UNIT 8: Fisheries assessments. 2 Fisheries data Why do we need fisheries data? FAO (2005): “Information is critical to EAF. It underpins the formulation.

Slides:



Advertisements
Similar presentations
Department of Fisheries Activities Specific to the SMMA Thomas Nelson Department of Fisheries Ministry of Agriculture, Lands, Forestry and Fisheries SAINT.
Advertisements

Indicators for ecosystem based management: Methods and applications Verena Trenkel, Anik BrindAmour, Pascal Lorance, Stéphanie Mahevas, Marie-Joëlle Rochet.
Stock Assessment for Central Southern Management Area (CSMA) Striped Bass Stocks Marine Fisheries Commission Business Meeting February 11, 2011.
UNIT 6b: SOLOMON ISLAND COASTAL FISHERIES. 2 Coastal fisheries Activity 6.1: Assess prior knowledge by class discussion of their understanding of coastal.
Issues in fisheries sustainability
Towards Healthy Stocks and Healthy Profits in European Fisheries Rainer Froese IFM-GEOMAR Presentation at Hearing „How much fish.
Stock assessment of red mullet and hake in the Egyptian Mediterranean Waters Sahar Mehanna Fish Population Dynamics Lab NIOF, Egypt.
UNIT 4: Ecosystem Approach to Fisheries Management - EAFM.
1 Ecological and Economic Considerations in Management of the U.S. Pacific sardine Fishery Samuel F. Herrick Jr NOAA Fisheries Southwest Fisheries Science.
UNIT 5: Fish biology.
Marine Fisheries Terms to Know Fishery – Refers to aspects of harvesting and managing aquatic organisms. Can refer specifically to a species being harvested,
How to manage a sustainable small scale artisanal fishery Erik Maitz Boman – Data monitoring officer Department of Agriculture and Fisheries.
Ecological Objective 3: Harvest of commercially exploited fish and shellfish Populations of selected commercially exploited fish and shellfish are within.
Descriptor 3 for determining Good Environmental Status (GES) under the MSFD was defined as “Populations of all commercially exploited fish and shellfish.
UNIT 2: Fisheries management. 2 Purpose of management Activity 2.1: Class views on what is fisheries management? What is fisheries management? “The application.
State of the Marine Environment Rainer Froese Leibniz Institute of Marine Sciences, Kiel IfM-GEOMAR
Queen Conch Experts Workshop Miami, United States of America, 22–24 May 2012 Paul Medley.
Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research The overlap between Science and Advice; the example of North Sea cod.
Status of lake trout in Lake Superior Shawn Sitar, MIDNR; Chuck Bronte, USFWS; Mark Ebener, CORA; Tom Fratt, RCFD; Ken Gebhardt, BMIC; Ted Halpern,
Stock assessment, fishery management systems, and the FMSP Tools -- Summary -- FMSP Stock Assessment Tools Training Workshop Bangladesh 19th - 25th September.
Trade of sharks listed in CITES Appendix ll Japan’s Practice on NDF Fisheries Agency of Japan.
Fiji Locally Managed Marine Area (LMMA) Network.
UNIT 9: An Ecosystem Approach to Fisheries Management Plan.
Population Dynamics Mortality, Growth, and More. Fish Growth Growth of fish is indeterminate Affected by: –Food abundance –Weather –Competition –Other.
Fishery Biology. Fisheries Management n Provide people with a sustained, high, and ever-increasing benefit from their use of aquatic resources n Problems.
Three Simple Rules for Ecosystem-Based Fisheries Management Rainer Froese GEOMAR, Kiel, Germany Presentation at the ICCAT workshop in Madrid, Spain, 9-11.
Scientific Observer Program Goals & Objectives Thanks to L. Chilton for initial development of this presentation.
UNIT 1: Threats to sustainable fisheries. 2 Internal threats Activity 1.1: List three (3) potential threats to fisheries. INTERNAL THREATS Overfishing.
PROGRESS REPORT 1 st SEMESTER (JANUARY – JULY 2014) THE ASSESSMENT ON BLUE SWIMMING CRABS (Portunus pelagicus (Linnaeus, 1758)) FISHERIES IN NORTH COAST.
Empirical and other stock assessment approaches FMSP Stock Assessment Tools Training Workshop Bangladesh 19 th - 25 th September 2005.
UNIT 10: Monitoring and Compliance. 2 Monitoring & compliance Activity 10.1: Class prior experience and local examples of compliance and monitoring activities.
STFA/SCCFA/CFMC Spiny Lobster Project David Olsen, STFA Josh Nowlis, Bridge Environment Daryl Bryan, STFA Funded by Caribbean Fishery Management Council.
Fisheries in the Seas Fish life cycles: Egg/sperm pelagic larvaejuvenile (first non-feeding – critical period – then feeding) (first non-feeding – critical.
