Relative demographic susceptibility does not explain the extinction chronology of Sahul’s megafauna

Essential revisions:

1) Additional analyses (no additional data collection). The reviewers had specific concerns about the effects of sampling on the extinction chronology and the influence of body mass on a number of things (recovery potential, life history/demographic correlates, etc). Specifically, the analytical issues that present the biggest problems revolve around sampling uncertainty and body mass correlation. The former could be addressed by introducing some sensitivity tests. These could be directed towards chronological biases (how does removing one date affect the confidence intervals?)

Hidden chronological biases in time series of dated palaeontological specimens will always exist, which are particularly compounded at the limits of radiocarbon dating. That said, we agree that another treatment of the chronologies is warranted to demonstrate that different sets of assumptions do not change our general conclusions about the lack of a chronological signal.

To this end, we have revisited all the dates we derived from Saltré et al. [1], which were predicted regions of extinction-timing agreement among six frequentist models correcting for the Signor-Lipps effect (apart from the two updated extinction dates for mainland Thylacinus and Sarcophilus from White et al. [2] that have already been recalculated). For the remaining taxa (Diprotodon, Genyornis, Megalibgwilia, Metasthenurus, Palorchestes, Phascolonus, Procoptodon, Protemnodon, Sismosthenurus, Sthenurus, Thylacoleo, and Zygomaturus), we adapted the Gaussian-resampled, inverse-weighted McInerny (GRIWM) approach we designed and tested previously [3, 4] to derive new estimates and uncertainties of extinction time. Here, we jack-knifed the estimates 10,000 times for each taxon, calculating the median and 95% lower and upper confidence bounds.

This approach does not depend on distributional assumptions given that it is a resampling approach [4], even if it often provides wider uncertainty windows (especially for older dates). The main effect of this approach was to push back the extinction date for Metasthenurus (from a median of 50 ka to 89 ka), and push forward some of the dates within the other macropodiformes and vombatiforms. However, the net effect when we related these new estimates to any of the different risk metrics (mass, generation length, vital rate-specific extinction risk, or median susceptibility rank) was to maintain our general conclusion of no relationship for the chronology. We therefore did not repeat the supplementary analysis of the climate conditions based on these new extinction estimates.

We have placed these new results in the supplementary information, essentially making a new version of Figure 1 (in new Appendix S8; new Figure S9), Figure 6 (in new Appendix S8; new Figure S10), and Figure 7 (in new Appendix S8; new Figure S11). We also now refer to these additional results in the Discussion section, and have added a description of the approach in this new Appendix and a brief overview in the Methods. We have also included the GRIWM code in the updated Github respository (github.com/cjabradshaw/MegafaunaSusceptibility), as well as the raw dates for calculating the new estimates for each taxon (.csv files).

Methods:

“We also examined the sensitivity of our overall results to uncertainty in extinction estimates by deriving a jack-knifed version of the Gaussian-Resampled, Inverse-Weighted McInerny (GRIWM) model [3, 4] (Supplementary Information Appendix S8).”

Discussion:

“… went extinct (even after considering alternative approaches to calculate the window of extinction – Supplementary Information Appendix 8; Figure S9–S11).”

As well as geographical sampling biases (how does removing a region affect the trends?). The latter in particular would be important in the claims of a continental trend.

We would dearly love to do this. Even our ‘regional’ (south-eastern Sahul) assessment of spatial patterns of extinction [5] required us to lump taxa into one large group because of a lack of spatial replication of dated fossil specimens. Therefore, it is not yet currently possible to generate regional estimates of extinction time at the taxonomic scale of genus yet for Sahul megafauna. We have already indicated this limitation in paragraph six of the Discussion.

It is also possible that biases are a function of taxon sampling. There are an increasing number of small mammal Pleistocene extinctions being recognized in Australia, and it is unclear if these follow the same trends as the megafauna. If so, that would indeed remove the body size issues.

