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CR prepress abstract   -  DOI:

Direct and indirect effects of environmental drivers on reindeer reproduction

John-André Henden*, Torkild Tveraa, Audun Stien, Jarad Pope Mellard, Filippo Marolla, Rolf Anker Ims, Nigel Gilles Yoccoz

*Corresponding author:

ABSTRACT: The impact of climate change on the dynamics of populations has been documented and is widespread. However, weather variability influences populations both directly and indirectly and is mediated by species interactions. This complexity may impede proper climate impact assessments. Hence, predicting the consequences of climate change may require including processes that occur both with time lags and across trophic levels. Based on our current understanding of the mechanisms linking local climate and trophic interactions in tundra ecosystems, we used a state-space formulation of a mediation model that allowed for assessing the relative contribution of direct and indirect environmental (weather and trophic) effects on reindeer (Rangifer tarandus) reproductive success. Our study shows that mediator effects of body condition cause delayed, but predictable effects of weather, plant productivity and reindeer densities on reproductive success. Furthermore, these predictors also affected reproductive success directly and with the same sign, suggesting that direct and indirect effects pulled in the same direction with respect to their combined total effect on reproductive success. Hence, e.g. poor weather conditions did not only affect calf production negatively the same year, but also increased the likelihood of poor reproductive success the subsequent year. The results support that calf slaughter mass (as a proxy for herd body condition) is an important indicator of the state of reindeer herds with respect to their production potential and resilience to weather events and climate change. Finally, the model framework employed in the present study can be further developed as a potential vehicle for near-term forecasting and thereby constitute a useful tool for adaptive management.