paper: refs, acknowledgements

R/weather.R

@@ -20,6 +20,13 @@
 #' These parameters are stored in this object in the respective `PARAM_vec` 
 #' fields.
 #' 
+#' # Snow model
+#'
+#' The precipitation and temperature inputs are used in order to estimate the 
+#' snow cover for each day by use of a snow model.
+#' The employed model is as formulated by Kokkonen et al. 2006 and makes use 
+#' of parameters from Rango and Martinec, 1995.
+#'
 #' @field weather_file Name of provided weather data file.
 #' @field years numeric Integer representation of the contained years.
 #' @field vec_size Length of the PARAM_vec vectors, which is equal to *number 
@@ -41,6 +48,10 @@
 #'   - snow
 #'   - ndays (number of days in this year)
 #'
+#' @references
+#' \insertRef{rango1995RevisitingDegreeDayMethod}{growR}
+#' \insertRef{kokkonen2006ConstructionDegreedaySnow}{growR}
+#'
 #' @md
 #' @export
 WeatherData = R6Class(
@@ -137,9 +148,9 @@ WeatherData = R6Class(
       T_melt = -1.
       # melt coefficient [mm C-1 d-1] (Rango and Martinec, 1995)
       C_melt = 3.
-      # freeze coefficient [mm C-1 d-1] (Kokkonen et al, ??)
+      # freeze coefficient [mm C-1 d-1] (Kokkonen et al, 2006)
       C_freeze = 0.05
-      # liquid water retention coeff. (Kokkonen et al, ??)
+      # liquid water retention coeff. (Kokkonen et al, 2006)
       C_retention = 0.25   
 
       liquidP_vec = (1./(1. + exp(-1.5*(Ta_vec - 2.)))) * PP_vec

inst/REFERENCES.bib

@@ -142,3 +142,30 @@ @article{kruijt2008EffectsRisingAtmospheric
   langid = {english},
   keywords = {Climate scenario,CO-effect,CO2 growth,evapotranspiration,Evapotranspiration,skimmed,Soil moisture,Stomatal conductance,The Netherlands,Water management}
 }
+
+@inproceedings{kokkonen2006ConstructionDegreedaySnow,
+  title = {Construction of a Degree-Day Snow Model in the Light of the Ten Iterative Steps in Model Development},
+  booktitle = {{{iEMSs}} Third Biennial Meeting: "{{Summit}} on {{Environmental Modelling}} and {{Software}}". {{International}} Environmental Modelling and Software Society, Burlington, {{USA}}, July 2006},
+  author = {Kokkonen, Teemu and Koivusalo, Harri and Jakeman, Anthony and Norton, John},
+  year = {2006},
+  publisher = {{International Environmental Modelling and Software Society (iEMSs)}},
+  address = {{Switzerland}},
+  langid = {english},
+  keywords = {growR,snow,snow processes}
+}
+
+@article{rango1995RevisitingDegreeDayMethod,
+  title = {Revisiting the {{Degree-Day Method}} for {{Snowmelt Computations}}},
+  author = {Rango, A. and Martinec, J.},
+  year = {1995},
+  journal = {JAWRA Journal of the American Water Resources Association},
+  volume = {31},
+  number = {4},
+  pages = {657--669},
+  issn = {1752-1688},
+  doi = {10.1111/j.1752-1688.1995.tb03392.x},
+  urldate = {2023-12-13},
+  langid = {english},
+  keywords = {degree-day method,growR,hydrograph analysis and modeling,snow,snow and ice hydrology,snowmelt}
+}
+

joss_paper/paper.bib

@@ -63,6 +63,18 @@ @inbook{IPCC2022Chapter05
   type = {Book Section}
 }
 
+@book{thornley1998GrasslandDynamicsEcosystem,
+  title = {Grassland {{Dynamics}}: {{An Ecosystem Simulation Model}}},
+  shorttitle = {Grassland {{Dynamics}}},
+  author = {Thornley, J. H. M.},
+  year = {1998},
+  publisher = {{CAB International}},
+  googlebooks = {aULwAAAAMAAJ},
+  isbn = {978-0-85199-227-3},
+  langid = {english},
+  keywords = {Computers / Data Science / Data Modeling \& Design,Science / Environmental Science,Science / Life Sciences / Ecology}
+}
+
 @article{thornley1997TemperateGrasslandResponses,
   title = {Temperate {{Grassland Responses}} to {{Climate Change}}: An {{Analysis}} Using the {{Hurley Pasture Model}}},
   shorttitle = {Temperate {{Grassland Responses}} to {{Climate Change}}},
@@ -245,3 +257,102 @@ @phdthesis{schaumberger2011RaeumlicheModelleZur
   annotation = {ISBN-13: 978-3-902559-67-8}
 }
 
