Protecting Kenya’s wildlife while helping build a vital highway

Highways are essential for prosperity – and they can also be a threat to wildlife. Here are some ideas of how these two priorities can be met, on a highway across Kenya.

Kenya’s A8 highway runs from the port city of Mombasa westwards, right across the country. Improving this road is a big part of Kenya’s plan to build a transportation network that meets the country’s Vision 2030 program, to become an industrialized, emerging economy.

Location

Nairobi, Kenya

Client

Rift Valley Highway Limited

But Kenya’s wildlife is also vital to the country’s future – partly through the tourism industry. Expanding the A8 highway from Nairobi to Mau Summit, from two to four lanes, with fences alongside, has implications for wildlife that must be managed. There’s also a need to protect the livelihoods of people in the area, including livestock herders who need to cross the road to reach pastures and watering places.

In 2021, the consortium leading the highway expansion sought the collaboration of WSP to comprehensively evaluate the corridor's impact on biodiversity, economic activities, and social dynamics. WSP's role extended beyond issue resolution; it involved developing proactive plans to minimize and mitigate potential adverse effects, emphasizing a commitment to responsible and sustainable practices from the project's inception.

The project being set in a complex biodiversity context, home to a variety of large mammals, including endangered species, such as the Maasai and Nubian Giraffe, and many other iconic African species, such as lions, buffaloes, zebras, hippos, etc., WSP had to develop a solid work plan that relied on adaptability, innovations and collaborations to adequately handle biodiversity issues, representing leading practice in impact assessments for linear infrastructure projects.

Maya Brennan Jacot Biodiversity Specialist

Understanding the environmental, social and economic picture

To understand the potential impacts, an Environmental and Social Impact Assessment (ESIA) and an Environmental and Social Management System (ESMS) were developed in accordance with Kenyan laws and the International Finance Corporation’s Performance Standards (IFC PS).

To do this work, WSP started by gaining an understanding of the current conditions.

Camera traps: Over a six-month study period, the team strategically installed 50 cameras in areas with the highest animal populations to understand whereabouts and movement patterns of wildlife. These cameras captured images automatically every 15 minutes, transmitting them through the mobile phone network. The team was able to remotely monitor and make necessary adjustments to the cameras.

Big data analysis and Innovation: The cameras captured a staggering 642,291 images – each categorized by location and timestamp. Managing such extensive data, particularly with the task of identifying animals in each image, posed a significant challenge. WSP’s Innovation and Research & Development played a pivotal role in overcoming these challenges. They established a dedicated portal on WSP servers to aggregate the images and devised an Artificial Intelligence (AI) capability for identifying animals in photos. The focus of this AI was on four key species for conservation reasons and their susceptibility to vehicular collisions: African Buffalo, Giraffe, Plains Zebra and Spotted Hyena.

Connectivity modeling: A key focus of our efforts was to safeguard wildlife from potential harm or fatalities while crossing the road. While installing fences on either side could have addressed this concern, it presented additional risks to wildlife, particularly in terms of habitat continuity.

In numerous regions globally, Kenya included, wildlife faces challenges as human development encroaches upon historically wild territories. This has led to the reduction of wildlife habitats, with potential blockages along crucial animal movement routes. Therefore, a critical factor in successful wildlife conservation involves developing an understanding of connectivity—how animals navigate between different sections of their habitat. WSP employed computer modeling to delineate suitable habitat areas, identifying the core habitats of various species. This data was then utilized to map essential connectivity routes crucial for wildlife conservation efforts.

Habitat suitability

Source: Lechner, Tiang and Ang

Core habitat

Step 1b: Connectivity

From the team's comprehensive research, WSP crafted a Wildlife Mitigation Plan and a Biodiversity Action Plan, aiming for no net loss and net gain of connectivity. These plans were designed to adaptively manage the project's impact, ensuring successful biodiversity outcomes.

WSP also pinpointed areas where the highway expansion might impact habitat connectivity and subsequently recommended the installation of highway crossings. These crossings, including overpasses and passageways under the roadway, were strategically proposed to minimize disruptions to wildlife.

The success of this initiative hinged on expert collaboration and stakeholder engagement. Consulting with local communities proved instrumental in comprehending biodiversity-related impacts, considering mitigation measures, but also in understanding the potential economic changes along the corridor, such as impacts on animal herders.

The methodologies applied in developing the Environmental and Social Impact Assessment (ESIA) and associated documents provide valuable insights for future projects. Notably, this project has demonstrated the capability to use statistical methods to quantify connectivity, even in landscapes with limited formal data. It sets a benchmark for impact assessments in linear infrastructure projects in the developing world, establishing a best-practice standard that future endeavors should emulate.

Length of highway expansion

175 Km 175 Km

Strategically Installed

50 Cameras 50 Cameras

Images were Captured

642,291 642,291

What makes this project stand out

Comprehensive Approach to Wildlife Protection

This includes the strategic installation of camera traps, extensive data analysis using innovative techniques like AI, and the development of wildlife mitigation and biodiversity action plans. By prioritizing wildlife conservation, the project sets a benchmark for future infrastructure projects in similar environments.

Innovative Connectivity Modeling

This project uses computer modeling to identify suitable habitats and core habitats of different species, ensuring successful conservation of wildlife. This sets a new standard for mitigating the impact of infrastructure projects on wildlife connectivity.

Engagement with Local Communities and Stakeholders

This approach provides valuable insights into biodiversity-related impacts and considers potential economic changes along the corridor. By addressing the needs and concerns of all stakeholders, the project sets a best-practice standard for similar endeavors.