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June 12, 2025

'Traffic light' dog-walking zones can benefit people, dogs and environment, says report

Credit: University of Exeter
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Credit: University of Exeter

An estimated 12.5 million dogs live in the UK—up by about 30% since before the COVID pandemic.

The RENEW project held workshops with conservationists and professionals working with to review evidence, and came up with recommendations to help reduce the potential impacts of dog walking on the environment. The report is titled

These include a "traffic light" system—green, amber or red pawprints to show where dogs can roam off leashes, where paws should be kept on paths, and where dog walking should be prevented to protect sensitive wildlife or habitats.

"Dogs are an important part of many people's lives, and the vast majority of dog owners don't set out with an intention to disturb wildlife," said David Bavin, lead author on the report.

"The aim of this research is to find a balance between providing welcoming spaces for people and dogs and minimizing any negative impacts on wildlife and the environment."

Having a national standard—with clear signs like the traffic light pawprints—would make it easier for everyone to know what's expected, the researchers say.

"This is a simple way of helping dog walkers understand the landscape they're in, and opens up great conversations about how we share space," said Hannah Molloy, from the Parliamentary Group for Dog Welfare.

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The report—by RENEW's ExCASES research group—finds:

The researchers advocate a "One Health" approach—meaning one that aims to balance the health and well-being of people, animals and ecosystems.

They say we should strive for no "net loss" of access for dog walkers. Instead, restrictions should be evidence-based, only used where necessary, and—where possible—alternative sites should be created where dogs can be walked without restrictions.

"Some of this is being done really well already," Bavin said. "Projects such as Dorset Dogs are working very effectively with dog owners, while Holkham Estate, in Norfolk, employed a zoning approach following consultation with local communities."

Stephen Jenkinson, an independent specialist on dogs in the outdoors, said, "It's so helpful this report confirms how walkers with dogs will avoid conflict with wildlife if given clear, credible and relevant choices about where to go and what to do. While such vital information is lacking in most places, the report usefully highlights the good practice that already exists."

The team argue that expanding to UK land—which is largely privately owned and inaccessible—would ease pressure on current pinch points such as nature reserves.

"We hope to encourage a positive national conversation about dog walking, in collaboration with people and organizations working in both the conservation and canine sectors," said report co-author Dr. Sarah Crowley, from the University of Exeter.

Bavin added, "We all rely on the health of our environment, which is why our approach seeks to support the health, welfare and resilience of people, dogs, and nature."

The ExCASES includes an accessible overview of current evidence of dog walking impacts on biodiversity, and best practice recommendations for how to fairly and sustainably manage these.

The RENEW project (Renewing biodiversity through a people in nature approach) is a collaboration between the University of Exeter and the National Trust.

More information: David Bavin et al, Paws for Thought: towards environmentally friendly dog walking in the UK, University of Exeter and The National Trust / RENEW (2025).

Provided by University of Exeter

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A "traffic light" zoning system for dog walking—using green, amber, and red pawprints to indicate permitted, restricted, and prohibited areas—can help balance the needs of people, dogs, and wildlife. Evidence shows dog walking may disturb wildlife and pollute habitats, especially in urban and coastal areas. Clear, evidence-based guidance and expanded access can reduce negative impacts while supporting well-being.

This summary was automatically generated using LLM.