R. Environmental influences on human migration in with approximately half of the coastal states exceeding accuracy rural Ecuador. Demography 50, 1217–1241 (2013). expectations. There were notable exceptions, however, as four 11. Hugo, G. Future demographic change and its interactions with migration and states fell far below accuracy expectations—Massachusetts, Maine, climate change. Glob. Environ. Change 215, 521–533 (2011). Mississippi, and Rhode Island—with another eight states falling 12. Haer, T., Kalnay, E., Kearney, M. & Moll, H. Relative sea-level rise and the just below expectations (Supplementary Table 1). In spite of these conterminous United States: consequences of potential land inundation in issues, our out-of-sample validation found the projections to be terms of population at risk and GDP loss. Glob. Environ. Change 23, 1627–1636 (2013). reasonably calibrated, as four of the top six most affected states 13. Crossett, K., Ache, B., Pacheco, P. & Haber, K. National Coastal Population exceed expectations. Report, Population Trends from 1970 to 2020 (National Oceanic and Past trends do not guarantee future trends. Local growth Atmospheric Administration, Department of Commerce/US Census Bureau, ordinances and population saturation points could improve future 2014); http://oceanservice.noaa.gov/facts/coastal-population-report.pdf population projections. Furthermore, vertical land movement 14. Curtis, K. & Schneider, A. Understanding the demographic implications of will exacerbate the impacts of SLR, specifically in southeast climate change: estimates of localized population predictions under future 12,28 scenarios of sea-level rise. Popul. Environ. 33, 28–54 (2011). Louisiana and the Chesapeake Bay areas . Although we do not 15. Cromley, R. G., Ebenstein, A. Y. & Hanink, D. M. Estimating components of model vertical land movement, our results could be considered population change from census data for incongruent spatial/temporal units and conservative in the aforementioned areas expected to see the attributes. J. Spat. Sci. 54, 89–99 (2009). greatest land subsidence, as it is the combination of SLR and vertical 16. Swanson, D. A., Schlottman, A. & Schmidt, B. Forecasting the population of land movement that can prove the most destructive. census tracts by age and sex: an example of the Hamilton–Perry method in action. Popul. Res. Policy Rev. 29, 47–63 (2010). The approach demonstrated in this paper allows for spatially 17. Hauer, M., Evans, J. & Alexander, C. Sea-level rise and sub-county population and temporally aligning population data with any type of hazard projections in coastal Georgia. Popul. Environ. 37, 44–62 (2015). modelling requiring small-area spatio-temporal population 18. Hammer, R. B., Stewart, S. I., Winkler, R. L., Radeloff, V. C. & Voss, P. R. projections that can be readily used by decision makers and Characterizing dynamic spatial and temporal residential density patterns from researchers. For example, other by-products of SLR, such as loss of 1940–1990 across the North Central United States. Landscape Urban Plan. 69, coastal wetlands, saltwater intrusion, and higher storm surges from 183–199 (2004). 29–31 19. Sea Level Rise and Coastal Flooding Impacts (NOAA, 2014); tropical cyclones could also be modelled, as well as economic https://coast.noaa.gov/slrdata impacts from these hazards. For instance, using the example of 20. Fox, S. This is adaptation: the elimination of subsidies under the National 25 the cost for relocating some Alaskan coastal villages of US$1 Flood Insurance Program. Columbia J. Environ. Law 39, 205–249 (2014). million per resident, the cost of relocation could exceed US$14.0 21. Nicholls, R. J. et al. Sea-level rise and its possible impacts given a ‘beyond trillion (2014 values). More precise cost estimates could incorporate 4 ◦C world’ in the twenty-first century. Phil. Trans. R. Soc. A 369, our approach. There is high potential for coupling population 161–181 (2011). 22. Gornitz, V., Couch, S. & Hartig, E. K. Impacts of sea level rise in the New York projections in dynamic systems simulations that incorporate City metropolitan area. Glob. Planet. Change 32, 61–88 (2001). such stressors into multivariate scenario modelling. We note, 23. Arenstam Gibbons, S. J. & Nicholls, R. J. Island abandonment and sea-level rise: however, that our small-area projection method requires detailed an historical analog from the Chesapeake Bay, USA. Glob. Environ. Change 16, demographic information on the age of housing stock, thus limiting 40–47 (2006). the applicability of the approach to nations and jurisdictions where 24. Abel, N. et al. Sea level rise, coastal development and planned retreat: analytical such data are regularly collected and available. framework, governance principles and an Australian case study. Environ. Sci. Policy 14, 279–288 (2011). 25. Huntington, H. P., Goodstein, E. & Euskirchen, E. Towards a tipping point in Methods responding to change: rising costs, fewer options for Arctic and global societies. Methods and any associated references are available in the online Ambio 41, 66–74 (2012). version of the paper. 26. UN Statistics Division Demographic Statistics (UNdata, 2015); http://data.un.org/Data.aspx?d=POP&f=tableCode:240 Received 4 April 2015; accepted 15 February 2016; 27. Tayman, J., Smith, S. & Lin, J. Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models. Popul. Res. published online 14 March 2016 Policy Rev. 26, 347–369 (2007). 28. Nicholls, R. J. & Leatherman, S. P. Adapting to sea-level rise: relative sea-level References trends to 2100 for the United States. Coast. Manage. 24, 301–324 (1996). 1. Sweet, W. P. J., Marra, J., Zervas, C. & Gill, S. Sea Level Rise and Nuisance Flood 29. Nicholls, R. J. & Cazenave, A. Sea-level rise and its impact on coastal zones. Frequency Changes Around the United States NOAA Technical Report NOS Science 328, 1517–1520 (2010). CO-OPS 073 (NOAA, 2014); http://tidesandcurrents.noaa.gov/publications/ 30. Nicholls, R. J. Planning for the impacts of sea level rise. Oceanography 24, NOAA_Technical_Report_NOS_COOPS_073.pdf 144–157 (2011). 2. IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: 31. Burton, D. A. Comments on ‘‘Assessing future risk: quantifying the effects of Global and Sectoral Aspects (eds Field, C. B. et al.) (Cambridge Univ. sea level rise on storm surge risk for the southern shores of Long Island, Press, 2014). New York’’. Nat. Hazards 63, 1219–1221 (2012).

