diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 6aac2e702..c8af139f8 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -56,7 +56,7 @@ jobs:
              matrix.python-version == '3.10'
             )
           }}
-      uses: codecov/codecov-action@v4
+      uses: codecov/codecov-action@v5
       with:
         fail_ci_if_error: true
         token: ${{ secrets.CODECOV_TOKEN }}
diff --git a/docs/source/_toc.yaml b/docs/source/_toc.yaml
index 24f7205cc..000cc5b87 100644
--- a/docs/source/_toc.yaml
+++ b/docs/source/_toc.yaml
@@ -194,8 +194,8 @@ subtrees:
           - file: api/models/soil
             title: The soil model
             entries:
-              - file: api/models/soil/carbon
-                title: The carbon submodule
+              - file: api/models/soil/pools
+                title: The pools submodule
               - file: api/models/soil/constants
                 title: The constants submodule
               - file: api/models/soil/env_factors
diff --git a/docs/source/api/models/soil/carbon.md b/docs/source/api/models/soil/pools.md
similarity index 89%
rename from docs/source/api/models/soil/carbon.md
rename to docs/source/api/models/soil/pools.md
index b7029387b..c6a10469e 100644
--- a/docs/source/api/models/soil/carbon.md
+++ b/docs/source/api/models/soil/pools.md
@@ -24,10 +24,10 @@ language_info:
   version: 3.11.9
 ---
 
-# API documentation for the {mod}`~virtual_ecosystem.models.soil.carbon` module
+# API documentation for the {mod}`~virtual_ecosystem.models.soil.pools` module
 
 ```{eval-rst}
-.. automodule:: virtual_ecosystem.models.soil.carbon
+.. automodule:: virtual_ecosystem.models.soil.pools
     :autosummary:
     :members:
 ```
diff --git a/poetry.lock b/poetry.lock
index 8c4507e46..ba2b64089 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -33,17 +33,6 @@ doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)",
 test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
 trio = ["trio (>=0.26.1)"]
 
-[[package]]
-name = "appdirs"
-version = "1.4.4"
-description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-optional = false
-python-versions = "*"
-files = [
-    {file = "appdirs-1.4.4-py2.py3-none-any.whl", hash = "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128"},
-    {file = "appdirs-1.4.4.tar.gz", hash = "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41"},
-]
-
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -740,13 +729,13 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "dask"
-version = "2024.10.0"
+version = "2024.11.2"
 description = "Parallel PyData with Task Scheduling"
 optional = false
 python-versions = ">=3.10"
 files = [
-    {file = "dask-2024.10.0-py3-none-any.whl", hash = "sha256:1ddc27c7967e134b4f8296a488521485a5ac4927cc63e2abfa0b24227b93217f"},
-    {file = "dask-2024.10.0.tar.gz", hash = "sha256:dfd3efec5d8d8340fb647d0347637133030cad261b714623cc27de286e9db037"},
+    {file = "dask-2024.11.2-py3-none-any.whl", hash = "sha256:6115c4b76015e8d9d9c2922b6a0a1c850e283fb7fee74eebbd2e28e9c117c30d"},
+    {file = "dask-2024.11.2.tar.gz", hash = "sha256:9a72bee3f149ff89bc492340d4bcba33d5dd3e3a9d471d2b4b3872f2d71ddaae"},
 ]
 
 [package.dependencies]
@@ -764,7 +753,7 @@ array = ["numpy (>=1.24)"]
 complete = ["dask[array,dataframe,diagnostics,distributed]", "lz4 (>=4.3.2)", "pyarrow (>=14.0.1)"]
 dataframe = ["dask-expr (>=1.1,<1.2)", "dask[array]", "pandas (>=2.0)"]
 diagnostics = ["bokeh (>=3.1.0)", "jinja2 (>=2.10.3)"]
-distributed = ["distributed (==2024.10.0)"]
+distributed = ["distributed (==2024.11.2)"]
 test = ["pandas[test]", "pre-commit", "pytest", "pytest-cov", "pytest-rerunfailures", "pytest-timeout", "pytest-xdist"]
 
 [[package]]
@@ -934,13 +923,13 @@ test = ["pytest", "pytest-cov", "pytest-mpl", "pytest-subtests"]
 
 [[package]]
 name = "flexparser"
-version = "0.3.1"
+version = "0.4"
 description = "Parsing made fun ... using typing."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "flexparser-0.3.1-py3-none-any.whl", hash = "sha256:2e3e2936bec1f9277f777ef77297522087d96adb09624d4fe4240fd56885c013"},
-    {file = "flexparser-0.3.1.tar.gz", hash = "sha256:36f795d82e50f5c9ae2fde1c33f21f88922fdd67b7629550a3cc4d0b40a66856"},
+    {file = "flexparser-0.4-py3-none-any.whl", hash = "sha256:3738b456192dcb3e15620f324c447721023c0293f6af9955b481e91d00179846"},
+    {file = "flexparser-0.4.tar.gz", hash = "sha256:266d98905595be2ccc5da964fe0a2c3526fbbffdc45b65b3146d75db992ef6b2"},
 ]
 
 [package.dependencies]
@@ -1215,13 +1204,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "hypothesis"
-version = "6.115.5"
+version = "6.122.0"
 description = "A library for property-based testing"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "hypothesis-6.115.5-py3-none-any.whl", hash = "sha256:b7733459ae9a93020fac3b91b41473c9b85e975139a152a70d88f3a5caa3fa3f"},
-    {file = "hypothesis-6.115.5.tar.gz", hash = "sha256:4768c5fb426b305462ed31032d6e216a31daaefb1dc3134fdf2795b7961d7cb3"},
+    {file = "hypothesis-6.122.0-py3-none-any.whl", hash = "sha256:523451a187cb0e861074bc560c2d27382b7872c28b57c6e14e98bb2152fe3a0e"},
+    {file = "hypothesis-6.122.0.tar.gz", hash = "sha256:8f1675a62f70e2821b347f550e6d3b5478ec25470b6e0281c974b57ab53f5dc7"},
 ]
 
 [package.dependencies]
@@ -1230,10 +1219,10 @@ exceptiongroup = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 sortedcontainers = ">=2.1.0,<3.0.0"
 
 [package.extras]
-all = ["black (>=19.10b0)", "click (>=7.0)", "crosshair-tool (>=0.0.74)", "django (>=4.2)", "dpcontracts (>=0.4)", "hypothesis-crosshair (>=0.0.16)", "lark (>=0.10.1)", "libcst (>=0.3.16)", "numpy (>=1.19.3)", "pandas (>=1.1)", "pytest (>=4.6)", "python-dateutil (>=1.4)", "pytz (>=2014.1)", "redis (>=3.0.0)", "rich (>=9.0.0)", "tzdata (>=2024.2)"]
+all = ["black (>=19.10b0)", "click (>=7.0)", "crosshair-tool (>=0.0.78)", "django (>=4.2)", "dpcontracts (>=0.4)", "hypothesis-crosshair (>=0.0.18)", "lark (>=0.10.1)", "libcst (>=0.3.16)", "numpy (>=1.19.3)", "pandas (>=1.1)", "pytest (>=4.6)", "python-dateutil (>=1.4)", "pytz (>=2014.1)", "redis (>=3.0.0)", "rich (>=9.0.0)", "tzdata (>=2024.2)"]
 cli = ["black (>=19.10b0)", "click (>=7.0)", "rich (>=9.0.0)"]
 codemods = ["libcst (>=0.3.16)"]
-crosshair = ["crosshair-tool (>=0.0.74)", "hypothesis-crosshair (>=0.0.16)"]
+crosshair = ["crosshair-tool (>=0.0.78)", "hypothesis-crosshair (>=0.0.18)"]
 dateutil = ["python-dateutil (>=1.4)"]
 django = ["django (>=4.2)"]
 dpcontracts = ["dpcontracts (>=0.4)"]
@@ -1354,13 +1343,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipython"
-version = "8.29.0"
+version = "8.30.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
-    {file = "ipython-8.29.0-py3-none-any.whl", hash = "sha256:0188a1bd83267192123ccea7f4a8ed0a78910535dbaa3f37671dca76ebd429c8"},
-    {file = "ipython-8.29.0.tar.gz", hash = "sha256:40b60e15b22591450eef73e40a027cf77bd652e757523eebc5bd7c7c498290eb"},
+    {file = "ipython-8.30.0-py3-none-any.whl", hash = "sha256:85ec56a7e20f6c38fce7727dcca699ae4ffc85985aa7b23635a8008f918ae321"},
+    {file = "ipython-8.30.0.tar.gz", hash = "sha256:cb0a405a306d2995a5cbb9901894d240784a9f341394c6ba3f4fe8c6eb89ff6e"},
 ]
 
 [package.dependencies]
@@ -1370,16 +1359,16 @@ exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 jedi = ">=0.16"
 matplotlib-inline = "*"
 pexpect = {version = ">4.3", markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""}
-prompt-toolkit = ">=3.0.41,<3.1.0"
+prompt_toolkit = ">=3.0.41,<3.1.0"
 pygments = ">=2.4.0"
-stack-data = "*"
+stack_data = "*"
 traitlets = ">=5.13.0"
-typing-extensions = {version = ">=4.6", markers = "python_version < \"3.12\""}
+typing_extensions = {version = ">=4.6", markers = "python_version < \"3.12\""}
 
