Many species reintroductions in the UK, including the Red Kite, Eurasian Beaver, and White-tailed Eagle, have shown promising signs of restoring biodiversity and rebuilding damaged ecosystems. Yet nature is a complex network of interactions, and even successful reintroductions can produce unexpected effects on other species. Conservation decisions are often based on limited data and observations made after changes have already occurred. What is needed is a new approach.

To understand how ecosystems behave, scientists often begin with simple models of interaction. One of the most common is the relationship between foxes and rabbits.

When rabbit populations are high, foxes thrive. Food is abundant, survival improves, and their numbers begin to rise. But this success does not last indefinitely. As foxes become more numerous, the pressure on rabbits increases, and their population begins to fall. With fewer rabbits available, foxes in turn begin to decline, and the cycle gradually resets.

At first glance, this pattern suggests a predictable rhythm in nature—almost like a natural balance that repeats over time.

But real ecosystems are not this simple.

Foxes do not depend on a single food source. They hunt rodents, birds, and amphibians, and they also scavenge carrion. They may even consume fruit and berries when available. At the same time, their survival is shaped by disease, habitat change, climate, and human activity.

As more species and interactions are added, the system stops behaving like a simple cycle and becomes a complex web of dependencies.

And in systems this interconnected, predicting the long-term effects of a single conservation decision becomes extremely difficult.

This is where AI could play a transformative role. By analysing vast amounts of ecological data, AI can begin to model the intricate relationships within ecosystems and predict the likely outcomes of conservation decisions before they are made.

But its power increases significantly when combined with the idea of a digital twin.

A digital twin of an ecosystem would be a living virtual representation of the natural world. It would be continuously updated using data from satellites, drones, camera traps, weather stations, acoustic sensors, and field surveys. Together, this stream of information would allow the AI to build a detailed picture of the environment—tracking populations of plants and animals, mapping their interactions, and monitoring changes in habitat and climate over time.

Rather than relying only on historical data, the system could then explore the future. It could simulate thousands of possible outcomes, allowing conservation managers to test different actions within the virtual ecosystem before any intervention takes place in the real world. The reintroduction of a predator, the restoration of a wetland, the planting of a woodland, or the removal of an invasive species—all could be explored safely in advance.

Crucially, the digital twin would not be static. As new data flows in from the real ecosystem, the model would be continuously refined. Each real-world outcome would feed back into the system, improving its accuracy and strengthening its predictions. Over time, this would create a dynamic feedback loop in which the AI becomes increasingly capable of understanding ecological complexity.

If we can build a digital twin of our ecosystems and use AI to explore the consequences of our actions before we take them we may finally begin to shift from reacting to environmental change to anticipating it.

The question is no longer whether such systems are possible. It is whether we can develop and deploy them quickly enough to make a difference before biodiversity loss reaches a point of no return.

My inbox is full of campaign emails asking for donations, volunteers, or other forms of support. The problem is that most of them fail to inspire action. They may be worthy causes, but their communications rarely make a convincing case for me to set aside a few hours or reach for my credit card. To separate the campaigns that truly deserve support from those that don’t, I have developed “The Supermarket Test.”

We are all busy juggling competing demands and priorities. As a result, campaign communications must be clear, concise, and immediately relevant to the interests of the audience they are trying to reach. But relevance alone is not enough. Effective communication must also inspire people to act. It must create a sense of urgency, importance, or personal connection that moves someone from simply reading the message to supporting the cause.

Picture a busy supermarket. Shoppers push overflowing trolleys through crowded aisles, shopping lists in hand, scanning shelves for elusive ingredients and trying to complete their weekly shop as quickly as possible. Now imagine approaching one of those shoppers and asking for a few minutes of their time to discuss an important issue that affects them. Your challenge is not simply to inform them about a campaign, but to persuade them to support it. In those few brief moments, you must explain why the issue matters, how it connects to a wider movement, why they should care, and what action you would like them to take. This is what I call the Supermarket Test.

A campaign passes the Supermarket Test if it can persuade someone to change their behaviour or take action in the middle of a busy, distraction-filled environment. If the message is too complicated, too abstract, or fails to connect with people’s immediate concerns, it will be ignored.

Consider a campaign aimed at improving public health by reducing the consumption of ultra-processed foods. You approach a shopper in a supermarket and, after gaining their attention, briefly explain the health risks associated with these products. If, after that short conversation, they put the item back on the shelf, the campaign has passed the Supermarket Test. It may seem like a high bar, but it demonstrates that the message was clear, relevant, persuasive, and capable of motivating immediate action. If I attempted this in my local supermarket, I have little doubt that security would soon be showing me the way out. Nevertheless, the principle still holds. The Supermarket Test can be applied wherever people are busy and their attention is in short supply.

Next time a campaign lands in your inbox, or you’re approached on the street by a fundraiser, ask yourself whether it passes The Supermarket Test. If it does, get involved. If it doesn’t, politely decline and move on.

AI is taking over many aspects of our lives, including creating works of art. Can this be true? Let’s go and knock on Alan Turing’s door and ask him.

Alan Turing, developed a test to answer the question: Can machines think? The test, called the Imitation Game, replaces the question with a practical test of intelligent behaviour. It involves a human judge who communicates (usually via text) with another human and a machine behind a wall. The judge asks questions and receives answers, and shape must determine which is the machine and which is the human. Although Turing’s test was about intelligent behaviour the same approach can be taken to test creativity. So let’s set up an experiment where you the reader are the judge, and you have to decide which of the following poems were written by AI.

Let’s start. At the end of each poem ask yourself: could this have been written by AI or a human? Here is the first one:

The poem captures the effect of Spring on the poet. Now for the next one:

This poem describes how the changes in the flora and fauna send signs that Spring has started. Finally,

Before you read on - stop for a few minutes and make your decision.

