Understanding connectivities among species distributions, biodiversity, marine habitats and climate change is necessary for the design of an effective conservation management, such as in the implementation of marine protected area (MPA). In this study, we observed the richness of 89 "rare" or "exotic" fish species (observed outside their known distribution range) related to climate change. We modeled and predicted their seasonal distributions according to the species ecological niches (determined in this study) using the GIS model. Superposing the models of all species using GIS, we determined the preferential zones or zones of high biodiversity (hotspots) over time. The GIS approach offers an alternative to measure seasonal species richness in poor-data areas. This approach allowed also species track movement over time. This information could be then used to measure the effectiveness of MPA positioning related to the hotspot areas. Our study area covers a wide latitudinal range of the Eastern Atlantic waters, from the warm tropical/subtropical waters to the temperate waters. This area is located in three large marine ecosystems: the Canary current, the South European Atlantic Shelf and the Celtic Seas. The transitional zone in the central region has well known for its sensitivity to the detection of climate change. From 1982 to 2012, the SST in all of studied ecosystems has increased consistently over time, with magnitude and trend varied among ecosystems. The change of number of species in each decadal period differed among ecosystems. Increasing number of species in an ecosystem was generally followed by decreasing trend in adjacent ecosystems. Species ecological niches were obtained by extracting the environmental values in the location of species occurrence at the time of observation. The environmental data and the occurrence records used were at global scale, and the methods yields coherent results with the results obtained from observational studies. The flexibility of GIS Model used in this study allowed us to follow the evolution of species seasonal distribution over time. Generally, most of the studied species showed a northbound trend in their distribution. These northbound tendencies were more evident in the middle region, confirming the effect of global warming in shifting marine species distribution. This approach provides an alternative of measuring seasonal richness of poor-known species and/or modeling in poor-data areas. The results present a complete picture of predictive number of species in an area over time. MPAs superficial analysis by country (countries lying in the study area) showed that UK has the highest number of MPA and the largest protected areas, following by France and Mauritania. Frequencies of the MPAs touched by the hotspot were strongly influenced by seasonal variations. Thus, considering seasonal variations in a conservation effort could preserve species adaptive variation under environmental changes. Overall, our works provide several alternative methods for species distribution studies and for studies poor-known species in data-poor area. The results provide evidences of ocean warming effect in shifting marine fish distribution.