 [package.extras]
 all = ["ipython[black,doc,kernel,matplotlib,nbconvert,nbformat,notebook,parallel,qtconsole]", "ipython[test,test-extra]"]
 black = ["black"]
-doc = ["docrepr", "exceptiongroup", "intersphinx-registry", "ipykernel", "ipython[test]", "matplotlib", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "sphinxcontrib-jquery", "tomli", "typing-extensions"]
+doc = ["docrepr", "exceptiongroup", "intersphinx_registry", "ipykernel", "ipython[test]", "matplotlib", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "sphinxcontrib-jquery", "tomli", "typing_extensions"]
 kernel = ["ipykernel"]
 matplotlib = ["matplotlib"]
 nbconvert = ["nbconvert"]
@@ -1684,13 +1673,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.2.5"
+version = "4.3.1"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.2.5-py3-none-any.whl", hash = "sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321"},
-    {file = "jupyterlab-4.2.5.tar.gz", hash = "sha256:ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75"},
+    {file = "jupyterlab-4.3.1-py3-none-any.whl", hash = "sha256:2d9a1c305bc748e277819a17a5d5e22452e533e835f4237b2f30f3b0e491e01f"},
+    {file = "jupyterlab-4.3.1.tar.gz", hash = "sha256:a4a338327556443521731d82f2a6ccf926df478914ca029616621704d47c3c65"},
 ]
 
 [package.dependencies]
@@ -1710,9 +1699,9 @@ tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"]
-docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
-docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.6.9)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.1.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==5.4.1)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.2.post3)", "matplotlib (==3.9.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.14.1)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
 upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
 
@@ -2039,51 +2028,47 @@ files = [
 
 [[package]]
 name = "matplotlib"
-version = "3.9.2"
+version = "3.9.3"
 description = "Python plotting package"
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "matplotlib-3.9.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab68d50c06938ef28681073327795c5db99bb4666214d2d5f880ed11aeaded66"},
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 [[package]]
 name = "matplotlib-inline"
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+    {file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"},
+    {file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"},
+    {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"},
+    {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"},
+    {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"},
+    {file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"},
+    {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"},
+    {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"},
+    {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"},
 ]
 
 [[package]]
@@ -4309,20 +4326,21 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.5"
+version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
-    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"]
+discord = ["requests"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
@@ -4378,17 +4396,34 @@ files = [
     {file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"},
 ]
 
+[[package]]
+name = "types-requests"
+version = "2.32.0.20241016"
+description = "Typing stubs for requests"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-requests-2.32.0.20241016.tar.gz", hash = "sha256:0d9cad2f27515d0e3e3da7134a1b6f28fb97129d86b867f24d9c726452634d95"},
+    {file = "types_requests-2.32.0.20241016-py3-none-any.whl", hash = "sha256:4195d62d6d3e043a4eaaf08ff8a62184584d2e8684e9d2aa178c7915a7da3747"},
+]
+
+[package.dependencies]
+urllib3 = ">=2"
+
 [[package]]
 name = "types-tqdm"
-version = "4.66.0.20240417"
+version = "4.67.0.20241119"
 description = "Typing stubs for tqdm"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-tqdm-4.66.0.20240417.tar.gz", hash = "sha256:16dce9ef522ea8d40e4f5b8d84dd8a1166eefc13ceee7a7e158bf0f1a1421a31"},
-    {file = "types_tqdm-4.66.0.20240417-py3-none-any.whl", hash = "sha256:248aef1f9986b7b8c2c12b3cb4399fc17dba0a29e7e3f3f9cd704babb879383d"},
+    {file = "types-tqdm-4.67.0.20241119.tar.gz", hash = "sha256:1769e0e94d5e6d8fa814965f9cf3d9928376dd15dabcbcb784bb8769081092b4"},
+    {file = "types_tqdm-4.67.0.20241119-py3-none-any.whl", hash = "sha256:a18d4eb62db0d35c52707ae13d821b5a57970755273ecb56e133ccc0ac7e7c79"},
 ]
 
+[package.dependencies]
+types-requests = "*"
+
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -4517,24 +4552,24 @@ test = ["websockets"]
 
 [[package]]
 name = "xarray"
-version = "2024.10.0"
+version = "2024.11.0"
 description = "N-D labeled arrays and datasets in Python"
 optional = false
 python-versions = ">=3.10"
 files = [
-    {file = "xarray-2024.10.0-py3-none-any.whl", hash = "sha256:ae1d38cb44a0324dfb61e492394158ae22389bf7de9f3c174309c17376df63a0"},
-    {file = "xarray-2024.10.0.tar.gz", hash = "sha256:e369e2bac430e418c2448e5b96f07da4635f98c1319aa23cfeb3fbcb9a01d2e0"},
+    {file = "xarray-2024.11.0-py3-none-any.whl", hash = "sha256:6ee94f63ddcbdd0cf3909d1177f78cdac756640279c0e32ae36819a89cdaba37"},
+    {file = "xarray-2024.11.0.tar.gz", hash = "sha256:1ccace44573ddb862e210ad3ec204210654d2c750bec11bbe7d842dfc298591f"},
 ]
 
 [package.dependencies]
 numpy = ">=1.24"
-packaging = ">=23.1"
+packaging = ">=23.2"
 pandas = ">=2.1"
 
 [package.extras]
-accel = ["bottleneck", "flox", "numba (>=0.54)", "numbagg", "opt-einsum", "scipy"]
+accel = ["bottleneck", "flox", "numba (>=0.54)", "numbagg", "opt_einsum", "scipy"]
 complete = ["xarray[accel,etc,io,parallel,viz]"]
-dev = ["hypothesis", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "sphinx", "sphinx-autosummary-accessors", "xarray[complete]"]
+dev = ["hypothesis", "jinja2", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "sphinx", "sphinx_autosummary_accessors", "xarray[complete]"]
 etc = ["sparse"]
 io = ["cftime", "fsspec", "h5netcdf", "netCDF4", "pooch", "pydap", "scipy", "zarr"]
 parallel = ["dask[complete]"]
@@ -4562,4 +4597,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "1d8a04b2c4c21608fc5359b45d56ee1f070d44405a9147457e6dfc424bcda8bb"
+content-hash = "24c8405fe6ac3f9ab5de5dd7abcc2c9b9d7cd0f6ab6715709b5da5f1f61b45e4"
diff --git a/pyproject.toml b/pyproject.toml
index c1b3351a1..d3b5e6c61 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -52,7 +52,7 @@ types-tqdm = "^4.66.0.20240106"
 [tool.poetry.group.test.dependencies]
 hypothesis = "^6.54.2"
 pytest = ">=7.1.2,<9.0.0"
-pytest-cov = ">=3,<6"
+pytest-cov = ">=3,<7"
 pytest-datadir = "^1.4.1"
 pytest-mock = "^3.8.1"
 
diff --git a/tests/conftest.py b/tests/conftest.py
index 9e4ee2738..581cc89de 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -260,10 +260,13 @@ def dummy_carbon_data(fixture_core_components):
         "soil_c_pool_necromass": [0.058, 0.015, 0.093, 0.105],
         "soil_enzyme_pom": [0.022679, 0.009576, 0.050051, 0.003010],
         "soil_enzyme_maom": [0.0356, 0.0117, 0.02509, 0.00456],
+        "soil_n_pool_don": [0.000571428, 0.00142857, 0.00014285, 0.002857142],
+        "soil_n_pool_particulate": [0.00714285, 0.00071425, 0.00285714, 0.01428571],
         "pH": [3.0, 7.5, 9.0, 5.7],
         "bulk_density": [1350.0, 1800.0, 1000.0, 1500.0],
         "clay_fraction": [0.8, 0.3, 0.1, 0.9],
         "litter_C_mineralisation_rate": [0.00212106, 0.00106053, 0.00049000, 0.0055],
+        "litter_N_mineralisation_rate": [3.5351e-5, 7.0702e-5, 0.000183, 1.63333e-5],
         "vertical_flow": [0.1, 0.5, 2.5, 1.59],
     }
 
diff --git a/tests/core/test_data.py b/tests/core/test_data.py
index 511a4b7b5..5f4891662 100644
--- a/tests/core/test_data.py
+++ b/tests/core/test_data.py
@@ -974,6 +974,8 @@ def test_output_current_state(mocker, dummy_carbon_data, time_index):
             "soil_c_pool_necromass",
             "soil_enzyme_pom",
             "soil_enzyme_maom",
+            "soil_n_pool_don",
+            "soil_n_pool_particulate",
         ],
         time_index,
     )
diff --git a/tests/models/soil/conftest.py b/tests/models/soil/conftest.py
index 1c70e99c4..5755aa886 100644
--- a/tests/models/soil/conftest.py
+++ b/tests/models/soil/conftest.py
@@ -75,3 +75,24 @@ def environmental_factors(dummy_carbon_data, fixture_core_components):
     return EnvironmentalEffectFactors(
         water=water_factors, pH=pH_factors, clay_saturation=clay_saturation_factors
     )
+
+
+@pytest.fixture
+def enzyme_mediated_rates(
+    dummy_carbon_data, fixture_core_components, environmental_factors
+):
+    """Enzyme mediated rates based on dummy carbon data."""
+    from virtual_ecosystem.models.soil.constants import SoilConsts
+    from virtual_ecosystem.models.soil.pools import calculate_enzyme_mediated_rates
+
+    return calculate_enzyme_mediated_rates(
+        soil_enzyme_pom=dummy_carbon_data["soil_enzyme_pom"],
+        soil_enzyme_maom=dummy_carbon_data["soil_enzyme_maom"],
+        soil_c_pool_pom=dummy_carbon_data["soil_c_pool_pom"],
+        soil_c_pool_maom=dummy_carbon_data["soil_c_pool_maom"],
+        soil_temp=dummy_carbon_data["soil_temperature"][
+            fixture_core_components.layer_structure.index_topsoil_scalar
+        ],
+        env_factors=environmental_factors,
+        constants=SoilConsts,
+    )
diff --git a/tests/models/soil/test_carbon.py b/tests/models/soil/test_pools.py
similarity index 73%
rename from tests/models/soil/test_carbon.py
rename to tests/models/soil/test_pools.py
index 76f5a81c2..17311d3fb 100644
--- a/tests/models/soil/test_carbon.py
+++ b/tests/models/soil/test_pools.py
@@ -1,4 +1,4 @@
-"""Test module for soil.carbon.py.
+"""Test module for soil.pools.py.
 
