Forecasting in the face of ecological complexity: Number and strength of species interactions determine forecast skill in ecological communities. (13th July 2022)

• Record Type: Journal Article
• Authors: Daugaard, Uriah; Munch, Stephan B.; Inauen, David; Pennekamp, Frank; Petchey, Owen L.
• Is Part Of: Ecology letters. Volume 25:Number 9(2022)
• Page Start: 1974
• Page End: 1985
• Publication Date: 2022-07-13
• Subjects: community ecology -- complexity -- ecological forecasting -- empirical dynamic modelling -- experiment -- food webs -- interaction strength -- microbial community -- prediction -- temperature; Ecology -- Periodicals; 577
• DOI: 10.1111/ele.14070
• Languages: English
• ISSNs: 1461-023X

Abstract

Abstract: The potential for forecasting the dynamics of ecological systems is currently unclear, with contrasting opinions regarding its feasibility due to ecological complexity. To investigate forecast skill within and across systems, we monitored a microbial system exposed to either constant or fluctuating temperatures in a 5‐month‐long laboratory experiment. We tested how forecasting of species abundances depends on the number and strength of interactions and on model size (number of predictors). We also tested how greater system complexity (i.e. the fluctuating temperatures) impacted these relations. We found that the more interactions a species had, the weaker these interactions were and the better its abundance was predicted. Forecast skill increased with model size. Greater system complexity decreased forecast skill for three out of eight species. These insights into how abundance prediction depends on the connectedness of the species within the system and on overall system complexity could improve species forecasting and monitoring. Abstract : We investigated how forecasting of species abundances depends on the number and strength of interactions and on system complexity by carrying out a five‐month long laboratory experiment involving a microbial communities exposed to constant or fluctuating temperatures. We found that the more interactions a species had, the weaker these interactions were and the better its abundance was predicted, and that increasing the system complexity (i.e. adding the fluctuating temperatures) decreased the forecast skill for three out of eight species. These insights into how abundance prediction depends on the connectedness of the species within the system and on overall system complexity could improve species forecasting and monitoring.