Contents lists available at ScienceDirect Journal of Experimental Marine Biology and Ecology journal homepage: www.elsevier.com/locate/jembe Kelp-beddynamicsacrossscales:Enhancingmappingcapabilitywithremote sensing and GIS Anne P. St-Pierre ⁎ , Patrick Gagnon Department of Ocean Sciences, Ocean Sciences Centre, Memorial University of Newfoundland, 0 Marine Lab Road, St. John's, Newfoundland and Labrador A1C 5S7, Canada ARTICLEINFO Keywords: Kelp bed Urchin barrens Remote sensing Geographic information system (GIS) Aerial and satellite imagery Benthic monitoring ABSTRACT Kelp are important drivers of productivity and biodiversity patterns in cold-water and nutrient-rich rocky reefs. Scuba-andboat-basedmethodsareroutinelyusedtostudysubmergedkelpbeds.However,thesetime-consuming and labor-intensive methods enable monitoring of beds or the factors and processes that control their distribution over only small spatial (few 100s of m 2 ) and temporal (<5years) scales. Remote sensing and geographic in- formation system (GIS) technologies are increasingly used to compare marine species distribution over multiple spatiotemporalscales.However,thereiscurrentlynoclearframeworkandlimiteddemonstrationoftheirpotential for studies of broad-scale changes in completely submerged kelp beds. The present study aims to establish the foundation of a simple, accessible, and robust set of remote sensing and GIS-based methods to address key questionsaboutthestabilityofsubtidalkelpbedsacrossmultiplespatialandtemporalscales.Itteststhesuitability ofconventionalimageclassificationmethodsformappingkelpfromdigitalaerial(acquiredonboardahelicopter) andsatellite(SPOT7)imageryof~250haofseabedaroundfourislandsintheMinganArchipelago(northernGulf ofSt.Lawrence,Canada).Threeclassificationmethodsarecompared:1)asoftware-ledunsupervisedclassification in which pixels are grouped into clusters based on similarity in spectral signature among pixels; 2) a software-led supervised classification in which pixels are assigned to categories based on similarity in the spectral signature of pixelsandthatofreferencedatafromeachcategory;and3)avisualclassificationcarriedoutbyatrainedobserver. Supervised classification of satellite imagery and visual classification of aerial imagery were the top methods to map kelp, with overall accuracies of 89% and 90%, respectively. Unsupervised classification of both types of imagery showed poor discrimination between kelp and non-kelp benthic classes. Kelp bed edges were more dif- ficulttoidentifyonsatellitethanaerialimagerybecausetheformerpresentedpoorercontrastsandalowerspatial resolution. Kelp bed edges identified with visual classification appeared artificially jagged for both types of ima- gery,mainlybecauseofthecoarse(225-m 2 )spatialunitsusedforthisclassification.Kelpbededgesweresmoother on maps created with the unsupervised and supervised classifications, which used 1-m-pixel images. The present study demonstrates that conventional remote sensing and GIS methods can accurately map submerged kelp beds over large spatial domains in the Mingan Archipelago or in other benthic systems with similar oceanic conditions and a largely dichotomous (kelp-barrens) biological makeup. 1. Introduction Kelp (large brown seaweeds of the order Laminariales) are key dri- versofproductivityandbiodiversitypatternsincold-waterandnutrient- rich,shallowrockyreefs(Dayton,1985; TegnerandDayton,2000).Kelp typically form structurally complex aggregates, known as kelp beds or forests, which provide critical habitat to a variety of fish and in- vertebrates (Estes et al., 2004; Ling, 2008; Steneck et al., 2002). Worldwide, large-scale shifts from kelp-dominated to urchin-dominated community states have occurred following increases in the intensity of urchin grazing on kelp, or as a result of climate-driven shifts in species distribution (Lingetal.,2015; Stenecketal.,2002; Vásquezetal.,2007; Wernberg et al., 2016). Although these shifts between community states affect 10s to 100s of km 2 of coastal habitats (Filbee-Dexter and Scheibling, 2014; Krumhansletal.,2016; MoyandChristie,2012),most studies of subtidal kelp systems, including distributional aspects, have been conducted over small spatial (few hundreds of meters) and tem- poral(lessthanfiveyears)scalesmainlybecauseofthelimitationsofthe time-consuming and labor-intensive scuba techniques typically em- ployed (Gagnon et al., 2004; Lauzon-Guay and Scheibling, 2007; https://doi.org/10.1016/j.jembe.2019.151246 Received 5 May 2019; Received in revised form 4 September 2019; Accepted 3 October 2019 ⁎ Corresponding author. E-mail address: apsp66@mun.ca (A.P. St-Pierre). Journal of Experimental Marine Biology and Ecology 522 (2020) 151246 0022-0981/ © 2019 Elsevier B.V. All rights reserved. T