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© 2016 Macmillan Publishers Limited. All rights reserved NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE2961 LETTERS

Acknowledgements contributed significantly to the methodological design, conceptual framing, and editing Publication supported in part by an Institutional Grant (NA10OAR4170098) to the of the paper. D.R.M. produced the inundation modelling for Louisiana and contributed Georgia Sea Grant College Program from the National Sea Grant Office, National to the editing of the paper. Oceanic and Atmospheric Administration, US Department of Commerce. Data reported in the paper are available in the Supplementary Methods. The authors are grateful for the assistance and constructive comments from K. Devivo, C. Hopkinson, J. M. Shepherd, Additional information S. Holloway, T. Mote, J. Baker and W. Anderson. Supplementary information is available in the online version of the paper. Reprints and permissions information is available online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to M.E.H. Author contributions M.E.H. produced the small-area population projections and the projections of inundation, contributed to the methodological design, wrote the paper, and is the Competing financial interests corresponding author to whom requests for materials should be addressed. J M.E. The authors declare no competing financial interests.

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© 2016 Macmillan Publishers Limited. All rights reserved LETTERS NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE2961

Methods proportionally fitted to the marginals. Equation (1) demonstrates this proportional The methodology for overlaying projected small-area population with sea-level rise fitting approach. (SLR) inundation layers is outlined in this section. First, we describe the data sets and basic methodology behind SLR inundation layers. Second, the methodology to t Cj t−1 historically estimate housing un ts is introduced. Third, the methodology to X Hˆ t = t−1 ∗ H t (1) convert housing units to population is reviewed. Fourth, the extrapolation ij P t ij Hj i=1939 approach undertaken to produce population projections is reviewed. Next, the i=1939 determination of at-risk populations through intersection with SLR curves and inundation models is described. Last, we evaluate the accuracy of our The number of housing units in county j as counted in the census taken in time t population projections. t is denoted as Cj and the number of housing units in block group i in county j Ñ é t based on the ‘year structure built’ question in the ACS is denoted as Hij . Thus, any Data. Many assessments of the populations at risk from SLR have used an elevation estimate of housing units in any given block group in county j is given as a based ‘bath-tub’ approach for inundation modelling12,14,32, whereby all areas under proportionally adjusted estimate based on the ratio of the total number of housing a given threshold (usually 1 m, 2 m, 3 m, or 6 m) are flooded without explicit un ts as counted in the Census to a county’s estimated housing units from the ACS consideration of hydrological connectedness. A known limitation of the simple for t −1. For instance, an estimate of the number of housing units for block group i bath-tub approach is that areas protected from inundation by dykes or levees will in county j for the year 1980 would be equal to the number counted at the county 1980 be shown as inundated. For example, much of New Orleans, Louisiana is located at level according to the 1980 census, Cj , divided by the number of housing units at P1979 1980 an elevation well below local mean sea level. Under a simple bath-tub approach, all the county level in the ACS for the period 1939–1979, i=1939 Hj , multiplied by areas of New Orleans located below sea level, including those protected from the number of housing units observed in the ACS for the period 1939–1979 for P1979 1980 floodwaters by dykes and levees, would be shown as inundated under even an block group i in county j, i=1939 Hij . This process is terated for each decade in tial cond tion (0 m) SLR model. until the most recent time period, that is, the 2010 census. These estimates of For this research, we used SLR inundation data sets developed by the National housing units for each block group in each county provide the key input needed to Oceanographic and Atmospheric Administration (NOAA) as the basis for convert an estimate of housing units into an estimate of total population. simulating future SLR impacts on human populations in the coastal United States (US)19,33. The NOAA data sets are based on a 1/3 arcsecond (10m) resolution digital Housing units to population. Equation (2) demonstrates the approach employed elevation model (DEM), which is then used to simulate expected 0.3 m increment here to make use of the Housing Unit (HU) method to convert an estimate of (1 foot) changes in the mean higher high water (MHHW) mark, up to a maximum Housing Units to an estimate of population. scenario of 1.8 m (6 feet), on areas of the continental US that are hydrologically connected to the coastal zone. The low SLR value of 0.3 m and the high SLR value Pt =H ∗ PPHU+GQ (2) of 1.8 m in the NOAA data sets generally represent the range of low to high SLR scenarios defined by the most current US National Climate Assessment3. The Where H is the number of housing units, PPHU is the persons per household, and underlying 1/3 arcsecond DEM is used by the US federal government for GQ is the group quarters population. Any error associated with the HU method is development of floodplain contours, rated as ±0.3 m at the 85% confidence attributable to the qual ty of the inputs39, as the HU method is considered a interval34. Because such floodplain contour maps