Rpath - Rpath 1.1.0

• Added ability to import .eiixml files via the create.rpath.from.eiixml() function
• Added balance functionality to estimate P/B from input Biomass and EE, also
  allowing a missing Q/B to be estimated from input PC and the estimated P/B
• Corrected accounting for single-stage interdetrital flows during balance
• Behavior change: if all of P/B, Q/B, and PC are supplied as inputs for a group, recalculate PC during balance to ensure internal model consistency (instead of leaving PC unchanged and possibly inaccurate)
• Improved error messages in rpath() balance routine to help diagnose models that are missing parameters
• Improved warning message content in check.rpath.params() to aid diagnosis
• Modified rpath.stanzas() so it no longer produces errors when called with a model that has no multistanza groups (instead it returns the model unchanged)
• Added Western Bering Sea model .eiixml and EwE output csv files as an import example
• Added Convert_EwE_to_Rpath vignette to describe .eiixml import process
• Tested eiixml input routines on over 150 models available via EcoBase with most producing consistent results between Rpath and EwE; some remaining balancing differences between Rpath and EwE are noted in the Convert_EwE_to_Rpath vignette
• Fixed some table ordering issues with stanza inputs
• Documentation fixes

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet 10 months ago

Rpath - Rpath 1.0.0

• Fix group parameter reference in adjust.scenario
• Fix Force bymort double-counting bug ecosim.cpp
• rsim step dyt fix in ecosim_multistep
• Removed old datasets
• Switch from single to double operators in ecosim.cpp
• Added examples to all functions
• Updated documentation/website
• Added package hex
• Added a bibliography file
• Created issue templates
• Added contributors guideline and code of conduct

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet 12 months ago

Rpath - Rpath 0.5.0

Initial release to coincide with seminal publication.

Sean M. Lucey, Sarah K. Gaichas, Kerim Y. Aydin,
Conducting reproducible ecosystem modeling using the open source mass balance model Rpath, Ecological Modelling, Volume 427, 2020, 109057, ISSN 0304-3800, https://doi.org/10.1016/j.ecolmodel.2020.109057

Abstract

Ecosystem models are important tools for conducting ecosystem-based management. A particularly useful method of characterizing the flow of energy through an ecosystem and the subsequent direct and indirect implications of management actions is mass balance modeling. Here we outline the equations as utilized in Rpath, an R implementation of the mass balance algorithms popularized by Ecopath with Ecosim that are designed to work with fisheries data sources. We believe that common practices in R will aid in the reproducibility of conducting analysis using a mass balance model as all of the code is contained within a single script file. This includes the built-in statistical and graphical functions of R. In addition to added reproducibility, R is a coding language with which ecologists are familiar. This familiarity offers greater flexibility for practitioners to tailor the model to their needs. We have made the code available on an open software development platform which should aid in continuous community development of the tool.

Keywords: Ecopath; Ecosim; Mass balance; Reproducibility; R; Rpath

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.5.1

Minor Changes

• Original implementation of the MTI function did not produce results consistent with the EwE software. This is fixed
• increase parameter in MTI function is redundant and removed.
• Mixotroph diet fix in ecopath function

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.6.0

Sean M. Lucey, Kerim Y. Aydin, Sarah K. Gaichas, Steven X. Cadrin, Gavin Fay, Michael J. Fogarty, André Punt,
Evaluating fishery management strategies using an ecosystem model as an operating model, Fisheries Research, Volume 234, 2021, 105780, ISSN 0165-7836, https://doi.org/10.1016/j.fishres.2020.105780.

Abstract:

Management Strategy Evaluation (MSE) is an effective tool to gauge the relative performance of fishery management options. For the most part, MSEs have been applied to single-species management procedures. However, to be more inclusive of all the biological and technical interactions occurring within a system, ecosystem-based strategies are emerging. In order to test the feasibility of these strategies, a full ecosystem model should be used as an operating model. Mass balance food web models include many features that managers are interested in and therefore can be useful as an operating model. Until recently, full feedback interactions between a management strategy and a mass balance operating model were impractical. However, with the development of Rpath, users now have the ability to fully customize their mass balance models. We developed new functionality for the Rpath modelling framework that allows it to be used as a flexible operating model. Using an example Georges Bank model, we demonstrate how Rpath can now pause the simulation, evaluate an external model, and use the results to modify the parameters of the operating model. This new flexibility will allow users to test a variety of management strategies or couple to other models making Rpath a valuable tool for conducting MSEs.

