Project highlights

  • Unique data and methods: the project will use high-resolution satellite images from Planet Scope (4 m resolution), forest plots, and machine learning methods.  
  • New insight on forest ecology to climate mitigation strategies: The research offers a new insight into the potential of multi-species afforestation strategies to contribute to climate change mitigation and biodiversity restoration simultaneously. 
  • Impact: The project is highly relevant to the carbon Net Zero national strategy, where Natural England, our leading project partner, will directly benefit from the outputs of this research. 

Overview

How do the carbon and biodiversity of tropical and temperate forest ecosystems vary at the local and ecosystem levels? Globally there is a generally positive relationship between carbon stocks and biodiversity; tropical moist forests are rich in both (Liang et al., 2016). The carbon-biodiversity scaling hypothesis states (Cardinale, Ives, and Inchausti, 2004) that the high number of tree species leads to a high amount of aboveground biomass (carbon) such as in tropical forest areas. On the other hand, in temperate regions such UK deciduous forests have low tree diversity but relatively high amount of carbon storage. Because the carbon-biodiversity scaling function is scale-dependent (Gonzalez et al., 2020 and Thompson et al., 2021) and well described in tropical forest ecosystems (Liang et al., 2016), the intermedium spectrum of the biodiversity-carbon scaling function of temperate regions is currently unknow.  

Testing the carbon-biodiversity scaling hypothesis at large scales requires forest inventory and remote sensing data (Gonzalez, 2020) from tropical and temperate regions available only in a few regions. Therefore, this study aims quantify the amount of carbon and biodiversity of tropical and temperate forests by investigating its functional scale relationship from local (a few random forest inventory plots) to regional scales (thousands km square of remote sensing images). The study will scale the spectrum of the biodiversity-carbon function of forests, which is currently unavailable. The inclusion of UK temperate forests into this spectrum will improve the global understanding, and directly feed into our goals of understanding the carbon balance and biodiversity values of UK woodland.  

The main research questions of this study are (Q) are:  

Q1. How do the carbon and biodiversity of forest trees vary across scales (from forest plots to remote sensing images) and ecosystems (from tropical and temperate forests)? 

Q2. What is the functional scaling relationship between carbon and biodiversity in tropical and temperate forests? 

Q3. What are the proportions (ratios) of tree species per carbon in tropical and temperate forests and what is the role of the carbon-biodiversity function to enhance and maintain forest productivity in both ecosystems?   

The building of a new ecological and remote sensing framework to quantify forests’ biodiversity and carbon storage at high resolution and large scales, would be a huge benefit to Natural England, with the development of a new methodology that we could use in the future in our conservation work. This will increase our capacity for monitoring, data analysis and evaluation of techniques to help inform the development of indicators, a key priority for Natural England. 

On the left a map of the world with areas highlighted in blue, on the right a graph of productivity and tree species richness.
Figure 1: Global effect of tree species diversity on forest productivity. Ground-sourced data from 777,126 global forest biodiversity permanent sample plots (dark blue dots, left), which cover a substantial portion of the global forest extent (white), reveal a consistent positive and concave-down biodiversity-productivity relationship across forests worldwide (red line with pink bands representing 95% confidence interval, right). Figure and figure captions without modifications from Liang et al. 2016.

CENTA Flagship

This is a CENTA Flagship Project

Case funding

This project is suitable for CASE funding

Host

University of Leicester

Theme

  • Climate and Environmental Sustainability

Supervisors

Project investigator

  • Dr Fernando Del Bon Espirito-Santo (UoL)

Co-investigators

  • Professor Heiko Balzter (UoL)
  • Dr Beth Cole (Natural England)

How to apply

Methodology

The project aims to design a novel methodology to quantify the functional relationship between tree species and aboveground biomass (carbon) of forests using high-resolution remote sensing data from Planet Scope (4 m resolution), forest plots, and machine learning methods. The study will build an entirely new spectrum of the biodiversity-carbon function of forests based on remote sensing and ground data and will better address the intermedium spectrum of the biodiversity-carbon scaling function in temperate woodland regions of the UK. 

PlanetScope data, operated by Planet, is a constellation of approximately 200 satellites, able to image the entire land surface of the Earth every day at approximately 4 m of resolution. The Space Park Leicester is a partner of the Planet, and this huge data is currently available for this project. To product the first high resolution maps of forest carbon stocks and tree species, we will use an extensive source of published data and forest inventories collected by Dr Fernando Espirito-Santo in the Amazon and Africa. Tree data will be from field-based forest inventory plot records from around the globe. We will also use national and international forestry databases, including National Forest Inventory (NFI) analyses from 21 countries, the Global Index of Vegetation-Plot Database (GIVD http://www.givd.info), the Smithsonian Tropical Research Institute’s in-house database (http://www.stri.si.edu), and ICP-Level-I plot data for most of Europe (http://www.icp-forests.org).  

