## 4 Discussion
We hypothesize that these electromagnetic signals respond to changes in the resistivity field of the medium, which in turn is related to changes in the porosity and microfracture conditions and the volume of fluids contained, as suggested in Figure 6. Given changes in the deviatoric stress that generates earthquakes, changes in the porosity field, pore pressure gradients (up to distances greater than the size of the seismic source), and fluid mobility are expected. Thus, our reported changes in \(\rho_{a}\) and the latter observ  
Figure 5: Antarctic Peninsula Map, including the archipelagos of the Shetland Plate (north of the Bransfield Basin). The beach balls represent focal mechanisms, and the green circles are some earthquakes with depths <50 km reported by the USGS. The free air anomalies [16] (upper map) define the geometry of the Bransfield Basin. The heat flow distribution [17] (lower map) in the area is <90 mW/m\({}^{2}\). Suggested faults inside the basin were interpreted with swath bathymry data [18]. The Marambio station (red square) represents the location of the MT monitoring. Figure made with GeoMapApp (www.geomapapp.org, accessed on 15 December 2022). on the surface (Figures 3 and 4) constitute possible evidence of the fluid migration in the upper lithosphere during the seismic swarm. Additional confirmation of the phenomena suggested in this work could come from studies that analyze the elastic and inelastic fields using seismic swarm data (e.g., [61; 62; 63]). We believe that permanent MT monitoring could be an interesting strategy for understanding the pore pressure conditions before fracture initiation in strong earthquakes or seismic swarm scenarios. In this work, we report an experiment near the Antarctic Peninsula, a region of very low anthropogenic electromagnetic noise and gas emission contamination, with low solar activity during the recorded dataset, and a relevant scenario generated by an isolated seismic swarm in an area of active tectonics. Even under these particular circumstances and when we are not inverting the 1D-\(\rho_{a}\) profile, uncertainties in the estimation of \(\rho_{a}\) could come from large periods analyzed, which means related to the deeper crustal structure. A future potential solution to this issue could be to stack signals from other near MT stations to consolidate space-time 1D-\(\rho_{a}\) maps that may reinforce the trusty anomalies. In addition, other gas measurements around the study region may clarify the role of the fluid migration paths involved in the dynamics of closing and opening of the porosity field. Finally, we suggest several possible outlooks that the scientific community may address in the future for this type of research: (1) Deploy arrays of permanent MT stations in areas of high tectonic activity that allow the consolidation of datasets on the relationship between seismicity and crustal \(\rho_{a}\) anomalies. (2) In areas of active magmatism, in addition to deploying MT instruments at different distances, it could be necessary to install monitoring networks for fluid pressure and gas emission sensors to verify the hypothesis of fluid migration and pore pressure that trigger seismicity. (3) Design numerical experiments that allow inferring stress conditions, fluid volumes, and changes in the petrophysical properties of the crust necessary to reproduce \(\rho_{a}\) anomalies, such as those reported in this work. Figure 6: Schematic representation of the generation processes previous to (left) and after the seismic swarm. With no significant temporal variations in the tectonic stress (\(\Delta\sigma_{s}\)), no changes are expected in \(\rho_{a}\) nor in fluid migration that triggers pore pressure and gas emissions.