Author response:
The following is the authors’ response to the original reviews
Public Reviews:
Reviewer #1 (Public review):
This paper presents a computational model of the evolution of two different kinds of helping ("work," presumably denoting provisioning, and defense tasks) in a model inspired by cooperatively breeding vertebrates. The helpers in this model are a mix of previous offspring of the breeder and floaters that might have joined the group, and can either transition between the tasks as they age or not. The two types of help have differential costs: "work" reduces "dominance value," (DV), a measure of competitiveness for breeding spots, which otherwise goes up linearly with age, but defense reduces survival probability. Both eventually might preclude the helper from becoming a breeder and reproducing. How much the helpers help, and which tasks (and whether they transition or not), as well as their propensity to disperse, are all evolving quantities. The authors consider three main scenarios: one where relatedness emerges from the model, but there is no benefit to living in groups, one where there is no relatedness, but living in larger groups gives a survival benefit (group augmentation, GA), and one where both effects operate. The main claim is that evolving defensive help or division of labor requires the group augmentation; it doesn't evolve through kin selection alone in the authors' simulations.
This is an interesting model, and there is much to like about the complexity that is built in. Individual-based simulations like this can be a valuable tool to explore the complex interaction of life history and social traits. Yet, models like this also have to take care of both being very clear on their construction and exploring how some of the ancillary but potentially consequential assumptions affect the results, including robust exploration of the parameter space. I think the current manuscript falls short in these areas, and therefore, I am not yet convinced of the results. Much of this is a matter of clearer and more complete writing: the Materials and Methods section in particular is incomplete or vague in some important junctions. However, there are also some issues with the assumptions that are described clearly.
Below, I describe my main issues, mostly having to do with model features that are unclear, poorly motivated (as they stand), or potentially unrealistic or underexplored.
We would like to thank the reviewer for the thoughtful comments that helped us to greatly improve the clarity of our paper.
One of the main issues I have is that there is almost no information on what happens to dispersers in the model. Line 369-67 states dispersers might join another group or remain as floaters, but gives no further information on how this is determined. Poring through the notation table also comes up empty as there is no apparent parameter affecting this consequential life history event. At some point, I convinced myself that dispersers remain floaters until they die or become breeders, but several points in the text contradict this directly (e.g., l 107). Clearly this is a hugely important model feature since it determines fitness cost and benefits of dispersal and group size (which also affects relatedness and/or fitness depending on the model). There just isn't enough information to understand this crucial component of the model, and without it, it is hard to make sense of the model output.
We use the same dispersal gene β to represent the likelihood an individual will either leave or join a group, thereby quantifying both dispersal and immigration using the same parameter. Specifically, individuals with higher β are more likely to remain as floaters (i.e., disperse from their natal group to become a breeder elsewhere), whereas those with lower β are either more likely to remain in their natal group as subordinates (i.e., queue in a group for the breeding position) or join another group if they dispersed.
We added in the text “Dispersers may migrate to another group to become subordinates or remain as floaters waiting for breeding opportunities, which is also controlled by the same genetic dispersal propensity as subordinates” to clarify this issue. We also added in Table 1 that β is the “genetic predisposition to disperse versus remain in a group”, and to Figure 1 that “subordinates in the group (natal and immigrants) […]” after we already clarified that “Dispersers/floaters may join a random group to become subordinates.”
Related to that, it seems to be implied (but never stated explicitly) that floaters do not work, and therefore their DV increases linearly with age (H_work in eq.2 is zero). That means any floaters that manage to stick around long enough would have higher success in competition for breeding spots relative to existing group members. How realistic is this? I think this might be driving the kin selection-only results that defense doesn't evolve without group augmentation (one of the two main ways). Any subordinates (which are mainly zero in the no GA, according to the SI tables; this assumes N=breeder+subordinates, but this isn't explicit anywhere) would be outcompeted by floaters after a short time (since they evolve high H and floaters don't), which in turn increases the benefit of dispersal, explaining why it is so high. Is this parameter regime reasonable? My understanding is that floaters often aren't usually high resource holding potential individuals (either b/c high RHP ones would get selected out of the floater population by establishing territories or b/c floating isn't typically a thriving strategy, given that many resources are tied to territories). In this case, the assumption seems to bias things towards the floaters and against subordinates to inherit territories. This should be explored either with a higher mortality rate for floaters and/or a lower DV increase, or both.
When it comes to floaters replacing dead breeders, the authors say a bit more, but again, the actual equation for the scramble competition (which only appears as "scramble context" in the notation table) is not given. Is it simply proportional to R_i/\sum_j R_j ? Or is there some other function used? What are the actual numbers of floaters per breeding territory that emerge under different parameter values? These are all very important quantities that have to be described clearly.
Although it is true that dispersers do not work when they are floaters, they may later help if they immigrate into a group as a subordinate. Consequently, immigrant subordinates have no inherent competitive advantage over natal subordinates (as step 2.2. “Join a group” is followed by step 3. “Help”, which occurs before step 5. “Become a breeder”). Nevertheless, floaters can potentially outcompete subordinates of the same age if they attempt to breed without first queuing as a subordinate (step 5) when subordinates are engaged in work tasks. We believe that this assumption is realistic and constitutes part of the costs associated with work tasks. However, floaters are at a disadvantage for becoming a breeder because: (1) floaters incur higher mortality than individuals within groups (Eq. 3); and (2) floaters may only attempt to become breeders in some breeding cycles (versus subordinate groups members, who are automatically candidates for an open breeding position in the group in each cycle). Therefore, due to their higher mortality, floaters are rarely older than individuals within groups, which heavily influences their dominance value and competitiveness. Additionally, any competitive advantage that floaters might have over other subordinate group members is unlikely to drive the kin selection-only results because subordinates would preferably choose defense tasks instead of work tasks so as not to be at a competitive disadvantage compared to floaters.