Minor Changes

• Notation/variable name changes to match publcation, eg. CC-> Catch, BB -> Biomass
• Fixes for CRAN checks

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.7.0

Margaret Heinichen, M. Conor McManus, Sean M. Lucey, Kerim Aydin, Austin Humphries, Anne Innes-Gold, Jeremy Collie,
Incorporating temperature-dependent fish bioenergetics into a Narragansett Bay food web model, Ecological Modelling, Volume 466, 2022, 109911, ISSN 0304-3800, https://doi.org/10.1016/j.ecolmodel.2022.109911.

Abstract

Food web models capture shifting species interactions, making them useful tools for exploring community responses to disturbances. The inclusion of environmental drivers, such as temperature, can improve model predictions, as energy demands of an organism can be temperature specific. While mass-balance models such as Ecopath with Ecosim (EwE) and the R implementation, Rpath, have included some thermal responses in past work, models have yet to include temperature-dependent energetic demands and metabolic costs. Our work demonstrates the inclusion of temperature-dependent bioenergetics into an Rpath food web model using the case study of a warming estuary: Narragansett Bay (Rhode Island, U.S.A). Thermal response parameters from literature were used to construct Kitchell curves describing temperature-dependent consumption and modified Arrhenius curves describing temperature-dependent respiration. Surface water temperature time series from 1994 to 2054 for high and low warming scenarios were created using observed temperatures and projections from the Coupled Model Intercomparison Project (CMIP6) multi-model ensemble. The integration of temperature-dependent fish bioenergetics resulted in lower projected biomasses as energetic demands increased. The degree to which biomass was impacted varied by functional group, though piscivorous fishes were particularly affected as both that group and their prey groups had forced bioenergetic changes. The differences in the model-predicted biomasses highlight the importance of accounting for thermal effects on marine species in ecosystem models, which will become increasingly important as ocean temperatures continue to rise in Narragansett Bay and elsewhere.

Keywords: Food web model; Fish bioenergetics; Rpath; Estuary; Climate change; Thermal responses

Minor changes

• Added CI workflows
• Added/updated documentation (pkgdown)
• stanza changes
• Variable name changes

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.8.0

Minor changes

• Bug fix in adjust.forcing

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.9.1

Minor changes

• Documentation updates

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago

Rpath - Rpath 0.9.0

George A. Whitehouse, Kerim Y. Aydin,
Assessing the sensitivity of three Alaska marine food webs to perturbations: an example of Ecosim simulations using Rpath, Ecological Modelling, Volume 429, 2020, 109074, ISSN 0304-3800, https://doi.org/10.1016/j.ecolmodel.2020.109074.

Abstract

Ecosystem modelling is a useful tool for exploring the potential outcomes of policy options and conducting experiments that would otherwise be impractical in the real world. However, ecosystem models have been limited in their ability to engage in the management of living marine resources due in part to high levels of uncertainty in model parameters and model outputs. Additionally, for multispecies or food web models, there is uncertainty about the predator-prey functional response, which can have implications for population dynamics. In this study, we evaluate the sensitivity of large marine food webs in Alaska to parameter uncertainty, including parameters that govern the predator-prey functional response. We use Rpath, an R implementation of the food web modeling program Ecopath with Ecosim (EwE), to conduct a series of mortality-based perturbations to examine the sensitivity and recovery time of higher trophic level groups in the eastern Chukchi Sea, eastern Bering Sea, and Gulf of Alaska. We use a Monte Carlo approach to generate thousands of plausible ecosystems by drawing parameter sets from the range of uncertainty around the base model parameters. We subjected the ecosystem ensembles to a series of mortality-based perturbations to identify which functional groups the higher trophic level groups are most sensitive to when their mortality was increased, whether the food webs returned to their unperturbed configurations following a perturbation, and how long it took to return to that state. In all three ecosystems, we found that the number of disrupted ensemble food webs was positively related to the biomass and the number of trophic links of the perturbed functional group, and negatively related to trophic level. The eastern Chukchi Sea was most sensitive to perturbations to benthic invertebrate groups, the eastern Bering Sea was most sensitive to shrimp and walleye pollock, and the Gulf of Alaska was most sensitive to shrimps, pelagic forage fish, and zooplankton. Recovery time to perturbations were generally less than 5 years in all three ecosystems. The recovery times when fish groups were perturbed were generally longer than when benthic invertebrates were perturbed, and recovery times were shortest when it was pelagic invertebrates. The single model ensemble approach produced simulation results that described a range of possible outcomes to the prescribed perturbations and provided a sense for how robust the results are to parameter uncertainty.

Keywords: Rpath; Ecosim; food web; Chukchi Sea; Bering Sea; Gulf of Alaska

New features

• Added ecosense functionality
• Added several example models

Minor changes

• Added CI tests
• Updated documntation - vignettes added

Biosphere - Ecological and Environmental Modeling - R
Published by andybeet about 1 year ago