Temporal transferability of marine distribution models: The role of algorithm selection

Species distribution modelling of the Southern Ocean benthos: a review on methods, cautions and solutions

“…To run performant SDMs, several assumptions must be tested and computing methods adapted to each case study (Austin 2002, de la Hoz et al 2019). Among them, the choice of the modelling algorithm should be of major concern, as no algorithm works best for all species, in all areas, at all spatial scales and in all time periods (Jarnevich et al 2015, Qiao et al 2015).…”

The impact of climate change on the geographical distribution of habitat-forming macroalgae in the Rías Baixas

“…This is well known limitation of mechanistic distribution models based only on the physiological threshold of the species, which tend to over-predict species prevalence (Martínez et al, 2015). The false presences can be associated to other environmental factors, such as high atmospheric temperatures during low tide affecting those individuals inhabiting the low intertidal, the tidal range or the wind speed (Martínez et al, 2012, de la Hoz et al, 2019. Despite the model tending to over-predict the presence of H. elongata, it can provide useful information about potential areas of extinction in the future.…”

“…Thus, we may hypothesize that the water thermal conditions of the Rías Baixas will be favorable for all these species, as exemplified in this study by B. bifurcata. Once the thermal conditions are suitable, the distribution of the macroalgae species communities will be linked to other environmental factors, such as substrate, air temperature and significant wave height (Martínez et al, 2012, De la Hoz et al, 2019Ramos et al, 2020). Moreover, the distribution of the macroalgae will also depended on their dispersal ability.…”