Biostatistics: Sampling strategies Data collection for fisheries assessment: Monitoring and sampling strategies.
ALADYM (Age-Length Based Dynamic Model): a stochastic simulation tool to predict population dynamics and management scenarios using fishery-independent.
Summary of Atlantic Swordfish Species Working Group Discussion (see also SCI -021)
GIANNOULAKI M., SOMARAKIS S., MACHIAS A., SIAPATIS A., PAPACONSTANTINOU C. Hellenic Centre for Marine Research, PO Box 2214, Iraklion 71003, Greece Department.
The management of small pelagics. Comprise the 1/3 of the total world landings Comprise more than 50% of the total Mediterranean landings, while Two species,
Institute of Coastal Research Self management of vendace fishery, Bothnian Bay Teija Aho, Swedish Board of Fisheries Institute of Coastal Research, Öregrund,
USING INDICATORS OF STOCK STATUS WHEN TRADITIONAL REFERENCE POINTS ARE NOT AVAILABLE: EVALUATION AND APPLICATION TO SKIPJACK TUNA IN THE EASTERN PACIFIC.
Mrs Nafisat Bolatito IKENWEIWE (PhD) DEPARTMENT OF AQUACULTURE AND FISHERIES MANAGEMENT UNIVERSITY OF AGRICULTURE, ABEOKUTA FISH STOCK ASSESSMENT
Fisheries 101: Modeling and assessments to achieve sustainability Training Module July 2013.
Stock Assessment Methodologies for Reef Systems: A Joint Analyses
REVERSING ENVIRONMENTAL DEGRADATION TRENDS IN THE SOUTH CHINA SEA AND GULF OF THAILAND THE REGIONAL SYSTEM OF FISHERIES REFUGIA: MULTIPLE.
Unit 4 Data needs for fisheries management Peter Manning FAO Coastal Fisheries Policy and Planning Course, 28/01/08 – 8/02/08, Apia, Samoa Secretariat.
Management Procedures (Prof Ray Hilborn). Current Management Cycle Fishery: Actual Catches Data Collection Assessment Management Decision.
10. STEP 1: DEFINE & SCOPE Essential EAFM Date Place 10. Step 1: Define and scope the FMU Version 1.
Narrated by your classmates. Emptying the Oceans Describe why the old cliché that “there are always more fish in the sea is misleading” Define the terms:
1 Federal Research Centre for Fisheries Institute for Sea Fisheries, Hamburg Hans-Joachim Rätz Josep Lloret Institut de Ciències del Mar, Barcelona Long-term.
Management of the brown crab (Cancer pagurus) fishery in Ireland Oliver Tully Irish sea Fisheries Board (BIM)
Size Structure Dynamics
PARTICIPANTS NCMR (Responsible Institute), IMBC [Greece] IREPA[Italy] U. Barcelona, U. Basque, UPO[Spain] EFIMAS MEETING NICOSIA CRETE 2004 APRIL
Third Tuna Data Workshop (TDW-3) June 2009, Auckland, New Zealand Oceanic Fisheries Programme (OFP) Secretariat of the Pacific Community (SPC) SESSION.
Data requirement of stock assessment. Data used in stock assessments can be classified as fishery-dependent data or fishery-independent data. Fishery-dependent.
Day 4, Session 1 Abundance indices, CPUE, and CPUE standardisation
Training course in fish stock assessment and fisheries management
SAMPLING TECHNIQUES N. JAYAKUMAR Assistant professor Dept. of Fisheries Biology and Resource Management Fisheries college & Research Institute, Thoothukudi-8.
Population Dynamics and Stock Assessment of Red King Crab in Bristol Bay, Alaska Jie Zheng Alaska Department of Fish and Game Juneau, Alaska, USA.
Chang Ik Zhang Pukyong National University An integrated ecosystem-based approach for assessing and forecasting impacts of fisheries 2 nd YSRSC, Xiamen,
PRINCIPLES OF STOCK ASSESSMENT. Aims of stock assessment The overall aim of fisheries science is to provide information to managers on the state and life.
FISHING EFFORT & CPUE.
Rest of talk 6.
Regional artisanal data collection
The use of Data in Fisheries Management
Unit 4 Fisheries Planning
Towards improved stock assessments and management
What types of data do we need to collect
Progress in the implementation of RTMCF1 Action Plan.
13. Steps 3.1 & 3.2 Develop objectives, indicators and benchmarks
Regional artisanal data collection
Presentation transcript:

UNIT 8: Fisheries assessments

2 Fisheries data Why do we need fisheries data? FAO (2005): “Information is critical to EAF. It underpins the formulation of national policies, the development of management plans and the evaluation of management progress.” Fisheries information can be biological, ecological, economic, social or cultural. It can be documented or oral history. Fisheries information tells us about - Current fishery status - Fishery trends through time - Management effectiveness All information types should be used where possible (scientific data – traditional knowledge). But remember, we will always be lacking information!

