Community-Based Nursery Beds

The purpose of community-based permanent nursery beds is to ensure the production of high-quality, resilient seedlings for reforestation efforts while building local capacity. Each of the four project districts (Luwero, Mbale, Busia, and Kapchorwa) established one centralized nursery bed per location, equipped with essential tools, irrigation facilities, and trained nursery operators. Seeds were delivered early (December 2023–January 2024) to allow for the full growth and hardening process, ensuring seedlings met survival standards. The nurseries produced 96,423 seedlings of multi-purpose tree species, including Grevillea and Agrocarpus, which were selected for their adaptability to local climatic conditions, drought resistance, and soil stabilization properties. Nurseries also served as training hubs, where farmers learned good agroforestry techniques, seed propagation, pest control, and seedling management techniques.

  • Technical Knowledge: Trained operators with skills in seed management, seedling management, farmer training, community mobilisation and engagement, root pruning, and hardening-off processes.
  • Access to Inputs: Reliable supply of quality seeds, potting materials, and pest control inputs.
  • Water Availability: Sustainable irrigation systems to overcome drought periods and maintain seedling health.
  • Community Engagement: Active participation from farmers and local leaders to monitor and support nursery operations.
  • Early seed delivery, proper management, good nursery management and seedling hardening significantly improved tree survival rates in harsh field conditions.
  • Poor irrigation infrastructure in some locations exposed seedlings to water stress during dry spells. Investment in simple irrigation techniques is recommended to mitigate this.
  • Root damage and poor seedling management during transplanting led to seedling mortality in some cases. Ensuring proper root ball integrity during handling is critical.
     

    Advice: Establish contingency production targets (10–15% above the actual requirement) to buffer losses from pests or weather-related issues. Additionally, develop on-site water harvesting systems to support irrigation during drought periods.

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.
Web Platform for Collaborative Data Integration

This building block focuses on the creation of a web-based platform that serves as the core tool of Bio-Scanner. The platform is designed to centralize biodiversity data by allowing users to upload, access, and analyze information related to jaguar distribution and other species. The dashboard facilitates collaborative data integration, making it accessible to researchers, conservation practitioners, and decision-makers. By feeding this information into the algorithm, the platform helps refine predictions on species distribution, population dynamics, and behaviors.

The purpose of this building block is to provide an accessible and user-friendly platform that acts as a central hub for biodiversity data. It allows users to contribute data (e.g., camera-trap images or additional species records), visualize trends, and understand key insights about jaguar populations. The platform is designed to democratize access to AI-driven conservation tools and foster collaboration across stakeholders, improving conservation outcomes.

Enabling factors:

  • Development of a secure, scalable, and user-friendly web application to handle large datasets.
  • Collaboration with technical experts in AI, web development, and conservation biology to design functionalities that meet user needs.
  • Accessibility features to ensure the platform can be used by decision-makers, academic researchers, and local conservation practitioners alike.
  • A robust data governance framework to protect sensitive data while promoting transparency and sharing
  • Simplifying the user interface is critical for engaging a broad audience, including non-technical users.
  • Ensuring data interoperability through standardized formats facilitates integration with other conservation projects and tools.
  • A participatory design approach involving users from different sectors helps tailor the platform’s functionality to meet diverse needs.
  • Regular updates and maintenance are essential to ensure long-term usability and relevance.
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  
Whale-watching tour operators

Whale-watching tour operators

Willingness to participate. 

Love for the Marine Reserve. 

Make the tour operators ve a part of it. 

Technology

SMART Conservation Tool software

Plant Propagation: increased efficiency with improved collecting techniques

Once plants have been collected, they are transferred to our conservation nursery for propagation, or to our seed lab for viability testing and storage. We are seeing increased effectiveness of these methods with freshly collected seeds and cuttings making it quickly to our staff. As many of these individual plants were not previously known, these actions boost the genetic diversity of ex-situ collections, providing a safe place in the face of environmental degradation.

Previously, botanists would need to scale the remote cliff environments where these species occur, making conservation collections difficult and time-consuming to collect and transfer back to nursery staff for propagation. With the Mamba mechanism, collections are quickly collected and transferred to the nursery. 

Fresh cuttings and seeds have a higher success rate in propagation.

