Forecasting in the face of ecological complexity: Number and strength of species interactions determine forecast skill in ecological communities,Ecology Letters

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Forecasting in the face of ecological complexity: Number and strength of species interactions determine forecast skill in ecological communities
Ecology Letters ( IF 7.6 ) Pub Date : 2022-07-13 , DOI: 10.1111/ele.14070
Uriah Daugaard ₁ , Stephan B Munch ₂ , David Inauen ₁ , Frank Pennekamp ₁ , Owen L Petchey ₁

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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.

中文翻译：

面对生态复杂性的预测：物种相互作用的数量和强度决定了生态群落的预测技能

目前尚不清楚预测生态系统动态的潜力，由于生态复杂性，其可行性存在不同意见。为了研究系统内和系统间的预测技能，我们在为期 5 个月的实验室实验中监测了暴露于恒定或波动温度的微生物系统。我们测试了物种丰度的预测如何取决于相互作用的数量和强度以及模型大小（预测变量的数量）。我们还测试了更高的系统复杂性（即波动的温度）如何影响这些关系。我们发现一个物种的相互作用越多，这些相互作用就越弱，预测的丰度就越好。预测技能随着模型大小的增加而增加。更大的系统复杂性降低了八分之三的预测技能。

更新日期：2022-07-13

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