the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Aug 2025
BORIS-2 – a benthic ecosystem model based on allometry
Abstract. We present a model describing the population dynamics of benthic biota, feeding from a common resource that is supplied by a flux of sinking organic carbon arriving on the seafloor. By using allometric relationships for the physiological processes of growth, mortality and respiration, and for food limitation, the model represents the population dynamics of organisms ranging in size from bacteria (10-14 g wet weight C) to large metazoans (103 gwwt C). The effect of temperature on physiological rates is also included. The only forcing information required is the ambient temperature and the rate of supply of sinking organic carbon. The model can be used for, and tuned to, specific locations. However, a parameter set is provided that is generally applicable. The ability of the model to simultaneously reproduce biomass size distributions at five contrasting sites is demonstrated for this parameter set. Other examples of use are also shown, using the model to explore global patterns of benthic biomass, and responding to a change in food supply.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Geoscientific Model Development. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.-
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2025-2180', Juan Antonio Añel, 08 Aug 2025
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CC1: 'Reply on CEC1', Andrew Yool, 08 Aug 2025
Dear Juan,
Thank you for your assessment of our repository. This is just to confirm that it does contain the model code, both for running in steady state (via steady_state.m) and dynamic (via benthic_dydt.m) modes. The repository also contains the scripts necessary for producing the figures that appear in the manuscript, and our Supplement includes a User Manual for using the scripts archived in the Zenodo record. If you think that any of these materials are insufficiently clear, please let us know and we will amend them when the manuscript is revised. We hope this is sufficient clarification for our manuscript's Discussion to proceed.
With best regards,
Andrew Yool.
Citation: https://doi.org/10.5194/egusphere-2025-2180-CC1 -
CEC2: 'Reply on CC1', Juan Antonio Añel, 08 Aug 2025
Dear authors,
Thanks for the quick clarification. Our doubt was caused by the fact that routines included look quite basic, only showing a few parameters and lines of code. Could it be that you have included relevant information in the binary files (.mat) which we can not read? It would be good if you could avoid sharing information as binary files that only can be read using the M language interpreter. If you can, please, do it.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-2180-CEC2 -
CC2: 'Reply on CEC2', Andrew Yool, 08 Aug 2025
Dear Juan,
As an allometric model with only a few process terms, BORIS is deceptively simple, so its codebase is quite brief. Running it does not require the *.mat files directly - these provide geographical boundary conditions / forcing. As the model is essentially non-spatial, this forcing information is ordinarily provided via its parameter list. However, this sort of additional geographical information allows BORIS to be run for arbitrary spatial locations, or to be run across the globe systematically, as can be see in Figure 4. I hope this answers your question.
With best regards,
Andrew Yool.
Co-author.
Citation: https://doi.org/10.5194/egusphere-2025-2180-CC2
-
CC2: 'Reply on CEC2', Andrew Yool, 08 Aug 2025
-
CEC2: 'Reply on CC1', Juan Antonio Añel, 08 Aug 2025
-
AC1: 'Reply on CEC1', Adrian Martin, 18 Aug 2025
I am very sorry for my delay in replying but I am only just back from leave.
With thanks to him for doing so in my absence, I hope the response by co-author Andrew Yool has addressed your concerns.
By way of summary, we have provided all code necessary to run the model and all data files needed to reproduce all figures in the manuscript. The code has been fully listed and described on the associated Zenodo page and there is additionally a User Guide included as Supplementary Material to the manuscript.
The model may appear simple but this is largely because the use of allometry allows considerable computational efficiency when modelling the dynamics of organisms spanning a very large range of sizes. This advantage offered by the allometric approach is a significant factor in why we thought GMD the ideal journal to publish in. The model simultaneously and explicitly simulates the dynamics of 59 size groups of organisms as well as the food supply supporting them.
If you need any further information please don't hesitate to ask.
Citation: https://doi.org/10.5194/egusphere-2025-2180-AC1
-
CC1: 'Reply on CEC1', Andrew Yool, 08 Aug 2025
-
RC1: 'Comment on egusphere-2025-2180', Anonymous Referee #1, 25 Nov 2025
The manuscript describes the BORIS-2 model, a benthic ecosystem model based on class size that builds on a previous version that simulated ecosystems with a smaller size range and different representation of physiological processes. It describes a steady state solution used to test and evaluate the model and compare it to data from five different sites with a range of depths and overlying pelagic environments.