 This module tests the functionality of the soil carbon module
 """
@@ -9,19 +9,42 @@
 from virtual_ecosystem.models.soil.constants import SoilConsts
 
 
-def test_calculate_soil_carbon_updates(dummy_carbon_data, fixture_core_components):
+def test_calculate_all_pool_updates(dummy_carbon_data, fixture_core_components):
     """Test that the two pool update functions work correctly."""
-    from virtual_ecosystem.core.constants import CoreConsts
-    from virtual_ecosystem.models.soil.carbon import calculate_soil_carbon_updates
+    from virtual_ecosystem.models.soil.pools import SoilPools
+    from virtual_ecosystem.models.soil.soil_model import SoilModel, make_slices
+
+    # Find and store order of pools (this requires loads of steps because it needs to
+    # work with the integrator)
+    y0 = np.concatenate(
+        [
+            dummy_carbon_data[name].to_numpy()
+            for name in map(str, dummy_carbon_data.data.keys())
+            if name in SoilModel.vars_updated
+        ]
+    )
+    delta_pools_ordered = {
+        name: np.array([])
+        for name in map(str, dummy_carbon_data.data.keys())
+        if name in SoilModel.vars_updated
+    }
+    no_cells = 4
+    slices = make_slices(no_cells, len(delta_pools_ordered))
+    pools = {
+        str(pool): y0[slc] for slc, pool in zip(slices, delta_pools_ordered.keys())
+    }
+    soil_pools = SoilPools(data=dummy_carbon_data, pools=pools, constants=SoilConsts)
 
     change_in_pools = {
-        "soil_c_pool_lmwc": [0.0022585928, 0.0060483065, -0.019175058, 0.024247214],
+        "soil_c_pool_lmwc": [0.00226177439, 0.006049897295, -0.019174323, 0.024255464],
         "soil_c_pool_maom": [0.038767651, 0.00829848, 0.05982197, 0.07277182],
         "soil_c_pool_microbe": [-0.04978105, -0.02020101, -0.10280967, -0.00719517],
-        "soil_c_pool_pom": [0.00178122, -0.00785937, -0.01201551, 0.00545857],
+        "soil_c_pool_pom": [0.00177803841, -0.007860960795, -0.012016245, 0.00545032],
         "soil_c_pool_necromass": [0.001137474, 0.009172067, 0.033573266, -0.08978050],
         "soil_enzyme_pom": [1.18e-8, 1.67e-8, 1.8e-9, -1.12e-8],
         "soil_enzyme_maom": [-0.00031009, -5.09593e-5, 0.0005990658, -3.72112e-5],
+        "soil_n_pool_don": [2.4081961e-5, 2.84920682e-6, 4.84845086e-5, -5.83499913e-5],
+        "soil_n_pool_particulate": [1.102338e-5, 6.422491e-5, 0.000131687, 1.461799e-5],
     }
 
     # Make order of pools object
@@ -29,31 +52,9 @@ def test_calculate_soil_carbon_updates(dummy_carbon_data, fixture_core_component
     for pool in change_in_pools.keys():
         pool_order[pool] = np.array([])
 
-    delta_pools = calculate_soil_carbon_updates(
-        soil_c_pool_lmwc=dummy_carbon_data["soil_c_pool_lmwc"].to_numpy(),
-        soil_c_pool_maom=dummy_carbon_data["soil_c_pool_maom"].to_numpy(),
-        soil_c_pool_microbe=dummy_carbon_data["soil_c_pool_microbe"].to_numpy(),
-        soil_c_pool_pom=dummy_carbon_data["soil_c_pool_pom"].to_numpy(),
-        soil_c_pool_necromass=dummy_carbon_data["soil_c_pool_necromass"].to_numpy(),
-        soil_enzyme_pom=dummy_carbon_data["soil_enzyme_pom"].to_numpy(),
-        soil_enzyme_maom=dummy_carbon_data["soil_enzyme_maom"].to_numpy(),
-        pH=dummy_carbon_data["pH"],
-        bulk_density=dummy_carbon_data["bulk_density"],
-        soil_moisture=dummy_carbon_data["soil_moisture"][
-            fixture_core_components.layer_structure.index_topsoil_scalar
-        ].to_numpy(),
-        soil_water_potential=dummy_carbon_data["matric_potential"][
-            fixture_core_components.layer_structure.index_topsoil_scalar
-        ].to_numpy(),
-        vertical_flow_rate=dummy_carbon_data["vertical_flow"],
-        soil_temp=dummy_carbon_data["soil_temperature"][
-            fixture_core_components.layer_structure.index_topsoil_scalar
-        ],
-        clay_fraction=dummy_carbon_data["clay_fraction"],
-        mineralisation_rate=dummy_carbon_data["litter_C_mineralisation_rate"],
+    delta_pools = soil_pools.calculate_all_pool_updates(
         delta_pools_ordered=pool_order,
-        model_constants=SoilConsts,
-        core_constants=CoreConsts,
+        top_soil_layer_index=fixture_core_components.layer_structure.index_topsoil_scalar,
     )
 
     # Check that the updates are correctly calculated. Using a loop here implicitly
@@ -67,7 +68,7 @@ def test_calculate_microbial_changes(
 ):
     """Check that calculation of microbe related changes works correctly."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_microbial_changes
+    from virtual_ecosystem.models.soil.pools import calculate_microbial_changes
 
     expected_lmwc_uptake = [1.29159055e-2, 8.43352433e-3, 5.77096991e-2, 5.77363558e-5]
     expected_microbe = [-0.04978105, -0.02020101, -0.10280967, -0.00719517]
@@ -100,7 +101,7 @@ def test_calculate_enzyme_mediated_rates(
 ):
     """Check that calculation of enzyme mediated rates works as expected."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_enzyme_mediated_rates
+    from virtual_ecosystem.models.soil.pools import calculate_enzyme_mediated_rates
 
     expected_pom_to_lmwc = [3.39844565e-4, 8.91990315e-3, 1.25055119e-2, 4.14247999e-5]
     expected_maom_to_lmwc = [1.45988485e-3, 2.10172756e-3, 4.69571604e-3, 8.62951373e-6]
@@ -124,7 +125,7 @@ def test_calculate_enzyme_mediated_rates(
 def test_calculate_enzyme_changes(dummy_carbon_data):
     """Check that the determination of enzyme pool changes works correctly."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_enzyme_changes
+    from virtual_ecosystem.models.soil.pools import calculate_enzyme_changes
 
     biomass_loss = np.array([0.05443078, 0.02298407, 0.12012258, 0.00722288])
 
@@ -148,7 +149,7 @@ def test_calculate_maintenance_biomass_synthesis(
     dummy_carbon_data, fixture_core_components
 ):
     """Check maintenance respiration cost calculates correctly."""
-    from virtual_ecosystem.models.soil.carbon import (
+    from virtual_ecosystem.models.soil.pools import (
         calculate_maintenance_biomass_synthesis,
     )
 
@@ -167,7 +168,7 @@ def test_calculate_maintenance_biomass_synthesis(
 
 def test_calculate_carbon_use_efficiency(dummy_carbon_data, fixture_core_components):
     """Check carbon use efficiency calculates correctly."""
-    from virtual_ecosystem.models.soil.carbon import calculate_carbon_use_efficiency
+    from virtual_ecosystem.models.soil.pools import calculate_carbon_use_efficiency
 
     expected_cues = [0.36, 0.33, 0.3, 0.48]
 