Which one was generated by AI? The first poem was written by Tom B, Year 6, who is showing early signs of being a fine poet. I hope that he is still writing. The last poem was by E E Cummings. He uses both form and format to depict spring as a gentle, precise, and creative force that subtly transforms the world, much like a hand rearranging a window display. The second poem was generated by AI, and its comes down to you and what it means to you. But I feel that the second poem lacks any depth compared to the other two.

It is nearly impossible to define what turns a few words laid out in a certain way into a poem. But a good poem should invoke an emotional response. The AI-generated poem put together words that describe spring; we don’t experience a moment in Spring that the others produce.

You may have picked the AI-generated poem; maybe not. But I hope that you agree that AI has a long way to go before it is labelled ‘creative’. If you are a budding poet, then keep writing; you will be ahead of AI for many years.

It is easy to look at the weather and conclude that climate change is happening. It seems to be getting either wetter or drier for longer periods of time. But drawing that conclusion would cause the philosopher Aristotle to shake his head in disapproval.

Let’s look at an example to find out what is frustrating Aristotle. We know that if it rains, the pavement gets wet. We walk outside one day and see that the pavement is wet; therefore, we conclude that it has rained. But this is where the argument goes wrong. The ground might be wet because we live next door to a keen gardener and their sprinkler was on, or another neighbour has washed their car, or worse, a water pipe leaked; there are any number of other reasons.

If we take a similar approach with linking climate change and the weather. We could follow the following reasoning:

• If greenhouse-gas–driven climate change is happening, we will see more extreme weather,
• We see extreme weather,
• Therefore, greenhouse-gas–driven climate change is happening.

But there could be other reasons. The climate can be influenced by solar changes, volcanic eruptions, ocean cycles, orbital variations and land-use changes. Climate scientists are well aware of this and take a different approach to avoid the mistaken argument.

Returning to the example. We walk outside and see that the pavement is wet. The possible causes are that it has rained, the neighbour’s sprinkler was on, or someone has washed their car. Rather than jumping to a conclusion, we should ask, “How likely is each possible cause?” Before seeing the pavement, our expectations are that it is fairly likely that it had rained, less likely that a sprinkler was on, and somewhere in between that a car had been washed. Then ask: How well does each cause explain the wet pavement? If it rained, a wet pavement is very likely. If a sprinkler were on, it would also be quite likely. If someone washed a car, maybe only part of the pavement is wet.

After seeing the wet pavement, you might reason; rain is still the most likely, because we live in a wet part of the country, and therefore it was already fairly likely and strongly explains the wet pavement. A sprinkler becomes possible, especially if you know that your neighbour is a keen gardener. Car washing becomes less likely unless we see other clues (like soap or a hose). This approach is not asking, “What could cause this?” but asking, “Which cause is most likely given both my prior knowledge and the evidence?”

Climate science does not rely on one heatwave, one storm or one flood to draw conclusions about the effect of climate change on the weather. Instead, they use: long-term statistical patterns, multiple independent lines of evidence, and quantitative physical models. They combine all of this evidence to give a probabilities that climate change is influneced by human activity compared to other effects. For example, since 2017 about 93% of extreme heat events studied showed that climate change made them more likely or more severe. For the 126 rainfall or flooding events studied, 56% found human activity had made the event more likely or more severe, for the 81 drought events it’s 68%.

To cut through the noise from the socials about weather and climate change why don’t you look at the global studies at Carbon Brief, where accurate science is carried out, and then make your own mind up. That would get a thumbs up from Aristotle.

The best summary of the benefits from reading is in a book about managing a football team. Reading the list of benefits, a question sprung to mind - can reading books improve mental health?

In Marcelo Bielsa: The Foundation of Success at Leeds United, which describes the background to their 2018/19 season, Salim Lamrani writes: “The benefits of reading are many, as it develops intelligence, consolidates memory, strengthens concentration, stimulates imagination, enriches vocabulary, improves knowledge, increases communication skills, spreads culture, strengthens reflection and analytical skills, reduces stress levels, contributes to the opening of the mind, and the development of sensitivity and empathy, represents an accessible mode of distraction and brings happiness”. Some of the players were surprised by the idea while others were regular readers, but they were all willing to take part. The reading activity was integrated into the player’s weekly schedule.

Reading can reduce stress by focusing on a story, ideas, or knowledge, which shifts the mind away from stressful thoughts. It also allows temporary experience in another world. For example, reading a novel lets the imagination explore different places, lives, and problems, which gives a break from immediate concerns and helps the mind reset. Reading, especially slower forms like novels or essays, encourages deep focus, which has the opposite effect of fast digital stimulation, and allows the mind to move into a calmer state, similar to meditation. Stories often help people process emotions indirectly by identifying with characters who face loss, conflict, and uncertainty. This helps people understand and regulate their own feelings. Also, reading improves understanding which strengthens the mind’s ability to control behaviour, emotions, and thoughts, and helps to manage stress and emotional reactions.

Ongoing research is being carried into the benefits for mental health and well-being. For example, the National Institute for Health and Care Research has researched the impact of reading as part of a group. Other initiatives such as Reading for Wellbeing, funded by the best-selling crime fiction author Ann Cleeves, facilitate access to books and support reading for pleasure to improve well-being. More articles are appearing that describe the benefits of book clubs, such as increasing social connection, which combats loneliness.

Leeds United were promoted at the end of the 2019/20 season. Hopefully, reading books as part of their training schedule played a small part in their success. Joining a reading group could be prescribed by GPs and included as part of the revamped NHS’ Integrated Care Systems?