are used to set flood insurance demographic identity. The Hammer method, outlined above, can provide a rates at the parcel-scale, there is confidence in applying a similar 0.3 m interval long-range back cast of housing units for normalized boundaries in any given assessment of SLR as generalized across much larger geographic areas (for example, census geography (whether ts 1990, 2000, or 2010 geographies). Whereas counties and Census boundaries). However, we also note that the NOAA SLR data Census-designated boundaries may change, housing units typically do not move18. set does not take into account additional land loss caused by other natural factors Based on the ‘year structure built’ question in Census data, the method produces such as erosion, subsidence, or future construction, and are provided ‘as is’ without proportionally adjusted housing unit estimates at the sub-county CBG, which is the warranty to their performance. smallest geography possible for such projections using US Census data. We used the 1/9 arcsecond (3 m) NED data to develop the SLR projection Equation (3) demonstrates the approach employed here to use the HU method t+1 model for Louisiana. A 3 m MHHW surface was created using NOAA’s vertical to project a population. While PPHU and GQ are held constant, Hij can be datum conversion software, VDatum (http://vdatum.noaa.gov) and a triangulated projected though any set of extrapolation methods40–43. irregular network (TIN) was created and used for hydrologic connectivity mapping = t+1 ∗ t + t for the 0 m depth grid (current condition). A linear superposition method was used Pt+1 Hij PPHUij GQij (3) by adding 0.9 m (3 ft) and 1.8 m (6 ft) to the 0 m depth grid to map SLR scenarios. A small-area housing unit projection method was used to produce sub-county Projection approach. We employed a linear/exponential (LIN/EXP), population projections for all US coastal counties expected to have direct impacts regression-based extrapolation based on the past 70 years of population change for from the 1.8 m SLR scenario (n=319). The sub-county unit for these projections 1940–2010. Geographies that have experienced growth used a linearÛ regression was Census Block Groups (CBGs), w th geographies defined by the 2010 US whereas geographies that have experienced decline use an exponential regression. Census. Data for conducting the population projections come from three main A LIN/EXP model is used to ensure that long-range linear projections of decline do sources. The first source of data comes from the American Community Survey not project negative populations,Û and that long-range exponential projections of (ACS) 2008–2012 estimates. The ACS provides the ‘year structure built’ data, and growth do not produce extreme values of runaway growth. Recent research the 2010 boundaries for CBGs. The second piece of data is the actual historic count suggests that a LIN/EXP model outperforms both a linear and an exponential of housing units (HU) and population for each county. This data is available as model, respectively44. Included within the regression formulae is an adjustment digitized records from the Census Bureau’s website. For 1940 to 1990, data can be factor allowing for the projected and observed populations at launch year to be found at http://www.census.gov/prod/cen1990/cph2/cph-2-1-1.pdf. Census 2000 identical. This is computed by adding the residual of the estimate at time t back data can be downloaded through American FactFinder. Finally, our Group into the regressed estimate of time t. This allows the projection to go through the Quarters (GQ) population data come from the 2010 Census. It should be noted launch year population. The small data requirements make these extrapolation that the ACS data, although similar to decennial data, is subject to sampling error, methods ideal for small-area projections, and the use of a regression-based but all released ACS data have confidence limits above 90% (ref. 35). Furthermore, extrapolation allows for estimates of projection intervals. GQ tends to be the most volatile aspect of the Census Bureau’s Estimates Program If the base housing stock is growing: and ACS (ref. 36), but is an important aspect of the HU method. t+z = + + t − +  Hij (α βz) H (α βt) (4) Estimates of historic housing units. Demographic projections of small-areal units (that is, sub-county units) tend to be less robust than projection methodologies at If the base housing stock is declining: larger scales16,37. The changeabil ty of many sub-county boundaries (for example, t+z = β ∗ α + t − β ∗ α  Census Tracts and CBGs) at each decennial Census cycle provides a classic example Hij e z H (e t ) (5) of the modifiable areal unit problem (MAUP), thus effectively limiting the development of more long-range projections to areas in which geographic The use of a regression-based extrapolation allows for the creation of projection boundaries remain stable16. In the US, counties are the smallest geographies with intervals. We follow aÛ long line of inquiry in determining the credibility of boundaries that tend to remain stable over time. population projections using projection intervals45–50. These projection intervals We use a modified version of the Hammer method17,18 based on a proportional use the standard error of the estimate for the models and their sample sizes. fitting algor thm to project sub-county populations38. Hammer’s method is Intervals were generated using equations 4.1 and 4.2 from Hyndman & essentially a combination of a growth-allocation and proportional fitting approach, Athanasopoulos’ Forecasting:Û Principles and Practice51. We have chosen to produce where the growth between time periods is allocated to each block group and a set of three population projections for each block group, an upper, middle and

