Structure, Photosynthesis and Light In Canopy Environments (SPLICE)
Lead Research Organisation:
UNIVERSITY OF READING
Department Name: Meteorology
Abstract
The SPLICE project (Structure, Photosynthesis and Light In Canopy Environments) seeks to improve our understanding of global photosynthesis and hence our ability to model climate change, by considering the way in which the three-dimensional structure of plants interacts with light and how this in turn impacts on the uptake of carbon. We will employ state-of-the-art techniques to measure the three dimensional structure and photosynthesis of forests and construct detailed computer simulations to create a virtual laboratory that we can use to improve simulations from climate models.
The process of photosynthesis is fundamental to life on Earth. In this project we are concerned with its role in the terrestrial carbon cycle, which in turn is important for understanding climate change. The land surface absorbs around 25% of anthropogenic CO2 emissions and this proportion has remained remarkably constant despite increasing emissions. Whether or not this will continue is unknown. Earth System Models (ESMs), which are essentially climate models that include climate-relevant biological process, include the uptake of carbon by plants via photosynthesis so that they can model (a) the influence of this process on atmospheric carbon dioxide concentrations and (b) the impact of climate change on global vegetation. There have been significant advances made in the modelling of photosynthesis inside these models in recent decades, for example the interaction with the nitrogen cycle, but they still include some very simple assumptions. We argue that chief amongst these is the way in which the three dimensional structure of vegetation is represented - something that has not been improved for nearly four decades.
The equations in ESMs that govern the interception of light by plants, which in turn drives photosynthesis, make the simplifying assumption that leaves are randomly arranged in space, not clustered into tree crowns or around branches. This allows relevant equations in physics to be solved in such a way that results in computationally efficient computer code, but does not represent reality very closely. Recent research from the University of Reading has shown that the impact of including even a simple representation of these effects into an ESM can have large impacts on the global carbon cycle. In particular we showed an enhancement in the modelled estimates of global photosynthesis of 5 billion tonnes of carbon per year, or more than half of CO2 released from burning fossil fuels. Most of this occurs in the tropics, an area of the Earth likely to be especially vulnerable to the impacts of climate change.
SPLICE will measure the 3D structure of 26 forests around the world using a combination of terrestrial Lidar scanning and airborne Lidar surveys. Lidar uses scattered laser light to infer structure of forests and information from it can be used to reconstruct a branch-by-branch simulation of the forest. We will take these data and build detailed 3D models of the forest light environment and resulting photosynthesis. The photosynthetic flux will be measured using a variety of techniques, including observations of solar induced fluorescence (SIF) from drones. These observations will be used to test our 3D models. SIF occurs as part of photosynthesis and although it has been known about for some time the technology to observe it remotely is relatively new. It provides a close proxy for the amount of carbon being taken up by photosynthesis.
Our final step will be to use the detailed 3D models to develop a modified version of the computer codes used in ESMs to represent the interaction of light with vegetation canopies. These modified codes will be used in the land surface component of UKESM - the UK's new Earth System Model - to assess the impact of these changes globally and the magnitude of their impact on the carbon cycle and hence climate change.
The process of photosynthesis is fundamental to life on Earth. In this project we are concerned with its role in the terrestrial carbon cycle, which in turn is important for understanding climate change. The land surface absorbs around 25% of anthropogenic CO2 emissions and this proportion has remained remarkably constant despite increasing emissions. Whether or not this will continue is unknown. Earth System Models (ESMs), which are essentially climate models that include climate-relevant biological process, include the uptake of carbon by plants via photosynthesis so that they can model (a) the influence of this process on atmospheric carbon dioxide concentrations and (b) the impact of climate change on global vegetation. There have been significant advances made in the modelling of photosynthesis inside these models in recent decades, for example the interaction with the nitrogen cycle, but they still include some very simple assumptions. We argue that chief amongst these is the way in which the three dimensional structure of vegetation is represented - something that has not been improved for nearly four decades.
