Quantifying Novel Ecosystems

The concept of “novel ecosystems” is becoming increasingly prominent in the scientific literature concerning ecology and conservation in the Anthropocene. However, the literature reveals several inconsistent and qualitative framings of the “novel ecosystems” concept, hindering systematic efforts to study or address novel ecosystems. This dissertation quantifies novelty in ecosystems and develops a methodology to identify and predict the emergence of novel ecosystems in dynamic landscapes.

Previous attempts to define novelty have not been widely accepted in the scientific community, impeding its practical application in conservation. The project assessed previous methods to identify their strengths and weaknesses, aiming to develop a new method for successfully quantifying novelty.

Building on the findings from the previous methods, two rigorous metrics were developed. Firstly, we tested a method based on calculating dissimilarity between variables associated with novelty at two time periods to get a total novelty score. A second method using Euclidean distance in principal components analysis (PCA) was developed to measure temporal and spatial novelty by calculating distances between points in PCA space. Crucially, both methods involve biotic and abiotic factors.

Applying these metrics in the United Kingdom (UK) context using data from the British Trust for Ornithology (BTO), AVONET, the UK Centre for Ecology and Hydrology (UK CEH) and the Centre for Environmental Data Analysis (CEDA) across a time scale spanning 1968 to 2011 showed how abiotic and biotic novelty do not reflect the same spatial or temporal patterns. This is demonstrated in another application using data from the Global Biodiversity Information Facility (GBIF) and lepidoptera traits, showing the method’s reproducibility and reliability.

Overall, I advocate for the use and further development of the PCA method to quantify ecological novelty, incorporating both abiotic and biotic variables whilst maintaining flexibility in its application to different scenarios.