Regarding whether floaters aren't usually high resource holding potential (RHP) individuals and, therefore, our assumptions might be unrealistic; empirical work in a number of species has shown that dispersers are not necessarily those of lower RHP or of lower quality. In fact, according to the ecological constraints hypothesis, one might predict that high quality individuals are the ones that disperse because only individuals in good condition (e.g., larger body size, better energy reserves) can afford the costs associated with dispersal (Cote et al., 2022). To allow differences in dispersal propensity depending on RHP, we extended our model in the Supplemental Materials by incorporating a reaction norm of dispersal based on their rank (D = 1 / (1 + exp (β<sub>R</sub> * R – β<sub>0</sub>)) under the section “Dominance-dependent dispersal propensities” and now referenced in L195. This approach allows individuals to adjust their dispersal strategy to their competitiveness and to avoid kin competition by remaining as a subordinate in another group. Results show that the addition of the reaction norm of dispersal to rank did not qualitatively influence the results described in the main text.
We also added “number of floaters” present in the whole population to the summary tables as requested.
As a side note, the “scramble context” we mention was an additional implementation in which we made rank independent of age. However, since the main conclusions remained unchanged, we decided to remove it for simplicity from the final manuscript, but we forgot to remove it from Table 1 before submission.
I also think the asexual reproduction with small mutations assumption is a fairly strong one that also seems to bias the model outcomes in a particular way. I appreciate that the authors actually measured relatedness within groups (though if most groups under KS have no subordinates, that relatedness becomes a bit moot), and also eliminated it with their ingenious swapping-out-subordinates procedure. The fact remains that unless they eliminate relatedness completely, average relatedness, by design, will be very high. (Again, this is also affected by how the fate of the dispersers is determined, but clearly there isn't a lot of joining happening, just judging from mean group sizes under KS only.) This is, of course, why there is so much helping evolving (even if it's not defensive) unless they completely cut out relatedness.
As we showed in the Supplementary Tables and the section on relatedness in the SI (“Kin selection and the evolution of division of labor"), high relatedness does not appear to explain our results. In evolutionary biology generally and in game theory specifically (with the exception of models on sexual selection or sex-specific traits), asexual reproduction is often modelled because it reduces unnecessary complexity. To further study the effect of relatedness on kin structures more closely resembling those of vertebrates, however, we created an additional “relatedness structure level”, where we shuffled half of the philopatric offspring using the same method used to remove relatedness completely, effectively reducing withingroup relatedness structure by half. As shown in the new Figure S3, the conclusions of the model remain unchanged.
Finally, the "need for division of labor" section is also unclear, and its construction also would seem to bias things against division of labor evolving. For starters, I don't understand the rationale for the convoluted way the authors create an incentive for division of labor. Why not implement something much simpler, like a law of minimum (i.e., the total effect of helping is whatever the help amount for the lowest value task is) or more intuitively: the fecundity is simply a function of "work" help (draw Poisson number of offspring) and survival of offspring (draw binomial from the fecundity) is a function of the "defense" help. As it is, even though the authors say they require division of labor, in fact, they only make a single type of help marginally less beneficial (basically by half) if it is done more than the other. That's a fairly weak selection for division of labor, and to me it seems hard to justify. I suspect either of the alternative assumptions above would actually impose enough selection to make division of labor evolve even without group augmentation.
In nature, multiple tasks are often necessary to successfully rear offspring. We simplify this principle in the model by maximizing reproductive output when both tasks are carried out to a similar extent, allowing for some flexibility from the mean. We added to the manuscript “For example, in many cooperatively breeding birds, the primary reasons that individuals fail to produce offspring are (1) starvation, which is mitigated by the feeding of offspring, and (2) nest depredation, which is countered by defensive behavior. Consequently, both types of tasks are necessary to successfully produce offspring, and focusing solely on one while neglecting the other is likely to result in lower reproductive success than if both tasks are performed by individuals within the group.”
Regarding making fecundity a function of work tasks and offspring survival as a function of defensive tasks, these are actually equivalent in model terms, as it’s the same whether breeders produce three offspring and two die, or if they only produce one. This represents, of course, an oversimplification of the natural context, where breeding unsuccessfully is more costly (in terms of time and energy investment) than not breeding at all.
Overall, this is an interesting model, but the simulation is not adequately described or explored to have confidence in the main conclusions yet. Better exposition and more exploration of alternative assumptions and parameter space are needed.
We hope that our clarifications and extension of the model satisfy your concerns.
Reviewer #2 (Public review):
Summary:
This paper formulates an individual-based model to understand the evolution of division of labor in vertebrates. A main conclusion of the paper is that direct fitness benefits are the primary factor causing the evolution of vertebrate division of labor, rather than indirect fitness benefits.
Strengths:
The paper formulates an individual-based model that is inspired by vertebrate life history. The model incorporates numerous biologically realistic details, including the possibility to evolve age polytheism where individuals switch from work to defence tasks as they age or vice versa, as well as the possibility of comparing the action of group augmentation alone with that of kin selection alone.
Weaknesses:
The model makes assumptions that restrict the possibility that kin selection leads to the evolution of helping. In particular, the model assumes that in the absence of group augmentation, subordinates can only help breeders but cannot help non-breeders or increase the survival of breeders, whereas with group augmentation, subordinates can help both breeders and non-breeders and increase the survival of breeders. This is unrealistic as subordinates in real organisms can help other subordinates and increase the survival of non-breeders, even in the absence of group augmentation, for instance, with targeted helping to dominants or allies. This restriction artificially limits the ability of kin selection alone to lead to the evolution of helping, and potentially to division of labor. Hence, the conclusion that group augmentation is the primary driving factor driving vertebrate division of labor appears forced by the imposed restrictions on kin selection. The model used is also quite particular, and so the claimed generality across vertebrates is not warranted.
We would like to thank the reviewer for the in-depth review. We respond to these and other comments below.
I describe some suggestions for improving the paper below, more or less in the paper's order.