@@ -202,7 +203,7 @@ def test_calculate_carbon_use_efficiency(dummy_carbon_data, fixture_core_compone
 )
 def test_calculate_enzyme_turnover(dummy_carbon_data, turnover, expected_decay):
     """Check that enzyme turnover rates are calculated correctly."""
-    from virtual_ecosystem.models.soil.carbon import calculate_enzyme_turnover
+    from virtual_ecosystem.models.soil.pools import calculate_enzyme_turnover
 
     actual_decay = calculate_enzyme_turnover(
         enzyme_pool=dummy_carbon_data["soil_enzyme_pom"], turnover_rate=turnover
@@ -215,7 +216,9 @@ def test_calculate_microbial_carbon_uptake(
     dummy_carbon_data, fixture_core_components, environmental_factors
 ):
     """Check microbial carbon uptake calculates correctly."""
-    from virtual_ecosystem.models.soil.carbon import calculate_microbial_carbon_uptake
+    from virtual_ecosystem.models.soil.pools import (
+        calculate_microbial_carbon_uptake,
+    )
 
     expected_uptake = [1.29159055e-2, 8.43352433e-3, 5.77096991e-2, 5.77363558e-5]
     expected_assimilation = [4.64972597e-3, 2.78306303e-3, 1.73129097e-2, 2.77134508e-5]
@@ -239,7 +242,7 @@ def test_calculate_enzyme_mediated_decomposition(
     dummy_carbon_data, fixture_core_components, environmental_factors
 ):
     """Check that particulate organic matter decomposition is calculated correctly."""
-    from virtual_ecosystem.models.soil.carbon import (
+    from virtual_ecosystem.models.soil.pools import (
         calculate_enzyme_mediated_decomposition,
     )
 
@@ -265,7 +268,7 @@ def test_calculate_enzyme_mediated_decomposition(
 def test_calculate_maom_desorption(dummy_carbon_data):
     """Check that mineral associated matter desorption is calculated correctly."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_maom_desorption
+    from virtual_ecosystem.models.soil.pools import calculate_maom_desorption
 
     expected_desorption = [2.5e-5, 1.7e-5, 4.5e-5, 5.0e-6]
 
@@ -297,7 +300,7 @@ def test_calculate_sorption_to_maom(
 ):
     """Check that sorption to mineral associated matter is calculated correctly."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_sorption_to_maom
+    from virtual_ecosystem.models.soil.pools import calculate_sorption_to_maom
 
     actual_sorption = calculate_sorption_to_maom(
         soil_c_pool=dummy_carbon_data[pool_name],
@@ -310,7 +313,7 @@ def test_calculate_sorption_to_maom(
 def test_calculate_necromass_breakdown(dummy_carbon_data):
     """Check that necromass breakdown to lmwc is calculated correctly."""
 
-    from virtual_ecosystem.models.soil.carbon import calculate_necromass_breakdown
+    from virtual_ecosystem.models.soil.pools import calculate_necromass_breakdown
 
     expected_breakdown = [0.0134008455, 0.0034657359, 0.0214875626, 0.0242601513]
 
@@ -320,3 +323,44 @@ def test_calculate_necromass_breakdown(dummy_carbon_data):
     )
 
     assert np.allclose(actual_breakdown, expected_breakdown)
+
+
+def test_calculate_litter_mineralisation_split(dummy_carbon_data):
+    """Test that the calculation of the mineralisation split works as expected."""
+    from virtual_ecosystem.models.soil.pools import (
+        calculate_litter_mineralisation_split,
+    )
+
+    expected_split = {
+        "dissolved": [3.18159e-6, 1.590795e-6, 7.35e-7, 8.25e-6],
+        "particulate": [0.00211787841, 0.001058939205, 0.000489265, 0.00549175],
+    }
+
+    actual_split = calculate_litter_mineralisation_split(
+        mineralisation_rate=dummy_carbon_data["litter_C_mineralisation_rate"],
+        litter_leaching_coefficient=SoilConsts.litter_leaching_fraction_carbon,
+    )
+
+    assert set(expected_split.keys()) == set(actual_split.keys())
+
+    for key in actual_split.keys():
+        assert np.allclose(actual_split[key], expected_split[key])
+
+
+def test_calculate_soil_nutrient_mineralisation(
+    dummy_carbon_data, enzyme_mediated_rates
+):
+    """Test that function to calculate soil nutrient mineralisation works properly."""
+    from virtual_ecosystem.models.soil.pools import (
+        calculate_soil_nutrient_mineralisation,
+    )
+
+    expected_rate = [2.42745875e-5, 6.371041e-6, 5.104285e-5, 1.690808e-6]
+
+    actual_rate = calculate_soil_nutrient_mineralisation(
+        pool_carbon=dummy_carbon_data["soil_c_pool_pom"],
+        pool_nutrient=dummy_carbon_data["soil_n_pool_particulate"],
+        breakdown_rate=enzyme_mediated_rates.pom_to_lmwc,
+    )
+
+    assert np.allclose(actual_rate, expected_rate)
diff --git a/tests/models/soil/test_soil_model.py b/tests/models/soil/test_soil_model.py
index 77b56d950..551c4d3a0 100644
--- a/tests/models/soil/test_soil_model.py
+++ b/tests/models/soil/test_soil_model.py
@@ -18,9 +18,11 @@
     (DEBUG, "soil model: required var 'soil_c_pool_lmwc' checked"),
     (DEBUG, "soil model: required var 'soil_c_pool_microbe' checked"),
     (DEBUG, "soil model: required var 'soil_c_pool_pom' checked"),
+    (DEBUG, "soil model: required var 'soil_c_pool_necromass' checked"),
     (DEBUG, "soil model: required var 'soil_enzyme_pom' checked"),
     (DEBUG, "soil model: required var 'soil_enzyme_maom' checked"),
-    (DEBUG, "soil model: required var 'soil_c_pool_necromass' checked"),
+    (DEBUG, "soil model: required var 'soil_n_pool_don' checked"),
+    (DEBUG, "soil model: required var 'soil_n_pool_particulate' checked"),
     (DEBUG, "soil model: required var 'pH' checked"),
     (DEBUG, "soil model: required var 'bulk_density' checked"),
     (DEBUG, "soil model: required var 'clay_fraction' checked"),
@@ -257,28 +259,34 @@ def test_update(mocker, fixture_soil_model, dummy_carbon_data):
             does_not_raise(),
             Dataset(
                 data_vars=dict(
-                    lmwc=DataArray(
-                        [0.05110324, 0.0229453, 0.09239938, 0.01485271], dims="cell_id"
+                    soil_c_pool_lmwc=DataArray(
+                        [0.05110474, 0.02294602, 0.0923997, 0.01485682], dims="cell_id"
                     ),
-                    maom=DataArray(
+                    soil_c_pool_maom=DataArray(
                         [2.5194618, 1.70483236, 4.53238116, 0.52968038], dims="cell_id"
                     ),
-                    microbe=DataArray(
+                    soil_c_pool_microbe=DataArray(
                         [5.7752035, 2.29002929, 11.24843316, 0.99642482],
                         dims="cell_id",
                     ),
-                    pom=DataArray(
-                        [0.10088985, 0.99607906, 0.69401895, 0.35272921], dims="cell_id"
+                    soil_c_pool_pom=DataArray(
+                        [0.10088826, 0.99607827, 0.69401858, 0.35272508], dims="cell_id"
                     ),
-                    necromass=DataArray(
+                    soil_c_pool_necromass=DataArray(
                         [0.05840539, 0.01865113, 0.10632815, 0.06904724], dims="cell_id"
                     ),
-                    enzyme_pom=DataArray(
+                    soil_enzyme_pom=DataArray(
                         [0.02267842, 0.00957576, 0.05004963, 0.00300993], dims="cell_id"
                     ),
-                    enzyme_maom=DataArray(
+                    soil_enzyme_maom=DataArray(
                         [0.0354453, 0.01167442, 0.02538637, 0.00454144], dims="cell_id"
                     ),
+                    soil_n_pool_don=DataArray(
+                        [0.00058347, 0.00143007, 0.00016726, 0.00282812], dims="cell_id"
+                    ),
+                    soil_n_pool_particulate=DataArray(
+                        [0.00714836, 0.00074629, 0.00292269, 0.01429302], dims="cell_id"
+                    ),
                 )
             ),
             (),
@@ -312,14 +320,12 @@ def test_integrate_soil_model(
 
     with raises:
         new_pools = fixture_soil_model.integrate()
+
         # Check returned pools matched (mocked) integrator output
-        assert np.allclose(new_pools["soil_c_pool_lmwc"], final_pools["lmwc"])
-        assert np.allclose(new_pools["soil_c_pool_maom"], final_pools["maom"])
-        assert np.allclose(new_pools["soil_c_pool_microbe"], final_pools["microbe"])
-        assert np.allclose(new_pools["soil_c_pool_pom"], final_pools["pom"])
-        assert np.allclose(new_pools["soil_c_pool_necromass"], final_pools["necromass"])
-        assert np.allclose(new_pools["soil_enzyme_pom"], final_pools["enzyme_pom"])
-        assert np.allclose(new_pools["soil_enzyme_maom"], final_pools["enzyme_maom"])
+        assert set(new_pools.keys()) == set(final_pools.keys())
+
+        for key in new_pools.keys():
+            assert np.allclose(new_pools[key], final_pools[key])
 
     # Check that integrator is called once (and once only)
     if mock_output:
@@ -360,15 +366,14 @@ def test_order_independance(
         "soil_temperature",
         "clay_fraction",
         "litter_C_mineralisation_rate",
+        "litter_N_mineralisation_rate",
     ]
     for not_pool in not_pools:
         new_data[not_pool] = dummy_carbon_data[not_pool]
 
     # Then extract soil carbon pool names from the fixture (in order)
     pool_names = [
-        str(name)
-        for name in dummy_carbon_data.data.keys()
-        if str(name).startswith("soil_c_pool_") or str(name).startswith("soil_enzyme_")
+        name for name in dummy_carbon_data.data.keys() if name in SoilModel.vars_updated
     ]
 
