South-West Pacific Node Training 12-16 November 2007

COMPONENT 2A - Project 2A2 Knowledge, monitoring, management and benefi cial use of coral reef ecosystems

April 2008

REEF MONITORING

SOUTH-WEST PACIFIC NODE TRAINING 12-16 NOVEMBER 2007

Author: Naushad YAKUB The CRISP programme is implemented as part of the policy developped by the Secretariat of the Pacifi c Regional Environment Programme for a contribution to conservation and sustainable development of coral reefs in the Pacifi c

he Initiative for the Protection and Management of Coral Reefs in the Pacifi c T (CRISP), sponsored by France and prepared by the French Development Agency (AFD) as part of an inter-ministerial project from 2002 onwards, aims to develop a vision for the future of these unique eco-systems and the communities that depend on them and to introduce strategies and projects to conserve their biodiversity, while developing the economic and environmental services that they provide both locally and globally. Also, it is designed as a factor for integration between developed countries (Australia, New Zealand, Japan and USA), French overseas territories and Pacifi c Island developing countries.

The CRISP Programme comprises three major components, which are:

Component 1A: Integrated Coastal Management and Watershed Management - 1A1: Marine biodiversity conservation planning - 1A2: Marine Protected Areas - 1A3: Institutional strengthening and networking - 1A4: Integrated coastal reef zone and watershed management CRISP Coordinating Unit (CCU) Component 2: Development of Coral Ecosystems Programme manager: Eric CLUA - 2A: Knowledge, monitoring and management of coral reef ecosytems SPC - PO Box D5 - 2B: Reef rehabilitation 98848 Noumea Cedex - 2C: Development of active marine substances New Caledonia - 2D: Development of regional data base (ReefBase Pacifi c) Tel.: (687) 26 54 71 Component 3: Programme Coordination and Development E-mail: [email protected] - 3A: Capitalisation, value-adding and extension of CRISP Programme activities www.crisponline.net - 3B: Coordination, promotion and development of CRISP Programme

COMPONENT2A Knowledge, monitoring and management of coral reef ecosytems

 PROJECT 2A-1: Postlarvae (fi sh and crustacean) capture and culture for aquarium trade and restoking  PROJECT 2A-2: Improvement of knowledge and capacity for a better management of reef ecosystems  PROJECT 2A-3: Synopsis and extension work on indicators for monitoring the health of co- CRISP contact person: ral ecosystems and developing a remote sensing tool Ken McKAY School of Marine Studies  PROJECT 2A-4: Faculty of Islands and Oceans Testing of novel information feedback methods for local communities and The University of the South Pacifi c users of reef and lagoon resources Suva, Fiji Tel.: (679) 3 232 612  PROJECT 2A-5: Fax: (679) 3 231 526 Specifi c studies on i) the eff ects on the increase in atmospheric CO2 on the E-mail: [email protected] health of coral formation and ii) the development of ecotourism

This CRISP component is funded by the following agency: Objectives The GCRMN South West Pacific Node includes 7 countries: Fiji Islands, Solomon Islands, Vanuatu, New Caledonia, Nauru, Samoa and Tuvalu. However countries present were Solomon Islands, Western Samoa, Vanuatu and Fiji Islands. The objectives of this training were to: 1. Train GCRMN country coordinators to analyze data using Ms-Excel with appropriate templates 2. Train the GCRMN South West Pacific Node Country Coordinators on setting up a coral reef monitoring database using Ms-Access

1 Day 1 – 12th November 2007

A brief session was conducted on techniques used by the present coordinators of South West Pacific Node for GCRMN.

Solomon Islands This technique was introduced in Solomon Islands in 2004 that was adapted from Indonesia. This method was called PIX (point intercept transect with X) for the sake of this training only to differentiate between other techniques used by other SW node countries. This technique uses: 1. 50m transect with X shaped aluminum bars (70cm length) screwed at center at every 1m 2. 50m x 5pts (from X shaped bar) = 250 pts per transect 3. 5 divers: a. 1 lays tape b. 2 benthic cover to life-form category c. 3 & 4 UVC (underwater visual census) to fish species using own fish species list. d. 5 invertebrates. Invertebrates are collected at 2 depths as well except for sea cucumbers the depth is 25m. 4. Depth 5 and 10 m 5. Permanent monitoring sites, total of 32 6. Data is tallied as total life-form category per transect 7. Analysis – summary of tallied points with mean, standard deviation and standard error. However this method is adopted well but analysis is difficult as there has been no training conducted for proper data analysis. The representatives are willing to adapt to the modified GCRMN ReefCheck techniques as conducted by Vanuatu and Fiji Islands.

