Climate change is causing marked shifts to historic environmental regimes, including increases in precipitation events (droughts and highly wet periods). Relative to droughts, the impacts of wet events have received less attention, despite heavy rainfall events increasing over the past century. Further, impacts of wet and dry events are often evaluated independently; yet, to persist and maintain their ecosystem functions, plant communities must be resilient to both precipitation events. This is particularly critical because while community properties can modulate the resilience (resistance, recovery, and invariability) of ecosystem functions to precipitation events, community properties can also respond to precipitation events. As a result, community responses to wet and dry years may impact the community's resilience to future events. Using two decades (2000–2020) of annual net primary productivity data from early successional grassland communities, we evaluated the plant community properties regulating primary productivity resistance and recovery to contrasting precipitation events and invariability (i.e. long‐term stability). We then explored how resilience‐modulating community properties responded to precipitation. We found that community properties—specifically, evenness, dominant species (
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.
- Award ID(s):
- 2024349
- PAR ID:
- 10445756
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Animal Ecology
- Volume:
- 90
- Issue:
- 9
- ISSN:
- 0021-8790
- Page Range / eLocation ID:
- p. 2027-2040
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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