First, the introduction goes to great lengths trying to convince the reader that this model is the first in this or another way, particularly in being only for vertebrates, as illustrated in the abstract where it is stated that "we lack a theoretical framework to explore the conditions under which division of labor is likely to evolve" (line 13). However, this is a risky and unnecessary motivation. There are many models of division of labor and some of them are likely to be abstract enough to apply to vertebrates even if they are not tailored to vertebrates, so the claims for being first are not only likely to be wrong but will put many readers in an antagonistic position right from the start, which will make it harder to communicate the results. Instead of claiming to be the first or that there is a lack of theoretical frameworks for vertebrate division of labor, I think it is enough and sufficiently interesting to say that the paper formulates an individual-based model motivated by the life history of vertebrates to understand the evolution of vertebrate division of labor. You could then describe the life history properties that the model incorporates (subordinates can become reproductive, low relatedness, age polyethism, etc.) without saying this has never been done or that it is exclusive to vertebrates; indeed, the paper states that these features do not occur in eusocial insects, which is surprising as some "primitively" eusocial insects show them. So, in short, I think the introduction should be extensively revised to avoid claims of being the first and to make it focused on the question being addressed and how it is addressed. I think this could be done in 2-3 paragraphs without the rather extensive review of the literature in the current introduction.
We have revised the novelty statements in the Introduction by more clearly emphasizing how our model addresses gaps in the existing literature. More details are provided in the comments below.
Second, the description of the model and results should be clarified substantially. I will give specific suggestions later, but for now, I will just say that it is unclear what the figures show. First, it is unclear what the axes in Figure 2 show, particularly for the vertical one. According to the text in the figure axis, it presumably refers to T, but T is a function of age t, so it is unclear what is being plotted. The legend explaining the triangle and circle symbols is unintelligible (lines 227-230), so again it is unclear what is being plotted; part of the reason for this unintelligibility is that the procedure that presumably underlies it (section starting on line 493) is poorly explained and not understandable (I detail why below). Second, the axes in Figure 3 are similarly unclear. The text in the vertical axis in panel A suggests this is T, however, T is a function of t and gamma_t, so something else must be being done to plot this. Similarly, in panel B, the horizontal axis is presumably R, but R is a function of t and of the helping genotype, so again some explanation is lacking. In all figures, the symbol of what is being plotted should be included.
We added the symbols of the variables to the Figure axes to increase clarity. In Figure 3A, we corrected the subindex t in the x-axis; it should be subindex R (reaction norm to dominance rank instead of age). As described in Table 1, all values of T, H and R are phenotypically expressed values. For instance, T values are the phenotypically expressed values from the individuals in the population according to their genetic gamma values and their current dominance rank at a given time point.
Third, the conclusions sound stronger than the results are. A main conclusion of the paper is that "kin selection alone is unlikely to select for the evolution of defensive tasks and division of labor in vertebrates" (lines 194-195). This conclusion is drawn from the left column in Figure 2, where only kin selection is at play, and the helping that evolves only involves work rather than defense tasks. This conclusion follows because the model assumes that without group augmentation (i.e., xn=0, the kin selection scenario), subordinates can only help breeders to reproduce but cannot help breeders or other subordinates to survive, so the only form of help that evolves is the least costly, not the most beneficial as there is no difference in the benefits given among forms of helping. This assumption is unrealistic, particularly for vertebrates where subordinates can help other group members survive even in the absence of group augmentation (e.g., with targeted help to certain group members, because of dominance hierarchies where the helping would go to the breeder, or because of alliances where the helping would go to other subordinates). I go into further details below, but in short, the model forces a narrow scope for the kin selection scenario, and then the paper concludes that kin selection alone is unlikely to be of relevance for the evolution of vertebrate division of labor. This conclusion is particular to the model used, and it is misleading to suggest that this is a general feature of such a particular model.
The scope of this paper was to study division of labor in cooperatively breeding species with fertile workers (i.e., primarily vertebrates), in which help is exclusively directed towards breeders to enhance offspring production (i.e., alloparental care). Our focus is in line with previous work in most other social animals, including eusocial insects and humans, which emphasizes how division of labor maximizes group productivity. Other forms of “general” help are not considered in the paper, and such forms of help are rarely considered in cooperatively breeding vertebrates or in the division of labor literature, as they do not result in task partitioning to enhance productivity.
Overall, I think the paper should be revised extensively to clarify its aims, model, results, and scope of its conclusions.
Recommendations for the authors:
Reviewer #1 (Recommendations for the authors):
I reserved this section for more minor comments, relating to clarity and a general admonition to give us more detail and exploration of some basic population genetic quantities.
Another minor point, although depending on whether I assume right or wrong, it could be major: I am not entirely sure that dispersers help in the groups they join as helpers, because of line 399, which states specifically that individuals who do remain in natal territories do. But I assume dispersers help (elsewhere, the authors state helping is not conditional on relatedness to the breeder). Otherwise, this model becomes even weirder for me. Either way, please clarify.
Apologies if this was not clear. Immigrants that join a group (so dispersers from another group) as a subordinate help and queue for a breeding position, as does any natal subordinate born into the group. We rephased the sentence to “Subordinate group members, either natal or immigrants to the group, […]”
More generally, in simulation studies like this, there can be interactions between the strength of selection (which affects overall genetic variation maintained in the population), population size, and mutation rate/size, which can affect, for example, relatedness values. None of these quantities is explored here (and their interactions are not quantified), so it is not possible to evaluate the robustness of any of these results.
Thank you for your comments about the parameter landscape. It is important to point out that variations in the mutation rate do not qualitatively affect our results, as this is something we explored in previous versions of the model (not shown). Briefly, we find that variations in the mutation rates only alter the time required to reach equilibrium. Increasing the step size of mutation diminishes the strength of selection by adding stochasticity and reducing the genetic correlation between offspring and their parents. Population size could, in theory, affect our results, as small populations are more prone to extinction. Since this was not something we planned to explore in the paper directly, we specifically chose a large population size, or better said, a large number of territories (i.e. 5000) that can potentially host a large population.
The authors also never say how it is actually determined. There is the evolved helping variable, and there is also the evolved reaction norm. I assume that the actual amount of help of each type is given by the product of T (equation 1) and H (for defense) and (1-T) and H (for work), but this should be stated explicitly.
Help provided is an interaction between H (total effort) and T (proportion of total effort invested in each type of task). To clarify the distinction between these two processes, we have now added “Hence, the gene α regulates the amount of help expressed, while the genes γ determine which specific helping tasks are performed at different time points in the breeding cycle”.