X X X X X 1m 2m 50m

2 Figure 1 50m transect with X Western Samoa The method was modified by the trainees in the last GCRMN Train the Trainers Workshop held in 2003 in Fiji Islands. This technique uses PIT: 1. 50m transect at every 2m interval – 25 points per transect 2. 1.5m on each side of transect 3. 3 divers a. 1 - 1.5m from transect on left b. 2 - in center c. 3 - 1.5 from transect on right 4. Depth is 5m maximum 5. Snorkel surveys 6. Back reef and Reef flat Samoa collects fish and invertebrate data to family level with target fish collected to species level.

Diver 1

1.5m Diver 2

Diver 3

Figure 2

The above illustration shows the method in which Samoa collects data for benthic life-form categories.

Vanuatu and Fiji Islands These 2 countries use the Reef Check method as depicted in the figures below adapted from the Reef Check Training manual.

Figure 3

The transect is 100m long with 4 by 20m transects with 5m gap in between transects, however the method is PIT as well.

Figure 4

Fish (attached as fish species list) and invertebrates’ data are collected to Reef Check indicator families with abundance. However it was suggested if atleast fish data could be collected with length estimates to calculate biomass for family or species.

Day 3 – 13th November 2007 This day started with a brief follow-up from yesterday’s session where different techniques used to collect substrate, fish and invertebrate data was discussed with clear portrait of techniques used.

Coral data analysis was introduced using different life-form categories adapted from the Australian Institute of Marine Science (AIMS) as part of GCRMN reporting. However Vanuatu uses Reef Check categories while Fiji uses both GCRMN and Reef Check which is interchangeable.

Sample coral data template was shown with different life-form categories and health status as bleached (B), lives (L) and partly bleached (PB). In addition data filtering, sorting and checking for typo errors was shown as well. This data was analyzed using pivot table and appropriate graphs were plotted. The formatting of graphs with title, customize legends, fonts and colors was also shown. For example data was analyzed for each site for total life-form category and health.

5 Figure 5 Example of Coral data template

Figure 6 Pivot Table showing count of benthic versus site code

6 Figure 7 Graph created from pivot table showing count of benthic vs site code The templates were created for Solomon Islands and Samoa for data entry and these templates were used to analyze data country specific data. The column headings were date, site code, transect, benthic code and health. The resulting graphs were easy to interpret and can easily adapted to GCRMN reporting requirements. The Solomon Islands template is illustrated below (figure 8) whereby all data inclusive all transects and sites were entered in a single excel spreadsheet for easy analysis.

Figure 8 The day finished with a brief introduction to database with importing excel spreadsheets, linking tables, creating and running queries. However the participants showed negative response due to uncertainty on liking tables and creating queries.

Day 4 – 14th November 2007 After the brief follow-up from yesterday’s session, fish data template was introduced. Each column with appropriate headings: date, site code, transect, species, family, abundance, a & b values, biomass per species and total biomass.

Figure 9 Fish data template with column showing calculation of biomass.

Pivot table was used for data analysis and plotting of graphs. Each country used this template by exporting their data and graphs were plotted. A brief was given on calculating the species richness which is simply the number in the unit of study. A standardized list was developed to accomplish GCRMN requirements for each country in the Southwest Pacific Node: • Percentage substrate cover per site per country o Solomon Islands % cover = life-form group x 100 1000 8 • Samoa % cover = life-form group x100 390 o Vanuatu and Fiji Islands – Reef Check graph which is created automatically due to excel template created by Reef Check • Time series percentage hard coral and algae cover with standard deviations for each country • Abundance and/or biomass data for fish and invertebrates depending on each country’s requirements