     # Add pool values from object in reversed order
@@ -393,15 +398,17 @@ def test_order_independance(
 
 def test_construct_full_soil_model(dummy_carbon_data, fixture_core_components):
     """Test that the function that creates the object to integrate exists and works."""
-    from virtual_ecosystem.core.constants import CoreConsts
     from virtual_ecosystem.models.soil.constants import SoilConsts
-    from virtual_ecosystem.models.soil.soil_model import construct_full_soil_model
+    from virtual_ecosystem.models.soil.soil_model import (
+        SoilModel,
+        construct_full_soil_model,
+    )
 
     delta_pools = [
-        0.0022585928,
-        0.0060483065,
-        -0.019175058,
-        0.024247214,
+        0.00226177439,
+        0.006049897295,
+        -0.019174323,
+        0.024255464,
         0.038767651,
         0.00829848,
         0.05982197,
@@ -410,10 +417,10 @@ def test_construct_full_soil_model(dummy_carbon_data, fixture_core_components):
         -0.02020101,
         -0.10280967,
         -0.00719517,
-        0.00178122,
-        -0.00785937,
-        -0.01201551,
-        0.00545857,
+        0.00177803841,
+        -0.007860960795,
+        -0.012016245,
+        0.00545032,
         0.001137474,
         0.009172067,
         0.033573266,
@@ -426,23 +433,30 @@ def test_construct_full_soil_model(dummy_carbon_data, fixture_core_components):
         -5.09593e-5,
         0.0005990658,
         -3.72112e-5,
+        2.4081961e-5,
+        2.84920682e-6,
+        4.84845086e-5,
+        -5.83499913e-5,
+        1.102338e-5,
+        6.422491e-5,
+        0.000131687,
+        1.461799e-5,
     ]
 
     # make pools
     pools = np.concatenate(
         [
-            dummy_carbon_data[str(name)].to_numpy()
+            dummy_carbon_data[name].to_numpy()
             for name in dummy_carbon_data.data.keys()
-            if str(name).startswith("soil_c_pool_")
-            or str(name).startswith("soil_enzyme_")
+            if name in SoilModel.vars_updated
         ]
     )
 
     # Find and store order of pools
     delta_pools_ordered = {
-        str(name): np.array([])
+        name: np.array([])
         for name in dummy_carbon_data.data.keys()
-        if str(name).startswith("soil_c_pool_") or str(name).startswith("soil_enzyme_")
+        if name in SoilModel.vars_updated
     }
 
     rate_of_change = construct_full_soil_model(
@@ -453,7 +467,6 @@ def test_construct_full_soil_model(dummy_carbon_data, fixture_core_components):
         top_soil_layer_index=fixture_core_components.layer_structure.index_topsoil_scalar,
         delta_pools_ordered=delta_pools_ordered,
         model_constants=SoilConsts,
-        core_constants=CoreConsts,
     )
 
     assert np.allclose(delta_pools, rate_of_change)
diff --git a/tests/test_main.py b/tests/test_main.py
index cc7585329..e24bfa4e1 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -25,9 +25,11 @@
     (DEBUG, "soil model: required var 'soil_c_pool_lmwc' checked"),
     (DEBUG, "soil model: required var 'soil_c_pool_microbe' checked"),
     (DEBUG, "soil model: required var 'soil_c_pool_pom' checked"),
+    (DEBUG, "soil model: required var 'soil_c_pool_necromass' checked"),
     (DEBUG, "soil model: required var 'soil_enzyme_pom' checked"),
     (DEBUG, "soil model: required var 'soil_enzyme_maom' checked"),
-    (DEBUG, "soil model: required var 'soil_c_pool_necromass' checked"),
+    (DEBUG, "soil model: required var 'soil_n_pool_don' checked"),
+    (DEBUG, "soil model: required var 'soil_n_pool_particulate' checked"),
     (DEBUG, "soil model: required var 'pH' checked"),
     (DEBUG, "soil model: required var 'bulk_density' checked"),
     (DEBUG, "soil model: required var 'clay_fraction' checked"),
diff --git a/virtual_ecosystem/data_variables.toml b/virtual_ecosystem/data_variables.toml
index a79bb9986..c3ad17371 100644
--- a/virtual_ecosystem/data_variables.toml
+++ b/virtual_ecosystem/data_variables.toml
@@ -541,42 +541,56 @@ variable_type = "float"
 axis = ["spatial"]
 description = "Soil low molecular weight carbon pool"
 name = "soil_c_pool_lmwc"
-unit = "kg C m-3"
+unit = "kg C m^-3"
 variable_type = "float"
 
 [[variable]]
 axis = ["spatial"]
 description = "Soil mineral associated organic matter pool "
 name = "soil_c_pool_maom"
-unit = "kg C m-3"
+unit = "kg C m^-3"
 variable_type = "float"
 
 [[variable]]
 axis = ["spatial"]
 description = "Soil microbial biomass (carbon) pool"
 name = "soil_c_pool_microbe"
-unit = "kg C m-3"
+unit = "kg C m^-3"
 variable_type = "float"
 
 [[variable]]
 axis = ["spatial"]
 description = "Particulate organic matter pool"
 name = "soil_c_pool_pom"
-unit = "kg C m-3"
+unit = "kg C m^-3"
 variable_type = "float"
 
 [[variable]]
 axis = ["spatial"]
 description = "Necrotic organic matter pool"
 name = "soil_c_pool_necromass"
-unit = "kg C m-3"
+unit = "kg C m^-3"
+variable_type = "float"
+
+[[variable]]
+axis = ["spatial"]
+description = "Dissolved organic nitrogen pool"
+name = "soil_n_pool_don"
+unit = "kg N m^-3"
+variable_type = "float"
+
+[[variable]]
+axis = ["spatial"]
+description = "Particulate organic nitrogen pool"
+name = "soil_n_pool_particulate"
+unit = "kg N m^-3"
 variable_type = "float"
 
 [[variable]]
 axis = ["spatial"]
 description = "Bulk density of soil"
 name = "bulk_density"
-unit = "kg m-3"
+unit = "kg m^-3"
 variable_type = "float"
 
 [[variable]]
diff --git a/virtual_ecosystem/example_data/config/data_config.toml b/virtual_ecosystem/example_data/config/data_config.toml
index 2ea715d7f..2f7d1626f 100644
--- a/virtual_ecosystem/example_data/config/data_config.toml
+++ b/virtual_ecosystem/example_data/config/data_config.toml
@@ -65,6 +65,12 @@ var_name = "soil_enzyme_pom"
 [[core.data.variable]]
 file = "../data/example_soil_data.nc"
 var_name = "soil_enzyme_maom"
+[[core.data.variable]]
+file = "../data/example_soil_data.nc"
+var_name = "soil_n_pool_don"
+[[core.data.variable]]
+file = "../data/example_soil_data.nc"
+var_name = "soil_n_pool_particulate"
 
 # Litter 
 [[core.data.variable]]
diff --git a/virtual_ecosystem/example_data/data/example_soil_data.nc b/virtual_ecosystem/example_data/data/example_soil_data.nc
index 1426655da..a9ce75e25 100644
Binary files a/virtual_ecosystem/example_data/data/example_soil_data.nc and b/virtual_ecosystem/example_data/data/example_soil_data.nc differ
diff --git a/virtual_ecosystem/example_data/generation_scripts/soil_example_data.py b/virtual_ecosystem/example_data/generation_scripts/soil_example_data.py
index 89092eb25..33893b8e0 100644
--- a/virtual_ecosystem/example_data/generation_scripts/soil_example_data.py
+++ b/virtual_ecosystem/example_data/generation_scripts/soil_example_data.py
@@ -45,6 +45,13 @@
 # Generate a range of plausible values (0.01-0.5) for the MAOM enzyme pool [kg C m^-3].
 maom_enzyme_values = 0.01 + 0.49 * gradient / 64.0
 
+# Generate a range of plausible values (2.5e-4 - 5.0e-4) for the DON pool [kg N m^-3]
+don_values = 2.5e-4 + 2.5e-4 * gradient / 64.0
+
+# Generate a range of plausible values (7.5e-4 - 1.5e-3) for the particulate N pool [kg
+# N m^-3]
+particulate_n_values = 7.5e-4 + 7.5e-4 * gradient / 64.0
+
 # Make example soil dataset
 example_soil_data = Dataset(
     data_vars=dict(
@@ -58,6 +65,8 @@
         soil_c_pool_necromass=(["x", "y"], necromass_values),
         soil_enzyme_pom=(["x", "y"], pom_enzyme_values),
         soil_enzyme_maom=(["x", "y"], maom_enzyme_values),
+        soil_n_pool_don=(["x", "y"], don_values),
+        soil_n_pool_particulate=(["x", "y"], particulate_n_values),
     ),
     coords=dict(
         x=(["x"], cell_displacements),
diff --git a/virtual_ecosystem/models/soil/__init__.py b/virtual_ecosystem/models/soil/__init__.py
index 5378cc8e5..732439124 100644
--- a/virtual_ecosystem/models/soil/__init__.py
+++ b/virtual_ecosystem/models/soil/__init__.py
@@ -6,8 +6,8 @@
 * The :mod:`~virtual_ecosystem.models.soil.soil_model` submodule instantiates the
   SoilModel class which consolidates the functionality of the soil module into a single
   class, which the high level functions of the Virtual Ecosystem can then make use of.
-* The :mod:`~virtual_ecosystem.models.soil.carbon` provides a model for the soil carbon
-  cycle.
+* The :mod:`~virtual_ecosystem.models.soil.pools` provides functionality to track
+  all soil pools over time.
 * The :mod:`~virtual_ecosystem.models.soil.env_factors` provides functions that capture
   the impact of environmental factors on microbial rates.
 * The :mod:`~virtual_ecosystem.models.soil.constants` provides a set of dataclasses
diff --git a/virtual_ecosystem/models/soil/constants.py b/virtual_ecosystem/models/soil/constants.py
index 94596453d..74d97188c 100644
--- a/virtual_ecosystem/models/soil/constants.py
+++ b/virtual_ecosystem/models/soil/constants.py
@@ -9,8 +9,6 @@
 
 from virtual_ecosystem.core.constants_class import ConstantsDataclass
 
-# TODO - Once lignin is tracked a large number of constants will have to be duplicated
-
 
