Alternative stable states explain unpredictable biological control of Salvinia molesta in Kakadu

Abstract

Suppression of the invasive plant Salvinia molesta by the salvinia weevil is an iconic example of successful biological control. However, in the billabongs (oxbow lakes) of Kakadu National Park, Australia, control is fitful and incomplete. By fitting a process-based nonlinear model to thirteen-year data sets from four billabongs, here we show that incomplete control can be explained by alternative stable states--one state in which salvinia is suppressed and the other in which salvinia escapes weevil control. The shifts between states are associated with annual flooding events. In some years, high water flow reduces weevil populations, allowing the shift from a controlled to an uncontrolled state; in other years, benign conditions for weevils promote the return shift to the controlled state. In most described ecological examples, transitions between alternative stable states are relatively rare, facilitated by slow-moving environmental changes, such as accumulated nutrient loading or climate change. The billabongs of Kakadu give a different manifestation of alternative stable states that generate complex and seemingly unpredictable dynamics. Because shifts between alternative stable states are stochastic, they present a potential management strategy to maximize effective biological control: when the domain of attraction to the state of salvinia control is approached, augmentation of the weevil population or reduction of the salvinia biomass may allow the lower state to trap the system.

Detecting dynamical changes in nonlinear time series using locally linear state‐space models

“…If sufficient information exists about a system, a potentially better strategy is to fit system-specific, nonlinear, biologically explicit models in order to investigate the possibility of alternative states (e.g., Ives et al 2008, Schooler et al 2011). This typically requires time series that are rich in dynamical patterns taken from systems that are biologically well-understood.…”

Evidence of alternate attractors from a whole-ecosystem regime shift experiment

“…The strong empirical evidence from laboratory experiments (Schröder et al 2005) proves the potential for multiple attractors in ecological systems. In field settings, statistical comparisons of mechanistic models with and without alternative attractors have proven a powerful means of testing for multiple attractors in ecosystems when long-term data are available (Carpenter and Pace 1997;Carpenter 2003;Scheffer and Carpenter 2003;Mumby et al 2007;Ives et al 2008;Schooler et al 2011). Thus, the consistency of models and data in long-term observational studies represents the primary evidence for multiple attractors in ecosystems.…”

A large herbivore triggers alternative successional trajectories in the boreal forest

“…AST can come about in at least two ways: (1) through competitive effects of certain colonizers (initial floristic composition, sensu Egler 1954) that inhibit the recruitment of other species and (2) through local extirpation of a key constituent of the ''normal'' successional trajectory. Hence, for a given set of abiotic parameters, AST may lead to vastly different alternative states, as observed in aquatic systems (van Geest et al 2007, Schooler et al 2011, savannas (Seymour et al 2010), and tropical forests (Norden et al 2011). In a system where multiple alternative states potentially exist, herbivores may not only slow down or accelerate succession; but also they may change the direction of succession through their effect on key plant species (Seabloom andRichards 2003, Baskett andSalomon 2010).…”