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

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

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

Bioregions

Challenge • In each bioregion, use the extensive amount of 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 4

Part 1: Setting the Stage • A structured process is needed for consistency across bioregions • Objectives hierarchy: Broad » National Goals »Strategic Objectives »Conservation Priorities » Design Strategies (Targets) Specific 5

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. 6

Objectives hierarchy: »National Goals » Strategic Objectives »Conservation Priorities » Design Strategies (Targets) 7

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 8

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 9

Objectives hierarchy: »National Goals »Strategic Objectives » Conservation Priorities » Design Strategies (Targets) 10

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 11

Examples of Conservation Priorities • 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) 12

Examples of Conservation Priorities

Objectives hierarchy: »National Goals »Strategic Objectives »Conservation Priorities » Design Strategies (Targets) 14

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 15

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 16

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 17

Marxan Decision Support Tool in Conservation Planning Adrian Gerhartz-Abraham

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 )

Marxan and conservation planning principles The “ideal” is to sample every kind of biodiversity 1. species (composition) 2. habitats (structure) R epresentative 3. ecological processes (function) 4. ecological ‘regions’ (biogeography) Also, sampling across the full range of variation of each feature (i.e., replication) Protecting enough to ensure persistence of biodiversity A dequate and continuity of ecological process that ensure ecosystem services. BUT How much is enough ? Achieving objectives with a minimum “cost”, that is to say, E fficient with the least possible impact for all those involved “Processes by which genes, organisms, populations, species, nutrients and/or energy move among spatially distinct Connectivity habitats, populations, communities or ecosystems” (MPA Center Report, 2017).

How does a DST (e.g., Marxan) work in Protected Area planning? 1. The management area needs to be subdivided into 1 planning units (PU) 1km 2 2. Quantitative information (area) of each conservation priority for each PU 0.6 0.4 0.6 e.g., Nursery habitat 0.2 0.4 2 Kelp distribution = 3 km 2 0.8 3. Quantitative targets for each conservation priority that the system will aim to capture e.g., 33% (~1 Km 2 ) target of habitat distribution to be 3 captured in the system 4. A cost associated to each PU (e.g., Area as a surrogate of management cost; Landings value as a surrogate of importance for fisheries; etc.) 4

What does Marxan do? • Identifies a group of sites which meet conservation targets for a range of biodiversity features for a minimal cost Low 0.6 0.6 0.4 Fishing Activity 0.2 High 0.4 0.8 Fishing Activity Most efficient D: target met with the Scenarios smallest impact A B C D Problem : 0.6 0.6 0.4 0.6 0.6 0.4 0.6 0.6 0.4 0.6 0.6 0.4 Protect 1 km 2 of kelp habitat 0.4 0.2 0.2 0.4 0.4 0.2 0.8 0.2 0.4 0.8 0.8 0.8 for the least impact Target met but Low impact but Target met but medium impact Target not met high Impact • Marxan does not provide final answers but it is a tool to support decision-making

In Summary 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)

Benefits of using Marxan • 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 • 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

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 26

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) 27

Fisheries Data Examples

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 29

Coastal EBSAs and Eco-Units Coastal Process in the Scotian Shelf Bioregion • 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 opinion and local knowledge 30

Data Gaps Work is being done to fill information gaps, such as: • Indigenous information • Connectivity data • Spatial gaps (e.g., deep waters) 31

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 32