It is also weird that after introducing the T variable as a function of age, Figure 3 actually depicts it as a function of dominance value.
Thank you for pointing out an error in Eq. 1. This inequality was indeed written incorrectly in the paper (but is correct in the model code); it is dominance rank instead of age (see code in Individual.cpp lines 99-119). We corrected this mistake throughout the manuscript.
What is "scramble context"?
“Scramble context” was an additional implementation that we decided to remove from the final manuscript, but we forgot to remove from Table 1 before submission. We have now removed it from the table.
Reviewer #2 (Recommendations for the authors):
Some specific comments:
(1) L 31: "All theoretical..." These absolute statements are risky and unnecessary.
Rephrased to “To date, most theoretical and empirical work…”
(2) L 46: I believe Tom Wenseleers has published on the evolution of division of labor with reproductive workers and high within-colony conflict.
Tom Wenseleers has indeed produced some models on the evolution of cooperation in social insects where some workers may reproduce. However, these models focus on the relevance of relatedness and policing selecting for a reduction in within-group conflict and the evolution of reproductive division of labor. Our model focuses instead on division of labor among workers (helpers). We have rephased this section to “task specialization is linked to sterility and where conflict of interest is generally low” to account for species of social insect in which variation in relatedness between group members and higher levels of reproductive conflict may arise. We also cited one of his papers.
(3) L 57: Again, unnecessary categorical statements.
Rephrased to “Although a great deal of recent empirical work highlights the importance of direct benefits in the evolution of cooperative breeding behavior in vertebrates [21–24], we lack understanding on the joint influence of direct and indirect fitness benefits in the evolution of division of labor.”
(4) L 67: This is said to be a key distinction, but in the paper, such a key role is not clearly shown. This and other tangential points are unnecessary to keep the introduction to the point.
The different fitness costs of different tasks is the basis of our model on division of labor. Therefore, this is a key distinction and basis from which to describe different tasks in the model. We have left this sentence unchanged.
(5) L 61-73: "In vertebrates, however, helpers may obtain fitness benefits directly via reproduction..." Some social insects may do so as well. It seems unnecessary and incorrect to say that vertebrate sociality is fundamentally different from invertebrate one. I think it is sufficiently interesting to say this work aims to understand vertebrate division of labor, by explicitly modeling aspects of its life history, without saying this can't happen in invertebrates or that no other model has ever done anything like it.
Our point is not that, in some social insects, workers cannot obtain direct fitness benefits, but that previous models where the focus is on the colony reproductive outcome are only a good approximation to eusocial insect with sterile workers. However, to make this clearer we have added “In vertebrates and social insect with fertile workers, however, helpers may obtain fitness benefits directly via […]”.
(6) L 74-86: By this point, the introduction reads like a series of disconnected comments without a clear point.
In L60 we added: “Understanding how direct and indirect benefits interact is particularly important in systems where individuals may differentially bear the fitness costs of cooperation”. By adding this sentence, we emphasize our focus on the largely unexplored direct fitness benefits and costs, as well as their interaction with indirect fitness. We then proceed to explain why it is crucial to consider that tasks have varying direct fitness costs and how the fitness benefits derived from cooperation change with age and resource-holding potential. These elements are essential for studying the division of labour in species with totipotent workers.
(7) L 87: This sentence gives a clear aim. It would be clearer if the introduction focused on this aim.
With the new sentence added in L60 (see previous comment), we bring the focus to the main question that we are trying to address in this paper earlier in the Introduction.
(8) L 88: "stochastic model" should be changed to "individual-based model".
Done.
(9) L 104: "limited number" is unclear. Say a fixed finite number, or something specific.
Done.
(10) L 105: "unspecified number" is unclear. Say the number of subordinates emerges from the population dynamics.
Changed to “variable number of subordinate helpers, the number of which is shaped by population dynamics, with all group members capable of reproducing during their lifetime”.
(11) L 112: "Dispersers" is used, but in the previous lines 107-109, the three categories introduced used different terms. Those three terms introduced should be used consistently throughout the paper, without using two or more terms for one thing.
We use the term “disperser” to describe individuals that disperse from their natal group.
Dispersers can assume one of three roles: (1) they can join another group as "subordinates"; (2) they can join another group as "breeders" if they successfully outcompete others; or (3) they can remain as "floaters" if they fail to join a group. "Floaters" are individuals who persist in a transient state without access to a breeding territory, waiting for opportunities to join a group in an established territory. We rephased the sentence to “Dispersers cannot reproduce without acquiring a territory (denoted here as floaters)”. This was also clarified in other instances where the term “dispersers” was used (e.g. L407). Other instances where this might not have been so clear, we replace “dispersers” with “floaters”.
(12) L 112: "(floaters)" Unclear parenthesis.
See previous comment.
(13) L 115: There should be a reference to Methods around here.
Added a reference to Figure 1.
(14) L 117: To be clearer, say instead that dominance value is a linearly increasing function of age as a proxy of RHP and a linearly decreasing function of help provided due to the costs of working tasks. And refer to equation 2.
Rephrased to “We use the term dominance value to designate the competitiveness of an individual compared to other candidates in becoming a breeder, regardless of group membership, that increases as a function of age, serving as a proxy for resource holding potential (RHP), and decreases as a function of help provided, reflecting costs to body condition from performing working tasks (Eq. 2).” We did not include “linearly” to keep it simpler, since it is clear from Eq. 2, which is now referenced here.
(15) L 119: "Subordinate helpers". As all subordinates are helpers, the helper qualifier is confusing.
Subordinates are not necessarily helpers, as they can evolve help values of 0, hence, why we make it explicit here.
(16) L 119: "choose". This terminology may be misleading. The way things are implemented in the model is that individuals are assigned a task depending on their genetic traits gamma. Perhaps it would be better to use a less intentional term, like perform one of two tasks.
We changed “choose between two” to “engage in one of two”, which has less connotations of intentionality.
(17) L 124: "Subordinates can [...] exhibit task specialization that [...] varies with their dominance value". It should be that it varies with age.
Apologies. The equation was wrong; it does vary with dominance value. We corrected it accordingly.