This is true, but the unfortunate reality is that for the small mammals known to have gone extinct in Pleistocene Sahul, there are few or no accurately dated specimens, no estimates for final extinction dates, and much of the research on these species is yet to be published. Thus, although the reviewer is correct in saying size-biased taxon sampling could affect our results, we are unable to include smaller extinct species in our analyses because we do not know when they went extinct. We have partly mitigated this bias by pairing extinct species with the largest extant species from the same functional/taxonomic group in our analyses. Nonetheless, we now also state in the Discussion that this is an issue and point to addressing it in the future:

“There is also an increasing number of small marsupial and placental mammals known to have gone extinct during the Pleistocene in Sahul [e.g., 6, 7]. The inclusion of these smaller species in future demographic susceptibility/chronology of extinction analyses will likely be insightful, but unfortunately estimates of extinction dates – which require at least 8 – 10 reliability dated specimens [3, 4] – are not yet available for these animals.”

2) Better framing of the five putative drivers of extinctions (these are not considered or glossed over in the present manuscript)):

i. Appears to assume that only human hunting will differentially affect demographically sensitive species. However, novel or extreme climate change can also affect such species (e.g. Selwood, K.E., McGeoch, M.A. and Mac Nally, R., 2015. The effects of climate change and land‐use change on demographic rates and population viability. Biological Reviews, 90(3), pp.837-853.)

This is a good suggestion for inclusion. We have now reworded our description of scenario (i) and updated Figure 1 to include the ways in which climate change can affect demography as described in Selwood et al. [8]. We have also modified the main text to include the reference and some of the most-pertinent conclusions from that paper (paragraph immediately before Figure 1 in the Introduction):

“However, there are many other ways that climate change can alter demography (reviewed in [8]). […] An increasing frequency of climate-induced catastrophes can also drive relatively smaller populations toward extinction faster, meaning large-bodied species with smaller populations are potentially more susceptible.”

ii. This mechanism is predicated on using a modelling result [ref. 25] as data. It also makes the bold claim that species inhabiting certain habitats are less accessible to human hunters without any consideration of the archaeological or modern record on this point (e.g. Roberts, P., Hunt, C., Arroyo-Kalin, M., Evans, D. and Boivin, N., 2017. The deep human prehistory of global tropical forests and its relevance for modern conservation. Nature Plants, 3(8), pp.1-9; Fa, J.E. and Brown, D., 2009. Impacts of hunting on mammals in African tropical moist forests: a review and synthesis. Mammal Review, 39(4), pp.231-264).

Perhaps a debatable concept given previous writings in this area for Sahul [9], but considering we cannot examine this mechanism explicitly with our approach, we have decided to remove reference to habitat access here in the Introduction (including removing the last mechanism in Figure 1). However, we maintained the text regarding the hypothesised relative susceptibility to human hunting in terms of mode of travelling (gait) and burrowing behaviour (Discussion).

iii. Many of the supporting references here do not seem like logical choices for this argument. E.g. [28] refers to coral-reef fishes. Moreover, this hypothesis conflicts with much modern data showing that extinction risk and body size are correlated under climate and environmental change (e.g. Cardillo, M., Mace, G.M., Jones, K.E., Bielby, J., Bininda-Emonds, O.R., Sechrest, W., Orme, C.D.L. and Purvis, A., 2005. Multiple causes of high extinction risk in large mammal species. Science, 309(5738), pp.1239-1241. Liow, L.H., Fortelius, M., Bingham, E., Lintulaakso, K., Mannila, H., Flynn, L. and Stenseth, N.C., 2008. Higher origination and extinction rates in larger mammals. Proceedings of the National Academy of Sciences, 105(16), pp.6097-6102. Tomiya, S., 2013. Body size and extinction risk in terrestrial mammals above the species level. The American Naturalist, 182(6), pp.E196-E214.)

In terms of reference 28 (Monaco et al.), the taxon is somewhat irrelevant. Rather, that paper focuses on the mechanisms of dispersal and establishment to new regions of climate suitability. For this reason, we think it is a useful citation.

For the other suggested papers, we have added them to the relevant text in the Introduction (including Figure 1) and the Discussion.

We acknowledge that scenario (iv) is in conflict with a widely observed pattern — climate change selects for a faster pace of life history (including faster growth, earlier maturation and decreased adult survival) and leads to smaller maximum adult body size. Indeed, this pattern corresponds to scenario (i) in which species with a slower life history (generally larger animals) succumbed first.

On the other hand, Scenario (iv) relates to another widely hypothesised pattern: that species with lower dispersal and higher specialisation are more vulnerable to climate change. In this scenario, larger species (which tend to have higher dispersal and less specialisation) are predicted to have later extinction dates (i.e., opposite pattern to i). We have now reworded scenario (i) to make the distinction between these scenarios clearer.