 

Drone Collection: Using a drone-based robotic arm to collect inaccessible plants

The Mamba tool allows us to collect plant material via seeds or cuttings from endangered species that we have identified and mapped in the previous building block. This tool has an effective range well over 1000m, making even the most inaccessible areas available for management actions. 

The development of this tool by experienced robotics engineers, expedited the conservation of many species by field staff at the National Tropical Botanical Garden and partners at the Plant Extinction Prevention Program. The Mamba has an interchangeable head system that provides customizable collecting depending on the target species and the type of material necessary for conservation. Many of the components of this mechanism are 3D-printed, which is cost-effective and flexible for speedy development processes. The Mamba is built with readily available drone components which also reduces the cost and building time. The development of this tool was undertaken by P.h.D students, and integrates state of the art hardware and software solutions specifically designed for this application.

When undertaking a project of this type, it is critical to have the proper pairing of experienced field staff with professional robotics engineers, as both parties provide crucial information to guide both development and effective conservation considerations. It is worth noting that the development process was iterative, leaving space for testing and revising the design, and ultimately allowing for deployment of a well-functioning and highly useful tool. 

Mitigate biodiversity loss

Conserving ecosystems is key to curbing climate change, and maintaining ecosystem services (GBF target 11), which are closely linked to over 50% of the world’s GDP. Over 1 million species face the threat of extinction this century; however, selecting which areas to conserve is challenging with the existing data gap, which is biased towards observations in the global north. Increasing the amount of biodiversity data in the Global South is critical in the conservation of endangered species, found at high density in biodiversity hotspots in the Global South. Amphibians are ideal for acoustic identification due to their diverse vocalizations and are crucial ecosystem indicators (Estes-Zumpf et al., 2022), with over 40% of species at risk of extinction (Cañas et al., 2023). Increasing labeled data for the more than 7,000 amphibian species worldwide would enhance conservation efforts and reduce knowledge gaps in vulnerable ecosystems. By using a citizen science platform to aid in the mitigation of biodiversity loss, we help establish local environmental stewardship of these critical habitats (GBF Target 20).

Other citizen apps have shown the potential that citizen science has on mitigating biodiversity loss. eBird, the largest citizen science project related to biodiversity, has 100 million bird observations from users around the world. These observations help to "document the distribution, abundance, habitat use and bird trends through collected species list, within a simple scientific framework." (Sánchez-Clavijo et. al., 2024).  

iNaturalist, another citizen science app, that uses computer vision algorithms for species identification, has also proven successful in mitigating biodiversity loss. To date, the app has over 200,000,000 observations, with 6 million observations per month, globally. On iNaturalist, research-grade observations are shared with GBIF, which in turn uses that knowledge for policy decisions, research, and community building (GBIF, 2023). 

Currently, our app identifies 71 species of frogs and toads, worldwide. Though many of them are identified as least concern (LC) under the IUCN, we do have one IUCN endangered species, the Southern Bell Frog (Ranoidea raniformis). This lack of threatened species included, underscores the need for diverse practitioners to participate in bioacoustic ecological monitoring. Increasing data points on vulnerable species can serve to inform policy decisions using data-driven insights. Local communities and Indigenous Peoples will be a key asset in increasing the number of species included in the app, as their local knowledge allows us to track species in remote regions. 

  • Closing data gaps: get more data from citizen scientists, especially from local communities and Indigenous Peoples.
  • Enabling environmental stewardship: accessibility to a diverse set of users.

We initially set a goal to decrease data gaps in the Global South. However, getting access to enough calls for rare, cryptic, and endangered species in the Global South to train our model proved to be challenging. Therefore, to improve model performance, we turned our attention to as many species as we could tackle, worldwide. Getting users engaged worldwide will lead to more recordings in data-poor regions like the Global South, allowing us to retrain our model in the future with increased data on endangered, rare, and cryptic species. 

This user engagement perfectly aligns with multiple targets, the most evident one being GBF target 20: Strengthen Capacity-Building, Technology Transfer, and Scientific and Technical Cooperation for Biodiversity. But other targets are key in this building block: by increasing the data points, we will be able to identify invasive alien species, addressing GBF Target 6, as well as protecting wild species from illegal trade, by obscuring their location from users. This is aligned with GBF Target 5, which seeks to "Ensure Sustainable, Safe and Legal Harvesting and Trade of Wild Species."