Figure 10 Pivot table showing total abundance of fish per species per site

Figure 11 Graphs showing fish abundance per species per site

Moreover, a standardized list of coral life-form categories matching with Reef Check categories was developed in relation to consistence data for Vanuatu and Fiji Islands. The list is as follows: Samoa, Solomon Islands & Fiji Islands Vanuatu & Fiji Islands Acropora OT Hard Coral OT Non- Acropora Bleaching Hard Coral Hard coral bleaching Soft Coral Soft Coral Soft coral bleaching Algae (DCA & CA) Nutrient indicator algae Abiotic RC, SD, RB, SI Sponge Sponge

10 DC RKC

Finally the group developed fish species list with a & b values according to their needs; Solomon Islands, species and families; Samoa mostly family with few species and Vanuatu and Fiji Islands families only due to Reef Check indicator list. This list is adapted from Kulbicki et al 2005; and the participants are given a copy each.

Solomon Islands Sci Name Family Code a b Acanthurus spp Acanthuridae Acanthurus spp 0.034 2.866 Acanthurus pyroferus Acanthuridae Acpyr 0.028 2.983 Acanthurus albipectoralis Acanthuridae Acalb 0.028 2.983 Acanthurus auranticavus Acanthuridae Acaur 0.028 2.983 Acanthurus blochii Acanthuridae Acblo 0.025 3.032 Acanthurus dussumieri Acanthuridae Acdus 0.043 2.868 Acanthurus lineatus Acanthuridae Aclin 0.028 2.983 Acanthurus nigrofuscus Acanthuridae Acnig 0.026 3.028 Acanthurus triostegus Acanthuridae Actri 0.083 2.570 Acanthurus xanthopterus Acanthuridae Acxan 0.027 2.984 Anyperodon leucogrammicus Serranidae Anleu 0.001 3.548 Balistidae Balistidae Balis 0.006 3.393 Bolbometopan muricatum Scaridae Bmur 0.022 2.971 Caranx ignoblis Carangidae Caign 0.008 3.197 Caranx lugubris Carangidae Calug 0.016 3.059 Caranx melampygus Carangidae Camel 0.020 2.986 Caranx sexfasiatus Carangidae Casex 0.023 2.918 Casionidae Caeionidae Cason 0.020 2.986 Cephalopholis argus Serranidae Cearg 0.009 3.278 Cephalopholis boenak Serranidae Ceboe 0.009 3.181 Cephalopholis cyanostigma Serranidae Cecyn 0.015 3.019 Cephalopholis miniata Serranidae Cemin 0.012 3.109 Cephalopholis sexmaculata Serranidae Cesex 0.011 3.114 Cephalopholis urodeta Serranidae Ceuro 0.012 3.109 Cetoscarus bicolor Scaridae Cebic 0.028 2.818 Cheilinus fasiatus Labridae Chfas 0.022 2.971 Cheilinus triobulatus Labridae Chtri 0.016 3.058 Cheilinus undulatus Labridae Chund 0.016 3.059 Chlororus bleekeri Scaridae Chble 0.011 3.136 Chlororus sordidus Scaridae Chsor 0.024 2.969 Chlorurus microrhinos Scaridae Cmic 0.024 2.969 Cromileptes altivelis Serranidae Calt 0.024 2.969 Ctenochaetus striatus Acanthuridae Ctstr 0.096 2.489 Diagramma pictum Haemulidae Dipic 0.023 3.063 Diotontidae Diotontidae Dioto 0.014 2.988 Epinephelus fuscogutattus Serranidae Efus 0.068 2.784 Epinephelus hexagonattus Serranidae Ehex 0.013 3.057 11 Epinephelus maculatus Serranidae Emac 0.012 3.053 Epinephelus merra Serranidae Emer 0.011 3.062 Epinephelus ongus Serranidae Eong 0.016 2.966 Epinephelus polypekaidon Serranidae Epol 0.019 2.928 Ganthodentext aureolineatus Lethrinidae Gaur 0.008 3.166 Gymnocranius grandoculis Lethrinidae Ggra 0.018 3.063 Hipposcarus loniceps Scaridae Hlon 0.032 2.885 Lethrinus erythracanthus Lethrinidae Leery 0.022 2.898 Lethrinus genivittatus Lethrinidae Legen 0.023 2.956 Lethrinus harak Lethrinidae Lehar 0.011 3.178 Lethrinus olivaceous Lethrinidae Leoli 0.017 3.043 Lethrinus ornatus Lethrinidae Leorn 0.017 3.043 Lutjanus adetii Lutjanidae Lutade 0.018 2.995 Lutjanus argentimaculatus Lutjanidae Lutarg 0.017 3.042 Lutjanus bohar Lutjanidae Lutboh 0.029 2.851 Lutjanus bohar Lutjanidae Lutboh 0.017 3.043 Lutjanus fulviflamma Lutjanidae Lutfulvifla 0.017 3.022 Lutjanus fulvus Lutjanidae Lutfulv 0.007 3.261 Lutjanus gibbus Lutjanidae Lutgib 0.028 2.844 Lutjanus kasmira Lutjanidae Lutkas 0.016 3.059 Lutjanus lutjanus Lutjanidae Lutlutj 0.021 