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© 2016 Macmillan Publishers Limited. All rights reserved NATURE CLIMATE CHANGE DOI: 10.1038/NCLIMATE2961 LETTERS lower bound based on the 90% projection interval. Thus we produce a set of the equations in the preceding section with base period 1940–2000. If less than 2/3 210,942 projections—one for every block group in the study area (n=72,664) as of the ACS estimates of HU in 2010 falls within the 2/3 projection interval, then the well as for the upper and lower bound. results would suggest less than ideal accuracy in terms of long-range projections. Alternatively, if greater than 2/3 of the ACS estimates of HU falls within the 2/3 Assessing at-risk populations. At-risk projected populations of sea-level rise projection interval, then the results would suggest an ideal amount of accuracy in under prescribed SLR scenarios were calculated using equation (6). terms of long-range projections. It should be noted in the consideration of these inputs that the ACS data, although similar to decennial data, is subject to many ! ! X types of error. Although all released ACS data have confidence limits above 90% t =X+ P t − ∗ t (ref. 60), the ‘true’ estimate from the ‘year structure built’ question cannot be PRij ij Aij (6) t 1 known. Our evaluation should be considered in lieu of the limitations of t 1 PR PR ij ij ACS accuracy. Supplementary Table 1 shows the number of ACS housing unit projections that where the population at risk of sea-level rise (PRt ) is equal to the population fall within the 2/3 projection interval. Overall, 68.1% of the 2010 estimates fell projected at time t (P t ) minus the sum of the previously impacted populations within the projection interval, suggesting an adequate degree of feasibility (PRt−1) multiplied by the land lost due to SLR (At ). We subtract out previously associated with these projections in the aggregate. Seven states greatly exceed the impacted populations to ensure populations are not double counted. We consider target 2/3 projection interval. Four states, however, fell far below the target 2/3 this approach a first-order, one-way interaction between population dynamics and projection interval—Massachusetts, Maine, Mississippi, and Rhode Island—with inundation modelling. Supplementary Fig. 1 demonstrates this first-order, one-way another eight states falling just below the target. interaction between population dynamics and SLR in four select counties. Projections inherently rely on historic trend data, and therefore performance Land lost due to SLR is calculated with a spatial overlay workflow in ArcGIS tends to suffer when growth deviates the greatest from historical patterns. 10.1 as one minus the percentage of land lost under the preceding amount of SLR, State-level aggregation might hide underlying geographic variability, and the that is, 0.3 m divided by 0 m, 0.6 m divided by 0.3 m, and so on. The first step in the variation in the projected exposure to SLR is heavily influenced by areas with the analysis was to use a base, 0 m MHHW layer, which was derived from NOAA’s 0 m greatest deviation in past population growth. To assess these patterns, we scenario, and used as the initial condition to calculate a base of dry land area considered the block-group-specific coefficient of variation. Panel A in contained within the geographies of 2010 CBGs. The resulting calculation is Supplementary Fig. 2 demonstrates the coefficient of variation for each block therefore a total area of dry land, without any distinction between habitable and group’s population projection model. We find that overall variation in projected uninhabitable dry land, available at present for human hab tation within each CBG populations is generally relatively low, with the greatest variation occurring in parts geography. Each subsequent scenario is expressed as the ratio of each scenario to of Louisiana, southern Texas, and inland North Carolina and Virginia. The Pacific the previous scenario. Coast also tends to have lower overall variation compared to the Gulf and Atlantic Next, we used the method developed for the US National Climate Assessment4 coasts. By comparison, if we assess the overall contribution to uncertainty in to determine the years SLR could be expected to exceed 0.3 m intervals. The projected populations in panel B of Supplementary Fig. 2 (the standard error), we following quadratic equation was used as the basis for calculating deterministic find most uncertainty in the Gulf Coast region, specifically from Mississippi curves for high (1.8 m) and medium (0.9 m) SLR scenarios at 2100: through South Florida. Three of the four states with greatest observed downward deviation in accuracy from the 66% interval show some of the lowest standard E(t)=at +bt 2 (7) errors, with Mississippi being the exception. The northeast states, including those that fall under the 66% threshold, nevertheless show low coefficients of variation. where E(t)= eustatic SLR, in metres, at time t; a= global linear trend SLR These results provide confidence that our overall small-area projections meet or constant of 0.0033 m yr−1; t = years since 2010; b=SLR acceleration coefficient exceed accepted feasibility standards for more standard projection geographies, and −2 −4 −5 (units of m yr ), with bhigh =1.86×10 ; bmedium =7.44 E ×10 . thus are well-suited for finer-grain assessments of future human hazard exposure. These curves were then used to find the years when SLR would exceed 0.3 m increments under the high (1.8 m) and medium (0.9 m) curves. These correspond to 2058, 2082 and 2100 for the medium curve (0.9 m) and 2045, 2061, 2073, 2083, References 2092 and 2100 for the high curve (1.8 m). With a recreation of NOAA’s hydrologic 32. Lam, N. S.