Accounting for species interactions is necessary for predicting how arctic arthropod communities respond to climate change

TY - JOUR

T1 - Accounting for species interactions is necessary for predicting how arctic arthropod communities respond to climate change

AU - Abrego, Nerea

AU - Roslin, Tomas

AU - Huotari, Tea

AU - Ji, Yinqiu

AU - Schmidt, Niels Martin

AU - Wang, J.

AU - Yu, Douglas W

AU - Ovaskainen, Otso

PY - 2021/6

Y1 - 2021/6

N2 - Species interactions are known to structure ecological communities. Still, the influence of climate change on biodiversity has primarily been evaluated by correlating individual species distributions with local climatic descriptors, then extrapolating into future climate scenarios. We ask whether predictions on arctic arthropod response to climate change can be improved by accounting for species interactions. For this, we use a 14-year-long, weekly time series from Greenland, resolved to the species level by mitogenome mapping. During the study period, temperature increased by 2°C and arthropod species richness halved. We show that with abiotic variables alone, we are essentially unable to predict species responses, but with species interactions included, the predictive power of the models improves considerably. Cascading trophic effects thereby emerge as important in structuring biodiversity response to climate change. Given the need to scale up from species-level to community-level projections of biodiversity change, these results represent a major step forward for predictive ecology.

AB - Species interactions are known to structure ecological communities. Still, the influence of climate change on biodiversity has primarily been evaluated by correlating individual species distributions with local climatic descriptors, then extrapolating into future climate scenarios. We ask whether predictions on arctic arthropod response to climate change can be improved by accounting for species interactions. For this, we use a 14-year-long, weekly time series from Greenland, resolved to the species level by mitogenome mapping. During the study period, temperature increased by 2°C and arthropod species richness halved. We show that with abiotic variables alone, we are essentially unable to predict species responses, but with species interactions included, the predictive power of the models improves considerably. Cascading trophic effects thereby emerge as important in structuring biodiversity response to climate change. Given the need to scale up from species-level to community-level projections of biodiversity change, these results represent a major step forward for predictive ecology.

KW - Arctic

KW - Arthropoda

KW - climate change

KW - community assembly

KW - food web

KW - joint species distribution model

KW - trophic cascade

UR - http://www.scopus.com/inward/record.url?scp=85102845313&partnerID=8YFLogxK

U2 - 10.1111/ecog.05547

DO - 10.1111/ecog.05547

M3 - Journal article

SN - 0906-7590

VL - 44

SP - 885

EP - 896

JO - Ecography

JF - Ecography

IS - 6

ER -