(18) L 133: "maximised" This is apparently important for the modelling procedure, but it is completely unclear what it means. Equation 4 comes out of nowhere, and it is said that such an equation is the maximum amount of help that can affect fecundity. Why? What does this mean? If there is something that is maximised, this should be proven. This value is then used for something (line 507), but it is unclear why or what it is used for (it says "we use the value of Hmax instead" without saying what for, no justification for the listed inequalities are given, and the claimed maximisation of an unspecified variable at those H values is not proven). Moreover, the notation in this section is also unclear: what are the sums over? Also, Hdefence and Hwork should vary over the index that is summed over, but the notation suggests that those quantities don't vary.
We changed “maximized” to “greatest”, and we added a clarification to the rationality behind the maximization of the impact of help in the breeder’s productivity: “For example, in many cooperatively breeding birds, the primary reasons that breeders fail to produce offspring are (1) starvation, which is mitigated by the feeding of offspring, here considered as a work task, and (2) nest depredation, which is countered by defensive behavior. Consequently, both types of tasks are often necessary for successful reproduction, and focusing solely on one while neglecting the other is likely to result in lower reproductive success than if both tasks are performed by helpers within the group.”
We now also clarify that the sums are for help given within a group (L 507), and added indexes to the equations.
(19) L 152: "habitat saturation" How is this implemented? How is density dependence implemented? Or can the population size keep increasing indefinitely? It would be good to plot the population size over time, the group size over time, and the variance in group size over time. This could substantiate later statements about enhancing group productivity and could all be shown in the SI.
Habitat saturation emerges from population dynamics due to the limited availability of territories and the fluctuating number of individuals, leading highly productive environments to experience habitat saturation. Although the number of group members is not restricted in our model, the population could theoretically increase indefinitely. However, this is not observed in the results presented here, as we selected parameter landscapes that stabilize population numbers. We confined our parameters to those where the population neither increased indefinitely (nor collapsed), as we did not incorporate density-dependent mortality traits for simplification. Consequently, the group size in the SI, where the standard deviation is already included, closely represents group size at any other given time during equilibrium.
L 336: we changed “environments with habitat saturation” to “environments that lead to habitat saturation”, to increase clarity.
(20) L 152: "lifecycle". Rather than the lifecycle, the figure describes the cycle of events in a single time step. The lifecycle (birth to death) goes over multiple time steps (as individuals live over multiple steps). So this figure shouldn't be called a life cycle.
We changed “lifecycle” to “breeding cycle”.
(21) L 156: "generation". This is not a generation but a time step.
We changed “generation” to “breeding cycle”.
(22) L 157: "previous life cycle" would mean that the productivity of a breeder depends on the number of helpers that its parents had, which is not what is meant.
We changed “lifecycle” to “breeding cycle”.
(23) L 158: "Maximum productivity is achieved when different helping tasks are performed to a similar extent." Again, unclear why that is the case.
We added a clarification on this, see response to comment 18.
(24) L 160: "Dispersers/floaters". Use just one term for a single thing.
See response to comment 11.
(25) L 162: "dispersal costs". I don't recall these being described in Methods.
Individuals that disperse do not enjoy the protection of living in a territory and within a group of other individuals, so they have a higher mortality risk, described in Eq. 3.3. (negative values in the exponential part of the equation increase survival). The cost of dispersal is the same as individuals that remain as floaters at a given time step.
(26) L 164: "generation" -> time step.
We changed this to “breeding cycle”.
(27) L 170: "Our results show that division of labor initially emerges because of direct fitness benefits..." This is a general statement, but the results are only particular to the model. So this statement and others in the manuscript should be particular to the model. Also, Figure 2 doesn't say anything about what evolves "initially" as it only plots evolutionary equilibria.
We rephrased this statement to “Our results suggest that voluntary division of labor involving tasks with different fitness costs is more likely to emerge initially because of direct fitness benefits”, to more accurately represent the conditions under which we modeled the division of labor.
Our reference to “initially” is regarding group formation (family groups versus aggregations of unrelated individuals or a mix). This is shown in the comparison between the different graphs at equilibrium. The initial state of the simulation is that all individuals disperse and do not cooperate.
(28) L 171: "but a combination of direct and indirect fitness benefits leads to higher rates and more stable forms of division of labor". What do you mean by "higher rates and more stable forms of division of labor"? Say how division of labor is shown in the figure (with intermediate T?).
Yes, intermediate values of T show division of labor if γR ≠ 0. This is described under the section “The role of dominance in task specialization”. We added “with intermediate values suggesting a division of labor” to the Figure 2 legend.
(29) L173-175: "as depicted in Figure 2, intermediate values of task specialization indicate in all cases age/dominance-mediated task specialization (γt ≠ 0; Table 1) and never a lack of specialization (γt = 0; Table 1)". This sentence is unclear and imprecise. Does this sentence want to say that in Figure 2, all plots with intermediate values of T involve gamma t different from zero? If so, just say that.
Rephrased to: “In Figure 2, all plots depicting intermediate values of T exhibit non-zero γR values and, hence, division of labor”.
(30) L179-180: "forms of help that impact survival never evolve under any environmental condition when only kin selection occurs". This is misleading because under the KS scenario, help cannot positively impact survival in this model, so they never evolve.
Help cannot affect survival but could potentially affect group persistence. If helpers increase breeder productivity and offspring remain philopatric and queue for the breeding position, then they will receive help from related individuals.
(31) L 210: "initially". What do you mean by that?
Help only evolves in our model in family groups, which may then open the door for the evolution of help in mixed-kin groups. Therefore, we use “initially” to refer to the ancestral group structure that likely led to cooperation under benign environmental conditions. We rephased this section to “in more benign (and often highly productive) environments that lead to habitat saturation, help likely evolved initially in family groups, and defensive tasks are favored because competition for the breeding position is lower under kin selection.”
(32) L 212: "kin selection is achieved". What does that mean?
Rephased to “kin selection acts not only by selecting subordinates in their natal group to increase the productivity of a related breeder […]”
(33) L 216: "division of labor seems to be more likely to evolve in increasingly harsh environments". Say in parentheses where this is shown.
Added.
(34) L 218: "help evolves in benign environments". I don't see where this is shown. Figure 2 doesn't show that H is higher with lower m (e.g., in KS+GA column).
Help does not evolve in benign environments under only direct fitness benefits derived from group augmentation (shown in Figure 2).
(35) L 225: "y-axis" should be "vertical axis", as y has another meaning in the model.
Done.
(36) L 226: "likelihood". Here and throughout, "likelihood" should be changed to probability. Likelihood means something else.
Thank you for the advice, we have corrected this through the manuscript.
(37) L 236: "the slope of the reaction norm for the dominance value in task specialization".
Unclear. Clearer to say: the rate at which individuals to shift from defense to work as they age.
The important part is not so much the rate but the direction, that is, from work task to defense (or vice versa) as their rank increases. Changed to “the direction and rate of change in task specialization with dominance”.
(38) L 257: "(task = 0; cost to dominance value)," This seems out of place.
This aims to clarify that work tasks have a cost to dominance, while defense tasks have a cost to survival. This is particularly relevant in this model since different helping tasks are defined by their fitness costs.
(39) L 258: "increase"-> "increase with age".
Added “with dominance”.
(40) L 262: "division of labor equilibria" What is that?
Changed to “at equilibrium when division of labor evolves”
(41) L 268: "Our findings suggest that direct benefits of group living play a driving role in the evolution of division of labor via task specialization in species with totipotent workers". This is a very general statement, but the results are much more circumscribed. First, the model is quite specific by assuming that, in the absence of group augmentation (xn=0), indirect fitness benefits can only be given to breeders (Equation 5) but not to other subordinates (Equations 2, 3.1). This is unrealistic, particularly for vertebrates, and reduces the possibility that indirect fitness benefits play a role.
As previously discussed, the scope of this paper was to study division of labor in cooperatively breeding species with fertile workers in which help is exclusively directed towards breeders to enhance offspring production through alloparental care. Other forms of “general” help do not result in task partitioning to enhance productivity.
Second, the difference in costs of work and defense are what drive the evolution of "division of labor" (understood as intermediate T in case this is what the authors mean) in the KS scenario, but the functional forms of those two costs are quite specific and not of the same form, so these functions may bias the results found. Specifically, R is an unbounded linear function of work and the effect of this function becomes weaker as the individual ages due to the weakening force of selection with age (Equation 2) whereas Sh is a particular bounded nonlinear function of defense (Equation 3.1). These differences may tend to make the effect of Sh stronger due to the particular functions chosen.
The difference in costs is inherent to the nature of the different tasks (work versus defense): while survival is naturally bounded, with death as the lower bound, dominance costs are potentially unbounded, as they are influenced by dynamic social contexts and potential competitors. Therefore, we believe that the model’s cost structure is not too different from that in nature.
Third, no parameter sweep is given to see to what extent these results hold across the many parameters involved. So, in summary, the discussion should at least reflect that the results are of a restricted nature rather than giving the impression that they are of the suggested level of generality.
During the exploratory phase of the model development, various parameters and values were assessed. However, the manuscript only details the ranges of values and parameters where changes in the behaviors of interest were observed, enhancing clarity and conciseness. For instance, variation in yh (the cost of help on dominance when performing “work tasks”) led to behavioral changes similar to those caused by changes in xh (the cost of help in survival when performing “defensive tasks”), as both are proportional to each other. Specifically, since an increase in defense costs raises the proportion of work relative to defense tasks, while an increase in the costs of work task has the opposite effect, only results for the variation of xh were included in the manuscript to avoid redundancy. Added to Table 1: “To maintain conciseness, further exploration of the parameter landscape was not included in the manuscript”.
(42) L 270: "in eusocial insects often characterized by high relatedness and reproductive inhibition, sterile workers acquire fitness benefits only indirectly". This is misleading. Sterile workers of any taxa, be it insects or vertebrates, can only acquire fitness benefits indirectly as they are sterile, but eusocial insects involve not only sterile workers.
Rephased to “In contrast, in eusocial species characterized by high relatedness and permanent worker sterility, such as most eusocial insects, workers acquire fitness benefits only indirectly”. In any case, permanent sterility only occurs in eusocial invertebrates; in vertebrates with reproductive inhibition sterility is only temporal and context dependent. Therefore, in vertebrates, sterile workers may potentially obtain direct fitness benefits if the social context changes, as is the case in naked mole-rats.
(43) L 273: "Group members in eusocial species are therefore predicted to maximize colony fitness due to the associated lower within-group conflict". Again, this is incorrect. Primitively eusocial insects have high conflict.
We added “Group members in such eusocial species” to clarify that we are not referring here to primitively eusocial species but those with permanent sterile workers.
(44) L 277: "when the benefits of cooperation are evenly distributed among group members". In this model, the benefits of cooperation are not evenly distributed among group members: breeders reproduce, but subordinates don't.
Subordinates may reproduce if they become breeders later in life. However, subordinates also benefit from cooperation as subordinates directly (greater survival in larger groups), and indirectly if they are related to the breeder. Here we refer to the first one, and we expand on that in the following sentence.
(45) L 280: "survival fitness benefits derived from living in larger groups seem to be key for the evolution of cooperative behavior in vertebrates [22, 63], and may also translate into low within-group conflict. This suggests that selection for division of labor in vertebrates is stronger in smaller groups". I don't see how the previous sentence suggests this. The paper does not present results to support this statement (i.e., no selection gradients in smaller vs larger groups are shown).
The benefits of living in a larger group entail diminishing returns, so those living in smaller groups benefit greater by an increase in productivity and group size than those in a larger group.
(46) L 284: "Our model demonstrates that vertebrates evolve a more stable division of labor". Where is that shown? How is "more stable" measured?
Rephrased to “vertebrates are more likely to evolve division of labor”. This is shown in Figure 2, that exemplifies that division of labor evolves in a wider range of environmental condition and to a higher degree (intermediate values of T).
(47) L 287: "direct fitness benefits in the form of group augmentation select more strongly for defensive tasks". Where is that shown? Establishing this would entail comparing selection gradients with direct fitness benefits of group augmentation and without them.