+@inproceedings{kokkonen2006ConstructionDegreedaySnow,
+  title = {Construction of a Degree-Day Snow Model in the Light of the Ten Iterative Steps in Model Development},
+  booktitle = {{{iEMSs}} Third Biennial Meeting: "{{Summit}} on {{Environmental Modelling}} and {{Software}}". {{International}} Environmental Modelling and Software Society, Burlington, {{USA}}, July 2006},
+  author = {Kokkonen, Teemu and Koivusalo, Harri and Jakeman, Anthony and Norton, John},
+  year = {2006},
+  publisher = {{International Environmental Modelling and Software Society (iEMSs)}},
+  address = {{Switzerland}},
+  langid = {english},
+  keywords = {growR,snow,snow processes}
+}
+
+@article{rango1995RevisitingDegreeDayMethod,
+  title = {Revisiting the {{Degree-Day Method}} for {{Snowmelt Computations}}},
+  author = {Rango, A. and Martinec, J.},
+  year = {1995},
+  journal = {JAWRA Journal of the American Water Resources Association},
+  volume = {31},
+  number = {4},
+  pages = {657--669},
+  issn = {1752-1688},
+  doi = {10.1111/j.1752-1688.1995.tb03392.x},
+  urldate = {2023-12-13},
+  langid = {english},
+  keywords = {degree-day method,growR,hydrograph analysis and modeling,snow,snow and ice hydrology,snowmelt}
+}
+
+@article{hoglind2020BASGRAModelGrassland,
+  title = {{{BASGRA}}\_{{N}}: {{A}} Model for Grassland Productivity, Quality and Greenhouse Gas Balance},
+  shorttitle = {{{BASGRA}}\_{{N}}},
+  author = {H{\"o}glind, Mats and Cameron, David and Persson, Tomas and Huang, Xiao and {van Oijen}, Marcel},
+  year = {2020},
+  month = feb,
+  journal = {Ecological Modelling},
+  volume = {417},
+  pages = {108925},
+  issn = {0304-3800},
+  doi = {10.1016/j.ecolmodel.2019.108925},
+  urldate = {2023-04-20},
+  langid = {english},
+}
+
+@misc{vanoijen2015BASGRA_2014,
+  title = {{{BASGRA}}\_2014},
+  author = {Van Oijen, M. and H{\"o}glind, M. and Cameron, D.R. and Thorsen, S.M.},
+  year = {2015},
+  month = aug,
+  doi = {10.5281/zenodo.27867},
+  urldate = {2023-12-13},
+  abstract = {This is the first public release of BASGRA, the BASic GRAssland model, developed jointly by Marcel van Oijen, Mats H{\"o}glind, David Cameron and Stig Morten Thorsen. A full description of the model can be found in the User Guide included in this release.},
+  howpublished = {Zenodo},
+  keywords = {Grassland model}
+}
+
+@article{moore1997GRAZPLANDecisionSupport,
+  title = {{{GRAZPLAN}}: {{Decision}} Support Systems for {{Australian}} Grazing Enterprises. {{III}}. {{Pasture}} Growth and Soil Moisture Submodels, and the {{GrassGro DSS}}},
+  shorttitle = {{{GRAZPLAN}}},
+  author = {Moore, A. D. and Donnelly, J. R. and Freer, M.},
+  year = {1997},
+  month = dec,
+  journal = {Agricultural Systems},
+  volume = {55},
+  number = {4},
+  pages = {535--582},
+  issn = {0308-521X},
+  doi = {10.1016/S0308-521X(97)00023-1},
+  urldate = {2023-12-13},
+}
+
+@article{lazzarotto2009DynamicsGrassClover,
+  title = {Dynamics of Grass{\textendash}Clover Mixtures{\textemdash}{{An}} Analysis of the Response to Management with the {{PROductive GRASsland Simulator}} ({{PROGRASS}})},
+  author = {Lazzarotto, P. and Calanca, P. and Fuhrer, J.},
+  year = {2009},
+  month = mar,
+  journal = {Ecological Modelling},
+  volume = {220},
+  number = {5},
+  pages = {703--724},
+  issn = {0304-3800},
+  doi = {10.1016/j.ecolmodel.2008.11.023},
+  urldate = {2023-05-24},
+  langid = {english},
+  keywords = {Allocation,Feedback mechanisms,Fertilization,Grass/clover interactions,Grassland model,PROGRASS,Root development},
+}
+
+@article{graux2011DevelopmentPastureSimulation,
+  title = {Development of the {{Pasture Simulation Model}} for Assessing Livestock Production under Climate Change},
+  author = {Graux, A. -I. and Gaurut, M. and Agabriel, J. and Baumont, R. and Delagarde, R. and Delaby, L. and Soussana, J. -F.},
+  year = {2011},
+  month = nov,
+  journal = {Agriculture, Ecosystems \& Environment},
+  volume = {144},
+  number = {1},
+  pages = {69--91},
+  issn = {0167-8809},
+  doi = {10.1016/j.agee.2011.07.001},
+  urldate = {2023-12-13},
+  keywords = {Biogeochemical cycles,CH emission,Grassland,Grazing,Ruminants},
+}
+

