Course aim

To build the next generation of interdisciplinary professionals in biodiversity informatics, with the ability to make an informed decision to pursue a career path in biodiversity or bio-mathematics research.

Course Outcomes

• Awareness of key mathematical concepts applied to analysis of biodiversity data.
• Understanding of key ecological concepts such as competition, mutualism, stability.
• Awareness and understanding of different kinds of biodiversity data (as classified in the Essential Biodiversity Variables concept).
• Knowledge of availability of data on Essential Biodiversity Variables (EBVs) from freely available and restricted databases
• Ability to synthesize data to create a biodiversity database.
• Ability to apply R programming skills to process and analyse biodiversity data, in particular ecological network analyses and species distribution modelling.

Scope

The United Nation’s Sustainable Development Goal #15 calls for the ‘Protection, restoration and promotion of a sustainable terrestrial ecosystem, sustainable management of forests, to combat desertification, a halt and reversal of land degradation and a halt of biodiversity loss by the year 2030 (https://sdgs.un.org/).  Over 31 000 species are currently at risk of extinction, and this is occurring at an even faster rate that before. 

Anthropogenic activities and climate change are major threats to our ecosystem. Climate for instance is promoting biome shifts for many plants and animal species. At the same time, the climate is exacerbating antagonistic plant interactions which are caused by pathogens and pests. Along with anthropogenic activites, climate is also influencing mutalistic plant interactions such as plant-insect pollination which is important to over 70% of known plant species. Most of these plants produce the food which we consume.

The successful attainment of the SDG #15 would trigger the success of several other SDGs such as zero hunger (goal #2), clean water and sanitation (goal #6), climate action (goal # 13) among others. This is so because our ecosystem (agro, forest, grassland or aquatic) provides essential services which mankind benefits from. These services include (i) supporting services, e.g. nutrient recycling,  primary production and soil formation; (ii) provisioning services e.g. food, crops, raw materials, organic matter, fodder, fertilizer, genetic resources, water, biogenic minerals, medicinal resources, energy; (iii) regulating services e.g. pollination, carbon sequestration, climate regulation, waste decomposition, detoxification, water purification, air purification, pest and disease control; and (iv) cultural services e.g. therapeutic, spiritual, recreational, educational, science (MA, 2005).

The importance to fully understand, monitor and regulate ecosystems can therefore not be overstated. This requires a constant and comprehensive documentation of components in the system, how sub-units interact internally and with the whole, the changes occurring over time and space, drivers that alter their structure, how their distribution is affected and how this evidence could be used for decision making. The advent of computing is now playing a critical role to provide deep insights in the field of biodiversity in a cost- and time-effective manner. This creates a transdisciplinary space where biologists, mathematicians, computer scientists, policy makers, industy and the community can collaborate to generate research-driven solutions to conserve and sustain our ecosystems.  Building a critical mass of such interdisciplinary professionals is paramount.