Forecasting the impacts of drought on human-modified tropical forests by integrating models with data

Lead Research Organisation: University of Bristol
Department Name: Biological Sciences

Abstract

Tropical forests are among the most biodiverse ecosystems on the planet and play a critical role in slowing climate change by absorbing huge amounts of CO2 from the atmosphere through photosynthesis. Yet these ecological powerhouses are increasingly under threat from rampant deforestation and a rise in the frequency of extreme climate events such as droughts. Understanding how tropical forests will respond to these pressures has therefore emerged as a key priority for ongoing efforts to safeguard their biodiversity and the services they provide to society. Working in Borneo - where deforestation rates since the 1970s have been among the highest in the world - this project will explore the extent to which logging tropical forests jeopardises their ability to cope with drought. By combining field experiments with cutting-edge 3D remote sensing technologies and process-based modelling, I aim to uncover how drought impacts the carbon cycle of logged tropical forests: from the growth and survival of seedlings on the forest floor to the dynamics of whole ecosystems across Borneo. In doing so I will shed light on the limits of tropical forests to withstand climate change and develop the tools needed for protecting these ecosystems as we strive to transition towards a more sustainable future.

Planned Impact

Who will benefit as a result of this fellowship?

The proposed research will directly and indirectly benefit a range of non-academic stakeholders working in Borneo and beyond. These include (i) regional conservation and sustainable development non-governmental organizations (NGOs) such as the South East Asia Rainforest Research Partnership (SEARRP), the Heart of Borneo Rainforest Foundation and the Roundtable on Sustainable Palm Oil (RSPO), (ii) state government bodies such as the Sabah Forestry Department (SFD), (iii) industry partners that rely on remote sensing technologies for ecosystem monitoring and carbon accounting, including Permian Global, Carbomap and Ecometrica, as well as (iv) the general public.

How will they benefit from this research?

In recent decades Sabah has emerged as an important testbed for international efforts to conserve and sustainably manage tropical forests. This project will directly inform the strategy of conservation and sustainable development NGOs working in the region. For instance, SEARRP and the Heart of Borneo Rainforest Foundation will be able to tailor their conservation and restoration projects based on a better understanding of the resilience of tropical forests to habitat degradation and climate change. Similarly, the project will provide robust data for organisations such as RSPO to refine and enforce its certification schemes for suitable oil-palm production.

The project will also help regional government bodies such as SFD to make complex decision on how best to manage forests in the region to meet multiple (and oftentimes conflicting) objectives (e.g., timber production and carbon sequestration). For instance, the carbon dynamics models developed through this project will allow SFD to refine its annual allowable cut estimates to ensure they are sufficient to support local livelihoods without becoming unsustainable. Similarly, the project will provide critical data to inform decisions on where to set aside land for conservation to ensure the best outcomes for both biodiversity and carbon storage under current and future climate scenarios.

Industry stakeholders also stand to benefit as a result of this project. Permian Global - an investment firm dedicated to the protection and recovery of tropical rainforest to mitigate climate change - will be able to leverage the forest dynamics models developed through this project to improve the carbon stock trajectories that underpin the REDD+ projects they oversee in the region. By doing so they will be able to better estimate their pool of carbon credits and increase their value on the market. Additionally, industry partners that rely on remote sensing data for ecosystem monitoring and precision forestry - including the Edinburgh based Carbomap and Ecometrica - will be able to advance their workflows by incorporating new approaches for fusing repeat LiDAR and satellite data developed through this project.

Finally, this project will provide a powerful platform to raise awareness among the general public on the consequences of land-use intensification in the tropics for biodiversity and climate change on a global scale. Addressing these issues is central to meeting the United Nations Sustainable Development Goals, but these topics can often feel far removed. In this regard remote sensing technologies such as LiDAR and high-resolution satellite imagery provide an intuitive way to communicate the scale and speed at which human activity is reshaping our planet. Leveraging these immersive digital platforms I hope to engage and instil a sense of curiosity in the next generation of scientists, explorers and policy makers.

Publications

10 25 50
 
Description BCAI Research Grants
Amount £22,968 (GBP)
Organisation University of Bristol 
Sector Academic/University
Country United Kingdom
Start 03/2020 
End 03/2021
 
Description Combining long-term field data and remote sensing to test how tree diversity influences aboveground biomass recovery in logged tropical forests
Amount £650,416 (GBP)
Funding ID NE/X000281/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 05/2023 
End 05/2026
 
Description FORTRESS - Forest ecosystems and their resilience to climate extremes across Europe
Amount € 1,882,000 (EUR)
Funding ID 101076609 
Organisation European Research Council (ERC) 
Sector Public
Country Belgium
Start 09/2023 
End 09/2028
 
Description Habitat fragmentation and its impact on the world's tropical forests
Amount £171,400 (GBP)
Funding ID RPG-2023-169 
Organisation The Leverhulme Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 01/2024 
End 12/2026
 
Description Leverhulme Trust Research Project Grants
Amount £163,306 (GBP)
Funding ID RPG-2020-341 
Organisation The Leverhulme Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2021 
End 02/2024
 
Description Royal Society Research Grants
Amount £19,778 (GBP)
Funding ID RGS\R1\201216 
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2020 
End 03/2021
 
Title L2C - Canopy height models across the Brazilian Amazon 
Description Canopy height models derived from LiDAR data collected across the Brazilian Amazon. The files are provided in .tiff format in 7 zip folders. A full description of the data set is available here: https://zenodo.org/record/4968706#.YzB693ZKg5s We also provide the summary data used for statistical analysis in the associated publication: Reis and Jackson et al 2022. Forest disturbance and growth processes are reflected in the geographic distribution of large canopy gaps across the Brazilian Amazon. Journal of Ecology. Each transect covered 375 ha (12.5 km × 300 m) by emitting full-waveform laser pulses from a Trimble Harrier 68i airborne sensor (Trimble; Sunnyvale, CA) aboard a Cessna aircraft (model 206). The average point density was set at four returns per square meters, the field of view was equal to 30°, the flying altitude was 600 m, and transect width on the ground was approximately 494 m. Global Navigation Satellite System (GNSS) data were collected on a dual-frequency receiver (L1/L2). The pulse footprint was set to be below 30 cm, based on a divergence angle between 0.1 and 0.3 milliradians. Horizontal and vertical accuracy were controlled to be under 1 m and under 0.5 m, respectively. The data collection was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Brasil (CAPES; Finance Code 001); Conselho Nacional de Desenvolvimento Científico e Tecnológico (Processes 403297/2016-8 and 301661/2019-7); Amazon Fund (grant 14.2.0929.1) The research project was funded by the UK Natural Environment Research Council project number NE/S010750/1 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://zenodo.org/record/7104043
 
Title Tallo database 
Description The Tallo database (v1.0.0) is a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. Data were compiled from 61,856 globally distributed sites and include measurements for 5,163 tree species. For a full description of the database, see: Jucker et al. (2022) Tallo - a global tree allometry and crown architecture database. Global Change Biology, https://doi.org/10.1111/gcb.16302. If using the Tallo database in your work please cite the original publication listed above, as well as this repository using the corresponding DOI (10.5281/zenodo.6637599). 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://zenodo.org/record/6637598