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Using cover measurements to estimate aboveground understorey biomass in Maritime pine stands
Authors:Annabel J Porté  Jean-Charles Samalens  Raphaël Dulhoste  Rémi Teissier Du Cros  Alexandre Bosc  Céline Meredieu
Institution:1. UR1263 EPHYSE, INRA, 33140, Villenave d’Ornon, France
2. UMR1202 Biodiversity Genes & Communities, INRA, 33612, Cestas, France
3. MR1202 Biodiversity Genes & Communities, Université Bordeaux 1, 33405, Talence, France
4. ICAE-Facultad de Ciencias, Universidad de Los Andes, 5101, Mérida, Venezuela
5. IFN, Forest National Inventory, 33000, Bordeaux, France
Abstract:
  • ? Understorey plays a major role in forest fluxes and stocks balances, however this compartment is generally poorly quantified. Our objectives were to establish models to estimate understorey biomass using vegetation cover measurements and to investigate upscaling methodologies from stand to regional level.
  • ? Understorey aboveground biomass measurements were undertaken in Maritime pine stands of mesohygric, mesic and dry moorlands in South West France.
  • ? Average biomass stock in this compartment was estimated to 3.50 t DM ha?1. The more abundant species groups varied with moorland types, with a higher relative contribution of herbaceous species (23.3%), bracken (59.2%) and mosses (31.6%) for mesohygric, mesic and dry moorlands, respectively. For each species group, we established significant relationships to estimate biomass using a volumetric index, based on cover and height measurements. No relationship between stand characteristics and understorey biomass was founded. We investigated the upscaling of these estimations to a several thousands hectare area using understorey cover measurements done along a regular spatial grid. The only significant correlation linked one satellite vegetation index to understorey biomass.
  • ? We successfully developed empirical relationships to estimate the understorey biomass at the stand level. Further investigations could focus on the analysis of understorey variability over a finer space grid and the potential use of satellite vegetation indexes.
  • Keywords:
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