What is the West Norfolk Nature Network (WNNN)?
The West Norfolk Nature Network (WNNN) is a collaborative, farmer-led project uniting landowners across the region to create and enhance 4,500 hectares of semi-natural habitat.
Its aim is to restore nature at scale while continuing to produce food. Set within a wider 15,000-hectare landscape recovery area, WNNN brings together people, land, and resources to strengthen both wildlife and farming. The project is one of the 56 DEFRA Landscape Recovery pilots currently underway across England.
The first two years of the project are purely theoretical, scoping out what could be possible in the area. Once approved by DEFRA the project will go into implementation for the following 20-30 years.
The aim is for implementation to begin in the summer of 2026,working as a network to support long-term environmental gains and agricultural resilience.
Landscape Recovery
Landscape recovery lies at the heart of WNNN’s ambition. Working across a wide and ecologically significant area, the project is focused on rebuilding a connected landscape that supports both biodiversity and natural processes.
This includes restoring internationally important chalk stream habitats, wetlands, heathland, woodland and creating habitat corridors including scrub, ponds and trees that allow wildlife to move freely.
By linking isolated habitats and reversing decades of fragmentation, WNNN is helping to create a more balanced, climate-resilient environment that benefits nature as well as people
[LOGO CAROUSEL HERE]
Nature and Farming Together
WNNN aims to demonstrate that productive farming and ecological restoration can go hand in hand. Rather than taking valuable farmland out of production, the project targets less productive areas for nature recovery, while embedding regenerative techniques across working land.
These methods improve soil structure, reduce emissions, enhance water quality, and increase farm resilience to climate change. What makes this effort unique is the scale of cooperation: 30 farmers and landowners are working side by side to shape a landscape where healthy ecosystems and viable farms support one another.
WNNN Strategic Aims
The West Norfolk Nature Network follows a practical, joined-up approach, with key strategies including:
Blended public-private funding and robust long-term governance will help secure the future of the network beyond the current pilot.
How the WNNN started
WNNN began through proactive outreach and collaboration, guided by Natural England and driven by a shared sense of responsibility among local landowners.
These farmers saw the need for a more ambitious and coordinated response to biodiversity loss and climate pressures. Building on their collective experience from earlier environmental schemes, they formed the foundations of a network designed to work at landscape scale.
What started as conversations around shared challenges has grown into a dynamic partnership focused on long-term, connected recovery of land and wildlife across West Norfolk.
Farming and Nature: facts and future plans
4,500 hectares of semi natural habitat to be created or enhanced
A wider 15,000 hectare area is being shaped for joined-up recovery
Regenerative farming will enhance soils, water, and climate resilience
Habitat restoration will support key species within the landscape
Restoring rivers, ponds and wetlands will naturally clean our water, reduce flood risks and mitigate against droughts
WNNN offers a model for long-lasting nature recovery that supports both agriculture and the wider countryside
Nature & Community Together
WNNN is not only about restoring nature — it’s about reconnecting people with it. The project aims to create opportunities for communities to experience and care for their local environment through educational programmes, accessible nature areas, and heritage-inspired initiatives.
By embedding nature into daily life, WNNN hopes to foster lasting relationships between people and place, ensuring that the health of the landscape is valued and protected for generations to come.
Case Study 1
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Case Study 2
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Case Study 3
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