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Given a dynamic graph G, we aim to maintain a maximal independent set (MIS). This problem admits a deterministic solution in O(m^{2/3}) time [SOSA21], while randomized algorithms for oblivious adversary take O(polylog n) [FOCS19] time. Recently, Bernstein et al. [SODA26] proved a conditional lower bound of Ω(n^{1-o(1)}) amortized update time even for incremental MIS with adaptive adversary. In this paper, we establish similar deterministic bounds through the lens of incremental and fault tolerant algorithms for MIS, and show the following: 1) Incremental: MIS can be maintained under edge insertions in O(√m) amortized update time. 2) Fault Tolerant: Using O(m) preprocessing time, the MIS can be reported after k edge deletions in O(k+ ̅{n}²) time, where ̅{n} is the number of vertices on which deleted edges are incident. 3) Fully Dynamic: MIS can be maintained under fully dynamic edge updates (insertions and deletions) in O(m^{2/3}) amortized update time. Our incremental result is thus polynomially optimal even on allowing randomization with an adaptive adversary. Our fully dynamic result matches the state-of-the-art [SOSA21], and uses our incremental and fault tolerant algorithms as a black box. Although our fully dynamic algorithm does not improve the existing bounds, it provides additional insights into the harder edge-insertion case. We believe these insights may potentially be useful for improving the bounds for fully dynamic MIS in the future to match the incremental MIS bounds.