The importance of including phenology when modelling species ecological niche

Species distribution models have grown in complexity by incorporating fine-scale variables, including data on microclimate, physiology and species interactions. Recent studies have acknowledged the importance of the spatial scale by includ-ing higher resolution maps and more complex climatic variables. However, models rarely consider the consequences of including data related to time. Indeed, species phenology – and potential shifts in phenology due, for example, to climate change – is potentially one of the most neglected aspects of ecological modelling. We pres Species distribution models have grown in complexity by incorporating fine-scale variables, including data on microclimate, physiology and species interactions. Recent studies have acknowledged the importance of the spatial scale by includ-ing higher resolution maps and more complex climatic variables. However, models rarely consider the consequences of including data related to time. Indeed, species phenology – and potential shifts in phenology due, for example, to climate change – is potentially one of the most neglected aspects of ecological modelling. We pres-ent a literature review of relevant phenological aspects at different temporal scales and across several taxa. Such elements should be considered to define better the environmental niche and project present, future and past distribution models. We considered the available studies on plants, insects, reptiles, birds and mammals to evaluate how they dealt with the phenology of the investigated species, as well as the phenology of other resources and interacting species, to infer present, past and future projections. Here we focus on four main phenological aspects that, if not considered, may easily bias any projection, namely: 1) phenology can be accompa-nied by a shift in distribution within the year (e.g. migratory species); 2) activity may be restricted to a portion of the year (e.g. most ectotherms from temperate climates); 3) survival and reproduction success may depend on the synchrony with other species phenology (e.g. plants–pollinators interactions); 4) changes in climatic conditions can lead to shifts in phenology (e.g. anticipated or delayed blooms or changes in migration timing). In this review, we show how neglecting such factors may quickly lead to project a biased distribution. Finally, we provide a guide on evaluating whether the case study may be affected by such factors and what actions may improve the models.RP was supported by the Basque Government Department of Education (POS_2020_1_0009). MS was supported by the Spanish Ministry of Research and Innovation (FJC2019-040170-I).Peer reviewe