3 Data in the Pacific Govan (2011): “ To date the financial costs of scientific research and monitoring appear to have far exceeded investments in actual management of coastal areas. Using locally available information with simple approaches to community monitoring is a cost effective solution, and collaboration with government or regional technical agencies for generating highly technical and specific information such as stock assessment, is another.” In the Pacific: Simple data collection approaches will generally be warranted. Need to identify approaches in consultation with stakeholders.

4 Data types Traditional knowledge/anecdotes - simplest form of data - needs stakeholder/community consultation - collect using interviews with community members, especially elders or through community meetings - need wider community involvement - issues and management needs can be determined by consensus

5 Data types Catch and effort data Catch = how much is caught (weight or numbers) Effort = how long fishing; how many fishers; how many nets; length of nets

6 Data types Catch and effort data Use these to calculate Catch per Unit Effort (CPUE) = a measure of relative abundance Examples: - number of sea cucmbers collected for every hour spent collecting them for each collector; - weight of a target species caught per hour of line fishing for each collector and each fishing line used For example: Catch (C) = 36 kg; Effort (E) = 6 hours; Fishers (F) = 2 CPUE = (C/E)/F = (36/6)/2 = 3 kg/fisher/hour

7 Data types Size data Measure weight and/or size of all fish caught (sub-sample) Can be done by fishers themselves, landing sites or at markets Calculate average size: Average fish length = 253/7 = cm Totals Fish # Fish length (cm)

8 Data types Underwater Visual Surveys (UVS) In-water (SCUBA or snorkel) surveys of fish/invertebrate numbers and/or habitats Can collect: Species numbers per area (density = relative abundance) and sizes Species diversity Habitat types and characteristics This approach requires training and is more resource intensive

9 UVC sample data sheet

10 Data types Biological samples Includes gonads and otoliths Determine sex, maturity, reproductive status, age & longevity Derive: Sex ratios Size/age at maturity Spawning seasonality Age structure Growth rates Mortality rates Longevity Collecting data of this type requires resources and training. Careful consideration of resources and management needs is required.

11 Data types Social/economic data Why fisheries benefit communities Can help ensure these benefits continue Data collected by interviews with community members Data types include: # of fishers, dependence on fisheries income derived from fishing % of total income derived from fishing profitability use of harvested fish fishers’ involvement in decision-making

12

13

14 Activity DVD: Second half of Module 1Second half of Module 1 Activity 8.1: Identify examples of different fisheries data, how collected and how used in fisheries management?

15 Use of CPUE Russ et al (2003) Apo Island,Philippines use of CPUE data

16 Use of size data Average fish size from local catches of grouper over an 11 year period. A 35 cm minimum size limit was introduced in 2005 after community concerns of fewer and smaller fish.

17 Use of UVS data Russ et al (2003) Apo Island, Philippines: use of UVS data

18 Indicators Indicators & reference points Many data types can be used as an Indicator An indicator will inform us about changes in the resource we are managing It will also inform how well particular objectives are being met Based on the objective the desirable level of the indicator should be identified. This is called the target reference level. Also, a level below which the indicator goes is undesirable should be identified. This is called the limit reference level. How well the indicator is perfomring against reference levels is called the performance measure

19 Indicators

20 Use of indicators An example of the use of UVS data at SPC workshop (see Box 13, SPC, 2010):

21 Other analyses There are many other more complex analyses that use fishery data to describe populations dynamics including: Growth Mortality Yield per recruit Biomass dynamic models Age structured models These methods require robust data on size, age and catch Should be used only in data- and resource-rich situations Photo: Dave Welch

22 Unit review Fisheries data are important to inform about: - Current fishery status - Fishery trends through time - Management effectiveness Collection of data should be dictated by resource capability - Simple approaches are often needed Indicators are the data we use to measure fisheries status and management perfromance There are many different data types:

23 Unit review

24 Assessments Activity 8.3: In two teams use simulated data to calculate some basic fisheries statistics. Report back on methods, results, and the relevance to management. DVD: Fish and People Module 5: Fish and people: today and tomorrow 15 minute personal review: unit review, students to review main concepts of unit in the course notes, contribute any new words (new to them) to their own personal glossary in the back of their notebook (local language equivalent terms should also be recorded where possible)

25 Homework Answer one of the following: 1.Describe a method that is used to assess a fishery that you are familiar with and explain how the information is used in management. Do you think it is effective, or do you think that there is a better way to do things? 2.If you had an unlimited amount of money, design a plan to collect data on a fishery you are familiar with. Once you have your plan, imagine that after a few years you lost the funding to collect all but one piece of the data-what one thing would you keep collecting and why?