Thu, Aug 05, 2021:On Demand
Background/Question/Methods
Food web stability and resilience are at the heart of understanding the structure and functioning of ecosystems. Previous studies show that models of empirical food webs are substantially more stable than random ones, due to a few strong interactions embedded in a majority of weak interactions. Analyses of trophic interaction loops show that in empirical food webs the patterns in the interaction strengths prevent the occurrence of destabilizing heavy loops and thereby enhances resilience. Yet, it is still unexplored which biological mechanisms cause these patterns that enhance food web resilience. We quantified food web resilience using the real part of the maximum eigenvalue of the Jacobian matrix of the food web from a seagrass bed in the Yellow River Delta (YRD) wetland, that could be parameterized by the empirical data of the food web.
Results/Conclusions We found that the empirically based Jacobian matrix of the YRD food web indicated a much higher resilience than random matrices with the same element values but arranged in random ways. Investigating the trophic interaction loops revealed that the high resilience was due to a negative correlation between the negative and positive interaction strengths (per capita top-down and bottom-up effects, respectively) within positive feedback loops with three species. The negative correlation showed that when the negative interaction strengths were strong the positive was weak, and vice versa. Our invented reformulation of loop weight in terms of biomasses and specific production rates showed that energetic properties of the trophic groups in the loop and mass-balance constraints, e.g. the food uptake has to balance all losses, created the negative correlation between the interaction strengths. This result could be generalized using a dynamic intraguild predation model, which delivered the same pattern for a wide range of model parameters. Our results shed light on how energetic constraints at the trophic group and food web level create a pattern in interaction strengths within trophic interaction loops that enhances food web resilience.
Results/Conclusions We found that the empirically based Jacobian matrix of the YRD food web indicated a much higher resilience than random matrices with the same element values but arranged in random ways. Investigating the trophic interaction loops revealed that the high resilience was due to a negative correlation between the negative and positive interaction strengths (per capita top-down and bottom-up effects, respectively) within positive feedback loops with three species. The negative correlation showed that when the negative interaction strengths were strong the positive was weak, and vice versa. Our invented reformulation of loop weight in terms of biomasses and specific production rates showed that energetic properties of the trophic groups in the loop and mass-balance constraints, e.g. the food uptake has to balance all losses, created the negative correlation between the interaction strengths. This result could be generalized using a dynamic intraguild predation model, which delivered the same pattern for a wide range of model parameters. Our results shed light on how energetic constraints at the trophic group and food web level create a pattern in interaction strengths within trophic interaction loops that enhances food web resilience.