2.960 Lutjanus quinquelineatus Lutjanidae Lutqui 0.021 2.974 Lutjanus sebae Lutjanidae Lutuseb 0.013 3.138 Lutjanus semicinctus Lutjanidae Lutsem 0.008 3.247 Macolor macualris Lutjanidae mmac 0.018 2.969 Macolor niger Lutjanidae mnig 0.015 3.100 Monotaxis grandoculis Lethrinidae Mogra 0.012 3.152 Naso Hexacanthsu Acanthuridae Nahex 0.004 3.428 Naso liutratus Acanthuridae Naliu 0.017 3.022 Naso vlamingii Acanthuridae Navla 0.017 3.022 Ostracidae Ostracidae Ostra 0.023 3.022 Paracanthurus hepatus Acanthuridae Pahep 0.010 3.224 Parupenes barberinoides Mullidae Parinoides 0.020 2.956 Parupenes barberinus Mullidae Parinus 0.009 3.250 Parupenes bifasiatus Mullidae Pabif 0.009 3.250 Parupenes indicus Mullidae Paind 0.085 2.577 Parupenes multifasiatus Mullidae Pamul 0.030 2.946 Plectorhinchus chaetodontoides Haemulidae Plcha 0.015 3.130 Plectorhinchus gibbosus Haemulidae Plgib 0.013 3.122 Plectorhinchus lessoni Haemulidae Plles 0.015 3.122 Plectorhinchus lineatus Haemulidae Pllin 0.014 3.114 Plectorhinchus obscrum Haemulidae Plobs 0.011 3.211 Plectorhinchus orientalis Haemulidae Plori 0.017 3.040 Plectorhinchus orientalis Haemulidae Plori 0.023 2.962 Plectorhinchus picus Haemulidae Plpic 0.020 2.969 Plectropomus areolatus Serranidae Plare 0.013 3.079 Plectropomus laevis Serranidae Plae 0.027 2.885 Plectropomus leopardus Serranidae Pleo 0.020 2.969 Plectropomus maculatus Serranidae Pmac 0.012 3.089 Plectropomus oligocanthus Serranidae Poli 0.011 3.086 12 Pomacanthidae Pomacanthidae Po-canthidae 0.006 3.238 Pomacentridae Pomacentridae Po-centridae 0.012 3.060 Scarus altipinnis Scaridae Salt 0.018 3.029 Scarus chameleon Scaridae Scha 0.023 2.956 Scarus dimidiatus Scaridae Sdim 0.023 2.956 Scarus flavipectoralis Scaridae Sfla 0.023 2.956 Scarus forsteni Scaridae Sfor 0.023 2.956 Scarus frenatus Scaridae Sfre 0.023 2.956 Scarus ghobban Scaridae Sgho 0.017 3.041 Scarus globiceps Scaridae Sglo 0.023 2.956 Scarus longipinns Scaridae Slon 0.023 2.956 Scarus niger Scaridae Snig 0.013 3.160 Scarus oviceps Scaridae Sovi 0.023 2.956 Scarus ruboviolaceus Scaridae Srub 0.023 2.956 Scarus spinus Siganidae Sspi 0.023 2.956 Siganus argentues Siganidae Siarg 0.011 3.154 Siganus canaliculatus Siganidae Sican 0.015 3.122 Siganus corallinus Siganidae Sicor 0.002 3.821 Siganus doliatus Siganidae Sidol 0.010 3.272 Siganus javus Siganidae Sijav 0.015 3.122 Siganus lineatus Siganidae Silin 0.022 2.998 Siganus puellus Siganidae Sipue 0.018 3.028 Siganus vulpinus Siganidae Sivul 0.014 3.122 Variola louti Serranidae Vlou 0.012 3.079 Zebrasoma veliferum Acanthuridae Zvel 0.034 2.866 Samoa Sci Name Family Code a b Pomacentridae Pomacentridae Damselfish 0.021 3.191 Pomacantridae Pomacantridae Angelfish 0.058 2.718 Lethrinidae Lethrinidae Emperor 0.017 3.040 Mullidae Mullidae Goatfish 0.010 3.224 Upeneus vittatus Mullidae Striped Goatfish 0.007 3.354 Holocentridae Holocentridae Soldierfish 0.022 3.059 Carangidae Carangidae Jacks & Trevally 0.008 3.197 Caranx ignobilis Carangidae Giant Trevally 0.016 3.059 Caranx melampygus Carangidae Bluefin Trevally 0.023 2.918 Selar crumenopthalmus Carangidae Bigeye scad 0.010 3.194 Ballistidae Ballistidae Triggerfish 0.006 3.393 Balistapus undulatus Ballistidae Orangelined triggerfish 0.006 3.393 Rhinecanthus verrucosus Ballistidae Blackpatch triggerfish 0.006 3.393 Acanthuridae Acanthuridae Surgeon,unicornis,tangs 0.030 2.946 Acanthurus lineatus Acanthuridae Striped Surgeonfish 0.028 2.983 Ctenochaetus striatus Acanthuridae Lined Bristletooth 0.023 3.063 Acanthurus xanthopterus Acanthuridae Yellowfin 0.027 2.984 Acanthurus triostegus Acanthuridae Convic t 0.083 2.570 Naso unicornis Acanthuridae Bluespine Unicornfish 0.018 3.035 Naso lituratus Acanthuridae Orangespine Unicornfish 0.009 3.250 Sphyraenidae Sphyraenidae Barracuda 0.006 3.013 Sphyraena barracuda Sphyraenidae Great barracuda 0.006 3.011

