Yet, predictive biodiversity models rarely account for spatiotemporal variation in biotic interaction strength, as both the knowledge of the relevant variability and the data necessary to quantify it are usually lacking (Thuiller et al., 2013 Wisz et al., 2013).Ī key concept of statistical approach to prediction is transferability, defined by Sequeira et al. Spatial and temporal variability in biotic interactions is an integral part of food web functioning (Gripenberg & Roslin, 2007 Hunter & Price, 1992 Maron, Baer, & Angert, 2014). In particular, biotic interactions are important determinants of biodiversity distribution (Elith & Leathwick, 2009 Wisz et al., 2013) and their strength is related to the functioning and stability of ecosystems (Bartomeus et al., 2016 Gellner & McCann, 2016). However, the fast development of predictive ecology calls for caution, as it is not always clear whether the current understanding of ecological processes is comprehensive enough to warrant predictions (Mouquet et al., 2015). Predictive modelling is increasingly common in ecology, and statistical models created in one context are often used to predict the state of the system in other contexts, such as other geographical areas or climate regimes (Sequeira, Bouchet, Yates, Mengersen, & Caley, 2018 Thuiller et al., 2013). Enhanced collaboration between researchers whose main research interests lay in different parts of the food web could ameliorate this. Such attempts are currently constrained by the lack of data with replicated estimates of key players in food webs.

We propose that parametrizing a more complete set of functional links within food webs across abiotic and biotic contexts would improve transferability of biotic interaction models. Plant–rodent interactions are thus temporally variable and likely more complex than simple one-directional (bottom-up) relationships or variably overruled by other biotic interactions and abiotic factors. Yet, the temporal transferability of our models to the next population peak was poorer. Rodent abundance was related to both food and shelter biomass during the first peak, and spatial transferability was mostly good. We assessed the spatial and temporal predictability of food and shelter plants effects on peak-phase small rodent abundance during two consecutive rodent population peaks. The amplitude of rodent population cycles (i.e., peak-phase abundances) has been hypothesized to be determined by vegetation properties in tundra ecosystems. However, the consequences of the spatial and temporal variability of biotic interactions are poorly known, in particular for predicting species abundance and distribution. Variability in biotic interaction strength is an integral part of food web functioning.

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