Assessing hotspots within hotspots to conserve biodiversity and support fisheries management

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1 The following supplement accompanies the article Assessing hotspots within hotspots to conserve biodiversity and support fisheries management Mara Schmiing *, Hugo Diogo, Ricardo Serrão Santos, Pedro Afonso Centre of IMAR/Department of Oceanography and Fisheries of the University of the Azores, LARSyS Associated Laboratory, Rua Prof. Doutor Frederico Machado 4, Horta (Azores), Portugal *Corresponding author: Marine Ecology Progress Series 513: (2014) Supplement. Overview of species sighted in underwater visual censuses (Table S1). Additional results from statistical modelling: frequency distributions of the predictions of four biodiversity indices (Fig. S1); estimated smooth functions of four environmental variables to model biodiversity indices and the intrinsic vulnerability index (Fig. S2); map of the predicted spatial distribution of the Simpson diversity (Fig. S3) Table S1. Summary of sighted fish species, including their habitat characteristics (B: benthic, BP: benthopelagic, P: pelagic), trophic ecology (Car: carnivore, Her: herbivore, Omn: omnivore, Pla: planktivore), commercial interest (C: commercial, NC: non-commercial), intrinsic vulnerability index (IVUL) and relative frequency of occurrence for 2 islands of the Azores archipelago. The IVUL was taken from Cheung et al. (2007) and FishBase (marked with *; Froese & Pauly 2013). Mugilidae spp. include unidentifed Chelon labrosus or Liza aurata, Pagellus spp. include unidentified P. acarne or P. bogaraveo, and Seriola spp. include unidentified S. dumerilii or S. rivoliana Family Species Habitat Trophic Commercial IVUL Frequency ecology interest (%) Apogonidae Apogon imberbis B Car NC 15* 1.9 Belonidae Belone belone P Car NC 39* 0.6 Blastidae Balistes capriscus BP Car C Blenniidae Ophioblennius atlanticus B Her NC 30* 8.4 Parablennius ruber B Omn NC 23* 2.2 Bothidae Bothus podas B Car NC 51* 13.4 Carangidae Caranx crysos BP Car C Pseudocaranx dentex BP Car C Seriola dumerilii P Car C Seriola rivoliana P Car C 72* 2.8 Seriola spp. P Car C Trachinotus ovatus P Car NC 38* 6.5 Trachurus picturatus P Pla C Clupeidae Sardina pilchardus P Pla C Congridae Paraconger macrops B Car NC 38* 0.4 Dasyatidae Dasyatis pastinaca B Car NC Taeniura grabata B Car NC 79* 0.6 Kyphosidae Kyphosus spp. BP Her C Labridae Bodianus scrofa B Car C 47* 12.6 Coris julis B Car NC 60* 78.4 Labrus bergylta B Car C Labrus mixtus B Car C

2 Symphodus caeruleus B Car NC 37* 28.4 Symphodus mediterraneus B Car NC 23* 7.4 Thalassoma pavo B Car NC 40* 82.9 Xyrichthys novacula B Car NC 36* 1.1 Mugilidae Chelon labrosus BP Omn NC Liza aurata BP Omn NC 50* 0.9 Mugilidae spp. BP Omn NC Mullidae Mullus surmuletus B Car NC Muraenidae Gymnothorax unicolar B Car C 50* 1.5 Muraena augusti B Car C 61* 2.4 Muraena helena B Car C 74* 1.1 Myliobatidae Myliobatis aquila B Car NC 59* 0.9 Phycidae Phycis phycis B Car C Pomacentridae Abudefduf luridus B Omn NC 26* 54.5 Chromis limbata BP Pla NC 28* 69.0 Pomatomidae Pomatomus saltatrix BP Car C Scaridae Sparisoma cretense B Her C Scombridae Sarda sarda P Car C Scomber colias P Pla C Scorpaenidae Scorpaena maderensis B Car NC Scorpaena scrofa B Car C Serranidae Anthias anthias BP Car NC 38* 7.6 Epinephelus marginatus B Car C Mycteroperca fusca B Car C 58* 5.6 Serranus atricauda B Car C 61* 71.6 Sparidae Boops boops BP Pla NC Diplodus sargus B Omn C Diplodus vulgaris B Omn C Pagellus acarne BP Pla C Pagellus bogaraveo BP Pla C Pagellus spp. BP Pla C Pagrus pagrus B Car C 41* 9.7 Sarpa salpa B Her NC Sphyraenidae Sphyraena viridensis P Car C Synodontidae Synodus saurus B Car NC 31* 6.5 Tetraodontidae Sphoeroides marmoratus B Omn NC Triakidae Galeorhinus galeus BP Car C Tripterygiidae Tripterygion delaisi B Car NC 14* 0.6 2

3 Fig. S1. Frequency distribution of predictions of (A) species richness, (B) Shannon index, (C) Simpson diversity and (D) taxonomic distinctness. The tick marks on the x-axes indicate calculated predicted values. Predictions were divided into 3 classes using Jenks optimisation (natural breaks, dashed lines). High biodiversity was defined to be within the range of the highest class 3

4 Fig. S2. Estimated smooth functions (s(x)) and 95% confidence band (grey shaded area) of the environmental variables depth, distance to sediment (Dsed), exposure to current and swell to model 4 biodiversity indices and the intrinsic vulnerability index (IVUL) of shallow fish assemblages. Note that taxonomic distinctness and the IVUL were modelled with a gamma distribution using the inverse link function and thus the shown relations are inverted. NS: variable not significant 4

5 Fig. S3. Predicted spatial distribution of the Simpson diversity (1 D) of coastal fishes (subtidal habitat down to 40 m depth), in relation to the boundaries of the existing marine protected area network (black rectangles) in 2 islands of the Azores archipelago. The outline of the rocky substrate is shown as a black contour LITERATURE CITED Cheung WWL, Watson R, Morato T, Pitcher TJ, Pauly D (2007) Intrinsic vulnerability in the global fish catch. Mar Ecol Prog Ser 333:1 12 Froese R, Pauly D (2013) FishBase. (accessed on 13 June 2013) 5