-N., Arenas, H., Li, Z. & Liu, K.-B. An estimate of population connectedness approach for Louisiana at 0 m, 0.9 m and 1.8 m, we assessed impacted by climate change along the U. S. Coast. J. Coast. Res. 56, Louisiana’s population at 0.9 m intervals rather than 0.3 m intervals. This 1522–1526 (2009). corresponds to the years 2100 for the 0.9 m curve and 2073 and 2100 for the 33. Marcy, D. et al. in Proc. 2011 Solutions to Coastal Disasters Conference, 1.8 m curve. Anchorage, Alaska (eds Wallendorf, L. A., Jones, C., Ewing, L. & Battalio, B.) We explicitly do not migrate those who are projected to be at risk from SLR. 474–490 (American Society of Civil Engineers, 2011). Our current understanding of the human migratory response to environmental 34. FEMA Revised Procedure Memorandum No. 38—Implementation of events is not robust enough to model where these inundated persons will Floodplain Boundary Standard (Section 7 of MHIP V1.0) (2007); potentially move, or if they will move at all. There are several hypotheses on human http://www.fema.gov/media-library-data/1437593713238- migration and climate change, mostly drawing from environmental events in the cadcd346d3c4b9739304a26be5c12af7/Revised_PM_38_10_2007.pdf twentieth century14,52–55. These hypotheses, however, result in empirical migration 35. Swanson, D. A. & Tayman, J. Sub-national Population Estimates effects that are highly dependent on the type of environmental pressure. Drought, (Springer, 2012). flooding, tropical cyclones, and tsunamis all exhibit differing migration 36. Beaghen, M. & Stern, S. in Joint Statistical Meetings: Proc. Survey Research patterns56–58, with very little research suggesting the effect of SLR on human Methods 2123–2137 (American Statistical Association, 2009). migration systems14. Furthermore, very little research has been undertaken that 37. Baker, J., Alcantara, A., Ruan, X. M., Watkins, K. & Vasan, S. A comparative would be the bedrock of modelling who moves, where, and in what proportion55. evaluation of error and bias in census tract-level age/sex-specific population Will impacted populations migrate landwards? Could future coastal cities resemble estimates: component I (net-migration) vs component III (Hamilton–Perry). Venice, Italy, complete with populations still adapting to rising sea levels? Or will Popul. Res. Policy Rev. 32, 919–942 (2013). populations move to more land-locked cities for protection? These questions still 38. Deming, W. E. & Stephan, F. F. On a least squares adjustment of a sampled remain unanswered. For these reasons, our approach is strictly a model of the frequency table when the expected marginal totals are known. Ann. Math. Stat. confluence between two processes, SLR and population growth. Although this 11, 427–444 (1940). confluence implies a high level of societal impact (for example, coastal flood 39. Siegel, J. & Swanson, D. A. Methods and Materials of Demography 2nd edn protection, architectural adaptation, migration, and so on) in the most general (Emerald Group Publishing, 2008). sense, our approach here makes no prediction as to what the specific impacts will 40. Smith, S. K. & Cody, S. Evaluating the housing unit method: a case be in any particular location. study of 1990 population estimates in Florida. J. Am Plann. Assoc. 60, 209–221 (1994). Evaluation of projections. Projection intervals, produced through the use 41. Bogue, D. J. A technique for making extensive population estimates. J. Am. Stat. of a regression-based projection, allow us to determine the degree of feasibility in a Assoc. 45, 149–163 (1950). projection. Previous analyses have used the 2/3 (or 66%) projection interval to assess 42. Starsinic, D. E. & Zitter, M. Accuracy of the housing unit method in preparing the degree of accuracy in a population projection27,46 representing empirical ‘low’ population estimates for cities. Demography 5, 475–484 (1968). and ‘high’ scenarios from cohort-component projections59. The use of a 2/3 interval 43. Armstrong, J. S. Principles of Forecasting: A Handbook for Researchers and is ‘‘neither so wide as to be meaningless nor too narrow to be overly restrictive’’50. Practitioners (Springer, 2001). To assess the degree of feasibility, we assess all intervals on the 2008–2012 ACS 44. Wilson, T. New evaluations of simple models for small area population estimate of HU for each CBG in the study area. We produce projections based on forecasts. Popul. Space Place 21, 335–353 (2014).

