- Start date: 1 December 2017
- End date: 30 November 2020
- Funder: NERC
- Value: £645,690
- Co-investigators: Prof Tim Baker
This proposal aims to make a step change in the precision and accuracy of our knowledge of the distribution of peatlands in the tropics, and to develop a capacity to predict and monitor future changes to the carbon storage function of these peatlands.
Tropical forest ecosystems are important for carbon storage. The densest 'carbon hotspots' occur where peat underlies the vegetation. Peat is an organic soil formed by the accumulation of plant litter, often over thousands of years, usually under waterlogged conditions which limit micro-organism activity and inhibit litter decomposition. Given that they store so much carbon per unit area, tropical peatlands should be priorities for conservation. Unfortunately, it is not currently known with certainty where peatlands occur. Even using satellite imagery, it is challenging to distinguish forest overlying peat from forest occurring on dry soil. Mapping peat deposits in the field by trial and error is impractical given the large areas of remote terrain involved. This proposal builds on an extensive record of research into tropical peatlands by the research team.
Our group has worked extensively in the Pastaza-Marañón Foreland Basin (PMFB) in Peruvian Amazonia. Here, in one of the highest-rainfall regions of Amazonia, the existence of extensive bodies of peat was only revealed by a publication in 2009. Since then, we have undertaken extensive fieldwork and laboratory analyses, and have developed an algorithm that uses remotely-sensed (satellite) data to predict the distribution of vegetation types associated with peat in the PMFB. On this basis we estimate that there is more than 35,000 square km of peat in the PMFB, making it by far the largest known peatland complex in Amazonia. Our results were used to build the science case for the first ever carbon-conservation project funded by the Green Climate Fund, a major, intergovernmental, UN- and UK-backed climate mitigation project. We now want to develop the science ba further to enable similar projects throughout the scheme.
Our first aim is to substantially develop and improve our current method for inferring the distributions of vegetation, peat and carbon from satellite data, by addressing fundamental gaps in our understanding of the controls on these distributions and by testing a set of technical improvements. We will then test how well our model works on floodplains in other parts of Amazonia. Ultimately we want to know how widespread peat is across the whole of Amazonia.
Our second aim is to develop, for the first time, the ability to predict and monitor future changes to tropical peatland carbon stocks. It is already possible to predict carbon accumulation patterns in northern peatlands from climatic and topographic data, and hence to predict how carbon accumulation may change under future climate scenarios (e.g. climatic drying), but a lack of basic data has prevented similar modelling from being attempted in the tropics.
Recent advances in fusing modelling and remotely-sensed data are also opening new possibilities for monitoring present-day changes to the carbon cycle. In order to achieve our second aim, we will study the pattern of peatland carbon storage through the last several thousand years, measure the rates at which litter is added to the peat and removed by decomposition today, and determine how these rates are affected by variations in hydrological regimes.
We will use this information to determine, using a process-based model of peat accumulation, the conditions required for peat to accumulate. By doing so we will be able to evaluate and refine two complementary, simpler process-based models of peat distribution and carbon cycling that are suited to prediction and monitoring on a pan-tropical scale.