Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data

Abstract: Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly to conduct precise monitoring on a large scale, leaving most lakes unmonitored or only partially monitored. The challenge is hence to build a predictive model that can use the incomplete, partially‐monitored data to make near‐future CB predictions. By using 30 years of monitoring data for 78 water bodies in Alberta, Canada, combined with data of watershed characteristics (including natural land cover and anthropogenic land use) and meteorological conditions, we train a Bayesian network that predicts future 2‐week CB with an area under the curve (AUC) of 0.83. The only monitoring data that the model needs to reach this level of accuracy are whether the cell count and Secchi depth are low, medium, or high, which can be estimated by advanced high‐resolution imaging technology or trained local citizens. The model is robust against missing values as in the absence of any single covariate, it performs with an AUC of at least 0.78. While taking a major step toward reduced‐cost, less data‐intensive CB forecasting, our results identify those key covariates that are worth the monitoring investment for highly accurate predictions

When and why ecological systems respond to the rate rather than the magnitude of environmental changes

Ecologists and conservation biologists have become quite familiar with the concept of tipping points: abrupt changes in an ecosystem's state that occur after a period of relative stasis. Most of the familiar ecological examples of tipping points occur either because a once-stable state has lost stability, or the system has been subjected to a particularly large perturbation and transitions to an alternative stable state, distinct from the pre-perturbed state. A different class of tipping points, known as rate-induced tipping (or r-tipping) points, are likely present in many ecological communities but remain little known in the field. Rate-induced tipping occurs when an environmental change is too fast for the community to track; even though the original state never loses stability, the ecological response to the change is too slow to remain in that stable state's basin of attraction. R-tipping is part of the broader phenomenon of rate dependence that arises because ecological systems cannot respond instantaneously to external changes. In this article, we provide a non-technical introduction to the theory of rate dependent responses to change, discuss the implications of this theory to conservation problems, and illustrate its application through a series of case studies. When a tipping point is rate dependent, effective management relies not only on the type of intervention used but also the rate at which it is applied. Our work highlights how a mechanistic understanding of different types of tipping points leads to stronger guidance on when, where, and how different interventions can used to achieve conservation goals.</p

When and why ecological systems respond to the rate rather than the magnitude of environmental changes

Ecologists and conservation biologists have become quite familiar with the concept of tipping points: abrupt changes in an ecosystem's state that occur after a period of relative stasis. Most of the familiar ecological examples of tipping points occur either because a once-stable state has lost stability, or the system has been subjected to a particularly large perturbation and transitions to an alternative stable state, distinct from the pre-perturbed state. A different class of tipping points, known as rate-induced tipping (or r-tipping) points, are likely present in many ecological communities but remain little known in the field. Rate-induced tipping occurs when an environmental change is too fast for the community to track; even though the original state never loses stability, the ecological response to the change is too slow to remain in that stable state's basin of attraction. R-tipping is part of the broader phenomenon of rate dependence that arises because ecological systems cannot respond instantaneously to external changes. In this article, we provide a non-technical introduction to the theory of rate dependent responses to change, discuss the implications of this theory to conservation problems, and illustrate its application through a series of case studies. When a tipping point is rate dependent, effective management relies not only on the type of intervention used but also the rate at which it is applied. Our work highlights how a mechanistic understanding of different types of tipping points leads to stronger guidance on when, where, and how different interventions can used to achieve conservation goals.</p

Stoichiometric Ecotoxicology for a Multisubstance World

Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology