# Multiple stressors

Organisms face a range of natural stressors, including food scarcity and predation, as well as anthropogenic stressors like pesticides. The combined effects of these stressors can be additive, but they often interact synergistically, leading to potentiation. Consequently, accurately predicting the joint impact of multiple stressors is of critical importance.

## Cause

Species are adapted to specific environmental conditions, but this adaptation is never absolute. The further environmental factors deviate from the optimal range for a given species, the more these factors become stressors. Global change—characterized by phenomena such as global warming, pesticide contamination, and shifts in land use—is accelerating these changes. Consequently, an increasing number of species are being subjected to a growing intensity and diversity of anthropogenic stressors.

## Predictive Models

Predicting the effects of multiple stressors is crucial for risk assessment and the effective management of anthropogenic influences. A range of predictive models is available, each tailored to the specific characteristics of the combined stressors. Three widely validated models provide robust frameworks for understanding and predicting the combined effects of multiple stressors, enabling informed decisions in environmental management and policy:
* Concentration Addition Model (CA) - The cumulative effect of stressors or toxicants with similar modes of action is captured by the concentration addition model. This model assumes that the stressors are interchangeable and that their combined effect can be calculated through a shared cause-effect relationship. For example, the combined impact of wine and hard liquor can be predicted based on their alcohol content: both exert their effects through alcohol, and their total impact is determined by summing their individual contributions in a common cause-effect framework.
* Stress Addition Model (SAM) - The cumulative impact of non-similarly acting stressors is described by the Stress Addition Model. SAM operates on the principle that each organism has a finite “general stress capacity,” encompassing all types of stress. Once this capacity is exceeded, the organism cannot survive. The total “general stress” is the sum of specific stress levels imposed by independent stressors. For instance, the combined effect of food scarcity and pesticide exposure can be predicted if the mortality rates for each stressor are known.
* Effect Addition Model (EA) - When stressors have independent effects, the probabilistic summation of their impact is described by the Effect Addition model. EA calculates the additive impact of two stressors by subtracting the product of their individual effects from the sum of their individual mortalities. This approach accounts for the fact that an organism affected by stressor A cannot also be impacted by stressor B after its demise. An example is repeated fishing in a pond: in the first net haul, a portion of the fish population is removed. In the second haul, another portion is removed from the remaining fish, assuming the vitality of the fish is unaffected by the initial haul and that the effects are independent.

## Synergistic and Antagonistic Effects

The presence of multiple stressors can result in synergistic or antagonistic effects on individuals. These effects, however, can only be accurately assessed when compared to an appropriate null model. A common and effective choice is the Effect Addition Model, which assumes the stressors act independently. This model serves as a parsimonious null hypothesis because it avoids making assumptions about nonlinear interactions between stressors.
Using effect addition as a null model has revealed that the combined effects of environmental stressors and toxicants often exhibit strong synergy. This synergy significantly increases individual sensitivity to toxicants, with susceptibility amplifying by a factor of 10 to 100 depending on the intensity of co-occurring environmental stressors. This highlights the critical need to account for such interactions when assessing risks and developing mitigation strategies.