The Key Processes in Integrating Mangrove Conservation into National Policy

The process was the cornerstone for transforming ideas into tangible results. The first step was ensuring the availability of high-quality data and demonstrating its importance within both local and national contexts. In the case of mangroves, this included their role in spatial and development planning, included in the National Territorial Development Plan, which highlights their impact on coastal livelihoods, climate adaptation, and potential blue carbon credits.

Once the data was gathered, the next step was presenting it to IUCN’s partners and members, fostering a supportive alliance to create a unified voice for advocating with decision-makers. This process continued by establishing and maintaining an open, trustworthy, and technically robust dialogue with policymakers and their technical teams. A key component of this was understanding how governance, policy and legal frameworks are developed and implemented, ensuring that even if contributions weren’t fully aligned with initial expectations, they remained practical and applicable and are adopted.

Ongoing monitoring, along with continued support from IUCN, ensured that the strategies were effectively implemented and adjusted when necessary. It’s important to acknowledge that while conservation and adaptation efforts are globally supported, they often require significant budgets, that are not available locally. To secure funding, these issues must be at the forefront of governance planning, allowing for the budgets and co-financing by development partners to be available.

Critical factors that facilitated the process included the global campaign of raising awareness about the benefits of mangroves for sustainable livelihoods, Mozambique’s focus on the mangrove strategy, and the development of key national policies like the PNDT and Marine Spatial Plan. IUCN’s commitment and its ability to identify opportunities to mainstream mangroves within these national strategies, coupled with its extensive network and reliability, were equally essential.

Several lessons emerged throughout this process. First, technical assistance, similar to that provided to the government proved invaluable, as did the capacity to step up in alignment with government processes. The ability to access upgraded technical support when required, and the involvement of academia and civil society organisations, are critical for a successful approach. Maintaining ongoing information-sharing and an awareness campaign, combined with consultations, helped sustain engagement throughout the process.

The Power of Knowledge about Mangroves in Shaping Conservation and Policy

The vital role of mangroves in coastal ecosystems has been emphasised through a wealth of scientific data and research. This knowledge has become the entry point for educating planners and decision-makers on the socio-economic significance of mangroves, from providing community income to supporting coastal adaptation. Through studies conducted by SOMN on Mozambique’s mangrove use and data from the Global Mangrove Alliance, IUCN has united key conservation actors such as WWF, WCS, Centro Terra Viva, BIOFUND, ABIODES, and government institutions to establish a common voice in advocating for mangrove protection.

IUCN and SOMN played a pivotal role in the elaboration and approval of the National Mangrove Strategy, which outlined clear goals, approaches, and restoration principles and were endorsed by the Government and conservation partners. Building on this foundation, the strategy was integrated into national policies, particularly the National Territorial Development Plan. This plan not only drives sustainable development but also maps out Mozambique's rich biodiversity, including its mangrove ecosystems. This allows local governments and community leaders to identify key conservation hotspots and priority restoration areas. The strategy also provides geographical and quantitative data, enabling conservationists and NGOs to monitor and track progress in their interventions.

Key for these activities were the existing data and studies, IUCN's broad network of members and partners, and the trust and credibility IUCN has built with policymakers.

While the knowledge was foundational, its true potential was realized through effective processes and strong partnerships. IUCN's acceptance by the government and its partners was quintessential to ensure engagement and ownership at every stage of the process. It was also vital to ensure the quality and availability of data, and to collaborate closely with the government to adapt and incorporate recommendations into the legal framework, ensuring that mangrove conservation became a long-term priority.

AGROFORESTRY PROJECT FARMERS WITH SEEDLINGS
Community-Based Nursery Beds
Tree Planting at community Level
Cash Crop Integration for Sustainable Incomes
AGROFORESTRY PROJECT FARMERS WITH SEEDLINGS
Community-Based Nursery Beds
Tree Planting at community Level
Cash Crop Integration for Sustainable Incomes
AGROFORESTRY PROJECT FARMERS WITH SEEDLINGS
Community-Based Nursery Beds
Tree Planting at community Level
Cash Crop Integration for Sustainable Incomes
AGROFORESTRY PROJECT FARMERS WITH SEEDLINGS
Community-Based Nursery Beds
Tree Planting at community Level
Cash Crop Integration for Sustainable Incomes
Delopment of the SIREN App

This building block is to explain how I developped an App that allow fishers to contribute to marine science knowledge in Africa. 

Initially we gave fishers a pre-printed form to report opportunistic sightings they encountered. However, the form was getting lost most of the time. 

We decided to move to a digital solution. The existing App by then required internet to work and was just too complicated for fishers. So we thought we shoud develop an App that will be more userfriendly for fishers. 

We wrote the  algorithm (workflow) of the App and then contracted an Indian development company to write the code. 

Later we had to bring the development of SIREN back to Cameroon to reduce the cost of developement. 

