Designing Networks of Marine Protected Areas in DFOs Three Atlantic - - PowerPoint PPT Presentation

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Designing Networks of Marine Protected Areas in DFOs Three Atlantic - - PowerPoint PPT Presentation

Designing Networks of Marine Protected Areas in DFOs Three Atlantic Bioregions Presentation for Indigenous Protected Areas Workshop Max Westhead, DFO and Adrian Gerhartz-Abraham, Dalhousie March 29, 2017 Outline 1 . Setting the Stage for


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Designing Networks of Marine Protected Areas in DFO’s Three Atlantic Bioregions

Presentation for Indigenous Protected Areas Workshop

Max Westhead, DFO and Adrian Gerhartz-Abraham, Dalhousie

March 29, 2017

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Outline

  • 1. Setting the Stage for MPA Network Design
  • 2. MPA Network Design Analysis
  • 3. Timelines and Opportunities
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Bioregions

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Challenge

  • In each bioregion, use the extensive amount
  • f available ecological and human-use data

to design a comprehensive, resilient, and representative network of marine protected areas

  • Respect existing rights and activities
  • Meet conservation goals while minimizing

potential socio-economic impacts

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Part 1: Setting the Stage

  • A structured process is needed for consistency

across bioregions

  • Objectives hierarchy:

» National Goals »Strategic Objectives »Conservation Priorities »Design Strategies (Targets)

Broad Specific

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National Goals

High-level statements that outline what the National MPA Network aims to achieve:

1) To provide long-term protection of marine biodiversity, ecosystem function and special natural features. 2) To support the conservation and management of Canada's living marine resources and their habitats, and the socio-economic values and ecosystem services they provide. 3) To enhance public awareness and appreciation of Canada's marine environments and rich maritime history and culture.

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Objectives hierarchy:

»National Goals »Strategic Objectives »Conservation Priorities »Design Strategies (Targets)

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Strategic Objectives

  • Statements that outline what a regional MPA

network aims to achieve.

  • Slightly different in each bioregion to take into

account differences in environments and regional context

  • Guide the identification of specific Conservation

Priorities to be captured in the network

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Examples of Strategic Objectives

  • Help maintain ecosystem structure, functioning

and resilience within the bioregion

  • Provide protection for marine areas that

contain unique or rare features (populations, communities, species or habitats)

  • Protect representative examples of identified

ecosystem and habitat types in the bioregion

  • Help protect species at risk and their habitats to

ensure their survival and possibly improve their state

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Objectives hierarchy:

»National Goals »Strategic Objectives »Conservation Priorities »Design Strategies (Targets)

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Conservation Priorities

  • Individual populations or species, groups of

species, habitats, communities, ecological processes or other ecological features

  • Selection of Conservation Priorities guided by:

– The Strategic Objectives – Data availability – Data quality – Suitability of feature for spatial protection

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  • Eelgrass beds
  • Atlantic cod distribution
  • Vazella pourtalesi (sponge) concentrations
  • Areas of high fish species richness
  • Representative oceanographic areas
  • Species of Aboriginal importance
  • Forage fish species (capelin)

Examples of Conservation Priorities

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Examples of Conservation Priorities

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Objectives hierarchy:

»National Goals »Strategic Objectives »Conservation Priorities »Design Strategies (Targets)

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Design Strategies

  • Statements that specify the type and target

for each Conservation Priority

– i.e., what specifically is being targeted, and how much should be captured in the network?

Vazella sponge example:

  • Type: Significant concentrations of Vazella
  • Target: Capture 80-100% of this feature in the

network

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Design Strategies

  • Specifying targets:

–Helps to measure success in capturing Conservation Priorities in the network –Increases transparency in decision-making

  • Science meetings (CSAS) in each

bioregion to inform Design Strategies

–Indigenous information identified as a gap in Maritimes Region

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Part 2: Network Design Analysis

  • All 3 bioregions using Marxan to help design

an MPA network that:

– Meets the ecological targets – Minimizes socio-economic impacts

  • Marxan does not give the final solution!

– Helps to identify key areas and explore trade-offs – Good starting point for discussions

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Marxan

Decision Support Tool in Conservation Planning

Adrian Gerhartz-Abraham

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What is Marxan?