joss_paper/paper.md

@@ -38,24 +38,28 @@ anthropogenic climate change [@IPCC2022Chapter05].
 
 There is thus ample motivation to study the properties and dynamics of 
 grasslands.
-Experimental approaches, while of fundamental importance, suffer from high 
-costs in time resources required, as a study site typically has to be maintained 
-over several years in order to make a scientific observation.
-For this reason, the method of investigating grassland dynamics by means of 
-mathematical models and simulatory approaches has found widespread 
-application, with dozens of models being formulated, employed and further 
-developed.
-Each of these models has been developed with different applications in mind 
+Mathematical models offer an efficient pathway to investigating grassland 
+dynamics.
+Additionally, such models can be employed in agricultural and political 
+decision support systems, see e.g. [GrazPlan](https://grazplan.csiro.au/) 
+[@moore1997GRAZPLANDecisionSupport].
+Simulatory approaches have therefore found widespread application, with 
+dozens of models being formulated, employed and further developed.
+Each of these models has been created with different applications in mind 
 and thus comes with its own focal points and a set of advantages and 
 disadvantages.
 To give just a few examples:
 
-- The Hurley Pasture Model [@thornley1997TemperateGrasslandResponses] is a 
-  rather complete and detailed mechanistic model for managed pastures.
-- [RothC](https://www.rothamsted.ac.uk/rothamsted-carbon-model-rothc) was 
-  developed for the long-term 
-  Rothamsted Parkgrass Experiment [@jenkinson1994TrendsHerbageYields] and 
-  thus uses comparatively long time scales with a focus on the carbon balance.
+- The [Hurley Pasture Model](https://sites.massey.ac.nz/hurleypasturemodel/hurley-pasture-model/)[@thornley1998GrasslandDynamicsEcosystem]
+  is a rather complete and detailed mechanistic model for managed pastures.
+- [BASGRA](https://github.com/davcam/BASGRA/) [@hoglind2020BASGRAModelGrassland] 
+  and its descendant [BASGRA_N](https://github.com/MarcelVanOijen/BASGRA_N) 
+  [@vanoijen2015BASGRA_2014] are multi-year grassland models which 
+  prominently include tiller dynamics.
+- PROGRASS [@lazzarotto2009DynamicsGrassClover] was developed to capture the 
+  interactions in grass/clover mixtures.
+- The focus of PaSim [@graux2011DevelopmentPastureSimulation] is the 
+  investigation of livestock production under climate change conditions.
 - ModVege @[jouven2006ModelPredictingDynamics] is another mechanistic model 
   that is designed to capture the dominant processes with a minimum of 
   required input parameters.
@@ -115,6 +119,10 @@ work with the model in its original formulation or with any combination of
 the provided extensions.
 These additions include:
 
+- Simulation of snow cover by use of a model by 
+  @kokkonen2006ConstructionDegreedaySnow and 
+  @rango1995RevisitingDegreeDayMethod, important when modelling grassland in 
+  mountainous regions.
 - A cut decision algorithm, which allows the model to simulate management 
   decisions in the absence of such input data. The decision process is based 
   on work by @petersen2021DynamicSimulationManagement and 
@@ -140,5 +148,12 @@ The distribution as an `R` package on [CRAN](https://cran.r-project.org/)
 ensures an easy installation procedure and a relatively high standard of code 
 quality and documentation through CRAN's submission policies.
 
+# Acknowledgements
+
+The work of K.~K. has been supported by 
+[Agroscope](https://www.agroscope.admin.ch/), the [National Center for 
+Climate Sevices (NCCS)[https://www.nccs.admin.ch/nccs/de/home.html] and the 
+[Federal Office for Agriculture](https://www.blw.admin.ch/blw/en/home.html).
+
 # References