A multi-scale assessment of the regrowth potential of secondary forests in the Brazilian Amazon
Now that humanity has cleared or damaged at least three-quarters of the world’s primary forests, the regrowth of tropical forests plays a key role in global biogeochemical cycles, climate regulation and biodiversity conservation. It has been estimated that 20% of total past deforestation in the Brazilian Amazon is now covered by secondary forests, yet their exact extent, age and ecological value remain uncertain.
This study will make use of a multi-scale remote sensing approach and comprehensive forest inventory data in order to model and predict the carbon and biodiversity value of secondary forests. Data from survey plots will be linked with airborne and terrestrial LiDAR (light detection and ranging) and satellite images to address the following questions:
Q1. Can we quantify key ecosystem values and processes within secondary forests by linking data on forest structure and biodiversity collected in a network of secondary forest plots with optical and LiDAR (light detection and ranging) remote sensing?
Q2. How do soil, climate and land-use configuration affect the successional trajectory of secondary forests across regions (>1 million hectares), and can we identify key thresholds that may be limiting forest recovery?
Q3. Can we provide Amazon-wide estimates of the recovery of carbon and biodiversity in secondary forests?
The position will suit an enthusiastic PhD candidate willing to learn remote sensing, tropical ecology and statistical modelling simulations. As well as a NERC studentship, the successful applicant will be supported by resources from linked research projects, enabling a much broader set of data collection than would normally be possible in a PhD.
The successful applicant will develop skills allowing them to undertake numerical simulations and mapping of land-use processes; evaluate the recovery of secondary forest across the Brazilian Amazon; and produce innovative methodologies to combine remote sensing with forest plots.
Applications should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Natural Sciences, Biology, and Ecology. Some experience of remote sensing and environmental field work will be advantageous. Applicants should be willing to learn Portuguese and be pro-active in engaging with an international network of partners, including non-scientific stakeholders such as Amazonian farmers or reserve managers.
For further details please contact Dr Fernando Del Bon Espirito-Santo email@example.com Jos Barlow firstname.lastname@example.org