13 Chanos chanos Chanidae Milkfish 0.005 3.389 Vanuatu & Fiji Islands - Reef Check Sci Name Family Code a b Butterflyfish ChaetodontidaeChae todontidae 0.042 2.847 Sweetlips Haemulidae Haemulidae 0.022 2.898 Grouper Serranidae Serranidae 0.013 3.031 Snapper Lutjanidae Lutjanidae 0.023 2.886 Parrotfish Scaridae Scaridae 0.022 2.971 Moray Eel Muraenidae Muraenidae 0.005 2.614 Barramundi Cod Serranidae Cromileptes altivelis 0.096 2.489 Humphead Wrasse Labridae Cheilinus undulatus 0.011 3.136 Bumphead Parrotfish Scaridae Bolbometopon muricatum 0.018 3.045 Rabbitfish Siganidae Siganidae 0.015 3.122 Surgeonfish,unicornis,tangs Acanthuridae Acanthuridae 0.030 2.946

Recommendations: • Integrate modified GCRMN technique at 0.5m with PIX method with cent er of X bar as a life-form category for GCRMN for Solomon Islands • To record health of coral on each 0.5m as B (bleached), PB (partly bleached) and L (Live). This would standardize the GCRMN method and show a picture of coral health as well for resiliency. • Ms-Excel is preferred due to easy m anipulation and use of pivot table f or data analysis and graphs. • A guideline needs to be prepared for data entry, sorting, pivot table and graphs especially with graph labels and other formatting. • To collect fish fork-length parameter for calculation of biomass either to species or families level. • A central database is only possible if the node countries could standard ize the methodology, however, at present different countries are using different methods and will require separate database due to variability in methodology. • The highly recommended method is using a 50m transect at 0.5m gives 100 points which gives percentage cover of life-form categories, life-form category x 100, 100