Training and skills

The student will be trained in Sentinel data processing on the HPC facility SPECTRE-2 at Leicester. The student will take the new MSc module GY7709 (Satellite Data Analysis in Python), available since 2019-2021, and any other modules deemed suitable, dependent on the background of the student. Complementary individual training in using AI, especially TensorFlow, will be available from the Department of Mathematics. Further training will take place ‘on-the-job’ as part of the research team. 

Partners and collaboration

In the letter of support of Natural England, as a CASE sponsor, Dr Isabel Alonso highlights that “The project is highly relevant to the work of Natural England, and we can benefit from the outputs in a number of ways. The project aims to design a novel methodology to quantify the functional relationship between tree species and aboveground biomass (carbon) of forests using high-resolution remote sensing data from Planet Scope (4 m resolution), forest plots, and machine learning methods. The study will focus on the entire spectrum of the biodiversity-carbon function of forests, which is currently unavailable. The inclusion of UK temperate forests into this spectrum will improve the global understanding, and directly feed into our goals of understanding the carbon balance and biodiversity values of UK woodland. As a CASE partner we will support the development of the UK case study, with access to our National Nature Reserves. This will increase our capacity for monitoring, data analysis and evaluation of techniques to help inform the development of indicators, a key priority for Natural England.”  

Other partners: 

  • NCEO 
  • Space Park Leicester 
  • Planet – satellite assembly, operations, and data analytics company 
  • The Brazilian Space Institute (INPE) 

Further details

If you wish to apply to the project, applications should include:

  • A CV with the names of at least two referees (preferably three and who can comment on your academic abilities)

Applications to be received by Wednesday 31st May 2023. 

Further reading

Gonzalez, A., Germain, R.M., Srivastava, D.S., Filotas, E., Dee, L.E., Gravel, D., Thompson, P.L., Isbell, F., Wang, S., Kéfi, S., Montoya, J., Zelnik, Y.R. and Loreau, M. (2020), Scaling-up biodiversity-ecosystem functioning research. Ecol Lett, 23: 757-776. 

Cardinale, B.J., Ives, A.R. & Inchausti, P. (2004). Effects of species diversity on the primary productivity of ecosystems: extending our spatial and temporal scales of inference. Oikos, 104, 437– 450. 

Cardinale, B.J., Wright, J.P., Cadotte, M.W., Carroll, I.T., Hector, A., Srivastava, D.S. et al. (2007). Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci., 104, 18123– 18128. 

Bond, E.M. & Chase, J.M. (2002). Biodiversity and ecosystem functioning at local and regional spatial scales. Ecol. Lett., 5, 467– 470. 

Burley, H.M., Mokany, K., Ferrier, S., Laffan, S.W., Williams, K.J. & Harwood, T.D. (2016). Macroecological scale effects of biodiversity on ecosystem functions under environmental change. Ecol. Evol., 6, 2579– 2593. 

Bush, A., Sollmann, R., Wilting, A., Bohmann, K., Cole, B., Balzter, H. et al. (2017). Connecting Earth observation to high-throughput biodiversity data. Nat. Ecol. Evol., 1, 0176. 

Liang J, Crowther TW, Picard N, and others 23 co-authors (2016) Positive biodiversity-productivity relationship predominant in global forests. Science 354:aaf8957.  

Thompson, Patrick L.  and Kéfi, Sonia  and Zelnik, Yuval R.  and Dee, Laura E.  and Wang, Shaopeng  and de Mazancourt, Claire  and Loreau, Michel  and Gonzalez, Andrew (2021), Scaling up biodiversity–ecosystem functioning relationships: the role of environmental heterogeneity in space and time. Proceedings of the Royal Society B: Biological Sciences, 288: 20202779.  

COVID-19

Current COVID-19 pandemic might affect project delivery due to the following: 

  •  Travel disruptions. 
  •  This problem can be mitigated by video-conference software to hold meetings and training events. 
  • The project is not reliant on fieldwork as it uses primarily digital data. 
  •  Slow internet causing disruptions in video-conference meetings: 
  •  This may affect partners and can be mitigated by holding virtual meetings at times when internet traffic is at minimum 
  • Prevention of face-to-face meetings due to national/local lockdowns 
  •  The project can be run entirely remotely if needed. Regular check-ins online are scheduled. Project design to remain entirely digital, no physical experiments. 
  • PhD training cannot take place in person 
  • Teaching and learning are now taking place following the blended learning approach under IGNITE, which can be switched to completely online teaching under conditions of restrictions and includes asynchronous and synchronous delivery.