The authors did an excellent job organizing the manuscript; the explanation on the model itself, the validation and choice of coefficients, and the differences between the current version and BORIS-1 are well written and well linked when necessary. The arguments justifying the choices that need to be made to choose general coefficients and forcings to represent the different sites are well argued and informative for users that may want to run a transient version.
The figures and tables are clear and contain all the necessary information. In my view the paper is suitable for publication, although I do have a few of suggestions on the text:
Line 289-291: It seems reasonable to me to use the sediment traps at 3000 m, but out of curiosity, how much to they diverge? Thinking of future exercises linking ecosystem to sediment diagenetic processes, information of resuspension/sedimentation is always useful
Line 304-307: these sentences could be linked better
Line 519-521: The global estimate of carbon burial also shows spatial variation, thought to be much higher in shelf environments. I would assume there could be differences between the shallower and deeper sites chosen for model validation that could be mentioned or briefly discussed here.
Citation: https://doi.org/10.5194/egusphere-2025-2180-RC1 - AC2: 'Reply on RC1', Adrian Martin, 31 Mar 2026
-
RC2: 'Comment on egusphere-2025-2180', Anonymous Referee #2, 10 Dec 2025
In this manuscript Martin et al. provide a model description and evaluation of an updated benthic community model, BORIS2. This model is a size based model of benthic heterotrophs / detritivores and extends the size range of the previous BORIS model both on the lower and upper ranges. Compared with the previous BORIS model, this second version also makes a number of improvements on the assumptions around metabolism and ingestion. This model is evaluated against 5 sites, including abyssal sites at the Porcupine abyssal plain and clarion clipperton zone. The inclusion of these two deep sites makes it so that this model is much more readily applicable for regional or other large-scale domains.
Main comments
My primary concern in this manuscript surrounds the introduction of the interference parameter, a_i. This parameter is described as the competitive interference between other scavengers, and shows up in the growth/feeding equation as modifying the biomass B. My concern about this primarily is because the size scaling parameters for the other processes are all identical (see next paragraph) – the entirety of the emergent structure of the community relies on this single parameter, which is very poorly understood and is not common to other ecosystem models. The functional form of the feeding relationship changes such that if you were to rewrite it to an equivalent Monod-like relationship, it would be g*f(R,B) = gR/(R+aB) but instead of a fixed half-saturation constant, aB varies with mass. So then the initial slope becomes R/aB. While I am not doubting that the introduction of a size-dependent scaling for Biomass in this feeding relationship could be useful, unfortunately I am also not convinced of the need for it either. Perhaps it is because I am not familiar with DeAngelis et al. 1975. To convince readers, perhaps the authors could show plots of this functional form (at a minimum), and ideally some more plots showing the authors’ central claim here, that you cannot achieve an emergent community structure in this model that matches observations without this parameter included. Personally, I think that it may be possible to achieve reasonable matches with the observations with more parsimonious parameterizations, if the scaling exponents for the other processes were allowed to vary.
The scaling exponents for growth, respiration, and mortality are all the same and set to -0.1. It is not the most common practice amongst community/ecosystem models to set all of the biomass scaling exponents to be the same value. As the authors state in section 2.7, a more common scaling for growth and respiration would be around -0.2 or -0.25 (I think the theoretical prediction would be -0.25 but realistic values may vary). However, mortality is often assumed to have a different scaling than growth and respiration. Here, in this model, there is no representation of predators of these organisms (i.e., demersal fish) so I was a little surprised that the authors removed the quadratic loss term, and did not tune the mortality scaling to implicitly represent the role of predators within the ecosystem. In this case the emergent community structure then arises from the relationship between growth-respiration and mortality.
Can you describe a bit more what ends up being the closure term in the model, and if not – whether the lack of a closure term ends up constraining your parameter space so that bottom-up control can be the dominant control for the ecosystem?
Finally, for the benthos, the authors use the scaling exponent of the biomass size spectrum to constrain the model. I completely understand that these are very poorly observed systems and that available observational constraints are few and far in between. However, the danger in using the biomass size spectrum slope to validate the model is that very small variations in the size spectrum slope can have large implications for the total biomass. From a quick calculation, a 10% variation in the (normalized) biomass size spectrum slope (from -0.5 to -0.55) for a community that spans 10 orders of magnitude in size (e.g. 1 to 1e10 micrograms C) would result in a 3-fold difference in total community biomass. (This is using the fact that the normalized biomass size spectrum is integrable). Ecosystem modelers would certainly consider a 10% difference from an observed quantity to be an absolutely excellent match – but here the implications for total community biomass become quite large when the observed quantity used for model validation is a scaling exponent.