We work with volunteer around the world that will continuously support with the development of the SIREN

  • passion and determination
  • availability of seed fund to develop an initial version of the SIREN App
  • Collaboration with local App developpers
  • Extending the collaboration to international volunteers 
  • understand
  • The first developper company I contracted for the development of SIREN was a foreign company based in India. The cost of develpment was very high and there was a lot of miscomunication due to language barriers. When we started working with local developpers, the cost of development decreased importantly and it was easier to communicate.
  • Before giving a smarphone to fisher for data collection you must develop a trust relationship with him before otherwise the phone will never be used by the fisher to report sightings.
Capacity Development through Technology Training

This building block emphasizes the importance of training students and local actors in advanced technologies for conservation purposes. In Bio-Scanner, students from the Universidad Politécnica de Yucatán  are trained in using AI algorithms, camera-trap data processing, and decision-support tools, fostering a new generation of professionals equipped to address biodiversity challenges.

The purpose of this building block is to build local capacity by providing hands-on training in cutting-edge technologies. This ensures that local actors can independently use, maintain, and replicate the solution in other contexts while fostering professional development among students.

Enabling factors:

  • Access to training resources and mentoring from experts in AI and conservation.
  • Collaboration with academic institutions to recruit and support students in applying their skills to real-world projects.
  • Ongoing support and capacity-building to ensure trainees can effectively use the tools and scale their applications.
  • Practical, hands-on training is more effective than theoretical approaches in building capacity for conservation technologies.
  • Partnerships with academic institutions provide a sustainable pipeline of trained professionals for long-term conservation efforts.
  • Regular follow-up and support after training help trainees apply their skills effectively and adapt to challenges.
  • Integral overview of the project, helps trainees to gain an overall vision of the entire initiative and notice the impact of their work in the project.
Advanced Image Recognition Algorithms for Jaguar Monitoring

This building block is centered on the use of Convolutional Neural Networks (CNNs), including Siamese and Autoencoder architectures, to detect and identify individual jaguars based on unique features such as rosette patterns and morphology. These algorithms process camera-trap data efficiently, reducing the time required for analysis and providing critical insights for decision-making in conservation.

The purpose of this building block is to enhance the monitoring and understanding of jaguar populations by automating the identification process. The algorithms detect jaguars in camera-trap images and classify individuals, contributing to understanding population size, distribution patterns, and behaviors. This facilitates conservation planning and policy-making by decision-makers. Additionally, the models are scalable and can be adapted to other species and ecosystems, expanding their applicability beyond the Yucatán Peninsula.

Enabling factors:

  • Availability of high-quality camera-trap data for training and validating the algorithms.
  • Technical expertise in AI and machine learning for developing and fine-tuning models.
  • Collaborative partnerships with local institutions for field data collection and algorithm design, development and testing.
  • Access to sufficient computational resources to train and deploy the algorithms effectively.
  • High-quality and diverse datasets are critical for achieving accurate and reliable results.
  • Community and academic involvement, such as the participation of the Dzilam de Bravo community and the Universidad Politécninca de Yucatán, enhances project outcomes by ensuring local capacity and ownership, and technological expertise to design the necessary algorithms.
  • Explainability in AI models (e.g., through Gradient Cam) is essential to build trust and ensure the results are accessible to decision-makers.
Spatial Intelligence for Wildfire Management

This building block provides the essential spatial intelligence for PyroSense, enabling a dynamic understanding of the geographical landscape. Its core purpose is to identify fire risk areas, pinpoint incident locations, and visualize resource deployment. This is crucial for strategic decision-making, allowing proactive resource allocation, and response planning. 

PyroSense utilizes a robust Geographic Information System (GIS) to power this function. The GIS integrates various spatial data layers, including topography, vegetation, infrastructure, etc. Initially, baseline risk maps are created by analyzing factors, guiding the placement of sensors and cameras.

Upon detection of a potential fire by environmental sensors or AI, the system immediately feeds the precise coordinates into the GIS. This real-time location data, combined with meteorological data (local and satellite), enables dynamic risk assessments. The GIS also serves as a central operational dashboard, visualizing the real-time positions of all deployed assets, including drones and first responder teams. This facilitates optimal resource allocation and coordination. This critical information is then communicated via a web application to stakeholders, providing clear visual situational awareness and supporting informed decision-making. 

  • Accurate and Up-to-Date GIS Data: Access to current geospatial data on topography, vegetation,  historical fire activity is essential for reliable risk assessments.
  • A powerful GIS platform is necessary for integrating diverse data layers, performing complex analyses, and running real-time AI.
  • Expertise is needed to interpret GIS data, validate models, and use the platform for strategic planning and incident management.
  • Connectivity with environmental sensors, drone feeds, and meteorological data is crucial for dynamic risk mapping and accurate fire tracking.

The accuracy and utility of geospatial planning are directly proportional to the quality and timeliness of the underlying GIS data. Investing in high-resolution, frequently updated maps and environmental data is paramount. Furthermore, the ability to integrate real-time sensor and drone data into the GIS for dynamic risk assessment proved to be a game-changer, moving beyond static planning to predictive capabilities. 

Initial challenges included the significant effort required to collect and digitize comprehensive baseline GIS data for large, remote areas. Data standardization across different sources (e.g., various government agencies, local surveys) was also a hurdle. Additionally, ensuring the GIS platform could handle the computational load of real-time data fusion and complex fire spread simulations without latency issues was a technical challenge.

  • Before deployment, dedicate substantial resources to acquiring and standardizing all relevant geospatial data. 
  • Choose a GIS platform that can scale with increasing data volumes and computational demands.
  • Ensure that local teams are proficient in using the GIS platform