The equations in ESMs that govern the interception of light by plants, which in turn drives photosynthesis, make the simplifying assumption that leaves are randomly arranged in space, not clustered into tree crowns or around branches. This allows relevant equations in physics to be solved in such a way that results in computationally efficient computer code, but does not represent reality very closely. Recent research from the University of Reading has shown that the impact of including even a simple representation of these effects into an ESM can have large impacts on the global carbon cycle. In particular we showed an enhancement in the modelled estimates of global photosynthesis of 5 billion tonnes of carbon per year, or more than half of CO2 released from burning fossil fuels. Most of this occurs in the tropics, an area of the Earth likely to be especially vulnerable to the impacts of climate change.
SPLICE will measure the 3D structure of 26 forests around the world using a combination of terrestrial Lidar scanning and airborne Lidar surveys. Lidar uses scattered laser light to infer structure of forests and information from it can be used to reconstruct a branch-by-branch simulation of the forest. We will take these data and build detailed 3D models of the forest light environment and resulting photosynthesis. The photosynthetic flux will be measured using a variety of techniques, including observations of solar induced fluorescence (SIF) from drones. These observations will be used to test our 3D models. SIF occurs as part of photosynthesis and although it has been known about for some time the technology to observe it remotely is relatively new. It provides a close proxy for the amount of carbon being taken up by photosynthesis.
Our final step will be to use the detailed 3D models to develop a modified version of the computer codes used in ESMs to represent the interaction of light with vegetation canopies. These modified codes will be used in the land surface component of UKESM - the UK's new Earth System Model - to assess the impact of these changes globally and the magnitude of their impact on the carbon cycle and hence climate change.
Publications
Essery R
(2024)
A Flexible Snow Model (FSM 2.1.0) including a forest canopy
Essery R
(2025)
A Flexible Snow Model (FSM 2.1.1) including a forest canopy
in Geoscientific Model Development
Quaife T
(2025)
A Two Stream Radiative Transfer Model for Vertically Inhomogeneous Vegetation Canopies Including Internal Emission
in Journal of Advances in Modeling Earth Systems
Stretton M
(2025)
The influence of 3D canopy structure on modelled photosynthesis
in Agricultural and Forest Meteorology
Stretton M
(2025)
The impact of forest canopy structure on modelled photosynthesis
| Description | The representation of vegetation in climate models is relatively simple. This project examined the assumption, common to most climate models, that leaves are distributed randomly in space. We showed that this can lead to poor approximations of carbon uptake especially in forests with open canopies. We also refuted a previous hypothesis that 3D structure would tend to enhance photosynthesis, with our results showing that, whilst that is possible, it is not the norm. |
| Exploitation Route | The outputs of the project are mostly relevant to the climate modelling community to improve estimates of carbon uptake by the land surface. |
| Sectors | Environment Other |
| Description | The new canopy radiative transfer model developed as part of SPLICE has been adopted by two different groups, both of which are outside of academia: the Finnish Meteorological Institute and a small German SME (iLabs). We have ongoing collaborations with both of these teams and expect more impact to emerge in the comings years. |
| First Year Of Impact | 2025 |
| Sector | Environment,Other |
| Title | Eco-physiological responses in oak and hazel, Alice Holt Forest, Hampshire, UK, July 2023 |
| Description | This dataset contains information about photosynthesis and gas exchange from tree species in Alice Holt Forest, Hampshire, UK. Data were collected between 18th-20th July 2023, alongside other observations examining the forest canopy structure and photosynthesis. Leaves were sampled across one hazel tree within the understory, and two oak trees. Data from the oak trees were collected with height, using a 12 m tower (six 2 m platforms), with leaves sampled across three platforms. The photosynthesis parameters were collected using a Handy PEA+ continuous excitation chlorophyll fluorimeter and gas exchange data were collected using a LI-COR 6400. This research was funded by UKRI NERC as part of the SPLICE project (NE/W006596/1). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | n/a |
| URL | https://catalogue.ceh.ac.uk/id/40365cee-fda6-402f-9839-c206463dbe7d |
| Title | L2SM |
| Description | L2SM is a Python flexible module for building two-steam radiative transfer models of vegetation canopies and support vertically varying properties and internal emissions. |
| Type Of Technology | Physical Model/Kit |
| Year Produced | 2025 |
| Open Source License? | Yes |
| Impact | Relevant parts of this software has been adopted by both the Finnish Meteorological Institute and a German SME (iLabs) to facilitate prediction of Solar Induced Fluorescence from their respective models. |
