Quantifying the Resilience and Functioning of Freshwater Ecosystems Across Spatial and Temporal Gradients of Environmental Stress

How natural and semi-natural systems will adapt to extreme events as our climate changes remains a pressing question in ecology. Ecosystems are highly sensitive to multiple, and often interacting, environmental pressures, such as agricultural intensification and climate change, which vary in distribution and intensity across spatiotemporal scales, and with regional variations (e.g. geo-climate).

This can result in impacts, which alters both the structural and functional properties of the ecosystems. Consequently, this places ecosystems under significant stress, reducing ecosystem services. The capacity of an ecosystem to deal with stress is finite, and consequently they are predicted to undergo regime shifts when the adaptive capacity of the system is exceeded, although recent studies demonstrate a lack of empirical evidence for such shifts (Hillebrand et al. 2020).

This project will focus on the capacity of lotic systems to absorb, adapt and recover from episodic disturbances across a gradient of environmental stress and community resilience.

The project is a CASE studentship in collaboration with the Agri-Food and Biosciences Institute (AFBI) in Northern Ireland and will experimentally quantify and assess the relative merits of different measures of ecological resilience (Holling 1973) and multiple measures of ecological stability (Donohue et al. 2013).

This project, therefore, offers the opportunity to evaluate the mechanisms that underpin variation in ecological stability and will attempt to quantify empirically species-specific contributions to multiple measures of stability including variability, resistance and recovery (engineering resilience). Emphasis will be placed on freshwater invertebrate and benthic biofilm community structure, with a focus on quantifying species interactions, and both functional (e.g. body mass, trophic level and trophic role) and structural properties (e.g. abundances and richness) to support a fundamental exploration of different stability concepts and their relevance in applied management.