Behavioral plasticity allows ungulates to balance risk and reward following megafire

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Abstract

Anthropogenic climate and land use change has accelerated the frequency of extreme climatic disturbances such as megafire. These megafires dramatically alter ecosystems and threaten the long-term conservation of economically and ecologically important species, including native ungulates. Recent work suggests that ungulate species may be able to adjust to the immediate effects of megafire by adjusting their movement and behavior, but whether these adjustments persist or change over time following these major disturbances is far less is understood. We take advantage of a rare research opportunity to examine how a dominant ungulate species, black-tailed deer (Odocoileus hemionus columbianus), adjusts its movement and behavior immediately following a megafire. We collected GPS data from 24 individual doe over the course of a year and fit these data to resource selection functions (RSFs) and hidden Markov movement models (HMMs) to assess whether and how deer alter habitat selection and behavioral decisions to adjust to novel landscape conditions following this megafire. We found compelling evidence of adaptive capacity across black-tailed deer following megafire, with deer modifying their habitat usage and behavior following megafire. Deer avoided exposed (chaparral) and severely burned areas immediately following megafire, but later altered these behaviors to eventually select for areas that burned at higher severities to potentially take advantage of enhanced forage in these recovering areas. These results suggest that despite their high site fidelity, this deer population, and similar ungulate species, can effectively navigate altered landscapes to track relatively sudden shifts in predation risk and resource availability. The successful adjustment of dominant ungulate species to extreme disturbances such as these could help facilitate resilience at broader ecological and trophic scales.

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  1. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/8361323.

    Summary

    Calhoun et al. used GPS data from 24 individual doe over the course of a year to investigate whether and how deer alter habitat selection and behavioral decisions to adjust to novel landscape conditions following megafire. They found that deer avoided exposed and severely burned areas immediately following megafire, but later they altered this behavior to eventually select for areas that burned at higher severities to potentially take advantage of enhanced forage in these recovering areas. This study will move the scientific field forward because using the results of dear behavior could help identify if further conservation interventions are needed for populations across the US following megafire and other ungulate populations globally. With the rise of global temperatures and climate change, understanding animal's behavioral plasticity will help in conservation aid. This study merits publication once the requested additional recommended edits are provided.

    Major Strengths

    Major strengths of the paper include a precise abstract that properly introduces and summarizes the study's hypotheses, methods, and conclusions. The flow of the paper was simple and easy to follow. The necessity for the study and future implications of their findings are clearly stated. Lastly, in lines 423-427 and 442-444 of the discussion, the authors provide a possible further study inspired by the findings of this study.

    Major Critiques

    While the Results and Discussion both provided valuable and necessary interpretations and conclusions of the study, they are slightly repetitive and wordy. To address this weakness, the authors should either combine the two sections or keep them separate and make each more concise.  Most of the figures are clear and easy to understand, however, the coloring of Figure S1.1 makes it challenging to decipher. The colors representing the different vegetation types are too similar and difficult to differentiate. Making the colors more distinctive is necessary for easy interpretation of this figure. Lastly, the caption of Figure S1.4 lacks context and needs more explanation to add importance to this graph.

    Minor Critiques

    Megafires/ "high severity fires" are defined as "wildfires that surpass the size and severity of historical fires" on line 50 and "fires that burn the dominant vegetation type in an ecosystem" on lines 62-63. This definition lacks clarity about the geological distance that defines a megafire. To better define "megafire," the authors should include a range of possible areas impacted that would be considered a megafire. Furthermore, in lines 96-105 of the introduction, the authors present the specifics of the study, examining 24 black-tail deer for one year in areas of high megafire frequency. To add a control to this study, the authors should also study black-tail deer (or a similar species) in a non-megafire-frequent area. They could then compare the behaviors of these two different groups.

    Competing interests

    The author declares that they have no competing interests.

  2. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/8148504.

