The overall aim of the biological component of HERB Research is to increase our understanding of the nature of the TMCF ecosystem and the controls upon and distribution of biodiversity within it. TMCF is thought to be one of the most diverse ecosystems in existing. It is also very poorly known biologically and is under threat from climatic change and the expansion of the agricultural frontier. TMCF is characterised by vegetation of unusually low stature (for tropical systems) with an abundance of epiphytes. The peculiar climatic conditions of TMCF lead to distinctive hydrological and biological characteristics. In order to further understand the biological and ecological characteristics of these systems, the HERB project aims to fulfill the following objectives:
- (1) To evaluate the contribution of edaphic (soil), climatic and ecological factors on the structural and ecophysiological characteristics of TMCF.
- (2) To examine the photosynthetic characteristics of TMCF vegetation, in particular the processes of photosynthesis at high ambient humidity.
- (3) To measure and model the productivity and carbon balance of TMCF, its seasonal variability and implications for carbon sequestration.
- (4) To examine the nutrient balance of TMCF and assess the role of nutrients in controlling TMCF vegetation.
- (5) To examine the contribution of the epiphytic biomass to the productivity of TMCF landscapes.
- (6) To develop GIS-based models for the spatial distribution of particular plant and animal species and genera on the basis of climatic, edaphic and hydrological tolerance limits along with landscape ecology.
- (7) To develop theoretical models for the spatial distribution of biodiversity in complex landscapes based on the theories of biogeography applied to GIS-derived measures of landscape variability and on modelled processes of evolution.
These objectives will be met through a combination of advanced field monitoring techniques using electronic dataloggers and various sensors, targeted field campaigns and the development of GIS based models to provide enhanced theoretical awareness and the capacity for simulating medium and long term behaviour of the system.