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45. Cohen, J. E. Population forecasts and confidence intervals for Sweden: a 53. McLeman, R. A. Climate and Human Migration: Past Experiences, Future comparison of model-based and empirical approaches. Demography 23, Challenges (Cambridge Univ. Press, 2013). 105–126 (1986). 54. Gutmann, M. P. & Field, V. Katrina in historical context: environment and 46. Swanson, D. A. & Beck, D. M. A new short-term county population projection migration in the US. Popul. Environ. 31, 3–19 (2010). method. J. Econ. Soc. Meas. 20, 25–50 (1994). 55. Fussell, E., Curtis, K. J. & DeWaard, J. Recovery migration to the City of New 47. Swanson, D. A., Tayman, J. & Barr, C. F. A note on the measurement of accuracy Orleans after Hurricane Katrina: a migration systems approach. Popul. Environ. for subnational demographic estimates. Demography 37, 193–201 (2000). 35, 305–322 (2014). 48. Smith, S. K., Tayman, J. & Swanson, D. A. State and Local Population 56. Hunter, L. M., Murray, S. & Riosmena, F. Rainfall patterns and U. S. migration Projections: Methodology and Analysis (Plenum, 2001). from rural Mexico. Int. Migr. Rev. 47, 874–909 (2013). 49. Swanson, D. A., Tayman, J. & Bryan, T. MAPE-R: a rescaled measure of 57. Thiede, B. & Brown, D. Hurricane Katrina: who stayed and why? Popul. Res. accuracy for cross-sectional subnational population forecasts. J. Popul. Res. 28, Policy Rev. 32, 803–824 (2013). 225–243 (2011). 58. Kayastha, S. L. & Yadava, R. P. in Population Redistribution and 50. Swanson, D. A. & Tayman, J. Emerging Techniques in Applied Demography Development in South Asia (eds Kosiński, L. A. & Elahi, K. M.) 79–88 93–117 (Springer, 2015). (Springer, 1985). 51. Hyndman, R. J. & Athanasopoulos, G. Forecasting: Principles and Practice 59. Stoto, M. A. The accuracy of population projections. J. Am. Stat. Assoc. 78, (On Demand Publishing, LLC-Create Space, 2014). 13–20 (1983). 52. McLeman, R. A. & Hunter, L. M. Migration in the context of vulnerability and 60. Swanson, D. A. & Tayman, J. in Subnational Population Estimates Ch. 6 adaptation to climate change: insights from analogues. Wires Clim. Change 1, Vol. 31, Ch. 6 (Springer Series on Demographic Methods and Population 450–461 (2010). Analysis Vol. 31, 2012).