3) More nuanced interpretation of model output.

The major weakness in this manuscript is in the discussion. The authors should be very clear in their discussion that their model does not indicate that demographic factors had no part in extinct events per se, but rather that they don't explain extinction chronology. Extinction chronologies reflect a number of different factors and processes, but they don't take away from the fact that certain life history traits can make a species more likely to go extinct from those factors.

The authors seem to argue that demographics don't explain the megafaunal extinction in the Sahul, but in fact, their results suggest that they do; the only thing demographics by themselves don't explain is the chronology. Extinction risk as determined by demographic susceptibility is highly related to body mass and generation time (which in turn is also affected by body mass) but differential survival (timing of extinction) is determined by factors such as geographic range size, dispersal ability, access to refugia, and behavioral and morphological adaptations against hunting, and the ability to survive catastrophic events. A reiteration of this point would be beneficial to the clarity of this otherwise well written manuscript.

We agree that we are testing whether demographic susceptibility explains the chronology, and we did not intend to suggest that demographic variability played no role in the extinctions. That said, we understand now that perhaps we were not clear enough on the distinction between demographic susceptibility to extinction (something we clearly showed) versus testing for a relationship between demographic vulnerability and extinction chronology (a hypothesis we specifically rejected).

The relevant paragraphs of the Discussion appear to be mainly the first and last, which we have now updated to read as follows:

First paragraph:

“The megafauna species of Sahul demonstrate demographic susceptibility to extinction largely following expectations derived from threat risk in modern species – species with slower life histories have higher demographic risk to extinction on average [10-13]. […] As different perturbations compromise different aspects of a species’ life history, its relative susceptibility to extinction compared to other species in its community varies in often unpredictable ways.”

last paragraph:

“That we found no clear patterns among the extinct megafauna of Sahul to explain their relative extinction chronology supports the notion that, at least for mammals, extinction risk can be high across all body masses depending on a species’ particular ecology [15], even if relative extinction risk appears to follow allometric expectations [10-13, 16] as we demonstrated clearly here (Figure 3, 5, 7). […] Nonetheless, more spatially and community-dependent models are still needed to provide a more complete picture of the dynamics of Late Pleistocene megafauna extinctions”

We also modified the 3^rd paragraph of the Discussion as follows:

“This lack of relationship to the chronology, combined with the result that many of the extant species had, in fact, some of the highest extinction susceptibilities, suggest that no obvious demographic properties can explain the taxon-specific timing within the Sahul extinction event of the Late Pleistocene. […] However, this conclusion does not accord well with the notion that Late Pleistocene megafauna extinctions were non-random and occurred at a much higher pace than background extinction rates [18, 19].”

The authors clearly (and elegantly) show that extinct species, which were all large, and had long generation times, had demographic traits that made them more susceptible to extinction. This is evident in figures 3 and 4. However, in the discussion, in lines 301-303, they state that no demographic trends explain the extinction. This is not supported by the results. While the timing of when species go extinct doesn't correlate with demographic susceptibility, the peculiar nature of the extinction-a large size biased extinction-is explained by demographic factors, and is a phenomenon that has been explored in a global analysis by Lyons et al. 2016 Biol. Lett. Therefore, demographic trends DO explain why certain species go extinct, while others survive. The authors should be careful when they say that "that no obvious demographic trends can explain the great Sahul mass extinction event"; instead, they should re-iterate that no obvious demographic trend explains the extinction chronology.

As indicated in Response #7, we did not intend to give this impression, but agree that our wording needs to be clearer. We have amended this paragraph to:

“This lack of relationship to the chronology, combined with the result that many of the extant species had, in fact, some of the highest extinction susceptibilities, suggest that no obvious demographic properties can explain the taxon-specific timing within the Sahul extinction event of the Late Pleistocene. […] However, this conclusion does not accord well with the notion that Late Pleistocene megafauna extinctions were non-random and occurred at a much higher pace than background extinction rates [18, 19].”

We have also now cited Lyons et al. [20] in the first paragraph of the Discussion.