 @dataclass(frozen=True)
 class SoilConsts(ConstantsDataclass):
@@ -256,6 +254,13 @@ class SoilConsts(ConstantsDataclass):
     a loose manner.
     """
 
+    solubility_coefficient_don: float = 1.0
+    """Solubility coefficient for dissolved organic nitrogen [unitless].
+
+    Value taken from :cite:t:`fatichi_mechanistic_2019`, where it is estimated in quite
+    a loose manner.
+    """
+
     necromass_decay_rate: float = (1 / 3) * np.log(2)
     """Rate at which microbial necromass decays to low molecular weight carbon [day^-1]
 
@@ -288,3 +293,17 @@ class SoilConsts(ConstantsDataclass):
     remainder becoming LMWC. Replacing this with a function that depends on
     environmental conditions is a post release goal.
     """
+
+    litter_leaching_fraction_carbon = 0.0015
+    """Fraction of carbon mineralisation from litter that occurs by leaching [unitless].
+    
+    The remainder of the mineralisation consists of particulates. Value is an order of
+    magnitude estimate taken from :cite:t:`fatichi_mechanistic_2019`.
+    """
+
+    litter_leaching_fraction_nitrogen = 0.0015
+    """Fraction of nitrogen mineralisation from litter that occurs by leaching.
+    
+    [unitless]. The remainder of the mineralisation consists of particulates. Value is
+    an order of magnitude estimate taken from :cite:t:`fatichi_mechanistic_2019`.
+    """
diff --git a/virtual_ecosystem/models/soil/carbon.py b/virtual_ecosystem/models/soil/pools.py
similarity index 64%
rename from virtual_ecosystem/models/soil/carbon.py
rename to virtual_ecosystem/models/soil/pools.py
index e95605680..99b3f6422 100644
--- a/virtual_ecosystem/models/soil/carbon.py
+++ b/virtual_ecosystem/models/soil/pools.py
@@ -1,7 +1,9 @@
-"""The ``models.soil.carbon`` module  simulates the soil carbon cycle for the Virtual
-Ecosystem. At the moment five pools are modelled, these are low molecular weight carbon
+"""The ``models.soil.pools`` module simulates all soil pools for the Virtual
+Ecosystem. At the moment four carbon pools are modelled (low molecular weight carbon
 (LMWC), mineral associated organic matter (MAOM), microbial biomass, particulate organic
-matter (POM), and POM degrading enzymes.
+matter (POM)), as well as two enzyme pools (POM and MAOM) degrading enzymes, and two
+nitrogen pools (dissolved organic nitrogen (DON) and particulate organic nitrogen
+(PON)).
 """  # noqa: D205
 
 from dataclasses import dataclass
@@ -9,7 +11,7 @@
 import numpy as np
 from numpy.typing import NDArray
 
-from virtual_ecosystem.core.constants import CoreConsts
+from virtual_ecosystem.core.data import Data
 from virtual_ecosystem.models.soil.constants import SoilConsts
 from virtual_ecosystem.models.soil.env_factors import (
     EnvironmentalEffectFactors,
@@ -18,6 +20,9 @@
     calculate_temperature_effect_on_microbes,
 )
 
+# TODO - At this point in time I'm not adding specific phosphatase enzymes, need to
+# think about adding these in future
+
 
 @dataclass
 class MicrobialChanges:
@@ -64,145 +69,189 @@ class EnzymeMediatedRates:
     """
 
 
-# TODO - This function should probably be shortened. I've done some work on this
-# already, but I need to keep an eye on it as new pools are added.
-def calculate_soil_carbon_updates(
-    soil_c_pool_lmwc: NDArray[np.float32],
-    soil_c_pool_maom: NDArray[np.float32],
-    soil_c_pool_microbe: NDArray[np.float32],
-    soil_c_pool_pom: NDArray[np.float32],
-    soil_c_pool_necromass: NDArray[np.float32],
-    soil_enzyme_pom: NDArray[np.float32],
-    soil_enzyme_maom: NDArray[np.float32],
-    pH: NDArray[np.float32],
-    bulk_density: NDArray[np.float32],
-    soil_moisture: NDArray[np.float32],
-    soil_water_potential: NDArray[np.float32],
-    vertical_flow_rate: NDArray[np.float32],
-    soil_temp: NDArray[np.float32],
-    clay_fraction: NDArray[np.float32],
-    mineralisation_rate: NDArray[np.float32],
-    delta_pools_ordered: dict[str, NDArray[np.float32]],
-    core_constants: CoreConsts,
-    model_constants: SoilConsts,
-) -> NDArray[np.float32]:
-    """Calculate net change for each carbon pool.
+class SoilPools:
+    """This class collects all the various soil pools so that they can be updated.
 
-    This function calls lower level functions which calculate the transfers between
-    pools. When all transfers have been calculated the net transfer is used to
-    calculate the net change for each pool.
+    This class contains a method to update all soil pools. As well as taking in the data
+    object it also has to take in another dictionary containing the pools. This
+    dictionary is modifiable by the integration algorithm whereas the data object will
+    only be modified when the entire soil model simulation has finished.
+    """
 
-    Args:
-        soil_c_pool_lmwc: Low molecular weight carbon pool [kg C m^-3]
-        soil_c_pool_maom: Mineral associated organic matter pool [kg C m^-3]
-        soil_c_pool_microbe: Microbial biomass (carbon) pool [kg C m^-3]
-        soil_c_pool_pom: Particulate organic matter pool [kg C m^-3]
-        soil_c_pool_necromass: Microbial necromass pool [kg C m^-3]
-        soil_enzyme_pom: Amount of enzyme class which breaks down particulate organic
-            matter [kg C m^-3]
-        soil_enzyme_maom: Amount of enzyme class which breaks down mineral associated
-            organic matter [kg C m^-3]
-        pH: pH values for each soil grid cell [unitless]
-        bulk_density: bulk density values for each soil grid cell [kg m^-3]
-        soil_moisture: amount of water contained by each soil layer [mm]
-        soil_water_potential: Soil water potential for each grid cell [kPa]
-        vertical_flow_rate: The vertical flow rate [TODO]
-        soil_temp: soil temperature for each soil grid cell [degrees C]
-        clay_fraction: The clay fraction for each soil grid cell [unitless]
-        mineralisation_rate: Amount of litter mineralised into POM pool [kg C m^-3
-            day^-1]
-        delta_pools_ordered: Dictionary to store pool changes in the order that pools
-            are stored in the initial condition vector.
-        core_constants: Set of constants shared between models.
-        model_constants: Set of constants for the soil model.
+    def __init__(
+        self, data: Data, pools: dict[str, NDArray[np.float32]], constants: SoilConsts
+    ):
+        self.data = data
+        """The data object for the Virtual Ecosystem simulation."""
+        self.pools = pools
+        """Pools which can change during the soil model update.
+        
+        These pools need to be added outside the data object otherwise the integrator
+        cannot update them and the integration will fail.
+        """
+        self.constants = constants
+
+    def calculate_all_pool_updates(
+        self,
+        delta_pools_ordered: dict[str, NDArray[np.float32]],
+        top_soil_layer_index: int,
+    ) -> NDArray[np.float32]:
+        """Calculate net change for all soil pools.
+
+        This function calls lower level functions which calculate the transfers between
+        pools. When all transfers have been calculated the net transfer is used to
+        calculate the net change for each pool.
+
+        The data that this function uses (which comes from the `data` object) is stored
+        in a dictionary form. This becomes an issue as the `scipy` integrator used to
+        integrate this function expects a `numpy` array, and if the order of variables
+        changes in this array the integrator will generate nonsensical results. To
+        prevent this from happening a dictionary (`delta_pools_ordered`) is supplied
+        that contains all the variables that get integrated, this dictionary sets the
+        order of variables in the output `numpy` array. As this dictionary is passed
+        from :func:`~virtual_ecosystem.models.soil.soil_model.SoilModel.integrate` this
+        ensures that the order is the same for the entire integration.
+
+        Args:
+            delta_pools_ordered: Dictionary to store pool changes in the order that
+                pools are stored in the initial condition vector.
+            top_soil_layer_index: Index for layer in data object representing top soil
+                layer
+
+        Returns:
+            A vector containing net changes to each pool. Order [lmwc, maom].
+        """
+
+        # Find temperature and soil moisture values for the topsoil layer
+        soil_water_potential = self.data["matric_potential"][
+            top_soil_layer_index
+        ].to_numpy()
+        soil_temperature = self.data["soil_temperature"][
+            top_soil_layer_index
+        ].to_numpy()
+        soil_moisture = self.data["soil_moisture"][top_soil_layer_index].to_numpy()
+
+        # Find environmental factors which impact biogeochemical soil processes
+        env_factors = calculate_environmental_effect_factors(
+            soil_water_potential=soil_water_potential,
+            pH=self.data["pH"].to_numpy(),
+            clay_fraction=self.data["clay_fraction"].to_numpy(),
+            constants=self.constants,
+        )
+        # find changes related to microbial uptake, growth and decay
+        microbial_changes = calculate_microbial_changes(
+            soil_c_pool_lmwc=self.pools["soil_c_pool_lmwc"],
+            soil_c_pool_microbe=self.pools["soil_c_pool_microbe"],
+            soil_enzyme_pom=self.pools["soil_enzyme_pom"],
+            soil_enzyme_maom=self.pools["soil_enzyme_maom"],
+            soil_temp=soil_temperature,
+            env_factors=env_factors,
+            constants=self.constants,
+        )
+        # find changes driven by the enzyme pools
+        enzyme_mediated = calculate_enzyme_mediated_rates(
+            soil_enzyme_pom=self.pools["soil_enzyme_pom"],
+            soil_enzyme_maom=self.pools["soil_enzyme_maom"],
+            soil_c_pool_pom=self.pools["soil_c_pool_pom"],
+            soil_c_pool_maom=self.pools["soil_c_pool_maom"],
+            soil_temp=soil_temperature,
+            env_factors=env_factors,
+            constants=self.constants,
+        )
 