What would enhance this manuscript would be a series of sensitivity studies showing focused (generally) on the range of parameter space for this model. I appreciated that the authors included section 2.7 but I found it difficult to follow without some examples in the manuscript. Ideally, it would be great to see what the model results are when interference pre-factor were set to low values and the interference exponent was set to 0, combined with allowing beta of mortality to vary relative to the beta of growth and respiration, but I leave it up to the authors to decide what would be most appropriate.
Lastly – it would be remis for me to write all this without noting that it is extremely difficult to model a system that is as poorly observed and understood as the benthos. All model representations of a new system must start somewhere and BORIS1/BORIS2 is notable as the first of its kind. I apologize for the somewhat rambling paragraphs above – but in my mind, all these model and parameter choices are all highly connected with each other.
Minor comments
Lines 112-113, I think fg should be kg, right?
Line 260, I found it confusing that the biomass scaling (alpha) was defined as a negative, resulting in values that are negative. I look into the benthos observations literature specifically and did not get the sense that this was common practice. If not common practice can you just use the raw values, allowing alpha to be positive?
Section 2.7, lines 385-384, 406-425. I overall like this discussion but found it hard to follow without some more concrete examples.
Citation: https://doi.org/10.5194/egusphere-2025-2180-RC2 - AC3: 'Reply on RC2', Adrian Martin, 31 Mar 2026
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2025-2180', Juan Antonio Añel, 08 Aug 2025
Dear authors,
After checking your manuscript, we have great doubts about its compliance with the Code and Data policy of our journal.
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
In the Zenodo repository that you cite, a few routines are shared (namely four M language scripts), which do not seem to be the full BORIS-2 model that you present in your manuscript.
Our policy is clear regarding the fact that all the code and data necessary to replicate the work presented in a manuscript must be public and without access restrictions before the submission of a manuscript to our journal. Therefore, please clarify if the current code in the Zenodo repository that you have shared is all the BORIS-2 code. If it is not the case, please, in a prompt manner publish the BORIS-2 code in an acceptable repository from the ones listed in our policy, and reply to this comment with the information for it: links and permanent handler (e.g. DOI).
I note that in lack of compliance with our policy we will have to reject your manuscript for publication.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-2180-CEC1 -
CC1: 'Reply on CEC1', Andrew Yool, 08 Aug 2025
Dear Juan,
Thank you for your assessment of our repository. This is just to confirm that it does contain the model code, both for running in steady state (via steady_state.m) and dynamic (via benthic_dydt.m) modes. The repository also contains the scripts necessary for producing the figures that appear in the manuscript, and our Supplement includes a User Manual for using the scripts archived in the Zenodo record. If you think that any of these materials are insufficiently clear, please let us know and we will amend them when the manuscript is revised. We hope this is sufficient clarification for our manuscript's Discussion to proceed.
With best regards,
Andrew Yool.
Citation: https://doi.org/10.5194/egusphere-2025-2180-CC1 -
CEC2: 'Reply on CC1', Juan Antonio Añel, 08 Aug 2025
Dear authors,
Thanks for the quick clarification. Our doubt was caused by the fact that routines included look quite basic, only showing a few parameters and lines of code. Could it be that you have included relevant information in the binary files (.mat) which we can not read? It would be good if you could avoid sharing information as binary files that only can be read using the M language interpreter. If you can, please, do it.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-2180-CEC2 -
CC2: 'Reply on CEC2', Andrew Yool, 08 Aug 2025
Dear Juan,
As an allometric model with only a few process terms, BORIS is deceptively simple, so its codebase is quite brief. Running it does not require the *.mat files directly - these provide geographical boundary conditions / forcing. As the model is essentially non-spatial, this forcing information is ordinarily provided via its parameter list. However, this sort of additional geographical information allows BORIS to be run for arbitrary spatial locations, or to be run across the globe systematically, as can be see in Figure 4. I hope this answers your question.
With best regards,
Andrew Yool.
Co-author.