4) More careful discussion of results relative to literature. The authors further go on to suggest that their results suggest that the extinctions were random, but the size-selectivity clearly shows that the extinctions were in fact not random with respect to body size. Their analyses do show that the rate of extinction doesn't exceed background to the same degree that it's been suggested in prior studies, and this is something that researchers need to explore further. Also, the authors raise an important point in lines 309-311 that human hunting could have interacted with demographic susceptibility, something that Lyons et al. 2016 Biol. Lett. show, and the results of the present study should be discussed in light of the 2016 paper.

We had meant that the chronology of the extinctions might have arisen at random, not that the extinctions themselves were random (we later dismiss this suggestion). But we agree that our wording was unclear. We have reworded this to:

“This opens the possibility that the chronology instead reflects either a random set of circumstances – that species succumbed to circumstantial combinations of stressors depending on the local perturbations experienced by particular populations [5, 17] – or even that the chronology is still insufficiently resolved.”

We are uncertain what the reviewer is referring to with respect to extinction rate. While we mentioned that previous work [18, 19] concluded that the Sahul megafauna extinction rate was higher than the background rate, we offer no such data or analysis on rates of extinction (i.e., extinctions per unit time); rather, we demonstrate how quickly populations of certain sizes could have gone extinct at increasing magnitudes of perturbations to demographic rates.

For the Lyons et al. [20] conclusions, we have added a new sentence in the paragraph mentioned after the first sentence:

“Indeed, Lyons et al. [20] concluded that either large-bodied mammals were selectively targeted by humans during the Late Quaternary, that these species were relatively more vulnerable to human hunting than smaller-bodied species, or both.”

They also raise an important point in lines 312-320 that behavioral or morphological adaptations may have allowed some seemingly "high risk" species to persist despite anthropogenic pressure. These model "mis-matches" have been reported by Alroy 2001 Science as well in a multispecies overkill simulation. It would be beneficial to discuss the present results within the context of other examples of model mismatches, such as those from Alroy 2001.

This is a good reference for mismatches, although they only describe hypotheses as opposed to modelled mechanisms. We have therefore added the following sentence to the end of the relevant paragraph:

“Similar hypotheses regarding risk-persistence mismatches in multispecies simulations have been proposed for the Late Pleistocene megafauna extinction event in North America [21].”

In lines 353-358, the authors once again state that their results show no clear relationship between body-mass and demographic disadvantage, despite clearly showing these relationships in Figures 3 and 4, and even stating as much in the beginning of the discussion. The plots clearly show that large bodied taxa were at a demographic disadvantage. There is a difference between explaining why certain taxa go extinct vs. why they go extinct at a certain point in time, and this should be made clear. The authors are correct in stating that demographic factors don't explain the relative extinction chronology, i.e. when species go extinction relative to each other, but they do explain why large species go extinct, and why these extinctions take place after human arrival. Moreover, generation length, which is also correlated with demographic susceptibility, is highly correlated with body mass (Brook and Bowman 2005 Pop. Ecol), once again showing that body mass-related effects do help explain the extinctions.

We have completely redrafted this paragraph as explained in Response #7. We have also added the citation to Brook and Bowman [16] at the end of the first sentence in that paragraph.

The authors rightfully point out earlier in the discussion that spatial variation, local climates, ecological interactions, etc. all influence how and why a particular population disappears. Extinction chronologies reflect a number of different factors and processes, but they don't take away from the fact that certain life history traits can make a species more likely to go extinct from those factors. Large proboscideans like mammoths had a high risk of extinction based on life history traits, but managed to survive on island refugia into the mid-Holocene. Similar other examples exist, and show that extinction chronologies can vary vastly.

Good point. We have added the following sentence encapsulating this idea, and added a new citation:

“For example, large proboscideans like mammoths managed to persist well into the Holocene on island refugia despite having a high intrinsic extinction risk [22].”

Therefore, the lack of correlation can be explained by these factors, and the authors need to expand on these in their discussion, perhaps if possible, by giving specific examples. They should be more careful in their discussion by clearly distinguishing drivers of extinction risk, and how these drivers can be de-coupled from timing, but at the same time providing a good explanation for the biological factors leading to the extinction. Here again the authors should consider the work of Brook and Bowman and Lyons et al.

The changes we have made throughout the Discussion suffice to make this distinction clear now, especially with the addition of the suggested references. Thank you.

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