-    Returns:
-        A vector containing net changes to each pool. Order [lmwc, maom].
-    """
+        labile_carbon_leaching = calculate_leaching_rate(
+            solute_density=self.pools["soil_c_pool_lmwc"],
+            vertical_flow_rate=self.data["vertical_flow"].to_numpy(),
+            soil_moisture=soil_moisture,
+            solubility_coefficient=self.constants.solubility_coefficient_lmwc,
+        )
+        don_leaching = calculate_leaching_rate(
+            solute_density=self.pools["soil_n_pool_don"],
+            vertical_flow_rate=self.data["vertical_flow"].to_numpy(),
+            soil_moisture=soil_moisture,
+            solubility_coefficient=self.constants.solubility_coefficient_don,
+        )
 
-    # Find environmental factors which impact biogeochemical soil processes
-    env_factors = calculate_environmental_effect_factors(
-        soil_water_potential=soil_water_potential,
-        pH=pH,
-        clay_fraction=clay_fraction,
-        constants=model_constants,
-    )
-    # find changes related to microbial uptake, growth and decay
-    microbial_changes = calculate_microbial_changes(
-        soil_c_pool_lmwc=soil_c_pool_lmwc,
-        soil_c_pool_microbe=soil_c_pool_microbe,
-        soil_enzyme_pom=soil_enzyme_pom,
-        soil_enzyme_maom=soil_enzyme_maom,
-        soil_temp=soil_temp,
-        env_factors=env_factors,
-        constants=model_constants,
-    )
-    # find changes driven by the enzyme pools
-    enzyme_mediated = calculate_enzyme_mediated_rates(
-        soil_enzyme_pom=soil_enzyme_pom,
-        soil_enzyme_maom=soil_enzyme_maom,
-        soil_c_pool_pom=soil_c_pool_pom,
-        soil_c_pool_maom=soil_c_pool_maom,
-        soil_temp=soil_temp,
-        env_factors=env_factors,
-        constants=model_constants,
-    )
+        # Calculate transfers between the lmwc, necromass and maom pools
+        maom_desorption_to_lmwc = calculate_maom_desorption(
+            soil_c_pool_maom=self.pools["soil_c_pool_maom"],
+            desorption_rate_constant=self.constants.maom_desorption_rate,
+        )
 
-    labile_carbon_leaching = calculate_leaching_rate(
-        solute_density=soil_c_pool_lmwc,
-        vertical_flow_rate=vertical_flow_rate,
-        soil_moisture=soil_moisture,
-        solubility_coefficient=model_constants.solubility_coefficient_lmwc,
-    )
+        necromass_decay_to_lmwc = calculate_necromass_breakdown(
+            soil_c_pool_necromass=self.pools["soil_c_pool_necromass"],
+            necromass_decay_rate=self.constants.necromass_decay_rate,
+        )
 
-    # Calculate transfers between the lmwc, necromass and maom pools
-    maom_desorption_to_lmwc = calculate_maom_desorption(
-        soil_c_pool_maom=soil_c_pool_maom,
-        desorption_rate_constant=model_constants.maom_desorption_rate,
-    )
-    necromass_decay_to_lmwc = calculate_necromass_breakdown(
-        soil_c_pool_necromass=soil_c_pool_necromass,
-        necromass_decay_rate=model_constants.necromass_decay_rate,
-    )
-    necromass_sorption_to_maom = calculate_sorption_to_maom(
-        soil_c_pool=soil_c_pool_necromass,
-        sorption_rate_constant=model_constants.necromass_sorption_rate,
-    )
-    lmwc_sorption_to_maom = calculate_sorption_to_maom(
-        soil_c_pool=soil_c_pool_lmwc,
-        sorption_rate_constant=model_constants.lmwc_sorption_rate,
-    )
+        necromass_sorption_to_maom = calculate_sorption_to_maom(
+            soil_c_pool=self.pools["soil_c_pool_necromass"],
+            sorption_rate_constant=self.constants.necromass_sorption_rate,
+        )
+        lmwc_sorption_to_maom = calculate_sorption_to_maom(
+            soil_c_pool=self.pools["soil_c_pool_lmwc"],
+            sorption_rate_constant=self.constants.lmwc_sorption_rate,
+        )
 
-    # Determine net changes to the pools
-    delta_pools_ordered["soil_c_pool_lmwc"] = (
-        enzyme_mediated.pom_to_lmwc
-        + enzyme_mediated.maom_to_lmwc
-        + maom_desorption_to_lmwc
-        + necromass_decay_to_lmwc
-        - microbial_changes.lmwc_uptake
-        - lmwc_sorption_to_maom
-        - labile_carbon_leaching
-    )
-    delta_pools_ordered["soil_c_pool_maom"] = (
-        necromass_sorption_to_maom
-        + lmwc_sorption_to_maom
-        - enzyme_mediated.maom_to_lmwc
-        - maom_desorption_to_lmwc
-    )
-    delta_pools_ordered["soil_c_pool_microbe"] = microbial_changes.microbe_change
-    delta_pools_ordered["soil_c_pool_pom"] = (
-        mineralisation_rate - enzyme_mediated.pom_to_lmwc
-    )
-    delta_pools_ordered["soil_c_pool_necromass"] = (
-        microbial_changes.necromass_generation
-        - necromass_decay_to_lmwc
-        - necromass_sorption_to_maom
-    )
-    delta_pools_ordered["soil_enzyme_pom"] = microbial_changes.pom_enzyme_change
-    delta_pools_ordered["soil_enzyme_maom"] = microbial_changes.maom_enzyme_change
+        # Calculate the split of the mineralisation flux between dissolved and
+        # particulate forms
+        litter_mineralisation_fluxes_C = calculate_litter_mineralisation_split(
+            mineralisation_rate=self.data["litter_C_mineralisation_rate"].to_numpy(),
+            litter_leaching_coefficient=self.constants.litter_leaching_fraction_carbon,
+        )
+        litter_mineralisation_fluxes_N = calculate_litter_mineralisation_split(
+            mineralisation_rate=self.data["litter_N_mineralisation_rate"].to_numpy(),
+            litter_leaching_coefficient=self.constants.litter_leaching_fraction_nitrogen,
+        )
 
-    # Create output array of pools in desired order
-    return np.concatenate(list(delta_pools_ordered.values()))
+        # Find mineralisation rate from POM
+        pom_n_mineralisation = calculate_soil_nutrient_mineralisation(
+            pool_carbon=self.pools["soil_c_pool_pom"],
+            pool_nutrient=self.pools["soil_n_pool_particulate"],
+            breakdown_rate=enzyme_mediated.pom_to_lmwc,
+        )
+
+        # Determine net changes to the pools
+        delta_pools_ordered["soil_c_pool_lmwc"] = (
+            litter_mineralisation_fluxes_C["dissolved"]
+            + enzyme_mediated.pom_to_lmwc
+            + enzyme_mediated.maom_to_lmwc
+            + maom_desorption_to_lmwc
+            + necromass_decay_to_lmwc
+            - microbial_changes.lmwc_uptake
+            - lmwc_sorption_to_maom
+            - labile_carbon_leaching
+        )
+
+        delta_pools_ordered["soil_c_pool_maom"] = (
+            necromass_sorption_to_maom
+            + lmwc_sorption_to_maom
+            - enzyme_mediated.maom_to_lmwc
+            - maom_desorption_to_lmwc
+        )
+
+        delta_pools_ordered["soil_c_pool_microbe"] = microbial_changes.microbe_change
+        delta_pools_ordered["soil_c_pool_pom"] = (
+            litter_mineralisation_fluxes_C["particulate"] - enzyme_mediated.pom_to_lmwc
+        )
+        delta_pools_ordered["soil_c_pool_necromass"] = (
+            microbial_changes.necromass_generation
+            - necromass_decay_to_lmwc
+            - necromass_sorption_to_maom
+        )
+        delta_pools_ordered["soil_n_pool_don"] = (
+            litter_mineralisation_fluxes_N["dissolved"]
+            + pom_n_mineralisation
+            - don_leaching
+        )
+
+        delta_pools_ordered["soil_n_pool_particulate"] = (
+            litter_mineralisation_fluxes_N["particulate"] - pom_n_mineralisation
+        )
+        delta_pools_ordered["soil_enzyme_pom"] = microbial_changes.pom_enzyme_change
+        delta_pools_ordered["soil_enzyme_maom"] = microbial_changes.maom_enzyme_change
+
+        # Create output array of pools in desired order
+        return np.concatenate(list(delta_pools_ordered.values()))
 