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Summary of the Editorial and Review Process

1. The author submits a manuscript and it receives a tracking number. 2. An editor is assigned to the manuscript. 3. The editorial team decides whether to send the manuscript out to review. If the decision is not to send the manuscript for review, the editor contacts the author with the decision. 4. The editor assigns potential reviewers to the manuscript and the author is notified. 5. Reviewers agree to review the manuscript. 6. Reviewers submit their reports to the editor. 7. The editorial team discusses the reports and the editor makes the final decision. 8. The editor contacts the author with the decision. 9. If the decision is negative the author is given the opportunity to transfer their manuscript to another journal. If the manuscript was peer reviewed the referee comments are also transferred. Please see our Manuscript Transfer FAQ for more information about this service.

Presubmission Inquiries

Researchers may request informal feedback from the editors on whether a potential manuscript may be appropriate for the journal. Presubmission inquiries are optional and should not be used to submit a full manuscript. If your manuscript is already written please proceed with a full formal submission. For a presubmission inquiry you may either submit summary files or enter pertinent information in the "Abstract" and "Manuscript Comment" text boxes. To expedite the process, it is not necessary to provide details of contributing authors. If you are invited to submit a full manuscript, the e -mail conveying our invitation will contain a link that will allow you to submit the manuscript files and other required information under the same tracking number.

Preparing Files for Submission

We strongly encourage all authors to read our brief guide to submission before submitting their manuscript. For initial submissions and most revisions, authors should submit the following files for consideration by the editorial team and the referees (if the paper is sent for external review):