  • 1. Most widely used decision support software

for conservation planning globally

  • 2. Intended to solve reserve design problem

known as the ‘minimum set problem’ (i.e., capture a set amount of biodiversity for the least cost)

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Representative Adequate Efficient

The “ideal” is to sample every kind of biodiversity

  • 1. species (composition)
  • 2. habitats (structure)
  • 3. ecological processes (function)
  • 4. ecological ‘regions’ (biogeography)

Protecting enough to ensure persistence of biodiversity and continuity of ecological process that ensure ecosystem services. BUT How much is enough? Also, sampling across the full range of variation of each feature (i.e., replication) Achieving objectives with a minimum “cost”, that is to say, with the least possible impact for all those involved

Marxan and conservation planning principles

Connectivity

“Processes by which genes, organisms, populations, species, nutrients and/or energy move among spatially distinct habitats, populations, communities or ecosystems” (MPA Center Report, 2017).

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  • 2. Quantitative information (area) of each conservation priority for

each PU

  • 3. Quantitative targets for each conservation priority that the system

will aim to capture

0.2 0.4 0.8

How does a DST (e.g., Marxan) work in Protected Area planning?

  • 1. The management area needs to be subdivided into

planning units (PU)

e.g., 33% (~1 Km2) target of habitat distribution to be captured in the system

1km2 0.6

1 2 3

e.g., Nursery habitat Kelp distribution = 3 km2

  • 4. A cost associated to each PU (e.g., Area as a surrogate
  • f management cost; Landings value as a surrogate of

importance for fisheries; etc.)

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0.6 0.4

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High Fishing Activity

  • Identifies a group of sites which meet conservation

targets for a range of biodiversity features for a minimal cost

  • Marxan does not provide final answers but it is a

tool to support decision-making

What does Marxan do?

Scenarios

Most efficient D: target met with the smallest impact

A B C D

Low Fishing Activity

0.4 0.8 0.6 0.6 0.4 0.2

Problem : Protect 1 km2 of kelp habitat for the least impact

0.4 0.8 0.6 0.6 0.4 0.2 0.4 0.8 0.6 0.6 0.4 0.2 0.4 0.8 0.6 0.6 0.4 0.2 0.4 0.8 0.6 0.6 0.4 0.2 Low impact but Target not met Target met but medium impact Target met but high Impact

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Marxan Objective:

  • 1. Minimize:

a) The total “Cost” of the reserve network b) Total “Boundary” of the reserve network

  • 2. While meeting all conservation targets (i.e.,

minimizing the penalties for not adequately representing conservation features)

In Summary

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  • Useful to see how goals/objectives translate into

reserve options

  • Provides many good solutions and can be flexible for

stakeholder engagement

  • Incorporates different kinds of data to solve complex

reserve design problems

  • Identification of ‘key’ locations (both for conservation

and for not allocating reserves)

Benefits of using Marxan

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Benefits of using Marxan

  • Addresses core conservation planning principles

(Representation; Adequacy; Efficiency)

  • Selects areas in a systematic, repeatable and

transparent manner

  • Facilitates the exploration of trade-offs between

socio-economic and ecological objectives

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Marxan Analysis

  • Data inputs:

– Ecological data layers representing each Conservation Priority – Human-use data layers

  • For use in Marxan, human-use data must be:

– Georeferenced – Converted to the same unit

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Fisheries Data

  • Commercial fisheries data is the main human-

use input into Marxan

– Data available for most commercial fisheries – Want to avoid the most important areas for commercial fisheries where possible – Data can easily be converted into the same units (e.g., landing by weight)

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Fisheries Data Examples

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Other Human-Use Data

  • Other examples of human-use data to be

considered at the network design stage (either in Marxan or post-Marxan):

– Culturally important areas and uses – Aquaculture sites – Oil and gas production and significant discovery licenses – Utility corridors (e.g., under sea cables) – Other industrial developments (e.g., tidal energy) – Shipping traffic

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  • Different approach being used in the coastal

planning area – not using Marxan

  • Ecological data in the coast is mostly

descriptive in nature, with many gaps

– Relying on the use of Ecologically and Biologically Significant Areas (EBSAs) as a starting point – 54 EBSAs described in the coast based on expert

  • pinion and local knowledge

Coastal Process in the Scotian Shelf Bioregion

Coastal EBSAs and Eco-Units

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Data Gaps

Work is being done to fill information gaps, such as:

  • Indigenous information
  • Connectivity data
  • Spatial gaps (e.g., deep waters)