 
 def calculate_microbial_changes(
@@ -651,3 +700,58 @@ def calculate_necromass_breakdown(
     """
 
     return necromass_decay_rate * soil_c_pool_necromass
+
+
+def calculate_litter_mineralisation_split(
+    mineralisation_rate: NDArray[np.float32], litter_leaching_coefficient: float
+) -> dict[str, NDArray[np.float32]]:
+    """Determine how nutrients from litter mineralisation get split between soil pools.
+
+    All nutrients that we track (carbon, nitrogen and phosphorus) get divided between
+    the particulate organic matter pool and the dissolved pool for their respective
+    nutrient (for the carbon case this pool is termed low molecular weight carbon). This
+    split is calculated based on empirically derived litter leaching constants.
+
+    Args:
+        mineralisation_rate: The rate at which the nutrient is being mineralised for the
+            litter [kg C m^-3 day^-1]
+        litter_leaching_coefficient: Fraction of the litter mineralisation of the
+            nutrient that occurs via leaching rather than as particulates [unitless]
+
+    Returns:
+        A dictionary containing the rate at which the nutrient is added to the soil as
+        particulates and as dissolved matter [kg C m^-3 day^-1].
+    """
+
+    return {
+        "particulate": (1 - litter_leaching_coefficient) * mineralisation_rate,
+        "dissolved": litter_leaching_coefficient * mineralisation_rate,
+    }
+
+
+def calculate_soil_nutrient_mineralisation(
+    pool_carbon: NDArray[np.float32],
+    pool_nutrient: NDArray[np.float32],
+    breakdown_rate: NDArray[np.float32],
+):
+    """Calculate mineralisation rate from soil organic matter for a specific nutrient.
+
+    This function assumes that nutrients are mineralised in direct proportion to their
+    ratio to carbon in the decaying organic matter. This function is therefore does not
+    capture mechanisms that exist to actively release nutrients from organic matter
+    (e.g. phosphatase enzymes).
+
+    Args:
+        pool_carbon: The carbon content of the organic matter pool [kg C m^-3]
+        pool_nutrient: The nutrient content of the organic matter pool [kg nutrient
+            m^-3]
+        breakdown_rate: The rate at which the pool is being broken down (expressed in
+            carbon terms) [kg C m^-3 day^-1]
+
+    Returns:
+        The rate at which the nutrient in question is mineralised due to organic matter
+        breakdown [kg nutrient m^-3 day^-1]
+    """
+
+    carbon_nutrient_ratio = pool_carbon / pool_nutrient
+    return breakdown_rate / carbon_nutrient_ratio
diff --git a/virtual_ecosystem/models/soil/soil_model.py b/virtual_ecosystem/models/soil/soil_model.py
index b9285028e..f8011a39d 100644
--- a/virtual_ecosystem/models/soil/soil_model.py
+++ b/virtual_ecosystem/models/soil/soil_model.py
@@ -27,14 +27,13 @@
 
 from virtual_ecosystem.core.base_model import BaseModel
 from virtual_ecosystem.core.config import Config
-from virtual_ecosystem.core.constants import CoreConsts
 from virtual_ecosystem.core.constants_loader import load_constants
 from virtual_ecosystem.core.core_components import CoreComponents
 from virtual_ecosystem.core.data import Data
 from virtual_ecosystem.core.exceptions import InitialisationError
 from virtual_ecosystem.core.logger import LOGGER
-from virtual_ecosystem.models.soil.carbon import calculate_soil_carbon_updates
 from virtual_ecosystem.models.soil.constants import SoilConsts
+from virtual_ecosystem.models.soil.pools import SoilPools
 
 
 class IntegrationError(Exception):
@@ -50,9 +49,11 @@ class SoilModel(
         "soil_c_pool_lmwc",
         "soil_c_pool_microbe",
         "soil_c_pool_pom",
+        "soil_c_pool_necromass",
         "soil_enzyme_pom",
         "soil_enzyme_maom",
-        "soil_c_pool_necromass",
+        "soil_n_pool_don",
+        "soil_n_pool_particulate",
         "pH",
         "bulk_density",
         "clay_fraction",
@@ -66,7 +67,14 @@ class SoilModel(
         "soil_c_pool_necromass",
         "soil_enzyme_pom",
         "soil_enzyme_maom",
+        "soil_n_pool_don",
+        "soil_n_pool_particulate",
         "matric_potential",
+        "vertical_flow",
+        "soil_temperature",
+        "soil_moisture",
+        "litter_C_mineralisation_rate",
+        "litter_N_mineralisation_rate",
     ),
     vars_updated=(
         "soil_c_pool_maom",
@@ -76,6 +84,8 @@ class SoilModel(
         "soil_c_pool_necromass",
         "soil_enzyme_pom",
         "soil_enzyme_maom",
+        "soil_n_pool_don",
+        "soil_n_pool_particulate",
     ),
     vars_populated_by_first_update=(),
 ):
@@ -112,6 +122,8 @@ def __init__(
             or np.any(data["soil_enzyme_pom"] < 0.0)
             or np.any(data["soil_enzyme_maom"] < 0.0)
             or np.any(data["soil_c_pool_necromass"] < 0.0)
+            or np.any(data["soil_n_pool_don"] < 0.0)
+            or np.any(data["soil_n_pool_particulate"] < 0.0)
         ):
             to_raise = InitialisationError(
                 "Initial carbon pools contain at least one negative value!"
@@ -208,7 +220,7 @@ def integrate(self) -> dict[str, DataArray]:
             [
                 self.data[name].to_numpy()
                 for name in map(str, self.data.data.keys())
-                if name.startswith("soil_c_pool_") or name.startswith("soil_enzyme_")
+                if name in self.vars_updated
             ]
         )
 
@@ -216,7 +228,7 @@ def integrate(self) -> dict[str, DataArray]:
         delta_pools_ordered = {
             name: np.array([])
             for name in map(str, self.data.data.keys())
-            if name.startswith("soil_c_pool_") or name.startswith("soil_enzyme_")
+            if name in self.vars_updated
         }
 
         # Carry out simulation
@@ -230,7 +242,6 @@ def integrate(self) -> dict[str, DataArray]:
                 self.layer_structure.index_topsoil_scalar,
                 delta_pools_ordered,
                 self.model_constants,
-                self.core_constants,
             ),
         )
 
@@ -263,7 +274,6 @@ def construct_full_soil_model(
     top_soil_layer_index: int,
     delta_pools_ordered: dict[str, NDArray[np.float32]],
     model_constants: SoilConsts,
-    core_constants: CoreConsts,
 ) -> NDArray[np.float32]:
     """Function that constructs the full soil model in a solve_ivp friendly form.
 
@@ -278,7 +288,6 @@ def construct_full_soil_model(
         delta_pools_ordered: Dictionary to store pool changes in the order that pools
             are stored in the initial condition vector.
         model_constants: Set of constants for the soil model.
-        core_constants: Set of constants shared between models.
 
     Returns:
         The rate of change for each soil pool
@@ -288,24 +297,15 @@ def construct_full_soil_model(
     slices = make_slices(no_cells, len(delta_pools_ordered))
 
     # Construct dictionary of numpy arrays (using a for loop)
-    soil_pools = {
+    all_pools = {
         str(pool): pools[slc] for slc, pool in zip(slices, delta_pools_ordered.keys())
     }
 
-    # Supply soil pools by unpacking dictionary
-    return calculate_soil_carbon_updates(
-        pH=data["pH"].to_numpy(),
-        bulk_density=data["bulk_density"].to_numpy(),
-        soil_moisture=data["soil_moisture"][top_soil_layer_index].to_numpy(),
-        soil_water_potential=data["matric_potential"][top_soil_layer_index].to_numpy(),
-        vertical_flow_rate=data["vertical_flow"].to_numpy(),
-        soil_temp=data["soil_temperature"][top_soil_layer_index].to_numpy(),
-        clay_fraction=data["clay_fraction"].to_numpy(),
-        mineralisation_rate=data["litter_C_mineralisation_rate"].to_numpy(),
+    soil_pools = SoilPools(data, pools=all_pools, constants=model_constants)
+
+    return soil_pools.calculate_all_pool_updates(
         delta_pools_ordered=delta_pools_ordered,
-        model_constants=model_constants,
-        core_constants=core_constants,
-        **soil_pools,
+        top_soil_layer_index=top_soil_layer_index,
     )