Citation: https://doi.org/10.5194/egusphere-2025-2180-CC2
-
CC2: 'Reply on CEC2', Andrew Yool, 08 Aug 2025
-
CEC2: 'Reply on CC1', Juan Antonio Añel, 08 Aug 2025
-
AC1: 'Reply on CEC1', Adrian Martin, 18 Aug 2025
I am very sorry for my delay in replying but I am only just back from leave.
With thanks to him for doing so in my absence, I hope the response by co-author Andrew Yool has addressed your concerns.
By way of summary, we have provided all code necessary to run the model and all data files needed to reproduce all figures in the manuscript. The code has been fully listed and described on the associated Zenodo page and there is additionally a User Guide included as Supplementary Material to the manuscript.
The model may appear simple but this is largely because the use of allometry allows considerable computational efficiency when modelling the dynamics of organisms spanning a very large range of sizes. This advantage offered by the allometric approach is a significant factor in why we thought GMD the ideal journal to publish in. The model simultaneously and explicitly simulates the dynamics of 59 size groups of organisms as well as the food supply supporting them.
If you need any further information please don't hesitate to ask.
Citation: https://doi.org/10.5194/egusphere-2025-2180-AC1
-
CC1: 'Reply on CEC1', Andrew Yool, 08 Aug 2025
-
RC1: 'Comment on egusphere-2025-2180', Anonymous Referee #1, 25 Nov 2025
The manuscript describes the BORIS-2 model, a benthic ecosystem model based on class size that builds on a previous version that simulated ecosystems with a smaller size range and different representation of physiological processes. It describes a steady state solution used to test and evaluate the model and compare it to data from five different sites with a range of depths and overlying pelagic environments.
The authors did an excellent job organizing the manuscript; the explanation on the model itself, the validation and choice of coefficients, and the differences between the current version and BORIS-1 are well written and well linked when necessary. The arguments justifying the choices that need to be made to choose general coefficients and forcings to represent the different sites are well argued and informative for users that may want to run a transient version.
The figures and tables are clear and contain all the necessary information. In my view the paper is suitable for publication, although I do have a few of suggestions on the text:
Line 289-291: It seems reasonable to me to use the sediment traps at 3000 m, but out of curiosity, how much to they diverge? Thinking of future exercises linking ecosystem to sediment diagenetic processes, information of resuspension/sedimentation is always useful
Line 304-307: these sentences could be linked better
Line 519-521: The global estimate of carbon burial also shows spatial variation, thought to be much higher in shelf environments. I would assume there could be differences between the shallower and deeper sites chosen for model validation that could be mentioned or briefly discussed here.
Citation: https://doi.org/10.5194/egusphere-2025-2180-RC1 - AC2: 'Reply on RC1', Adrian Martin, 31 Mar 2026
-
RC2: 'Comment on egusphere-2025-2180', Anonymous Referee #2, 10 Dec 2025
In this manuscript Martin et al. provide a model description and evaluation of an updated benthic community model, BORIS2. This model is a size based model of benthic heterotrophs / detritivores and extends the size range of the previous BORIS model both on the lower and upper ranges. Compared with the previous BORIS model, this second version also makes a number of improvements on the assumptions around metabolism and ingestion. This model is evaluated against 5 sites, including abyssal sites at the Porcupine abyssal plain and clarion clipperton zone. The inclusion of these two deep sites makes it so that this model is much more readily applicable for regional or other large-scale domains.
Main comments
My primary concern in this manuscript surrounds the introduction of the interference parameter, a_i. This parameter is described as the competitive interference between other scavengers, and shows up in the growth/feeding equation as modifying the biomass B. My concern about this primarily is because the size scaling parameters for the other processes are all identical (see next paragraph) – the entirety of the emergent structure of the community relies on this single parameter, which is very poorly understood and is not common to other ecosystem models. The functional form of the feeding relationship changes such that if you were to rewrite it to an equivalent Monod-like relationship, it would be g*f(R,B) = gR/(R+aB) but instead of a fixed half-saturation constant, aB varies with mass. So then the initial slope becomes R/aB. While I am not doubting that the introduction of a size-dependent scaling for Biomass in this feeding relationship could be useful, unfortunately I am also not convinced of the need for it either. Perhaps it is because I am not familiar with DeAngelis et al. 1975. To convince readers, perhaps the authors could show plots of this functional form (at a minimum), and ideally some more plots showing the authors’ central claim here, that you cannot achieve an emergent community structure in this model that matches observations without this parameter included. Personally, I think that it may be possible to achieve reasonable matches with the observations with more parsimonious parameterizations, if the scaling exponents for the other processes were allowed to vary.