In Figure 2, when we compare the GA column to KS+GA column, we see that at equilibrium, more helpers choose defense tasks, specially when they are free to choose their preferred task (circles).
(48) L 288: "kin selection alone seems to select only for work tasks." Again, this may be an artifact of the model assuming that helpers cannot increase non-breeders' fitness components except via group augmentation, and that defense tasks are inherently more costly than work tasks.
As stated previously, we are studying task specialization in cooperative breeders where help is in the form of alloparental care (from allofeeding and egg care to defense from predators). We also assume that the costs are different, but whether one or the other is more costly depends on the relative context (e.g., a task can be more costly if it affects competitiveness in a very competitive environment). It is important to note that we name these tasks “work” and “defense” for practical reasons, but the focus of the paper is on tasks with different fitness costs that for their characteristics may not fit so well in under this terminology. While we acknowledge that most tasks have both kinds of fitness costs to a degree, here we focus on the main fitness costs of each kind of task (L430-436).
(49) L 290: "are comparatively large". This sounds as if the tasks are large, which is presumably not what is meant.
Rephrased to “costs to dominance value and to the probability of attaining a breeding position are comparatively larger than survival costs.”
(50) L 298: "helpers are predicted to increase defensive tasks with age or rank, whereas in harsh environments, work tasks are predicted to increase with age or rank." Add parentheses referring to where this is shown.
This is shown in Figure 3, but since this is described in the discussion, we did not add a reference to the figure. If the editor would like us to refer to figures here, we can (see also comments below relating to the same issue).
(51) L 308: "the role of age and environmental harshness on the evolution of division of labor". What is the prediction? Simply, the role of age is an assumption, not a prediction.
Rephrased to “the role of environmental harshness on the evolution of division of labor via age-dependent task specialization”.
(52) L 315: "individuals shifting from work tasks such as foraging for food, digging, and maintaining the burrow system, to defensive tasks such as guarding and patrolling as individuals grow older and larger". Say in parentheses where this is predicted.
This prediction comes from Figure 3, we do not reference it here since we are in the Discussion section.
(53) L 320: "Under these conditions, our model predicts the highest levels of task partitioning and division of labor." Where is this predicted? Add parentheses referring to where this is shown. As it is, it is not possible to check the validity of the statement.
This prediction comes from Figure 2 column KS+GA, we do not reference it here since we are in the Discussion section. The results with references to the figures are found under the Results section. In the discussion, we reiterate the results already described and add some examples from real data that seem to confirm our predictions.
(54) L 322: "In line with our model predictions, larger and older helpers of this species invest relatively more in territory maintenance, whereas younger/smaller helpers defend the breeding shelter of the dominant pair to a greater extent against experimentally exposed egg predators". These predictions are neat, but are now very difficult to understand from the figures. Maybe at the bottom of 3A, you could add a diagram work->defense for negative gamma_t and defense>work for positive gamma_t (or whatever order it is).
Done.
(55) L 325: "Territory maintenance has been shown to greatly affect routine metabolic rates and, hence, growth rates [80], which directly translates into a decrease in the likelihood of becoming dominant and attaining breeding status, as predicted by our model." This seems to be an assumption, not a prediction.
That is true. We removed: “as predicted by our model”.
(56) L 352: "controlled". This means something else.
Changed to “addressed”.
(57) L 356: "summary, our study represents the first theoretical model aimed at elucidating the potential mechanisms underlying division of labor between temporal non-reproductives via task specialization in taxa beyond eusocial organisms". Again, claiming to be the first is risky and unnecessary.
Rephrased to “our study helps to elucidate”.
(58) L 358: "Harsh environments, where individuals can obtain direct fitness benefits from group living, favor division of labor, thereby enhancing group productivity and, consequently, group size." I'm not sure about this conclusion as harsh environments (large m in Figure 2) also involve the evolution of no division of labor (from the triangles and circles that are zero in the right bottom panel) and perhaps more so than with less harsh environments (intermediate m). Incidentally, in the bottom right panel of Figure 2, do the two separate clusters of triangles and circles mean that there is some sort of evolutionary branching?
Yes, there are two different equilibria for the same set of conditions. Although it is true that for m=0.3 less division of labor evolves when kin selection and group augmentation act together, it is not the case when only group augmentation takes place. In addition, we qualify m=0.2 as harsh as opposed to benign in which we observe the rise of habitat saturation (m=0.1). m=0.3 is then an extreme harsh environment, in which in several instances different parameter landscape causes population collapse (see figures in the Supplemental Material).
(59) L 360: "Variation in the relative fitness costs of different helping tasks with age favors temporal polyethism". I don't see that this has been shown. Temporal polyethism evolves here whenever gamma_t evolves non-zero values. Figure 3A shows that non-zero gamma_t evolves with harsher environments, but I don't see what the "variation in relative fitness costs of different helping tasks" refers to.
The evolved reaction norms of the model are towards different fitness costs depending on the task performed, since this is how we define the different types of tasks in the model.
(60) L 382: "undefined". Say variable. Undefined is something else.
Undefined is more accurate, since we did not define how many subordinates there were per group, while “variable” could have been defined within a range, which was not the case in this model.
(61) L 390: "each genetic locus". Say earlier that each genetic trait is controlled by a single locus.
Added.
(62) L 395: "complete" and "consistent" -> "certain".
We changed one to “certain” and another to “absolute” to avoid using the same adjective twice in a sentence.
(63) L 396: What determines whether dispersers become subordinates or floaters? A trait? Or a fixed probability?
We added “which is also controlled by the same genetic dispersal predisposition as for subordinates”.
(64) L 412-413: "cycle". This should be a breeding step.
Changed to “season” instead.
(65) L 418: Say negatively impacts (it could also be positively impacts, which I guess is not what you mean).
Done.
(66) L 425: "a sample of floaters". Chosen how?
Added “randomly drawn”.
(67) L 426-428. But the equation in Table 1 indicates that all floaters compete for breeding spots, not a sample of floaters. This is not clear.
