Project properties

Title Reforesting tropical landscapes: a large-scale demographic study using satellite images in Panama
Group Forest Ecology and Forest Management Group
Project type thesis
Credits 27-39
Supervisor(s) FEM group: Prof. Dr. Pieter (P.A.) Zuidema
Other organisation: MSc Cristina Barber and Dr. Trevor Caughlin ( Boise State University, Idaho, USA)
Examiner(s) Prof. Dr. Pieter (P.A.) Zuidema
Contact info;
Begin date 2018/06/01
End date
Description Also possible as internship.

Secondary forest growth has the potential to restore ecosystem functions to millions of hectares of degraded land. As a consequence, forest restoration at the landscape scale has become a conservation priority for national and international environmental policies. However, forest landscape restoration remains a high risk investment, in part due to low predictability of restoration outcomes in heterogeneous landscapes. Predictive models have the potential to increase forest restoration success and enable spatial targeting of limited resources for restoration. Modeling early forest succession requires data over a large spatial extent to account for landscape-scale factors, including biophysical variables (e.g. topography) and socioeconomic variables (e.g. land use history). The study will be developed in Panama, in Azuero peninsula, a dry tropical forest area with a long history of deforestation due to cattle ranching. As consequence of rural exodus the area is going through an abandonment process and some areas are growing back to secondary forest. This conjuncture of factors has created a unique heterogeneous landscape with different secondary succession stages that will allow studying secondary succession from its early moment until forest reach maturity.
The study objective is to create a demographic distribution model that incorporates landscape factors to describe and predict landscape population growth of tree species. Developing this quantitative framework will bridge the gap between remotely sensed data and forest inventory plot data. We recently found that a single hyperspectral image can accurately predict DBH growth rates of tropical trees in plantation. This method has great potential to forecast tree demography over wide scales, with application to precision forestry and ecological restoration. However, whether this method will work on naturally-grown trees remains unknown.
The student will do a month of field work on dry secondary tropical forest colleting recruits and parent trees vital rates including re-measuring Cedrela odorata trees across the Azuero landscape to test this question.

Population and forest dynamics / Modelling/Americas/tropical zone
Used skills Some of the skills that will be used or learned will be:
� Field work methodology
� Plant identification
� Forest/population dynamics modeling
Speaking Spanish is not required but is useful.
Requirements FEM-30306 Forest Ecology and Forest Management; FEM-30806 Resource Dynamics and Sustainable Utilization