    Overall summary:

    This work seeks to study the movement behavior of black-tailed deer immediately following a megafire, to understand whether ungulate species are able to adjust to the immediate effects of megafires - specifically how deer alter habitat selection and behavioral decisions adjusting to a novel landscape. The authors use hourly GPS tracking data from doe over the period of a year and fit data from specific time periods to Resource Selection Functions and Hidden Markov Movement models. The authors claim that this work shows evidence of adaptive capacity, with deer initially avoiding severely burned areas but later selecting these areas for enhanced foraging. The authors suggest that this species, and by extension other ungulates, can navigate altered can navigate altered environments, with implications for understanding broader resilience.

    This manuscript has a clear premise and generally articulates points well and was overall easy to follow, with the author's line of argument being clear. It could benefit from some expansion of certain parts, e.g. why the models used were selected in particular (lines 101-5); how the predictions in lines 107-116 fit into the design of the models/testing the hypothesis; how far this work applies to other ungulate species/should be restricted to black-tailed deer in this particular ecological context; etc. There are also some trivial errors in description of data which I have detailed below. Overall, however, the data generated align with the points the authors are making and agree with their argument.

    Major Comments:

    How many deer were used to provide data for analysis? In line 99, 24 deer are mentioned, but in line 140, it is 16; and in lines 157-8, there is an implication that data from 10 deer were used. A more clear description of the number of deer providing data, and how many individual deer provided data across multiple, or all, seasons described is necessary to establish what data is actually being collected and assessed in this work. A related point: in line 150-1, the authors state that a minimum of 500 recordings were needed for assessment - how many deer were excluded, if any?

    The authors suggest that this work could apply to other ungulates, but it's not clear which, and where. It could be helpful to provide greater clarity about which kinds of species and habitats would be worthy of such a comparison, and which might provide interesting contrasts, to support future study. There is a nod to this point at the end of the discussion, in lines 446-450 where the authors discuss potential differences that might be expected with oak woodland savannas. How far this work extends to other ungulate species in other contexts, and not just black-tailed deer in the California setting, would be helpful for the authors to expand upon.

    Could the authors comment in more detail about any background levels of changes in behavior in deer, in times without fire? Or in times with more "normal" fire patterns? In order to make the claims made in this manuscript, it seems necessary to discuss what any "regular" behavior in the absence of megafires may be, in order to make this comparison. For example, does other work show an otherwise consistent distribution of behaviors, especially when comparing different seasons? Particularly putting this work into context in the discussion with reference to the literature cited on lines 72-79 and 89 would be helpful, in a similar fashion to the comments the authors make in the discussion with reference to the magnet effect.

    Minor Comments:

    I was not clear on the rationale for selection of the models used for analysis of the data (lines 101-5) and would appreciate a little expansion on the suitability of those models, in broad terms - there is a lot of technical detail in the methods describing the models, which is very helpful, but a sentence or two on why these models were selected (and others rejected) would be helpful to guide the reader towards the argument the authors are making. In particular it would be helpful to state at the end of Section 1 (lines 107-116) how the predictions fit into the model design, and testing of the hypothesis.

    In line 169, please describe what the acronym NDVI stands for.

    In lines 258-61, there appear to be errors in the description of the data of Table 1 and Figure 2, possibly some text was repeated and not deleted.

    Is Figure 3 describing only "Recently Burned"? Lines 296-7 seem to suggest this is the case.

    What precisely do the covariate terms mean, in real terms, in Figure 3? For example, what is the significance of "severity squared"? How is it different in real terms from severity, and why is it being shown to the reader in this figure?

    It is difficult to discern differences between different factors from key in the legends in some of the figures, e.g. Figure 4 - please consider changing the color transparency/contrast to allow the different curves to be discerned, or label the curves directly on the graph.

    Figure S1.3 is mentioned in line 326, before the first mention of Figure S1.2, on line 340.

    Conflicts:

    I have no conflicts to report; I have not been involved with nor discussed this work with the author. I do not stand to gain or suffer financially or otherwise from this publication.

    License:

    This review is published under a CC-BY license.

    Competing interests

    The author declares that they have no competing interests.