Peer-review publication has become a standard vessel for sharing the knowledge gained in scientific research, with its number increasing exponentially in the recent decades. To this end, robust statistical methods that allow us to synthesize and generalize these knowledge points in published literature, and to develop and test overarching hypotheses, are urgently needed. We here use a meta-analysis and test a few hypotheses on the influence of climate change on biodiversity maintenance in regional ecosystems. Based on the work by Hans van Houwelingen and colleagues in 2002, we developed a maximum likelihood estimate of parameter in random and mixed effect models. This approach was then applied to a real dataset collected from published literature of the impact of ambient temperature increase on species performance. We found that in general, the current and predicted temperature is negatively affecting different species independently of localities. Some taxonomic groups are negatively affected by temperature rise whilst others seem to be robust to the temperature change. Species richness and suitable habitat were found to be the most sensitive species attributes to temperature rise. We classified the methodology used by studies from which we extracted the data in two main groups: observation and modelling. We found that the modelling approach exaggerates the reality found from the observations. The main focus of this study was to add another layer of knowledge on the loss of biodiversity due to climate change, thereby showing that if nothing is done to stabilize the increase of temperature, the current species taxa tolerant to a temperature rise will also be vulnerable, therefore more loss of biodiversity can be expected toward the end of this century.

Submitted in fulfilment of a Masters degree.