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The MPA Network Design

  • A network design is not the final picture

–Gives a general idea of priority sites for future protection

  • It is a long-term plan for each bioregion

–Will be adjusted over time as new information comes in

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The MPA Network Design

  • New AOIs to be selected based on the draft

MPA network designs starting in 2017

  • Each new MPA will have distinct

information collection and consultation processes

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Part 3. Timelines

Consultation to inform on process and collect information Finalize MPA network design Release draft MPA network design* Consultation

  • n draft

design

2016 2017 2018 2020 2019

Design and implement individual sites Consultation

  • n site design

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Opportunities

  • Still considering new information for

development of draft MPA network designs (2017)

  • Opportunity for input during consultation period
  • n draft designs (2018), including Indigenous

information

  • New scientific data, Indigenous information, and

human-use information will factor into future iterations of the MPA network designs (2018-

  • nward) and at site level implementation

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Thank you

Maxine Westhead maxine.westhead@dfo-mpo.gc.ca

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Resource Slides

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How Oceans Act MPAs are Created

Step 1: Select Area of Interest (AOI)

  • Engage stakeholders (ongoing during the designation process)
  • Create a multi-stakeholder advisory body

Step 2: Conduct overview and assessment of AOI

  • Overview of available ecological and human use information
  • Assess potential risk of human activities to the ecosystem

Step 3: Develop regulatory intent

  • Describes proposed boundaries and management scenario
  • Cost benefit analysis
  • Consult through advisory body and other mechanisms

Step 4: Develop regulatory documents and designate the MPA

  • Publish in Canada Gazette (includes public consultation period)

Step 5: MPA management

  • Research and monitoring, education and outreach, activity approvals, etc.
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Advance opportunities Phase 1 Gather data & information Phase 2 Design MPA network Phase 3 Create and implement Action Plan Phase 4 Monitor and manage sites

2015 2016 2017 2018 2020 2019 Consult on potential MPA Network Design Scenarios Finalize MPA Network Design Consult

MPA Network Development in NL Shelves Bioregion (proposed timeline)

Gather information and consult on MPA Network Objectives

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  • From 1996 to 2009 twenty-two individual LEK data

collection exercises were undertaken which cover the entire DFO NL Region

  • This is a spatial database collected through interviews

with local residents with an interest in participating. Mostly commercial fishers

  • Data collected on the following themes, Groundfish,

Pelagics, Shellfish Marine Mammals, Aquatic Plants, Aquaculture, Infrastructure, Culture Tourism and Recreation, Shoreline Classification (Scale 1:50,000)

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NL Shelves Bioregion: Community- based Coastal Resource Inventory

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Examples of Stakeholder Identified Conservation Priorities in the NL Shelves Bioregion

  • 1. Atlantic Cod
  • 2. Coral and Sponges
  • 3. At Risk Species
  • 4. Marine Habitats
  • 5. Marine birds
  • 6. Cetaceans
  • 7. Species of Aboriginal

Importance

  • 8. Forage Fish Species

(capelin)

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Community Coastal Resource Inventory Areas for a given fishery are mapped. In this case – the Cod fixed gear fishery Marxan Planning Units which

  • verlay these areas are

extracted to represent the footprint of that fishery inshore Non-georeferenced points with associated logbook values are distributed by NAFO Zone to the CCRI planning units. Georeferenced points are mapped as per usual.

Mapping Commercial Logbook Data using the Coastal Community Resource Inventory

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  • In 2012 a LEK survey was conducted through a

personal services contract

  • Fifteen fishers were interviewed from several

communities along the southern Labrador coast

  • Extra emphasis was placed on trying to identify

special areas or areas worthy of conservation attention

NL Shelves Bioregion: Offshore Local Ecological Knowledge Survey

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Identifying Design Strategies (EGSL)

  • What?

Percentage associated to each CP

  • Why?

It quantifies strategic conservation objectives Helps measure the achievement of results for the MPA network

  • How?

Different scenarios = various conservation levels

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Identifying Design Strategies (EGSL)

  • Minimum target = 10%
  • CBD expert workshop (Nagoya, 2010)
  • Québec City (2011)
  • "medium" and "high" targets
  • Targets selected for basic scenarios for all

conservation priorities: 10% - 20 % - 30%

Defining criteria for assigning higher targets

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Identifying Design Strategies (cont.)

  • Different CPs, different conservation level:
  • Increase targets if the conservation level is higher, e.g.,

species at risk:

  • 20% - 30% - 40%
  • Other criteria for assigning higher targets than those in

basic scenarios:

  • Number of COs per CP
  • Species of particular interest
  • "Direct" vs. "substitute" data
  • "Integrated" or "non-integrated" data