The number of floaters sampled to try to breed at a given group is N<sub>f,b</sub> = 𝑓∗𝑁<sub>𝑓</sub>/𝑁<sub>𝑏</sub> (Table 1).
Therefore, N<sub>f,b</sub> is the sample size of floaters for a given open breeding position, and f is how many groups on average a floater attempts to access in each time step.
(68) L 432. In the figure, the breeding cycle is called a step, but here it is called a cycle. There should be a single term used throughout. Breeding is not really a cycle here (it doesn't involve multiple steps that are repeated cyclically), so it seems more appropriate to call this breeding steps or breeding seasons.
Taken into account previous comments, we changed the terms “generation” and “life cycle” to “breeding cycle”. We added “or seasons”.
(69) L 439: "generations". What are generations here, as generations are overlapping? You probably mean time steps or something else.
Changed to “breeding cycles”.
(70) L 439: "equilibrium was reached". Presumably, equilibrium is reached only asymptotically, so some cutoff is implemented in practice. So maybe say explicitly what cutoff was implemented.
As mentioned, we run the model for 200’000 time steps, and if equilibrium was not reached for the phenotypic values, then we run the model for longer, with 400’000 time steps being the maximum at which all simulation reached equilibrium. In some cases, genetic values did not reach equilibrium at ranges at which there was no impact on phenotypic values, so these were disregarded to assess whether equilibrium was reached.
(71) L 452: "Even though individuals are likely to change the total amount of help given throughout their lives". Do you mean in real organisms or in the model? Say which. If it is in the model, it is not clear how.
We added “in nature” to clarify that this was not the case in the model.
(72) L 455: "For more details on how individuals may adapt their level of help with age and social and environmental conditions, see [63]." Do you mean real individuals or in the model? Again, if it is in the model, it is unclear how this is possible and should be explained in this paper at least briefly rather than citing another one.
We rephrased it to “How individuals in the model may adapt their level of help with age and social and environmental conditions has been described elsewhere.” We do not go into detail here because it is not within the scope of the paper, and those results have been described elsewhere.
(73) L 475: "helpers". Make terminology consistent throughout.
All helpers are subordinates, but not all subordinates are helpers, as they may evolve no help. Since here we are describing those subordinates that do help, we use that terminology. We added “subordinate helpers” to clarify this further.
(74) L 476: "proportional". The dependence in Equation 1 is not "proportional to". Say something like "a survival probability (not rate) that decreases with the amount of help provided".
Done.
(75) L 482: "environmental"-> baseline, as defined first.
Done.
(76) L 486: "benefits". Can you briefly say in parentheses what those benefits are in real organisms? As in line 475, where you reminded the reader of survival costs due to predator defense.
Added “such as those offered by safety in numbers or increased resource defense potential”.
(77) L 494. "we first outline a basic model in which individuals". It is not clear what this sentence says, and the remainder of this section does not clarify it.
We made two models for comparison, one where individuals can choose freely which task they prefer to perform, and another in which there is an increase in productivity when both kinds of tasks are performed to a similar extent at group level. In the latter model, individuals may choose an unpreferred task at certain times during their lived to increase the effect of the help provided in the breeder’s (and group’s) productivity.
We rephrased this section to “we first outline a basic model where individuals evolve their preferred helping task. Then we compare this to another model in which the breeder’s reproductive outcome is maximized when the group’s helping effort in each kind of tasks is performed to a roughly equal degree.”
(78) L 496: "by performing both tasks". Sounds as if the breeder performs both tasks, not helpers.
We changed to “when the group’s helping effort in each kind of tasks”.
(79) L 497: "the maximum amount of cumulative help of each type (sigma Hmax) that can affect fecundity is given by Eq. 4:" This statement is imprecise. Presumably, what is meant is that this level of help maximises breeder productivity, as stated earlier in the paper. However, there is no proof that this level of help maximises breeder productivity, so this expression seems unjustified and it is unclear how it is used.
This is a description of the model set up. As described later in the same section, the cumulative help of each time that will influence the breeder’s fecundity if maximum Hmax. Therefore, it does represent the maximum amount of cumulative help of each type that can affect the breeder’s fecundity.
(80) L 500: "reproduced" -> "reproduce".
Done.
(81) L 503. Say here what K is so that the reader knows what equation 5 is showing.
Added “K” to the “The quantity of offspring produced (K)”.
(82) L 503: "diminishing returns" -> "diminishing returns as help increases".
Done.
(83) L 507: Why these inequalities?
These inequalities explain the use of Hmax (response to comment 79). We rephased it to “the cumulative defense effort is larger than 
or the cumulative work effort is larger than 
”.
(84) L 526: "removing the influence of relatedness from the model". It would be helpful to plot relatedness in this and the other scenario to check that it is indeed low here and high in the other.
The actual values of relatedness are provided in the Supplemental Material Table S1. We added this reference to Figure 2.
(85) L 528: "It is possible that direct and indirect fitness benefits could have an additive effect on the evolution of alloparental care". This is technically incorrect. It is also unclear what the point of this sentence is.
We have removed this sentence.
(86) Table 1: Say what are the allowed values for these genotypic traits (can they take negative values, be greater than one, are they continuous or discrete?): e.g., alpha \in [0,1] or alpha \in (-infinity, infinity). For phenotypic traits, it would be helpful if the third column lists the equation where the trait is defined. As the variables in the first column are scalars, they should not be bold face. Survival "rate" should be survival "probability" throughout.
All genetic traits can take any real number (-infinity, infinity), but the phenotypic values are either constrained by the equation like for logistic formulas, or manually constrained like for dispersal propensity or help (only positive numbers allowed). We added “Each genetic trait is controlled by a single locus, and may take any real number” (L403), and added the boundaries for help and dominance value in Table 1. We decided against including the equations in the table due to space constraints. We removed the bold face as suggested. We changed all instances of “survival rate” to “survival probability”.
(87) Figures S1, S2: I don't recall seeing references to these figures in the main text, but there should be, as well as for Tables S1-S3.
Table S1 is now referenced in Figure 2. The other figures are now referenced in the main text when we reference the different sections in the Supplemental Materials (L190 and L198). Other Tables are referenced in their respective Figures in the SI.
