A probabilistic methodology to reconstruct biodiversity from implicit interactions with indicator species along latitudinal co-occurrence networks

Abstract

The relationship between species presence, biodiversity reconstruction, and latitudinal gradients is a complex and multifaceted topic that has been the subject of extensive research in ecology. Recent studies have provided valuable insights into the patterns and drivers of these phenomena. Also, with the ongoing decline in biodiversity, there is a need for efficient field monitoring techniques. Indicator species (IS) emerged as a promising tool to monitor diversity because their presence indicates a maximum number of conditionally co-occurring species. We aim to assess the effectiveness of IS for biodiversity reconstruction implicitly based on their co-occurrence with other species through a network-based methodology. The IS are identified based on various network metrics and the likelihood of species occurrences is computed based on (1) their conditional occurrence probability with IS and (2) the occurrence probability of IS. We test the approach with field observations of birds in the Cote-Nord region of Quebec. From our methodology, the climate latitudinal gradient plays a significant role on the alternation in composition of IS with an almost complete turnover between northern and southern networks. The latitudinal gradient impacts also the nature of the inter-specific interactions with more avoidance relationship toward the Tropics and more cooperation liaisons toward the north. Regarding the effectiveness in the reconstruction of assemblages occurrence, we observe a strong negative correlation (r [≤] -0.95) between the percentage of sites occupied and the dissimilarity between the original and the estimated occurrences. More precisely, species must be present in more than 29% and 33% of northern and southern sites to recover well from its co-occurrence with IS. Therefore, it is more challenging to reconstruct biodiversity in communities closet to Tropics due to higher complex interactions and interspecific competition in these areas, which make it more difficult to infer community composition. In conclusion, our method demonstrates that it is possible to predict local species assemblages based on their implicit interactions with local IS. Nevertheless, the relatively low success of less present species illustrates the need for further theoretical development to reconstruct biodiversity, mainly to recover the occurrence of rare species.