Abstract Resilience is broadly understood as the ability of an ecological system to resist and recover from perturbations acting on species abundances and on the system's structure. However, one of the main problems in assessing resilience is to understand the extent to which measures of recovery and resistance provide complementary information about a system. While recovery from abundance perturbations has a strong tradition under the analysis of dynamical stability, it is unclear whether this same formalism can be used to measure resistance to structural perturbations (e.g. perturbations to model parameters).Here, we provide a framework grounded on dynamical and structural stability in Lotka–Volterra systems to link recovery from small perturbations on species abundances (i.e. dynamical indicators) with resistance to parameter perturbations of any magnitude (i.e. structural indicators). We use theoretical and experimental multispecies systems to show that the faster the recovery from abundance perturbations, the higher the resistance to parameter perturbations.We first use theoretical systems to show that the return rate along the slowest direction after a small random abundance perturbation (what we call full recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before losing any species (what we call full resistance). We also show that the return rate along the second fastest direction after a small random abundance perturbation (what we call partial recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before at most one species survives (what we call partial resistance). Then, we use a dataset of experimental microbial systems to confirm our theoretical expectations and to demonstrate that full and partial components of resilience are complementary.Our findings reveal that we can obtain the same level of information about resilience by measuring either a dynamical (i.e. recovery) or a structural (i.e. resistance) indicator. Irrespective of the chosen indicator (dynamical or structural), our results show that we can obtain additional information by separating the indicator into its full and partial components. We believe these results can motivate new theoretical approaches and empirical analyses to increase our understanding about risk in ecological systems.
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Assessing Community College Biology Student Perceptions of Being Called on in Class
In a large ( n =383) mixed methods study in a community college, students in classes that use warm random call report benefits (e.g., engagement, eustress) and drawbacks of being called on (e.g., distress, anxiety), and perceive more peer interaction. This urges continued investigation of warm random call and possible context-dependent effects.
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- Award ID(s):
- 1730130
- PAR ID:
- 10482726
- Editor(s):
- Tanner, Kimberly
- Publisher / Repository:
- American Society for Cell Biology
- Date Published:
- Journal Name:
- CBE—Life Sciences Education
- Volume:
- 22
- Issue:
- 4
- ISSN:
- 1931-7913
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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