Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.

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Cazalilla and Marston Reply:The authors of the Comment [1] propose an improvement to our timedependent density-matrix renormalization group (TdDMRG) algorithm as described in our Letter [2], providing few details about the proposed extension. Luo, Xiang, and Wang (LXW) [1] then point out that the oscillations at late times (t > 18) shown in two of the lines plotted in Fig. 2 of our manuscript are an artifact of the truncation of the Hilbert space.LXW are correct that the oscillations we reported in the one case of V=w 1:1 are in fact spurious. We had systematically examined the errors induced by truncations of the Hilbert space in our Letter. However, we failed to notice that, for the case of V=w 1:1 when the leads are insulating, the eigenvalues of the reduced density matrices become so small so quickly (due to the gap to excitations) that our code discarded the same portion of the Hilbert space for truncations M 256 and 512. Thus we were left with the illusion that we had achieved convergence in this one case, when in fact we had not.Unfortunately the Comment [1] does not provide enough details regarding the construction of the (reduced) density matrix. As Eq. (1) of the Comment [1] shows, LXW's density matrix requires knowledge of the wave function at different times; but to obtain the timeevolved wave function, one needs the density matrix in the first place. Thus it seems that LXW use an iterative procedure: LXW apparently carry out repeated integrations forward in time for each chain size starting with the shortest chain, of length four sites. Once the density matrix is constructed for a chain of a given length, it is then lengthened by the addition of two sites via the usual (infinite-size) density-matrix renormalization group (DMRG) algorithm, and time integration is repeated again from the beginning. The process is then repeated until a sufficiently long chain is built up, tailored to the particular choice of applied bias. Thus the proposed modification of our TdDMRG algorithm is computationally intensive and time-consuming. We further point out