The scaling exponents for growth, respiration, and mortality are all the same and set to -0.1. It is not the most common practice amongst community/ecosystem models to set all of the biomass scaling exponents to be the same value. As the authors state in section 2.7, a more common scaling for growth and respiration would be around -0.2 or -0.25 (I think the theoretical prediction would be -0.25 but realistic values may vary). However, mortality is often assumed to have a different scaling than growth and respiration. Here, in this model, there is no representation of predators of these organisms (i.e., demersal fish) so I was a little surprised that the authors removed the quadratic loss term, and did not tune the mortality scaling to implicitly represent the role of predators within the ecosystem. In this case the emergent community structure then arises from the relationship between growth-respiration and mortality.
Can you describe a bit more what ends up being the closure term in the model, and if not – whether the lack of a closure term ends up constraining your parameter space so that bottom-up control can be the dominant control for the ecosystem?
Finally, for the benthos, the authors use the scaling exponent of the biomass size spectrum to constrain the model. I completely understand that these are very poorly observed systems and that available observational constraints are few and far in between. However, the danger in using the biomass size spectrum slope to validate the model is that very small variations in the size spectrum slope can have large implications for the total biomass. From a quick calculation, a 10% variation in the (normalized) biomass size spectrum slope (from -0.5 to -0.55) for a community that spans 10 orders of magnitude in size (e.g. 1 to 1e10 micrograms C) would result in a 3-fold difference in total community biomass. (This is using the fact that the normalized biomass size spectrum is integrable). Ecosystem modelers would certainly consider a 10% difference from an observed quantity to be an absolutely excellent match – but here the implications for total community biomass become quite large when the observed quantity used for model validation is a scaling exponent.
What would enhance this manuscript would be a series of sensitivity studies showing focused (generally) on the range of parameter space for this model. I appreciated that the authors included section 2.7 but I found it difficult to follow without some examples in the manuscript. Ideally, it would be great to see what the model results are when interference pre-factor were set to low values and the interference exponent was set to 0, combined with allowing beta of mortality to vary relative to the beta of growth and respiration, but I leave it up to the authors to decide what would be most appropriate.
Lastly – it would be remis for me to write all this without noting that it is extremely difficult to model a system that is as poorly observed and understood as the benthos. All model representations of a new system must start somewhere and BORIS1/BORIS2 is notable as the first of its kind. I apologize for the somewhat rambling paragraphs above – but in my mind, all these model and parameter choices are all highly connected with each other.
Minor comments
Lines 112-113, I think fg should be kg, right?
Line 260, I found it confusing that the biomass scaling (alpha) was defined as a negative, resulting in values that are negative. I look into the benthos observations literature specifically and did not get the sense that this was common practice. If not common practice can you just use the raw values, allowing alpha to be positive?
Section 2.7, lines 385-384, 406-425. I overall like this discussion but found it hard to follow without some more concrete examples.
Citation: https://doi.org/10.5194/egusphere-2025-2180-RC2 - AC3: 'Reply on RC2', Adrian Martin, 31 Mar 2026
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Adrian Peter Martin
Noelie Benoist
Brian Bett
Anieke Brombacher
Jennifer Durden
Sophy Oliver
Andrew Yool
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1048 KB) - Metadata XML
-
Supplement
(150 KB) - BibTeX
- EndNote
- Final revised paper
Dear authors,
After checking your manuscript, we have great doubts about its compliance with the Code and Data policy of our journal.
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
In the Zenodo repository that you cite, a few routines are shared (namely four M language scripts), which do not seem to be the full BORIS-2 model that you present in your manuscript.
Our policy is clear regarding the fact that all the code and data necessary to replicate the work presented in a manuscript must be public and without access restrictions before the submission of a manuscript to our journal. Therefore, please clarify if the current code in the Zenodo repository that you have shared is all the BORIS-2 code. If it is not the case, please, in a prompt manner publish the BORIS-2 code in an acceptable repository from the ones listed in our policy, and reply to this comment with the information for it: links and permanent handler (e.g. DOI).
I note that in lack of compliance with our policy we will have to reject your manuscript for publication.
Juan A. Añel
Geosci. Model Dev. Executive Editor