Rethinking ecological networks in changing environments
Modern science has presented us with a wealth of information for understanding biodiversity, including excellent predictive models of the environment, climate, and population dynamics. Yet, while ecologists are good at homing in on different parts of ecosystems, we are often less proficient at understanding the shared dynamics of entire ecosystems. Connecting these different ecosystem sectors and unravelling complex high-dimensional data remains a major challenge for both basic and applied ecology. Network thinking can address both of these challenges.
The environmental template on which ecological interaction networks, or the web of biotic interactions among organisms, assemble and persist is being rapidly altered via global climate and land-use change. Organisms respond to fundamentally different frequencies in environmental fluctuations, such as diurnal light cycles, tides, seasonality and decadal climatic cycles. Yet, while we know just how context dependent species interactions are in both time and space, much of our understanding of ecological networks emerges from snapshots. Networks comprise species-specific responses to environmental fluctuations and interspecific interactions between species. These interactions may amplify or dampen environmental signal and noise. Thus, we cannot understand and predict how a network will respond to changing environmental regimes without understanding time-varying responses and interactions. This presents a critical need for ecology.
Rather than relying on observations of fleeting interactions or preconceived notions of how species interact, I propose a fundamentally different way of thinking that relies on coupling detailed natural history (field- and experimentally-derived vital rates of how species interact with their environment) with mechanistic models to generate understanding of networks under fluctuating environmental conditions. Instead of incorporating biotic interactions at the outset, they emerge from the model itself under different environmental contexts, thereby representing a completely new way of understanding and quantifying networks in fluctuating environments. The advances to our understanding of ecological networks provided by this research agenda will enable better prediction and management of entire ecosystems in future climate settings where natural cycles in the environment are disrupted.
Beyond developing new theory on networks in changing environments, I will employ this newly-derived modelling framework to: 1. quantify how targeted management interventions under uncertain environmental futures propagate through entire ecosystems, including interactions among species, with specific focus on the American Southwest and New Zealand; 2. disentangle how different frequencies of environmental fluctuations interact with the spatial scale at which species move to generate new insight into ecosystem stability under global change—an issue of fundamental importance for humanity moving forward; and 3. use global datasets to deconstruct the role of both natural and human-altered environmental fluctuations on species coexistence and interaction networks across broad spatial and temporal scales. My proposed research programme spans multiple sub-fields of ecology in taking a high-level quantitative view of entire ecosystem dynamics in space and time—something that is rarely achieved in a mechanistic and predictive manner. This research has the potential to change the way we think about communities, ecosystems and ecological networks, how we develop biodiversity theory, and how we manage ecosystems under global change.
Link to project summary here.