We know that biodiversity is changing, and we can identify trends and directions in this change. In some cases we can attribute these to factors such as climate change, agricultural expansion, urbanization or pollution, but the underlying causes of change are rarely clear and simple. Many factors interact to cause the changes we see, and the results may be unpredictable.
In order to respond effectively to negative changes, we need to know what causes them. If ecosystem health is declining, what are the most important drivers of that change? How will those drivers interact and manifest themselves over time? Will declines continue to be gradual, or are there tipping points, beyond which irreversible change occurs?
To answer such questions we use sophisticated models to recreate the dynamics and causality of biodiversity change. This enables us to understand where we are now and to extrapolate ahead to the future, in order to predict the likely causes and results of change over time.