1. Cover letter (this is optional and will not be accessible to the reviewers). 2. If the manuscript is a revision, a separate ‘response to referees’ letter that addresses the referees’ and editors comments in a point-by-point manner will be required. 3. The Nature Research Journals are flexible with regard to the format of initial submissions. Within reason, style and length will not influence consideration of a manuscript. To facilitate the review process we strongly encourage you to incorporate the manuscript text and figures into a single pdf or Microsoft Word file. Suitably high resolution figures may be inserted within the text at appropriate positions or grouped at the end. Each figure legend should be presented on the same page as its figure. The reference list should include article titles. If providing a pdf, please number all lines. If you upload a Word document the system will number the lines for you. We can accept LaTeX files at the acceptance stage, but before then please supply compiled PDFs. • Please be aware that authors of papers containing data from the life sciences are required to complete a reporting summary and an editorial policy checklist (and potentially other field-specific checklists if relevant) prior to external peer review. Failure to provide these forms in a timely fashion when requested may delay handling of the submission. The completed reporting summary and any field-specific checklists will be published with all accepted papers. More information can be found here. • Image data should be provided at sufficient resolution for reviewers to properly assess the data. If this is not possible in a combined manuscript file, authors should either submit separate high resolution figure files or (preferably) deposit image data in a suitable repository (e.g. figshare) and use their option to provide a private sharing link for the referees to access it.

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4. Supplementary information files, including copies of any related manuscripts under consideration at other journals. • Please submit supplementary figures small tables and text as a single combined PDF (with the pieces in the order: figures, tables, text). • Tables larger than one page (in general, >50 rows or >10 columns) should be provided as tabular data files rather than a PDF. • For optimal quality video files please use H.264 encoding, the standard aspect ratio of 16:9 (4:3 is second best) and do not compress the video. Videos should be submitted as avi, mov, mp4 or mpg files and will be rendered using the Brightcove video platform; for additional information please refer to this page. • Please keep individual file sizes below 50 MB unless a file must be larger.

Figures

Production-quality figures are not required at initial submission, but to avoid potential substantial revisions at later stages you may wish to note some of the guidelines below even at the initial submission stage.

It is recommended that you convert all your figures to JPEG before generating PDFs or uploading individual files. This will reduce the file sizes and the amount of time it takes the files to upload to our submission site and will also give you a closer approximation to the way your figures will appear on our site. If you choose to submit your files in PowerPoint format, please do not make a JPEG of these within PowerPoint. The conversion is more successful when a raw PowerPoint file is submitted.

General Figure Guidelines

• Use distinct colors with comparable visibility and consider colorblind individuals by avoiding the use of red and green for contrast. Recoloring primary data, such as fluorescence images, to color-safe combinations such as green and magenta, turquoise and red, yellow and blue or other accessible color palettes is strongly encouraged. Use of the rainbow color scale should be avoided. • Use solid color for filling objects and avoid hatch patterns. • Avoid background shading. • Figures divided into parts should be labeled with a lower-case, boldface 'a', 'b', etc in the top left-hand corner. Labeling of axes, keys and so on should be in 'sentence case' (first word capitalized only) with no full stop. Units must have a space between the number and the unit, and follow the nomenclature common to your field. • Commas should be used to separate thousands. • Unusual units or abbreviations should be spelled out in full, or defined in the legend.

Final Figure Submission Guidelines

Should your manuscript be accepted, you will receive more extensive instructions for final submission of display items. However, a summary of our guidelines for final figure preparation are included here.

• Images should be saved in RGB color mode at 300 dpi or higher resolution. • Use the same typeface (Arial, Helvetica or Times New Roman) for all figures. Use symbol font for Greek letters. • We prefer vector files with editable layers. Acceptable formats are: .ai, .eps, .pdf, .ps, .svg for fully editable vector -based art; layered .psd or .tiff for editable layered art; .psd, .tif, .jpeg or .png for bitmap images; .ppt if fully editable and without styling effects; ChemDraw (.cdx) for chemical structures. • Figures are best prepared at the size you would expect them to appear in print. At this size, the optimum font size is 7pt and no lines should be thinner than 0.25 pt (0.09 mm).

Starting the Process

To start the manuscript submission process, click on the 'Submit Manuscript' link on the ‘Home’ page. Authors may submit a manuscript in one of our standard formats.

Checking Your Manuscript Status

After submission you will receive an acknowledgement email. You can check the status of your manuscript at any time in the review process by:

1. Accessing the system with your password or link sent to you in the acknowledgement email. 2. Clicking on the link represented by your manuscript tracking number and abbreviated title. 3. Clicking on the "Check Status" link at the bottom of the displayed page

This procedure will display detailed tracking information about where your manuscript is in the submission/peer-review process.

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